Previous studies aimed at the genomic characterization of melanoma led to the classification of four genomic subtypes based on the presence of mutations in the three most frequently mutated, mutually exclusive, driver genes: BRAF, NRAS, NF1 and Triple WT (wild-type). Triple WT melanomas experience the lowest mutational burden, and significantly mutated genes (SMGs) in this subtype have yet to be identified. The mutational spectra of Triple WT melanomas also display low contributions of mutational signature 7 (UV mutagenesis), which is in stark contrast to the other melanoma subtypes, suggesting that other mutational processes are driving Triple WT melanomas. Aggregation of a larger melanoma cohort followed by harmonized and uniform genomic analysis would enable the identification of SMGs, pathways, copy-number alterations (CNAs) and mutational processes implicated at lower frequencies, as well as enrich for Triple WT melanomas. These subtypes also display diverse clinical characteristics, outcomes and immune profiles. Thus, more detailed genomic characterization of these subtypes will be paramount to identifying novel biological targets and therapeutic vulnerabilities of low frequency driver genes, pathways, and mutational processes. The spectrum of noncoding mutations and structural variants (SV) in melanoma remains largely undefined. Previous studies have considered transcription factor binding sites as a single entity, and primarily focused on mutations in promoter regions. However, vast resources exist to study the localization of noncoding mutations and SVs with respect to chromatin architecture, regulatory elements and other epigenomic factors. Thus, aggregation of a larger cohort of melanoma whole-genomes would elucidate the spectrum of noncoding mutations and SVs, and their interplay with melanocyte chromatin architecture and regulatory mechanisms. In this proposed research, I will aggregate upwards of 1000 melanoma whole-exome samples from previously published studies and perform harmonized genomic analysis. Specifically, I will identify SMGs both across and within subtypes, transcriptional differences between the subtypes, active mutational processes, and chromosomal regions recurrently targeted by CNAs. Additionally, I will aggregate over 250 melanoma whole- genome samples from previously published studies, and perform harmonized and uniform molecular analysis. Specifically, I will identify positively selected noncoding elements, regions recurrently targeted by SVs, and driver fusions. Additionally, to define the functional relevance of noncoding events, I will develop a Bayesian statistical framework that superimposes mutations and SVs onto regulatory sequences and TAD boundaries from Hi-C data. The proposed work will yield a more comprehensive insight into the molecular landscape of melanoma, more refined subtypes, and insight into alterations and mechanisms driving Triple WT melanomas. As such, these findings may prompt clinical implications and provoke clinical trials aimed at novel biological targets and therapeutic vulnerabilities. !

Public Health Relevance

Previous studies aimed at the genomic characterization of melanoma led to the classification of four genomic subtypes based on mutations in the three most frequently mutated, mutually exclusive, genes (BRAF, NRAS, NF1, Triple Wild-Type). These subtypes are associated with diverse clinical characteristics, outcomes, immune profiles, treatment responses and treatment options. Aggregation of the largest melanoma cohort to date would enable a more complete genomic representation of melanoma subtypes, and will have the potential to identify novel therapeutic targets and treatment options. !

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
5F31CA239347-02
Application #
9889799
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Radaev, Sergey
Project Start
2019-05-01
Project End
2022-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115