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MiRNAs are the most abundant non-coding RNAs enriched in EVs, and studies have also showed that EVs contain components of the RNA-induced silencing complex (RISC), suggesting potent regulatory role of EV-miRNA in recipient cells . Several studies have reported the regulation of signaling pathways in ECs by miRNAs delivered via tumor-derived EVs (Table 3). MiR-494 containing EVs secreted by tumor cells were taken up by ECs and promoted the migration of EC via targeting of PTEN and subsequent activation of Akt/eNOS pathway . EV-encapsulated miR-9 transferred from tumor cells to ECs reduced SOCS5 level, leading to JAK-STAT pathway activation to promote endothelial cell migration and sprout . Colorectal cancer cells secreted miR-1246 via EVs, which activated Smad1/5/8 signaling through targeting promyelocytic leukemia (PML) mRNA in recipient ECs, promoting angiogenic activities .Table 3MiRNAs involved in angiogenesis regulation by tumor-derived extracellular vesiclesmiRNAs in EVsTargetsFunctionRefmiR-494PTENpromote ECs migration, tube formationmiR-9SOCS5promote ECs migration, tube formationmiR-1246PMLpromote ECs proliferation, migration, tube formationmiR-23aPHD1, PHD2, ZO-1increase the number of tumor vessels, disrupt endothelial barriersmiR-210Ephrin-A3Promote ECs tube formationmiR-105ZO-1destroy tight junctions and integrity of vascular endothelial barriersSOCS5 suppressor of cytokine signaling 5, PML promyelocytic leukemia, PHD prolyl hydroxylase, ZO-1 tight junction protein 1
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review
| 99.7 |
Hypoxia is a potent trigger of angiogenesis. Some studies have focused on clarifying how hypoxia affects tumor angiogenesis through tumor cell-derived EVs. Hsu et al. found that more exosomes were produced under hypoxic conditions than normoxic conditions by lung cancer cells. Tumor-derived exosomal miR-23a directly suppressed the expression of prolyl- hydroxylase 1 and 2 (PHD1 and 2), leading to the accumulation of HIF-1α in ECs and increased angiogenesis . Tadokoro et al. reported that exosomes derived from leukemia cells under hypoxia are potent inducers of angiogenesis through transfer of miR-210 to ECs, downregulating the expression of receptor tyrosine kinase ligand Ephrin-A3 in HUVECs . Neutral Sphingomyelinase 2 (nSMase2) was shown to regulate exosomal miR-210 secretion by metastatic cancer cells .
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study
| 99.7 |
Tumor-induced vascular vessels commonly have abnormal structure with increased permeability and incomplete cellular junction . Zhou et al. showed that in endothelial monolayers, exosomal miR-105 derived from breast cancer cells efficiently destroyed tight junctions and the integrity of natural vascular endothelial barriers by targeting ZO-1 in ECs, thus promoting breast cancer metastasis . Similarly, lung cancer cells-secreted exosomal miR-23a also inhibited tight junction protein ZO-1, thereby increasing vascular permeability and cancer trans-endothelial migration . Collectively, these observations suggest that tumor-secreted EV miRNAs participate in intercellular communication and function as a novel pro-angiogenic mechanism.
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study
| 99.94 |
As angiogenesis is essential for tumor growth and progression, anti-angiogenic therapies have been developed to improve the outcomes of cancer patients. Several agents, including bevacizumab, aflibercept and most recently ramucirumab that target the VEGF/VEGFR signaling pathway, have been approved across some cancer types. In addition, multi-targeted tyrosine kinase inhibitors (TKIs), such as sorafenib and sunitinib, also block angiogenesis signaling. However, the overall response rate of these anti-angiogenic therapies is unsatisfactory in the clinic. Therefore, selecting out the patients, who would benefit from anti-angiogenic treatment, will help to promote therapy efficacy and avoid unnecessary toxic adverse effect. Due to the high tissue specificity and stability of miRNAs and their altered expression in tumor angiogenesis, miRNAs have been suggested as potent predictive biomarkers for therapeutic response (Table 4).Table 4Tissue and blood miRNA biomarkers for anti-angiogenesis therapeutic responseClinical OutcomesmiRNAsSample typeDetection timeTherapyCancerPatient cohortaRefBetter outcomesmiR-378tissuepost-therapybevacizumabovarian cancer113/34miR-455-5ptissuepost-therapybevacizumabmCRC212/121miR-221tissuepost-therapysunitinibmRCC30/27miR-155, miR-484tissuepost-therapysunitinibmRCC16/63miR-126bloodpre- and post-therapybevacizumabmCRC75/68miR-665bloodpre-therapybevacizumab/erlotinibNSCLC51/50Worse outcomesmiR-664-3p,tissuepost-therapybevacizumabmCRC212/121miR-425-3ptissuepre- and post-therapysorafenibHCC26/58miR-223bloodpre-therapybevacizumab/erlotinibNSCLC51/50mCRC metastatic colorectal cancer, HCC hepatocellular carcinoma, mRCC metastatic renal cell carcinoma, NSCLC non-small-cell lung canceraThe pattern A/B represents patient number in training cohort and validation cohort respectively
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review
| 99.9 |
Bevacizumab, a humanized monoclonal antibody against VEGF-A, has been approved as combination therapy or monotherapy for first- and second-line treatment of several advanced cancers, including metastatic colorectal cancer (mCRC), metastatic renal cell carcinoma (mRCC), metastatic non-small cell lung cancer (NSCLC), progressive glioblastoma, metastatic cervical cancer and ovarian cancer etc. . In TCGA dataset, high miR-378 expression was associated with poor progression-free survival (PFS) in recurrent ovarian cancer patients treated with bevacizumab (low vs. high, 9.2 vs. 4.2 months; p = 0.04). Multivariate analysis revealed that miR-378 expression was an independent predictor for PFS after anti-angiogenic treatment . For patients with mCRC treated with first line CAPEOX (capecitabine and oxaliplatin) alone, or CAPEOX and bevacizumab (CAPEOXBEV), predictive miRNAs for therapy effectiveness were identified using PCR arrays. Higher miR-664-3p level and lower miR-455-5p level were predictive of improved outcome in the CAPEOXBEV cohorts and showed a significant interaction with bevacizumab effectiveness .
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study
| 99.94 |
Several multi-target TKIs have potent anti-angiogenic effects due to the inhibition of VEGFR and PDGFR, and have been approved, including sorafenib for mRCC and unresectable hepatocellular carcinoma (HCC), and sunitinib for mRCC. High level of miR-425-3p was associated with longer PFS in HCC patients treated with sorafenib. Multivariate analysis confirmed the predictive significance of miR-425-3p, suggesting that assessment of miR-425-3p levels in liver biopsies could help in stratifying patients with advanced HCC for sorafenib treatment . Khella et al. compared miRNA profile between patients with a short (≤12 months) versus prolonged (> 12 months) PFS under sunitinib as first-line therapy for metastatic RCC. They developed miRNA statistical models that could accurately distinguish the two groups. MiR-221 overexpression was validated to be associated with a poor PFS, while its target VEGFR2 was associated with longer survival . In another study, miRNA profiling in tumor tissues of sunitinib-treated mRCC patients was performed by TaqMan Low Density Arrays. Decreased tissue levels of miR-155 and miR-484 were significantly associated with increased time to progression (TTP), suggesting miR-155 and miR-484 are potentially connected with sunitinib resistance and failure of the therapy .
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review
| 99.6 |
Although tissue miRNA expression could serve as molecular classifier for clinical outcome, there are several drawbacks including small quantities of diagnostic tumor tissue, genetic tumor heterogeneity in space and time, and unavailable acquisition of repeated biopsies. Therefore, circulating biomarkers offer a non-invasive opportunity for early diagnosis, prognosis evaluation and drug response prediction in cancer. Circulating miRNAs are stable and reproducible in blood due to their incorporation in exosomes/microvesicles or protein complexes, protecting them from degradation by endogenous RNase [109, 110]. Technical advances in detection and profiling makes them promising candidates. Recently, the occurrence of miRNAs in the serum or plasma of human has been repeatedly observed and become the focus of biomarker discovery.
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review
| 99.9 |
Hansen et al. investigated the predictive value of circulating miR-126 in mCRC patients receiving first-line chemotherapy combined with bevacizumab. Blood samples of patients were collected before treatment (baseline), 3 weeks after treatment and at progression. Evaluation of miR-126 expression in plasma showed that non-responders had an increase in miR-126 level relative to baseline, while responders with decreased miR-126 alteration. The results indicated that changes in circulating miR-126 during treatment represented a possible biomarker for the response to anti-angiogenic containing therapy . M. Joerger’s study assessed the predictive value of circulating miRNA in patients with non-squamous NSCLC, receiving treatment with first-line bevacizumab and erlotinib followed by platinum-based chemotherapy at progression. MiRNA profiling in pre-treatment blood showed that 12 miRNAs were significantly associated with tumor shrinkage following bevacizumab/erlotinib treatment, with miR-665 being the strongest predictive marker. Patients with high miR-665 expression had a higher chance for tumor shrinkage. Furthermore, miR-223 was found to be associated with both TTP following bevacizumab/erlotinib treatment and TTP following second-line chemotherapy . Collectively, these studies indicate that tissue and circulating miRNAs could serve as predictive biomarkers for response to anti-angiogenic therapy.
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study
| 88.3 |
Given the important regulatory role of miRNAs in tumor angiogenesis, targeting or delivering miRNAs to tumors holds great promise as a novel therapeutic approach. In this case, it is essential to deliver antagomiRs or miRNA mimics into tumor cells or endothelial cells. As naked miRNAs are hydrophilicity, unable to pass through cell membranes, and could be easily degraded by serum RNase , in vivo application of miRNA requires formulation into delivery systems. Here we summarize some miRNA delivery approaches that have been applied to suppress angiogenesis in vivo (Table 5).Table 5MiRNA-based therapeutics to target tumor angiogenesismiRNAsDelivery systemsCancerTargetsRefmiR-125bPEIlung cancer, colorectal cancerVE-cadherinmiR-192DOPCovarian cancer, renal tumorEGR1, HOXB9miR-200DOPClung cancer, ovarian cancer, renal cancerIL8, CXCL1miR-520dDOPCovarian cancerEphA2miR-132cRGDbreast cancerp120RasGAPmiR-499APRPG-PEGcolorectal cancerVEGFmiR-29a/cCMVsgastric cancerVEGFmiR-150CMVssarcomaVEGFPEI polymer polyethylenimine, DOPC 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine, cRGD cyclicArginine-Glycine-Aspartic acid, APRPG-PEG Ala-Pro-Arg-Pro-Glypeptide-conjugated polyethyleneglycol, CMVs Cell-derived membrane vesicles
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review
| 99.9 |
Nanoparticle delivery systems, including viral and non-viral ones, have been addressed to protect miRNAs from degradation by serum nucleases when administered systemically . The advantage of non-viral approach is safety and avoiding induction of toxic immune response compared with viral delivery. Non-viral delivery systems mainly use liposomes, lipoplexes and polyplexes as miRNA carriers. The encapsulation of miRNAs into polycation liposomes has been well studied. Muramatsu et al. injected miR-125b directly into the subcutaneous tumor using non-viral vectors composed of the cationic polymer polyethylenimine (PEI). Administration of miR-125b induced formation of non-functional blood vessels and inhibited in vivo tumor growth by targeting VE-cadherin, suggestive of therapeutic potential . Another kind of liposome is neutral liposomalparticle 1,2-dioleoyl- sn-glycero-3-phosphatidylcholine (DOPC) . Wu et al. reported that the delivery of miR-192, which targets EGR1 and HOXB9, to tumors using the DOPC nanoliposomes significantly inhibited tumor angiogenesis of multiple ovarian and renal cancer models . This delivery platform has also been used for miR-200 and miR-520d in several cancer types in preclinical models to inhibit tumor angiogenesis in vivo [117, 118].
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review
| 99.9 |
To turn miRNA into therapeutics, it is critical to deliver antagomiRs or miRNA mimics specifically into target cells. Endothelial cells in the tumor microenvironment have been actively targeted in vivo for miRNA delivery. The cyclic Arginine-Glycine-Aspartic acid (cRGD) peptide coupled nanoparticle is most widely used. The cRGD could bind to integrin αvβ3 and αvβ5, which are present on tumor ECs, as well as on certain tumor cells. Studies have reported that systemic administration of anti-miR-296, anti-miRNA-132 or miR-7 mimics using the cRGD modified nanoparticles strongly reduced angiogenesis and tumor burden in mice, offering promise for miRNA-based anti-tumor therapeutic [86, 119, 120]. In addition to cRGD modification, anti-angiogenic effect was achieved by using miRNA- incoporated nanoparticles bearing Ala-Pro-Arg-Pro-Gly (APRPG) peptide as well. APRPG has an affinity for VEGFR-1, which is overexpressed on ECs and certain cancer cells . In vivo delivery of miR-499 via APRPG-PEG-modified lipoplexes accumulated in both angiogenic vessels and cancer cells, resulting in the downregulation of miR-499 targeted proteins and inhibition of tumor growth and angiogenesis .
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review
| 99.5 |
Cell-derived membrane vesicles (CMVs), including exosomes and microvesicles, are endogenous carriers transporting biological molecules to recipient cells. In contrast to established synthetic nanoparticles, CMVs are natural transporters and hence, less likely to exert toxicity or immune response, which probably due to their lowhoming to the liver [123, 124]. Moreover, CMVs are shown to contain ribonucleoprotein involved in cellular RNA transport as well as RISC components. Exosomes have already been utilized to transfer therapeutic RNAi to treat diseases [125, 126]. Therefore, CMVs hold great promise as a novel class of miRNA delivery system.
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review
| 99.8 |
Zhang et al. revealed that CMVs derived from HEK293T cells are capable of packing and transporting miR-29a/c into gastric cancer cells. The in vivo experiments illustrated that CMVs could stably transfer miR-29a/c into the implanted tumor cells in mice, playing anti- angiogenic role by directly targeting VEGF . Their data proved that CMVs function as a potential carrier of miRNAs for targeted therapy in gastric cancer. Similarly, Liu et al. used a MV-delivered antisense RNA against miRNA to treat tumors. With the utilization of CMVs derived from HEK293T cells, they transferred anti-miR-150 into mice and found that the neutralization of miR-150 downregulated VEGF levels in vivo and attenuates angiogenesis and tumor growth . These results propose a novel anti-cancer strategy using miRNA- containing CMVs to control tumor angiogenesis.
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study
| 67.6 |
Significant advances have been made in exploring the regulatory role of miRNAs in tumor angiogenesis. The rapidly increasing discoveries shall pave the way in the use of miRNAs as predictive biomarkers for anti-angiogenic treatments and as miRNA-based strategy against tumor angiogenesis in the future, though there are some challenges.
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review
| 99.9 |
Given the low response rate of anti-angiogenic agents, a step forward would be discovering predictive biomarkers to distinguish responders from non-responders. So far, several candidate miRNA biomarkers have been identified, but they emerged from small studies and should be confirmed in large prospective trials. Besides, there has been no unified control miRNAs for normalization in the analysis of circulating miRNA expression. A proposed solution to this problem may be the introduction of exogenous control .
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review
| 99.7 |
Multi-targeted anti-angiogenic approach might exert increasing antitumor efficacy. Since a single miRNA has the potential to regulate angiogenesis by targeting multiple mRNAs, miRNA holds great promise as therapeutic approach for tumor angiogenesis treatment . However, targeting miRNAs systemically may affect normal angiogenesis in which these miRNAs might play regulatory roles as well. In this regard, it is important to identify and target miRNAs that could distinguish angiogenic endothelial cells in tumor vasculature from those in normal tissues [131, 132], thus achieving more specific therapeutic effect and reducing side effect.
|
review
| 99.75 |
At the same time, developing technologies to deliver miRNAs to specific cells in vivo is highly essential for their therapeutic application. Despite having many strategies reported, the successful delivery approach in vivo is still limited. Clinical translation has been hampered by dose-dependent toxicity upon systemic administration [133, 134]. Intriguingly, Kalluri’s recent study showed that exosomes derived from normal fibroblast-like mesenchymal cells exhibited a superior ability to deliver RNAi to suppress pancreatic cancer growth, and showed minimum cytotoxic effects in vivo compared to synthetic nanoparticles. The engineered exosomes (known as iExosomes) target oncogenic KRAS with enhanced efficacy probably due to that CD47 on exosomes surface contributed to the evasion from immune clearance in the circulation, and KRAS-stimulated macropinocytosis increased pancreatic cancer cells uptake of iExosomes . This study offers insight into the therapeutic potential of exosomes in the delivery of nucleic acid-based drugs. However, in terms of using exosomes for specific targeting of angiogenesis-related miRNAs in tumor cells or ECs, there are several aspects to consider. New targeting moieties should be tested for selective homing of exosomes to certain tumor cells and tumor-associated ECs. New targeting moieties, such as peptides and antibody fragments, could be cloned into exosomal surface proteins, or directly attached to the surface of exosomes through chemical conjugation, therefore bypassing time-consuming cloning procedures. Furthermore, the use of miRNA sponge would allow for persistent suppression of miRNA in target tissues following exosome delivery. Additionally, it is critical to find a robust cell source that produces high quantities of exosomes for use in miRNA delivery. For instance, Myc-immortalized human ES-derived mesenchymal stem cells (MSCs) have been demonstrated as a scalable source for production of therapeutic exosomes for regenerative medicine .
|
review
| 99.9 |
In summary, better understanding of the regulatory network of miRNAs in tumor angiogenesis provides new insights in the biological process of tumor-associated neovasculature. Advances in profiling and delivery system offer clinical translation potential of miRNAs as predictive biomarkers for anti-angiogenic therapy response and therapeutics against tumor angiogenesis.
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review
| 99.9 |
Arrhythmogenic cardiomyopathy (ACM) is a genetic disorder in which the ventricular myocardium is progressively replaced by fibro-fatty tissue. Since this occurs predominantly in the right ventricle, the disease is also known as arrhythmogenic right ventricular cardiomyopathy (ARVC). ACM is associated with progressive heart failure and severe ventricular arrhythmias, often leading to sudden death, especially in young people and athletes . About half of the affected individuals harbor mutations in one of the five genes of the cardiac desmosome (PKP2, JUP, DSP, DSG2, DSC2), of which mutations in PKP2 are most common. Desmosomes are intercellular junctions that confer strong cell–cell adhesion and provide a mechanical connection between cardiomyocytes. Therefore, desmosomal defects can have deleterious effects on tissue integrity. In addition, desmosomal proteins play an important role in signaling and regulation of cell proliferation and differentiation . In ACM, pathogenic mechanisms include suppression of Wnt signaling and activation of the Hippo pathway leading to adipogenesis. Beside desmosomal genes, mutations in eight additional genes (DES, PLN, TGFB3, CTNNA3, LMNA, TMEM43, RYR2, and TTN) have been found to cause ACM . Recently, two studies reported FLNC and CDH2 as possible novel causative genes for ACM [4, 5]. In most patients, ACM is inherited in an autosomal dominant mode with reduced penetrance (not all individuals with a causal mutation develop ACM) and variable expressivity (the severity and the nature of the symptoms may vary between affected individuals, even if they have the same causal mutation).
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review
| 99.9 |
Autosomal dominant mutations have only been identified in up to 60% of all ACM patients suggesting the existence of unknown mechanisms such as higher genetic heterogeneity, modifier genes, or cross talk between genetic background and environmental factors . In fact, three loci have been mapped in ACM linkage studies, for which the causal gene has not yet been identified: ARVD3 (OMIM %602,086) at 14q12–32.3 , ARVD4 (OMIM %602,087) at 2q32.1–32.3 , and ARVD6 (OMIM %604,401) at 10p14-p12 . In addition, the frequency of variants associated with ACM has been found to be much higher than expected given the phenotype prevalence in the general population, suggesting that a high number of these variants are not monogenic causes of ACM . In fact, recent reports have suggested digenic inheritance as an alternative disease mechanism of ACM [11–14]. In digenic inheritance the presence of two variants in two different genes is required for the manifestation of a clinical phenotype; in the absence of one of these variants, the other variant might be benign. For example, Xu et al. screened 198 ACM patients for variants in the desmosomal genes. Of the 38 patients in which PKP2 variants were detected, additional variants in PKP2 itself (compound heterozygosity) were identified in nine patients; variants in other desmosomal genes (digenic inheritance) were identified in 13 patients. Related family members harboring a variant in just one of these genes were unaffected by ACM. The authors concluded that the disease was caused by compound heterozygosity or digenic inheritance in these patients . Rasmussen et al. investigated 12 families with variants in DSG2. In three of these families, additional variants were identified in the DSP gene in affected family members. Only individuals with both variants in DSG2 and DSP were affected by ACM, leading the authors to conclude that low penetrance of desomosmal variants in ACM patients may also be explained by digenic inheritance . Cooper et al. proposed that digenic inheritance may occur as a result of variants in two genes encoding different subunits of the same protein (complex); two proteins that interact functionally; are a receptor-ligand pair; are a target gene and transcription factor; or compromise the same regulatory, biosynthetic, or degradative pathway . Digenic inheritance is distinct from modifier genes: in digenic inheritance, both variants individually usually do not lead to disease, whereas in modifier genes one pathogenic variant is enhanced by a putatively contributing variant of unknown significance . Non-genetic factors known to influence ACM penetrance are age, male sex and intense physical activity [16, 17].
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review
| 51.3 |
We performed whole exome sequencing on two families, in which diagnostic tests have identified a PKP2 mutation in affected and healthy individuals. Assuming a digenic mode of inheritance, we determined all genes, where in addition to the observed PKP2 variant a second causal variant was expected to be present in either the affected individuals or the PKP2 carriers. Filtering and prioritizing these genes, we determined four candidate genes in the first, and eleven candidate genes for digenic inheritance in the second family.
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clinical case
| 95.75 |
In this study two Italian families comprising eight and four individuals, respectively, were investigated. Two individuals in the first and one individuals in the second family have been diagnosed with arrhythmogenic cardiomyopathy (ACM) according to the diagnostic task force criteria (Table 1). Furthermore, previous clinically certified molecular tests on known ACM related genes have identified PKP2 variants in all affected and some healthy family members (Fig. 1).Table 1Clinical characteristics of studied individualsa FamilyIDGenderAgePhysical exerciseAffected by ACMType of first symptomAge at first symptomDiagnosed ACM mutationICDACM TherapyDysfunction and structural alterationsTissue characteristic of wallRepolarization abnormalitiesDepolarization or conduction abnormalitiesArrhythmiasComorbiditiesFam1Fam1.I.2F87nono––NM_004572.3(PKP2):c.2013delCnononenonen.a.nonenonenonehypertentionFam1.II.1M70nono – – – nononen.a.n.a.nonenonenonehyperlipidemiaFam1.II.2F67nono––NM_004572.3(PKP2):c.2013delCnononenonen.a.minornonenonehyperlipidemiaFam1.II.3F62nono–––nononen.a.n.a.nonenonenonehyperlipidemiaFam1.II.4M68nono–––nononen.a.n.a.nonenonenonemyocardial infarctionFam1.III.1M39yesno––NM_004572.3(PKP2):c.2013delCnononenonen.a.minornonenonenoneFam1.III.2M35noyesVT21NM_004572.3(PKP2):c.2013delCyesSotalolmajorn.a.majormajormajorhyperlipidemiaFam1.III.3F31yesyesSyncope17NM_004572.3(PKP2):c.2013delCyesSotalolmajorn.a.majornonemajornoneFam2Fam2.I.1M67nono–––nononen.a.n.a.nonenonenonenoneFam2.I.2F66nono––NG_009000.1(PKP2):c.2569_2577 + 41delnononenonen.a.minornonenoneatrial fibrillationFam2.II.1M34yesyesSyncope24NG_009000.1(PKP2):c.2569_2577 + 41delyesSotalolminorn.a.majormajormajornoneFam2.II.2M41yesno––NG_009000.1(PKP2):c.2569_2577 + 41delnononenonen.a.nonenonenonenone aIndividuals classified as they reach major or minor diagnostic criteria n.a.: not available; VT: Ventricular Tachycardia; ICD: implantable cardioverter defibrillator; Athletic lifestyle: defined as intense sportive activity more than 3 times a week Fig. 1Pedigrees of the two families analyzed in this study. Only labeled individuals were sequenced. +: Heterozygous variant, filled black symbols: affected individuals; white symbols with +: carrier individuals; white empty symbols: healthy individuals. Left: Family 1 (Fam1); the blue + symbol indicates the presence of the NM_004572.3(PKP2):c.2013delC variant, the orange + symbol indicates the presence of the four Fam1 variants ENSP00000312435.2(DAG1):p.Leu86Phe, ENSP00000263347.7(TCF25):p.Ser390Phe, ENSP00000259371.2(DAB2IP):p.Asp10Gly, ENSP00000357816.5(CTBP2):p.Gly70Arg. Right: Family 2 (Fam2); the pink + symbol indicates the presence of the NG_009000.1(PKP2):c.2569_2577 + 41del variant, the green + symbol indicates the presence of the ENSP00000434586.1(TTN):p.Gln24857His and the ENSP00000434586.1(TTN):p.Arg23483His variants
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study
| 99.8 |
Pedigrees of the two families analyzed in this study. Only labeled individuals were sequenced. +: Heterozygous variant, filled black symbols: affected individuals; white symbols with +: carrier individuals; white empty symbols: healthy individuals. Left: Family 1 (Fam1); the blue + symbol indicates the presence of the NM_004572.3(PKP2):c.2013delC variant, the orange + symbol indicates the presence of the four Fam1 variants ENSP00000312435.2(DAG1):p.Leu86Phe, ENSP00000263347.7(TCF25):p.Ser390Phe, ENSP00000259371.2(DAB2IP):p.Asp10Gly, ENSP00000357816.5(CTBP2):p.Gly70Arg. Right: Family 2 (Fam2); the pink + symbol indicates the presence of the NG_009000.1(PKP2):c.2569_2577 + 41del variant, the green + symbol indicates the presence of the ENSP00000434586.1(TTN):p.Gln24857His and the ENSP00000434586.1(TTN):p.Arg23483His variants
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clinical case
| 99.9 |
Family 1 (Fam1) consists of eight individuals in three generations of which two are affected by ACM (Fam1.III.2 and Fam1.III.3). The five individuals Fam1.I.2, Fam1.II.2, Fam1.III.1, Fam1.III.2, and Fam1.III.3 carry the heterozygous one base-pair deletion NM_004572.3(PKP2):c.2013delC, NP_004563.2(PKP2):p.Lys672ArgfsTer12, which results in a premature stop codon after a frameshift mutation.
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clinical case
| 99.9 |
Family 2 (Fam2) consists of two parents and their two sons, one of which (Fam2.II.1) is affected by ACM. The male patient Fam2.II.1, his brother Fam2.II.2 and their mother Fam2.I.2 carry the heterozygous nine base pair deletion NG_009000.1(PKP2):c.2569_2577 + 41del, which crosses an exon/intron border.
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clinical case
| 99.94 |
Samples were prepared following the Nextera® Rapid Capture Exome Enrichment kit protocol and were sequenced on two lanes of a HiSeq 2500 in paired end mode (2 × 100). Reads were aligned with BWA and variants called with GATK , following the best practice recommendations. Variants were annotated with information from Ensembl , the ExAC project (allele frequency (AF), variants with AF < 0.01 are called rare), PROVEAN deleteriousness prediction scores (variants with scores < −2.5 are called deleterious) (for SNPs and indels), and LR.PF3 pathogenicity prediction scores (for SNPs only). Copy number variations (CNVs) were called with XHMM . MAESTROweb [26, 27] was used to predict the effect of variants on protein stability based on protein structure, where structure data were available. Sequence conservation was computed with ConSurf . A detailed description is given in the Additional file 1.
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study
| 100.0 |
To investigate whether individuals in the two families develop ACM if they carry the PKP2 mutation and a variant that affects a second unknown gene, a set of putative causal genes was compiled in each family. All genes were determined that have a least one variant that meets the following three criteria: (i) The variant has a consequence, that is classified as either “high” (transcript ablation, splice acceptor variant, splice donor variant, stop gained, frameshift variant, stop lost, start lost, transcript amplification) or “moderate” (inframe insertion, inframe deletion, missense variant, protein altering variant) by Ensembl. (ii) The variant is either present in the family’s affected individuals and not in any family’s PKP2 carrier individuals or it is present in the family’s PKP2 carrier individuals and not in any family’s affected individuals in either a dominant or a recessive mode. (iii) The variant has a coverage of at least 10X in all affected and carrier individuals.
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study
| 100.0 |
In addition to the Fam1 and Fam2 family members, an unrelated female ACM affected individual, her carrier sister, and their carrier aunt, all carrying a heterozygous PKP2 exon 4 deletion, were used to exclude variants as described in (ii) (see Additional file 1 for details). Variants were not filtered based on allele frequency or pathogenicity prediction. Furthermore, all genes were determined that harbored copy number variations (CNV; either a deletion or a duplication) in the affected and carrier individuals applying the same genotype selection criteria as for variants.
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clinical case
| 95.2 |
Each family’s gene set was filtered to only include genes expressed in the heart. The RNA gene dataset was downloaded from the ProteinAtlas version 15, which contains gene expression levels of 45 cell lines and 32 tissues based on RNA-seq. A gene was considered expressed in the heart, if it had an expression level of at least 5 FPKM in the heart muscle in this dataset. We call the genes/variants determined by these filtering steps Fam1 genes/variants and Fam2 genes/variants. This gene selection is visualized in Fig. 2.Fig. 2Methods summary. Whole exome sequencing and variant calling was performed for each individual in both families. For each family, genes are selected that have at least one variant with a high or moderate variant impact, that differ between healthy and affected PKP2 carriers, that have a coverage of at least 10X, and that are expressed in the heart. These genes are filtered to include only genes related to ACM or PKP2 and are computationally prioritized. Results are presented in Table 2
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study
| 100.0 |
Methods summary. Whole exome sequencing and variant calling was performed for each individual in both families. For each family, genes are selected that have at least one variant with a high or moderate variant impact, that differ between healthy and affected PKP2 carriers, that have a coverage of at least 10X, and that are expressed in the heart. These genes are filtered to include only genes related to ACM or PKP2 and are computationally prioritized. Results are presented in Table 2
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study
| 100.0 |
A set of 15 genes known to be involved in ACM was created by literature review [4, 5, 30]. In particular, the ACM gene set consists of the desmosomal genes PKP2, JUP, DSP, DSG2, and DSC2 and the genes DES, PLN, RYR2, TGFB3, TMEM43, TTN, CTNNA3, LMNA, FLNC, and CDH2.
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review
| 99.75 |
Since PKP2 is relevant for the development of ACM in both families, we assumed that the second unknown gene is directly related to PKP2 . Following the probable mechanisms of digenic inheritance described by Cooper et al. , a set of PKP2-related genes was compiled based on the following five criteria. (i) The two gene products form a protein complex. Gene complex data were downloaded from the BioPlex database version 4. Genes that interacted with PKP2 with a confidence of at least 0.7 were selected. (ii) The two gene products interact functionally. PKP2 interactors were downloaded from the STRING database version 10 and the mentha database version 2016–08-07. STRING interactions were restricted to those with a confidence of at least 0.7. The union of PKP2 interactors from the two databases was selected. (iii) The two gene products are transcription factor and target gene. The Ensembl database version 84 and ORegAnno database (release 2015.12.22) were manually reviewed for transcription factors of PKP2. (iv) The two gene products participate in the same pathway. “Biological process” (BP) gene annotations from the Gene Ontology (GO) were used as an approximation. All biological process annotations of PKP2 and all their annotated proteins were queried from the GO database version 2016.7 using the Dintor GOAnnotator tool . Processes were restricted to those where at least half of their annotated genes were expressed in the heart and all genes annotated to these processes were selected, creating a set of genes that share a biological function with PKP2. (v) The two genes are paralogs. Though not specifically listed as a mechanism of digenic inheritance, Cooper et al. discussed that paralogous genes might provide a level of redundancy by resuming gene function in case of a disruption . Therefore, genes paralogous to PKP2 were queried from Ensembl 86.
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study
| 100.0 |
The intersection of Fam1 and Fam2 genes with the PKP2-related genes was prioritized using the Dintor MetaRanker tool , by equally weighting gene expression, number of variants, variant class (consequence class “high” was rated higher than class “moderate”), minimum ExAC allele frequency of the gene’s variant(s), minimum PROVEAN score of the gene’s variant(s), binary prediction (neutral or deleterious) of this PROVEAN score, and presence in a linkage region (see Fig. 2). The LR.PFS3 model was not used in the ranking since it is not defined for indels.
|
study
| 100.0 |
For each of the eight samples relevant to this study (Fam1.I.2, Fam1.II.2, Fam1.III.1, Fam1.III.2, Fam1.III.3, Fam2.I.2, Fam2.II.1, and Fam2.II.2), an average of 54.3 ± 15.3 million reads was generated. The mean base quality was well above 30Q at all read positions, yet a drop in quality could be observed in the last 20 bases of each read. Nearly all reads (99.9%) could be successfully mapped to the human reference genome GRCh37, resulting in a mean coverage of 24.4 ± 3.9X at a mean mapping quality of 45.2 ± 0.8Q. On average, 85.1 ± 3.8% of the exonic target region was covered with at least 10X.
|
study
| 100.0 |
The filtering strategy described in the Methods Section and visualized in Fig. 2 resulted in 85 variants in 74 distinct genes in Fam1 and 242 variants in 212 distinct genes in Fam2. The gene sets for both families obtained by this filtering strategy are available as Additional file 1: Table S1. No CNVs in either family met the selection criteria. Since the number of genes per family was too large to analyze in detail, we decided to restrict our analysis to known ACM related genes and then to PKP2-related genes.
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study
| 100.0 |
From the 15 ACM-related genes, none was present in the gene set of Fam1, while TTN was in the gene set of Fam2 (Table 2). Specifically, the affected male patient Fam2.II.1 and his healthy father Fam2.I.1 harbored three distinct heterozygous missense variants in TTN. The two rare variants ENSP00000434586.1:p.Gln24857His (isoform N2B) and ENSP00000434586.1:p.Arg23483His (isoform N2B) were predicted deleterious by PROVEAN and LR.PFS3. Both variants were confirmed by Sanger sequencing (see Additional file 1). The third TTN variant ENSP00000434586.1:p.Ile3716Val (isoform N2B) is common, not conserved, and was predicted neutral by PROVEAN and LR.PFS3. TTN encodes for titin, the largest human protein, which has over 300 highly repetitive independently folding domains, including 152 immunoglobulin like, 132 fibronectine 3 (Fn3), 19 Kelch, 14 tetratricopeptide repeat, and 15 solenoid domains . The variant Arg23483His is located in the 125th of the 132 Fn3 domains (PF00041), while Gln24857His is located inside titin’s only serine kinase domain (PF00069), a structurally conserved protein domain that plays an important role in the regulation of cell proliferation, apoptosis and cell differentiation. The location of this variant and other functional residues in the protein structure of the kinase domain is visualized in Fig. 3. The mutated residue Gln24857His is located opposite of the active site and results in a charge and polarity change. The variant was further predicted to destabilize the protein structure by MAESTROweb (ΔΔG = 1.433, confidence = 0.8). In addition, the wild type residue glutamine was highly conserved in a multiple sequence alignment of homologous sequences from 63 species computed by ConSurf.Table 2Fam1 and Fam2 genes and corresponding variants that overlap with the ACM genes or the PKP2-related genesFamilyGene seta Gene rankb Gene nameHGVSpVariant consequencePROVEAN predictionc Population frequencyd Genotypee CommentFam2ACM–TTNENSP00000434586.1:p.Gln24857Hismissensedeleteriousrarehet in Fam2.II.1 and Fam2.I.1Mutations in TTN can cause ACM .Fam2ACM–TTNENSP00000434586.1:p.Arg23483Hismissensedeleteriousrarehet in Fam2.II.1 and Fam2.I.1Mutations in TTN can cause ACM .Fam2ACM–TTNENSP00000434586.1:p.Ile3716Valmissenseneutralcommonhet in Fam2.II.1 and Fam2.I.1Mutations in TTN can cause ACM .Fam1PKP2 (GO: neg. Reg. cell prolif.)1DAG1ENSP00000312435.2:p.Leu86Phemissenseneutralrarehet in Fam1.III.2, Fam1.III.3, Fam1.II.1β-dystroglycan binds to Hippo pathway effector Yap to inhibit cardiomyocyte proliferation in mice .Fam1PKP2 (GO: heart developm.)2TCF25ENSP00000263347.7:p.Ser390Phemissenseneutralrarehet in Fam1.III.2, Fam1.III.3, Fam1.II.1Negatively regulates SRF, whose increased expression causes cardiomyopathy in mice .Fam1PKP2 (GO: neg. Reg. cell prolif.)3DAB2IPENSP00000259371.2:p.Asp10Glymissenseneutralrarehet in Fam1.III.2, Fam1.III.3, Fam1.II.1One variant in DAB2IP has been associated with coronary heart disease .Fam1PKP2 (GO: neg. Reg. cell prolif.)4CTBP2ENSP00000357816.5:p.Gly70Argmissenseneutralcommonhet in Fam1.III.2, Fam1.III.3, Fam1.II.1Ctbp2-null mice have defective heart morphogenesis. CTBP2 may be a regulator of Wnt-mediated gene expression .Fam2PKP2 (GO: neg. Reg. cell prolif.)1IRF1ENSP00000384406.1:p.Asn259Sermissensedeleteriousrarehet in Fam2.II.1 and Fam2.I.1IRF1 is associated with cancer and a negative regulator of coronary artery smooth muscle cells (OMIM *147575).Fam2PKP2 (GO: reg. of bicell. Tight. junction assembly)2MYO1CENSP00000412197.2:p.Gln766Lysmissenseneutralrarehet in Fam2.II.1 and Fam2.I.1OMIM *606538Fam2PKP2 (GO: cardiac muscle cell action pot.)3DMDENSP00000367948.2:p.Arg2151Trpmissenseneutralcommonhemi in Fam2.II.1, Fam2.I.1; het in Fam2.I.2Recessive mutations in DMD can cause muscle dystrophy (OMIM *300377).Fam2PKP2 (GO: heart development)4MKKSENSP00000382008.2:p.Ile339Valmissenseneutralrarehet in Fam2.I.2 and Fam2.II.2Recessive mutations in MKKS can cause Bardet-Biedl syndrome (OMIM *604896).Fam2PKP2 (GO: neg. Reg. cell prolif.)5NOTCH2ENSP00000256646.2:p.Asp1327Glymissenseneutralcommonhet in Fam2.I.1 and Fam2.II.1This variant has been reported causal for Congenital heart disease as compound heterozygote with L2408H, which is absent in Fam2 .Fam2PKP2 (GO: heart development)6PKD1ENSP00000456672.1:p.Arg198Trpmissenseneutralrarehet in Fam2.II.1 and Fam2.I.1Dominant mutations have been associated with polycystic kidney disease (OMIM *601313).Fam2PKP2 (PPI / GO: pos. Reg. sodium ion)7SCN5AENSP00000398962.2:p.His558Argmissenseneutralcommonhet in Fam2.I.1, Fam2.I.2, Fam2.II.2, Fam1.II.3This variant has been reported causal for isolated conduction disease as compound heterozygote with T215I, which is absent in Fam2 .Fam2PKP2 (GO: neg. Reg. cell prolif.)8MYOCDENSP00000341835.4:p.Gln304delinframe deletionneutralcommonhet in Fam2.II.1 and Fam2.I.1Cardiac muscle-specific transcriptional coactivator of serum response factor. Mutations have been associated with hypertrophic cardiomypathy (OMIM *606127).Fam2PKP2 (PPI)9DSC1ENSP00000257198.5:p.Cys848Phemissenseneutralcommonhet in Fam2.II.1 and Fam2.I.1Desmosomal protein desmocolin 1 (*OMIM 125643).Fam2PKP2 (PPI)10DROSHAENSP00000339845.3:p.Ser321Leumissenseneutralcommonhom in Fam2.I.2, Fam2.II.2; het in all others except Fam1.II.2Ribonuclease III. Mutations have been associated with cancer (OMIM *608828). a ACM: known ACM genes; PKP2: PKP2 related genes b PKP2-related genes are listed according to their rank from top to bottom cdeleterious: PROVEAN score < −2.5; neutral: PROVEAN score > = 2.5 dcommon: ExAC AF > = 0.01; rare: ExAC AF < 0.01 or NA; ExAC: Exome Aggregation Consortium ehet: heterozygous; hom: homozygous; hemi: hemizygous. If an individual is not listed, his/her genotype is homozygous reference Fig. 3Structure of the titin kinase domain (PDB 1tki chain A). Functional residues are represented as ball and stick, D24874 is the catalytic aspartate. The ATP binding site includes residue K24783 as well as the nearby yellow loop. The calcium/calmodulin binding helix is colored blue, the helix in orange blocks the ATP binding site in this autoinhibited conformation. Residue Q24857 is solvent exposed on the side opposite to the functional residues
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clinical case
| 94.75 |
Structure of the titin kinase domain (PDB 1tki chain A). Functional residues are represented as ball and stick, D24874 is the catalytic aspartate. The ATP binding site includes residue K24783 as well as the nearby yellow loop. The calcium/calmodulin binding helix is colored blue, the helix in orange blocks the ATP binding site in this autoinhibited conformation. Residue Q24857 is solvent exposed on the side opposite to the functional residues
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other
| 99.56 |
In the next analysis step, we identified 311 genes related to PKP2 following the criteria defined in the Methods section: (i) Five genes form a complex with PKP2, (ii) 33 genes interact with PKP2, (iii) four genes are transcription factors of PKP2, (iv) 275 genes are involved in one of 12 biological processes together with PKP2, (v) and three genes are paralogs of PKP2. A list of these PKP2-related genes is available as Additional file 1: Table S2. Four Fam1 genes and ten Fam2 genes were in the set of PKP2-related genes and were prioritized based on their expression in the heart, the number and type of variants, their allele frequencies and deleteriousness prediction. These PKP2-related genes and variants of both families are summarized in Table 2. The full table with additional, detailed annotations is available as Additional file 1: Table S3.
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study
| 100.0 |
Of the four PKP2-related genes DAG1, DAB2IP, and CTBP2 in Fam1 are associated with PKP2 through the GO BP process “negative regulation of cell migration”, while TCF25 is associated with PKP2 through the GO BP process “heart development”. The variants in all four genes are predicted neutral by PROVEAN, and all but the one in CTBP2 are rare. The highest ranking PKP2-related gene in Fam1 is DAG1, which encodes for dystroglycan, a central component of the dystrophin–glycoprotein complex (DGC). Dystroglycan is post-translationally cleaved into α- and β-dystroglycan subunits . α-dystroglycan is an extracellular protein involved in the interactions between DGC and extracellular matrix components, while β-dystroglycan contains a single transmembrane domain and a C-terminal cytoplasmic tail. The DAG1 candidate substitution ENSP00000312435.2:p.Leu86Phe is located in the α-dystroglycan N-terminal region, where the leucine side chain is solvent exposed on the side of a Ig-like domain . The position is in close proximity to Thr63, identified as a O-glycosylation (see Additional file 1: Fig. S1). The variant was predicted to stabilize protein structure by MAESTROweb (ΔΔG = −0.231, confidence = 0.9). For the other three candidate genes, no protein structure was available in PDB, so predictions with MAESTROweb could not be computed.
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study
| 100.0 |
The highest ranking PKP2-related gene in Fam2 is the interferon regulatory factor 1 (IRF1), which harbors a rare, deleterious-predicted missense variant in the affected male patient Fam2.II.1 and his healthy father Fam2.I.1. IRF1 inhibits cell growth in coronary artery smooth muscle cells . Repression of IRF1 has lead to a higher susceptibility to the formation of neointima (scar tissue) following vessel injury in mice .
|
clinical case
| 99.2 |
In this study we investigated the genetic cause of ACM in two families using whole exome sequencing. Since all affected and some unaffected individuals were known to harbor PKP2 variants, we investigated whether a second gene was involved in a digenic inheritance pattern, with the second gene either causing ACM in the affected individuals together with PKP2, or compensating the effect of the PKP2 variants in the carriers. We identified 74 and 212 genes in families 1 and 2, respectively, which carried variants consistent with the mode of digenic inheritance. To obtain results that can be easily interpreted, we restricted our analysis to genes either associated with ACM or related to PKP2. In family 1 we identified four genes that are annotated with the same biological process as PKP2. In family 2 we identified the ACM associated gene TTN and ten genes related to PKP2 through a shared biological process or protein interactions (see Fig. 2).
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study
| 100.0 |
Of the four PKP2-related Fam1 genes, the genes homologous to DAG1, TCF25, and CTBP2 have been linked to cardiomyocyte proliferation or heart development in mice and, in case of TCF25, also in human. DAG1 and TCF25 negatively regulate heart development, while a knock out of CTBP2 leads to a lethal malformation of the heart in mice. A variant in DAB2IP has been associated with coronary heart disease in two studies, indicating that this gene might also play a crucial rule for the normal functioning of the heart. It has been reported that β-dystroglycan, a protein product of DAG1, directly binds to the Hippo pathway effector Yap to inhibit cardiomyocyte proliferation in mice . In particular, the Hippo pathway and DGC cooperatively regulate tissue growth in mouse hearts after injury. Yap and the Hippo pathway have been directly implicated in ACM pathogenesis . TCF25 (previously named NULP1) was suggested as a transcription factor that negatively regulates the serum response factor (SRF). SRF controls muscle differentiation and cellular growth and regulates cardiac genes. SRF over-expression has been shown to cause cardiomyopathy and cardiac hypertrophy in mice. Therefore, TCF25 may function as a transcriptional repressor of SRF in human heart development . DAB2IP acts as a tumor suppressor gene, and is inactivated by methylation in prostate and breast cancers. A genome-wide association study found the rs7025486 variant in DAB2IP associated with coronary heart disease, which was replicated in a second study . CTBP2 encodes two proteins, a transcriptional repressor and a major component of synaptic ribbons. Silencing the homologous Ctbp2 gene in mice causes defects in heart morphogenesis and results in early embryonic lethality . Ctbp2-null mice show similar axial truncation phenotypes as mice with mutations in some Wnt target genes, suggesting that CTBP2 may be a regulator of Wnt-mediated gene expression . Indeed, CtBP2 acts as corepressor of C/EBPα, an early regulator of adipogenesis, and target of the Wnt signaling pathway . Furthermore, Sox6 has been found to bind Ctbp2 to repress the fibroblast growth factor 3 and Sox6 to regulate the cardiac myocyte development in mice . Although none of the variants in these four genes are predicted to be deleterious and the variant in DAG1 is even predicted to stabilize protein structure, they could nevertheless affect protein stability, flexibility, and interaction with the other binding partners. However, in the present study we could not find any indication that these genes may act together with PKP2 to cause the ACM phenotype in the affected individuals of Fam1.
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study
| 99.94 |
Since TTN is a known ACM associated gene, it is a likely candidate in the second family. TTN encodes for titin, the largest human protein with isoforms ranging from about 27.000 to 36.000 amino acids. Titin is functionally linked to the desmosome (and thereby to PKP2), since titin filaments are a key component of sarcomeres and connect to the transitional junction at the intercalated disk . In a cohort of 38 ACM families, Taylor et al. identified novel TTN mutations in 18% of the families . In addition to ACM, TTN has been associated with dilated, hypertrophic, and restrictive cardiomyopathy ; its association with hypertropic cardiomyopathy, however, is still under debate . The affected patient Fam2.II.1 and his father both harbor two rare heterozygous missense variants that are predicted deleterious. The Gln24857His variant is located in titin’s only kinase domain at a conserved position and is predicted to destabilize protein structure, while Arg23483His is located in one of the 132 Fn3 domains. Therefore, the Gln24857His variant is more likely to impair titin function than the Arg23483His variant, even though disease causal variants in repetitive titin domains have been reported . Studies with transfected cell lines have shown that heterozgyous mutations, in contrast to homozygous mutations, still allow for functional sarcomeres but may alter the organizational characteristics and impair the normal cardiac function . These findings agree well with the hypothesis that either one or both of these variants alter the structure of titin and only lead to ACM in combination with the PKP2 mutation.
|
clinical case
| 92.9 |
In addition to the genes described here in more detail, there are other promising candidates for the second causal gene in Fam2 (see Table 2). For example, of the PKP2-related genes, NOTCH2 and SCN5A harbor one of two compound heterozygous variants that have been reported to cause congenital heart disease and isolated conduction disease, respectively [51, 52]; DMD harbors a neutral hemizygous variant in the affected Fam2 individual, a gene where recessive variants can cause muscle dystrophy; DAG1 and MKKS are associated with recessive diseases, yet the variants in the affected individuals are heterozygous; IRF1 is associated with non-cardiac diseases; DSC1, a desmosomal gene not associated with heart disease, harbors a common missense variant that is predicted neutral. Since all of these genes are interesting candidates for follow up studies, it would be interesting to test whether the same or other rare variants in our candidate genes can be identified in a large cohort ACM patients, both in patients carrying desmosomal mutations or other ACM related mutations as well as in genetically unsolved cases.
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study
| 100.0 |
Digenic inheritance has previously been reported as a disease-causal mechanism for ACM, however, these studies have focused on desmosomal genes. As a result, there are no reports of digenic inheritance in ACM with PKP2 and a non-desmosomal gene such as TTN.
|
study
| 99.94 |
We are aware of limitations in our study. Both families have relatively few members, which resulted in a large set of variants and genes as possible candidates for digenic inheritance. Only 85% of the exome was covered with at least 10X. Since we required a minimum coverage of 10X to accept a variant call, 15% of the exome could not be investigated. However, coverage at the ACM genes was well above average, so it is unlikely that variants were missed in these genes. Due to the large number of candidate genes in each family, we restricted our analysis to ACM or PKP2-related genes, potentially removing causative digenic genes with unknown associations. Even though the TTN variants in Fam2 were confirmed by Sanger sequencing, no functional validation of the variant effects was performed. Therefore, it still needs to be shown if TTN or any of the candidate genes in Fam1 truly cause ACM together with PKP2 in the respective family. A functional validation could be performed based on induced pluripotent stem cell (iPSC) models from the ACM-affected individuals, where the PKP2 variant or the TTN/Fam1 variants are reversed . In the iPSC derived cardiomyocytes the effect of the genetic variants could be investigated by comparing fat accumulation and cell electrophysiology to the double mutant cells. Other cell models that could be employed for validation are progenitor cells (they differentiate easily in vitro), non-contractile cardiac mesenchymal stromal cells (ideal for studying lipid metabolism), or primary or immortalized cardiomyocytes (enable investigation of gap-junctions and ion-channels) . Yet, even if successful, such experiments would demonstrate the mode of effect in the respective family, while general conclusions about the role of TTN/Fam1 genes in ACM could not necessarily be drawn from them. To evaluate the roles of these genes in ACM more generally, other ACM patients carrying desmosomal variants could be checked for rare variants in the respective genes. Unfortunately, we currently do not have additional ACM patients for testing and the NCBI Sequence Read Archive does not contain public whole exome or whole genome sequence data of ACM patients. The search for genes with a digenic effect is a considerable challenge since variants in both relevant genes do not necessarily have a pathogenic effect when occurring individually . The functional or structural change caused by the variant in either protein may be subtle, and may for example lead to a change at a protein binding affinity or a change in gene expression. Therefore, standard criteria usually applied to evaluate the likelihood of variant pathogenicity like rarity and computational predictions might not be well suited. Consequently, we did not exclude variants based on these criteria, yet in the absence of functional validation and more appropriate models, we prioritized and discussed our results according to these methods. We would like to recall that we did not distinguish between variants that were present in the affected and not in the carriers and variants present in the carriers but not in the affected, since we were interested in genes whose function might differ between affected individuals and carriers due to the variants. However, we point out that of the 17 variants listed in Table 2, only three (Ile339Val in MKKS, His558Arg in SCN5A, and Ser321Leu in DROSHA) are present in the carriers and not in the affected individuals, suggesting that our strategy of prioritizing based on rarity and predicted pathogenicity is appropriate. Finally, we acknowledge the possibility that more than two genes could be involved in the pathogenesis (oligogenic inheritance) or, contrarily, that environmental factors could influence the penetrance of the PKP2 variants without other genetic variants having an effect on the development of ACM. However, in our study, the main non-genetic disease modulators (age, sex, and physical exercise) are not sufficient to explain the different phenotypic expression in affected individuals and carriers in the two analyzed families (see Table 1). In Fam1, both the carrier Fam1.III.1 and the affected Fam1.III.2 are male and are close in age, and carrier Fam1.III.1 and the affected Fam1.III.3 are both physically active. In Fam2, both the affected Fam2.II.1 and the carrier Fam2.II.2 are male, physically active, and relatively close in age.
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study
| 99.94 |
Enhancing the grain yield potential of wheat is a key focus of wheat breeders. Grain yield is the product of various yield components. Wheat grain yield per unit area is the product of grain yield per spike (GYS) and the number of spikes per unit area. The latter depends on sowing density and is highly affected by environmental factors. The GYS is determined by grain number per spike (GpS) and thousand grain weight (TGW), which are variably correlated in different wheat collections/populations. A significant negative correlation between these two traits has been reported in bi-parental populations [1–3], but no significant correlation was observed between TGW and GpS in collections of Chinese landraces , French winter wheat cultivars and CIMMYT-derived spring wheat collections . On the other hand, a significant positive correlation between TGW and GpS was reported in modern Chinese cultivars .
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study
| 99.94 |
TGW in wheat has been one of the target traits for selection during domestication and breeding [7, 8]. For example, in China, an increase in wheat yield potential from ~1 T ha−1 in 1992 to ~5.4 T ha−1 today is mainly due to the genetic increase in TGW from ~20 g to ~45 g, respectively . However, genetic gain in TGW has not reached its limit and thus provides an opportunity to increase yield potential . It is estimated that an increase in yield of 140–160 kg ha−1 can be obtained by just a 1-g increase in TGW . However, genes and their roles in controlling TGW in wheat are still largely unknown. In wheat, TGW is a quantitative trait controlled by several genes/QTL distributed on all chromosomes [8, 11]. For example, Su et al. discovered eight TGW-related QTL on chromosomes 2D, 4B, 5A, 7A and 7B, explaining up to 16.2% of the phenotypic variation. Similarly, four QTL for TGW on chromosomes 1D, 2A, 5D, and 6A explained 5.9 to 20.1% of phenotypic variation in different environments .
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study
| 99.94 |
Nevertheless, from this plethora of QTLs, few loci/genes have been cloned by map-based cloning approaches mainly because of the large and complex hexaploid genome (~17 Gb) that consists of three homeologous genomes (A, B, D) and an abundance of repeat sequences (80%) . Studies on comparative genomics have shown high synteny and collinearity among different grass genomes, such as those of wheat, barley, rice, millet, maize and sorghum. This pattern of genome organization in the members of the grass family provides a powerful approach for gene discovery in common wheat . A large number of genes have been discovered in common wheat by synteny-based cloning, in which the gene sequences of model crops such as rice and barley have been used as references to identify orthologous genes in wheat. For example, the genes TaTGW6 [16, 17], TaCwi-A1 , TaSus2-2B , TaSus2-2A, TaSus1-7A , TaGW2-6A, 6B [9, 12, 21], TaCKX6-D1 , TaSAP1-A1 , TaGS1a , TaGS-D1 , and TaGASR-A1 were discovered using rice-wheat synteny and using molecular markers in marker-assisted wheat breeding. Hence, the isolation and characterization of genes controlling grain size in common wheat will help breeders maximize yield potential by establishing gene-based breeding programs.
|
review
| 96.75 |
The FLOURY ENDOSPERM2 (Flo2) gene is a member of a conserved gene family in plants. In rice, this gene has been shown to have a tetratricopeptide repeat (TPR) motif consisting of 3–16 tandem repeats of 34 aa residues that mediate protein–protein interactions in the nucleus [27, 28]. The OsFlo2 gene was cloned in the indica cultivar ‘Kasalath’; this gene was found to have 23 exons and 22 introns and coded for a protein consisting of 1720 amino acid residues that had three TPR motifs in the middle . The expression of Flo2 was constitutive in both vegetative tissues and developing seeds, and the expression was relatively high level in developing seeds. The flo2 mutants exhibit a significant reduction in amylose content and grain weight and exhibit altered expression of various starch synthesis-related genes, indicating its key role in regulating rice grain weight and starch quality [27, 28]. In this article, we report the rice-wheat synteny-based isolation of Flo2 orthologs in hexaploid wheat, the association of TaFlo2-A1 sequence polymorphisms with TGW and the comparison of temporal expression profiles of TaFlo2-A1 haplotypes in flag leaves and developing caryopses.
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study
| 100.0 |
For cloning the TaFlo2 gene in hexaploid wheat, Chinese Spring (CS) and two sets of cultivars with lower and higher TGW were used; the set of cultivars with higher TGW included Dixiuzao (49.5 g), Enmai4 (49.2 g), Liying 5(49.4 g) and Laizhou 953 (52.2 g), and the set with lower TGW included Jinyang 60 (23.5 g), Baihuamai (24.1 g), Sanyuehuang (25.2 g) and Zipi (25.5 g). The Chinese Spring nulli-tetrasomic lines were used to assign TaFlo2 genes to wheat homeologous chromosomes. The Chinese Micro Core Collection (MCC, 262 accessions) and Pakistani wheat collection (130 accessions) were used to confirm the association between TaFlo2-A1 haplotypes and TGW. To avoid the effect of population structure, normalized MCC subpopulations were used for association analysis [19, 29]. The Pakistani collection was selected based on previous reports [30, 31] considering the effect of population structure on association analyses.
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study
| 100.0 |
The genomic sequence of the rice OsFlo2 gene (NC_008397) was used as a query for BLAST searches against the wheat sequences database in the URGI (https://urgi.versailles.inra.fr/). All wheat scaffold sequences with high similarity to the rice OsFlo2 sequence were assembled to construct a putative TaFlo2 gene using DNAMAN (http://www.lynnon.com). Based on the scaffold sequences, six conserved primer pairs were used to specifically amplify TaFlo2 coding and promoter sequences from the three wheat sub-genomes: A, B and D (Table 1). The TaFlo2 mRNA of 4902 bp was cloned in Chinese Spring using three primer pairs designed from the predicted mRNA sequence (Table 1). Genomic DNA was extracted from young seedlings of each line using the CTAB method . A 20-μl reaction volume comprising 0.5 μl (5 μM) of each primer, 2× Taq mix (GenStar, Beijing, China) and 100 ng of DNA was used for PCR amplification that consisted of a cycle profile of 5 min at 94 °C; 35 cycles of 30 s at 94 °C, 30 s at 60 °C and 4 min at 72 °C; and a final extension of 10 min at 72 °C. The PCR products were detected by electrophoresis in 1% agarose gels with nucleic acid dye (Tiangen, Beijing, China), and gel images were captured using a UV spectrometer (BioRad, Hercules, CA, USA). The targeted PCR products were obtained from the agarose gels and purified using the TIANgel MIDI Purification Kit (Tiangen, Beijing, China). The purified PCR products were then ligated into the pGEM-T Easy cloning vector (TransGen Biotech, Beijing, China). The ligation product was transformed to 50 μl of Trans1-T1 competent cells by the heat shock method (Tiangen, Beijing, China). Positive clones from each transformation were selected based on positive PCR tests and were sequenced (Beijing Genomics Institute). The sequences were analyzed using DNAMAN software (http://www.lynnon.com).Table 1Primer sequences used in this studyPrimer namePrimer sequence (5′-3′)Position on scaffold sequenceAnnealing temperature (°C)PCR product sizeFunctionFlo2-1FTGTGCTGGAATCACCCACTC793–812601061cloning TaFlo2 /polymorphism detectionFlo2-1RGCGCGGCGAAAACTAATCAT1853–1844Flo2-2FGTGCCGTCCATAATCGTTGC1546–1565601781cloning TaFlo2 /polymorphism detectionFlo2-2RCATGTGCGGCAAAAGACACA3326–3307Flo2-3FAACGGGCATGTGTCTTTTGC3299–3318603025cloning TaFlo2 /polymorphism detectionFlo2-3RCGACGCAGCTCTGAAAATCG6332–6313Flo2-4FCGCTTAGCAGTGGATTTGCC5719–5738603948cloning TaFlo2Flo2-4RATCCAACAAACAGGTGCCCA9667–9647Flo2-5FTTGCGGAAGCCCATCATTCT8387–8406603836cloning TaFlo2Flo2-5RTGACCTTCTGCGGATGCTTT1222–12,203Flo2-6FCAGAACAGGGCCGGTACAAT11,368–11,387602600cloning TaFlo2Flo2-6RCGCTCATCTGGATAGGGCAA13,967–13,948TaFlo2-InDel8FACCCCTCCTCCGTTATCGTC1337–135660145/1538-bp InDel polymorphism in TaFlo2-A1 TaFlo2-InDel8RCCTCCTTCTTCTTGCGGTCG1470–1489Flo2-A1FGTGCTCCGATCCGATGTGCAGTTAT5387–5411585872A specificFlo2-A1RGTGCACAACCAAGTAAAAGG5973–5954Flo2-B1FGTC ATC ACTAGAGGA ATTTTCC6851–6872589022B specificFlo2-B1RCTCTCAGAACTGTGGAT7752–7736Flo2-D1FCTGTATCTGTAATTTGTTCCG5378–5398583262D specificFlo2-D1RCTTCCGAAAAATGTGGGG5704–5687mFlo2-1FTAACGGTGGTGCACTTGTGT–581868Cloning mRNAmFlo2-1RTCAGCCGCAAGTTATGCTCA–mFlo2-2FTGCGGACGAGATGGAAAACA–581809Cloning mRNAmFlo2-2RAGCAGTCAGCCGATGGTATG–mFlo2-3FATGCGTACTCCCTAAGCGTG–581889Cloning mRNAmFlo2-3RCACGAAGTGCTGCTTGCTTT–eTaFlo2FCCATTCGGCTTTCGTGCAAA–55134Expression analysiseTaFlo2RTGTTTTCCATCTCGTCCGCA–ActinFAGCCATACTGTGCCAATC–55134Internal controlActinRGCAGTGGTGGTGAAGGAGTAA–
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The 262 MCC and 130 Pakistani varieties were genotyped with the primer pair TaFlo2-InDel8, and PCR product was run on 8% polyacrylamide gels. Based on TaFlo2-InDel8 scoring, the MCC and Pakistani accessions sorted into two groups according to their haplotypes (TaFlo2-A1a or TaFlo2-A1b) for the TaFlo2-A1 gene. For MCC, the average values of TGW of the two haplotype groups were calculated using replicated data collected from 3 years (2002, 2005, 2006) of plants in Beijing . For Pakistani varieties, the average values of TGW of the two haplotype groups were calculated using replicated data from 2 years (2009, 2010) of field trials at the University of Agriculture, Faisalabad. The resulting values were then compared and statistically analyzed using SPSS 13.0 for Windows (IBM, New York, USA).
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The Yangmai 19, Chinese Spring, Pubing3228, Shannong23 and Zhengmai9405 varieties were sown at the experimental station of the Institute of Genetics & Developmental Biology, CAS in Beijing, China in October 2014; three rows of each variety were planted. The length of each row was 2 m, and the row-to-row distance was 20 cm. The plants were managed in accordance with standard agronomic practices; irrigation and fertilizer were supplied for optimal growth. Twelve- day-old flag leaves of five plants from each variety were harvested and stored at −80 °C. Unfertilized grains were collected from each variety 1–2 days before flowering (DBF). Fertilized grains were collected from each variety at 5, 10, 15, 20 and 25 days after flowering (DAF). The flag leaf and developing grain samples were processed for the preparation of total RNA as described previously . Three biological replicates that were collected from different plants were analyzed separately for each variety for quantitative RT-PCR evaluation. For TaFlo2-A1 transcripts analysis, the primer set eTaFlo2, which is specific for TaFlo2-A1 (Table 1), was designed and used. Quantitative RT-PCR was then carried out as described by Feng et al. . The wheat actin gene was used as an internal control. The relative expression level of TaFlo2-A1 in each flag leaf and in each sample of developing grains was calculated using the data of three technical replicates as described previously . Statistical comparisons of TaFlo2-A1 expression levels (presented as the mean ± SD) among different samples were made by ANOVA using SPSS 13.0.
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Nucleotide and protein identities among the compared sequences were calculated using DNAMAN (http://www.lynnon.com). Amino acid sequence alignment was accomplished using ClustalW2 in EMBLEBI (www.ebi.ac.uk/Tools/msa/clustalw2). Potential signal peptide sequences in the deduced proteins of TaFLO2 and its homologs were predicted using Softberry software (http://www.softberry.com/berry.phtml). The predicted TaFLO2 protein was BLASTed both in the NCBI smart blast system (http://blast.st-va.ncbi.nlm.nih.gov/smartblast) to search for homologous proteins and in the NCBI CD system (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) to search for conserved domains.
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To select potential candidate TaFlo2 genes, the rice Flo2 sequence (NC_008397) was used as a query against the wheat genome sequences database in the URGI (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi). Three bread wheat scaffolds (IWGSC_chr2AL_ab_k71_contigs_longerthan_200_6436403, IWGSC_chr2BL_ab_k71_contigs_longerthan_200_7959819, IWGSC_chr2DL_ab_k71_contigs_longerthan_200_9909583) with high similarity (E value = 0 and similarity >73%) were identified as potential orthologs to the rice Flo2 gene. The sequences of these scaffolds were downloaded and assembled with DNASTAR (http://www.dnastar.com/) to construct a putative TaFlo2 sequence.
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To search TaFlo2 homologs and predict their deduced protein sequence and structure, Softberry (http://www.softberry.com/berry.phtml) and NCBI (https://www.ncbi.nlm.nih.gov/) tools were used. The deduced proteins of TaFlo2-A1 (1734 aa), TaFlo2-B1 (1698 aa) and TaFlo2-D1 (1682 aa) were highly similar (>94% identity among themselves) and exhibited >77% similarity with the rice FLO2 protein. Like in the rice FLO2 protein , four tetratricopeptide repeat (TPR) motifs were observed in the deduced TaFLO2 protein at the positions of 947–988, 1032–1072, 944–1017 and 1028–1106 amino acid residues. Furthermore, three mitochondrial CLU domains were also observed at 737–878, 50–162 and 357–401 amino acid residues (Fig. 1a). The TaFLO2 protein showed high similarity with Aegilops tauschii, Brachypodium distachyon and long-grain rice proteins (Fig. 1b).Fig. 1 a Putative structure of the OsFLO2 and TaFLO2 proteins. Clu_N (mitochondrial function, CLU-N-term), CL (clustered mitochondria domain), CLU-center (an uncharacterized central domain of CLU mitochondrial proteins), TPR (tetratricopeptide repeat). b Similarity between the TaFLO2 protein and proteins from related plant species
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a Putative structure of the OsFLO2 and TaFLO2 proteins. Clu_N (mitochondrial function, CLU-N-term), CL (clustered mitochondria domain), CLU-center (an uncharacterized central domain of CLU mitochondrial proteins), TPR (tetratricopeptide repeat). b Similarity between the TaFLO2 protein and proteins from related plant species
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| 99.94 |
To clone the full-length genomic sequence of TaFlo2 in Chinese Spring, six conserved primer pairs were used (Table 1). The assembly of sequences with the six conserved primer pairs yielded three fragments, 14,009, 14,078 and 13,814 bp. Based on alignment with wheat scaffolds in the database and genome-specific primers, the fragments were designated TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1. The open reading frames of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 were 12,183 bp, 12,270 bp and 12,022 bp in length, respectively. The TaFlo2 mRNA of 4902 bp was cloned with three primer pairs (Table 1). Based on the prediction and alignment with cloned mRNA, the cloned genomic sequences from 2AL, 2BL and 2DL consisted of 23, 23 and 24 exons, respectively (Fig. 2a). Among the three homoeologs, the sequence and size of the first four exons were conserved, whereas the size and sequence of the other exons varied.Fig. 2Polymorphism, molecular marker and ORF structure of TaFlo2 homoeologs. a Exon and intron pattern in the ORFs of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1. The length of each ORF (between the start and stop codons) is shown to the right of the graph. The number of nucleotides in each exon or intron is indicated. CDSf: First coding sequence, CDSi: Internal coding sequence, CDSl: Last coding sequence. b Alignment of the part of cloned TaFlo2 orthologs. Polymorphism both in the promoter and first intron is indicated by stars. c PCR product of molecular marker TaFlo2-InDel8 discriminated by PAGE in 60 MCC accessions
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Polymorphism, molecular marker and ORF structure of TaFlo2 homoeologs. a Exon and intron pattern in the ORFs of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1. The length of each ORF (between the start and stop codons) is shown to the right of the graph. The number of nucleotides in each exon or intron is indicated. CDSf: First coding sequence, CDSi: Internal coding sequence, CDSl: Last coding sequence. b Alignment of the part of cloned TaFlo2 orthologs. Polymorphism both in the promoter and first intron is indicated by stars. c PCR product of molecular marker TaFlo2-InDel8 discriminated by PAGE in 60 MCC accessions
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To detect polymorphisms in the putative TaFlo2 sequences between high and low TGW accessions, three conserved primers that covered scaffold segments from 793 to 6332 bp were used (Table 1). Polymorphism in TaFlo2-A1 sequences between high and low TGW accessions was observed between 1396 to 1791 bp, while no sequence variation was observed between high and low TGW accessions in TaFlo2-B1 and TaFlo2-D1 (Fig. 2b; Additional file 1: Figure S1). The conserved sequences of TaFlo2-B1 and TaFlo2-D1 in all the higher and lower TGW accessions implicated non-functional nature of these genes. An 8-bp InDel was identified in TaFlo2-A1 sequences from 1396 to 1403 bp which was −17 to −10 bp upstream of the first coding sequence (ATG) at position 1417–1419 bp (Fig. 2b). Five SNPs (G/C, A/G, C/T, C/G and −/T) were observed at 1514, 1538, 1545, 1727 and 1791 bp. From the start codon (ATG), the positions of these five SNPs (G/C, A/G, C/T, C/G and −/T) were in the first intron at 98, 122, 128, 311 and 375 bp, respectively (Fig. 2b). The 8-bp InDel and the five SNPs together formed the two haplotypes designated TaFlo2-A1a and TaFlo2-A1b (Fig. 2b). From the position 1792 to 6332 bp, no polymorphism was observed in the TaFlo2-A1 sequence.
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To characterize the observed TaFlo2-A1 haplotypes in large wheat populations, a molecular marker based on the 8-bp InDel observed in the promoter region was designed and named TaFlo2-Indel8 (Table 1). The forward and reverse primers of TaFlo2-Indel8 are located at −80 bp and 72 bp from the start codon, respectively. The PCR products of TaFlo2-Indel8 in the accessions with or without the 8-bp InDel have lengths of 153 bp and 145 bp, respectively. The bands of 153 bp and 145 bp were easily discriminated by polyacrylamide gel electrophoresis and represented the haplotypes TaFlo2-A1a and TaFlo2-A1b, respectively (Fig. 2c).
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To assign chromosomal locations to TaFlo2 genes, genome-specific primers and a set of Chinese Spring nulli-tetrasomic lines were used. The TaFlo2 genes TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 were found to be located on chromosomes 2A, 2B and 2D (Fig. 3). The cloned sequences of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 showed >99% similarity with 2AL, 2BL and 2DL scaffolds (IWGSC_chr2AL_ab_k71_contigs_longerthan_200_6436403, IWGSC_chr2BL_ab_k71_contigs_longerthan_200_7959819, IWGSC_chr2DL_ab_k71_contigs_longerthan_200_9909583). Further analysis revealed that the TaFlo2-A1 gene was located on deletion bin ‘2AL1–0.85-1.00’.Fig. 3Assignment of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 to wheat chromosomes 2A, 2B and 2D, respectively, by PCR mapping with the genomic DNA of Chinese Spring (CS) and derivative nulli-tetrasomic lines (N2AT2B, N2BT2A and N2DT2A). The size (kb) of DNA markers is shown to the left of the image
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Assignment of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 to wheat chromosomes 2A, 2B and 2D, respectively, by PCR mapping with the genomic DNA of Chinese Spring (CS) and derivative nulli-tetrasomic lines (N2AT2B, N2BT2A and N2DT2A). The size (kb) of DNA markers is shown to the left of the image
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| 95.9 |
To associate TaFlo2-A1 with TGW, two natural populations, the Chinese Micro Core Collection (MCC) and the Pakistani collection, were used. In the MCC, the homozygous TaFlo2-A1a haplotype was found in 219 (83.5%) accessions, whereas the TaFlo2-A1b haplotype was found in 43 (16.5%) accessions. In the Pakistani wheat collection, the number of accessions carrying TaFlo2-A1a and TaFlo2-A1b were 85 (64.6%) and 45 (35.4%), respectively. Both in the MCC and Pakistani collections, the positive haplotype TaFlo2A-A1b had a lower frequency, which showed the scope of improving grain weight.
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The difference in TGW between the haplotypes TaFlo2-A1a and TaFlo2-A1b was statistically significant in both populations (P < 0.05, Table 2). In the MCC, the mean difference in TGW between the groups of accessions having TaFlo2-A1a and TaFlo2-A1b was significant (P ≤ 0.05) across the 3 years of data. The mean differences in TGW between the two haplotypes in 2002, 2005 and 2006 were 7.00 ± 1.12 g, 7.80 ± 1.11 g and 8.40 ± 0.94 g, respectively. Consistent with the results of the MCC, the mean difference in TGW between groups of accessions having TaFlo2-A1a and TaFlo2-A1b was also significant (P ≤ 0.05) across both years of data in the Pakistani wheat collection. The values of the mean difference between the two haplotypes (TaFlo2-A1a and TaFlo2-A1b) in the Pakistani wheat population were 4.50 ± 0.71 g and 5.20 ± 0.72 g for 2009 and 2010, respectively. The phenotypic variance for TGW explained by TaFlo2-A1 haplotypes was 6.19% in 2002, 7.76% in 2005 and 8.37% in 2006 in the MCC. In the Pakistani collection, the phenotypic variance for TGW explained by TaFlo2-A1 haplotypes was 4.42% in 2009 and 5.11% in 2010 (Table 2). Moreover, to determine whether TaFlo2-A1 also affects grain number per spike (GpS), an association analysis was performed for GpS in both populations. However, the differences in GpS between the haplotypes TaFlo2-A1a and TaFlo2-A1b were not significant in either population (P < 0.05, Table 2).Table 2Association of TGW and GpS with TaFlo2-A1 in the Chinese Micro Core Collection and Pakistani wheat collectionsNatural populationsYear (number of accessions) TaFlo2-A1a Mean ± SEa (number of accessions) TaFlo2-A1b Mean ± SE (number of accessions)Mean difference ± SEPVE (%)b TGWTGWGpSTGWGpSTGWGpSChinese Micro Core Collection2002 (137)33.6 ± 0.54(98)50.8 ± 1.2(98)40.6 ± 1.2(39)49.7 ± 1.5(39)7.0 ± 1.1**1.06 ± 2.1ns 6.192005 (169)30.7 ± 0.52(128)43.1 ± 0.8(128)38.5 ± 1.1(41)40.5 ± 1.1(41)7.8 ± 1.1**2.6 ± 1.5 ns 7.762006 (185)32.8 ± 0.43(141)51.4 ± 0.7(141)41.2 ± 0.9(44)48.6 ± 1.2(43)8.4 ± 0.9**2.7 ± 1.5 ns 8.37Pakistani collection2009 (130)40.6 ± 0.43(85)46.6 ± 1.1(85)45.1 ± 0.55(45)44.4–1.8(45)4.5 + 0.71**2.2 ± 1.9 ns 4.422010 (130)40.5 ± 0.47(85)47.8 ± 1.2(85)45.7 ± 0.46(45)44.9 + 1.6(45)5.2 ± 0.72**2.9 ± 2.0 ns 5.11 **indicates significant differences, and ns indicates non-significant differences (P < 0.01; Student’s t-test) among groups carrying different haplotypes aStandard error bPercentage of phenotypic variance explained by association analysis
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Collectively, our data demonstrated that TaFlo2-A1, like the OsFlo2 gene in rice, is associated with TGW in wheat. Furthermore, the lack of association of TaFlo2-A1 with GpS suggests that the high TGW of the examined genotypes is primarily due to the positive haplotype (TaFlo2-A1b) for high TGW instead of loci for low number of kernels per spike and/or low grain yield.
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To observe the contrasting effects of TaFlo2-A1a and TaFlo2-A1b on TGW at the gene expression level in flag leaves and developing grains, two polymorphic accessions were used. The expression level of TaFLO2 was positively correlated with TGW, which is consistent with previous results in rice . The haplotype TaFlo2-A1a, which exhibits low expression levels, represented the group of accessions that have low average TGW, and the haplotype TaFlo2-A1b, which exhibits high expression levels, represented the group of accessions that have high average TGW in both Chinese and Pakistani wheat populations. Quantitative RT-PCR assays showed that for both types of haplotypes, the expression level was maximum in 12-day-old flag leaves followed by expression in developing grains sampled at 5 DAF. However, the expression of both types of haplotypes decreased rapidly in the fertilized caryopses collected at 10, 15, 20 and 25 DAF. The expression level of TaFlo2-A1b was higher than that of TaFlo2-A1a at all tested stages but significantly differed only in flag leaves and developing grains at 5 DAF (Fig. 4a). Furthermore, the expression level was positively correlated in Chinese Spring and three cultivars (Pubing3228, Shannong23, and Zhengmai9405) in developing grains sampled at 5 DAF. The expression level was lowest in Chinese Spring (TGW, 21.3 g) and highest in the cultivar Zhengmai9405 (TGW, 64.1 g) (Fig. 4b). All these cultivars contained the positive haplotype TaFlo2-A1b. Together, these results suggested that the relative expression level of TaFlo2-A1 was highest in flag leaves but started to decrease in developing grains. However, the expression in developing grains at 5 DAF was positively correlated with TGW in cultivars carrying the positive haplotype.Fig. 4 a Expression of TaFlo2-A1 in flag leaves and developing grains. b Expression level of TaFlo2-A1b in cultivars with different TGW values at 5 DAF
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| 100.0 |
The rice OSFLO2 orthologs TaFLO2-A1, TaFLO2-B1 and TaFLO2-D1 were cloned, characterized and found to be located on homeologous chromosome group 2 in wheat. Sequence polymorphism observed in the promoter region of TaFlo2-A1 was associated with TGW. Thus, TaFLO2-A1 is a yield-related gene, and its manipulation could be useful for improving the grain yield potential of bread wheat. Many genes related to TGW and grain yield have been isolated and characterized in wheat using rice-wheat synteny . The success of rice-wheat orthology-based gene cloning in wheat is due to high nucleotide and amino acid similarity between the corresponding orthologous genes. For example, with their respective rice orthologs, TaTGW6 has 71% nucleotide and 68% amino acid similarity [16, 17]; TaGW2 has 98% nucleotide and ~ 87% amino acid similarity ; TaCKX6-D1 has 66% amino acid similarity ; TaGS-D1 has 75.5% cDNA and 72.2% amino acid similarity ; and TaGASR-A1 has 88% amino acid sequence similarity . These data provide a genetic framework for marker-assisted selection (MAS) to pyramid positive alleles for TGW and yield during cultivar development. However, there are still many important genes that have been characterized in rice that are not being used as template for cloning their orthologs in wheat, e.g., OsTB1 , GW5 , GS5 , GW8 , GW7/GL7 [40, 41], and OsAGSW1 . Thus, comparative genomics approaches between rice and wheat will remain useful in discovering orthologs of rice genes in wheat and will continue to enhance our understanding of the genetics of yield potential in wheat.
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| 99.9 |
Map-based cloning using QTL mapping approaches is an important strategy to isolate loci and genes controlling genetic polymorphism . However, progress on map-based cloning in wheat has been relatively slow compared to that in rice, and very few QTLs have been subjected to fine mapping in order to isolate candidate genes, mainly due to the complexity and large genome size of wheat.
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| 99.8 |
In our study, TaFlo2-A1 was found to be associated with TGW and explained from 4.42% (in the Pakistani collection) to 8.37% (in the MCC) of phenotypic variation. The TGW-related QTL identified on 2AL includes ‘Xgwm339-Xbarc311’ in 139 RILs between two hard red spring wheat lines ; QTgw.ipk-2A (Xgwm372) in 111 BC2F3 lines derived from the cross ‘Flair × XX86’ ; QGwt.crc-2A (Xgwm558-Xgwm294) in a double-haploid population generated from the cross ‘RL4452 × AC Domain’ ; QTkw.sdau-2A (Xwmc181a-Xubc840c) in 131 RILs derived from ‘Chuan 35050’ × ‘Shannong 483’ ; QSZ.uaf-2A.1 (Xwmc455) in natural populations of 108 CIMMYT and Pakistani spring wheat accessions ; and QTkw.hwwgr-2AL (Xgwm312–IWA6090) in 127 RILs derived from ‘Ning7840’ × ‘Clark’ . Furthermore, three QTL on 2AL that were stable across five trials were detected in the same MCC (262) used in present study .
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These QTL on 2AL are located between Xgwm71.2/Xgwm558 and Xgwm294, with an interval of 22 cM according to the consensus map of Somers or 16.1 cM according to the ITMI map (http://wheat.pw.usda.gov/ggpages/SSRclub/GeneticPhysical/). From this TGW-QTL-rich region, only one gene, TaCwi-A1, has been isolated thus far between the Xgwm 71.2 and Xbarc15 deletion bin ‘C-2AL1–0.85’, which is adjacent to the centromere . By integrating the information from the ITMI (http://wheat.pw.usda.gov/ggpages/SSRclub/GeneticPhysical/) and ‘Yu 8679 × Jing 411’ SSR + SNP maps, the location of TaFlo2-A1 was inferred on deletion bin ‘2AL1–0.85-1.00’. Hence, the TaFlo2-A1 is a TGW-related gene located on the distal deletion bin of chromosome 2AL, and the molecular marker ‘TaFlo2-InDel8’ is an addition to the kit of wheat breeders for marker-assisted selection.
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The relationship between the number of grains per spike (GpS) and the TGW was traditionally found as being negatively correlated [1–3]. However, the simultaneous selection of favored haplotypes for one plus neutral ones for the other or otherwise favored haplotypes for both traits has changed the correlations from negative to neutral or even positive . Therefore, no significant correlation was observed between TGW and GpS in the collections of Chinese landraces , French winter wheat cultivars or CIMMYT-derived spring cultivars and lines [6, 50], while significantly positive correlations were observed in Chinese modern cultivars .
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| 100.0 |
In many genome-wide association studies (GWAS) for TGW and GpS, many loci were found to be associated with only one of the traits [4, 29, 50]. The favored haplotypes at these loci should increase the phenotypic value of the one trait without negatively affecting the phenotypic value of the others. Thus, selection of such QTL was likely a major factor in changing the relationship between TGW and GpS over time. Similarly, selection of the favored haplotype (TaFlo2-A1b) identified in this study would help to increase TGW without reducing the average GpS in wheat.
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| 100.0 |
TaFlo2-A1, which is represented by two haplotypes in our study, was found to be significantly associated with TGW. Polymorphisms of an 8-bp InDel in the promoter and of five SNPs in the first intron were observed in TaFlo2-A1. The orthologs TaFlo2-B1 and TaFlo2-D1 lacked sequence variations associated with TGW (Fig. 2b). The association analysis of the Chinese Micro Core Collection (MCC) and Pakistani accessions indicated that TaFlo2-A1b was the superior haplotype for TGW. Nevertheless, some accessions that contained TaFlo2-A1a also had high TGW. This is mainly because the effect of TaFlo2-A1 is likely masked by other genes associated with grain size .
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In wheat, TaFlo2-A1 consists of 23 exons that encode 1734 amino acids with four TPR motifs at the positions of 947 to 988, 1032 to 1072, 944 to 1017 and 1028 to 1106 amino acid residues. Furthermore, three mitochondrial CLU domains were also observed at 737–878, 50–162 and 357–401 amino acid residues (Fig. 1a). The rice OsFlo2 gene also consists of 23 exons and encodes 1720 amino acids with three TPR motifs at the positions of 933–966, 975–1008, and 1017–1050 amino acid residues . However, no mitochondrial CLU was reported in rice FLO2 by She et al. . To confirm the absence of mitochondrial CLU in rice FLO2, we BLASTed the rice FLO2 protein (accession: CAE03171) in an NCBI CD search. The results of the rice FLO2 protein (accession: CAE03171) query using the NCBI CD system showed the presence of two mitochondrial CLU domains at the intervals of 52–124 and 721–863 and four TPRs at the intervals of 932–973, 1017–1057, 929–1002 and 1013–1091 amino acid residues (Fig. 1a). Thus, the prediction of wheat and rice FLO2 protein structure using NCBI CD indicates high similarity between their structures.
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Flo2 is considered to be a member of a conserved gene family in plants . TaFlo2-A1 is abundantly expressed in flag leaves and in developing grains at 5 DAF stage, and the expression level of the positive haplotype (TaFlo2-A1b) was higher than that of the negative haplotype (TaFlo2-A1a). The phenomenon of higher expression of the positive TaFlo2 haplotype is consistent with the results for rice OsFlo2, in which the overexpression of the positive haplotype significantly increases grain size . In rice, the flo2 mutation in the promoter and in the open reading frame hinders the expression of genes involved in the synthesis of starch and protein [27, 28]. In rice cultivars that have different genetic backgrounds, some flo2 mutations negatively affect grain quality attributes such as amylose content, grain appearance and physiochemical properties despite maintaining or increasing grain size [27, 28]. Based on these similarities between OsFlo2 and TaFlo2-A1 at the sequence, structure and expression levels, the 8-bp InDel mutation in the TaFlo2-A1 promoter likely regulates grain size by affecting the expression of genes involved in the synthesis of starch and protein in wheat grains. Therefore, the increased expression of TaFlo2-A1 has a positive effect on grain yield but may have a negative effect on some grain quality attributes in wheat, which shall need further investigations.
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| 100.0 |
The Flo2 orthologs in hexaploid wheat were cloned, and TaFlo2-A1 was found to be associated with TGW but not with grain number per spike (GpS) in both the MCC and Pakistani wheat collections. The frequency of TaFlo2-A1b (positive haplotype) was low in commercial wheat cultivars; thus this haplotype can be selected to improve grain weight. This study likely lead to additional investigations to understand the regulatory mechanism of the Flo2 gene in hexaploid wheat. The newly developed molecular marker ‘TaFlo2-InDel8’ could be incorporated into the kit of wheat breeders for use in marker-assisted selection.
|
study
| 100.0 |
Thyroid nodules are common among adults over the age of 60 years, with a prevalence of 50–70% (1, 2). Moreover, the incidence of thyroid cancer in the United States has increased by 211% between 1975 and 2013 (3), due to both an improved detection of small (<2 cm) thyroid nodules by thyroid ultrasonography and a true increase in thyroid cancer incidence (4). Nevertheless, the vast majority (85–95%) of thyroid nodules are benign (5). For this reason, the ability to distinguish between benign and malignant nodules is important in order to spare patients unnecessary diagnostic surgery.
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review
| 99.9 |
Fine needle aspiration (FNA) to facilitate this distinction first became widely practiced in the early 1980s (6), and is widely recognized as the gold standard initial diagnostic procedure in the differential diagnosis of thyroid nodules, being accurate, safe, and cost effective (7, 8). The sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), false-negative (FN) rate, and false-positive (FP) ranges of an FNA are 88.2–97.0%, 47.0–98.2%, 52.0–98.0%, 89.0–96.3%, 0.5–10.0%, and 1.0–7.0%, respectively (9).
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review
| 99.9 |
In 2009, the Bethesda classification system for FNA reporting was introduced by the National Cancer Institute, and recently, revised, included six categories based upon cytopathological features, with an associated malignancy rate and standardized management recommendation for each category (Table 1) (10). FNA reliably establishes the diagnosis of a benign or malignant nodule in 70–80% of all cases (11) and has decreased the proportion of benign nodules unnecessarily resected from 86 to 50% (12). However, 20–30% of FNA cases have indeterminate or suspicious cytological results that include Bethesda III, IV, and V categories (12) and, of these, 6–75% are malignant on final surgical pathology (13, 14). Due to the uncertainty of malignancy in these patients, their management has been challenging, usually including a repeat FNA or a diagnostic lobectomy. For this reason, the need for distinguishing benign from malignant lesions in this subset of thyroid nodules has led to the pursuit of differentiating molecular markers.
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review
| 99.9 |
Interest in achieving this distinction increased in 2002 with the recognition of the oncogenic role of the BRAF V600E mutation in approximately 58–69% of papillary thyroid cancers (PTC) (15, 16). However, genetic testing for BRAF V600E alone for the detection of PTCs is inadequate for clinical decision making due to its low sensitivity of 60% for PTC (17). Indeed, our group first published its use in indeterminate and suspicious thyroid lesions and found it to add minimal clinical value (18). In addition to studying the diagnostic utility of BRAF V600E, numerous studies have investigated the association of BRAF V600E and patient prognosis. However, the correlation between BRAF V600E and clinical features of PTCs has yielded inconsistent results. Some studies report that BRAF V600E is associated with a more advanced phenotype including an increased risk of lymph node metastasis, cancer recurrence, and patient mortality (19–21), while others report no such associations (22). Moreover, thyroid cancer with BRAF V600E and TERT promoter mutations has been associated with worse clinico-pathological outcomes (23, 24). BRAF testing can also be useful in deciding treatment in the setting of known metastatic thyroid cancer. Direct tyrosine kinase inhibitors, such as vemurafenib (25), dabrafenib (26), and sorafenib (27), have been shown to be effective in BRAF V600E metastatic thyroid cancers.
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review
| 99.75 |
Since mutational analysis of single genes has not proven adequate in guiding management decisions in indeterminate or suspicious thyroid nodules, attention turned to using panels of molecular markers. Currently, the most common molecular tests in clinical use are Afirma® Gene Expression Classifier (GEC) and Thyroseq® V2 (28). Introduced in 2011 by Veracyte, the Afirma® GEC has been considered a “rule-out” malignancy test. It includes a 142-gene expression molecular assay and uses microarray technology to measure the mRNA expression profiles to determine whether a thyroid nodule is “suspicious” or “benign.” The test’s primary aim is to spare patients with cytologically indeterminate FNA samples unnecessary diagnostic surgery (29). Among indeterminate/suspicious nodules (Bethesda Type III–V), the test has both a high Se (92%) and high NPV (93%) (30) (Table 2). In contrast, it has a low Sp (52%) and PPV (47%), and cannot accurately identify malignant lesions alone.
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review
| 70.94 |
ThyroSeq® v2, introduced in 2014 by CBL Path, is designed to identify malignant thyroid nodules by next generation sequencing (NGS), detecting 14 thyroid cancer-related genetic mutations, including RAS and BRAF mutations, 42 types of gene fusions associated with thyroid cancer, including PAX8/PPARγ and RET/PTC rearrangements, and mRNA expression levels for 16 genes; it is therefore considered a “rule-in” malignancy test (29). Among Bethesda Type III – IV nodules, the test is marketed as having a high Se, Sp, PPV, and NPV of 90–91%, 92–93%, 77–83%, and 96–97%, respectively, as well as having the ability to stratify risk based on the mutation detected (52, 53) (Table 3).
|
study
| 99.1 |
The 2015 American Thyroid Association (ATA) (60) and the 2016 American Association of Clinical Endocrinologists (AACE) (9) clinical guidelines recommend “considering,” molecular testing for indeterminate nodules. If molecular testing is being considered, ATA recommends that patients “should be counseled regarding the potential benefits and limitations of testing and about the possible uncertainties in the therapeutic and long-term clinical implications of results” (strong recommendation, low-quality evidence) (60). However, long-term outcome data on the use of molecular markers for therapeutic decision-making is currently unavailable. A recent report estimated that standard application of the GEC for all indeterminate thyroid nodules would result in only a 7.2% decrease in thyroidectomy volume (61). Similarly, two studies by our group showed that molecular markers did not significantly affect the surgical decision-making process, where only 7.9–8.4% of patients had altered clinical management as a result of molecular testing (39, 62). For these reasons, patient benefit from molecular marker use in routine clinical practice is likely marginal. Moreover, the AACE 2016 guidelines recommend molecular testing to complement cytologic evaluation in indeterminate nodules (Grade A recommendation), but only when the “results are expected to influence clinical management” (Grade A recommendation) (9). Testing for detection of BRAF, RET/PTC, PAX8/PPRG, and RAS mutations can be considered (Grade B recommendation). Furthermore, with the exception of BRAF V600E, there is insufficient evidence “to recommend in favor of or against the use of mutation testing as a guide to determine the extent of surgery” (Grade A recommendation) (9).
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review
| 99.9 |
Importantly, molecular testing is not recommended in patients with an indeterminate thyroid nodule if other indications for surgery are present such as a nodule greater than 4 cm, compressive symptoms, or personal preference (63). The utility of molecular testing in Bethesda Type V nodules at institutions with a high prevalence of malignancy is low, and provides little additional benefit from a “positive” test result due to the similar PPV as that of a Bethesda Type V FNA result. Moreover, a diagnostic lobectomy would still be recommended in the case of a “negative” result. Finally, a limitation of the current molecular markers is their insufficient data to recommend use among pediatric patients (≤18 years) (64). Until these tests can be validated using this patient population, they cannot be routinely used to complement the indeterminate FNA cytology results.
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review
| 99.9 |
Current published literature regarding Afirma® and Thyroseq® V2 validation studies are summarized in Tables 2 and 3. The data were summarized from the results of a PubMed search for English language studies that reported diagnostic accuracy in observational clinical settings published for GEC and Thyroseq® V2 up to November 30, 2017. References from the retrieved articles were also searched for additional studies. Inclusion criteria included reporting molecular marker diagnostic accuracy or enough information to calculate sensitivity, specificity, NPV, and PPV among Bethesda Type III or IV lesions. All calculations were made using the available published information. To adhere to current clinical guidelines, non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and malignant pathologies were categorized as malignant or “requiring resection.” Of the published literature, only two studies included pediatric patients in their cohort (31, 32).
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review
| 99.9 |
Among Afirma® GEC studies, Se, Sp, PPV, and NPV ranged from 75 to 100%, 5 to 53%, 13 to 100%, and 20 to 100%, respectively. Among Thyroseq® V2 studies, Se, Sp, PPV, and NPV ranged from 40 to 100%, 56 to 93%, 13 to 90%, and 48 to 97%, respectively. Valderrabano et al. report that the wide variation among reported diagnostic values can be explained by different defining characteristics of the study populations such as institutional prevalence of malignancy sample size, Bethesda Type included or combination thereof used, the proportions of each Bethesda Type, the definition of “benign” used in the study, and Hürthle cell (HC) predominance (65). Furthermore, among post-validation studies, the molecular test outcome itself influenced the clinical management.
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review
| 97.9 |
Supporting this, numerous studies have reported a lower specificity or higher false positive rate in GEC tests among indeterminate nodules with HC predominance. Brauner et al. reported 86% (37/43) patients with a GEC suspicious result had unnecessary surgery (46). The authors include a grouped cohort analysis of 122 HC predominant nodules between 2012 and 2014, showing 85 of 95 (89.5%) benign pathologies identified as GEC suspicious (46). Another study by Parajuli et al. reported on GEC’s increase in false positive rate among HC predominant nodules, but did not observe the same increase in Thyroseq® V2 (66). Additional studies assessing Thyroseq®’s performance in HC predominant nodules are lacking.
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review
| 93.7 |
One component of GEC, the Medullary Thyroid Cancer (MTC) Classifier, has been far less studied (Table 4). Among the few existing studies, Se, Sp, PPV, and NPV ranged from 91 to 100%, 100%, 98 to 100%, and 99 to 100%, respectively. Further evaluation of the MTC Classifier is needed to establish its clinical efficacy.
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review
| 99.44 |
Current challenges to the application of molecular markers are fourfold: (A) the recent introduction of the histopathological diagnosis NIFTP, (B) the correlation of genetic mutations within both benign and malignant pathologic diagnoses, (C) the lack of follow-up of molecular marker negative nodules, and (D) the cost-effectiveness of molecular markers.
|
review
| 99.9 |
In March 2015, Nikiforov et al. introduced the new histopathological term NIFTP, previously known as encapsulated follicular variant of papillary thyroid cancer, representing an indolent entity with very low risk of recurrence (70). Major diagnostic characteristics of NIFTP include features of FVPTC, such as a follicular growth pattern and nuclear features of PTC (enlargement, crowding, elongation, irregular contours, grooves, pseudoinclusions, and chromatin clearing), but a lack of vascular or capsular invasion, key features differentiating NIFTP from FVPTC.
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review
| 99.44 |
This new diagnosis represents a dramatic shift in thyroid pathology where an estimated 61% of lesions previously classified as FVPTCs will now be classified as NIFTP, thus decreasing the percentage of “malignancies” on final pathology compared with FNA. On pre-operative cytology, NIFTP is associated with FNA Bethesda Category III, IV, V, or VI in 15, 56, 27, and 2% of tumor samples, respectively (71). As a consequence, this has created a shift in the malignancy rate associated with each Bethesda category. Strickland et al. evaluated a cohort of 655 FNAs with subsequent resection specimens (72). When taking into account the new NIFTP diagnosis, indeterminate, and suspicious FNA samples of Bethesda III, IV, and V had an absolute decrease in rate of malignancy by 17.6, 8.0, and 41.5%, respectively (72). Similarly, Faquin et al. reported an absolute decrease in rate of malignancy in Bethesda III, IV, and V by 13.6, 15.1, and 23.4%, respectively (73).
|
study
| 98.5 |
Despite NIFTP’s extremely low-recurrence rate of 0.6% (two cases), there remains disagreement regarding NIFTP’s true malignant potential (74–80). Despite its likely benign and, at worst, indolent nature, current ATA guidelines recommend lobectomy as definitive therapy for NIFTP. More importantly, however, and, apropos of this review, Afirma® GEC and Thyroseq® V2 validation studies occurred before the establishment of NIFTP as a distinct entity. Because of this one needs to be circumspect about the real utility of these marker panels. And, as a consequence, these molecular diagnostic panels require recalibration to appropriately account for the newly introduced entity, NIFTP; a lesion that should likely not be considered malignant (70, 81, 82).
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review
| 99.9 |
The correlation between presence of mutations and malignancy is imprecise. Among 967 Bethesda Type III, IV, and V nodules, the detection of any mutation conferred the risk of histologic malignancy of 88, 87, and 95%, respectively (83). However, even in nodules with no detected mutations, the malignancy rates were 6, 14, and 28%, respectively. A systematic review by our group included 8,162 patients, of whom 42.5% had benign lesions (84). Among the benign lesions, RAS mutations, RET/PTC rearrangements, and PAX8/PPAR-gamma rearrangements were present up to 48, 68, 55% of the time, respectively. Thus, benign nodules frequently harbor mutations, while some malignant lesions harbor no detected mutations. The combination of the variable and potentially high level of mutations among benign nodules may explain the low specificity and PPV seen in Afirma. Furthermore, their prominence in benign lesions may also challenge the reported PPV of Thyroseq V2.
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study
| 99.9 |
This issue is further complicated when an indolent tumor, such as NIFTP, should be resected according to current ATA guidelines. NIFTP is commonly associated with RAS mutations (8/27, 29.6%) and its diagnosis is incompatible with the presence of BRAF V600E mutations (70, 79). Moreover, Nikiforov et al. describe that 22% (6/27) of NIFTP samples harbor no detectable mutations. To conform to the recommendation that this indolent lesion be resected, new validation studies must show the reliable identification of NIFTP by molecular markers, an unlikely occurrence given the fact that benign lesions also harbor them.
|
study
| 99.06 |
Despite a number of studies exploring the diagnostic value of GEC and Thyroseq® V2, the current published literature includes discrepancies in the follow-up of molecular marker negative nodules and their consideration as a benign pathology (85, 86). Consequently, this may lead to inaccuracies in diagnostic value calculation. A systematic review by Duh et al. (85) highlighted these issues. They included 12 studies and discussed the exclusion of cytologically indeterminate, GEC benign nodules from diagnostic performance calculations (malignant versus benign), leading to an erroneous decrease in Sp and NPV. This is due to the lack of surgical pathology specimens to establish a definitive diagnosis, as well as a lack of follow-up of GEC benign nodules to establish a reference diagnosis. To establish a diagnostic “reference standard” in these nodules that have not undergone surgery and include them in calculations, the authors argue that they should be considered as “true negative” only if no suspicious changes are noted on scheduled interval ultrasound examinations. However, even the natural history of benign thyroid nodules has been described to involve size changes. Indeed, a 5-year prospective study involving 1,567 sonographically or cytologically benign thyroid nodules showed nodule growth in 11.1% (87). However, thyroid cancer was diagnosed in five original nodules (0.3%), of which, only two had an increase in size. Furthermore, a retrospective study ranging from 1 month to 5 years, reported that 39% of the 268 benign thyroid nodules showed at least a 15% change in nodule volume (88). Only one of the 74 repeat-FNAs was malignant. The authors conclude that an increase in nodule volume alone is not a reliable predictor of malignancy.
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review
| 99.9 |
Two studies have described their experience with follow-up of GEC benign nodules on ultrasound. A study by Angel et al. including 56 patients with cytologically indeterminate, GEC benign nodules followed for a median of 13 months exhibited similar growth (≥20% in two dimensions or ≥50% in volume) to cytologically benign nodules (86). Furthermore, in a grouped cohort analysis by Kloos et al. of 443 GEC benign patients in six studies with a reported follow-up time of 7–26 months, 380 patients (85.8%) were spared unnecessary surgery (89). Clearly, the currently available follow-up periods are inadequate for a definitive assessment, and larger, prospective studies are needed to further evaluate the behavior of cytologically indeterminate, molecular marker “negative” thyroid nodules to help guide recommendations for management.
|
review
| 99.8 |
The cost-effectiveness of GEC and Thyroseq® has also been an intense area of research. The cost for GEC and MTC is $4,875 while the cost for Afirma® MTC alone is $975 and that of Afirma® BRAF is $475 (Table 5). The cost of Thyroseq® V2 is $3200 (29). Despite these high costs, insured patient costs are capped at $300 for either GEC or ThyroSeq® V2. Numerous studies have reported on the cost-effectiveness of both GEC (90, 91) and Thyroseq® V2 (92).
|
study
| 97.7 |
A 5-year cost effectiveness study of routine use of GEC reported 74% fewer operations for benign nodules with no increase in untreated cancers. Compared with standard clinical management based only on indeterminate FNA results, GEC may lower overall costs (standard cost $12,172 versus GEC cost $10,719) and improve quality of life for patients (91). Another study reported that to be cost effective, GEC’s specificity would have to be greater than 68% and decrease the number of unnecessary surgeries performed on benign nodules by more 50% (90). However, a study by Yip et al. compared the average cost per patient with Bethesda IV nodules larger than 1 cm extending 10 years from follicular neoplasm diagnosis in three groups: standard of care, GEC, and Thyroseq®. The authors reported a 13% increase in average cost per patient when using GEC at $13,027 (range $12,373–$13,666) when compared with the standard of care $11,505 (range $10,676–$12,347), but a 30% reduction in those using Thyroseq® cost $7,683 (range $7,174–$8,333) (92).
|
review
| 99.7 |
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