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Fig. 4Reversed metabolite fold-change direction in discovery- and validation cohorts. a Score scatter plot for the initial OPLS-DA model of 4578 metabolite features in the discovery cohort (Fig. 1, step 2b). Blue dots represent PDAC samples (scores, n = 44); white dots represent CP samples (n = 23); t1 on the x-axis, first component; to1 on the y-axis, first of two orthogonal components. Model parameters: CV-groups, 7; R2X(cum) 0.39; Q2(cum) 0.22; CV-ANOVA p = 0.02. The model was used to select 259 features for further analysis. b Score scatter plot for the OPLS-DA model in the validation cohort based on the 19 metabolites remaining from the discovery cohort (Fig. 1, step 4b). Orange dots represent PDAC samples (n = 20); white dots represent CP samples (n = 31); to1 on the y-axis, first (and only) orthogonal component. Model parameters: CV-groups, 7; R2X(cum) 0.648; Q2(cum) 0.699; CV-ANOVA p = 1.7E-11. c Loading (metabolite) scatter plot for the discovery cohort OPLS-DA model. The phospholipids are situated to the right of the vertical line, close to the dummy CP variable, indicating that they are down-regulated in PDAC compared to CP. d Loading scatter plot for the validation cohort OPLS-DA model. The phospholipids are situated to the left of the vertical line, close to the dummy PDAC variable; hence they are up-regulated in PDAC compared to CP. Based on this reversal of their fold-change directions, the 14 phospholipids were excluded from the final metabolite marker panel
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| 100.0 |
Reversed metabolite fold-change direction in discovery- and validation cohorts. a Score scatter plot for the initial OPLS-DA model of 4578 metabolite features in the discovery cohort (Fig. 1, step 2b). Blue dots represent PDAC samples (scores, n = 44); white dots represent CP samples (n = 23); t1 on the x-axis, first component; to1 on the y-axis, first of two orthogonal components. Model parameters: CV-groups, 7; R2X(cum) 0.39; Q2(cum) 0.22; CV-ANOVA p = 0.02. The model was used to select 259 features for further analysis. b Score scatter plot for the OPLS-DA model in the validation cohort based on the 19 metabolites remaining from the discovery cohort (Fig. 1, step 4b). Orange dots represent PDAC samples (n = 20); white dots represent CP samples (n = 31); to1 on the y-axis, first (and only) orthogonal component. Model parameters: CV-groups, 7; R2X(cum) 0.648; Q2(cum) 0.699; CV-ANOVA p = 1.7E-11. c Loading (metabolite) scatter plot for the discovery cohort OPLS-DA model. The phospholipids are situated to the right of the vertical line, close to the dummy CP variable, indicating that they are down-regulated in PDAC compared to CP. d Loading scatter plot for the validation cohort OPLS-DA model. The phospholipids are situated to the left of the vertical line, close to the dummy PDAC variable; hence they are up-regulated in PDAC compared to CP. Based on this reversal of their fold-change directions, the 14 phospholipids were excluded from the final metabolite marker panel
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After exclusion of the phospholipids the five metabolites N-palmitoyl glutamic acid, glycocholic acid, hexanoylcarnitine, chenodeoxyglycocholate and PAGN remained. They were used to build a refined validation cohort OPLS-DA model (Fig. 5a, b) to evaluate their discriminatory power in the absence of phospholipids. The predictive ability of the refined model as indicated by the Q2(cum) value was 0.513, i.e. approximately 50% of samples were correctly classified, and the R2X(cum) value was 0.736. The statistical significance of the model as indicated by cross-validated ANOVA was p = 8.2E−07.
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Fig. 5A marker panel of five metabolites discriminates PDAC and CP. a Score scatter plot for the refined OPLS-DA model of the five discriminative metabolites with consistent fold-change directions in the validation cohort (Fig. 1, step 4b and 5). Orange dots represent PDAC samples (n = 20); white dots represent CP samples (n = 31); t1 on the x-axis, first component; to1 on the y-axis, first (and only) orthogonal component. Model parameters: CV-groups, 5; R2X(cum) 0.736; Q2(cum) 0.513; CV-ANOVA p = 8.2E-07. b Corresponding loading scatter plot. All five metabolites in the marker panel show increased levels in PDAC compared to CP
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A marker panel of five metabolites discriminates PDAC and CP. a Score scatter plot for the refined OPLS-DA model of the five discriminative metabolites with consistent fold-change directions in the validation cohort (Fig. 1, step 4b and 5). Orange dots represent PDAC samples (n = 20); white dots represent CP samples (n = 31); t1 on the x-axis, first component; to1 on the y-axis, first (and only) orthogonal component. Model parameters: CV-groups, 5; R2X(cum) 0.736; Q2(cum) 0.513; CV-ANOVA p = 8.2E-07. b Corresponding loading scatter plot. All five metabolites in the marker panel show increased levels in PDAC compared to CP
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| 100.0 |
The PDAC incidence rate is expected to increase worldwide over the next years (Rahib et al. 2014), making the need for improved diagnostic tools even more acute. One group at risk of PDAC development is CP patients (Pinho et al. 2014) who would clearly benefit from the discovery of novel markers for PDAC diagnosis.
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| 99.6 |
Any preclinical biomarker study at the discovery stage should include an inflammatory control of the target organ to increase the chance of identifying disease-specific markers (Chechlinska et al. 2010; Lindahl et al. 2016). Here, CP serves as an inflammatory control of the pancreas for PDAC-specific marker discovery. In addition, CP is a risk factor for PDAC development and the two diseases share several inflammatory parameters. It is therefore imperative to identify PDAC-unique markers specific for the discrimination of PDAC and CP.
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| 85.4 |
In the present study, we have compared the metabolic profiles of PDAC and CP in blood in two independent cohorts using untargeted LC-MS. The fact that both cohorts did not consist of either serum or plasma is a drawback of the study. However, that they represent completely independent patients strengthens the validity of the proposed biomarkers. Previous reports comparing the metabolite profiles of serum and plasma samples have found good correlation between the two sample matrices (Denery et al. 2011; Yu et al. 2011; Ishikawa et al. 2014). We have identified three single discriminative metabolites as well as a five-metabolite panel of markers, since a marker panel can increase specificity and sensitivity compared to single discriminative metabolites (Wang et al. 2011; Wingren et al. 2012). All five metabolites identified here can be easily measured in a clinical MS-lab.
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| 99.94 |
PDAC and CP blood samples have been compared by LC-MS metabolomics analysis in two previous studies (Urayama et al. 2010; Fukutake et al. 2015). One of these targeted free amino acids in plasma. The advantage of a targeted approach is that sample preparation and analysis is optimized for a specific class of metabolites, but at the cost of covering only a limited part of the metabolome. Untargeted LC-MS on the other hand has the largest potential to identify novel metabolites due to increased metabolome coverage (Patti et al. 2012). In the second previous study comparing PDAC and CP, untargeted LC-MS was applied to plasma samples. Contrary to the present study, clinical data on e.g. disease stage and smoking status was available, which is important to avoid known confounding factors; however, the sample size (n = 10) was very limited which makes the results less generalizable. Other studies have applied different analytical metabolomics platforms to discriminate PDAC and CP in bodily fluids. In a study using gas chromatography-mass spectrometry, a majority of the serum discriminative metabolites were amino acids (Kobayashi et al. 2013), but included also some metabolites that would not have been particularly well captured in our LC-MS set-up such as some sugar species including, arabinose, ribulose and 1,5-Anhydro-D-glucitol and some organic acids such as uric acid, nonanoic acid and caprylic acid. In the mentioned study, CP samples were however included in the validation cohort only. Amino acids were also connected to future risk of pancreatic cancer in a metabolomics study applying LC-MS to prediagnostic plasma (Mayers et al. 2014). In the present study a number of amino acids were found dysregulated in PDAC compared to CP in the validation cohort only (data not shown), but lacking confirmation in a second cohort these results were excluded. Further, two studies have used nuclear magnetic resonance to study plasma and urine samples, respectively, but have not validated their results in a second cohort (Zhang et al. 2012) or had only three CP samples out of a total of 25 samples included in the benign control group (Davis et al. 2013).
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| 99.44 |
In the present study, the levels of a number of phospholipids were altered in PDAC compared to CP in both cohorts. Phospholipids were also found dysregulated in previous studies (Urayama et al. 2010; Ritchie et al. 2013; Sakai et al. 2016). However, we excluded all phospholipids as potential markers since they were down-regulated in PDAC in the discovery cohort as opposed to up-regulated in the validation cohort (Figs. 2, 4c, d). A possible explanation for these results is that different blood sample matrices, i.e. serum and plasma, were used in the two cohorts. Serum and plasma samples from the same individual are known to display different concentration levels for some metabolites, including phospholipids, due to the differences in sample handling (Yu et al. 2011). Noteworthy, as systemic phospholipid levels are altered by inflammatory responses in general, they are unlikely candidates for disease specific markers (Lindahl et al. 2016).
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| 99.94 |
As mentioned above, the two bile acids glycocholic acid and chenodeoxyglycocholate were significantly increased in PDAC compared to CP in the present study (Figs. 3, 5b). A possible explanation for increased levels of circulating bile acids is tumor growth into the bile duct. Another theory includes bile acid reflux into the pancreas, leading to pancreatitis and eventually malignant cell transformation; a direct carcinogenic effect of bile acids is also possible (Feng and Chen 2016). Bile acid levels in prediagnostic plasma have also been connected to future risk of pancreatic cancer (Mayers et al. 2014), supporting our results and reasoning.
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| 99.94 |
Two of the discriminative metabolite markers identified here, N-palmitoyl glutamic acid and hexanoylcarnitine (Figs. 3, 5b), are fatty acid conjugates with an amino acid and carnitine, respectively. N-acyl amino acids were only recently discovered as a novel group of compounds and little is known about their function (Hanus et al. 2014). However, a recent study in mice showed that certain N-acyl amino acids regulate cell metabolism through mitochondrial uncoupling (Long et al. 2016). Acylcarnitines in turn are vital for the transport of fatty acids into the mitochondrial matrix (Indiveri et al. 2011). Short-chain acylcarnitines including hexanoylcarnitine were previously found increased in serum in type 2 diabetes compared to normal glucose tolerance (Mai et al. 2013); both CP and PDAC may cause diabetes (Pinho et al. 2014).
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| 99.94 |
The levels of the nitrogenous metabolite PAGN were also increased in PDAC compared to CP in the present study (Fig. 5b). PAGN is a product of gut microbiota-host co-metabolism found in urine and blood (Barrios et al. 2015), and there are indications that the gut microbiota has an important role in carcinogenesis (Schwabe and Jobin 2013).
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| 100.0 |
In conclusion, this work has identified five metabolites capable of discriminating PDAC and CP in blood either as single or as a panel of markers. Findings were validated in a separate patient cohort. To determine the potential clinical benefit of these markers, further evaluation in larger clinical studies is needed. Nevertheless, we believe that these metabolites are potentially useful for early diagnosis of PDAC in CP patients.
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| 99.94 |
The research landscape for the human epidermal growth factor family of receptors has expanded with the discovery of their additional diverse roles in cancer. Extensive study of their function in aiding carcinogenesis and resistance to therapy is characterized and described in a number of reports1–3. In pancreatic cancer, the epidermal growth factor receptor (EGFR) is expressed in 30–90% of patients with pancreatic ductal adenocarcinoma (PDAC)4–6, marking aggressive disease with poor survival rates. EGFR has notably contributed to its early carcinogenesis from normal pancreatic epithelia, which transitions to neoplasms of pancreatic intraepithelial (PanIN) and finally, forming PDAC7.
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| 99.9 |
Receptor tyrosine kinases are implicated in resistance to treatment with their blockade stimulating compensatory pathways to rescue signaling activity. Recent studies reported that antagonism of EGFR resulted in the induction of other compensatory pathways such as the human epidermal receptor 3 (HER3) receptor8–10. HER3 amplification in solid tumors is associated with poor survival and resistance to therapy11. For example, cetuximab treatment demonstrated increased HER3 in colon12, head and neck13 and triple negative breast cancer14. In PDAC, HER3 is the preferred dimerization partner of EGFR15 with its concomitant activation rendering this malignancy impervious to EGFR and HER2 targeted therapy5. Furthermore, EGFR and HER3 are highly expressed in PDAC, marking this aggressive disease with poor survival rates5,6.
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| 96.94 |
With this perspective, combinatorial treatment strategies emerged to simultaneously target both the primary tumor’s molecular signature (e.g. EGFR) as well as the signaling mechanism likely to develop (e.g. HER3) upon resistance to first line therapy16. MEHD7945A or duligotuzumab, is a single agent fully human IgG1 monoclonal antibody (mAb) that targets both EGFR (KD ~ 1.9 nM) and HER3 (KD ~ 0.4 nM)17. It was developed to improve treatment response of solid tumors confounded with HER3-mediated resistance to EGFR-targeted treatment17. It is also efficacious in tumors refractory to both radiation and prolonged EGFR-specific treatment18,19. Importantly, it is safely tolerated by patients with locally advanced or metastatic epithelial cancers with no dose-limiting toxicities20. Partial response rates have been achieved in patients with cetuximab-refractory and prior chemo radiation squamous cell carcinoma of the head and neck (SCCHN)20.
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| 99.9 |
A companion diagnostic to MEHD7945A is critical for patient selection. In this study, we report the development of 89Zr (t1/2 = 3.27 d) labeled MEHD7945A (89Zr-MEHD7945A) and an evaluation of its pharmacological properties in PDAC by evaluating in vivo spatial distribution of the tracer against regional localization of EGFR and HER3 in Kras wild-type (BxPC-3) and mutant (AsPC-1) pancreatic cancer. We further investigated its specificity to EGFR and/or HER3 through in vitro, in vivo and ex vivo competitive blocking studies. Shifts in EGFR and HER3 expression during these blocking assays were measured by the radiotracer and further validated through immunoblots, flow cytometry and immunohistochemistry.
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| 100.0 |
The labeling of MEHD7945A with 89Zr was straightforward. Radiolabeling yields of >95% were obtained with >99% purity after purification. A specific activity of 4.53 ± 0.65 mCi/mg (25.5 ± 3.7 MBq/nmol) was established. The labeled protein retained its immunoreactivity toward both EGFR and HER3 with 74 ± 0.5% (n = 3) retention, which is within range of acceptable immunoreactivities (>60%) for clinical use21–25. 89Zr-MEHD7945A remains moderately intact >94% in both saline and 1:1 human serum:saline, over a 120 h incubation period at 37 °C (Supplementary Fig. S1).
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Among the three pancreatic cell lines, AsPC-1 (Supplementary Fig. S2A) displayed the highest EGFR and HER3 staining with ~85% of the cell population co-expressing both receptors. BxPC-3 (Supplementary Fig. S2B) demonstrated approximately ~74% of the cell population staining for both receptors. A very low level of Mia PACA2 (Supplementary Fig. S2C) cells co-express both receptors (0.42%). Western blots demonstrated relatively equal expression of EGFR between AsPC-1 and BxPC-3 cell lines, with almost no EGFR expression in Mia PACA2 (Supplementary Fig. S2D). The HER3 order of expression for the three pancreatic cells are as follows: AsPC-1 > BxPC-3 > Mia PACA2.
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| 100.0 |
Internalization of 89Zr-MEHD7945A in all cell lines was conducted at 37 °C (Fig. 1A, left). BxPC-3 displayed the highest uptake from 3.29 ± 0.28% at 1 h to almost a two-fold increase at 24 h with 5.91 ± 0.05% of the tracer internalized. In AsPC-1, the tracer was steadily internalized over time (2.58 ± 0.23% at 1 h, 3.23 ± 0.26% at 4 h and 4.70 ± 0.52% at 24 h) while the negative control cell line, Mia PACA2 demonstrated lower uptake across all time points (1.15 ± 0.06% at 1 h, 1.76 ± 0.17% at 4 h and 3.04 ± 0.21% at 24 h respectively). Significantly lower accumulation was observed in all cell lines at 4 °C, supporting an endocytotic mechanism of internalization (Fig. 1A, right).Figure 1In vitro characterization. 89Zr-MEHD7945A demonstrated higher internalization rates in BxPC-3 and AsPC-1 at 37 °C (left) compared to the EGFR/HER3-negative Mia PACA2 pancreatic cancer cell line. 89Zr-MEHD7945A showed a decrease in internalization at 4 °C (right) in all cell lines. (A) 89Zr-MEHD7945A demonstrated successful blocking with cold MEHD7945A and cetuximab at 10× and 25× doses. Blocking with DL3.6b at 10× lowered the uptake of the probe; binding was sustained at 25× dose of the anti-HER3 mAb. In both AsPC-1 and BxPC-3. (B) Non-linear regression analysis determined two sets of KD and Bmax for AsPC-1 with an. (C) The KD and Bmax values for BxPC-3 (D) are within the same range as the established values in AsPC-1 with an IC50 ~ 0.37 nM. (*Denote p < 0.01, ǂdenote p < 0.05, compared to no block).
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| 100.0 |
In vitro characterization. 89Zr-MEHD7945A demonstrated higher internalization rates in BxPC-3 and AsPC-1 at 37 °C (left) compared to the EGFR/HER3-negative Mia PACA2 pancreatic cancer cell line. 89Zr-MEHD7945A showed a decrease in internalization at 4 °C (right) in all cell lines. (A) 89Zr-MEHD7945A demonstrated successful blocking with cold MEHD7945A and cetuximab at 10× and 25× doses. Blocking with DL3.6b at 10× lowered the uptake of the probe; binding was sustained at 25× dose of the anti-HER3 mAb. In both AsPC-1 and BxPC-3. (B) Non-linear regression analysis determined two sets of KD and Bmax for AsPC-1 with an. (C) The KD and Bmax values for BxPC-3 (D) are within the same range as the established values in AsPC-1 with an IC50 ~ 0.37 nM. (*Denote p < 0.01, ǂdenote p < 0.05, compared to no block).
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In AsPC-1 cells, (Fig. 1B and Supplementary Table S1) co-administration of 89Zr-MEHD7945A and unlabeled MEHD7945A at an excess of 10- and 25-fold for 1 h reduced uptake (1.97 ± 0.74%, p < 0.0001 and 1.06 ± 0.82%, p < 0.0001, respectively) compared to unblocked cells (5.55 ± 0.64%). Blocking with the anti-EGFR antibody, cetuximab, which binds to the same EGFR epitope as MEHD7945A, also significantly reduced the radiotracer uptake (1.09 ± 0.47% at 10× and 1.47 ± 0.42% at 25× blocking doses, p < 0.0001). Competitive inhibition of the tracer with the anti-HER3 antibody DL3.6b with a 10-fold excess decreased tracer binding from 5.55 ± 0.64% to 3.47 ± 0.26% (p = 0.0194), whereas treatment with 25-fold excess of DL3.6b showed no significant difference with 5.60 ± 0.51% total bound compared to control. External validation through flow cytometry was performed on separate groups of AsPC-1 cells exposed for 48 h to 25-fold higher cold doses of MEHD7945A, cetuximab and DL3.6b (Supplementary Fig. S3A and Supplementary Table S1). Control untreated cells had a median fluorescent intensity (MFI) of 340.3 ± 32.8 for EGFR-expressing cells and 79.6 ± 11.5 for HER3-expressing cells. Blocking with MEHD7945A significantly reduced EGFR expression compared to control (32.6 ± 2.8 MFI, p < 0.0001) but did not significantly reduce cells bearing HER3 expression (57.3 ± 3.7 MFI, p = 0.096). Blocking with cetuximab significantly depleted EGFR expression (0.1 ± 0.9 MFI, p = 0.0001) but not HER3 (80.4 ± 6.9 MFI). Treatment with DL3.6b did not change EGFR expression (336.0 ± 3.6) but significantly attenuated total HER3 (48.2 ± 4.9 MFI, p = 0.0128).
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In BxPC-3 cells, normal uptake of the radiotracer was measured at 11.72 ± 3.54% (Fig. 1B and Supplementary Table S1). Binding was significantly reduced when co-administered with MEHD7945A (10-fold: 1.02 ± 0.34%, p = 0.0001; 25-fold: 0.29 ± 0.16%, p = 0.0001) and cetuximab (10-fold: 1.21 ± 0.46%, p = 0.0001; 25-fold: 1.02 ± 0.23%, p = 0.0001). Competition with 10-fold DL3.6b lowered radiotracer accumulation to 6.98 ± 0.69% (p = 0.0001). Interestingly, radiotracer uptake was not diminished at 25-fold excess DL3.6b with 16.36 ± 0.88% binding (p = 0.0001). From the flow cytometry analysis, control cells exhibited 307.7 ± 11.2 MFI and 127.0 ± 3.6 MFI for EGFR and HER3 respectively. MEHD7945A-blocked cells decreased EGFR expression (182.7 ± 28.4 MFI, p = 0.0001) and HER3 (95.4 ± 7.7 MFI, p = 0.0123). Exposure to cetuximab mitigated EGFR expression (3.3 ± 0.8 MFI, p = 0.0001) whereas HER3 abundance remained unchanged (130.3 ± 4.0 MFI). Incubation with DL3.6b decreased HER3 (63.3 ± 8.2 MFI, p = 0.0001) while EGFR levels remained similar to unblocked control (284.0 ± 13.1 MFI, p = 0.0739) (Supplementary Fig. S3 and Supplementary Table S1).
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Surface plasmon resonance (SPR) analysis of the dissociation constant (KD) of DFO-derivatized MEHD7945A vs. the unmodified mAb demonstrated relatively similar binding for HER3 (37 pM vs. 8.1 pM, respectively) and EGFR (3.4 nM vs. 1.9 nM respectively). Competitive binding of 89Zr-MEHD7945A with increasing concentrations of cold MEHD7945A was conducted in both BxPC-3 and AsPC-1 cells. In AsPC-1 (Fig. 1C, left), a KDHi ~ 0.31 nM and KDLo ~ 29.00 nM were achieved. Measured BmaxHi and BmaxLo values were ~1.94 × 105 and ~7.02 × 104 receptors sites were available. The IC50 was ~0.37 nM (Fig. 1C, right). From the plot in Fig. 1D (left), the dissociation constants KDHi and KDLo in BxPC-3 cells were determined to be 0.34 nM and 12.02 nM with a BmaxHi of ~7.25 × 104 and BmaxLo of ~1.10 × 105. The IC50 for 89Zr-MEHD7945A was observed to be ~0.48 nM in BxPC-3 (Fig. 1D, right).
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In Fig. 2A, cumulative tumor uptake of 89Zr-MEHD7945A was observed in the AsPC-1 xenograft with 3.98 ± 0.21 percent injected dose per gram of tissue (%ID/g) at 24 h post-injection (p.i.) with the maximum tumor-bound activity achieved at 72 h p.i. at 6.18 ± 1.0%ID/g. Retention of the radiotracer was observed to as far as 96 h p.i. (6.23 ± 1.35%ID/g). AsPC-1 tumors imaged with the non-specific isotype 89Zr-IgG had significantly less uptake (0.62 ± 0.53%ID/g at 24 h, 0.80 ± 0.44%ID/g at 48 h, 1.03 ± 0.55%ID/g at 72 h, and 0.83 ± 0.29%ID/g, p < 0.001) at all time points (Fig. 2B). Higher cumulative tumor uptake was observed in BxPC-3 xenografts with 6.72 ± 1.40%ID/g at 24 h p.i. (Fig. 2C). The tumor uptake peaked at 8.91 ± 2.1%ID/g at 72 h with observed retention at 96 h p.i. (8.56 ± 2.3%ID/g). Separate BxPC-3 tumors imaged with 89Zr-IgG showed significantly less uptake (for example, 0.75 ± 0.32%ID/g at 24 h p.i, 0.65 ± 0.46%ID/g at 48 h p.i. p < 0.001, Fig. 2D) for all time points.Figure 2In vivo PET imaging. In AsPC-1 xenografts, tumor volumes-of-interest (VOI) expressed as % ID/g generated from the 89Zr-MEHD7945A PET scans exhibited uptake as early as 24 h p.i., peaking at 72 h p.i. and retained to as long as 96 h p.i. (A) 89Zr-IgG control PET scans showed minimal uptake within the tumor at all time points. (B) Similarly in BxPC-3 tumors, PET scans exhibited uptake at 24 h p.i. with a peak at 72 h p.i. (C) Non-specific tumor uptake using 89Zr-IgG in BxPC-3 xenografts showed nominal accumulation across all time points. (D) Whole body tissue distribution revealed high tumor tissue uptake of the tracer at 24 h p.i,, which plateaued at 48 h through 120 h p.i. in BxPC-3 xenografts. A competitive blocking study using unmodified MEHD7945A at 48 h p.i. displayed at least a two-fold decrease in tumor binding, indicative of the probe’s specificity. (E) Of note, normal pancreas demonstrated minimal non-specific binding on all time points, suggesting that an excellent signal-to-noise contrast can be achieved.
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In vivo PET imaging. In AsPC-1 xenografts, tumor volumes-of-interest (VOI) expressed as % ID/g generated from the 89Zr-MEHD7945A PET scans exhibited uptake as early as 24 h p.i., peaking at 72 h p.i. and retained to as long as 96 h p.i. (A) 89Zr-IgG control PET scans showed minimal uptake within the tumor at all time points. (B) Similarly in BxPC-3 tumors, PET scans exhibited uptake at 24 h p.i. with a peak at 72 h p.i. (C) Non-specific tumor uptake using 89Zr-IgG in BxPC-3 xenografts showed nominal accumulation across all time points. (D) Whole body tissue distribution revealed high tumor tissue uptake of the tracer at 24 h p.i,, which plateaued at 48 h through 120 h p.i. in BxPC-3 xenografts. A competitive blocking study using unmodified MEHD7945A at 48 h p.i. displayed at least a two-fold decrease in tumor binding, indicative of the probe’s specificity. (E) Of note, normal pancreas demonstrated minimal non-specific binding on all time points, suggesting that an excellent signal-to-noise contrast can be achieved.
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Tissue distribution of 89Zr-MEHD7945A was analyzed in BxPC-3 tumor-bearing mice at 24–120 h p.i. (Fig. 2E and Supplementary Table S2). Tumor uptake was detected at 24 h p.i. with 24.6 ± 6.7%ID/g. The accumulation reached 31.1 ± 3.9%ID/g at 48 h p.i. and plateaued over the later time points with 32.8 ± 4.7%ID/g at 96 h p.i. and 32.7 ± 5.3%ID.g at 120 h p.i. Tumor accumulation decreased by two-fold (13.0 ± 3.4%ID/g) at 48 h p.i when 89Zr-MEHD7845A was administered with an excess of unmodified antibody to compete and block the radiotracer for receptor sites. Uptake in normal pancreas was significantly lower with <2%ID/g across all time points. Other organs within close proximity to the pancreas demonstrated low non-specific accumulation. For example at 48 h p.i., non-targeted binding in the liver, the primary clearance route for most mAbs, was 2.5-fold less than tumor uptake at 9.7 ± 2%ID/g. At the same time points, tissue-uptake values for the spleen, stomach and gut were 3.7 ± 1.8%ID/g, 1.3 ± 0.7%ID/g and 1.2 ± 0.3%ID/g respectively. Bone accumulation was observed over time with 6.84 ± 3.85%ID/g at 48 h p.i., which plateaued at 8.86 ± 4.34%ID/g at 120 h p.i. Blocking with MEHD7945A at 48 h p.i. moderately lowered the bone uptake to 4.03 ± 1.60%ID/g but was statistically insignificant.
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| 100.0 |
To understand the differences in tracer uptake between tumor models, spatial distribution of 89Zr-MEHD7945A was evaluated using digital autoradiography on AsPC-1 (Fig. 3A, left) and BxPC-3 tumors (Fig. 3A, right). Adjacent tumor sections of both AsPC-1 and BxPC-3 were evaluated for EGFR (Fig. 3B) and HER3 expression (Fig. 3C) by immunohistochemistry. Tissue viability and collagen content were qualitatively assessed via H&E staining (Supplementary Fig. S4A,B) and trichrome staining (Supplementary Fig. S4C), respectively. In both tumors, 89Zr-MEHD7945A accumulated in viable tumor regions with high EGFR expression (Fig. 3B). Staining of EGFR and HER3 showed strongest positivity on viable tumor cells. Although, the expression of EGFR in BxPC-3 and AsPC-1 tumor sections was similar, there was higher expression of HER3 in AsPC-1 when compared to BxPC-3. Areas with strong staining for HER3 co-localized with areas of high 89Zr-MEHD7945A registration (Fig. 3C). Taken together, the localization pattern indicates the dependence of 89Zr-MEHD7945A on both target expression and local pharmacokinetics. Collagen expression was qualitatively equivalent for both tumor sections. Looking at cell density, BxPC-3 tumors were observed to be two-fold more “cell dense” than AsPC-1 xenografts (258.8 ± 64.2 cells vs. 71.3 ± 14.9 cells, p = 0.0013, (Supplementary Fig. S4D).Figure 3Autoradiography and histology. Autoradiographs (A) of excised AsPC-1 (left) and BxPC-3 (right) tumor sections depicted co-localization of the tracer in areas where EGFR (BxPC-3 3+, AsPC-1 2+) (B) and HER3 (BxPC-3 1+, AsPC-1 2+) (C) are expressed.
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study
| 100.0 |
To determine whether 89Zr-MEHD7945A binds to either EGFR or HER3 alone or both, in vivo blocking studies were conducted. Blocking EGFR with cetuximab in AsPC-1 tumors (Fig. 4A and Supplementary Table S3) lowered the uptake of 89Zr-MEHD7945A by almost 3-fold (19.30 ± 5.60%ID/g vs. 7.72 ± 6.70%ID/g, p = 0.0457). In contrast, blocking the HER3 epitope with DL3.6b did not alter tumor accumulation of 89Zr-MEHD7945A (18.79 ± 8.75%ID/g).Figure 4In vivo competitive inhibition. In AsPC-1 xenografts, blocking with cetuximab (EGFR block) showed an almost 2-fold decrease in 89Zr-MEHD7945A uptake, whereas blocking HER3 with DL3.6b did not change probe uptake. (A) In BxPC-3 xenografts, blocking with cetuximab (EGFR block) showed a slight decrease in 89Zr-MEHD7945A, whereas blocking with DL3.6b (HER3 block) showed a statistically significant, increase in probe accumulation. (B) IHC staining in BxPC-3 tumors blocked with 25× cetuximab (25x EGFR, left), 25x DL3.6b (25x HER3, middle) or left unblocked (right) were assessed by IHC for EGFR (top) and HER3 (bottom) expression, and showed an increase in EGFR and HER3 in both blocked cohorts. (C) Tumor sections depicted for IHC are shown in 100×. Densitometry analysis of western blots on tumor lysates (n = 2) from AsPC-1 (left) and BxPC-3 (right) that were untreated, exposed to EGFR-block with cetuximab and a HER3-block with DL3.6b. (D) Densitometry is shown as a ratio of target protein/loading control.
|
study
| 100.0 |
In vivo competitive inhibition. In AsPC-1 xenografts, blocking with cetuximab (EGFR block) showed an almost 2-fold decrease in 89Zr-MEHD7945A uptake, whereas blocking HER3 with DL3.6b did not change probe uptake. (A) In BxPC-3 xenografts, blocking with cetuximab (EGFR block) showed a slight decrease in 89Zr-MEHD7945A, whereas blocking with DL3.6b (HER3 block) showed a statistically significant, increase in probe accumulation. (B) IHC staining in BxPC-3 tumors blocked with 25× cetuximab (25x EGFR, left), 25x DL3.6b (25x HER3, middle) or left unblocked (right) were assessed by IHC for EGFR (top) and HER3 (bottom) expression, and showed an increase in EGFR and HER3 in both blocked cohorts. (C) Tumor sections depicted for IHC are shown in 100×. Densitometry analysis of western blots on tumor lysates (n = 2) from AsPC-1 (left) and BxPC-3 (right) that were untreated, exposed to EGFR-block with cetuximab and a HER3-block with DL3.6b. (D) Densitometry is shown as a ratio of target protein/loading control.
|
study
| 100.0 |
In BxPC-3 xenografts (Fig. 4B and Supplementary Table S3), exposure to cetuximab showed no difference in 89Zr-MEHD7945A uptake between control (28.56 ± 10.81%ID/g) and cetuximab-blocked tumors (21.79 ± 14.19%ID/g, p = 0.39). Competition of the tracer with DL3.6b demonstrated an approximately two-fold increase in radiotracer accumulation of 46.89 ± 20.1%ID/g (p = 0.0021).
|
study
| 100.0 |
We next determined the underlying mechanism for the unexpected trend in tumor uptake of the blocked cohorts. Pathological analysis revealed an increase in EGFR (Fig. 4C, top) and HER3 (Fig. 4C, bottom) staining in both EGFR and HER3 blocked BxPC-3 tumors compared to control. From the western blots, cetuximab-treated AsPC-1 exhibited a two-fold decrease in total EGFR protein, coupled with a 1.3-fold increase in HER3 as shown by densitometry (Fig. 4D). With the DL3.6b blocked AsPC-1 tumors, a 2.25-fold increase in EGFR with a concomitant three-fold decrease in HER3 was displayed. Similar trends were observed in BxPC-3 wherein cetuximab-blocked groups displayed suppressed EGFR and HER3 (Fig. 4D). Saturation of the HER3 sites exhibited a moderate increase in EGFR expression, coupled with a decrease in HER3. These results imply that the blocking dose of antibody (cetuximab or DL3.6b) may be inducing an upregulation of either receptor in an attempt to maintain proliferation.
|
study
| 100.0 |
Figure 5A showed that an addition of excess cold MEHD7945A (100 nM) blocks the binding of 89Zr-MEHD7945A (1 nM). This demonstrated a saturable, concentration-dependent binding of the tracer. From the Scatchard plot (Fig. 5B), the Bmax was found to be 336.0 ± 25.5 fmol/mg or 2 × 105 binding sites per cell (assuming 1 million cells per tumor) and the KD was found to be ~0.51 ± 0.12 nM.Figure 5Ex vivo competitive binding assay. A digital autoradiograph of AsPC-1 tumor sections displayed saturable, concentration-dependent binding of 89Zr-MEHD7945A upon addition of 100-fold excess cold MEHD7945A. (A) A non-linear regression analysis and Scatchard plot of 89Zr-MEHD7945A plotted against the amount of bound ligand shows the Bmax ~ 336 fmol/mg and a KD ~ 0.51 nM (B).
|
study
| 100.0 |
Ex vivo competitive binding assay. A digital autoradiograph of AsPC-1 tumor sections displayed saturable, concentration-dependent binding of 89Zr-MEHD7945A upon addition of 100-fold excess cold MEHD7945A. (A) A non-linear regression analysis and Scatchard plot of 89Zr-MEHD7945A plotted against the amount of bound ligand shows the Bmax ~ 336 fmol/mg and a KD ~ 0.51 nM (B).
|
study
| 100.0 |
The MEGHAN trial was a randomized phase II study that evaluated drug efficacy of MEHD7945A compared to cetuximab in patients with recurrent/metastatic squamous cell carcinoma of the head and neck that progressed after chemotherapy26. Compared to cetuximab treatment alone, the study found that MEHD7945A did not significantly improve patient outcomes, even those with amplified neuregulin-1 expression, a HER3 ligand, as measured by disease free survival26. Despite this dismal outcome, the combined blockade of EGFR and HER3 merits a second look with trials that particularly focus on EGFR treatment-resistant patient populations. This rationale stems from an overwhelming body of evidence showing that dual inhibition of EGFR and HER3 promotes desensitization of lesions to EGFR blockade through HER3 crosstalk inhibition27–29. With this perspective, our initiative to develop a companion diagnostic to MEHD7945A is potentially useful for selecting patients within this space in order to benefit from this treatment. To the best of our knowledge, we are the first to develop a new PET radiotracer that simultaneously delineates both of EGFR and HER3 receptors. Only one recent study has described a bi-specific immunoPET imaging tracer, albeit, of different receptors, CD3 and EpCAM30. Other previous and currently investigated immunoPET tracers specific to these two receptor tyrosine kinases are limited to single antigen detection with either EGFR25,31–33 or HER334–37 alone. The paradigm is shifting, however, to combinatorial drug cocktails to debulk tumor. The quest for a potent and efficient therapy led to the development of bispecific antibodies or fragments to target more than one molecular signature (tumor associated antigens) amplified in lesions, e.g., EGFR/IGF1-R38, EGFR/Met39, and HER2/HER340. This stems from the rationale that a single agent targeting multiple markers vis-à-vis a monospecific approach can strongly stabilize specificity and selectivity for tumor instead of normal tissues. To select a patient population who stands to benefit from the treatment, non-invasive and quantitative imaging biomarkers are of utmost need. We believe that 89Zr-MEHD7945A satisfies this initiative.
|
review
| 75.44 |
The low expression of HER3 in malignancies and moderate expression in normal tissues41 mandate targeted drugs and imaging radiotracers to have a high avidity to this antigen40. Sub-nanomolar or higher affinities are preferable for improved tumor specificity and selectivity36,40. We examined whether the binding affinity of 89Zr-MEHD7945A for EGFR and HER3 were retained after radiolabeling. The results from the in vitro and ex vivo competitive binding assays exhibited nanomolar affinities, in good agreement with the established KD of the unmodified antibody17. Other immunoPET tracers singly targeting HER3 fall within the same range (i.e. 2.7 nM42 and 6.8 nM37). Only one other tracer, the affibody-based probe 68Ga-HEHEHE-Z08698-NOTA, exhibited picomolar binding affinity (50 pM)36,43. Established affinities of other immunoPET EGFR tracers are within the same range. For example, an affibody labeled with F-18 displayed a KD ~ 37 nM whereas a 67Ga-DOTA-cetuximab F(ab′)2 reported a KD ~ 8.6 nM, making the KD for our radiotracer within reasonable range.
|
study
| 100.0 |
The acquired PET images are validated by the tissue distribution data. Radiotracer uptake was observed in the lung, liver, spleen and bone, which can be attributed to the moderate expression of both EGFR and HER3 and their role in tissue growth44. This is supported by the data from competitive blocking studies where the tissues (listed above, excluding bone) in the blocked cohort of mice had lower probe accumulation at 48 h than the unblocked cohort (Fig. 2E, Supplementary Table S3). Cross-reactivity of the fully human MEHD7945A with murine EGFR and HER3 is expected; murine EGFR is 94% homologous to human EGFR45 whereas murine HER3 is orthologous to the human receptor with 90.8% sequence homology46. Bone accumulation can be a combination of specific EGFR/HER3 targeted delivery with reported expression of both RTKs in skeletal tissues47,48 and/or non-specific deposit of demetalated 89Zr from its chelate DFO. The latter is evidenced by the free 89Zr observed as early as 24 h with 95–97% of the tracer remaining intact at 120 h (Supplementary Fig. S1). The competitive inhibition experiment of 89Zr-MEHD7945A using unmodified MEHD7945A together with non-specific IgG isotopic probe control from our data is evident of specific tumor targeting of 89Zr-MEHD7945A and thereby eliminating the enhanced permeation effect as the underlying mechanism of delivery. Co-localization of the tracer with EGFR/HER3 expression as shown in the autoradiography and IHC studies further proved the probe’s selectivity for the receptors.
|
study
| 100.0 |
Despite the high number of EGFR and HER3 present as verified through Bmax values, flow cytometry and immunoblots, the tumor accumulation of the probe in AsPC-1 xenografts uptake was lower compared to BxPC-3 models. With PDAC reportedly possessing dense stroma, we initially rationalized that high levels of collagen, an essential component of the extracellular matrix may perturb tumor penetration of the probe. The trichome stain (Supplementary Fig. S4C), however, did not display any significant disparity in collagen levels between the two types of tumors. Looking at cell density from a pathological perspective, the BxPC-3 tumors were denser than the AsPC-1 tumors as shown by cell count (Supplementary Fig. S4D). This consequently lowered receptor sites available, which potentially explains the lower PET volume of interest (VOI) uptake attained in the AsPC-1 tumors.
|
study
| 100.0 |
We interrogated the dual specificity of the probe for either EGFR or HER3 through competitive binding assays. Interestingly, blocking either EGFR or HER3 separately increased or sustained the binding levels of the probe compared to blocking both receptors simultaneously. The highest blocking doses administered can be considered a treatment dose (HER3 IC50 ~ 0.12 µg/mL and EGFR IC50 ~ 0.02 µg/mL for the in vitro study17, and 0.04–1 mg per mouse in vivo49,50), potentially eliciting an activated feedback loop. Results of the study seemingly imply an “EGFR-only” mechanism of probe uptake. Looking closely at both AsPC-1 and BxPC-3 control untreated cells, the flow cytometry data indicated very low HER3 expression compared to EGFR, which is five-fold higher (Supplementry Table S1). We believe that any marginal change in HER3 when blocked with DL3.6b combined with the magnitude of EGFR expression may be below the sensitivity threshold of the radiotracer. With the in vivo competition assays, it would seem like the blocks were unsuccessful with the tracer uptake between control and blocked groups rendered statistically insignificant. In this case, external validation with immunohistochemistry (Fig. 4C) and western blots (Fig. 4D) supported feedback compensation of either EGFR or HER3, albeit on a smaller scale. We must keep in mind that the tumor was exposed to the blocking antibodies acutely vs. chronic exposure in a therapeutic setting; thus, a sustained and higher HER3 induction may not have been achieved. Nevertheless, the tracer detected varied expression of either RTKs. Admittedly, one of the main limitations of the probe lies in identification of which receptor is upregulated.
|
study
| 100.0 |
Our previous work demonstrated that the probe detected solely HER3 feedback upon AKT inhibition in triple negative breast cancer51. Moreover, we have unpublished data showing similar HER3 detection by the radiotracer in colorectal cancer upon MEK treatment. Our findings were corroborated by a wide body of evidence demonstrating HER3 feedback upon independent blockade of EGFR in colon cancer12, head and neck small cell cancer13, lung cancer52 and triple negative breast cancer. Thus, simultaneous blockade of both EGFR and HER3 with MEHD7945A is potentially more efficacious than single agent monotherapy.
|
study
| 99.94 |
In summary, we have successfully developed an EGFR/HER3 targeting immunoPET companion diagnostic to MEHD7945A (duligotuzumab) and evaluated its properties in the preclinical setting. This probe has high potential to non-invasively delineate and stage EGFR and HER3 positive tumors with high affinity and selectivity.
|
study
| 99.94 |
Validation of EGFR and HER3 expression in AsPC-1, BxPC-3 and Mia PACA2 pancreas cancer cells was conducted via standard flow cytometry and immunoblot analysis. Cells were labeled with anti-EGFR-AF488 (AY13, Biolegend) and anti-HER3-APC (1B4C3, Biolegend) and analyzed for receptor expression using BD LSR II FLOW cytometer (BD Biosciences).
|
study
| 100.0 |
The EGFR and HER3 protein expression were determined by SDS-PAGE using the Invitrogen XCell SureLock system. Briefly, proteins were extracted from cell pellets with RIPA buffer and protease and phosphatase inhibitors (HALT, ThermoFisher). Fifteen micrograms of protein were resolved by 4–12% SDS-PAGE and transferred to membrane. After blocking with 5% milk in TBS-0.1% Tween-20, membrane was incubated with anti-EGFR-XP (D38B1, Cell Signaling), anti-HER3-XP (D22C5, Cell Signaling), or anti-β-Actin (mAbcam 8226, Abcam) antibody overnight at 4 °C. After incubation with secondary antibody (anti-mouse HRP or anti-rabbit HRP, Amersham) the membrane was visualized by Ammersham ECL (GE Life sciences) and read using a ChemiDoc imaging system (Bio-Rad) and analyzed using image lab touch software 2.2 (Bio-Rad).
|
study
| 99.94 |
p-Benzyl-isothiocyanate-desferrioxamine (DFO-Bz-SCN, Macrocylics, Inc.) was conjugated to MEHD7945A and a non-specific human IgG isotype (Sigma) according to published protocols53,54. The synthesis was performed using 7:1 and 5:1 mole equivalence of DFO-Bz-SCN to MEHD7945A or IgG, respectively in a 0.9% saline, pH ~9 at 37 °C for 1 h. The pure mAb DFO-conjugates were obtained through by purification with a spin column filter with a molecular weight cut-off of 30 kDa (GE Vivaspin 500) to remove unbound chelate.
|
study
| 100.0 |
89Zr-oxalate was produced as previously described55. Approximately 1 mCi (37 MBq) of 89Zr-oxalate was neutralized to pH 7.0–7.2 using 1 M NaOH. MEHD7945A-DFO (200 µg) was added to the 89Zr solution. The reaction was quenched after 1–1.5 h incubation at room temperature upon addition of 10 µL of 50 mM EDTA (pH~7) to eliminate any non-specifically bound 89Zr. Radiolabeling efficiency and purity were determined via radio-instant Thin Layer Chromatography (iTLC) using silica gel-impregnated iTLC strip (Agilent Technologies, Santa Clara, CA) and 50 mM EDTA as the solid and mobile phase respectively. Pure 89Zr-MEHD7945A was obtained by passing through a spin column centrifugation filter (GE Vivaspin 500, MWCO: 30 kDa) with saline as the diluent. A radiochemical purity of >99% was achieved based on iTLC analysis. 89Zr-MEHD7945A was assessed for immunoreactivity as previously described56. Demetallation of 89Zr was monitored in 0.9% saline and 1:1 human serum:saline over time at 37 °C via iTLC.
|
study
| 100.0 |
All animal handling, manipulations, and experiments were conducted in accordance with the guidelines and regulations set by Wayne State University Institutional Animal Use and Care Committee (IACUC), MSKCC Animal Care and Use Committee and Research Animal Resource Center, which are accredited by the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC). For imaging experiments, female SCID mice (6–8 week old, Taconic) were subcutaneously implanted on the shoulders with BxPC-3 and AsPC-1 pancreatic cancer cells that were cultured in RPMI 1640 + 10% FBS + 1% NEAA + 1% PenStrep. All cells (5 × 106 cells/tumor) in 150 µL 1:1 media:Matrigel (BD Biosciences, Bedford, MA) were injected on the right shoulder. Monitoring of tumor growth was performed weekly with calipers. The tumor volume was calculated using the formula: length × width × height × π/6. Mice with tumor volumes ranging from 150–250 mm3 were utilized. For in vitro experiments, Mia PACA2 cells were cultured in DMEM + 10% FBS + 2.5% Horse Serum + 1% PenStrep. All cells were maintained at 37 °C at a 5% CO2 atmosphere.
|
study
| 100.0 |
Internalization of 89Zr-MEHD7945A was evaluated on AsPC-1, BxPC-3 and MIA PACA2 pancreatic cancer cell lines. Wells were seeded with ~1 × 105 cells and incubated overnight. Radiolabeled protein [1 μCi/mL (37 kBq/mL, 20 μg)] in 1 mL of media was added to each well. The plates were incubated at either 37 °C or 4 °C for 0.5–24 h. Following each incubation period, the media was collected and the cells were rinsed with 1 mL 1× phosphate buffered saline (PBS) twice. Surface-bound activity was removed by washing the cells in 1 mL 100 mM acetic acid + 100 mM glycine (1:1, pH 3.5) at 4 °C. The cells were then lysed with 1 mL 1 M NaOH. All washes (media plus PBS, acid and alkaline) were collected in separate tubes and measured for counts using a gamma counter (Perkin Elmer). The %-internalized activity was calculated as the ratio of the activity of the lysate and the total activity collected from the media plus PBS wash, acid, and base washes.
|
study
| 100.0 |
Surface plasmon resonance (SPR) (Biacore 3000, GE Healthcare) evaluated the binding affinity expressed as the equilibrium binding constant, KD of the MEHD7945A-DFO and the unmodified mAb using previously published protocols57. Immobilization of HER3 and EGFR proteins on a CM5 sensor chip was performed at 25 °C by amine-coupling chemistry using Biacore 3000 (GE Healthcare). To determine kinetic rate constants, the processed data were fitted to 1:1 Langmuir binding model using BIAevaluation software.
|
study
| 100.0 |
The total EGFR and HER3 binding sites on AsPC-1 and BxPC-3 cell lines were determined by homologous competitive saturation binding assay using radiolabeled 89Zr-MEHD7945A. Briefly, after detachment from cell culturing flasks by trypsinization, AsPC-1 and BxPC-3 were collected and re-suspended in PBS/1% BSA. Radiolabeled 89Zr-MEHD7945A was incubated with increasing concentration of MEDH7945A to AsPC-1 or BxPC-3 cells in PBS/1% BSA at room temperature. Sample incubation was terminated by vacuum filtration of samples through glass microfiber filters followed by triple PBS/1% BSA wash and counted on Wizard2 gamma counter. The IC50 was analyzed by sigmoidal dose response curve using a four-parameter logistic nonlinear regression. Two-site, non-linear saturation binding model was employed to determine KDHi and KDLo, the radioligand concentrations required to achieve a half-maximum binding at equilibrium. The BmaxHi and BmaxLo,, the maximum specific bindings to the two receptor sites were also analyzed.
|
study
| 100.0 |
AsPC-1 and BxPC-3 cells were plated at 200,000 cells/well and allowed to adhere overnight at 37 °C with 5% CO2. The cells were then co-incubated with either 10× (1 μg) or 25×, (2.5 μg) cold MEHD7945A, cetuximab, or DL3.6B and 89Zr-MEHD7945A [~0.5 μCi (0.0185 MBq), 100–125 ng] in 1 mL of complete media for 1 h at 37 °C with 5% CO2. Following incubation, the media was collected and the cells were rinsed with 1 mL 1× PBS twice. The cells were then lysed with 1 mL 1 M NaOH. All washes (media plus PBS, and alkaline) were collected in separate tubes and measured for counts using a gamma counter (Perkin Elmer). The %-bound activity was calculated as the ratio of the activity of the lysate and the total activity collected from the media, PBS, and base washes.
|
study
| 100.0 |
For flow cytometry studies, AsPC-1 and BxPC-3 cells were prepared as described above and then incubated with 10× or 25× cold antibodies in complete medium for 48 h at 37 °C with 5% CO2. After incubation, media was removed and cells were washed with 1× PBS and subsequently labeled with anti-EGFR-AF488 (AY13, Biolegend) and anti-HER3-APC (1B4C3, Biolegend) and analyzed for receptor expression using BD LSR II FLOW cytometer (BD Biosciences).
|
study
| 99.94 |
89Zr-MEHD7945A [200–275 μCi (7.4–10.2 MBq), 44–61 µg, 290–400 pmol] in sterile saline was intravenously (i.v.) administered on the lateral tail-vein in mice (n = 3–4) bearing either BxPC-3 or AsPC-1 s.c. xenografts. Small-animal PET scans were acquired between 24–96 h post-tracer administration using microPET-R4 and/or Focus 120 scanners (Concorde Microsystems). The mice were fully anesthetized with 1–2% isoflurane (Baxter, Deerfield, IL) throughout the scan. Images were reconstructed via filter back projection. ASIPro VMTM software (Siemens Concorde Microsystems) was used to analyze volumes-of-interest (VOI) on various planar sections from the acquired image by manually drawing on the tumor site and on select organs. The average VOI was calculated and expressed as % injected dose per gram of tissue (%ID/g). To prove specificity, competitive inhibition studies were conducted by co-administering ~200–500 µg (1.33 nmol–3.33 nmol) of non-radioactive MEHD7945A in BxPC-3 tumor-bearing mice (n = 3–5). PET imaging with 89Zr-IgG [230–250 μCi (8.51–9.25- MBq, 306–336 pmol, 46–50 μg) was conducted in mice with BxPC-3 and AsPC-1 tumors to assess non-specific accumulation of the tracer.
|
study
| 100.0 |
The tissue distribution of 89Zr-MEHD7945A was assessed in mice-bearing BxPC-3 tumors. A tracer dose of 10–15 μCi (370–555 kBq, 1–2 µg, 6.7–13.3 pmol) was injected i.v. on the lateral tail vein. In vivo competitive specificity assays were conducted in separate cohorts (n = 4–5 per group) of BxPC-3 and AsPC-1 xenografts. The tracer dose 25–30 μCi (0.925–1.11 MBq, 5–6 µg, 33.3–40 pmol) was co-injected with 10-fold higher blocking doses of either MEHD7945A (50 μg), cetuximab (50 μg) or the anti-HER3 mAb, DL3.6B (50 ug). Euthanasia via CO2 asphyxiation was performed between 24–120 h post injection (p.i.) of the tracer. For the in vivo competitive binding assay, mice were sacrificed 48 h p.i. Blood was immediately collected via cardiac puncture. Select organs were harvested, rinsed and dried to remove excess water. Bound activity was measured using a gamma counter. Activity measurements were background- and decay-corrected to the time of counting. The tissue uptake, expressed as % injected dose per gram of tissue was calculated. Western blots and immunohistochemistry (IHC) validated the tumor uptake of the tracer.
|
study
| 100.0 |
Following PET imaging, tumors were excised, embedded in optimal-cutting-temperature mounting medium (OCT, Sakura Finetek), frozen on dry ice and series of 10 μm frozen sections cut. To determine radiotracer distribution, digital autoradiography was performed by placing tissue sections in a film cassette against a phosphor imaging plate (Fujifilm BAS-MS2325; Fuji Photo Film) at −20 °C for an appropriate exposure period. Phosphor imaging plates were read at a pixel resolution of 25 μm with a Typhoon 7000 IP plate reader (GE Healthcare). Contiguous frozen sections were then used for staining and microscopy. Sections were fixed with ice-cold acetone for 10 minutes and dried at room temperature for 10 minutes before re-hydration in tap water followed by PBS. Superblock (ThermoFisher) was used to block slides for 40 minutes at room temperature. Slides were incubated in primary antibodies HER3-XP (D22C5, Cell Signaling, 1:40) and EGFR-XP (D38B1, Cell Signaling, 1:50) overnight at 4 °C. Slides were developed using Pollink-2 Plus HRP rabbit with DAB (GBI Labs, D39–18) or Klear mouse HRP with DAB (GBI Labs, D52–18) and dehydrated with alcohols and xylenes before being covered with permount. Imaging was performed with a Nikon Eclipse Ci microscope (Nikon) using Spot Basic 5.2 software (Diagnostic Instruments, Inc). Images were analyzed in panoramic viewer 1.15.4 for windows (3D HisTech)58. IHC evaluation and scoring for EGFR59 and HER360 followed previously described protocols60.
|
study
| 99.9 |
Sequential 10 μm frozen sections cut from a fresh-frozen AsPC-1 tumor were incubated in binding buffer (0.1%BSA, 40 mg/L bacitracin in PBS, pH 7.4) containing 0.5–10 nM 89Zr-MEHD7945A for 1 h at room temperature in a humidified chamber. Non-specific binding was assessed on additional sections by the addition of 100-fold mole excess of cold MEHD7945A. Activity standards of each concentration with a known volume were spotted onto a flexible TLC sheet (Avantor Performance Materials, Center Valley, PA). Sections and standards were then exposed to a storage phosphor plate, and read as described above. Activity concentrations of whole tumor section areas and standards were determined using ImageQuant 7.0 software, and subsequently converted to a molar concentration using the tumor sectional area calculated from the image, multiplied by the 10 µm section thickness to determine volume. Binding parameters (Bmax, KD) were determined by non-linear regression in addition to Scatchard analysis.
|
study
| 100.0 |
Statistical analysis was performed using two-way ANOVA test in in vitro assays and tumor uptake comparison unless otherwise stated. A value of P < 0.05 was considered statistically significant. Data were expressed as the mean ± S.D. All analyses were performed using GraphPad PRISM v.6 software unless otherwise stated.
|
study
| 99.94 |
All data generated or analyzed during this study are included in this published article (and its Supplementary Information files). The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
|
other
| 99.94 |
The Wayne State University Institutional Animal Use and Care Committee (IACUC) approved all animal experiments during an ethical review. Principles of laboratory animal care were followed and all procedures were conducted according to guidelines established by the National Institutes of Health, and every effort was made to minimize suffering.
|
other
| 99.94 |
Coercion into treatment for substance use disorder (SUD) is practised throughout the world, and it has been the subject of a long-standing ethical debate . According to Klag (2006), critics of legal coercion argue that compulsory treatment may violate basic civil rights . Furthermore, they hold that autonomy should be safeguarded, because free will can provide psychological and therapeutic benefits. Another argument against coercion is that treatment can only be effective when the person is motivated and willing to change. In support of this view, many argue that substance users must hit “rock-bottom” before they are able to recognize that treatment provides benefits. However, others believe that some chronic drug users will not enter and remain in treatment unless they are coerced, and that professionals should have the authority to exercise that power. Still others believe that the authorities should play the role of a surrogate parent, and thus, they have an obligation to intervene on behalf of impaired citizens; this view assumes that, after recovery, patients will be grateful for the intervention .
|
review
| 99.8 |
Israelsson found that 73 of 90 countries worldwide provided some form of compulsory commitment (acute or rehabilitative). In all cases, compulsion was motivated by the intent to protect an otherwise legally capable individual in a self-destructive and vulnerable situation, due to substance use . Three main legislative domains, mental health care, social services, and criminal justice, have been described as the foundations for the mandated treatment of patients with SUDs. Civil commitment combines the first two legislative domains . Although most countries may direct one or more of these domains to offer assistance to patients with SUDs, not all countries provide assistance through all three legislative domains. In most cases, involuntary admission of patients with SUDs is a controversial option, which is implemented only after voluntary care has produced unsuccessful results [4–6].
|
review
| 99.8 |
The Norwegian Public Health Act (§10.2) permits involuntary interventions for adult patients with SUDs. The act includes an option to retain the patient for up to 3 months, when voluntary efforts are insufficient, and the health of the patient is seriously at risk, due to extensive, prolonged substance use. In Norway, patients with SUD, whether voluntarily admitted or involuntarily admitted, are often treated in a single ward, and they receive the same types of therapy. In the acute phase, the main goal of retention is to provide life-saving treatment. Over the longer term, the aim is to motivate patients to enter voluntary treatment and engage in long-term recovery .
|
other
| 99.9 |
Perceived coercion is defined as an individual’s perception of pressure to enter treatment, in this instance for drug and alcohol problems . This pressure may be sensed from sources that are either external or internal to the person. Most previous studies compared various treatment indicators between patients legally mandated to treatment and patients voluntarily committed to treatment. It was previously shown that patients that were admitted voluntarily often experienced informal pressures to enter treatment . Interviews with patients suggested that perceptions of informal coercion were common. The rate of perceived coercion tends to increase with increasing illness severity [9, 10]. Thus, it is simplistic to distinguish patients based only on their formal status (admitted involuntarily or admitted voluntarily), because this classification lacks the complexity of the coercion construct. Furthermore, the formal status classification fails to consider that individuals with drug or alcohol problems are exposed to a wide range of pressures to enter treatment that are not necessarily of a legal nature, including pressures from family, friends, healthcare professionals, or employers [11–13]. From the patient’s point of view, and based on daily law practice, the distinction between voluntary and involuntary admissions may often be ambiguous. Moreover, it is not certain that a legal mandate always causes the patient to feel coerced into treatment or that patients who are self-referred never feel coerced. Due to their condition, some patients may be quite ambivalent about their need for treatment. In other instances, patients may wish to enter voluntary treatment, but do not qualify, or for some reason cannot be offered treatment; then, they are actually relieved to receive mandated treatment [2, 8, 11]. It is important to gain a better understanding of the factors that influence the perceptions of coercion among patients with SUD that are admitted either involuntarily or voluntarily, by comparing these two formally different approaches to treatment. Understanding the coercive forces that contribute to patients entering treatment will provide valuable insight for improving treatment and the overall rehabilitation process. This information also has potential value in addressing multiple issues faced by the treatment provider, the legal system, and policy makers .
|
review
| 99.3 |
The present study aimed to investigate the role that perceived coercion played among patients with SUD that entered treatment. We also aimed to clarify whether patients that were admitted involuntarily perceived coercion differently from those that were admitted voluntarily, and to identify factors that could predict perceived coercion.
|
study
| 100.0 |
This study compared two groups of patients admitted to SUD and psychiatry wards: those admitted involuntarily (IA group) and those admitted voluntarily (VA group). Patients in the IA group were recruited from three publicly funded treatment centres in the south-eastern part of Norway. These centres are located in Kristiansand, Tønsberg, and Oslo, and they have four, four, and three beds, respectively, for patients admitted involuntarily. All patients in the VA group were from a single ward in the Kristiansand centre. The three wards are organized quite similarly. They all treat patients of both genders, but most patients were males. The patients may spend time in communal areas, but the exterior doors are locked. Most patients are allowed to leave the ward, when accompanied by a representative from the staff. Many patients received visits from friends and family. Both as a routine procedure and due to suspicion, the patients are required to undergo a urine test for drug-screenings. All wards were multidisciplinary (psychiatrists, psychologists, social workers, occupational therapists, specialized nurses, and other trained staff) and had specialized units that offered treatment for patients with primary SUD combined with mental disorders, a combination which is often observed. Treatment included assessments of somatic and mental health; diagnoses, based on a structured interview and examination, consistent with the International Classification of Diseases and Related Health Problems, 10th Revision (ICD-10); pharmacotherapy; cognitive milieu therapy; and individual motivation enhancement. The patient population was recruited mainly from urban and suburban areas.
|
study
| 99.94 |
Recruitment for the study continued consecutively from 1 January 2009 to 17 December 2011. The criteria for inclusion were: substance abuse or dependence, age ≥18 years, good understanding/speech in Norwegian language, and at least 3 weeks of hospital residence after admission. Approximately 150 decisions are made yearly in Norway concerning the involuntary admission of patients with SUD into institutions, pursuant to the Public Health Act .
|
study
| 99.94 |
Before inclusion, patients in both the IA and VA groups were in a detoxified state, verified with negative urine tests for alcohol, opioids, central stimulants (amphetamines, methamphetamines, and cocaine), benzodiazepines, and cannabis. Patients with positive urine tests spent a minimum of 14 days in detoxification to establish baseline values that were not influenced by withdrawal symptoms. Patients were excluded when they exhibited mental retardation (IQ < 70) that prevented them from understanding the questionnaires. Pregnant patients with SUD were treated in specialized wards, and were not included in this study.
|
study
| 99.94 |
We identified 103 consecutive patients that were admitted involuntarily. Among these, 15 did not meet the inclusion criteria (12 patients stayed for an insufficient time period, and 3 patients had insufficient mental capacity); 11 patients were not asked to participate, due to logistical issues. Of the 77 patients eligible for inclusion, 12 patients refused to participate. Therefore, the rate of consent to participate was 84% (65/77 patients). Due to missing scores on the Perceived Coercion Questionnaire (PCQ), two patients were not included in the final analyses. The 63 patients included in the IA group were distributed among three treatment centres: 39 in Kristiansand, 16 in Tønsberg, and 8 in Oslo. We identified 223 patients that were admitted voluntarily; 72 were excluded (69 patients stayed for insufficient time periods, and 3 patients lacked sufficient mental capacity). Of the remaining 151 eligible patients, 14 patients refused to participate. Therefore, the rate of consent in the VA group was 91% (137/151 patients). However, due to missing PCQ scores, eight patients were not included in the final analyses.
|
study
| 100.0 |
The study was approved by The Regional Committee for Research Ethics in Norway (REK 08/206d, 2008/2900, 09/2413) and by the Privacy Issues Unit, Norwegian Social Science Data Services (NSD no. 18782). Written informed consent was obtained from all study participants.
|
other
| 99.94 |
The ICD-10 was used to diagnose current SUDs, the current type and severity of psychiatric problems, and the level of functioning . All patients were interviewed with a clinical psychiatric examination, supported by the Mini International Neuropsychiatric Interview (MINI) version 2005. The MINI is a short psychiatric interview for the assessment of psychiatric disorders, which is in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition and ICD-10 classification systems . This interview has high acceptance and validity [17, 18]. Interviews were conducted by senior psychiatrists and psychologists with several years of clinical and research experience in the psychiatric assessment of patients with physical disorders. Severe SUD was indicated by the injection of illicit drugs within 6 months before admission and a high lifetime frequency of overdoses.
|
study
| 95.6 |
Sociodemographic variables were measured with the European Addiction Severity Index. This personal, structured interview was designed for both clinical and research purposes. It focuses on seven areas: medical status, employment and support status, drug and alcohol use, legal status, family history, family and social relationships, and psychiatric status . Trained and certified staff performed all European Addiction Severity Index-based interviews.
|
study
| 99.94 |
The Symptom Checklist-90-R instrument was used to evaluate the range of psychological problems and symptoms of psychopathology. This test contains 90 items, which measures nine primary symptom dimensions, and it provides an overview of a patient’s symptoms and symptom intensity. Each of the 90 items is rated on a five-point Likert-type scale, ranging from ‘not at all’ (0 points) to ‘extremely’ (4 points); higher values indicate greater symptom severity during the past week. The Global Symptom Index score was used to assess the level of general psychological distress .
|
study
| 99.94 |
The PCQ was developed specifically for patients undergoing addiction treatment. The PCQ includes six subscales (Self, Family, Legal, Finance, Health, and Work). Five out of the six subscales measure external coercion to participate in a substance-abuse treatment programme. The sixth subscale, Self, measures an internal form of perceived coercion or pressure. For example, item #1 is, ‘I feel pressure to participate in this drug/alcohol treatment programme…because I know that I’m an addict/alcoholic and that I need rehab to get off drugs/alcohol,’ and #3 is ‘I feel pressure to participate in this drug/alcohol treatment programme…because I feel horrified and ashamed of the person I have turned into’. The PCQ instrument contains 30 items that are presented in the form of statements (see Additional file 1). Respondents rate each statement with a 5-point scale (1, strongly disagree; 2, somewhat disagree; 3, neither agree nor disagree; 4, somewhat agree; 5, strongly agree). A higher score implies a greater degree of coercion perceived by the respondent . Klag et al. (2006) reported that the PCQ has acceptable divergent validity. The validity was demonstrated by a negligible relationship between the PCQ and a presumably unrelated measure (i.e., a measure of spirituality), where the overall r was 0.04 and r values for PCQ subscales were 0.03–0.10) . A previous analysis of PCQ reliability indicated that the subscales showed adequate internal consistency (Cronbach’s alpha: 0.66–0.87) and good total internal consistency (Cronbach’s alpha: 0.87) . To validate the PCQ in the new setting, we undertook an exploratory factor analysis. First, three items were removed from the PCQ, based on a pre-test of the scale and the notion that these items seemed irrelevant in a Norwegian setting (see Additional file 1). We proceeded to examine whether the remaining items yielded a factor structure similar to that of the original version and whether each item had sufficient factor loadings on its respective subscales. The analysis included principal axis and oblique rotation methods (promax). Kaiser’s eigenvalue-greater-than-one rule was used to determine the number of factors . To ensure internal validity for the present study and to obtain the most parsimonious model, problematic items were removed when they had low factor loadings (<0.4) or did not work as intended. As a result of this analysis, we removed two items in the health subscale. One item was removed, because it represented an extra (seventh) subscale, which constituted a single item only (probably an overfactoring issue: this scale barely exceeded the eigenvalue-of-one criteria). The other item was removed, because it had a low factor loading (see Additional file 1). After these amendments, the scale factors were similar to those in the original scale, and all items had factor loadings > 0.4 on their respective subscales. Based on the PCQ scale results, we divided the patients into two groups: patients that did not perceive any form of coercion and patients that perceived some form of coercion (agreed or strongly agreed) on one or more of the subscales.
|
study
| 100.0 |
Continuous variables are reported as the mean and standard deviation. Categorical variables are reported as the frequency. Independent sample t-tests, the chi-squared test, and Fisher’s exact test were used to detect statistically significant differences between groups. The threshold for statistical significance was p < 0.05. Linear regression was performed to identify factors that were associated with the PCQ score. Results are presented as β-values with 95% confidence intervals (95% CI) . Analyses were performed with SPSS 22.0 software (SPSS Inc., Chicago, IL, USA).
|
study
| 100.0 |
We detected several significant differences between the IA and VA groups (Table 1). All patients met the ICD-10 criteria for current substance dependence or abuse. During the 6 months before admission, significantly more patients in the IA group had injected illicit drugs and at a higher frequency than patients in the VA group. In addition, patients admitted involuntarily had experienced more overdoses during their lifetime compared with patients admitted voluntarily. However, the burden of psychological symptoms (Symptom Checklist-90-R and suicide attempts) was higher in the VA than in the IA group. Significantly more patients admitted involuntarily received ‘no mental diagnoses’, but among all patients with comorbid mental disorders, no significant differences were detected between the IA and VA groups regarding mental health diagnoses. There were significantly more female patients in the IA group than in the VA group (49% vs. 27%, respectively).Table 1Baseline sociodemographic variables and mental stress scores for patients with substance use disordersVariableIAVA P-valueAge, years, mean (SD)28.52 (10.6)30.43 (8.6)0.177Female, n (%)35 (27.1)31 (49)0.002Education Years in primary school and high school, mean (SD)10.58 (1.4)10.63 (1.6)0.848 Years in college and university, mean (SD)0.28 (0.9)0.18 (0.8)0.442Sources of financial supporta, b Employment, n (%)6 (10)21 (17)0.236 Public welfare benefits, n (%)57 (95)109 (86)0.064 Partner, family, or friends, n (%)17 (29)37 (30)0.916 Illegal activity, n (%)23 (40)45 (37)0.691Living arrangementb With partner, n (%)7 (12)11 (9)0.512 Alone, n (%)30 (52)57 (46)0.499 With family, n (%)9 (16)25 (20)0.440 No stable arrangements, n (%)9 (16)15 (12)0.539 In a controlled environment, n (%)2 (3)15 (12)0.060Treated by a physician for somatic diseasesb, n (%)23 (43)27 (23)0.015Injecting illicit drugb, n (%)42 (71)58 (46)0.001Alcoholic delirium tremensc, n (%)8 (14)15 (12)0.731Overdoses on drugsc, n (%)40 (70)61 (50)0.010Suicide attemptsc, n (%)21 (36)69 (56)0.015Mental stress score SCL-90-R GSI, mean (SD)1.00 (0.7)1.31 (0.7)0.004 Number of patients63129 Abbreviations: IA involuntarily admitted, VA voluntarily admitted, SD standard deviation, SCL-90-R GSI Symptom Check List-90-Revised, Global Symptom Index aSome participants had more than one source of financial support bLast 6 months before admission cLifetime prevalence
|
study
| 99.94 |
The PCQ was used to measure patient perception of external and internal pressures to receive treatment for drug and alcohol problems . Patients in both the IA and VA groups reported perceived coercion during the admission process. When categorizing the PCQ scale, we found that, overall, only 14% of patients admitted involuntarily did not report perceiving coercion on any of the subscales, and 92% of patients admitted voluntarily agreed or strongly agreed that they perceived coercion on one or more of the subscales. The Self and Health subscales reflected the strongest sources of perceived coercion (Fig. 1).Fig. 1Distribution of the types of coercion perceived by patients with substance use disorders. Patients that were involuntarily or voluntarily admitted for substance abuse treatment completed the Perceived Coercion Questionnaire. Perceived coercion was defined as a report of ‘Somewhat Agree’ or ‘Strongly Agree’ on one or more subscales of the questionnaire. Numbers within the bars indicate the percentage that corresponds to only one coloured portion of the bar. IA: involuntarily admitted group; VA: voluntarily admitted group
|
study
| 100.0 |
Distribution of the types of coercion perceived by patients with substance use disorders. Patients that were involuntarily or voluntarily admitted for substance abuse treatment completed the Perceived Coercion Questionnaire. Perceived coercion was defined as a report of ‘Somewhat Agree’ or ‘Strongly Agree’ on one or more subscales of the questionnaire. Numbers within the bars indicate the percentage that corresponds to only one coloured portion of the bar. IA: involuntarily admitted group; VA: voluntarily admitted group
|
other
| 99.3 |
The VA group experienced significantly higher levels of coercion than the IA group in two of the six subscales (Table 2). For example, the mean score for the items on the Self subscale was 0.5 point higher in the VA group (3.3 versus 3.8 for the IA and VA groups, respectively). Closer examination of the Self subscale revealed that the VA group scored higher on three items: ‘Entering this programme is my last and only hope’; ‘I feel horrified and ashamed of the person I have turned into’; and ‘I am sick and tired of losing everything (things, people etc.) because of my drug/alcohol problem’ (Table 3). Notably, only 2/3 of the IA group agreed or strongly agreed with the assertion ‘I felt pressured to enter this drug/alcohol treatment programme, because I was legally required’. Paradoxically, some (12%) of the patients admitted voluntarily agreed or strongly agreed to that same assertion. In the linear regression model, we found that only the Global Score Index of the Scl-90-R was significantly associated with perceived coercion; however, this factor explained only 3% of the variance in the PCQ (Table 4).Table 2Perceived Coercion Questionnaire (PCQ) scoresVariableInvoluntarily admittedVoluntarily admitted P-valueSelf subscale16.7 (5.0)18.9 (4.4)0.003Family subscale15.5 (6.0)15.0 (6.4)0.555Legal subscalea 5.6 (2.2)3.1 (2.1)0.001Finance subscale12.8 (5.5)13.8 (5.9)0.259Health subscaleb 10.3 (3.5)11.2 (3.1)0.076Work subscale9.2 (5.2)10.1 (5.1)0.256Total PCQ76.2 (18.9)78.0 (18.5)0.536Number of patients63129Values represent the mean (standard deviation) aThe Legal subscale of the PCQ underwent minor revisions to account for differences in the Norwegian legal system (see Additional file 1) bThe Health subscale of the PCQ has been validated, but it was altered for the present study (see Additional file 1) Table 3Scores for the Perceived Coercion Questionnaire Self subscaleSelf subscaleIAVA P-valueSelf subscale, total score16.7 (5)18.9 (4)0.003I know that I’m an addict/alcoholic and that I need rehab to get off drugs/alcohol4.0 (1)4.3 (1)0.132Entering this programme is my last and only hope2.8 (1)3.3 (1)0.023I don’t know where else to go and what else to do3.0 (1)3.4 (1)0.053I feel horrified and ashamed of the person I have turned into3.2 (1)3.7 (1)0.013I am sick and tired of losing everything (things and people) to my drug/alcohol problem3.7 (1)4.2 (1)0.012Number of patients63129All values represent the mean (standard deviation); IA involuntarily admitted group, VA voluntarily admitted group Table 4Multivariable linear regression analysis results show the effects of independent variables on perceived coercion. N = 192 patientsVariableBeta (95 % CI) P-valuea R2c Female gender−0.13 (−11.16–1.07)0.117Age−0.09 (−0.50–0.12)0.441Living alone−0.01 (−5.80–5.57)0.713Global Score Index: Scl-90-R0.19 (0.82–9.35)0.0153 %Severity scores Injected drug abuse0.01 (−5.99–6.09)0.720 Drug overdoses (lifetime)0.10 (−2.85–9.99)0.970 Suicide attempts (lifetime)−0.10 (−6.84–5.40)0.340Treatment variable Treated for somatic diseasesb 0.12 (−1.39–11.12)0.113 Involuntary hospital admission−0.03 (−7.90–5.43)0.536 a p-value obtained from bivariate linear regression. Only one independent variable showed a p-value <0.20 in bivariate analyses bDuring the 6 months prior to admission c R2 adjusted = squared correlation coefficient to obtain a measure of explained variance
|
study
| 100.0 |
This study investigated perceived coercion among patients with SUD that were admitted either involuntarily or voluntarily to receive inpatient hospital treatment. The VA group showed significantly higher scores than the IA group on the internal sources of perceived coercion (Self subscale). No individual characteristics or independent variables were identified that affected perceived coercion in any clinically significant magnitude. Despite the different legal statuses of these groups upon admission to the hospital, the IA group did not report more perceived coercion, overall.
|
study
| 100.0 |
Many clinicians are reluctant to invoke coerced SUD treatment. For some, concern about patient autonomy is the primary deterrence to using coercive treatment, even when the individual’s autonomy is clearly compromised by the cognitive and neurobiological effects of alcohol or substance abuse . In modern bioethics, autonomy is considered one of the overarching ethical principles for protecting patients’ liberties and the right to make their own decisions, for better or worse . Coercion into SUD treatment is commonly equated with a legal mandate. This assumption gives rise to the view that patients referred to treatment by the legal system are coerced, and thus, they must enter against their will. In contrast, individuals that enter without a legal mandate are thought to participate in therapy freely and voluntarily . Our findings supported the view that these assumptions may represent an oversimplification. As expected, patients admitted involuntarily scored significantly higher on the Legal subscale than the patients admitted voluntarily. However, we found that some (14%) patients admitted involuntarily did not report the perception of coercion on any of the PCQ subscales, despite the legal status of their admission. Conversely, 92% of the patients admitted voluntarily agreed or strongly agreed that they perceived coercion, on one or more of the PCQ subscales. Apart from the Legal subscale, we found no significant differences between the IA and VA groups that evidenced greater perceived pressure to enter treatment. However, the VA group reported higher perceived pressure to enter treatment due to internal pressure (Self subscale) than the IA group; this finding indicated that the VA group had greater insight into their own problems, compared to the IA group.
|
study
| 99.94 |
Other studies have suggested that the patients’ experiences of coercion during the admission process in mental hospitals did not necessarily correspond to their legal status [5, 8, 23, 25]. In the present study, we also noted confusion among patients legally required to undergo treatment; 1/3 did not perceive that they were legally required to enter treatment. This misperception of legal status may have been influenced by the fact that, in our study, most of the patients admitted involuntarily stayed in the same wards as the patients admitted voluntarily, and the groups were treated almost equally. Additionally, the Norwegian approach to coercion is largely focused on rehabilitation, motivation, and treatment. Potentially, this premise of the law might influence the attitudes of the professionals involved in this type of treatment. One might speculate that this rehabilitative perspective might be more difficult to find among professionals in countries where coerced measures are guided more often by criminal law and traditions .
|
study
| 99.94 |
In coercion studies, it is common to analyse different types of perceived coercion, based on whether the source was external or internal. External coercion is used to motivate the patient to comply with SUD treatment by enforcing alternative consequences, such as a loss of employment or a loss of parental custody. Within the family setting, the consequences of refusing treatment may be broken relationships or the withdrawal of financial or emotional support by family members . An example of an informal type of coercion used to compel a patient to enter treatment is exemplified by the Johnson Intervention. This intervention is a therapeutic technique where the patient’s family or a social group confronts the patient with the consequences of continuous drinking or drug use . This approach is considered coercive, because the family members and friends set forth the consequences of continued drug use, namely certain losses that the individual will face, and these are contrasted with the outcome of SUD treatment. In the present study, both the IA and the VA groups perceived coercion from external sources. The most prominent of the external pressures seemed to arise from family and health-related issues, indicated by the higher scores on these subscales than on the financial and work subscales. The relatively low focus on financial and work issues might be related to the fact that Norwegian health and social welfare systems guarantee at least some level of welfare benefits to patients with SUD conditions. Compared to Klag’s study cohort of Australian patients in residential treatment within a therapeutic community setting, both our patient groups experienced a lesser degree of coercion (Australian vs. IA/VA: Family subscale 18.0 vs. 15.5/15.0; Finance subscale 14.28 vs. 12.8/13.8; and Work subscale 12.37 vs. 9.2/10.1) .
|
study
| 99.94 |
The Self subscale of the PCQ consisted of five items intended to measure how internal sources were perceived to coerce individuals into engaging in substance-abuse treatment. Both the IA and VA groups reported higher scores of perceived coercion from internal sources than from external sources, and scores were significantly higher in the VA group than in the IA group. Severe internal pressure (hitting rock bottom) often spurs people into treatment. All the questions on this subscale were related to this concept; consequently, it was not surprising that the internal domains distinguished individuals that sought voluntary treatment from those admitted involuntarily. The authors of the scale noted that “Given the complexity and multitude of pressures that [individuals with SUD] experience, it is reasonable to assume that further sub-categorization of the Self subscale might result in a more reliable and valid measure of the internal pressures that contribute to seeking treatment ”. Compared to the Australian patients in residential treatment within a therapeutic community , we found that both the IA and VA groups in our study perceived lower levels of coercion from internal sources (Australian vs. IA/VA: Self subscale 21.7 vs. 16.7/18.9).
|
study
| 100.0 |
One argument against invoking the legal coercion act more often in Norway is the notion that patients that perceive coercion would not be motivated to accept treatment. Some researchers hold that, for patients with SUD, the perception of coercion may influence the motivation for treatment, which in turn, was found to influence the patient’s perseverance with treatment and the treatment outcome . Thus, treatment can be effective only when the person is truly motivated, i.e., wants to change. A variation of this position holds that people that are addicted to substances must ‘hit rock bottom’ before they can benefit from treatment [27, 28]; however, this circumstance is not necessarily true for many patients coerced into treatment. According to this view, it is a poor investment to devote resources to patients that are unlikely to change, because they have little or no motivation to change. This argument leads to the empirical question of whether patients that are coerced into treatment lack recognition of their problem, and therefore, have no desire to change . In the present study, we found that the VA group scored higher than the IA group on the Self subscale, indicating that these patients might have had more insight into their own situation. Thus, the VA group could more readily admit and accept that they needed help. Nevertheless, the IA group also scored high on the Self subscale. This suggested that the IA patients also had some insight into their problems. These findings supported the notion that a less motivated patient admitted involuntarily may be able to benefit from the stay on the ward, in ways similar to the benefits observed among the patients admitted voluntarily. When Sullivan compared the Johnson Intervention method of referral to outpatient treatment, the coerced groups were more likely to complete treatment than non-coerced groups .
|
study
| 99.94 |
We could not identify any individual characteristics or independent variables that affected perceived coercion in a clinically significant manner, including patient legal status. This result contrasted with findings in other studies that focused on perceived coercion. Previous studies identified male gender, younger age, and illegal drug use as factors associated with higher levels of perceived coercion [2, 30]. This discrepancy might be explained by differences in the criteria for coercion; in Norway, these criteria are very strict; therefore, the selection procedure may have reduced the heterogeneity of the group.
|
study
| 99.94 |
The findings and conclusions of this analysis must be considered in light of some study limitations. Of note, this study was conducted in a country with a high average income. In addition, due to differences in legislation and practices in different countries and intangible variations in patient expectations and experiences, extrapolations of our findings to other settings are likely to involve complex interpretations. The first limitation was that our data on background characteristics and perceived coercion were self-reported. However, self-reporting should not have a major impact on standard background variables, and it should not affect the ratings of perceived coercion, because they are intended to measure self-perception. Second, the individuals studied in this analysis were selected to represent the general SUD treatment population; however, this sample may also be representative of all Norwegian patients. This patient selection should not differ from patients selected in other countries that apply civil commitment when entering treatment under some form of legal pressure; however, our sample may not necessarily be representative of patients in countries that practice only criminal justice acts. Finally, the relatively small sample size may have limited our power to detect important associations of clinical significance.
|
study
| 100.0 |
The main strength of this study was that it was the first to study experiences of coercion among patients with SUD, despite the fact that this law was established more than 20 years ago in Norway. This study highlighted the patients’ personal views on whether they were forced to undergo SUD treatment, irrespective of their legal status. This type of research is important because it sheds light on the processes that patients with SUD undergo, when the society invokes coercive laws with a rehabilitative purpose. More nuanced research is needed to understand how the patient’s perception of coercion is related to the motivation to enter treatment. An important topic for future research is the relationship between objective and perceived coercion.
|
study
| 99.94 |
Although the PCQ is considered a valid scale for the present setting, our amendments of the scale preclude comparison with other studies, both for the total PCQ score and for the altered subscales. However, the present study did not aim to conduct a cross-cultural comparison; therefore, we chose to focus on internal validity in the present setting.
|
study
| 99.94 |
Patients in both the IA and VA groups perceived some level of coercion to enter into treatment for SUDs. The VA and IA groups experienced similar overall levels of perceived coercion, but the VA group reported higher levels of perceived coercion from internal sources (Self subscale). As expected, the IA group scored significantly higher on the Legal subscale. All patients with SUD, whether involuntarily or voluntarily admitted, experienced high levels of perceived coercion that was unrelated to the law. Internal sources of perceived coercion were dominant in both groups.
|
study
| 99.94 |
Understanding the coercive forces that compel patients to enter treatment will provide valuable insight into ways to improve treatment and the overall process of patient rehabilitation. The information obtained here has potential value in addressing multiple issues for the treatment provider, the legal system, and policy makers, alike. For example, for therapists, a better understanding is important in treatment planning and in monitoring patient progress. Patients that feel pressured to be in treatment by external sources could receive interventions that reduce those pressures; this intervention might thereby increase the patient’s motivation to engage in treatment. Therefore, we anticipate that treatment providers might find it useful to implement the PCQ as part of their assessment.
|
other
| 99.9 |
Every clinical encounter includes a potential element of coercion and hierarchy; these components may be inescapable in any relationship between patients and healthcare personnel. However, knowledge of factors that lead to perceived coercion may elucidate ways to limit these components. The observations presented in this study indicated that, when a coerced admission is planned, information and collaboration with the patient will likely facilitate a better experience during admission and treatment for the patients, and thereby, a better process towards recovery. The findings of this study may yield new insights for healthcare professionals and policy makers.
|
study
| 99.6 |
The relationship between patients chosen for surgical therapy and their outcome in relation to economic, insurance, partnership, and racial issues has been infrequently studied. A recent retrospective study using the VA Central Cancer Registry in stage I/II non-small cell lung cancer (NSCLC) from 2001 to 2010 demonstrated that the disparity between Blacks and Whites receiving an operation decreased to similar rates during this time period. Furthermore, there was no survival difference between Black and Whites undergoing an operation, and no lung cancer-specific survival (LCSS) differences between races (2). Using data compiled from 38 state and the District of Columbia population-based cancer registries compiled by the North American Association of Central Cancer Registries, Sineshaw et al. demonstrated that the receipt of curative-intent surgery varied by state and was lower in blacks than whites in every state (statistically significant in Texas and Florida) (3). Similarly, using the Surveillance Epidemiology and End Reporting (SEER) database from 2007 to 2012, Taioli and Flores noted that even after adjusting by age and insurance status, blacks were less likely to receive surgery, but more likely to receive radiation than white patients (4). However, none of these studies evaluate race in relation to economic, marital, and insurance variables. Nor have these reports analyzed differences in outcome in the many different ethnic groups who are found in the United States.
|
review
| 99.25 |
Because lung cancer screening was shown to be of benefit in 2011 (5) and was approved by CMS in 2015, early-stage resectable (ESR) NSCLC is expected to increase and result in more lung cancer survivors (6). Therefore, assessing the presentation and outcomes of patients undergoing surgery for NSCLC and inter-relationship of ethnicity in regards to marital, economic, histologic, treatment, and insurance variables will be increasingly important.
|
other
| 98.7 |
The purpose of our study is to investigate the presenting characteristics of patients undergoing a definitive surgical procedure in nine different ethnic groups [White non-Hispanic (White), Black, White Hispanic (Hispanic), American Indian/Alaskan native (AI/AN), Chinese, Japanese, Other Asian, South Asian, and Other Race] and to assess prognosis and 90-day mortality for all surgical patients and for those presenting with early-stage, resectable tumors (ESR, <4 cm without involved nodes). The prognostic importance of race will be determined in a multivariate model that adjusts for known histopathologic and patient-related factors as well as income, marital status, and insurance.
|
study
| 99.94 |
Data for this study were taken from the SEER program of the National Cancer Institute, which started to collect and publish cancer incidence and survival data from population-based cancer registries in 1973. The “SEER-18” database used in this study includes registries in Atlanta, Connecticut, Detroit, Hawaii, Iowa, New Mexico, San Francisco-Oakland, Seattle-Puget Sound, Utah, Los Angeles, San Jose-Monterey, Rural Georgia, Greater California, Kentucky, Louisiana, New Jersey, Greater Georgia, and the Alaska Native Tumor Registry (7). Data are available from all cases diagnosed from 2000 and later for these registries. The SEER 18 sites cover approximately 28% of the American population (7).
|
study
| 99.94 |
Outcome and presenting characteristics were examined for all surgical patients (TS) (N = 35,689) and patients with presenting with ESR disease (N = 17,931) for whom sufficient information was collected to assess the outcome of treatment in relation to patient, economic, histopathologic, and insurance variables. Patients included in this investigation had NSCLC as their first primary cancer. Only microscopically confirmed tumors using NSCLC codes (8012-8014,8022,8031-8033,8046,8052,8070-8073,8082,8084,8123,8140,8200,8230,8250-8255,8260,8310,8333,8430,8470,8480-8481,8490,8550,8560,8972,8980) were included in this study.
|
study
| 100.0 |
Only patients undergoing a definitive surgical procedure without pre-operative radiation were included in this analysis. The surgical procedures defined as definitive were as follows: sublobar resection (sublobar resection; segmental resection, including lingulectomy; or wedge resection); and lobectomy or greater (lobectomy or bi-lobectomy, with or without extension to include the chest wall; lobectomy with mediastinal node dissection; extended lobectomy or bi-lobectomy, not otherwise specified; pneumonectomy with mediastinal node dissection; or pneumonectomy, not otherwise specified).
|
study
| 99.94 |
The outcome variables were overall survival (OS) and LCSS. Deaths from other causes were treated as censoring events. The main purpose of our investigation was to examine whether there are differences in presenting characteristics and outcomes in nine different ethnic groups by examining marital status, household income (<$50,000; $50–$74,999; >$75,000), type of insurance (insured, Medicaid, uninsured, unknown) in addition to established histopathologic and patient factors. Household income was listed in the SEER registry by median household income per county. The population was split into nine different ethnic groups as follows: White non-Hispanic (White), Black, White Hispanic (Hispanic), AI/AN, Chinese, Japanese, South Asian (Asian Indian and Pakistani), Other Asian (Filipino, Thai, Vietnamese, Korean, Kampuchean, Laotian, and Hmong), and Other Race (OR, Chamorran, Fiji Islander, Guamanian, Hawaiian, Melanesian, Micronesian, New Guinean, Pacific Islander, Polynesian, Samoan, Tahitian, Tongan, unknown, and other) in both the entire lung cancer surgical population as well as those presenting with ESR disease. We originally wanted to include black Hispanic patients as a separate patient category in this manuscript and its companion study assessing ethnic differences in all lung cancer patients and those with Stage IV disease, but since we wanted similar populations in both studies and because the number of Black Hispanic patients was scant in both the TS population and the ESR groups, we decided to include Black Hispanic patients in the Black category, similar to a past study (8). Black Hispanic patients represented approximately 0.6% of patient group undergoing surgical resection (19/3,276). Throughout this manuscript, the term population(s) will refer to total population of surgical patients (TS) and those with ESR disease, while group(s) will refer to the nine different ethnicities.
|
study
| 99.94 |
Variables examined for their potential effect on outcome were gender; age; year of diagnosis; marital status; race; ethnicity; tumor stage; t-stage, n-stage; nodes examined; nodes positive; node density (number of nodes positive/number of nodes examined); tumor size; histology; grade; SEER registry location; median family income; resection type; post-operative radiation; and tumor location. Median follow-up time was calculated by the methods of Schemper and Smith in which death becomes a censored follow-up time and was noted to be 36 and 35 months in the TS and ESR groups, respectively (9).
|
study
| 100.0 |
Chi-square and t-test were used to compare difference between the ethnic groups with respect to treatment, patient characteristics, and tumor characteristics. Cox proportional hazards models estimates (10) were used to calculate adjusted hazard ratios with their 95% confidence intervals, and to show how treatment and other covariates were related to OS and LCSS. Medicare eligibility was controlled through use of two strata for age at diagnosis (≥65 vs <65 years old) because individual cases will change when they enroll in Medicare. The cox proportional hazards assumption was checked by visual examination of survival plots.
|
study
| 100.0 |
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