Predicting adjuvant radiation therapy benefit in cutaneous squamous cell carcinoma with the 40-gene expression profile.

Aim: To independently confirm that the 40-gene expression profile (40-GEP) test can identify patients with high-risk cutaneous squamous cell carcinoma who are more or less likely to benefit from adjuvant radiation therapy (ART).Materials & methods: Primary cutaneous squamous cell carcinoma tumors from two academic centers received retrospective 40-GEP testing and were analyzed for 5-year metastasis-free survival and projected time to event.Results: Random sampling of matched patient pairs (n = 52 ART-treated; 371 no ART) showed a median 50% decrease in 5-year progression rate for ART-treated patients (vs no ART) with 40-GEP Class 2B. Class 2A was associated with a modest ART benefit, but not Class 1.Conclusion: The 40-GEP identified patients most likely to benefit from ART (Class 2B) and those that can consider deferring treatment (Class 1).

Independent validation study: 40-GEP identifies patients with cutaneous squamous cell carcinoma who would be most likely to benefit from adjuvant radiation therapy.

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.

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.

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 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.

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.

When caught early, cancer of the skin can usually be removed, and patients have excellent chances of survival. However, some patients will have their cancer come back or spread to a new location in their body.The 31-gene expression profile (GEP) test measures the expression levels of 31 genes from an individual patient's tumor. A proprietary formula uses this information to identify the risk of recurrence or spread as low risk (Class 1) or high risk (Class 2). Cancers with low-risk 31-GEP scores have a lower chance of cancer recurrence or spread than patients with a high-risk score.In this study, we wanted to determine if doctors treated patients with low-risk scores differently from patients with high-risk scores. We found that doctors changed approximately half of patient treatment plans (doctor visits, lab work, or imaging to see if the cancer has come back) after learning the 31-GEP test results. Doctors usually planned less frequent follow-up visits for Class 1 results and more frequent follow up for Class 2 results.This study found doctors understand and make changes to their treatment plans based on the patient's 31-GEP test result.

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.

Plain language summary Cutaneous squamous cell carcinoma is a common skin cancer, with approximately 2 million cases diagnosed each year in the USA. Because substantial numbers of patients experience metastasis, which can result in death, accurate metastatic risk assessment is important. Clinicians use clinicopathologic factors to determine risk for disease progression. However, traditional methods miss pinpointing many patients who experience metastasis and sometimes categorize patients as at risk who do not develop metastasis, indicating that additional tools are needed. A molecular test, the 40-gene expression profile (40-GEP), was developed to predict metastatic risk based on the biology of the tumor. This study demonstrates that the 40-GEP, either as an independent tool or together with traditional methods, accurately identifies patients' risk of metastasis. Using the 40-GEP could improve patient management to improve patient outcomes.

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.

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. METHODS: An integrated 31-GEP (i31-GEP) neural network algorithm incorporating clinicopathologic features with the continuous 31-GEP score was developed using a previously reported patient cohort (n = 1,398) and validated using an independent cohort (n = 1,674). RESULTS: Compared with other covariates in the i31-GEP, the continuous 31-GEP score had the largest likelihood ratio (G2 = 91.3, P < .001) for predicting SLN positivity. The i31-GEP demonstrated high concordance between predicted and observed SLN positivity rates (linear regression slope = 0.999). The i31-GEP increased the percentage of patients with T1-T4 tumors predicted to have < 5% SLN-positive likelihood from 8.5% to 27.7% with a negative predictive value of 98%. Importantly, for patients with T1 tumors originally classified with a likelihood of SLN positivity of 5%-10%, the i31-GEP reclassified 63% of cases as having < 5% or > 10% likelihood of positive SLN, for a more precise, personalized, and clinically actionable SLN-positive likelihood estimate. CONCLUSION: These data suggest the i31-GEP could reduce the number of SLNBs performed by identifying patients with likelihood under the 5% threshold for performance of SLNB and improve the yield of positive SLNBs by identifying patients more likely to have a positive SLNB.

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.

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.

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.

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.

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.

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.

NF-κB and STAT3 co-operation enhances high glucose induced aggressiveness of cholangiocarcinoma cells.

AIMS: The present report aimed to investigate the underlying genes and pathways of high glucose driving cholangiocarcinoma (CCA) aggressiveness. MAIN METHODS: We screened and compared the gene expression profiles obtained by RNA sequencing, of CCA cells cultured in high and normal glucose. Results from the transcriptomic analysis were confirmed in additional cell lines using in vitro migration-invasion assay, Western blotting and immunocytofluorescence. KEY FINDINGS: Data indicated that high glucose increased the expression of interleukin-1ß (IL-1ß), an upstream regulator of nuclear factor-κB (NF-κB) pathway, through the nuclear localization of NF-κB. High glucose-induced NF-κB increased the migration and invasion of CCA cells and the expression of downstream NF-κB targeted genes associated with aggressiveness, including interleukin-6, a potent triggering signal of the signal transducer and activator of transcription 3 (STAT3) pathway. Such effects were reversed by inhibiting NF-κB nuclear translocation which additionally reduced the phosphorylation of STAT3 at Y705. SIGNIFICANCE: These results indicate that NF-κB is activated by high glucose and they suggest that NF-κB interaction with STAT3 enhances CCA aggressiveness. Therefore, targeting multiple pathways such as STAT3 and NF-κB might improve CCA treatment outcome especially in condition such as hyperglycemia.

Accumulation of Molecular Aberrations Distinctive to Hepatocellular Carcinoma Progression.

Cancer develops through the accumulation of genetic and epigenetic aberrations. To identify sequential molecular alterations that occur during the development of hepatocellular carcinoma (HCC), we compared 52 early and 108 overt HCC samples by genome sequencing. Gene mutations in the p53/RB1 pathway, WNT pathway, MLL protein family, SWI/SNF complexes, and AKT/PI3K pathway were common in HCC. In the early phase of all entities, TERT was the most frequently upregulated gene owing to diverse mechanisms. Despite frequent somatic mutations in driver genes, including CTNNB1 and TP53, early HCC was a separate molecular entity from overt HCC, as each had a distinct expression profile. Notably, WNT target genes were not activated in early HCC regardless of CTNNB1 mutation status because ß-catenin did not translocate into the nucleus due to the E-cadherin/ß-catenin complex at the membrane. Conversely, WNT targets were definitively upregulated in overt HCC, with CTNNB1 mutation associated with downregulation of CDH1 and hypomethylation of CpG islands in target genes. Similarly, cell-cycle genes downstream of the p53/RB pathway were upregulated only in overt HCC, with TP53 or RB1 gene mutations associated with chromosomal deletion of 4q or 16q. HCC was epigenetically distinguished into four subclasses: normal-like methylation, global-hypomethylation (favorable prognosis), stem-like methylation (poor prognosis), and CpG island methylation. These methylation statuses were globally maintained through HCC progression. Collectively, these data show that as HCC progresses, additional molecular events exclusive of driver gene mutations cooperatively contribute to transcriptional activation of downstream targets according to methylation status. SIGNIFICANCE: In addition to driver gene mutations in the WNT and p53 pathways, further molecular events are required for aberrant transcriptional activation of these pathways as HCC progresses.