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We found that telomere length tends to be synchronously decreased in tumor cells and CAFs. A positive correlation (p < 0.01, r = 0.2) was revealed between the intensities of telomeres in the two cell types (Figure 3D), which implied potential cooperation between them in a cancer‐promoting effect. To confirm the result, the relative telomere length (RTL) of tumor and peritumor tissue pairs (n = 24) as well as isolated CAF and NTF pairs (n = 10) was assessed by qPCR, which indicated consistent results with FISH (supplementary material, Table S2). In brief, the RTL of peritumor tissues (median 0.92; IQR 0.89–1.02) was higher than that of tumor tissues (median 0.45; IQR 0.35–0.55; p < 0.001) (supplementary material, Figure S3A). Likewise, the RTL decreased in CAFs (median 1.50; IQR 1.15–1.64) compared with NTFs (median 2.06; IQR 1.68–2.34; p < 0.01) (supplementary material, Figure S3B). In addition, the RTL of leukocytes isolated from ten patient samples showed no differences between PTILs (median 1.66; IQR 1.05‐1–81) and TILs (median 1.64; IQR 1.02–1.97; p = 0.945) (supplementary material, Figure S3C). The statistics of telomere‐specific FISH variables are shown in the supplementary material, Table S2. Since telomere lengths are maintained by reactivation of telomerase in the majority of human malignancies 27, we also detected the mRNA level of telomerase by real‐time RT‐PCR in 64 HCC patients and found a positive correlation between TERT mRNA level and RTL (p < 0.0001, r = 0.806) (supplementary material, Figure S3D).
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| 100.0 |
We then focused on whether the telomere length had prognostic value and clinical relevance. We first defined samples with lower telomere signals in tumor cells than in paired peritumor liver cells as the shorter group, and higher telomere signals as the longer group (supplementary material, Figure S3E). Likewise, patients were grouped into shorter and longer according to the telomere signals of CAFs and NTFs (supplementary material, Figure S3F). Kaplan–Meier analysis demonstrated that the median OS time was 44.1 and 59.8 months for patients with shorter and longer telomeres in tumor cells, respectively (p < 0.0001, Figure 4A). The median TTR was 41.7 and 53.8 months for patients with shorter and longer telomeres in tumor cells, respectively (p = 0.004, Figure 4B). Similarly, patients with shorter telomeres in CAFs had a poorer prognosis for both OS (44.7 versus 58.3 months, p < 0.001, Figure 4C) and TTR (42.5 versus 52.1 months, p = 0.014, Figure 4D; log‐rank test for each comparison).
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| 100.0 |
Telomere length is associated with survival and recurrence of HCC. (A–F) Kaplan–Meier curves according to telomere signal intensity. (A, B) Tumor cells; (C, D) CAFs; (E, F) the combination of telomere signals in tumor cells and CAFs. P values are based on the log‐rank test. Log‐rank test1: comparing survival and recurrence across all four groups; log‐rank test2: comparing survival and recurrence between patients with shorter/shorter combination and patients with longer/longer combination of telomere length (see text for groupings). RFS, recurrence‐free survival.
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Alternatively, the influence of telomere length was evaluated within intratumor and peritumor areas. Using the median telomere length as the cut‐off (tumor cell median = 11.8, IQR 3.3–22.2; CAF median = 42.9, IQR 26.8–61.4), patients were also classified into shorter and longer groups. Kaplan–Meier analysis demonstrated that the median OS time was 43.2 and 56.4 months for patients with shorter and longer telomeres in tumor cells, respectively (p < 0.0001, supplementary material, Figure S4A). The median TTR was 40.8 and 51.3 months for patients with shorter and longer telomeres in tumor cells, respectively (p = 0.007, supplementary material, Figure S4B). Likewise, we also found that patients with shorter telomeres in CAFs had a significantly poorer OS (44.7 versus 58.3 months, p = 0.008, supplementary material, Figure S4C) and TTR (42.2 versus 50.4 months, p = 0.048, supplementary material, Figure S4D; log‐rank test for each comparison). However, telomere variation in peritumoral liver cells and NTFs showed no prognostic significance.
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| 100.0 |
Furthermore, we evaluated the relationship between patient clinicopathologic features and telomere length in tumor cells or CAFs. Reduced intensity of telomere signals in tumor cells correlated positively with larger tumor size (p < 0.001), the presence of vascular invasion (p = 0.046), poor tumor differentiation (p = 0.041), and advanced tumor stages (p = 0.001). Similarly, shorter telomeres in CAFs were associated with larger tumor size (p = 0.032) and the presence of vascular invasion (p = 0.031) (Table 1). However, no significance was found between telomere variation and other features, such as hepatitis virus, gender, cirrhosis, tumor encapsulation, and tumor number.
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Next, we classified the 257 HCC cases into four groups based on telomere lengths in tumor cells and CAFs. Group I contained cases with longer telomeres in both tumor cells and CAFs; group II included cases with longer telomeres in tumor cells but shorter telomeres in CAFs; group III included cases with shorter telomeres in tumor cells but longer telomeres in CAFs; group IV contained cases with shorter telomeres in both tumor cells and CAFs. Applying Kaplan–Meier analysis, patients in group IV had the shortest OS (median 43.5 months) and TTR (median 41.3 months), whereas patients in group I had the longest OS (median 61.2 months) and TTR (median 54.7 months) (Figure 4E, F). For OS, comparing the four combinations, p < 0.0001; comparing the shorter/shorter combination with the longer/longer combination, p < 0.0001; for TTR, comparing the four combinations, p = 0.019; and comparing the shorter/shorter combination with the longer/longer combination, p = 0.002.
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To illustrate whether the prognostic significance of telomere length was independent of clinical variables, clinicopathologic features showing significance by univariate analysis were adopted as covariates when performing multivariate Cox proportional hazard analyses (Table 2 and supplementary material, Tables S3 and S4). Shortened telomeres in HCC cells were an independent prognostic factor for both reduced overall survival (OS) and time to recurrence (TTR). Patients with shorter telomeres harbored a 2.555‐fold higher risk of death (HR 2.555; 95% CI 1.616–4.039, p < 0.001) and were more likely to suffer from relapse (HR 1.755; 95% CI 1.168–2.637, p = 0.007) than patients with longer telomeres. For telomere length in CAFs, multivariate analysis also revealed significant differences in OS and TTR between the two groups. In addition, the combination of shorter telomere in tumor cells and CAFs was an independent prognostic factor for both OS and TTR by multivariate analysis.
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| 99.94 |
Patients were divided into four groups based on their telomere densities of tumor cells and CAFs: group I, longer telomeres in tumor cells and longer telomeres in CAFs; group II, longer telomeres in tumor cells and shorter telomeres in CAFs; group III, shorter telomeres in tumor cells and longer telomeres in CAFs; group IV, shorter telomeres in tumor cells and shorter telomeres in CAFs. For details, see the supplementary material, Tables S3 and S4.
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| 99.94 |
To validate the clinical significance of telomere length, we analyzed the variation and the prognostic value of telomere length in an independent cohort of 371 HCC patients from TCGA 13. This cohort included 318 HCC patients with paired tumor and blood samples, as well as 53 HCC paired tumor and normal liver tissues (Figure 5A). Telomere length was quantified based on the linear mixed modeling adjusted high‐confidence whole‐genome sequencing (n = 54) and whole‐exome sequencing (n = 317) data. Consistent with our results, 81.94% of 371 samples displayed telomere attrition in tumor tissues (median 0.19; IQR 0.13–0.84) compared with normal controls (median 0.28; IQR 0.23–0.68) (p < 0.001; Figure 5B). Of note, 262 of 318 paired tumor and blood samples (82.38%) showed significant telomere attrition in tumor tissues (median 0.17; IQR 0.13–0.33) compared with the blood samples (median 0.27; IQR 0.22–0.35) (p < 0.001; Figure 5C). Likewise, 79.25% of 53 HCC patients with paired tumor and normal liver tissues had shorter telomeres in tumor (median 1.25; IQR 0.23–3.38) than in paired normal tissues (median 1.63; IQR 0.32–5.21), although no statistically significant difference was detected (p = 0.144; Figure 5D), probably due to the small sample size.
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Telomere length in the TCGA cohort. (A) Telomere lengths in the entire cohort, n = 371, in subset 1 (matched tumor tissues and normal liver tissues, n = 53) and in subset 2 (matched tumor tissues and normal blood samples, n = 318). Numbers at the top and bottom show HCC cases with longer and shorter telomere lengths than paired normal, respectively. (B) Telomere length in matched tumor tissues and normal controls (n = 371). (C) Telomere length in matched tumor tissues and normal blood samples (n = 318). (D) Telomere length in matched tumor tissues and normal liver tissues (n = 53). (E) Kaplan–Meier curves of OS according to telomere length in the subset of 53 patients with tumor tissue/normal liver tissue. (F) Distribution of tumor telomere length according to the presence and absence of TERTp mutations (n = 371). (G) Kaplan–Meier curves of OS according to TERTp mutation status log‐rank test (comparing TERTp mut and TERTp wt). (A–D, F) Error bars indicate interquartile range. NT, normal tissue; TT, tumor tissue; NB, normal blood; mut, mutation; wt, wild type.
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Using the median of telomere length in tumor tissues as the cut‐off value in the 53 cases with paired tumor and normal liver tissues, a significant difference in OS was revealed between patients with shorter and longer telomeres (median 20 versus 31 months, p = 0.039, log‐rank test; Figure 5E). However, no significant difference was seen in the 318 cases with paired tumor and blood samples (median 11 versus 11 months, p = 0.823). This subset of HCC patients received various treatments, including resection (n = 259), radiotherapy (n = 9), and ablation and embolization (n = 31) (19 patients' treatment data were unavailable) 10. Thus, it is possible that variations in treatment selection contribute to the lack of statistical significance for prognosis among the 318 patients.
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| 100.0 |
TERT promoter (TERTp) mutations are associated not only with increased transcription of the catalytic subunit but also with up‐regulated telomerase activity in tumor tissues 13. We evaluated the relationship between TERTp mutation and telomere length in the 371 HCC patients. TERTp mutation correlated positively and significantly with telomere shortening (p = 0.032; Figure 5F). In addition, patients with TERTp mutations showed a shorter OS compared with patients without TERTp mutations (p = 0.007, log‐rank test; Figure 5G). Altogether, the prognostic value of shortened telomeres was validated in the independent cohort of 371 HCC patients.
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| 100.0 |
It is well recognized that telomere dysfunction plays a critical role in cancer initiation and progression, although the exact underlying mechanisms still need in‐depth investigation. Herein, we provided a catalogue of telomere variation in tumor cells and non‐tumor cells within the tumor microenvironment of HCC by telomere‐specific FISH and qPCR. Telomere attrition was found in tumor cells and CAFs, but not in TILs or BDECs. Of note, our data revealed that shortened telomeres in tumor cells or CAFs were independently and significantly associated with poorer postoperative outcome in HCC patients. The results were validated in an independent cohort of 371 HCCs from the TCGA database.
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| 99.94 |
Telomere shortening has been reported in various human cancers using FISH 28, 29, 30, 31. Shortened telomeres were also found in peripheral blood leukocytes (PBLs) in some human cancers using qPCR 32, 33. Similarly, several studies have demonstrated that telomeres are shorter in HCC compared with peritumor tissues measured by Southern blot or qPCR 34, 35, 36. Investigators had also revealed that telomere shortening occurs in chronic liver diseases 35. However, contrasting conclusions also exist. Higher RTL was found to be associated with aggressive tumor behavior and higher grade in HCC mainly using qPCR 37, 38. RTL of PBLs in HCC was found to be the longest, followed by chronic hepatitis B (CHB) and healthy controls as the shortest, as measured by qPCR 37. The discrepancy in these results may result from the differences in detection methods, specimen sources, and therapeutic schedules. In this study, both qPCR and FISH assays confirmed that telomere shortening occurred in tumor cells and CAFs in over 60% of HCCs compared with their normal counterparts, independently validated in the TCGA dataset. More recently, WES and WGS data showed shorter telomeres in tumors than in normal tissues among 29 of 31 cancer types 13. Thus, telomere shortening should be considered as a common phenomenon in human cancers including HCC. In this respect, there is accumulating data that telomere shortening correlates with cancer susceptibility, such as breast cancer, head and neck squamous cell cancer, and gastrointestinal tumors 39, 40, 41.
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| 80.25 |
With regard to the prognostic value of telomere length, previous data were conflicting. For example, short telomeres correlated with poor prognosis in chronic lymphocytic leukemia, colorectal cancer, and prostate cancer 18, but with favorable prognosis in esophageal and breast cancers 42, 43. For HCC, two Chinese studies reported that patients treated with transarterial chemoembolization with longer leukocyte RTL had a shorter survival time 44, 45. In a Korean cohort containing 49 HCC patients, patients with a higher RTL tumor/non‐tumor ratio had a relatively poorer survival 37, while in a US cohort of 126 HCC patients, there was no association between telomere length and patient survival 38. The discrepancy in these results could be attributed to differences in follow‐up duration, baseline clinicopathologic characteristics, therapeutic schedules, and/or study populations. We noted that in the US cohort, the time interval for selection of these multi‐racial cases was 39 years, and detailed treatment data were lacking or changed over the years 35. It is known that dissimilarity of telomere length is found among multi‐racial populations 11. In this study, as the largest integrative analysis of telomere length in HCC to date, 257 Chinese patients who received curative surgical resection were randomly selected within 1 year, most of whom were HBV‐related cases. In addition, the method used in this study can evaluate cancer cells individually, while others evaluated tumor tissues as a whole. Using internal and external validation datasets, we demonstrated that shortened telomeres in tumor cells were independently and significantly associated with poor clinical outcome in HCC patients.
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| 99.94 |
The tumor microenvironment is increasingly recognized as a significant factor in cancer. In this regard, a recent study showed telomere shortening in cancer‐associated stromal cells 18, 46. Here, we comprehensively investigated non‐tumor cells within their local milieu in HCC, that is, CAF/NTF, TIL/NTIL, and T‐BDEC/P‐BDEC pairs. We found significant telomere variation in CAFs, but not in TILs or T‐BDECs. It has been reported that telomere shortening in fibroblasts can lead to an altered pattern of secreted factors, such as increased production of pro‐inflammatory cytokines and matrix‐degrading proteases 47. Therefore, CAFs with shortened telomeres may boost the progression of HCC 24, relevant to our findings that shorter telomere length in CAFs predicted worse prognosis.
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| 100.0 |
Various methods have been applied to measure telomere lengths. Telomere‐specific FISH facilitated our investigation of telomere lengths in distinct cell types within the tumor microenvironment at single‐cell resolution. Notable advantages of this method have been described previously 26, such as reduced nonspecific binding and more specific telomere information. The direct assessment of telomere lengths in fixed tissue samples should be valuable for validating hypotheses involving telomere shortening in tumorigenesis and progression.
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Last but not least, 16 and 22 HCC cases demonstrated markedly heterogeneous telomere lengths in tumor cells and CAFs within individual tumors (termed intratumor cell–cell heterogeneity). This heterogeneity may reflect inconsistent rates of telomere dynamics and variable reactivation of telomerase within subpopulations of cells due to variation in antioxidant protective effects, or differences in telomere preservation/extension mechanisms. Such intratumor heterogeneity was proposed as a major obstacle for curative therapy in HCC 3, 48, inviting new challenges in the molecular understanding of HCC 49.
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| 98.3 |
In conclusion, we revealed significant telomere shortening in HCC cells and CAFs compared with their normal counterparts. More importantly, telomere shortening in cancer cells or CAFs was identified as an independent prognostic indicator for reduced survival and increased recurrence in HCC patients, highlighting the critical role of telomere dysfunction in HCC progression. As such, telomere variation in tumor cells and CAFs within the tumor microenvironment of HCC should be considered as a valuable biomarker in future clinical practice.
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| 100.0 |
LJM and QG conceived and performed most of the experiments. LJM, MD, and ZCW developed the methodology. QG, LZL, AWK, LQD, JYS, XMZ, and YC provided facilities and acquired and managed patients. LJM, QG, and MD analyzed and interpreted data. QG, LJM, XYW, and MD wrote and reviewed the manuscript. LJM, ZBD, LXY, JZ, and JF organized data and constructed databases. QG and XYW supervised the study.
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| 99.94 |
SUPPLEMENTARY MATERIAL ONLINE Supplementary materials and methods Supplementary figure legends Figure S1. Measurement of telomere length by ImageJ and identification of cell types in TMA by H&E Figure S2. Representative FISH images of telomere length variation in HCC cells and non‐tumor cells Figure S3. Relative telomere length detected by qPCR Figure S4. Kaplan–Meier curves of OS and TTR according to the median telomere length Table S1. Patient characteristics Table S2. Descriptive statistics of telomere‐specific FISH (n = 257) Table S3. Univariate and multivariate analysis of factors associated with OS (n = 257) Table S4. Univariate and multivariate analysis of factors associated with TTR (n = 257)
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| 100.0 |
Figure S1. Measurement of telomere length by ImageJ and identification of cell types in TMA by H&E. Representative images of the telomere quantitative process, including the original, conversion, normalization, and gradually measurement, are shown. (A) Four images illustrate the intensity of DAPI signals stained for nuclear DNA (top panels) and the intensity of telomere signals in the same field of vision (bottom panels) in HCC cell lines. (B) Images indicate the DAPI signals stained for nuclear DNA (top panels) and matched telomere signals (bottom panels) in HCC tissues. (C) Representative H&E image staining of tumor cells, peritumor liver cells, NTFs, and CAFs (black arrow indicates fibroblasts). (D) Representative H&E images for illustrating PTILs, TILs, P‐BDECs, and T‐BDECs (original magnification ×40). NTFs = non‐tumoral fibroblasts; CAFs = carcinoma‐associated fibroblasts; PTILs = peritumor infiltrate lymphocytes; TILs = tumor infiltrating lymphocytes (arrowhead indicates lymphocyte); P‐BDECs = peritumor bile duct epithelial cells; T‐BDECs = tumor bile duct epithelial cells (black arrow indicates bile duct epithelial cells).
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Figure S2. Representative FISH images of telomere length variation in HCC cells and non‐tumor cells. (A) Tumor cells; (B) cancer‐associated fibroblasts (CAFs); (C) infiltrative lymphocytes; (D) bile duct epithelial cells (BDECs). White asterisks indicate tumor cells; short white arrows indicate CAFs; long white arrows indicate bile duct epithelial cells and white triangles infiltrative lymphocytes. Left panel: DAPI fluorescence; middle panel, Cy3‐PNA telomere probe fluorescence; right panel, merged images of telomere and DAPI (original magnification ×40).
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| 99.94 |
Figure S3. Relative telomere length detected by qPCR. (A) Shortened RTL was confirmed in tumor compared with adjacent non‐tumor tissues (n = 24). ***p < 0.001. (B) Shortened RTL was validated in CAFs compared with that in NTFs (n = 10). **p < 0.01. CAFs and NTFs were isolated using microbeads as described in the Materials and methods. (C) No significant difference was found in PTILs and TILs (n = 10). PTILs and TILs were isolated using microbeads as described in the Materials and methods. (D) The relative telomere length of tumor cells correlates significantly with the relative TERT mRNA level (n = 64; r = 0.806, p < 0.0001). (E) Representative images showing telomere intensity in paired tumor cells and peritumor liver cells. Case #29: fewer telomere signals in tumor cells than in paired peritumor cells; case #41: stronger telomere signals in tumor cells than in peritumor liver cells. (F) Representative images showing telomere intensity in paired NTFs and CAFs. Case #32: fewer telomere signals in CAFs than in NTFs; case #44: stronger telomere signals in CAFs than in NTFs. Short white arrows indicate NTFs and long white arrows CAFs. Original magnification ×40.
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Figure S4. Kaplan–Meier curves of OS and TTR according to the median telomere length. (A, B) Tumor cells; (C, D) CAFs. Longer telomeres in tumor cells or CAFs were associated with prolonged survival and reduced recurrence. P values were determined by the log‐rank test.
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Dengue virus (DENV) and Zika virus (ZIKV) belong to Flaviviridae family and both diseases affect significantly human health. These viruses are mainly transmitted by Aedes aegypti or albopictus infected mosquitoes. Other routes of infection, including sexual, maternal, and blood transfusions, have been recently reported for ZIKV 1. DENV and ZIKV, like other flaviviruses, are single‐stranded, positive‐sense RNA viruses with a genome of 10.7 kb and two flanking non‐coding regions (5′ NCR and 3′ NCR). The open reading frame encodes one polyprotein with three structural proteins: capsid, pre‐membrane/membrane, and envelope and seven nonstructural proteins: NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5 2. Four serotypes of DENV (DENV‐1 to −4), antigenically distinct have been described 3. In ZIKV, two major lineages, African (Nigeria, Senegal, and Uganda strains) and Asian (Malaysia 1966, Yap State 2007, and Cambodia 2010) have been described based on full genome sequences of the ORFs 4. The four DENV serotypes share approximately 70% amino acid identity with each other, while ZIKV displays an overall 43% homology with DENV (with up to 68% identity for more conserved non‐structural proteins) 1.
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| 97.44 |
Dengue incidence has increased 30‐fold in the last five decades 5. Currently, dengue is endemic in 128 countries, most of them developing nations, affecting approximately 3.97 billion people annually 6. The incidence of dengue increased greatly over the past two decades in Brazil, affecting all regions of the country, except the South 7. Forty years after its discovery, ZIKV reemerged during a 2007 outbreak on Yap Island in Micronesia, continued in 2013 in French Polynesia 8, 9, 10, and in 2014 moved to multiple Pacific islands. At the end of that period, it was introduced to South America 11, 12, 13, 14, 15. In Brazil, the first reports of suspected cases occurred in the Northeast, with a peak during the first quarter of 2015, but it was only confirmed in April 2015. The epidemic continued spreading in May 2016. Since then, autochthonous transmission of ZIKV had been reported in 42 countries and territories in the Region of the Americas 11, 13, 16, 17. Due to lack of reliable official data, Brazilian Ministry of Health estimated the number of cases based on reports of attack rates from other countries.
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| 95.9 |
Dengue infection may be asymptomatic or cause a febrile illness (dengue fever), accompanied by severe headaches, retro‐orbital pain, myalgia, arthralgia, gastro‐intestinal complications, liver inflammation, and skin rashes. When fever subside, patients may develop a more severe life‐threatening condition, characterized by an increase in vascular permeability, plasma leakage and hemorrhagic manifestations, leading to hypovolemic shock 18. Clinical features of ZIKV infection resemble—but are generally milder—those caused by DENV. It could range from asymptomatic infection to a febrile illness characterized by rash, fever, conjunctivitis, arthralgia, and arthritis 10, 14, 19. Unexpectedly, ZIKV outbreak also had a high attack rate and revealed an association with the appearance of Guillain‐Barré syndrome in adults 14, 20 and devastating congenital birth defects, including microcephaly in the developing fetus. It makes of Zika a major emerging public health problem 14, 21, 22.
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| 99.9 |
T cells have an essential role in protection against a variety of infections. Indeed, the development of successful vaccine formulations will require the generation of potent and long‐lasting T‐cell responses. However, there are still no clearly defined immune correlates of protection for these infections 23. The role of T cells during dengue infection is still controversial, with studies supporting either an immunoprotective or immunopathological role (reviewed in 24). Pioneer studies proposed that T cells have a detrimental role during secondary dengue infections in a process termed “original antigenic sin.” Based on this theory, cross‐reactive T cells generated during primary infection, which recognize secondary‐infected DENV serotype with low affinity, are poorly functional but prone to inducing immunopathology 25. Thus, cross‐reactive memory T cells are present in increased numbers and have a low activation threshold. They may outcompete their naïve subsets that have high affinity for secondary‐infected serotype with an overall detrimental outcome for protective immunity 25. Collectively, studies showed that dengue infection elicits a broad specific T cell response that peaks around day 8–10 from fever onset 24, 26. Dengue‐specific CD8+ T cells are present at higher frequencies compared to their CD4+ counterparts and preferentially target non‐structural proteins NS3, NS4b, and NS5, while CD4+ T cells are mainly directed toward the capsid envelope and the secreted protein NS1 27. A comparison of amino acid sequences of DENV and ZIKV CD8+ T cell epitopes point out a high sequence homology between the two viruses and suggests that some of these CD8+ epitopes may also exist in ZIKV 24.
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| 99.9 |
Therefore, we evaluated a cohort of well‐characterized DENV, ZIKV, or DENV/ZIKV‐infected patients and DENV‐exposed healthy donors. Molecular and serological methodologies confirmed all infections. Even without specific in vitro antigenic stimulation, DENV, ZIKV, and DENV/ZIKV infections induced expression of CCR5, CX3CR1, and CXCR3 on CD4+ and CD8+ T cells, indicating an activated status of these cells. However, DENV/ZIKV coinfection decreased the ability of CD4+ T cells to produce IFNγ+, TNF+, TNF+ IFNγ+, and TNF+ IL2+, compared to DENV and ZIKV infections. Finally, a hyporesponsiveness of effector/memory T cells in most of acute patients against DENV NS1 specific antigen might occur due to a clonal exhaustion. We would like to emphasize the potential impact of coinfection on the immune response from a human host.
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| 100.0 |
Blood samples from dengue‐exposed individuals were obtained from discarded routine blood donations’ buffy coats at Clementino Fraga Filho University Hospital (Brazil) during 2013. Because these samples were collected anonymously, they were exempt from informed consent. All four healthy adult donors were seronegative for DENV IgM, seropositive for DENV IgG, negative for RT‐PCR ZIKV and with no clinical history of infections in the past 3 months, suggesting that donors had experienced at least one DENV infections prior to blood donation. Patients’ blood samples were collected between February and March 2016 in ACD Vacutainer and dry tubes. Physicians at Walfrido Arruda Emergency Care Unit, Coronel Antonino (Mato Grosso do Sul, Brazil) evaluated clinical parameters and classified all infected patients according to WHO, 2009 18. All samples were screened for DENV, ZIKV, and CHIKV as a differential diagnosis.
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| 100.0 |
Serum samples were used for all diagnostic tests described below. For diagnosis of suspect dengue cases, DENV IgM Capture DxSelect™ (Focus Diagnostics, CA, USA) and Platelia™ Dengue NS1 Ag ELISA (BioRad Laboratories, CA, USA) were performed. Molecular detection and serotype typing were performed as previously described 28, by real‐time RT‐PCR protocol 29 and Simplexa™ Dengue Real Time RT‐PCR (Focus Diagnostics, Cypress, CA, USA) according to manufactureŕs protocol. We considered a positive diagnosis for DENV the samples positive for DENV qRT‐PCR or/and Dengue NS1 Ag, as stated above. Dengue patients were considered with primary infection provided being positive for IgM, whether negative for IgG or positive for IgG, provided the rate IgM/IgG was greater than 2.0. Dengue cases considered secondary infection presented IgM/IgG rate less than 2.0 18. We considered a positive diagnosis for Zika the samples positive for real‐time RT‐PCR for ZIKV, as described previously 19. DENV/ZIKV coinfected patients presented both criteria mentioned above for DENV and Zika positivity. For diagnosis of the suspected chikungunya cases, it was performed anti‐CHIKV IgM capture ELISA described by CDC 30 and Brazilian Ministry of Health 31, anti‐CHIKV ELISA IgM (Euroimmun, Lubeck, Germany) and molecular RT‐PCR protocol for CHIKV as described previously 32. Patient details are provided in Table 1.
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| 100.0 |
A mammalian recombinant DENV Non‐Structural‐1 (DENV NS1) from all four serotypes was used as stimuli for ELISPOT. This protein was donated by The Native Antigen Company (https://thenativeantigencompany.com/product/dengue-virus-ns1-protein-serotypes-1-4/?doing_wp_cron=1480736436.0465950965881347656250). Phytohemagglutinin (PHA), phorbol 12‐myristate 13‐acetate (PMA), ionomycin, Brefeldin A, and Saponin were supplied by Sigma–Aldrich (St. Louis, MO, USA). Detailed information of all mAbs used in this study is listed in Table S1.
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| 100.0 |
Briefly, peripheral blood mononuclear cells (PBMCs) and plasma were isolated by Ficoll‐Paque™ PLUS density gradient centrifugation (GE Healthcare, Uppsala, Sweden) and frozen in fetal bovine serum (FBS, Gibco, Invitrogen Co, Carlsbad, CA, USA) supplemented with 10% dimethyl sulfoxide (DMSO, Sigma–Aldrich). Cells were thawed on the day of the experiment and were used directly for ex vivo assay as follows.
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| 99.94 |
Cells were stained for surface markers (FITC anti‐CD3, APCCy7 anti‐CD4, AmCyan anti‐CD8, PECy7 anti‐CX3CR1, Pacific Blue anti‐CCR5 and, PerCP anti‐CXCR3) (Table S1) for 30 min, then washed, fixed with 2% paraformaldehyde, and maintained in PBS. The data were collected using BD® FACS ARIA IIu flow cytometer and analyzed using FlowJo 10 software (Tree Star®).
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| 99.9 |
For intracellular cytokine staining (ICS), PBMCs (2 × 105 cells/well) were incubated without stimuli or with PMA (10 ng/mL)/Ionomycin (1 μg/mL) for 2 h at 37°C. Then, Brefeldin A (10 μg/mL) was added to the cultures and incubated for 4 h. Cells were then washed and stained for extracellular markers for 30 min using BV510 anti‐CD3, PECy7 anti‐CD4, and PETexasRed anti‐CD8. After that, cells were washed and fixed with 2% paraformaldehyde. For ICS, cells were blocked with bovine serum albumin (1% BSA, Sigma–Aldrich), permeabilized with saponin (0.05%) and stained with eFluor® 660 anti‐IFNγ, Alexafluor® 700 anti‐TNF, and eFluor® 450 anti‐IL2 (Table S1). Samples were analyzed on BD® FACS ARIA IIu flow cytometer and analyzed using FlowJo 10 software (Tree Star®).
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study
| 99.94 |
IFNγ enzyme‐linked immunosorbent spot (ELISPOT) were performed using DENV‐exposed donors’ or acute patients’ thawed PBMCs that were immediately added to ELISPOT plates. Briefly, 96‐well plates (Multiscreen HTS; Millipore, Burlington, MA, USA) were coated overnight at 4°C with 2.5 μg/mL of capture mouse anti‐human IFNγ antibody (clone 1‐DK1; Mabtech, Nacka Strand, Sweden). The plates were washed with phosphate‐buffered saline (PBS) and blocked with RPMI 1640 (Gibco, Invitrogen Co) supplemented with 10% heat‐inactivated FBS for 1 h at room temperature. Blocking solution was removed, and 2 × 105 PBMCs were plated per well in the presence or absence of NS1 protein from all four DENV serotypes at a concentration of 0.1 μg/mL. After 20–24 h of incubation plates were washed and 1 μg/mL of biotinylated anti‐human IFNγ (clone 7‐B6‐1; Mabtech) was added for 2 h at room temperature. After washing, 100 μL of streptavidin‐alkaline phosphatase (Mabtech) was added and the plates were incubated in the dark for 1 h at room temperature. Then, plates were washed, and 50 μL of alkaline‐phosphatase substrate 5‐bromo‐4‐chloro‐3‐indolyl‐phosphate/nitro blue tetrazolium chloride (BCIP‐NBT); KPL (Gaithersburg, MD, USA) was added. After 10–15 min, colorimetric reaction was stopped with running tap water. Spots were counted using an automated ELISPOT reader (ImmunoSpot® S6UV Ultra, Cleveland, OH, USA). The number of IFNγ‐producing cells was expressed as spot‐forming cells (SFC) relative to 106 PBMCs. Values were calculated by subtracting the number of spots detected in unstimulated control wells. Values were considered positive if they were equal or greater than 10 spots and at least two times above the mean of unstimulated control wells. As a positive control, cells were stimulated with phytohemagglutinin (PHA at 5 μg/mL).
|
study
| 100.0 |
ELISPOT and chemokines receptors analysis were determined using nonparametric two‐tailed Mann–Whitney (Graph Pad Prism ver. 5.0). Multifunctional analysis of cytokine frequencies was performed using Boolean gating in FlowJoX ver. 10.3 and GraphPad Prism ver. 6.0. To compare the frequency of the multifunctional populations among the groups Mann–Whitney test was used. The differences of variables among groups were considered significant when p < 0.05.
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study
| 99.94 |
Peripheral venous blood was obtained from 4 DENV‐acute patients and 1 late‐acute phase disease (with 22 days’ illness), 4 ZIKV‐acute patients and, 7 DENV/ZIKV coinfected acute patients. As shown in Table 1, patient 2 confirmed DENV‐1 infection using Simplexa™ Dengue Real Time RT‐PCR (Ct, Cycle threshold value = 34.6) even after 22 days of onset of symptoms. All four matched healthy donors were negative for DENV IgM, positive for DENV IgG, and negative for RT‐PCR ZIKV, so they were referred here as DENV‐exposed donors. Thirteen patients (76.5%) had dengue during their lifetime, presumed by the positivity for DENV IgG, in which 5 individuals were from DENV group, 3 from ZIKV, and 5 from DENV/ZIKV coinfection group. Most of DENV‐ or DENV/ZIKV patients showed a mild clinical form (non‐warning signals or NWS) and no fatal cases were observed among the cohort studied. In general, symptoms and signs caused by these viruses were similar among the studied groups, and the patients presented typical symptoms such as fever, rash, arthralgia, myalgia, fatigue, headache, and conjunctival hyperemia. No differences were observed in age, gender distribution or days of disease comparing all groups. Similarly, no differences were seen for platelets, leukocytes, and lymphocytes counts among groups. The serotype DENV‐1 was predominant among DENV‐ or DENV/ZIKV‐coinfected patients (80%). Finally, all studied samples were also negative for CHIKV diagnosis. The characteristics of all acute patients are detailed in Table 1.
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study
| 99.94 |
Chemokines and their receptors are key drivers of inflammation. Our goal here was to assess the magnitude of T cell activation by ex vivo expression of chemokine receptors, particularly useful for dissecting T‐cell subsets with distinct migratory capacity and effector function. As shown in Figure 1, expression of ex vivo chemokine receptors such as CCR5, CX3CR1, and CXCR3 were consistently detected on CD4+ and CD8+ T cells from all acute patients and healthy exposed donors. DENV/ZIKV infected individuals presented higher frequencies of CCR5+ or CX3CR1+ compared to exposed donors. Although not significant (p = 0.0571), we observed that DENV or ZIKV infected individuals have a propensity to have high CX3CR1+ frequencies compared to exposed individuals. (Fig. 1b,c). No appreciable differences were detected in CXCR3 expression on CD4+ T cells among all groups (Fig. 1d). Intriguingly, among patients analyzed in DENV group, the lowest values for all chemokine receptors expression on CD4+ T cells were observed for patient 2, in which cells were obtained 22 days post infection, even though viral genome was still detected.
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study
| 100.0 |
Chemokine receptor expression on CD4+ and CD8+ T cell populations in acute DENV, ZIKV, and DENV/ZIKV patients. Peripheral blood mononuclear cells (2 × 105) were stained with mAb against surface markers CD3, CD8, CD4, CCR5, CX3CR1, and CXCR3. The expression of CCR5, CX3CR1, and CXCR3 on CD4+ (a) and CD8+ T cells (e) was showed in contour plots from one representative exposed donor, DENV‐, ZIKV, and DENV/ZIKV‐patients by flow cytometry. Frequency, median, 25th and 75th percentile of CCR5+ (b), CX3CR1+ (c), and CXCR3+ (d) CD4+ T cells from acute viral patients were compared between them and with those in exposed healthy controls. The same strategy was used for CD8+ T cells (f–h). Patient 2 in late acute phase (22 days of illness) was show as open squares. Statistical significance of differences between groups was determined by using two‐tailed Mann–Whitney test, where p < 0.05 were considered significant (*p < 0.05; **p < 0.01).
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study
| 100.0 |
As shown in Figure 2, even without antigenic in vitro stimulation, we observed low, but detectable, frequencies of IFNγ+ (0.1–1.6%, minimum to maximum), TNF+ (0.06–1.3%) and IL2+ (0.3–1.8%) producing T cells from acute patients and in healthy DENV‐exposed donors’ T cells (IFNγ, 0.1–0.6%; TNF, 0.1–0.7%; IL2, 0.5–4.9%).
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study
| 100.0 |
Frequency of IFNγ‐, TNF‐, and IL2‐producing CD4+ and CD8+ T cells in acute DENV, ZIKV, and DENV/ZIKV‐patients and exposed donors. Cultures of 2 × 105 PBMCs were stimulated with PMA/Ionomycin or unstimulated (medium) for 6 h in presence of brefeldin in the last 4 h. Then, cells were stained with mAb against surface markers CD3, CD8, CD4, and mAb against intracellular IFNγ, TNF, and IL2. Frequency of IFNγ, TNF, and IL2 on CD4+ (a) and CD8+ T cells (f) was exhibited in counter plots from one representative exposed donor, DENV‐, ZIKV, and DENV/ZIKV‐patients by flow cytometry for both conditions. Frequency, median, 25th and 75th percentile of IFNγ+ (b), TNF+ (c), and IL2+ (d) CD4+ T cells in unstimulated condition from acute viral patients were compared between them and with those in exposed healthy controls. The same strategy was used (g–i). Patient 2 in late‐acute phase (22 days of illness) was show as open squares. Bars represent the median of frequency of CD4+ T cells (e) and CD8+ T cells (j) expressing each of the seven possible combinations of IFNγ, TNF, and IL2 among the studied groups in unstimulated condition. Statistical significance of differences between groups and comparisons among the multifunctional populations were determined by using two‐tailed Mann–Whitney test and represented by lines. Values of p < 0.05 were considered significant (*p < 0.05; **p < 0.01).
|
study
| 100.0 |
Initially, we evaluated separately the frequency of IFNγ, TNF, IL2 producer CD4+ and CD8+ T lymphocytes, regardless of their simultaneous production (Fig. 2b–d, g–i). First, we observed a trend toward an increased frequency of total IFNγ+CD4+ T cells in DENV (exception of patient 2, open squares) compared to exposed donors. DENV/ZIKV‐patients and exposed healthy donors had similar frequencies of total IFNγ+CD4+ T cells (Fig. 2b). Exposed donors, DENV‐ and ZIKV‐patients had a similar frequency of total TNF+CD4+ T cells, while DENV/ZIKV‐patients had significantly decreased frequencies of total TNF+CD4+ T cells compared to exposed donors and DENV‐patients (Fig. 2c). A trend toward decreased frequencies of total IL2+CD4+ T cells was seen in all acute patients compared to exposed donors (Fig. 2d).
|
study
| 100.0 |
Then, we evaluated the fractions of each multifunctional cell population expressing all three, any combination of two or single production of cytokines (Fig. 2e and j). Among T CD4+ lymphocytes, the least prevalent populations with two functions were IFNγ+TNF+ and IL2+TNF+ in DENV/ZIKV‐patients compared to exposed donors. Higher frequency of IFNγ+TNF+ CD4+ T cells was observed in DENV‐ compared to DENV/ZIKV‐patients. Finally, we observed increased frequency of single IFNγ+CD4+ T cell population in ZIKV‐patients compared to exposed donors (Fig. 2e).
|
study
| 100.0 |
A similar analysis was applied to CD8+ T cells. We detected a significant increase in total IFNγ+CD8+ T cells frequency in DENV/ZIKV‐patients compared to exposed healthy donors. A trend toward increased frequency of total IFNγ+CD8+ T cells was observed in ZIKV and in DENV patients (except for patient 2, open squares) (Fig. 2g). Exposed donors, DENV, ZIKV, and DENV/ZIKV‐patients had similar frequency of total TNF+CD8+ T cells (Fig. 2h). A decreased frequency trend of total IL2+CD8+ T cells, similarly to total IL2+CD4+ T cells, was detected in all acute patients compared to exposed donors (Fig. 2i). Regarding the multifunctional analysis, we only detected a higher frequency of single IFNγ+CD8+ T cells in DENV‐ and DENV/ZIKV‐patients compared to exposed donors (Fig. 2e). Therefore, we suggest that DENV/ZIKV coinfection may influence differently CD4+ and CD8+ T cells responses, an effect mainly observed in the frequencies of CD4+IFNγ+TNF+, CD4+TNF+IL2+, and CD8+ total IFNγ+ populations.
|
study
| 100.0 |
We used DENV NS1 protein to evaluate DENV‐specific response in acute patients because ZIKV and DENV NS1 share 53–56% of amino acid identity 33. Moreover, NS1 has gained considerable attention for early dengue diagnostic tests. All healthy donors and 75% of acute patients in our cohort had indications of previous dengue, thus it was expected that they would be great responders of NS1 DENV. Considering this, we assessed DENV‐specific T cell response against a pool of NS1 from all four serotypes in PBMCs isolated from acute patients from DENV‐exposed donors by IFNγ ELISPOT assay (Fig. 3a).
|
study
| 100.0 |
DENV‐specific cells targeting DENV 1–4 NS1 protein in acute DENV, ZIKV, and DENV/ZIKV‐patients, and donors experiencing dengue. Peripheral blood mononuclear cells (2 × 105 in 0.1 mL) were incubated with recombinant mammalian (rm) NS1 (0.1 μg/mL) derived from four different DENV serotypes or PHA for 20 h and IFNγ production was measured by ELISPOT assay. (a) Representative IFNγ production from one representative exposed donor, DENV, ZIKV, and DENV/ZIKV‐patients are shown against rmNS1. (b) The values obtained of IFNγ production, expressed as spot‐forming cells (SFC) relative to 106 PBMC, is shown for the rmNS1 and PHA were compared between them and with those in exposed healthy controls. Graphs show the median, 25th and 75th percentile from acute‐patients and DENV‐exposed ZIKV naïve donors. Statistical significance was determined by using the two‐tailed Mann–Whitney test, where p < 0.05 were considered significant (*p < 0.05; **p < 0.01).
|
study
| 100.0 |
Our initial objective was to compare NS1 DENV‐specific memory response from dengue‐exposed donors with dengue‐infected individuals. Our data indicate that DENV NS1 memory response had the highest frequencies and magnitude in healthy dengue‐exposed donors compared to those with active DENV infection. Among DENV ingle‐infected patients, the 22‐days DENV patient 2 showed the best response to NS1, indicating that latter phases of dengue could be a better time point for evaluating specific cell responses through ELISPOT. Our second goal was to determine whether active ZIKV infection could affect the NS1 DENV‐specific memory response in two different situations: in DENV‐exposed patients or in those who have current ZIKV or DENV/ZIKV infections. Our data showed that DENV NS1 was not able to induce a response in any acute active ZIKV‐patients, even the samples being positive for Dengue IgG ELISA test. Two out five DENV/ZIKV‐patients responded with above 50 IFNγ SFC following DENV NS1 stimulation, while the other three responded with below 20 IFNγ SFC after stimulation (Fig. 3b). Finally, the magnitude of IFNγ SFC response was not statistically different among the groups of acute patients. In order to understand the specificity of this response, we intend to evaluate healthy donors exposed to Zika in the future.
|
study
| 100.0 |
Although T lymphocytes are not infected by DENV and appear not to be infected by ZIKV 34, the impact of each one and of the DENV/ZIKV coinfection seem to affect their function. To address this investigation, we attempted to analyze some features of CD4+ and CD8+ T cell response in PBMC from patients in a cohort of DENV only, ZIKV only and DENV/ZIKV coinfected patients. Our work began with extensive fieldwork in the Midwest region of Brazil in 2016. There, 134 suspected cases of dengue or zika with an acute febrile illness were recruited, including those with by at least two of the signs and symptoms (headache, myalgia or arthralgia, rash, pruritus, retro‐orbital pain, and prostration). Methods of serology and molecular biology have been designed to diagnose the etiologic agent. Of the suspected cases, 6% of them confirmed ZIKV alone, 50% DENV, 22% were coinfected DENV/ZIKV, the others chikungunya, coinfections or not confirmed cases. At this point we realize that we did not have a larger number of samples with zika alone (Azeredo et al. data in submission). Therefore, we analyzed small numbers of individuals in each studied group to match ZIKV‐infected patients’ number, even though aware of the possible impact on dispersion of variables such as age, gender, and others because of a reduced number of donors. Despite that, we could report for the first time some aspects of DENV/ZIKV coinfection and compare then to DENV and ZIKV only infections, as well as healthy donors. Herein, our data reported from 17 well‐characterized patients infected by DENV, ZIKV or DENV/ZIKV and 4 healthy donors.
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study
| 99.94 |
Our research evaluated the expression of chemokine receptors on T cells. Chemokine receptors have been useful for dissecting T‐cell subsets with distinct migratory capacity and effector function 35. We assessed the effector as well as memory T cells by an increased expression of CCR5, CX3CR1, or CXCR3, in contrast to their T naïve precursors. CCR5 and CXCR3 are closely linked to Th1 function on activated CD4+, memory/activated CD8+ T cells, and NK cells 36, 37, 38. Our data confirmed an increased expression of CCR5 on T cells from acute dengue patients 39, 40. CCR5 expression would be promoting an enhanced T cell recruitment into the liver, a hypothesis that was corroborated by a high frequency of CCL5+ cells in hepatic tissue from dengue fatal cases 40. It is widely accepted that CCR5 is part of host's immune response in the dengue, its role, mediating the traffic of immune cells from blood to target tissues or acting directly on the antiviral response, is still unknown. A recent study demonstrated CX3CR1‐based transcriptome and proteome‐profiling defined a core signature of memory CD8+ T cells with cytotoxic effector function 41. Highly polarized CX3CR1+ cytotoxic CD4+ T cells was specifically expanded in exposed donors and, in particular, in those donors carrying an HLA allele associated with protection from severe dengue 42. By the fact that an increased frequency of CD4 and CD8 T cells expressing CX3CR1 in patients with DENV and, for the first time, in patients with ZIKV and DENV/ZIKV, our data could indicate a potential cytotoxic capacity of T cells from these in acute patients. The protective role of CXCR3 against DENV infection has been demonstrated in experimental models since CXCR3−/− mice infected by DENV presented a higher mortality rates than the wild‐type mice. Moreover, brains of CXCR3−/− mice showed higher viral loads and quantitatively fewer CD8+ T cells than those of wild‐type mice 43. We hypothesize that an increase in the frequency CD4+ and CD8+ T cells expressing chemokine receptors would contribute to regulate virus progression through a precise control of inflammatory cells targeting the affected tissue. Thus, chemokine receptors would play a more immunoprotective role once T cells could exert an antiviral, effector, cytotoxic, and migratory activities.
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study
| 99.94 |
The frequency of IFNγ‐producing T cells has been the most used parameter to assess an effective immune or vaccine‐induced response. Similarly to IFNγ, TNF is capable of mediating the killing of a variety of intracellular infectious viruses, bacteria, and parasites 44, 45. Although IL2 has little direct effector function, it promotes the expansion of CD4+ and CD8+ T cells, amplifying any potential effector T cell responses. Importantly, it has been demonstrated that frequency of cytokine‐producing T cells alone is not sufficient to predict protection. To provide prospective evidence of the quality of T cell response, vis‐à‐vis multifunctional T cells is required 23. Regarding dengue, compelling evidence of the importance of multifunctional T‐cells to mediate protection was found in Flavivirus‐naïve volunteers vaccinated with live, attenuated DENV‐1 vaccine, rDEN1Δ30. The authors observed that multifunctional T cells increased significantly in non‐viremic subjects tended to have a higher frequency of multifunctional T cells compared to viremic subjects. Therefore, the presence of multifunctional T cells following rDEN1Δ30 vaccine safely and effectively prompt immune responses associated with control of infection and protection from re‐infection 46.
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review
| 67.56 |
Finally, we studied the magnitude of IFNγ response to DENV NS1. Gideon's team did not observe differences in IFNγ induction between peptide pools and recombinant proteins in overnight ELISPOT assay using PBMC from the same donors 47. A higher magnitude of IFNγ response to DENV NS1 was found in experienced dengue donors, but a hyporesponsiveness was found in any acute viruses, even experiencing dengue. In 2001, our group described a reduced frequency of CD4+ and CD8+ T lymphocytes and a poor ability for T‐lymphocyte proliferation in response to mitogens and dengue antigens in acute DENV‐infected patients, but re‐established in convalescence phase 48. Another study found that in vitro exposure to DENV‐2 of T lymphocytes isolated from healthy donors reduces the lymphoproliferative capacity in response to mitogen, suggesting that DENV‐2 can inhibit T cell‐mediated immunity, bypassing monocytes and dendritic cells, classical DENV cell targets 49.
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study
| 100.0 |
Briefly, mono‐ and coinfections similarly induced expression of CCR5, CX3CR1, and CXCR3 on CD4+ and CD8+ T cells. This could promote functional and migratory similarities of these cells, regardless of the infecting virus. However, DENV/ZIKV coinfection decreased the ability of CD4+ T cells to produce IFNγ+, TNF+, TNF+IFNγ+, and TNF+IL2+, compared to monoinfections. We suppose two antagonistic scenarios: coinfected people are more immunocompromised than those monoinfected, so coinfection would be the worst scenario for those individuals. Another example of potential adverse effects of this immunosuppression is, that a reduced capacity to activate CD4+IFNγ+TNF+ and CD4+TNF+IL2+ T cell populations might interfere with future development of specific or cross‐reactive memory lymphocytes, leading to a weak response in a subsequent encounter to other potential arbovirus. In the other scenario, coinfected people have a less inflammatory milieu than monoinfected people. This could mean that a reduced inflammatory condition could avoid harmful effects like cytokine storm. Nevertheless, once the clinical outcome of the patients was similar, it was not possible to associate the symptoms and clinical signs with the immune profile of each group.
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study
| 99.94 |
JBCdS, JCSA, ELdA, and LMdOP performed experiments, reviewed data, and planned the experimental strategy. MG collected data using a FACS ARIA BD flow cytometer. ABdP, JBCdS, TMAdSEP, LBdS, PCGN, and MdRQL performed all diagnostic tests. RVdC, JBCdS, TMAdS, LBdS, and ELdA collected samples and provided clinical information. JBCdS, JCSA, and LMdOP conceived and directed the study, and wrote the manuscript. All authors have critically read and edited the manuscript.
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other
| 99.94 |
As the field of oral pathology expands in Africa, currently emerging omics-based molecular techniques are, in principle, poised to improve the oral disease diagnosis and treatment [1–4]. Despite the vast ground covered by the advances in molecular and omics-based technologies in the developed world, there remains a gap in the uptake and application of these methods in developing countries due to existing militating factors. In order for Africa not be left behind in all these highly beneficial technologies, innovation and maximization of the existing infrastructure is highly required. A sine qua non to research and innovative discoveries is good record keeping; which remains sub-optimally practiced in most developing economies [5–9]. For example, it has been historically recorded that two previous presidents of the United States of America (Ulysses Simpson Grant & Stephen Grover Cleveland) were diagnosed with oral cancer [10, 11]; however such information is lacking on how many African presidents have had oral cancer in the past. In fact, history has it that some celebrities like Sigmund Freud, the father of modern psycho-analysis; Giacomo Puccini, a famous opera composer; and Sammy Davis Jr., a leading entertainer, died of head and neck cancer .
|
review
| 99.9 |
Accurate capture of disease burden in Africa would provide impetus for addressing prevalent early diagnosis and treatment monitoring bottlenecks. The emergence of high throughput omics based sciences in the post genomic era concomitantly attracts the application of computational biology and bioinformatics to elucidate various omics based data [4, 12–14]. Most challenges preventing the implementation of omics-based molecular approaches in routine diagnostic oral pathology in Africa are human resources and infrastructure. Low educational levels; lack of disease registries; poor funding and fiscal policies; lack of biospecimen repositories; and political unrests, inter alia; have significantly impeded research activities in many countries in Africa [15, 16].
|
review
| 99.2 |
Basic biomedical laboratory sciences provides the scientific foundation of clinical practice and supports the use of novel scientific discoveries to justify clinical decision making . However, there remains widespread disconnect between clinicians and basic medical scientists [18–21]. Granted the importance of the art of medicine and clinical practice , there is a significant necessity to embrace evidence based science in the era of precision medicine. This point was alluded to over a century ago by the Flexner Report of 1910 , which was employed to transform the medical education model in America by establishing integrated biomedical training systems as the gold standard. A shortage of needed infrastructure and manpower has fixated a significant proportion of medical research efforts in Africa on bedside practice; albeit medical practice from ancient Egyptian papyri has been documented for various aliment as early as around 2000 B.C [24–28]. Indeed, evidence of various primary and metastatic cancers has been found by paleopathological and archeological examination of Egyptian mummies [29–34]. Despite the antiquity of medical practice in Africa relative to other regions of the world, there still exists a paucity of application of novel omics-based approaches to routine diagnostic medical sciences.
|
review
| 99.9 |
Inequalities in social determinants of health in low and middle income countries such as those in sub-Saharan Africa constitutes a huge challenge to health care access [35–42]. In addition, there are ample evidences of the existence of ethnic-based disparities in health risks profile in many countries [43–47]. The prospect of using omics-based techniques under such daunting conditions in resource-limited settings is dismal. To set up the right atmosphere for routine diagnostic and therapeutic application of these merging omics-based techniques, systems have to be instituted to address these prevalent disparities in healthcare practice and access in sub-Saharan Africa.
|
review
| 99.75 |
Globally, these are interesting times to apply omics technologies in order to improve human health. Unfortunately, the African continent is way behind in terms of the financial and institutional commitment required to successfully implement a genomics program for research and clinical use. Genomics is a multi-million dollar endeavor with far reaching implications for a healthy and productive continent . It will unravel health risk, accelerate drug discoveries and motivate lifestyles [49, 50]. Of the sub-Sahara African nations, only South Africa is investing in genomics technologies despite the success stories reported in developed countries around the world. For instance, Nigeria is a country of about 200 million people and there is no genome center despite the training and collaborative opportunities presented through the Human Heredity and Health in Africa (H3Africa) Initiative (h3africa.org/) , which facilitates genomic researches and manpower development across Africa. Other factors that discourage the application of molecular research and emerging omics-based techniques to routine diagnostic oral pathology practice in Africa includes: poor access to research journals and conferences ; lack of needed skilled manpower [53, 54]; oral pathologist-to-population ratio (including workload and interest) [53, 55]; lack of well-equipped infrastructure such as laboratories and clinics [56–58]; poor internet facilities ; unstable electricity/power supply ; unfavorable health policies [61–63]; poor collaborative team science [64, 65]; knowledge gaps/educational levels [66–68]; war/local unrest ; lack of disease registries ; data/record gap in hospitals units [70, 71]; and religious/cultural beliefs , inter alia.
|
review
| 99.8 |
The mortality rate of oral cancer is extremely challenging and depends mainly on the staging of disease at diagnosis and commencement of treatment. Even, though the 5-year survival rate for first stage oral cancer cases can be as high as 80%, the 5-year survival rate for advanced stages (III/IV) are dismally low (20%); Up to 50% of oral cancer cases globally are only detected in late stages . Hence the use of emerging diagnostic approaches to improve early diagnosis and prompt commencement of treatment is key in reducing the high mortality of oral cancer.
|
review
| 99.9 |
A fundamental goal of surgical pathology is to distinguish benign lesions from malignant ones [74, 75]. It is also equally important to be able to differentiate between indolent and aggressive tumors . The use of hematoxylin and eosin (H&E) staining as well as the use of various special stains; backed with good clinicopathologic acumen, has partly improved the diagnosis of disease, albeit this is sometimes with limited diagnostic accuracy [77, 78]. The introduction of immunohistochemistry into diagnostic pathology significantly improved the confirmation of diagnoses, where morphological differential diagnosis using H&E presented a dilemma. However, immunohistochemistry has been cautiously used and interpreted after its limitations (such as variable antibody reactivity, background staining, poor quantitation, and subjective interpretation) became apparent [78–85]. Another layer of complexity is added to the diagnostic dilemma by intratumour heterogeneity and inter-biopsy heterogeneity, which presupposes that multiple cancer molecular signals can be detected in various sampled regions [86, 87]. This alludes to the notion that molecular classification of disease may be complimentary and in some situations more important than conventional histopathological diagnosis based on H&E staining [88–92]. The advent of various omics based molecular approaches as described hereafter, can potentially improve the diagnosis and monitoring of disease, particularly in the diagnostic grey areas. The benefit of using multiple high throughput techniques in a complementary and integrated manner would no doubt benefit personalized/precision medicine and the field of diagnostic oral pathology immensely (Fig. 1).Fig. 1Impact of omics based molecular approaches on personalized/precision medicine and the field of diagnostic oral pathology
|
review
| 99.9 |
The field of molecular biology has undergone significant evolution in the post-genomic era [93–97]. With the emergence of omics-based approaches, research capabilities have expanded from low to medium throughput biochemistry, to interrogation of the full complement of biomolecules in a high throughput manner. Further, biological molecule have now been characterized in a manner that was hitherto not possible . A few relevant high throughput omics based methods are described hereafter as they relate to the field of oral pathology and cancer.
|
review
| 99.9 |
To improve the field of molecular medicine, traditional biochemistry has employed various approaches such as: electrophoresis; Western, Northern, and Southern—blotting techniques for protein, RNA and DNA respectively ; enzyme-linked immunosorbent assay (ELISA) ; gene silencing and RNA interference ; gene cloning ; conventional and real-time qualitative polymerase chain reaction (PCR) ; karyotyping & fluorescence in situ hybridization (FISH) ; Comparative genomic hybridization (CGH) ; and chromosomal/cytogenetic analysis . However, many of these techniques are limited because they are low to medium throughput in their capabilities. These techniques have benefitted the field of oral pathology by enabling the identification of molecular markers of various diseases. For example, cytogenetic alterations such as copy number gain of 16q, 8q and loss 3p, 8p, 9p, 4q, 5q, 13q have been found to be biomarkers for premalignant oral lesions; while copy number gain of 3q, 8q, 9q, 20q, 7p, 11q13, 5p and copy number loss of 3p, 9q, 21q, 5q, 13q, 18q, 8p have been found to characterize oral squamous cell carcinoma [106–109]. Molecular alterations such as microsatellite instability (MSI), abnormal mismatch repair protein (MMR) proteins MLH1, PMS2, MSH2, MSH6, and loss of heterozygosity (LOH) of 9p21, 3p14 have been found to characterize premalignant oral lesions [106–108, 110, 111]; while perturbation of p53, EGFR/STAT, COX-2, NF-κB, VEGF, TGF-β/Ras pathways have been found in oral squamous cell carcinoma [112–114]. Identified potential biomarkers of metastatic oral squamous cell carcinoma includes E-cadherin, integrins, matrix metalloproteinases (MMPs), IL-8, chemokine receptor 7 and EGFR . Various fusion oncogenes have been used as potential biomarkers of salivary gland tumours; such as MYB-NF1B t(6:9)(q22-23:p23-24) for Adenoid cystic carcinoma ; CRTC1-MAML2 t(11:19)(q21-22:p13) for low or intermediate grade Mucoepidermoid carcinoma ; ETV6-NTRK3 for Mammary analogue secretory Carcinoma [116, 117]; PLAG & HMGA2 for Pleomorphic adenoma [118, 119]; EWSR1-POU5F1 t(6:22)(p21:q12) for high grade Mucopeidermoid carcinoma ; EWSR1-ATF1 t(12:22)(q15:q12) for low grade hyalinizing clear cell carcinoma ; NUT-BRD4 t(15:19)(q14:p13.1) for NUT midline carcinoma [121, 122]; and MECT1-MAML2 for low grade Mucoepidermoid carcinoma . Considering the impact of tradition molecular biology advances on diagnosis of tumors in the head and neck region, it is plausible that emerging high throughput omics based techniques would even bring greater breakthroughs to diagnostic oral pathology practice.
|
review
| 99.9 |
Prior to the completion of the human genome project (which costed billions of dollars and lasted over a decade), only short fragments of DNA could be sequenced using methods such as polymerase chain reaction and hybrid capture [124, 125]. However, with the advent of massive parallel sequencing (also known as Next Generation Sequencing), millions of DNA fragments can now be sequenced even without prior knowledge of the sequence . With an exponential reduction in the cost of sequencing, Next Generation Sequencing (NGS) has improved the utility of various omics field in understanding disease specific genomes .
|
review
| 99.9 |
The field of genomics and sequencing also owes its huge success to the development of the array technologies, which were initially fabricated for high throughput genomic interrogate the transcriptional levels of thousands of genes in a single experiment [126, 127]. This technology has made it possible to evaluate pathophysiological gene expression patterns in cells and tissues; as well as to identify drug targets in tissues . Different types of arrays and their application for various biological functions have been discussed in details elsewhere [126–128].
|
review
| 99.9 |
In addition, emerging technological advances have provided the unique opportunity to interrogate biological and genomic complexity to the single-cell resolution. This potentially provides high throughput omics based data which helps to delineate tissue heterogeneity from a bulk population of cells; as well as diversity in complex microbial ecosystems . Although technically challenging, single cell technology has been applied both to genomic and epigenomic analyses of diseases [129, 130]; as well as to drug discovery and development .
|
review
| 99.9 |
In tandem with the ever-increasing amount of data generated from high throughput data, a great number of omics fields have emerged . These omics fields have provided access to systems level interpretation of molecular processes. However these techniques requires robust bioinformatics and computational infrastructure to de-convolute and integrate the emerging data for clinical utility . The -omics suffix indicate the analysis of the full complement of a specific biomolecule; as well as its characterization, interaction or analysis . For example, the measurement of the full complement of protein in a cell, tissue, body fluid, or any biological system is known as proteomics; and this analogy applied to all other biomolecules such as lipids (lipidomics), genes (genomics), gene transcripts (transcriptomics), metabolites (metabolomics), etc. It has been notably demonstrated by Garcia et al. , that such omics based techniques would benefit personalized oral healthcare immensely. Examples of promising application of different omics based approaches are described below:
|
review
| 99.9 |
Genomics techniques provide a genome-wide access to genetic information and presents a robust opportunity to interrogate cancer biology in a high throughput manner. Genomics information have been used to develop databases that have enhanced our knowledge of the cancer genome expression greatly . Although, genomics has attained moderate success in target oncogene and tumor suppressor gene identification; there remains significant challenges in the transformation of these targets into therapies that would improve cancer patient management . Application of genomics to oral cancer diagnosis in diagnostic oral pathology would be greatly improved by advances in the field of dental and craniofacial informatics . Genomic alterations have been identified for leukoplakia as well as in the process of sequential oral tumorigenesis ; providing molecular information that were hitherto unavailable.
|
review
| 99.9 |
Differential transcriptomics profiling of oropharyngeal cancers based on human papilloma virus (HPV) status has been shown to provide reliable molecular signature to stratify these subtypes of head and neck cancer . Thus permitting high throughput analyses of gene transcript and drawing of biological inferences on HPV-related oral cancer.
|
study
| 99.94 |
Genome-wide association studies (GWAS) is an unbiased statistical approach used to identify common single nucleotide polymorphisms across the genome that are associated with complex traits. Since the early 2000s when it was first used, there have been over 2000 published GWAS studies . The success of GWAS is largely dependent on the coverage of the genotyping panel, the minor allele frequency of SNPs in the investigated population and on clearly defined phenotypes. GWAS has been used to identify many novel susceptibility loci for complex traits including oral cancers .
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review
| 99.75 |
Deep sequencing, massively paralleled sequencing or next generation sequencing (NGS) is a novel DNA or RNA sequencing technology that has transformed genomic research . As opposed to the Sanger sequencing, this is a high throughput method that can be used to sequence the complete human genome within a day . Significant progress in the sequencing research has led to a reduction in its per megabase cost, number of produced sequence reads per run as well as the genome diversity coverage; which helps to adequately elucidate complex phenotypes of diseases [142, 144]. NGS has been applied to understand oncogenic mutations in oral diseases such as ameloblastomas [145, 146]. Using this method, it was discovered that mutations in the SMO gene encoding smoothened protein was commoner in maxillary ameloblastomas, while BRAF V600E mutations were commoner in mandibular ameloblastomas . This has far reaching implications for the application of personalized medicine to the management of ameloblastomas . Molecular heterogeneity in head and neck cancers has also been elucidated using NGS methods .
|
review
| 99.9 |
There is an increasing confidence in our ability to understand the impact of identified coding variations. In addition, we are able to sequencing the entire protein coding regions in the genome also known as exome sequencing. Therefore, exome sequencing appears to be a promising omics tool for the rapid identification of functional variations. These thus provide an opportunity for small molecule development through pharmacogenomics and also serve as information for counselling to at-risk families with diseases. In recent times, exome sequencing was used to identify novel oral cancer genes and loci [148–151].
|
study
| 72.75 |
The study of stable and often heritable changes in gene expression patterns that are not caused by changes in the DNA sequence is known as epigenetics . Two of the most well characterized epigenetic alterations are histone modification and DNA methylation . Beyond the genome, the complete set of epigenetic modifications to the cellular DNA or histones (epigenome) are known to play an important role in the etiology of diseases . The epigenome plays a pivotal role in the regulation of chromatin activity and therefore affect DNA repair and gene expression . Epigenomic alterations have been established in obesity, diabetes and cancer [154–156]. Adequate evidence exists, that epigenetic dysregulations have been implicated in the pathogenesis of oral and oropharyngeal cancers [157–161]; hence it is plausible that epigenomic analyses would provide better insight into oral carcinogenesis.
|
review
| 99.9 |
Bacterial genetics of the human oral microbiota has been interrogated using a combination of transcriptomics and microbiomics techniques [162–164]. This techniques is highly beneficial for understanding infective dental pathologies such as periodontitis, osteomyelitis and caries; and can be potentially applied to non-infective diseases such as cancer as well [165, 166].
|
review
| 99.8 |
Mass spectrometry-based quantitative proteomics analysis has revealed an enhanced interferon-related signaling pathway for oral cancer cells in vitro, using labeled-mass spectrometry coupled to a high performance liquid chromatography (HPLC) system . Such findings required further study into the significance of interferon in the pathogenesis of oral squamous cell carcinoma and may serve as a basis for development of targeted therapies and potential biomarkers for oral cancer.
|
study
| 99.94 |
One of the major breakthroughs in the field of lipidomics that could potentially revolutionize the field of surgical oral pathology is the fast, real-time mass spectrometry based identification of surgical margin of tissues intraoperatively with the use of the i-knife . This technique diagnosed cancer margin accurately in a more reliable and unbiased manner using lipidomic signatures that differentiated between tumor and normal areas . This could potentially eliminate the intraoperative waiting time while sending surgical specimen for frozen section tumor margin analysis.
|
review
| 94.8 |
The science of metabolomics looks at the differential signature of metabolites in biological pathways in a high throughput manner. Tiziani et al. identified metabolomics signatures for early diagnosis or oral cancers using 1H-nuclear magnetic resonance (NMR) spectroscopy methods. This method could potentially be used for routine early clinical diagnosis of various oral cancers. Recently, the push for reliable non-invasive timely diagnosis of cancer has directed research interest in the area of exhaled breath analysis for early detection. Breathomics is a branch of metabolomics that measures the total amount of volatile organic compounds (VOCs) in exhaled air . Volatile and nonvolatile organic components of the exhaled air are relevant indicator of metabolic status for clinical diagnosis and monitoring purposes . Various metabolic processes in the body produce VOCs that are released into the blood and transported to the lung where they are passed to the airway and exhaled. Acquisition and measurement of unique VOCs that may indicate occurrence of chronic inflammation and/or oxidative stress are potential biomarkers for early cancer detection . This may be a plausible non-invasive early-stage cancer screening tool and may be potentially applied to the detection of head and neck cancers.
|
review
| 99.9 |
Nanotechnology is an emerging, highly beneficial, multidisciplinary area of research that deals with atomic and molecular levels of matter. Some clinical trials are currently directed at demonstrating the theranostic efficacy of nanomaterials against chronic diseases such as cancer . Today, nanomedicine plays a significant role in diagnostic sciences, gene therapy, drug delivery systems, as well as in screening of populations [174, 175]. Both the field of medicine and dentistry have benefitted reasonably from therapeutic and diagnostic applications of nanomaterials . Several forms of nanomaterials and nanotechnology methods have been used for the diagnosis and treatment of oral cancer. A few such modalities that have benefitted the field of oral pathology and oral cancer diagnosis and treatment are Surface Enhanced Raman Spectroscopy (SERS) [177, 178], composite organic–inorganic nanoparticles (COIN) [179, 180] and quantum dots (QD) [177, 181]. For example, Raman difference spectroscopy has been demonstrated as a non-invasive method for oral cancer diagnosis . There is no doubt however; that these and many other nanotechnology approaches would continue to enhance the application omics approaches to personalized medicine and oral pathology.
|
review
| 99.9 |
Molecular imaging is a highly beneficial tool with the capacity to improve every aspects of cancer care. It is an in vivo imaging-based characterization and measurement of the key biomolecules and molecular events that are basic to the malignant or aberrant state . Prior to the emergence of molecular imaging, a number of “gold standard” scientific approaches (such as ViziLite, VELscope, Trimira and OralCDx, etc.) aimed at oral lesion detection were fraught with inconsistencies during standard routine head and neck examinations [184–186]. However, the establishment of integrated MRI/PET has improved the consistency and effectiveness of earlier stage cancer detection . Molecular imaging such as positron emission tomography (PET) often integrated with cross sectional imaging in the form of PET/computed tomography (PET/CT), PET/magnetic resonance imaging (MRI)/MR spectroscopic imaging (MRSI), as well as optical imaging; play a vital role in cancer detection, staging and assessment of treatment response. The optical imaging is mostly performed with the radiotracer 18F-fluoro-2-deoxy-d-glucose [FDG], integrated with cross-sectional imaging in the form of PET/computed tomography (PET/CT) . PET has been said to be the leading molecular imaging approach in a clinical environment [189–191]. PET imaging methods have been successful in both staging of diverse cancers and assessment of response of tumors to therapy [192, 193]. Several authors have shown a significantly higher level of sialic acid in oral cancer patients when compared to normal patients [194–196]. The recent discovery of molecular imaging-based individualized potential molecular tumor fingerprint has facilitated a rapid and effective development of theranostic drugs for novel treatment algorithms [197, 198]. In another study, the efficacy of fluorescence imaging using topically applied lectin-fluorophore conjugates as compared to conventional tissue autofluorescence in distinguishing tumor from normal tissues was also investigated . The results revealed that the changes in glycosylation could differentiate normal from cancerous tissues in the oral cavity with high SNRs . This is potentially a non-invasive screening method for premalignant and malignant oral mucosal tumors; and as a method for defining surgical margins and monitoring cellular changes over time. To further validate this approach for oral cancer screening, in vivo testing in a larger clinical cohort is needed. Not least, Nanobodies have also been considered as highly beneficial agent in molecular imaging of cancers, due to its rapid accumulation in tumors, homogenous distribution; efficient blood clearance, high specificity, safety, high tumor signal-to-background ratios; as well as ease of conjugation to several kinds of imaging techniques .
|
review
| 99.9 |
Several advances have emerged in precision and personalized medicine which could potentially benefit the field of oral pathology vis-à-vis molecular oral cancer diagnostics and therapy. The advent of microfluidic technology [201, 202] has made it possible to establish a rapid multistage, multi-technique technology known as Lab-on a-chip [202, 203]. This has permitted a high turnover of requested laboratory investigations during clinical diagnosis and therapy. This technology and those mentioned above have rapidly improved the development of point-of-care (POC) diagnostic tools [204–206]. These developments may have potential applications for oral pathology and cancer management. It is also clear that stem cell science has improved the field of dentistry and oral pathology. Somatic stem cells can be harvested from patients and reprogrammed to form patient-specific induced pluripotent stem (iPS) cells . These iPS cells can be used for recombination and regenerative production of maxillofacial structures for transplantation and maxillofacial structure reconstruction . On the other hand, subpopulations of cancer stems cells have been previously identified in head and neck cancers, by the application of stem cell science . Such in-depth knowledge can also provide future stem cell-based targeted therapies against head and neck cancers . Quantum medicine approaches such as quantum tunneling has been previously used in understanding genetic mutations in cancers . A quantum mechanical approach is now being considered in the understanding of the evolution of cancers [211, 212]. There is no doubt that these emerging molecular concepts are poised to play a major role in oral pathology and cancer diagnosis; as well as therapies in the foreseeable future.
|
review
| 99.9 |
Considering the immense potential benefits of omics based approaches in the field of oral pathology and cancer diagnosis in developing African regions, the authors make the following recommendations:Government focus should be directed at funding Infrastructure (bridging the record gap); funding researchers and supporting research training (bridging the knowledge gap).As custodians of various tissue specimens, pathologists must take the lead (and must not be passive) in the application of omics based molecular techniques to routine diagnostic services. Advanced certification and annual remedial courses are also recommended.With favorable health policy change, omics based molecular approaches should be integrated into routine clinical practice, taking dutiful quality assurance (internal and external) measures.There should be private sector/non-governmental organization (NGO) participation to make the task of integration of omics into oral pathology effective.Reimbursement policy for oral pathologist who are willing to practice omics science must be favorable.Legislative initiative must be available to pass this concept into law.Scarce resources must be maximized (using mobile phones, internet, etc. to improve the practice of omics based approaches in oral pathology),Viable collaborative team science established (sharing ideas, research, equipment and meetings) must be established locally, regionally, continentally and globally.Research and Educational Networks (RENs) must be established using a trans/inter/multidisciplinary approachOmics-based science and personalized medicine topics should be integrated into the undergraduate and postgraduate medical/dental training curriculumThere are many freely available online platforms that tremendously facilitate omics based techniques, such as the Gene Expression Ominbus (GEO) ; National Center for Biotechnology Information (NCBI) ; and The Cancer Genome Atlas (TCGA) . Such platforms offer great opportunities to develop knowledge in the omics field and researchers should be well enlightened about this.
|
review
| 99.9 |
As custodians of various tissue specimens, pathologists must take the lead (and must not be passive) in the application of omics based molecular techniques to routine diagnostic services. Advanced certification and annual remedial courses are also recommended.
|
other
| 99.94 |
There are many freely available online platforms that tremendously facilitate omics based techniques, such as the Gene Expression Ominbus (GEO) ; National Center for Biotechnology Information (NCBI) ; and The Cancer Genome Atlas (TCGA) . Such platforms offer great opportunities to develop knowledge in the omics field and researchers should be well enlightened about this.
|
other
| 99.9 |
In the light of the aforementioned recommendations and the tremendous burden of cancer in Africa, healthcare goals needs to capture the most reliable and cost effective methods for screening and early diagnosis of disease. It is unfortunate that despite the fact that up to 80% of the burden of cancer is found in the low and middle income countries (LMIC), it only receives about 5% of the global spending on cancer . Africa has to piggy-back and emulate already existing transformative “training-the-trainer” systems in the Western world such as the: Training Residents in Genomics program (TRIG) and the Resident in Service Examination (RISE) practiced in the Americas and Western Europe [217, 218]. These programs exposes trainees to hands-on omics based molecular approaches during their residency program; and thus increases their confidence in requesting for and interpretation of such investigations. Considering that the cost of genomics investigation is on the decline and that we have entered into the $1000 genome era [219, 220], the pertinent question for African oral pathologists is “are you ready for a genome-related clinical visits (with respect to their genetic risk for oral pathologies) by patients?” It is plausible that future histopathological reports would proceed beyond classic histological findings to morpho-molecular findings ; and a good knowledge of omics based molecular techniques is a sine qua non for an astute diagnostician. Emphasis should be placed on the multimodality approaches for omics based diagnostic oral oncological practices. Although all these techniques improve our knowledge of disease biology in an in-depth manner, they are most likely to play an adjunctive/supportive role rather than replacing existing pathological techniques in its application for improving detection and prognostic evaluation of head and neck cancer.
|
review
| 99.9 |
Inducing angiogenesis is one of the hallmarks of cancer . Tumor-associated neovasculature is important for delivering nutrients and oxygen to growing tumors, and also playing key roles in multi-aspect of tumor biology, including tumor dissemination/metastasis , metabolic deregulation and cancer stem cell maintenance [4, 5]. For its fundamental role in tumor growth and progression, angiogenesis has become an appealing target in cancer treatment.
|
review
| 99.9 |
Angiogenesis is a complex process by which new blood vessels are formed from pre-existing ones by sprouting, remodeling and expansion of primary vascular networks . In normal conditions, following this morphogenesis, the vasculature becomes largely quiescent. However, within tumors, an “angiogenic switch” is always activated, causing continuous generation of new vessels . The “angiogenic switch” is governed by pro-angiogenic and anti-angiogenic signals elicited by tumor cells or tumor microenvironment [8, 9]. When pro-angiogenic signals are activated or anti-angiogenic signals are inhibited, the “angiogenic switch” is turned on. Understanding the regulation of tumor angiogenesis is critical to developing therapeutic strategies against cancer.
|
review
| 99.56 |
MicroRNAs (miRNAs) are small non-coding RNAs , that negatively regulate gene expression at post-transcriptional level. Through sequence-specific interaction with the 3′-untranslated region (UTR) of target mRNA, miRNAs suppress gene expression via transcript degradation or inhibition of protein translation. To date, miRNAs have been reported to play key roles in diverse biological processes of cancer, including tumor growth, metastasis, angiogenesis and drug resistance [11–14]. Extensive studies have shown that miRNAs could modulate the function of endothelial cells (ECs) via non-cell-autonomous (genetic and epigenetic alterations in a cell affect the phenotypes of other cells through changing microenvironment or intercellular interaction) and cell-autonomous (genetic and epigenetic alterations in a cell affect the cell’s own phenotypes) manner during tumor angiogenesis. MiRNAs in tumor cells regulate the expression of pro- or anti-angiogenic factors, thereby modulating the proliferation and migration of ECs in a paracrine manner. Endothelial miRNAs regulate the response of ECs to multiple angiogenic stimuli mainly by targeting growth factor receptors and signaling molecules autonomously. Recently, extracellular vesicles (EVs) are emerging as mediators of intercellular communication . Cancer cell-derived miRNA-containing EVs could be transferred to ECs where they induce pro-angiogenic effects. Importantly, several miRNAs have been shown to serve as predictive biomarkers for anti-angiogenic therapy response, especially as non-invasive biomarkers in the circulation. Furthermore, with the development of RNA delivery technology, miRNA-based interventions may act as novel therapeutic means to target tumor angiogenesis.
|
review
| 99.9 |
In our review, we will summarize the non-cell-autonomous and cell-autonomous roles of miRNAs, as well as EV-transferred miRNAs in the regulation of tumor angiogenesis. Moreover, we highlight the clinical implications of miRNAs as predictive biomarkers for anti-angiogenic therapy response in both tissue and circulation, and several miRNA delivery approaches that have been applied to suppress angiogenesis in vivo.
|
review
| 99.9 |
Angiogenesis is under the control of pro-angiogenic and anti-angiogenic factors . Tumor cells could produce and secrete such factors into surrounding environment to promote vessel growth. Endogenous activators and inhibitors are frequently targeted in tumor cells by miRNAs, which thereby regulate angiogenesis in a non-cell-autonomous manner (Table 1).Table 1MiRNAs involved in non-cell-autonomous regulation of tumor angiogenesis in tumor cellsTargetsmiRNAsExpression in tumor cellsRefVEGFmiR-20, miR-29b, miR-93, miR-126, miR-190, miR-195, miR-200, miR-203, miR-497, miR-503, miR-638, miR-27b, miR-128down[21–42]VEGF inducers HIF-1miR-22, miR-107, miR-519cdown[43–45] HIF-2miR-145down PI3K/AKT pathwaymiR-26a, miR-145down[47, 48] mTOR pathwaymiR-18a, miR-128, miR-145, miR-218down[49–52] IGF1R pathwaymiR-126, miR-181b, miR-148a, miR-152down[53–55]VEGF upstream TFs STAT3miR-874down Bmi-1miR-16down E2F3miR-34adown NF90miR-590-5pdownVEGF suppressor PTENmiR-21up E-cadherinmiR-9upVEGF independent factors FGFmiR-503down HDGFmiR-214, miR-497down[62, 63] angiogeninmiR-409-3pdown angiopoietinmiR-204down MMPsmiR-9, miR-26b-5p, miR-98, miR-181a-5pDown[66–69] TSP-1miR-17-92 cluster, miR-182, miR-194, miR-467up[75–78]IGF1R Insulin-like growth factor I receptor, Bmi-1 B-cell-specific Moloney murine leukemia virus integration site 1, E2F3 E2F transcription factor 3, NF90 Nuclear factor 90, TSP-1 thrombospondin-1, HDGF hepatoma-derived growth factor
|
review
| 97.8 |
The most predominant growth factor of angiogenesis is VEGF, consisting of VEGF-A/B/C/D and placental growth factor (PlGF) [16, 17]. VEGF-A (also known as VEGF) is a potent trigger for angiogenesis by signaling through VEGF receptor-2 (VEGFR-2) . While VEGF-B specifically regulate the embryonic angiogenesis of myocardial tissue and VEGF-C/D mainly participates in the genesis and maintenance of lymphatic vessels. Therefore, among the VEGF factors, VEGF-A is most widely studied in the regulation of tumor angiogenesis .
|
review
| 99.7 |
MiR-20 , miR-29b , miR-93 [23–25], miR-126 [26–30], miR-190 , miR-195 , miR-200 [33, 34], miR-203 , miR-497 [36, 37], miR-503 and miR-638 have been experimentally shown to directly target the 3’UTR region of VEGF-A mRNA in different types of cancer and subsequently impairing the pro-angiogenesis signaling of VEGF/VEGFR-2 in endothelial cells. These miRNAs are generally downregulated in cancer. Recently, the role of VEGF-C in initiating and potentiating neo-angiogenesis has been uncovered . MiR-27b and miR-128 functioned as inhibitor of tumor progression and angiogenesis through targeting VEGF-C [41, 42].
|
review
| 99.7 |
Apart from directly targeting VEGF, a handful of miRNAs regulate VEGF-dependent tumor angiogenesis by targeting VEGF inducers, such as HIF pathway (miR-22 , miR-107 , miR-519c , miR-145 ), PI3K/AKT pathway (miR-26a , miR-145 ), mTOR pathway (miR-18a , miR-128 , miR-145 , miR-218 ), IGF1R pathway (miR-126 , miR-181b , miR-148a , miR-152 ) and VEGF upstream transcription factors (STAT3: miR-874 , Bmi-1: miR-16 , E2F3: miR-34a , NF90: miR-590-5p ). Conversely, miRNAs targeting the suppressors of these VEGF inducers promoted tumor angiogenesis. Overexpression of miR-21 induced tumor angiogenesis by targeting PTEN, which in turn activated AKT and ERK signaling and finally enhanced HIF-1α and VEGF expression in prostate cancer cells . E-cadherin downregulation by miR-9 activated β-catenin signaling, in turn upregulating VEGF-A expression and promoting tumor angiogenesis .
|
study
| 99.94 |
Several other growth factors also play positive roles in tumor angiogenesis. MiRNAs have been reported to target these pro-angiogenic factors in tumor cells, such as FGF (miR-503 ), HDGF (miR-214 , miR-497 ), angiogenin (miR-409-3p ), angiopoietin (miR-204 ), and MMPs (miR-9 , miR-26b-5p , miR-98 , miR-181a-5p ). Moreover, some miRNAs were shown to simultaneously target more than one angiogenic factors. MiR-190 significantly suppressed tumor angiogenesis via targeting VEGF, HGF and IGF1, thus altering the local microenvironment and subsequently regulating neighboring ECs .
|
study
| 99.94 |
Angiogenesis is regulated by the balance between pro- and anti-angiogenic factors. Angiostatin, endostatin and thrombospondin-1 (TSP-1) are endogenous anti-angiogenic factors [70–72], among which TSP-1 is most well-known. TSP-1 binds to its receptor CD36 on the surface of ECs, as well as by binding to β1-integrins, leading to cell apoptosis . In addition, TSP-1 inhibits the activity of MMP-9, thereby hindering the release of VEGF-A sequestered in extracellular matrix . Several miRNAs, including miR-17-92 cluster , miR-182 , miR-194 and miR-467 , have been reported to target TSP-1 in tumor cells, thus decreasing TSP-1 secretion and promoting tumor angiogenesis.
|
review
| 72.3 |
The importance of miRNAs in ECs was demonstrated by the silencing of Dicer, an enzyme responsible for miRNA maturation. Knockdown of Dicer in ECs inhibited cell proliferation, migration and cord formation , indicating that miRNAs are important in the function of ECs. Many studies have shown that miRNAs in ECs regulate the cellular response to angiogenic factors by targeting surface receptors and signaling molecules (Table 2).Table 2MiRNAs involved in cell-autonomous regulation of tumor angiogenesis in ECsmiRNAsTargetsFunctionRefpro-angiogenesismiR-132p120RasGAPpromote ECs proliferation, tube formationmiR-130aGAX, HOXA5promote ECs proliferation, migration, tube formationmiR-146aBRCA1promote ECs proliferation, migration, tube formationanti-angiogenesismiR-128VEGFR-2inhibit ECs tube formationmiR-497VEGFR-2induce ECs apoptosismiR-296HGSinhibit ECs tube formationmiR-125bVE-cadherininhibit ECs tube formationmiR-34aE2F3, SIRT1, survivin, CDK4inhibit ECs proliferation, migration and tube formationmiR-126ADMinhibit ECs migration and tube formationHSG hepatocyte growth factor-regulated tyrosine kinase substrate, BRCA1 breast cancer 1, p120RasGAP Ras p21 protein activator 1, SIRT1 sirtuin 1, ADM adrenomedullin
|
review
| 99.56 |
Tyrosine kinase receptors VEGFR and platelet-derived growth factor receptor (PDGFR) are primarily located on the surface of ECs [80, 81]. The binding of VEGF-A to VEGFR-2 and PDGF to PDGFR initiates a cascade of signals that result in endothelial cell proliferation and migration . Several miRNAs have been reported to directly target these receptors in ECs, such as miR-128 and miR-497 , blocking their downstream signaling to inhibit tumor angiogenesis. On the contrary, miRNAs targeting the suppressors of these receptors promoted tumor angiogenesis. MiR-296 contributed to angiogenesis by directly targeting the hepatocyte growth factor-regulated tyrosine kinase substrate (HGS) mRNA, thereby reducing HGS-mediated degradation of VEGFR-2 and PDGFRβ in ECs . MiR-146a enhanced tumor angiogenesis by targeting BRCA1 which conferred a transcriptional repression on PDGFRA .
|
study
| 86.8 |
MiRNAs have been implicated as key modulators of angiogenic signal transduction pathways. MiR-125b suppressed tube formation of ECs by inhibiting VE-cadherin translation . MiR-34a was shown to inhibit the proliferation, migration and tube formation of ECs by downregulating a number of key proteins including E2F3, SIRT1, survivin and CDK4 . Conversely, miRNAs promote angiogenesis by targeting negative regulators in angiogenic signaling pathways. MiR-132 was highly expressed in the endothelium of human tumors and hemangiomas but was undetectable in normal endothelium. MiR-132 induced Ras activation via suppressing p120RasGAP expression, thus promoting neovascularization . MiR-130a is a positive regulator of ECs largely through targeting anti-angiogenic homeobox gene GAX and HOXA5 . Notably, miR-126 has been well known as an endothelial-specific miRNA and has pro-angiogenic action during embryo development . However, a recent study illustrated an anti-angiogenic role of miR-126 during tumor angiogenesis by targeting a pro-angiogenic gene adrenomedullin (ADM) . This study suggests that the role of miRNAs may vary depending on microenvironment.
|
study
| 99.1 |
The discovery of extracellular vesicles (EVs) represents an exciting area of research that offers novel mechanisms for intercellular communication. EVs, generally including exosomes (typically 30–100 nm) and microparticles or microvesicles (typically 100 nm-1 μm), are small secretory vesicles that contain proteins, DNA, and coding and non-coding RNAs . EVs can be released from various cell types under physiological and pathological conditions and transfer their cargo to proximal or distal cells . In many published articles, the collective term “microvesicles” was used for all the EVs between 30 and 1000 nm in- diameter.
|
review
| 99.9 |
Recent evidence has demonstrated that cancer cell-derived EVs can be transferred to ECs where they induce pro-angiogenic effects. Glioblastoma cells released exosomes containing mRNA, miRNAs and angiogenic proteins. These exosomes were taken up by brain microvascular endothelial cells and modulated angiogenesis . A set of pro-angiogenic mRNAs and miRNAs were enriched in the microvesicles of CD105-positive renal cancer stem cells, therefore conferring an activated angiogenic phenotype to ECs .
|
study
| 99.94 |
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