Results of a randomized, double-blind phase II clinical trial of NY-ESO-1 vaccine with ISCOMATRIX adjuvant versus ISCOMATRIX alone in participants with high-risk resected melanoma.

BACKGROUND: To compare the clinical efficacy of New York Esophageal squamous cell carcinoma-1 (NY-ESO-1) vaccine with ISCOMATRIX adjuvant versus ISCOMATRIX alone in a randomized, double-blind phase II study in participants with fully resected melanoma at high risk of recurrence. METHODS: Participants with resected stage IIc, IIIb, IIIc and IV melanoma expressing NY-ESO-1 were randomized to treatment with three doses of NY-ESO-1/ISCOMATRIX or ISCOMATRIX adjuvant administered intramuscularly at 4-week intervals, followed by a further dose at 6 months. Primary endpoint was the proportion free of relapse at 18 months in the intention-to-treat (ITT) population and two per-protocol populations. Secondary endpoints included relapse-free survival (RFS) and overall survival (OS), safety and NY-ESO-1 immunity. RESULTS: The ITT population comprised 110 participants, with 56 randomized to NY-ESO-1/ISCOMATRIX and 54 to ISCOMATRIX alone. No significant toxicities were observed. There were no differences between the study arms in relapses at 18 months or for median time to relapse; 139 vs 176 days (p=0.296), or relapse rate, 27 (48.2%) vs 26 (48.1%) (HR 0.913; 95% CI 0.402 to 2.231), respectively. RFS and OS were similar between the study arms. Vaccine recipients developed strong positive antibody responses to NY-ESO-1 (p≤0.0001) and NY-ESO-1-specific CD4+ and CD8+ responses. Biopsies following relapse did not demonstrate differences in NY-ESO-1 expression between the study populations although an exploratory study demonstrated reduced (NY-ESO-1)+/Human Leukocyte Antigen (HLA) class I+ double-positive cells in biopsies from vaccine recipients performed on relapse in 19 participants. CONCLUSIONS: The vaccine was well tolerated, however, despite inducing antigen-specific immunity, it did not affect survival endpoints. Immune escape through the downregulation of NY-ESO-1 and/or HLA class I molecules on tumor may have contributed to relapse

Reply to 'Comment on 'Efficacy and toxicity of treatment with the anti-CTLA-4 antibody ipilimumab in patients with metastatic melanoma after prior anti-PD-1 therapy''.

Background: Recent phase III clinical trials have established the superiority of the anti-PD-1 antibodies pembrolizumab and nivolumab over the anti-CTLA-4 antibody ipilimumab in the first-line treatment of patients with advanced melanoma. Ipilimumab will be considered for second-line treatment after the failure of anti-PD-1 therapy. Methods: We retrospectively identified a cohort of 40 patients with metastatic melanoma who received single-agent anti-PD-1 therapy with pembrolizumab or nivolumab and were treated on progression with ipilimumab at a dose of 3 mg kg(-1) for a maximum of four doses. Results: Ten percent of patients achieved an objective response to ipilimumab, and an additional 8% experienced prolonged (>6 months) stable disease. Thirty-five percent of patients developed grade 3-5 immune-related toxicity associated with ipilimumab therapy. The most common high-grade immune-related toxicity was diarrhoea. Three patients (7%) developed grade 3-5 pneumonitis leading to death in one patient. Conclusions: Ipilimumab therapy can induce responses in patients who fail the anti-PD-1 therapy with response rates comparable to previous reports. There appears to be an increased frequency of high-grade immune-related adverse events including pneumonitis that warrants close surveillance

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Systems analysis identifies miR-29b regulation of invasiveness in melanoma

BACKGROUND: In many cancers, microRNAs (miRs) contribute to metastatic progression by modulating phenotypic reprogramming processes such as epithelial-mesenchymal plasticity. This can be driven by miRs targeting multiple mRNA transcripts, inducing regulated changes across large sets of genes. The miR-target databases TargetScan and DIANA-microT predict putative relationships by examining sequence complementarity between miRs and mRNAs. However, it remains a challenge to identify which miR-mRNA interactions are active at endogenous expression levels, and of biological consequence. METHODS: We developed a workflow to integrate TargetScan and DIANA-microT predictions into the analysis of data-driven associations calculated from transcript abundance (RNASeq) data, specifically the mutual information and Pearson's correlation metrics. We use this workflow to identify putative relationships of miR-mediated mRNA repression with strong support from both lines of evidence. Applying this approach systematically to a large, published collection of unique melanoma cell lines - the Ludwig Melbourne melanoma (LM-MEL) cell line panel - we identified putative miR-mRNA interactions that may contribute to invasiveness. This guided the selection of interactions of interest for further in vitro validation studies. RESULTS: Several miR-mRNA regulatory relationships supported by TargetScan and DIANA-microT demonstrated differential activity across cell lines of varying matrigel invasiveness. Strong negative statistical associations for these putative regulatory relationships were consistent with target mRNA inhibition by the miR, and suggest that differential activity of such miR-mRNA relationships contribute to differences in melanoma invasiveness. Many of these relationships were reflected across the skin cutaneous melanoma TCGA dataset, indicating that these observations also show graded activity across clinical samples. Several of these miRs are implicated in cancer progression (miR-211, -340, -125b, -221, and -29b). The specific role for miR-29b-3p in melanoma has not been well studied. We experimentally validated the predicted miR-29b-3p regulation of LAMC1 and PPIC and LASP1, and show that dysregulation of miR-29b-3p or these mRNA targets can influence cellular invasiveness in vitro. CONCLUSIONS: This analytic strategy provides a comprehensive, systems-level approach to identify miR-mRNA regulation in high-throughput cancer data, identifies novel putative interactions with functional phenotypic relevance, and can be used to direct experimental resources for subsequent experimental validation. Computational scripts are available: http://github.com/uomsystemsbiology/LMMEL-miR-miner