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Adjuvant dabrafenib plus trametinib reduced the risk of relapse versus placebo in patients with resected, BRAFV600-mutant, stage III melanoma in the phase 3 COMBI-AD trial. This prespecified exploratory biomarker analysis aimed to evaluate potential prognostic or predictive factors and mechanisms of resistance to adjuvant targeted therapy. COMBI-AD is a randomised, double-blind, placebo-controlled, phase 3 trial comparing dabrafenib 150 mg orally twice daily plus trametinib 2 mg orally once daily versus two matched placebos. Study participants were at least 18 years of age and underwent complete resection of stage IIIA (lymph node metastases >1 mm), IIIB, or IIIC cutaneous melanoma, per American Joint Committee on Cancer 7th edition criteria, with a BRAFV600E or BRAFV600K mutation. Patients were randomly assigned (1:1) to the two treatment groups by an interactive voice response system, stratified by mutation type and disease stage. Patients, physicians, and the investigators who analysed data were masked to treatment allocation. The primary outcome was relapse-free survival, defined as the time from randomisation to disease recurrence or death from any cause. Biomarker assessment was a prespecified exploratory outcome of the trial. We assessed intrinsic tumour genomic features by use of next-generation DNA sequencing and characteristics of the tumour microenvironment by use of a NanoString RNA assay, which might provide prognostic and predictive information. This trial is registered with ClinicalTrials.gov, number NCT01682083, and is ongoing but no longer recruiting participants. Between Jan 31, 2013, and Dec 11, 2014, 870 patients were enrolled in the trial. Median follow-up at data cutoff (April 30, 2018) was 44 months (IQR 38–49) in the dabrafenib plus trametinib group and 42 months (21–49) in the placebo group. Intrinsic tumour genomic features were assessed in 368 patients (DNA sequencing set) and tumour microenvironment characteristics were assessed in 507 patients (NanoString biomarker set). MAPK pathway genomic alterations at baseline did not affect treatment benefit or clinical outcome. An IFNγ gene expression signature higher than the median was prognostic for prolonged relapse-free survival in both treatment groups. Tumour mutational burden was independently prognostic for relapse-free survival in the placebo group (high TMB, top third; hazard ratio [HR] 0·56, 95% CI 0·37–0·85, p=0·0056), but not in the dabrafenib plus trametinib group (0·83, 95% CI 0·53–1·32, p=0·44). Patients with tumour mutational burden in the lower two terciles seem to derive a substantial long-term relapse-free survival benefit from targeted therapy (HR [versus placebo] 0·49, 95% CI 0·35–0·68, p<0·0001). However, patients with high tumour mutational burden seem to have a less pronounced benefit with targeted therapy (HR [versus placebo] 0·75, 95% CI 0·44–1·26, p=0·27), especially if they had an IFNγ signature lower than the median (HR 0·88 [95% CI 0·40–1·93], p=0·74). Tumour mutational burden alone or in combination with IFNγ gene expression signature or other markers for an adaptive immune response might be of relevance for identifying patients with stage III melanoma who might derive clinical benefit from targeted therapy. Further validation in prospective clinical trials is warranted. Novartis Pharmaceuticals.

Immune and targeted therapies achieve long-term survival in metastatic melanoma; however, new treatment strategies are needed to improve patients’ outcomes 1 , 2 . We report on the efficacy, safety and biomarker analysis from the single-arm safety run-in (part 1; n  = 9) and biomarker (part 2; n  = 27) cohorts of the randomized, placebo-controlled, phase 3 COMBI-i trial ( NCT02967692 ) of the anti-PD-1 antibody spartalizumab, in combination with the BRAF inhibitor dabrafenib and MEK inhibitor trametinib. Patients ( n  = 36) had previously untreated BRAF V600-mutant unresectable or metastatic melanoma. In part 1, the recommended phase 3 regimen was identified based on the incidence of dose-limiting toxicities (DLTs; primary endpoint): 400 mg of spartalizumab every 4 weeks plus 150 mg of dabrafenib twice daily plus 2 mg of trametinib once daily. Part 2 characterized changes in PD-L1 levels and CD8 + cells following treatment (primary endpoint), and analyzed additional biomarkers. Assessments of efficacy and safety were key secondary endpoints (median follow-up, 24.3 months). Spartalizumab plus dabrafenib and trametinib led to an objective response rate (ORR) of 78%, including 44% complete responses (CRs). Grade ≥3 treatment-related adverse events (TRAEs) were experienced by 72% of patients. All patients had temporary dose modifications, and 17% permanently discontinued all three study drugs due to TRAEs. Early progression-free survival (PFS) events were associated with low tumor mutational burden/T cell–inflamed gene expression signature (GES) or high immunosuppressive tumor microenvironment (TME) GES levels at baseline; an immunosuppressive TME may also preclude CR. Overall, the efficacy, safety and on-treatment biomarker modulations associated with spartalizumab plus dabrafenib and trametinib are promising, and biomarkers that may predict long-term benefit were identified. Clinical activity and biomarker analysis from the COMBI-i trial evaluating PD-1, BRAF and MEK inhibition in patients with metastatic melanoma demonstrate high response rates and uncover molecular correlates of long-term treatment benefit.

Background CRISPR-Cas9 dropout screens are formidable tools for investigating biology with unprecedented precision and scale. However, biases in data lead to potential confounding effects on interpretation and compromise overall quality. The activity of Cas9 is influenced by structural features of the target site, including copy number amplifications (CN bias). More worryingly, proximal targeted loci tend to generate similar gene-independent responses to CRISPR-Cas9 targeting (proximity bias), possibly due to Cas9-induced whole chromosome-arm truncations or other genomic structural features and different chromatin accessibility levels. Results We benchmarked eight computational methods, rigorously evaluating their ability to reduce both CN and proximity bias in the two largest publicly available cell-line-based CRISPR-Cas9 screens to date. We also evaluated the capability of each method to preserve data quality and heterogeneity by assessing the extent to which the processed data allows accurate detection of true positive essential genes, established oncogenetic addictions, and known/novel biomarkers of cancer dependency. Our analysis sheds light on the ability of each method to correct biases under different scenarios. AC-Chronos outperforms other methods in correcting both CN and proximity biases when jointly processing multiple screens of models with available CN information, whereas CRISPRcleanR is the top performing method for individual screens or when CN information is not available. In addition, Chronos and AC-Chronos yield a final dataset better able to recapitulate known sets of essential and non-essential genes. Conclusions Overall, our investigation provides guidance for the selection of the most appropriate bias-correction method, based on its strengths, weaknesses and experimental settings.

Overrepresentation analysis is used to identify biological enrichment in a list of genes. Here, we introduce GeneTEA, a model that ingests free-text gene descriptions and incorporates natural language processing methods to learn a sparse gene-by-term embedding, which can be treated as a de novo gene set database. In benchmarks against existing overrepresentation analysis tools, only GeneTEA properly controls false discovery while consistently surfacing the most relevant biology, doing so with less redundancy. We show that the same approach can be applied to other organisms’ genomes or compounds. Furthermore, we provide an interactive app and API for the trained GeneTEA model.

In patients with metastatic cancer, spatial heterogeneity of somatic alterations may lead to incomplete assessment of a cancer’s mutational profile when analyzing a single tumor biopsy. In this study, we perform sequencing of cell-free DNA (cfDNA) and distinct metastatic tissue samples from ten rapid autopsy cases with pre-treated metastatic cancer. We show that levels of heterogeneity in genetic biomarkers vary between patients but that gene expression signatures representative of the tumor microenvironment are more consistent. Across nine patients with plasma samples available, we are able to detect 62/62 truncal and 47/121 non-truncal point mutations in cfDNA. We observe that mutation clonality in cfDNA is correlated with the number of metastatic lesions in which the mutation is detected and use this result to derive a clonality threshold to classify truncal and non-truncal driver alterations with reasonable specificity. In contrast, mutation truncality is more often incorrectly assigned when studying single tissue samples. Our results demonstrate the utility of a single cfDNA sample relative to that of single tissue samples when treating patients with metastatic cancer. It is currently unclear if cell-free DNA samples from metastatic cancers are as informative as tissue ones for cancer profiling. Here the authors show that cell-free DNA samples from rapid autopsies capture clonal and subclonal alterations of metastatic tumours and reveal more driver alterations than single tissue samples.

Background Matched sequencing of both tumor and normal tissue is routinely used to classify variants of uncertain significance (VUS) into somatic vs. germline. However, assays used in molecular diagnostics focus on known somatic alterations in cancer genes and often only sequence tumors. Therefore, an algorithm that reliably classifies variants would be helpful for retrospective exploratory analyses. Contamination of tumor samples with normal cells results in differences in expected allelic fractions of germline and somatic variants, which can be exploited to accurately infer genotypes after adjusting for local copy number. However, existing algorithms for determining tumor purity, ploidy and copy number are not designed for unmatched short read sequencing data. Results We describe a methodology and corresponding open source software for estimating tumor purity, copy number, loss of heterozygosity (LOH), and contamination, and for classification of single nucleotide variants (SNVs) by somatic status and clonality. This R package, PureCN, is optimized for targeted short read sequencing data, integrates well with standard somatic variant detection pipelines, and has support for matched and unmatched tumor samples. Accuracy is demonstrated on simulated data and on real whole exome sequencing data. Conclusions Our algorithm provides accurate estimates of tumor purity and ploidy, even if matched normal samples are not available. This in turn allows accurate classification of SNVs. The software is provided as open source (Artistic License 2.0) R/Bioconductor package PureCN ( http://bioconductor.org/packages/PureCN/ ).

Background Somatic alterations in the cancer genome, some of which are associated with changes in gene expression, have been characterized in multiple studies across diverse cancer types. However, less is known about germline variants that influence tumor biology by shaping the cancer transcriptome. Methods We performed expression quantitative trait loci (eQTL) analyses using multi-dimensional data from The Cancer Genome Atlas to explore the role of germline variation in mediating the cancer transcriptome. After accounting for associations between somatic alterations and gene expression, we determined the contribution of inherited variants to the cancer transcriptome relative to that of somatic variants. Finally, we performed an interaction analysis using estimates of tumor cellularity to identify cell type-restricted eQTLs. Results The proportion of genes with at least one eQTL varied between cancer types, ranging between 0.8% in melanoma to 28.5% in thyroid cancer and was correlated more strongly with intratumor heterogeneity than with somatic alteration rates. Although contributions to variance in gene expression was low for most genes, some eQTLs accounted for more than 30% of expression of proximal genes. We identified cell type-restricted eQTLs in genes known to be cancer drivers including LPP and EZH2 that were associated with disease-specific mortality in TCGA but not associated with disease risk in published GWAS. Together, our results highlight the need to consider germline variation in interpreting cancer biology beyond risk prediction.

Evan Eichler and colleagues explore the structural diversity and ancestral origins of the 17q21.31 inversion region. They find that complex duplication architectures have arisen independently on both inversion haplotypes and have recently reached high frequencies among Europeans, either through extraordinary genetic drift or selective sweeps. The 17q21.31 inversion polymorphism exists either as direct (H1) or inverted (H2) haplotypes with differential predispositions to disease and selection. We investigated its genetic diversity in 2,700 individuals, with an emphasis on African populations. We characterize eight structural haplotypes due to complex rearrangements that vary in size from 1.08–1.49 Mb and provide evidence for a 30-kb H1-H2 double recombination event. We show that recurrent partial duplications of the KANSL1 gene have occurred on both the H1 and H2 haplotypes and have risen to high frequency in European populations. We identify a likely ancestral H2 haplotype (H2′) lacking these duplications that is enriched among African hunter-gatherer groups yet essentially absent from West African populations. Whereas H1 and H2 segmental duplications arose independently and before human migration out of Africa, they have reached high frequencies recently among Europeans, either because of extraordinary genetic drift or selective sweeps.

While BRAF inhibitor combinations with EGFR and/or MEK inhibitors have improved clinical efficacy in BRAF V600E colorectal cancer (CRC), response rates remain low and lack durability. Preclinical data suggest that BRAF/MAPK pathway inhibition may augment the tumor immune response. We performed a proof-of-concept single-arm phase 2 clinical trial of combined PD-1, BRAF and MEK inhibition with sparatlizumab (PDR001), dabrafenib and trametinib in 37 patients with BRAF V600E CRC. The primary end point was overall response rate, and the secondary end points were progression-free survival, disease control rate, duration of response and overall survival. The study met its primary end point with a confirmed response rate (24.3% in all patients; 25% in microsatellite stable patients) and durability that were favorable relative to historical controls of BRAF-targeted combinations alone. Single-cell RNA sequencing of 23 paired pretreatment and day 15 on-treatment tumor biopsies revealed greater induction of tumor cell-intrinsic immune programs and more complete MAPK inhibition in patients with better clinical outcome. Immune program induction in matched patient-derived organoids correlated with the degree of MAPK inhibition. These data suggest a potential tumor cell-intrinsic mechanism of cooperativity between MAPK inhibition and immune response, warranting further clinical evaluation of optimized targeted and immune combinations in CRC. ClinicalTrials.gov registration: NCT03668431. Patients with BRAF V600E -mutated colorectal cancer have encouraging overall response rates to inhibition of PD-1, BRAF and MEK, with translational analyses suggesting that induction of tumor-intrinsic programs and immune programs contributes to improved outcomes via MAPK inhibition.