31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration

PURPOSE

The DecisionDx-Melanoma 31-gene expression profile (31-GEP) test is validated to classify cutaneous malignant melanoma (CM) patient risk of recurrence, metastasis, or death as low (class 1A), intermediate (class 1B/2A), or high (class 2B). This study aimed to examine the effect of 31-GEP testing on survival outcomes and confirm the prognostic ability of the 31-GEP at the population level.

METHODS

Patients with stage I-III CM with a clinical 31-GEP result between 2016 and 2018 were linked to data from 17 SEER registries (n = 4,687) following registries' operation procedures for linkages. Melanoma-specific survival (MSS) and overall survival (OS) differences by 31-GEP risk category were examined using Kaplan-Meier analysis and the log-rank test. Crude and adjusted hazard ratios (HRs) were calculated using Cox regression model to evaluate variables associated with survival. 31-GEP tested patients were propensity score-matched to a cohort of non-31-GEP tested patients from the SEER database. Robustness of the effect of 31-GEP testing was assessed using resampling.

RESULTS

Patients with a 31-GEP class 1A result had higher 3-year MSS and OS than patients with a class 1B/2A or class 2B result (MSS: 99.7% v 97.1% v 89.6%, P < .001; OS: 96.6% v 90.2% v 79.4%, P < .001). A class 2B result was an independent predictor of MSS (HR, 7.00; 95% CI, 2.70 to 18.00) and OS (HR, 2.39; 95% CI, 1.54 to 3.70). 31-GEP testing was associated with a 29% lower MSS mortality (HR, 0.71; 95% CI, 0.53 to 0.94) and 17% lower overall mortality (HR, 0.83; 95% CI, 0.70 to 0.99) relative to untested patients.

CONCLUSION

In a population-based, clinically tested melanoma cohort, the 31-GEP stratified patients by their risk of dying from melanoma.

Optimizing treatment approaches for patients with cutaneous melanoma by integrating clinical and pathologic features with the 31-gene expression profile test

BACKGROUND

Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher staged patients will not.

OBJECTIVE

To develop an algorithm by integrating the 31-gene expression profile test with clinicopathologic data for an optimized, personalized risk of recurrence (integrated 31 risk of recurrence [i31-ROR]) or death and use i31-ROR in conjunction with a previously validated algorithm for precise sentinel lymph node positivity risk estimates (i31-SLNB) for optimized treatment plan decisions.

METHODS

Cox regression models for ROR were developed (n = 1581) and independently validated (n = 523) on a cohort with stage I-III melanoma. Using National Comprehensive Cancer Network cut points, i31-ROR performance was evaluated using the midpoint survival rates between patients with stage IIA and stage IIB disease as a risk threshold.

RESULTS

Patients with a low-risk i31-ROR result had significantly higher 5-year recurrence-free survival (91% vs 45%, P < .001), distant metastasis-free survival (95% vs 53%, P < .001), and melanoma-specific survival (98% vs 73%, P < .001) than patients with a high-risk i31-ROR result. A combined i31-SLNB/ROR analysis identified 44% of patients who could forego sentinel lymph node biopsy while maintaining high survival rates (>98%) or were restratified as being at a higher or lower risk of recurrence or death.

LIMITATIONS

Multicenter, retrospective study.

CONCLUSION

Integrating clinicopathologic features with the 31-GEP optimizes patient risk stratification compared to clinicopathologic features alone.

Expanded evidence that the 31-gene expression profile test provides clinical utility for melanoma management in a multicenter study

OBJECTIVE

National Comprehensive Cancer Network (NCCN) guidelines for cutaneous melanoma (CM) recommend physicians consider increased surveillance for patients who typically have lower melanoma survival rates (stages IIB-IV as determined by the American Joint Committee on Cancer (AJCC), 8th edition). However, up to 15% of patients identified as having a low recurrence risk (stages I-IIA) experience disease recurrence, and some patients identified as having a high recurrence risk will not experience any recurrence. The 31-gene expression profile test (31-GEP) stratifies patient recurrence risk into low (Class 1) and high (Class 2) and has demonstrated risk-appropriate impact on disease management and clinical decisions.

METHODS

Five-year plans for lab work, frequency of clinical visits, and imaging pre- and post-31-GEP test results were assessed for a cohort of 509 stage I-III patients following an interim subset analysis of 247 patients.

RESULTS

After receiving 31-GEP results, 50.6% of patients had a change in management plans in at least one of the following categories-clinical visits, lab work, or surveillance imaging. The changes aligned with the risk predicted by the 31-GEP for 76.1% of patients with a Class 1 result and 78.7% of patients with a Class 2 result. A Class 1 31-GEP result was associated with changes toward low-intensity management recommendations, while a Class 2 result was associated with changes toward high-intensity management recommendations.

CONCLUSION

The 31-GEP can stratify patient recurrence risk in patients with CM, and clinicians understand and apply the prognostic ability of the 31-GEP test to alter patient management in risk-appropriate directions.

Validation of the 31-gene expression profile test to stratify melanoma-specific survival in an unselected, prospectively tested cohort of patients with stage IIB-III cutaneous melanoma

e21538

Background: Given recent FDA extended approval of Pembrolizumab for stage IIB-IIC cutaneous melanoma (CM) patients, it is critical to risk-stratify patients to balance potential benefits versus toxicities of adjuvant therapy. The 31-gene expression profile (31-GEP) is a validated test for CM for risk of recurrence or metastasis prognosis in patients with stage I-III CM. A low-risk (Class 1A) 31-GEP result is associated with lower recurrence risk and higher melanoma-specific survival than an intermediate (Class 1B/2A) or high-risk (Class 2B) result. To validate the 31-GEP’s ability to stratify patients’ risk in an unselected, prospectively tested cohort of therapy-eligible CM patients, we collaborated with the National Cancer Institute and the Surveillance, Epidemiology, and End Results (SEER) program. Methods: A linkage was conducted between SEER registries’ CM cases diagnosed 2012-2018, and 31-GEP tested patients between 2013-2020. A de-identified dataset was used for the analysis. Kaplan-Meier analysis with log-rank test was used to analyze patient melanoma-specific survival (MSS) in the overall cohort and the subset of patients with potential adjuvant therapy access: stage IIB-III melanoma (n = 615). Results: In the overall cohort of patients (N = 5,225), those with a 31-GEP Class 1A result had higher 3-year MSS than patients with a Class 2B result (99.7% vs. 90.4%, p < 0.001). In multivariable Cox regression analysis, a Class 2B result was an independent significant predictor of MSS (HR = 5.71, p = 0.01), as were age (HR = 1.05, p < 0.001), SLN positivity (HR = 2.42, p = 0.02), and T2b (HR = 8.29, p = 0.025) and T4b (HR = 11.99, p = 0.009) tumors. In the subset of patients with stage IIB-III melanoma, those with a 31-GEP Class 1A result had higher 3-year MSS (98.8% vs. 82.4%, p = 0.02) than patients with a Class 2B result. Patients with a Class 2B result had a five and a half times higher event rate than those with a Class 1A result for MSS (5.5% [21/382] vs. 1.0% [1/105]). Conclusions: In a large, unselected, prospectively tested cohort of patients with stage I-III CM, the 31-GEP stratified patient risk of dying from melanoma, validating previous studies. While the 31-GEP identified a subgroup (Class 1A) of traditionally high-risk patients (stage IIB-III CM) who had a > 98% MSS over three years, it can also facilitate identifying patients who could warrant earlier adjuvant therapy with a higher 31-GEP class designation.

Development and validation of a nomogram incorporating gene expression profiling and clinical factors for accurate prediction of metastasis in patients with cutaneous melanoma following Mohs micrographic surgery

BACKGROUND

There is a need to improve prognostic accuracy for patients with cutaneous melanoma. A 31-gene expression profile (31-GEP) test uses the molecular biology of primary tumors to identify individual patient metastatic risk.

OBJECTIVE

Develop a nomogram incorporating 31-GEP with relevant clinical factors to improve prognostic accuracy.

METHODS

In an IRB-approved study, 1124 patients from 9 Mohs micrographic surgery centers were prospectively enrolled, treated with Mohs micrographic surgery, and underwent 31-GEP testing. Data from 684 of those patients with at least 1-year follow-up or a metastatic event were included in nomogram development to predict metastatic risk.

RESULTS

Logistic regression modeling of 31-GEP results and T stage provided the simplest nomogram with the lowest Bayesian information criteria score. Validation in an archival cohort (n = 901) demonstrated a significant linear correlation between observed and nomogram-predicted risk of metastasis. The resulting nomogram more accurately predicts the risk for cutaneous melanoma metastasis than T stage or 31-GEP alone.

LIMITATIONS

The patient population is representative of Mohs micrographic surgery centers. Sentinel lymph node biopsy was not performed for most patients and could not be used in the nomogram.

CONCLUSIONS

Integration of 31-GEP and T stage can gain clinically useful prognostic information from data obtained noninvasively.

Improved cutaneous melanoma survival stratification through integration of 31-gene expression profile testing with the American Joint Committee on Cancer 8th Edition Staging

Cutaneous melanoma (CM) survival is assessed using averaged data from the American Joint Committee on Cancer 8th edition (AJCC8). However, subsets of AJCC8 stages I-III have better or worse survival than the predicted average value. The objective of this study was to determine if the 31-gene expression profile (31-GEP) test for CM can further risk-stratify melanoma-specific mortality within each AJCC8 stage. This retrospective multicenter study of 901 archival CM samples obtained from patients with stages I-III CM assessed 31-GEP test predictions of 5-year melanoma-specific survival (MSS) using Kaplan-Meier and Cox proportional hazards. In stage I-III CM population, patients with a Class 2B result had a lower 5-year MSS (77.8%) than patients with a Class 1A result (98.7%) and log-rank testing demonstrated significant stratification of MSS [χ2 (2df, n = 901) = 99.7, P < 0.001). Within each stage, 31-GEP data provided additional risk stratification, including in stage I [χ2 (2df, n = 415) = 11.3, P = 0.004]. Cox regression multivariable analysis showed that the 31-GEP test was a significant predictor of melanoma-specific mortality (MSM) in patients with stage I-III CM [hazard ratio: 6.44 (95% confidence interval: 2.61-15.85), P < 0.001]. This retrospective study focuses on Class 1A versus Class 2B results. Intermediate results (Class 1B/2A) comprised 21.6% of cases with survival rates between Class 1A and 2B, and similar to 5-year MSS AJCC stage values. Data from the 31-GEP test significantly differentiates MSM into lower (Class 1A) and higher risk (Class 2B) groups within each AJCC8 stage. Incorporating 31-GEP results into AJCC8 survival calculations has the potential to more precisely assess survival and enhance management guidance.

Analytical validity of DecisionDx-SCC, a gene expression profile test to identify risk of metastasis in cutaneous squamous cell carcinoma (SCC) patients

Background

To improve identification of patients with cutaneous squamous cell carcinoma (SCC) at high risk for metastatic disease, the DecisionDx-SCC assay, a prognostic 40-gene expression profile (40-GEP) test, was developed and validated. The 40-GEP assay utilizes RT-PCR gene expression analysis on primary tumor biopsy tissue to evaluate the expression of 34 signature gene targets and 6 normalization genes. The test provides classifications of low risk (Class 1), moderate risk (Class 2A), and high risk (Class 2B) of metastasis within 3 years of diagnosis. The primary objective of this study was to validate the analytical performance of the 40-gene expression signature.

Methods

The repeatability and reproducibility of the 40-GEP test was evaluated by performance of inter-assay, intra-assay, and inter-operator precision experiments along with monitoring the reliability of sample and reagent stability for class call concordance. The technical performance of clinical orders from September 2020 through July 2021 for the 40-GEP test was assessed.

Results

Patient hematoxylin and eosin (H&E) stained slides were reviewed by a board-certified pathologist to assess minimum acceptable tumor content. Class specific controls (Class 1 and Class 2B) were evaluated with Levey-Jennings analysis and demonstrated consistent and reproducible results. Inter-assay, inter-operator and intra-assay concordance were all ≥90%, with short-term and long-term RNA stability also meeting minimum concordance requirements. Of the 2586 orders received, 93.5% remained eligible for testing, with 97.1% of all tested samples demonstrating actionable class call results.

Conclusion

DecisionDx-SCC demonstrates a high degree of analytical precision, yielding high concordance rates across multiple performance experiments, along with exhibiting robust technical reliability on clinical samples.

Gene expression profiling for metastatic risk in head and neck cutaneous squamous cell carcinoma

OBJECTIVE

Over 50% of newly diagnosed cutaneous squamous cell carcinoma (cSCC) lesions occur in the head and neck (cSCC-HN), and metastasis to nodal basins in this region further complicates surgical and adjuvant treatment. The current study addressed whether the 40-gene expression profile (40-GEP) test can predict metastatic risk in cSCC-HN with improved accuracy and provide independent prognostic value to complement current risk assessment methods.

STUDY DESIGN

Multicenter, retrospective cohort study.

METHODS

Formalin-fixed paraffin-embedded primary tumor tissue and associated clinical data from patients with cSCC-HN (n = 278) were collected from 33 independent centers. Samples were analyzed via the 40-GEP test. Cases were staged per American Joint Committee on Cancer, Eighth Edition (AJCC8) and Brigham and Women's Hospital (BWH) criteria after comprehensive medical record and pathology report review. Metastasis-free survival (MFS) rates were determined, and risk factors were analyzed via Cox regression.

RESULTS

The 40-GEP test classified the cohort into low (Class 1, n = 126; 45.3%), moderate (Class 2A, n = 134; 48.2%), and high (Class 2B, n = 18; 6.5%) metastatic risk at 3 years postdiagnosis. Regional/distant metastasis occurred in 54 patients (19.4%). MFS rates were 92.1% (Class 1), 76.1% (Class 2A), and 44.4% (Class 2B; p < .0001). Multivariate analysis of 40-GEP results with AJCC8 or BWH tumor stage, or clinicopathologic risk factors, demonstrated independent prognostic value of the 40-GEP test (p < .03). Accuracy of predicting metastatic risk was also improved using 40-GEP classification (p < .02).

CONCLUSIONS

Improved metastatic risk stratification through the 40-GEP test could complement cSCC-HN risk assessment for better-informed decision-making for treatment and surveillance and ultimately improve patient outcomes.

LEVEL OF EVIDENCE

3.

Analytical Validation and Performance of a 7-Gene Next-Generation Sequencing Panel in Uveal Melanoma

INTRODUCTION

Gene expression profiling (GEP) is widely used for prognostication in patients with uveal melanoma (UM). Because biopsy tissue is limited, it is critical to obtain as much genomic information as possible from each sample. Combined application of both GEP and next-generation sequencing (NGS) allows for analysis of RNA and DNA from a single biopsy sample, offers additional prognostic information, and can potentially inform therapy selection. This study evaluated the analytical performance of a targeted custom NGS panel for mutational profiling of 7 genes commonly mutated in UM.

METHODS

One hundred five primary UM tumors were analyzed, including 37 formalin-fixed paraffin-embedded (FFPE) and 68 fine-needle aspiration biopsy specimens. Sequencing was performed on the Ion GeneStudio S5 platform to an average read depth of >500X per region of interest.

RESULTS

The 7-gene panel achieved a positive percent agreement of 100% for detection of both single-nucleotide variants and insertions/deletions, with a technical positive predictive value of 98.8% and 100%, respectively. Intra-assay and inter-assay concordance studies confirmed the assay's reproducibility and repeatability.

DISCUSSION/CONCLUSION

The 7-gene panel is a robust, highly accurate NGS test that can be successfully performed, along with GEP, from a single small-gauge needle biopsy sample or FFPE specimen.

Enhanced metastatic risk assessment in cutaneous squamous cell carcinoma with the 40-gene expression profile test

Aim: To clinically validate the 40-gene expression profile (40-GEP) test for cutaneous squamous cell carcinoma patients and evaluate coupling the test with individual clinicopathologic risk factor-based assessment methods. Patients & methods: In a 33-site study, primary tumors with known patient outcomes were assessed under clinical testing conditions (n = 420). The 40-GEP results were integrated with clinicopathologic risk factors. Kaplan-Meier and Cox regression analyses were performed for metastasis. Results: The 40-GEP test demonstrated significant prognostic value. Risk classification was improved via integration of 40-GEP results with clinicopathologic risk factor-based assessment, with metastasis rates near the general cutaneous squamous cell carcinoma population for Class 1 and ≥50% for Class 2B. Conclusion: Combining molecular profiling with clinicopathologic risk factor assessment enhances stratification of cutaneous squamous cell carcinoma patients and may inform decision-making for risk-appropriate management strategies.

Integrating 31-Gene Expression Profiling With Clinicopathologic Features to Optimize Cutaneous Melanoma Sentinel Lymph Node Metastasis Prediction

National guidelines recommend sentinel lymph node biopsy (SLNB) be offered to patients with > 10% likelihood of sentinel lymph node (SLN) positivity. On the other hand, guidelines do not recommend SLNB for patients with T1a tumors without high-risk features who have < 5% likelihood of a positive SLN. However, the decision to perform SLNB is less certain for patients with higher-risk T1 melanomas in which a positive node is expected 5%-10% of the time. We hypothesized that integrating clinicopathologic features with the 31-gene expression profile (31-GEP) score using advanced artificial intelligence techniques would provide more precise SLN risk prediction.

Risk Stratification of Patients with Stage I Cutaneous Melanoma Using 31-Gene Expression Profiling

BACKGROUND

While patients with localized cutaneous melanoma (CM) generally have good five-year melanoma-specific survival rates, identifying patients with localized disease at a high risk of recurrence could allow them access to additional follow-up or surveillance.

OBJECTIVE

We sought to examine the prognostic value of the 31-gene expression profile (31-GEP) test for the risk of recurrence in stage I CM patients according to 31-GEP main class (low risk: Class 1 vs. high-risk: Class 2) and the lowest and highest risk 31-GEP subclasses (Class 1A vs. Class 2B).

METHODS

Data from a previously described meta-analysis detailing the 31-GEP results for patients with stage I CM (N = 623) were re-analyzed to determine 31-GEP accuracy.

RESULTS

Patients with stage I CM and a Class 1 31-GEP result were less likely to have a recurrence (15/556; 2.7% vs. 6/67; 9.0%; p=0.018) than patients with a Class 2 result and had a higher five-year recurrence-free survival (RFS) (96% vs. 85%). Patients with a Class 2 result were 2.8 times as likely to experience a recurrence (positive likelihood ratio: 2.82; 95% confidence interval: 1.38-5.77). In a subset of patients with stage I CM stratified further into 31-GEP subclasses (n = 206), patients with a Class 1A result had a higher five-year RFS than those with a Class 2B result (98% vs. 73%). Patients with a Class 2B result were also 6.5 times as likely to experience a recurrence (positive likelihood ratio: 6.45; 95% confidence interval: 2.44-17.00) than those with a Class 1A result, and the 31-GEP had a negative predictive value of 96.3% (95% confidence interval: 92.3%-98.4%).

CONCLUSION

The 31-GEP test significantly differentiates between low and high recurrence risk in patients with stage I CM.

Long-Term Outcomes in a Multicenter, Prospective Cohort Evaluating the Prognostic 31-Gene Expression Profile for Cutaneous Melanoma

PURPOSE

Current guidelines for postoperative management of patients with stage I-IIA cutaneous melanoma (CM) do not recommend routine cross-sectional imaging, yet many of these patients develop metastases. Methods that complement American Joint Committee on Cancer (AJCC) staging are needed to improve identification and treatment of these patients. A 31-gene expression profile (31-GEP) test predicts metastatic risk as low (class 1) or high (class 2). Prospective analysis of CM outcomes was performed to test the hypotheses that the 31-GEP provides prognostic value for patients with stage I-III CM, and that patients with stage I-IIA melanoma and class 2 31-GEP results have metastatic risk similar to patients for whom surveillance is recommended.

MATERIALS AND METHODS

Two multicenter registry studies, INTEGRATE (ClinicalTrials.gov identifier:NCT02355574) and EXPAND (ClinicalTrials.gov identifier:NCT02355587), were initiated under institutional review board approval, and 323 patients with stage I-III CM and median follow-up time of 3.2 years met inclusion criteria. Primary end points were 3-year recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and overall survival (OS).

RESULTS

The 31-GEP was significant for RFS, DMFS, and OS in a univariate analysis and was a significant, independent predictor of RFS, DMFS, and OS in a multivariable analysis. GEP class 2 results were significantly associated with lower 3-year RFS, DMFS, and OS in all patients and those with stage I-IIA disease. Patients with stage I-IIA CM and a class 2 result had recurrence, distant metastasis, and death rates similar to patients with stage IIB-III CM. Combining 31-GEP results and AJCC staging enhanced sensitivity over each approach alone.

CONCLUSION

These data provide a rationale for using the 31-GEP along with AJCC staging, and suggest that patients with stage I-IIA CM and a class 2 31-GEP signature may be candidates for more intense follow-up.

Gene Expression Profiling in Uveal Melanoma: Five-Year Prospective Outcomes and Meta-Analysis

Introduction

The prognostic 15-gene expression profile (15-GEP) test for uveal melanoma (UM) predicts metastatic risk based on primary tumor biology. Here we report outcomes from a prospective registry of 15-GEP-tested patients, and a meta-analysis with published cohorts.

Objectives

Management and 5-year clinical outcomes following 15-GEP testing were evaluated.

Methods

Eighty-nine patients with 15-GEP results were prospectively enrolled at four centers. Physician-recommended management plans were collected, and clinical outcomes tracked every 6 months.

Results

Eighty percent of Class 1 (low-risk) patients underwent low-intensity management; all Class 2 (high-risk) patients underwent high-intensity management (p < 0.0001). Median follow-up for event-free patients was 4.9 years. Five Class 1 (10%) and 23 Class 2 (58%) tumors metastasized (p < 0.0001). Five-year Class 1 and 2 metastasis-free survival rates were 90% (81-100%) and 41% (27-62%; p < 0.0001), and melanoma-specific survival rates were 94% (87-100%) and 63% (49-82%; p = 0.0007). Class 2 was the only independent predictor of metastasis and was associated with increased risk for metastasis and mortality by meta-analysis.

Conclusions

UM patient management is guided by 15-GEP testing. Class 2 patients were managed more intensely, in accordance with an observed metastatic rate of >50%; Class 1 patients were safely spared intensive surveillance, resulting in appropriate utilization of healthcare resources.

Integrating the melanoma 31-gene expression profile test with surgical oncology practice within national guideline and staging recommendations

Aim: Define changes in clinical management resulting from the use of the prognostic 31-gene expression profile (31-GEP) test for cutaneous melanoma in a surgical oncology practice. Patients & methods: Management plans for 112 consecutively tested patients with stage I-III melanoma were evaluated for duration and number of clinical visits, blood work and imaging. Results: 31-GEP high-risk (class 2; n = 46) patients received increased management compared with low-risk (class 1; n = 66) patients. Test results were most closely associated with follow-up and imaging. Of class 1 patients, 65% received surveillance intensity within guidelines for stage I-IIA patients; 98% of class 2 patients received surveillance intensity equal to stage IIB-IV patients. Conclusion: We suggest clinical follow-up and metastatic screening be adjusted according to 31-GEP test results.

Integrating gene expression profiling into NCCN high-risk cutaneous squamous cell carcinoma management recommendations: impact on patient management

Objective: To integrate gene expression profiling into the management of high-risk cutaneous squamous cell carcinoma (cSCC) within the National Comprehensive Cancer Network (NCCN) guidelines to improve risk-aligned management recommendations.Methods: A cohort of 300 NCCN-defined high-risk cSCC patients, along with the American Joint Committee on Cancer (AJCC) T stage, Brigham and Women's Hospital (BWH) T stage, and known patient outcomes were analyzed. Risk classifications using a validated 40-gene expression profile (40-GEP) test and T stage were applied to NCCN patient management guidelines. Risk-directed patient management recommendations within the NCCN guidelines framework were aligned based on risk for metastasis.Results: Of the 300 NCCN high-risk cSCC patients, 159 (53.0%) were 40-GEP Class 1 and AJCC T1-T2, and 173 (57.7%) were Class 1 and BWH T1-2a, indicating low risk for metastasis and, thereby, suggesting low management intensity. The 40-GEP integration suggested high intensity management for only 24 (8.0%) patients (all Class 2B), and moderate intensity management for the remainder of the cohort.Conclusions: The 40-GEP test can be integrated within existing NCCN guideline recommendations for managing cSCC patients to help refine risk-directed management decisions. Integration of the 40-GEP test would allow >50% of this NCCN-defined high-risk cohort to be managed with the lowest intensity recommendations within the broad NCCN guidelines. High intensity management was deemed risk-appropriate for a small subpopulation (8.0%). This study demonstrates that the 40-GEP test, in combination with T stage, has clinical utility to impact patient management decisions in NCCN high-risk cSCC for improving risk-aligned management within the NCCN guidelines framework.

Performance of a prognostic 31-gene expression profile test in patients with node-negative cutaneous melanoma

e22071

Background: The National Comprehensive Cancer Network guidelines recommend considering sentinel lymph node biopsy (SLNB) for cutaneous melanoma (CM) patients with a 5-10% risk of SLN positivity and offering it to those with > 10% risk. However, SLNB limitations include identification of only 1/3 of patients who end up with distant metastasis and a regional metastasis false negative rate ranging from 5-21% indicating a need to detect the risk of metastasis in patients with a negative SLNB. The 31 gene expression profile (31GEP) test uses the molecular biology of the primary tumor to predict 5-year recurrence-free (RFS), distant metastasis-free (DMFS), melanoma-specific (MSS), and overall survival (OS). Therefore, the objective of this study is to determine whether the 31GEP can stratify risk for patients with SLN-negative results to help guide CM management. Methods: 607 primary CM tumors were collected from patients with SLN-negative status who were enrolled in multi-center IRB-approved studies. Tumors were staged according to the AJCC 8th edition and analyzed by 31GEP testing to differentiate low-risk (Class 1A), intermediate-risk (Class 1B/2A), and high-risk (Class 2B) tumor biology. Clinical data were recorded and Kaplan-Meier (KM) and Cox regression analyses were performed to assess the relationship between 31GEP class and patient outcomes including RFS, DMFS, MSS, and OS. Results: KM analysis for 5yr RFS, DMFS, MSS, and OS stratified by 31GEP class are listed in Table. Multivariate Cox regression analysis demonstrated that the 31GEP Class 2B status was an independent predictor of RFS, DMFS, MSS, and OS with hazard ratios of 4.4 (95% CI, 2.7-7.2; p < 0.001), 4.4 (95% CI, 2.3-8.5; p < 0.001), 15.6 (95% CI, 3.4-71.2; p < 0.001), and 5.4 (95% CI, 2.6-10.9; p < 0.001), respectively. Conclusions: The results indicate that the 31GEP can stratify risk for a subset of patients with SLNB-negative results with the highest 5-year survival rates being associated with a Class 1A result. Moreover, GEP Class 2B is a significant independent predictor of metastatic risk in patients who are node negative. [Table: see text]

Implications of a prognostic 40-gene expression profile (40-GEP) test for high-risk cutaneous squamous cell carcinoma (cSCC) on staging-based risk assessment and adjuvant therapy trial design

e22091

Background: Deaths due to cSCC are expected to exceed melanoma-specific deaths. With the demonstration of effective therapies for advanced cSCC, and as treatment of patients in the adjuvant setting is considered, accurate prognosis is critical. For improved identification of ‘high-risk’ patients, with biologically aggressive disease capable of metastasis, a prognostic 40-gene expression profile (40-GEP) test was validated using an independent cohort of patients with high-risk cSCC and known clinical outcomes. The test identified three groups with increasing metastasis risk profiles: Class 1 (low risk), Class 2A (high risk), and Class 2B (highest risk) having metastasis rates of 8.9%, 20.4%, and 60%, respectively. Multivariable analysis demonstrated prognostic efficacy of the 40-GEP test alone and in combination with clinicopathological staging systems. This study evaluated risk stratification with concurrent consideration of the 40-GEP result and the Brigham and Women’s Hospital (BWH) stage. The primary objective was evaluation of the potential impact of the 40-GEP on adjuvant clinical trial design. Methods: To determine if a 40-GEP Class 2B result could optimize clinical trial accrual, metastasis rates of BWH high-risk T stage patients (T2b-T3) alone and in combination with 40-GEP results from the validation cohort were used for two-arm trial sample size calculations. Results: Metastasis rates for cases with T2b-T3 tumors increased from 35.1% to 71.4% when selecting for T2b-T3 cases with a 40-GEP Class 2B result. To provide 80% power to detect hazard ratio of 0.6 with 3 years of follow-up (alpha = 0.05), in line with improvement rates by addition of radiation to surgery, 434 T2b-T3 patients are required for randomization. However, sample size could be reduced by 51% to 214 patients by focusing enrollment on T2b-T3 patients with a 40-GEP Class 2B result. Conclusions: These results support the incorporation of the 40-GEP test into selection processes for patients with T2b-T3 tumors who are at the highest risk for metastasis and appropriate for adjuvant clinical trials.

Validation of a 40-gene expression profile test to predict metastatic risk in localized high-risk cutaneous squamous cell carcinoma

BACKGROUND

Current staging systems for cutaneous squamous cell carcinoma (cSCC) have limited positive predictive value for identifying patients who will experience metastasis.

OBJECTIVE

To develop and validate a gene expression profile (GEP) test for predicting risk for metastasis in localized, high-risk cSCC with the goal of improving risk-directed patient management.

METHODS

Archival formalin-fixed paraffin-embedded primary cSCC tissue and clinicopathologic data (n = 586) were collected from 23 independent centers in a prospectively designed study. A GEP signature was developed using a discovery cohort (n = 202) and validated in a separate, nonoverlapping, independent cohort (n = 324).

RESULTS

A prognostic 40-GEP test was developed and validated, stratifying patients with high-risk cSCC into classes based on metastasis risk: class 1 (low risk), class 2A (high risk), and class 2B (highest risk). For the validation cohort, 3-year metastasis-free survival rates were 91.4%, 80.6%, and 44.0%, respectively. A positive predictive value of 60% was achieved for the highest-risk group (class 2B), an improvement over staging systems, and negative predictive value, sensitivity, and specificity were comparable to staging systems.

LIMITATIONS

Potential understaging of cases could affect metastasis rate accuracy.

CONCLUSION

The 40-GEP test is an independent predictor of metastatic risk that can complement current staging systems for patients with high-risk cSCC.

Molecular risk prediction in cutaneous melanoma: A meta-analysis of the 31-gene expression profile prognostic test in 1,479 patients

BACKGROUND

Multiple studies have reported on the accuracy of the prognostic 31-gene expression profile test for cutaneous melanoma. Consistency of the test results across studies has not been systematically evaluated.

OBJECTIVE

To assess the robustness of the prognostic value of the 31-gene expression profile.

METHODS

Raw data were obtained from studies identified from systematic review. A meta-analysis was performed to determine overall effect of the 31-gene expression profile. Clinical outcome metrics for the 31-gene expression profile were compared with American Joint Committee on Cancer staging.

RESULTS

Three studies met inclusion criteria; data from a novel cohort of 211 patients were included (n = 1,479). Five-year recurrence-free and distant metastasis-free survival rates were 91.4% and 94.1% for Class 1A patients and 43.6% and 55.5% for Class 2B patients (P < .0001). Meta-analysis results showed that Class 2 was significantly associated with recurrence (hazard ratio 2.90; P < .0001) and distant metastasis (hazard ratio 2.75; P < .0001). The 31-gene expression profile identified American Joint Committee on Cancer stage I to III patient subsets with high likelihood for recurrence and distant metastasis. Sensitivity was 76% (95% confidence interval 71%-80%) and 76% (95% confidence interval 70%-82%) for each end point, respectively. When 31-gene expression profile and sentinel lymph node biopsy results were considered together, sensitivity and negative predictive value for distant metastasis-free survival were both improved.

CONCLUSION

The 31-gene expression profile test consistently and accurately identifies melanoma patients at increased risk of metastasis, is independent of other clinicopathologic covariates, and augments current risk stratification by reclassifying patients for heightened surveillance who were previously designated as being at low risk.

The repertoire of mutational signatures in human cancer

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature¹. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium² of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses^3-15, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated-but distinct-DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

APOBEC mutation drives early-onset squamous cell carcinomas in recessive dystrophic epidermolysis bullosa

Recessive dystrophic epidermolysis bullosa (RDEB) is a rare inherited skin and mucous membrane fragility disorder complicated by early-onset, highly malignant cutaneous squamous cell carcinomas (SCCs). The molecular etiology of RDEB SCC, which arises at sites of sustained tissue damage, is unknown. We performed detailed molecular analysis using whole-exome, whole-genome, and RNA sequencing of 27 RDEB SCC tumors, including multiple tumors from the same patient and multiple regions from five individual tumors. We report that driver mutations were shared with spontaneous, ultraviolet (UV) light-induced cutaneous SCC (UV SCC) and head and neck SCC (HNSCC) and did not explain the early presentation or aggressive nature of RDEB SCC. Instead, endogenous mutation processes associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) deaminases dominated RDEB SCC. APOBEC mutation signatures were enhanced throughout RDEB SCC tumor evolution, relative to spontaneous UV SCC and HNSCC mutation profiles. Sixty-seven percent of RDEB SCC driver mutations was found to emerge as a result of APOBEC and other endogenous mutational processes previously associated with age, potentially explaining a >1000-fold increased incidence and the early onset of these SCCs. Human papillomavirus-negative basal and mesenchymal subtypes of HNSCC harbored enhanced APOBEC mutational signatures and transcriptomes similar to those of RDEB SCC, suggesting that APOBEC deaminases drive other subtypes of SCC. Collectively, these data establish specific mutagenic mechanisms associated with chronic tissue damage. Our findings reveal a cause for cancers arising at sites of persistent inflammation and identify potential therapeutic avenues to treat RDEB SCC.

Genomic evolution of uveal melanoma arising in ocular melanocytosis

Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here, we present a patient who developed UM arising within ocular melanocytosis who was treated with enucleation (eye removal), which provided an invaluable opportunity to interrogate both the UM and adjacent uveal tissue containing the melanocytosis using whole-exome and deep-targeted sequencing. This analysis revealed a clonal PLCB4 mutation in the melanocytosis, confirming that this is indeed a neoplastic condition and explaining why it predisposes to UM. This mutation was present in 100% of analyzed UM cells, indicating that a PLCB4-mutant cell gave rise to the UM. The earliest aberrations specific to the tumor were loss of Chromosomes 1p, 3, and 9p, which were present in virtually all tumor cells. A mutation in BAP1 arose later on the other copy of Chromosome 3 in a tumor subclone, followed by a gain of Chromosome 8q. These findings provide a mechanistic explanation for the well-known clinical association between ocular melanocytosis and UM by showing that this predisposing condition introduces the first “hit” and thereby increases the stochastic likelihood of acquiring further aberrations leading to UM.

Abstract 2903: Genomic evolution of uveal melanoma arising in ocular melanocytosis

Introduction: Ocular melanocytosis is an congenital condition characterized by the presence of excessive hyperpigmented melanocytes in the uveal tract. Epidemiological studies have shown that this condition is the strongest predisposing risk factor for development of uveal melanoma (UM). In UM patients, the presence of ocular melanocytosis doubles the risk of metastasis. UM has well-characterized driver mutations consisting of two groups. The first group consists of mutually exclusive gain-of-function mutations in members of the Gq signaling pathway (GNAQ, GNA11, CYSLTR2 and PLCB4), and are thought to represent initiating oncogenic events that are insufficient alone to cause full malignant transformation. The second group consists of near-mutually exclusive mutations in BAP1, SF3B1, and EIF1AX, which are thought to occur later in tumor progression. The genomics of ocular melanocytosis and matched UM have not been characterized previously. The purpose of this study was to investigate the genomic evolution of matched ocular melanocytosis and UM tumors.

Methods: Exome and deep-targeted sequencing data from two matched ocular melanocytosis and primary uveal melanomas were evaluated using a previously developed bioinformatic pipeline optimized to call mutations and CNVs in UM. Data from this analysis were used in downstream mutation subclone detection algorithms to determine genomic evolutionary patterns within these matched samples.

Results: For both cases, the initiating driver mutations that are characteristic of UM occur at the same genomic site in matched ocular melanocytosis and UM samples. This finding suggests that they arose within the melanocytosis and subsequently expanded in the tumor. Monosomy of chromosome 3 was absent from the melanocytosis but present in ~100% of tumor cells, indicating that it arose early during clonal tumor expansion. In Patient 1, the BAP1 mutation was present in a tumor subclone and chromosome 8q gain was present in a smaller subclone, indicating that they arose later during tumor evolution. In Patient 2, the BAP1 mutation and other copy number variations were present in ~100% of tumor cells indicating that tumor evolution was completed in this tumor. Additionally, no Gq signaling pathway driver mutations were found in the germline DNA of these patients indicating that that the mutations in ocular melanocytosis occurred somatically during development.

Conclusions: This study provides the first genomic evidence relating ocular melanocytosis to UM. This data shows that Gq signaling pathway driver mutations are early genomic events that are necessary but not sufficient for UM tumor development.These insights help further refine our genomic model of UM tumor evolution and may help to address persistent challenges in the field such as the failure of targeted therapies aimed at inhibiting the Gq pathway.

Citation Format: Michael A. Durante, Matthew G. Field, Margaret I. Sanchez, Kyle R. Covington, Christina L. Decatur, Sander R. Dubovy, J. William Harbour. Genomic evolution of uveal melanoma arising in ocular melanocytosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2903.

Performance of a 31-gene expression profile test in cutaneous melanomas of the head and neck

Background

We report the performance of a gene expression profile test to classify the recurrence risk of cutaneous melanoma tumors of the head and neck as low‐risk Class 1 or high‐risk Class 2.

Methods

Of note, 157 primary head and neck cutaneous melanoma tumors were identified. Survival analyses were performed using Kaplan‐Meier and Cox methods.

Results

Gene expression profile class and node status stratified tumors into significantly different 5‐year survival groups by Kaplan‐Meier method (P < .0001 for all end points), and both were independent predictors of recurrence in multivariate analysis. Overall, 74% of distant metastases and 88% of melanoma‐specific deaths had Class 2 risk.

Conclusion

The gene expression profile test identifies cases at increased risk for metastasis and death independent of a clinically or pathologically negative nodal status, suggesting that incorporation of this molecular tool could improve clinical management of patients with head and neck cutaneous melanoma, especially in those with a negative sentinel lymph node biopsy.

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.

Prospective, Multicenter Clinical Impact Evaluation of a 31-Gene Expression Profile Test for Management of Melanoma Patients

Objective: A 31-gene expression profile (GEP) test that has been clinically validated identifies melanoma patients with low (Class 1) or high (Class 2) risk of metastasis based on primary tumor biology.  This study aimed to prospectively evaluate the test impact on clinical management of melanoma patients.Methods:  Physicians at 16 dermatology, surgical or medical oncology centers examined patients to assess clinical features of the primary melanoma.  Recommendations for clinical follow-up and surveillance were collected.  Following consent of the patient and performance of the GEP test, recommendations for management were again collected, and pre- and post-test recommendations were assessed to determine changes in management resulting from the addition of GEP testing to traditional clinicopathologic risk factors.   Results:  Post-test management plans changed for 49% (122 of 247) of cases in the study when compared to pre-test plans. Thirty-six percent (66 of 181) of Class 1 cases had a management change, compared to 85% (56 of 66) of Class 2 cases.  GEP class was a significant factor for change in care during the study (p<0.001), with Class 1 accounting for 91% (39 of 43) of cases with decreased management intensity, and Class 2 accounting for 72% (49 of 68) of cases with increases.Conclusions: The reported study show that the 31-gene GEP test improves net health outcomes in the management of cutaneous melanoma.  Physicians used test results to guide risk-appropriate changes that match the biological risk of the tumor, including directing more frequent and intense surveillance to high-risk, Class 2 patients.

Analytic validity of DecisionDx-Melanoma, a gene expression profile test for determining metastatic risk in melanoma patients

BACKGROUND

The DecisionDx-Melanoma test provides prognostic information for patients with cutaneous melanoma (CM). Using formalin-fixed paraffin-embedded primary tumor tissue, the RT-PCR-based test classifies patients into a low- (Class 1) or high-risk (Class 2) category for recurrence based on expression of 31 genes. The current study was designed to assess the analytical validity of this test.

METHODS

Inter-assay, inter-instrument, and inter-operator studies were performed to evaluate reliability of the 31-gene expression test results, sample stability and reagent stability. From March 2013 through June 2016, the gene expression test was performed on 8244 CM tumors. De-identified data from Pathology Reports were used to assess technical success.

RESULTS

Robust sample and reagent stability was observed. Inter-assay concordance on 168 specimens run on 2 consecutive days was 99% and matched probability scores were significantly correlated (R² = 0.96). Inter-instrument concordance was 95%, and probability scores had a correlation R² of 0.99 (p < 0.001). From 8244 CM specimens submitted since 2013, 85% (7023) fulfilled pre-specified tumor content parameters. In these samples with sufficient tumor requirements, the technical success of the test was 98%.

CONCLUSION

DecisionDx-Melanoma is a robust gene expression profile test that demonstrates strong reproducibility between experiments and has high technical reliability on clinical samples.

Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients

BACKGROUND

The heterogeneous behavior of patients with melanoma makes prognostication challenging. To address this, a gene expression profile (GEP) test to predict metastatic risk was previously developed. This study evaluates the GEP's prognostic accuracy in an independent cohort of cutaneous melanoma patients.

METHODS

This multi-center study analyzed primary melanoma tumors from 523 patients, using the GEP to classify patients as Class 1 (low risk) and Class 2 (high risk). Molecular classification was correlated to clinical outcome and assessed along with AJCC v7 staging criteria. Primary endpoints were recurrence-free (RFS) and distant metastasis-free (DMFS) survival.

RESULTS

The 5-year RFS rates for Class 1 and Class 2 were 88% and 52%, respectively, and DMFS rates were 93% versus 60%, respectively (P < 0.001). The GEP was a significant predictor of RFS and DMFS in univariate analysis (hazard ratio [HR] = 5.4 and 6.6, respectively, P < 0.001 for each), along with Breslow thickness, ulceration, mitotic rate, and sentinel lymph node (SLN) status (P < 0.001 for each). GEP, tumor thickness and SLN status were significant predictors of RFS and DMFS in a multivariate model that also included ulceration and mitotic rate (RFS HR = 2.1, 1.2, and 2.5, respectively, P < 0.001 for each; and DMFS HR = 2.7, 1.3 and 3.0, respectively, P < 0.01 for each).

CONCLUSIONS

The GEP test is an objective predictor of metastatic risk and provides additional independent prognostic information to traditional staging to help estimate an individual's risk for recurrence. The assay identified 70% of stage I and II patients who ultimately developed distant metastasis. Its role in consideration of patients for adjuvant therapy should be examined prospectively.

Impact of Gene Expression Profiling on Decision-Making in Clinically Node Negative Melanoma Patients after Surgical Staging

INTRODUCTION

The surgeon's role in the follow-up of pathologic stage I and II melanoma patients has traditionally been minimal. Melanoma genetic expression profile (GEP) testing provides binary risk assessment (Class 1-low risk, Class 2-high risk), which can assist in predicting metastasis and formulating appropriate follow up. We sought to determine the impact of GEP results on the management of clinically node negative cutaneous melanoma patients staged with sentinel lymph node biopsy (SLNB).

METHODS

A retrospective review of prospectively gathered data consisting of patients seen from September 2015 - August 2016 was performed to determine whether GEP class influenced follow-up recommendations. Patients were stratified into four groups based on recommended follow-up plan: Dermatology alone, Surgical Oncology, Surgical Oncology with recommendation for adjuvant clinical trial, or Medical and Surgical Oncology.

RESULTS

Of ninety-one patients, 38 were pathologically stage I, 42 stage II, 10 stage III, and 1 stage IV. Combining all stages, GEP Class 1 patients were more likely to be followed by Dermatology alone and less like to be followed by Surgical Oncology with recommendation for adjuvant trial compared to Class 2 patients (P less than 0.001). Among stage 1 patients, Class 1 were more likely to follow up with Dermatology alone compared to Class 2 patients (82 vs. 0%; P less than 0.001). Among stage II patients, GEP Class 1 were more likely to follow up with Dermatology alone (21 vs 0%) and more Class 2 patients followed up with surgery and recommendations for adjuvant trial (36 vs 64%; P less than 0.05). There was no difference in follow up for stage III patients based on the GEP results (P=0.76).

CONCLUSION

GEP results were significantly associated with the management of stage I-II melanoma patients after staging with SLNB. For node negative patients, Class 2 results led to more aggressive follow up and management. J Drugs Dermatol. 2018;17(2):196-199.

Interim analysis of survival in a prospective, multi-center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test

BACKGROUND

A 31-gene expression profile (GEP) test that provides risk classification of cutaneous melanoma (CM) patients has been validated in several retrospective studies. The objective of the reported study was a prospective evaluation of the GEP performance in patients enrolled in two clinical registries.

METHODS

Three-hundred twenty two CM patients enrolled in the EXPAND (NCT02355587) and INTEGRATE (NCT02355574) registries met the criteria of age ≥ 16 years, successful GEP result and ≥1 follow-up visit for inclusion in this interim analysis. Primary endpoints were recurrence-free (RFS), distant metastasis-free (DMFS), and overall survival (OS).

RESULTS

Median follow-up was 1.5 years for event-free patients. Median age for subjects was 58 years (range 18-87) and median Breslow thickness was 1.2 mm (range 0.2-12.0). Eighty-eight percent (282/322) of cases had stage I/II disease and 74% (237/322) had a SLN biopsy. Seventy-seven percent (248/322) had class 1 molecular profiles. 1.5-year RFS, DMFS, and OS rates were 97 vs. 77%, 99 vs. 89%, and 99 vs. 92% for class 1 vs. class 2, respectively (p < 0.0001 for each). Multivariate Cox regression showed Breslow thickness, mitotic rate, and GEP class to significantly predict recurrence (p < 0.01), while tumor thickness was the only significant predictor of distant metastasis and overall survival in this interim analysis.

CONCLUSIONS

Interim analysis of patient outcomes from a combined prospective cohort supports the 31-gene GEP's ability to stratify early-stage CM patients into two groups with significantly different metastatic risk. RFS outcomes in this real-world cohort are consistent with previously published analyses with retrospective specimens. GEP testing complements current clinicopathologic features and increases identification of high-risk patients.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02355574  and NCT02355587.

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas, of a set of predominantly intrahepatic CCA cases, and propose a molecular classification scheme. We identified an IDH -mutant enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH -mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance.

Performance of a 31-gene expression profile (GEP) test for metastatic risk prediction in cutaneous melanomas (CM) of the head and neck

9576

Background: Accurate prognostication of distant metastatic risk using sentinel lymph node (SLN) biopsy for CM can be challenging in melanomas of the head and neck due to a higher false negative rate compared to other anatomical areas. A GEP signature that predicts metastatic risk based on primary tumor biology, providing a binary outcome of Class 1 (low risk of metastasis) or Class 2 (high risk), was previously described. The prognostic capabilities of the GEP independently and in combination with SLN status in a cohort of patients with primary head and neck CM are assessed here. Methods: All samples and clinical data were collected under an IRB-approved multicenter protocol. qPCR analysis was used to assess expression of the gene signature (Class 1 vs. Class 2). Distant metastasis-free survival (DMFS) and melanoma-specific survival (MSS) were assessed. Results: 157 subjects with primary CMs in the head and neck region were identified. 110 of 157 subjects had a SLN biopsy performed. Median age was 65 years (range 25-89) and median Breslow depth was 1.6 mm (range 0.2-15.0 mm). In 71 SLN-negative patients, 18 of 27 (67%) distant metastatic events were GEP Class 2. Overall, 73% (47 of 64) distant metastases, and 88% (22 of 25) deaths due to CM were called Class 2. By comparison, sensitivities for DMFS and MSS were 41% (26 of 64) and 52% (13 of 25), respectively, using SLN biopsy alone, and increased to 80% (51 of 64) and 88% (22 of 25), respectively, when combining the SLN status and GEP class. Kaplan-Meier 5-year DMFS and MSS rates based on SLN status alone or in combination with GEP are shown in the table. Conclusions: These data support the ability of the GEP test to accurately identify low- and high-risk cases of head and neck melanoma. The results strongly support the role of GEP testing to enhance current staging by better predicting the risk of distant metastasis and death for patients with melanoma in an anatomic region that is associated with a higher SLN biopsy false negative rate. [Table: see text]

Performance of a prognostic 31-gene expression profile test in stage III cutaneous melanoma subjects

9578

Background: The management of stage III cutaneous melanoma (CM) patients has changed significantly with the introduction of contemporary therapies. A 31-gene expression profile (GEP) test that provides a prediction of low or high risk of melanoma metastasis has been validated as an independent prognosticator of distant metastasis-free (DMFS) and melanoma-specific survival (MSS). We examine the prognostic accuracy of the test in a cohort of stage III, and particularly stage IIIA, subjects from a multicenter validation study. Methods: 207 primary CM tumors from 16 centers were analyzed as part of an IRB-approved study. Quantitative RT-PCR and predictive modeling were performed to classify metastasis and survival risk as Class 1 (low risk) or Class 2 (high risk). Results for Kaplan-Meier and Cox regression survival analysis are reported. Results: Of the 207 subjects with stage III melanoma, 76 were stage IIIA. The table shows 5-year DMFS and MSS rates for all stage III and stage IIIA groups. Patients with Class 2 GEP had significantly worse outcomes compared to Class 1. In univariate analyses, GEP was a significant predictor of DMFS and MSS with a hazard ratio for DMFS of 2.8 (95%-CI; 1.7-4.6) and for MSS of 4.0 (95%-CI; 1.7-9.4) for all stage III, while HR of 2.2 for DMFS (95%-CI; 1.0-4.7) and 4.3 for MSS (95%-CI; 1.2-15.2) were observed for the stage IIIA group. For all stage III cases, Breslow thickness and GEP were significant predictors of DMFS and MSS in multivariate models including ulceration and mitotic rate (p < 0.05). Conclusions: The results support the capability of the GEP to accurately predict stage III distant metastasis and survival, and that the test complements existing prognostic factors. GEP testing may be useful in identifying stage IIIA patients who are appropriate for adjuvant therapies and/or enrollment in clinical trials. [Table: see text]

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance.

Cross-species identification of genomic drivers of squamous cell carcinoma development across preneoplastic intermediates

Cutaneous squamous cell carcinoma (cuSCC) comprises 15-20% of all skin cancers, accounting for over 700,000 cases in USA annually. Most cuSCC arise in association with a distinct precancerous lesion, the actinic keratosis (AK). To identify potential targets for molecularly targeted chemoprevention, here we perform integrated cross-species genomic analysis of cuSCC development through the preneoplastic AK stage using matched human samples and a solar ultraviolet radiation-driven Hairless mouse model. We identify the major transcriptional drivers of this progression sequence, showing that the key genomic changes in cuSCC development occur in the normal skin to AK transition. Our data validate the use of this ultraviolet radiation-driven mouse cuSCC model for cross-species analysis and demonstrate that cuSCC bears deep molecular similarities to multiple carcinogen-driven SCCs from diverse sites, suggesting that cuSCC may serve as an effective, accessible model for multiple SCC types and that common treatment and prevention strategies may be feasible.

Multilevel Genomics-Based Taxonomy of Renal Cell Carcinoma

On the basis of multidimensional and comprehensive molecular characterization (including DNA methalylation and copy number, RNA, and protein expression), we classified 894 renal cell carcinomas (RCCs) of various histologic types into nine major genomic subtypes. Site of origin within the nephron was one major determinant in the classification, reflecting differences among clear cell, chromophobe, and papillary RCC. Widespread molecular changes associated with TFE3 gene fusion or chromatin modifier genes were present within a specific subtype and spanned multiple subtypes. Differences in patient survival and in alteration of specific pathways (including hypoxia, metabolism, MAP kinase, NRF2-ARE, Hippo, immune checkpoint, and PI3K/AKT/mTOR) could further distinguish the subtypes. Immune checkpoint markers and molecular signatures of T cell infiltrates were both highest in the subtype associated with aggressive clear cell RCC. Differences between the genomic subtypes suggest that therapeutic strategies could be tailored to each RCC disease subset.

Abstract A33: Discovery of chimeric transcripts involving APC and TERT in pediatric HCC by RNA sequencing

Background: Hepatocellular carcinoma (HCC) is a rare pediatric liver tumor with a poor prognosis. A characteristic DNAJB1-PRKACA gene fusion has been identified in a specific subtype, fibrolamelar HCC (FL-HCC). In the majority of pediatric cases of non-FL-HCC, a genetic cause has not been identified. We hypothesize that gene fusions could play a role in the tumorigenesis of pediatric HCC. The goal of this project is to utilize RNA sequencing to identify chimeric transcripts in pediatric HCC that could improve molecular characterization and identify potential oncogenic drivers of this disease.

Materials and Methods: We have used RNA sequencing (RNA-seq) to survey a cohort of 8 FL-HCCs, 4 pediatric HCCs, and 6 normal liver samples for chimeric transcripts. High quality RNA (RIN: 6.6-9.7) was extracted from fresh-frozen tissue and strand-specific, poly-A+ RNA-seq libraries were prepared for Illumina sequencing. Approximately 85 million paired-end reads (42.5 million fragments) of 2 x 100 bp length were generated per sample. Fusion transcripts in the tumor samples were detected using deFuse (v.0.6.1) on FASTQ files followed by subtraction of fusions also called in the normal liver dataset. The remaining calls in the HCC dataset were then filtered for the COSMIC Cancer Gene Census list to identify fusions involving known oncogenes or tumor suppressor genes. Candidate fusions were verified using BLAST and validated by RT-PCR.

Results: On average, 150 fusion transcripts were predicted per tumor sample using the deFuse algorithm. Further filtering by the normal liver dataset reduced the number of calls in the tumor datasets by ~60%. As expected, DNAJB1-PRKACA fusions were identified in the FL-HCC cohort with no additional fusions detected. Filtering by the COSMIC Cancer Gene Census list resulted in five additional fusion calls in HCC (three unique events in two tumors) two of which were confirmed by RT-PCR. The first event is an inversion within the APC and AP3B1 genes that results in the two in-frame fusion transcripts, APC-AP3B1 and APC3B1-APC, but no full-length APC transcript. The second event is a deletion encompassing the TERT promoter that results in the in-frame fusion LPCAT1-TERT. An increase in TERT expression is seen in this tumor as compared to both normal liver and other pediatric HCC tumors. Filtering for in-frame fusions involving non-COSMIC genes did not reveal any fusions in the two remaining HCCs and further analysis of these cases is ongoing.

Conclusion: The detection of chimeric transcripts by RNA-seq has allowed us to identify two unique structural events involving known cancer genes in two pediatric non-fibrolamellar HCCs. The chimeric transcripts found in these tumors provide further insight into the tumorigenic events of pediatric HCC.

Supported by research grants from Cancer Prevention and Research Institute of Texas RP101195 and RP120715 and National Institute of General Medical Sciences T32GM008307.

Citation Format: Katherine Haines, Angshumoy Roy, Linghua Wang, Pavel Sumazin, Kyle R. Covington, Donna M. Muzny, Vijetha Kumar, Harsha Doddapaneni, Hsu Chao, David A. Wheeler, Gail Tomlinson, D. Williams Parsons, Sharon E. Plon, Dolores Lopez-Terrada. Discovery of chimeric transcripts involving APC and TERT in pediatric HCC by RNA sequencing. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; 2015 Nov 9-12; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(5 Suppl):Abstract nr A33.

An open access pilot freely sharing cancer genomic data from participants in Texas

Genomic data sharing in cancer has been restricted to aggregate or controlled-access initiatives to protect the privacy of research participants. By limiting access to these data, it has been argued that the autonomy of individuals who decide to participate in data sharing efforts has been superseded and the utility of the data as research and educational tools reduced. In a pilot Open Access (OA) project from the CPRIT-funded Texas Cancer Research Biobank, many Texas cancer patients were willing to openly share genomic data from tumor and normal matched pair specimens. For the first time, genetic data from 7 human cancer cases with matched normal are freely available without requirement for data use agreements nor any major restriction except that end users cannot attempt to re-identify the participants (http://txcrb.org/open.html).

Ampullary Cancers Harbor ELF3 Tumor Suppressor Gene Mutations and Exhibit Frequent WNT Dysregulation

The ampulla of Vater is a complex cellular environment from which adenocarcinomas arise to form a group of histopathologically heterogenous tumors. To evaluate the molecular features of these tumors, 98 ampullary adenocarcinomas were evaluated and compared to 44 distal bile duct and 18 duodenal adenocarcinomas. Genomic analyses revealed mutations in the WNT signaling pathway among half of the patients and in all three adenocarcinomas irrespective of their origin and histological morphology. These tumors were characterized by a high frequency of inactivating mutations of ELF3, a high rate of microsatellite instability, and common focal deletions and amplifications, suggesting common attributes in the molecular pathogenesis are at play in these tumors. The high frequency of WNT pathway activating mutation, coupled with small-molecule inhibitors of β-catenin in clinical trials, suggests future treatment decisions for these patients may be guided by genomic analysis.

Mutational Strand Asymmetries in Cancer Genomes Reveal Mechanisms of DNA Damage and Repair

Mutational processes constantly shape the somatic genome, leading to immunity, aging, cancer, and other diseases. When cancer is the outcome, we are afforded a glimpse into these processes by the clonal expansion of the malignant cell. Here, we characterize a less explored layer of the mutational landscape of cancer: mutational asymmetries between the two DNA strands. Analyzing whole-genome sequences of 590 tumors from 14 different cancer types, we reveal widespread asymmetries across mutagenic processes, with transcriptional ("T-class") asymmetry dominating UV-, smoking-, and liver-cancer-associated mutations and replicative ("R-class") asymmetry dominating POLE-, APOBEC-, and MSI-associated mutations. We report a striking phenomenon of transcription-coupled damage (TCD) on the non-transcribed DNA strand and provide evidence that APOBEC mutagenesis occurs on the lagging-strand template during DNA replication. As more genomes are sequenced, studying and classifying their asymmetries will illuminate the underlying biological mechanisms of DNA damage and repair.

Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma

BACKGROUND

Papillary renal-cell carcinoma, which accounts for 15 to 20% of renal-cell carcinomas, is a heterogeneous disease that consists of various types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.

METHODS

We performed comprehensive molecular characterization of 161 primary papillary renal-cell carcinomas, using whole-exome sequencing, copy-number analysis, messenger RNA and microRNA sequencing, DNA-methylation analysis, and proteomic analysis.

RESULTS

Type 1 and type 2 papillary renal-cell carcinomas were shown to be different types of renal cancer characterized by specific genetic alterations, with type 2 further classified into three individual subgroups on the basis of molecular differences associated with patient survival. Type 1 tumors were associated with MET alterations, whereas type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-antioxidant response element (ARE) pathway. A CpG island methylator phenotype (CIMP) was observed in a distinct subgroup of type 2 papillary renal-cell carcinomas that was characterized by poor survival and mutation of the gene encoding fumarate hydratase (FH).

CONCLUSIONS

Type 1 and type 2 papillary renal-cell carcinomas were shown to be clinically and biologically distinct. Alterations in the MET pathway were associated with type 1, and activation of the NRF2-ARE pathway was associated with type 2; CDKN2A loss and CIMP in type 2 conveyed a poor prognosis. Furthermore, type 2 papillary renal-cell carcinoma consisted of at least three subtypes based on molecular and phenotypic features. (Funded by the National Institutes of Health.).