Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE22153, and GSE65904 cohorts from GEO database were processed and harmonized to mitigate batch effects. Lactate metabolism scores were assigned to individual cells using the 'AUCell' package. Weighted Co-expression Network Analysis (WGCNA) was employed to identify gene modules correlated with lactate metabolism. Machine learning algorithms were applied to construct a prognostic model, and its performance was evaluated in multiple cohorts. Immune correlation, mutation analysis, and enrichment analysis were conducted to further characterize the prognostic model's biological implications. Finally, the function of key gene NDUFS7 was verified by cell experiments. Machine learning resulted in an optimal prognostic model, demonstrating significant prognostic value across various cohorts. In the different cohorts, the high-risk group showed a poor prognosis. Immune analysis indicated differences in immune cell infiltration and checkpoint gene expression between risk groups. Mutation analysis identified genes with high mutation loads in SKCM. Enrichment analysis unveiled enriched pathways and biological processes in high-risk SKCM patients. NDUFS7 was found to be a hub gene in the protein-protein interaction network. After the expression of NDUFS7 was reduced by siRNA knockdown, CCK-8, colony formation, transwell and wound healing tests showed that the activity, proliferation and migration of A375 and WM115 cell lines were significantly decreased. This study offers insights into the prognostic significance of lactate metabolism-related genes in SKCM.

Assessment of The Utility of The Sarcoma DNA Methylation Classifier In Surgical Pathology.

Diagnostic classification of soft tissue tumors is based on histology, immunohistochemistry, genetic findings, and radiologic and clinical correlations. Recently, a sarcoma DNA methylation classifier was developed, covering 62 soft tissue and bone tumor entities. The classifier is based on large-scale analysis of methylation sites across the genome. It includes DNA copy number analysis and determines O 6 methylguanine DNA methyl-transferase methylation status. In this study, we evaluated 619 well-studied soft tissue and bone tumors with the sarcoma classifier. Problem cases and typical examples of different entities were included. The classifier had high sensitivity and specificity for fusion sarcomas: Ewing, synovial, CIC -rearranged, and BCOR -rearranged. It also performed well for leiomyosarcoma, malignant peripheral nerve sheath tumors (MPNST), and malignant vascular tumors. There was low sensitivity for diagnoses of desmoid fibromatosis, neurofibroma, and schwannoma. Low specificity of matches was observed for angiomatoid fibrous histiocytoma, inflammatory myofibroblastic tumor, Langerhans histiocytosis, schwannoma, undifferentiated sarcoma, and well-differentiated/dedifferentiated liposarcoma. Diagnosis of lipomatous tumors was greatly assisted by the detection of MDM2 amplification and RB1 loss in the copy plot. The classifier helped to establish diagnoses for KIT-negative gastrointestinal stromal tumors, MPNSTs with unusual immunophenotypes, and undifferentiated melanomas. O 6 methylguanine DNA methyl-transferase methylation was infrequent and most common in melanomas (35%), MPNSTs (11%), and undifferentiated sarcomas (11%). The Sarcoma Methylation Classifier will likely evolve with the addition of new entities and refinement of the present methylation classes. The classifier may also help to define new entities and give new insight into the interrelationships of sarcomas.

Long-term cost-effectiveness of a melanoma prevention program using genomic risk information compared with standard prevention advice in Australia.

PURPOSE: Evidence indicates that a melanoma prevention program using personalized genomic risk provision and genetic counseling can affect prevention behaviors, including reducing sunburns in adults with no melanoma history. This analysis evaluated its longer-term cost-effectiveness from an Australian health system perspective. METHODS: The primary outcome was incremental cost effectiveness ratio (ICER) of genomic risk provision (intervention) compared with standard prevention advice. A decision-analytic Markov model was developed using randomized trial data to simulate lifetime cost-effectiveness. All costs were presented in 2018/19 Australian dollars (AUD). The intervention effect on reduced sunburns was stratified by sex and traditional risk, which was calculated through a validated prediction model. Deterministic and probabilistic sensitivity analyses were undertaken for robustness checks. RESULTS: The per participant cost of intervention was AUD$189. Genomic risk provision targeting high-traditional risk individuals produced an ICER of AUD$35,254 (per quality-adjusted life year gained); sensitivity analyses indicated the intervention would be cost-effective in more than 50% of scenarios. When the intervention was extended to low-traditional risk groups, the ICER was AUD$43,746 with a 45% probability of being cost-effective. CONCLUSION: Genomic risk provision targeted to high-traditional melanoma risk individuals is likely a cost-effective strategy for reducing sunburns and will likely prevent future melanomas and keratinocyte carcinomas.

Early Detection and Prognostic Assessment of Cutaneous Melanoma: Consensus on Optimal Practice and the Role of Gene Expression Profile Testing.

Importance: Therapy for advanced melanoma has transformed during the past decade, but early detection and prognostic assessment of cutaneous melanoma (CM) remain paramount goals. Best practices for screening and use of pigmented lesion evaluation tools and gene expression profile (GEP) testing in CM remain to be defined. Objective: To provide consensus recommendations on optimal screening practices and prebiopsy diagnostic, postbiopsy diagnostic, and prognostic assessment of CM. Evidence Review: Case scenarios were interrogated using a modified Delphi consensus method. Melanoma panelists (n = 60) were invited to vote on hypothetical scenarios via an emailed survey (n = 42), which was followed by a consensus conference (n = 51) that reviewed the literature and the rationale for survey answers. Panelists participated in a follow-up survey for final recommendations on the scenarios (n = 45). Findings: The panelists reached consensus (≥70% agreement) in supporting a risk-stratified approach to melanoma screening in clinical settings and public screening events, screening personnel recommendations (self/partner, primary care provider, general dermatologist, and pigmented lesion expert), screening intervals, and acceptable appointment wait times. Participants also reached consensus that visual and dermoscopic examination are sufficient for evaluation and follow-up of melanocytic skin lesions deemed innocuous. The panelists reached consensus on interpreting reflectance confocal microscopy and some but not all results from epidermal tape stripping, but they did not reach consensus on use of certain pigmented lesion evaluation tools, such as electrical impedance spectroscopy. Regarding GEP scores, the panelists reached consensus that a low-risk prognostic GEP score should not outweigh concerning histologic features when selecting patients to undergo sentinel lymph node biopsy but did not reach consensus on imaging recommendations in the setting of a high-risk prognostic GEP score and low-risk histology and/or negative nodal status. Conclusions and Relevance: For this consensus statement, panelists reached consensus on aspects of a risk-stratified approach to melanoma screening and follow-up as well as use of visual examination and dermoscopy. These findings support a practical approach to diagnosing and evaluating CM. Panelists did not reach consensus on a clearly defined role for GEP testing in clinical decision-making, citing the need for additional studies to establish the clinical use of existing GEP assays.

Economic Evaluation of Three BRAF + MEK Inhibitors for the Treatment of Advanced Unresectable Melanoma With BRAF Mutation From a US Payer Perspective.

BACKGROUND: The combinations of BRAF + MEK inhibitors-encorafenib (ENC) + binimetinib (BIN), cobimetinib (COB) + vemurafenib (VEM), and dabrafenib (DAB) + trametinib (TRA)-are recommended for the treatment of BRAF-mutated advanced melanoma. OBJECTIVE: To assess the cost-effectiveness and cost-utility of ENC + BIN versus COB + VEM versus DAB + TRA from a US payer perspective. METHODS: A Markov model was constructed to simulate a hypothetical cohort over a time horizon of 10 years. The overall survival (OS) and progression-free survival (PFS) curves were independently digitized from a randomized controlled trial for ENC + BIN and fitted using R software. Published and indirectly estimated hazard ratios were used to fit OS and PFS curves for COB + VEM and DAB + TRA. Costs, life-year gains, and quality-adjusted life years (QALYs) associated with the 3 treatment combinations were estimated. A base case analysis and probabilistic sensitivity analysis (PSA) were conducted to estimate the incremental cost-utility ratio (ICUR). A discount rate of 3.5% was applied on cost and outcomes. RESULTS: The ENC + BIN versus COB + VEM comparison was associated with an ICUR of $656 233 per QALY gained. The ENC + BIN versus DAB + TRA comparison was associated with an ICUR of $3 135 269 per QALY gained. The DAB + TRA combination dominated COB + VEM. The base case analysis estimates were confirmed by the PSA estimates. ENC + BIN was the most cost-effective combination at a high willingness-to-pay (WTP) threshold of $573 000 per QALY and $1.5 million/QALY when compared to COB + VEM and DAB + TRA, respectively. CONCLUSION AND RELEVANCE: Given current prices and acceptable WTP thresholds, our study suggests that DAB + TRA is the optimum treatment. In this study, ENC + BIN was cost-effective only at a very high WTP per QALY threshold.

Cost-effectiveness of immune checkpoint inhibition and targeted treatment in combination as adjuvant treatment of patient with BRAF-mutant advanced melanoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) and targeted treatments have improved the health outcomes of patients with advanced melanoma. However, due to the high cost of novel therapies, it is crucial to evaluate their value by considering both effectiveness and cost. To compare the cost-effectiveness of these novel agents (atezolizumab-vemurafenib-cobimetinib, vemurafenib-plus-cobimetinib, dabrafenib-plus-trametinib, and encorafenib-plus-binimetinib) for first-line treatment of metastatic melanoma with the BRAFV600 mutation. METHODS: A patient-level model was developed to project the health outcomes of 4 strategies for patients with advanced melanoma. We estimated transition probabilities from the IMspire150 (ClinicalTrials.gov, NCT02908672), COMBI-AD (NCT01682083), and COLUMBUS (NCT01909453) trials using a parametric survival model. All health outcomes, including direct cost, quality-adjusted life-years (QALYs) and the incremental cost-effectiveness ratio (ICER), were estimated from the US payer perspective. Lifetime cost, QALYs, life-years (LYs), and ICERs were calculated. Univariable and probabilistic sensitivity analyses were performed to test model robustness, along with multiple scenario analyses. RESULTS: Of the 4 competing strategies, atezolizumab-vemurafenib-cobimetinib produced the best health outcomes, and the vemurafenib-cobimetinib strategy was the least expensive option. Atezolizumab-vemurafenib-cobimetinib, dabrafenib-plus-trametinib, and vemurafenib-cobimetinib formed the cost-effective frontier, indicating that the ordered ICERs were $325,113/QALYs for dabrafenib-plus-trametinib vs. vemurafenib-cobimetinib strategies and $2,247,500/QALYs for atezolizumab-vemurafenib-cobimetinib vs. dabrafenib-plus-trametinib strategies. Encorafenib-plus-binimetinib was dominated by the other 3 competing strategies. The drug price and first-line utility significantly influenced the model utcomes. CONCLUSIONS: For BRAF-mutant advanced melanoma, the vemurafenib-cobimetinib strategy could be considered the most cost-effective treatment at the willingness-to-pay threshold of $150,000.

Cost-Effectiveness Analysis of Sequential Treatment Strategies for Advanced Melanoma in Real Life in France.

Nine drugs have been marketed for 10 years for the treatment of advanced melanoma (AM). With half of patients reaching a second line, the optimal sequence of treatments remains unclear. To inform policy-makers about their efficiency, we performed a cost-effectiveness analysis of sequential strategies in clinical practice in France, for BRAF-mutated and wild-type patients. A multistate model was developed to describe treatment sequences, associated costs, and health outcomes over 10 years. Sequences, clinical outcomes, utility scores, and economic data were extracted from the prospective Melbase cohort, collecting individual data in 1518 patients since 2013, from their AM diagnosis until their death. To adjust the differences in patients' characteristics among sequences, weighting by inverse probability was used. In the BRAF-mutated population, the MONO-targeted therapies (TT)-anti-PD1 sequence was the less expensive, whereas the anti-PD1-BI-TT sequence had an incremental cost-effectiveness ratio (ICER) of 180,441 EUR/QALY. Regarding the BRAF wild-type population, the three sequences constituted the cost-effective frontier, with ICERs ranging from 116 to 806,000 EUR/QALY. For BRAF-mutated patients, the sequence anti-PD1-BI-TT appeared to be the most efficient one in BRAF-mutated AM patients until 2018. Regarding the BRAF wild-type population until 2018, the sequence starting with IPI+NIVO appeared inefficient compared to anti-PD1, considering the extra cost for the QALY gained.

Assessment of melanoma precision prevention materials incorporating MC1R genetic risk information.

Few studies have examined cognitive responses to mailed precision prevention materials. MC1R is a robust, well-described melanoma susceptibility marker. The purpose was to assess cognitive responses to generic or precision prevention materials incorporating MC1R genetic risk. Non-Hispanic White participants (n = 1134) enrolled in a randomized controlled trial received either precision prevention materials incorporating MC1R genetic risk (higher/average) or generic prevention (standard) materials. Six months after baseline, 808 (71.3%) participants reported on the amount of prevention materials read (5-point scale); believability and clarity of materials; intention to change preventive behaviors (7-point Likert scale); and recall of their MC1R genetic risk. Comparisons were conducted using Kruskal-Wallis and chi-squared tests. Overall, participants read most to all (Mdn = 4, IQR = 2) of the prevention materials, reported high believability (Mdn = 7, IQR = 1) and clarity (Mdn = 7, IQR = 1), and moderate intention to change preventive behaviors (Mdn = 5, IQR = 2). Higher-risk participants reported slightly less clarity (Mdn = 6, IQR = 2) than either average-risk (Mdn = 6, IQR = 1, p = 2.50 × 10-3) or standard participants (Mdn = 7, IQR = 1, p = 2.30 × 10-5); and slightly less believability (Mdn = 6, IQR = 1) than standard participants (Mdn = 7, IQR = 1, p = .005). Higher-risk participants were 2.21 times as likely (95% CI = 1.43-3.43) to misremember or forget their risk compared to average-risk participants; misremembering was observed only among higher-risk participants (14%). Mailed precision prevention information were mostly read, highly believable and clear, and resulted in moderate levels of intention to change sun protection behaviors, bolstering the feasibility of population-level precision prevention. Defensive reactions may explain lower clarity, believability, and higher incorrect risk recall among higher-risk participants.

Precision prevention uses an individual's genetics, environment, and/or lifestyle to promote prevention behaviors. However, if materials incorporating precision prevention information are not easily accessible, individuals may misinterpret or distrust findings. Few studies have examined participant-reported believability and clarity of mailed precision prevention materials, how much they read, and whether they intend to change preventive behaviors. We assessed genetic risk for melanoma by determining DNA variation at the MC1R gene, a known melanoma risk marker. Participants were mailed either precision prevention materials conveying their MC1R genetic risk or generic (without genetic risk information) prevention materials. Overall, participants read most of the materials, gave high believability and clarity scores, and reported moderate levels of intention to change preventive behavior. However, participants at higher genetic risk had slightly lower believability and clarity scores than the generic group and were more likely to forget or misremember their genetic risk than participants at average genetic risk. Among participants who correctly recalled their genetic risk, differences in believability diminished, while differences in clarity remained. We conclude that precision prevention materials are highly believable and clear, but additional strategies may be necessary to maximize believability, clarity, and risk recall for individuals at a higher genetic risk.

Bioinformatic and Machine Learning Applications in Melanoma Risk Assessment and Prognosis: A Literature Review.

Over 100,000 people are diagnosed with cutaneous melanoma each year in the United States. Despite recent advancements in metastatic melanoma treatment, such as immunotherapy, there are still over 7000 melanoma-related deaths each year. Melanoma is a highly heterogenous disease, and many underlying genetic drivers have been identified since the introduction of next-generation sequencing. Despite clinical staging guidelines, the prognosis of metastatic melanoma is variable and difficult to predict. Bioinformatic and machine learning analyses relying on genetic, clinical, and histopathologic inputs have been increasingly used to risk stratify melanoma patients with high accuracy. This literature review summarizes the key genetic drivers of melanoma and recent applications of bioinformatic and machine learning models in the risk stratification of melanoma patients. A robustly validated risk stratification tool can potentially guide the physician management of melanoma patients and ultimately improve patient outcomes.

Assessment of Risk of Hereditary Predisposition in Patients With Melanoma and/or Mesothelioma and Renal Neoplasia.

Importance: In BAP1 tumor predisposition syndrome, clear cell renal cell carcinoma (RCC) is frequently associated with melanoma and/or mesothelioma, while germline MITF p.E318K alterations are being increasingly reported in melanoma/RCC. Limited data exist on the co-occurrence of melanoma and/or mesothelioma with renal neoplasia and the prevalence of associated germline alterations. Objective: To assess the frequency of melanoma and/or mesothelioma co-occurring with renal neoplasia using our institutional nephrectomy registry and to determine the prevalence of BAP1 and MITF alterations within this cohort. Design, Setting, and Participants: In this genetic association study, medical records from 8295 patients from 1970 to 2018, renal neoplasia co-occurring with melanoma and/or mesothelioma within a single institutional nephrectomy registry was reevaluated based on contemporary histopathologic criteria and the medical records were reviewed. Data were analyzed from September 2019 to May 2021. Main Outcomes and Measures: Identified cases were screened for BAP1 loss using immunohistochemistry; while patients with melanoma and clear cell RCC were screened for MITF p.E318K alterations. Tumors from patients with potential germline alterations were analyzed with comprehensive molecular profiling using a 514-gene next generation sequencing panel. Results: Of a total of 8295 patients, 93 (1.1%; 95% CI, 0.9%-1.4%) had melanoma and/or mesothelioma co-occurring with renal neoplasia (cutaneous melanoma, n = 76; uveal melanoma, n = 11; mesothelioma, n = 6). A total of 69 (74.2%) were male; 24 (25.8%) were female; median age at diagnosis of renal neoplasia was 63 years (IQR, 58-70 years) and the median duration of follow-up was 8.5 years (IQR, 5.0-14.6 years). Two patients with clear cell RCC had germline BAP1 alterations in the setting of cutaneous melanoma and mesothelioma. Two patients with hybrid oncocytic tumors had biallelic inactivation of FLCN in a setting of Birt-Hogg-Dubé (BHD) syndrome associated with uveal melanoma and mesothelioma. Tumor-only screening of clear cell RCC associated with cutaneous (n = 53) and uveal melanoma (n = 6) led to the identification of 1 patient with a likely germline MITF p.E318K alteration. After excluding benign renal neoplasia (such as oncocytoma and angiomyolipoma), alterations of BAP1, FLCN, and MITF were identified in 5 of 81 patients (6.2%) with melanoma and/or mesothelioma and renal neoplasia. In contrast to hybrid oncocytic tumors in BHD, no unique genotype-phenotype correlations were seen for clear cell RCC with pathogenic BAP1/ MITF alterations and VHL loss of function variants. Four of 5 cases (80%) met current National Comprehensive Cancer Network criteria for germline testing based on a combination of age, multifocality, histologic findings, and family history. Conclusions and Relevance: In this genetic association study, findings support the continued use of these National Comprehensive Cancer Network criteria and suggest more stringent screening may be warranted in this patient population.

Cost-Effectiveness of the Dabrafenib Schedule in Combination With Trametinib Compared With Other Targeted Therapies, Immunotherapy, and Dacarbazine for the Treatment of Unresectable or Metastatic Melanoma With BRAFV600 Mutation in Colombia.

OBJECTIVES: Advanced melanoma accounts for 4% of malignant skin tumors, and approximately 80% of deaths are attributed to it. The most frequent mutation of the RAF gene is BRAFV600, which has been associated with a worse prognosis. The objective of the research was to evaluate the cost-effectiveness of the combined regimen of dabrafenib plus trametinib (D + T) compared with other targeted therapies, immunotherapy, and dacarbazine for the treatment of unresectable/metastatic melanoma with BRAFV600 mutation from the perspective of the Colombian health system. METHODS: A partitioned survival model with 3 states (progression-free survival, progression, and death) was used to evaluate the cost-effectiveness for a time horizon of 20 years. Owing to the perspective of the analysis, only direct medical costs were taken into account. The efficacy of the evaluated treatment and the comparators were measured in terms of overall survival and progression-free survival. All costs were expressed in Colombian pesos as of 2018, and outcomes and costs were discounted at 5% annually. Two analysis scenarios were considered, one in which only monitoring and follow-up costs were included in the progression phase and another in which costs of acquisition of possible treatment sequences were also included. RESULTS: In the first scenario (without postprogression medication costs), the combined D + T regimen was a dominant alternative to vemurafenib + cobimetinib but was not a cost-effective option compared with vemurafenib, nivolumab, ipilimumab, nivolumab + ipilimumab, pembrolizumab, and dacarbazine. In the second scenario (with drug costs in postprogression), D + T was dominant compared with vemurafenib + cobimetinib and cost-effective compared with nivolumab and pembrolizumab. Compared with other schemes, the incremental cost-effectiveness ratio was above the threshold of 3 gross domestic product per capita. Probabilistic sensitivity analyses showed that a willingness-to-pay threshold of Col$56 484 300 (US$19 108) per quality-adjusted life-year would not be reached at the current price of schema in Colombia. CONCLUSIONS: The combined scheme could be a cost-effective and even a cost-saving alternative to vemurafenib + cobimetinib, nivolumab, and pembrolizumab if the costs associated with the use of other medications are taken into account after progression to the first line of treatment. Compared with the other comparators, it produces a greater number of quality-adjusted life-years, but the incremental cost-effectiveness ratio is above that of the willingness to pay.

Cost-Effectiveness Analysis of Dabrafenib Plus Trametinib and Vemurafenib as First-Line Treatment in Patients with BRAF V600 Mutation-Positive Unresectable or Metastatic Melanoma in China.

Objective: To evaluate the cost-effectiveness of dabrafenib plus trametinib combination therapy versus vemurafenib as first-line treatment in patients with BRAF V600 mutation-positive unresectable or metastatic melanoma from a healthcare system perspective in China. Methods: This study employed a partitioned survival model with three health states (progression-free survival, post-progression survival and dead) to parameterize the data derived from Combi-v trial and extrapolated to 30 years. Health states' utilities were measured by EQ-5D-3L, also sourced from the Combi-v trial. Costs including drug acquisition costs, disease management costs and adverse event costs were based on the Chinese Drug Bidding Database and physician survey in China. The primary outcomes of the model were lifetime costs, life-years (LYs), quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses were conducted, respectively. Result: Dabrafenib plus trametinib is projected to increase a patient's life expectancy by 0.95 life-years over vemurafenib (3.03 vs. 2.08) and 1.09 QALY gains (2.48 vs. 1.39) with an incremental cost of $3833. The incremental cost-effectiveness ratio (ICER) was $3511 per QALY. In the probabilistic sensitivity analyses, at a threshold of $33,357 per QALY (three times the gross domestic product (GDP) per capita in China in 2020), the probability of dabrafenib plus trametinib being cost-effective was 90%. In the deterministic sensitivity analyses, the results were most sensitive to the dabrafenib plus trametinib drug costs, vemurafenib drug costs and discount rate of cost. Conclusion: Dabrafenib plus trametinib therapy yields more clinical benefits than vemurafenib. Using a threshold of $33,357 per QALY, dabrafenib plus trametinib is very cost-effective as compared with vemurafenib in China.

Cost-Effectiveness Analysis of Adjuvant Therapy for BRAF-Mutant Resected Stage III Melanoma in Medicare Patients.

BACKGROUND: Adjuvant therapy for stage III melanoma improves several measures of patient survival. However, decisions regarding inclusion of adjuvant therapies in the formularies of public payers necessarily consider the cost-effectiveness of those treatments. The objective of this study is to evaluate the cost-effectiveness of four recently approved adjuvant therapies for BRAF-mutant stage III melanoma in the Medicare patient population. METHODS: In this cost-effectiveness analysis, a Markov microsimulation model was used to simulate the healthcare trajectory of patients randomized to receive either first-line targeted therapy (dabrafenib-trametinib) or immunotherapy (ipilimumab, nivolumab, or pembrolizumab). The base case was a 65-year-old Medicare patient with BRAF V600E-mutant resected stage III melanoma. Possible health states included recurrence-free survival, adverse events, local recurrence, distant metastases, and death. Transition probabilities were determined from published clinical trials. Costs were estimated from reimbursement rates reported by CMS and the Red Book drug price database. Primary outcomes were costs (US$), life years, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). Model robustness was evaluated using one-way and probabilistic sensitivity analyses. RESULTS: Dabrafenib-trametinib provided 1.83 QALYs over no treatment and 0.23 QALYs over the most effective immunotherapy, pembrolizumab. Dabrafenib-trametinib was associated with an ICER of $95,758/QALY over no treatment and $285,863/QALY over pembrolizumab. Pembrolizumab yielded an ICER of $68,396/QALY over no treatment and dominated other immunotherapies. CONCLUSIONS: Pembrolizumab is cost-effective at a conventional willingness-to-pay (WTP) threshold, but dabrafenib-trametinib is not. Though dabrafenib-trametinib offers incremental QALYs, optimization of drug pricing is necessary to ensure dabrafenib-trametinib is accessible at an acceptable WTP threshold.

Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis.

PURPOSE: To date there has not been an extensive analysis of the outcomes of biomarker use in oncology. METHODS: Data were pooled across four indications in oncology drawing upon trial outcomes from www.clinicaltrials.gov: breast cancer, non-small cell lung cancer (NSCLC), melanoma and colorectal cancer from 1998 to 2017. We compared the likelihood drugs would progress through the stages of clinical trial testing to approval based on biomarker status. This was done with multi-state Markov models, tools that describe the stochastic process in which subjects move among a finite number of states. RESULTS: Over 10000 trials were screened, which yielded 745 drugs. The inclusion of biomarker status as a covariate significantly improved the fit of the Markov model in describing the drug trajectories through clinical trial testing stages. Hazard ratios based on the Markov models revealed the likelihood of drug approval with biomarkers having nearly a fivefold increase for all indications combined. A 12, 8 and 7-fold hazard ratio was observed for breast cancer, melanoma and NSCLC, respectively. Markov models with exploratory biomarkers outperformed Markov models with no biomarkers. CONCLUSION: This is the first systematic statistical evidence that biomarkers clearly increase clinical trial success rates in three different indications in oncology. Also, exploratory biomarkers, long before they are properly validated, appear to improve success rates in oncology. This supports early and aggressive adoption of biomarkers in oncology clinical trials.

Relatively mild symptoms after chronic overdose with a double-dose encorafenib: a case report.

Encorafenib (Braftovi) is indicated for the treatment of adult patients with unresectable or metastatic melanoma with a BRAF V600 mutation, in combination with binimetinib (Mektovi). According to the product label of encorafenib, there are no specific treatment recommendations in case of an overdose. We report on a 63-year-old man who ingested a double dose (900 mg) of encorafenib for 16 days. He developed overall minor chronic overdose symptoms such as nausea and vomiting grade 1 and muscle pain. Based on the most occurring adverse events of encorafenib, liver values, kidney function parameters and QTc interval were measured. Kidney function parameters were normal, whereas liver values were slightly increased (grade 1) and QTc slightly prolonged. The plasma concentration 3 h after the last dose was 2110 ng/mL. We describe the course of a case with a chronic overdose during 16 days of the double dose of encorafenib as well as the followed approach, which could be taken into account when observing an encorafenib overdose. Providing information in times of Covid-19 is challenging, but remains necessary for good clinical care.

FRAMe: Familial Risk Assessment of Melanoma-a risk prediction tool to guide CDKN2A germline mutation testing in Australian familial melanoma.

Germline mutations in CDKN2A greatly increase risk of developing cutaneous melanoma. We have constructed a risk prediction model, Familial Risk Assessment of Melanoma (FRAMe), for estimating the likelihood of carrying a heritable CDKN2A mutation among Australian families, where the prevalence of these mutations is low. Using logistic regression, we analysed characteristics of 299 Australian families recruited through the Sydney site of GenoMEL (international melanoma genetics consortium) with at least three cases of cutaneous melanoma (in situ and invasive) among first-degree blood relatives, for predictors of the presence of a pathogenic CDKN2A mutation. The final multivariable prediction model was externally validated in an independent cohort of 61 melanoma kindreds recruited through GenoMEL Queensland. Family variables independently associated with the presence of a CDKN2A mutation in a multivariable model were number of individuals diagnosed with melanoma under 40 years of age, number of individuals diagnosed with more than one primary melanoma, and number of individuals blood related to a melanoma case in the first degree diagnosed with any cancer excluding melanoma and non-melanoma skin cancer. The number of individuals diagnosed with pancreatic cancer was not independently associated with mutation status. The risk prediction model had an area under the receiver operating characteristic curve (AUC) of 0.851 (95% CI 0.793, 0.909) in the training dataset, and 0.745 (95%CI 0.612, 0.877) in the validation dataset. This model is the first to be developed and validated using only Australian data, which is important given the higher rate of melanoma in the population. This model will help to effectively identify families suitable for genetic counselling and testing in areas of high ambient ultraviolet radiation. A user-friendly electronic nomogram is available at www.melanomarisk.org.au .

Quality assessment of a clinical next-generation sequencing melanoma panel within the Italian Melanoma Intergroup (IMI).

BACKGROUND: Identification of somatic mutations in key oncogenes in melanoma is important to lead the effective and efficient use of personalized anticancer treatment. Conventional methods focus on few genes per run and, therefore, are unable to screen for multiple genes simultaneously. The use of Next-Generation Sequencing (NGS) technologies enables sequencing of multiple cancer-driving genes in a single assay, with reduced costs and DNA quantity needed and increased mutation detection sensitivity. METHODS: We designed a customized IMI somatic gene panel for targeted sequencing of actionable melanoma mutations; this panel was tested on three different NGS platforms using 11 metastatic melanoma tissue samples in blinded manner between two EMQN quality certificated laboratory. RESULTS: The detection limit of our assay was set-up to a Variant Allele Frequency (VAF) of 10% with a coverage of at least 200x. All somatic variants detected by all NGS platforms with a VAF ≥ 10%, were also validated by an independent method. The IMI panel achieved a very good concordance among the three NGS platforms. CONCLUSION: This study demonstrated that, using the main sequencing platforms currently available in the diagnostic setting, the IMI panel can be adopted among different centers providing comparable results.

Cost-Benefit Implication of Gene Expression Profiling and Adjuvant Therapy in Stage IIIA Melanoma.

BACKGROUND: Indiscriminate use of adjuvant therapy in stage IIIA melanoma is controversial. We sought to model the clinical impact and cost of implementing a gene expression profile (GEP) test to guide adjuvant therapy. STUDY DESIGN: A Markov decision-analysis model was created to represent resected stage IIIA melanoma with 3 treatment options: observation (OBS), adjuvant pembrolizumab for all patients (ALL), and selective adjuvant therapy (SEL). In the SEL option, only high-risk patients based on GEP stratification were treated with pembrolizumab. Cost of adjuvant therapy was normalized to reflect Medicare reimbursement schedules. The primary outcome was cost per mortality avoided at 10 years. RESULTS: Model projections for 10-year overall survival were 68% for OBS, 73% for SEL, and 76% for ALL. The estimated incremental cost-per-mortality-avoided (compared to OBS) was $2.1 million for SEL and $2.4 million for ALL. These translate to costs of $583.0K and $697.1K per life-year for the SEL and ALL strategies, respectively. CONCLUSIONS: Routine adjuvant pembrolizumab for stage IIIA melanoma is costly, and risk-stratification by GEP only marginally improves the value of therapy.

SOX10 is as specific as S100 protein in detecting metastases of melanoma in lymph nodes and is recommended for sentinel lymph node assessment.

BACKGROUND: Sentinel lymph node (SLN) biopsy remains crucial for melanoma staging. The European Organisation for Research and Treatment of Cancer Melanoma Group recommends performing immunohistochemical stainings for reproducible identification of melanoma metastases. S100 protein (pS100) is a commonly used melanocytic antigen because of its high sensitivity in spite of relatively low specificity. SRY-related HMG-box 10 protein (SOX10) is a transcription factor characterising neural crest-derived cells. It is uniformly expressed mostly in the nuclei of melanocytes, neural, and myoepithelial cells. Pathologists sometimes prefer SOX10 as a melanoma marker, but it has not yet been investigated on a large-scale to confirm that it is reliable and recommendable for routine SLN evaluation. METHODS: Four hundred one treatment-naïve lymph node (LN) metastatic melanomas were included in high-density tissue microarrays and were assessed for the presence of SOX10 and pS100 by immunohistochemistry. The slides were digitalised, shared and evaluated by a panel of experienced melanoma pathologists. RESULTS: The vast majority of melanomas were double-positive for pS100 and SOX10 (93.2%); a small percentage of the cases (3.9%) were double-negative melanomas. Discordance between the two markers was observed: 1.9% pS100(-)/SOX10(+) and 0.75% pS100(+)/SOX10(-). SOX10 was not expressed by immune cell types in the LN, resulting in a less controversial interpretation of the staining. CONCLUSIONS: SOX10 is as equally specific as pS100 for the detection of melanoma metastases in LNs. The interpretation of SOX10 staining is highly reproducible among different centres and different pathologists because of the absence of staining of immune cells.