Abstract Introduction We are conducting a multicenter study to identify classifiers predictive of disease-specific survival in patients with primary melanomas. Here we delineate the unique aspects, challenges, and best practices for optimizing a study of generally small-sized pigmented tumor samples including primary melanomas of at least 1.05mm from AJTCC TNM stage IIA-IIID patients. This ongoing study will target 1,000 melanomas within the international InterMEL consortium. We also evaluated tissue-derived predictors of extracted nucleic acids’ quality and success in downstream testing. Methods Following a pre-established protocol, participating centers ship formalin-fixed paraffin embedded (FFPE) tissue sections to Memorial Sloan Kettering Cancer Center for the centralized handling, dermatopathology review and histology-guided coextraction of RNA and DNA. Samples are distributed for evaluation of somatic mutations using next gen sequencing (NGS) with the MSK-IMPACT™ assay, methylation-profiling (array), and miRNA expression (Nanostring nCounter). Results Sufficient material was obtained for screening of miRNA expression in 683/685 (99%) eligible melanomas, methylation in 467 (68%), and somatic mutations in 560 (82%). In 446/685 (65%) cases, aliquots of RNA/DNA were sufficient for testing with all three platforms. Among samples evaluated by the time of this analysis, the mean NGS coverage was 249x, 59 (18.6%) samples had coverage below 100x, and 41/414 (10%) failed methylation QC due to low intensity probes or insufficient Meta-Mixed Interquartile (BMIQ)- and single sample (ss)- Noob normalizations. Six of 683 RNAs (1%) failed Nanostring QC due to the low proportion of probes above the minimum threshold. Age of the FFPE tissue blocks (p<0.001) and time elapsed from sectioning to co-extraction (p=0.002) were associated with methylation screening failures. Melanin reduced the ability to amplify fragments of 200bp or greater (absent/lightly pigmented vs heavily pigmented, p<0.003). Conversely, heavily pigmented tumors rendered greater amounts of RNA (p<0.001), and of RNA above 200 nucleotides (p<0.001). Conclusion Our experience with many archival tissues demonstrates that with careful management of tissue processing and quality control it is possible to conduct multi-omic studies in a complex multi-institutional setting for investigations involving minute quantities of FFPE tumors, as in studies of early-stage melanoma.
Immune checkpoint inhibitors have improved survival in advanced stage melanoma patients. Rates of new primary melanomas (NPM) in patients with prior melanoma have been reported to be as high as 12%. Little is currently known regarding the frequency or characteristics of NPMs occurring in melanoma patients treated with immune checkpoint inhibitors.To determine the frequency and describe clinicopathologic characteristics of NPMs diagnosed in patients during or after treatment with immune checkpoint inhibitors for metastatic melanoma.A retrospective analysis of prospectively collected data from the Melanoma Institute Australia and Westmead Hospital Dermatology databases. Clinicopathological data for the initial primary melanoma (IPM) and NPM were compared.Between 2013-2017, 14 NPMs in 13 patients (out of a total of 1047) treated with checkpoint inhibitors were identified. NPMs were significantly thinner than the IPM (median Breslow thickness 0.35 mm vs 2.0 mm, P = 0.0003), less likely to be ulcerated (0/14 vs 6/13, P = 0.004) and less likely to have nodal metastases (0/14 vs 6/13, P = 0.004). NPMs were significantly more likely to be detected in the in-situ stage (6/14 vs 0/13, P = 0.0016).NPMs are infrequent in patients treated with checkpoint inhibitors. When they occur, they are usually detected at an early stage and have features associated with a favourable prognosis, most likely reflecting close surveillance. Further study is required to determine long-term risk in patients achieving a durable response to immune checkpoint inhibitors, and to determine whether the immunotherapy itself influences both their development and biology.
Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.
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