Multiple Myeloma is a malignant proliferation of monoclonal plasma cells that are derived from post-germinal-center B cells. Myeloma cells produce monoclonal paraproteins and cause lytic bone lesions, anemia and renal failure. Myeloma accounts for almost 14% of all hematologic cancers. Despite intensive study, the etiology of Multiple Myeloma is unknown. Reports of substantial familial clustering of myeloma cases have been reported, including by our own team. These data are consistent with the existence of specific risk genes that predispose to Familial Myeloma and associated malignancies. Analogous to the BRCA1 breast cancer constitutional risk gene, which affects treatment decisions (surgical management and PARP inhibitors), surveillance (annual breast MRI) and prevention (oophorectomy), identification of Familial Myeloma risk genes is likely to provide important new mechanistic insights that can also significantly impact important clinical decision making for both affected individuals and at-risk family members. Unfortunately, there are currently no known constitutional familial or sporadic myeloma risk genes. Here, we will use an innovative strategy incorporating previously untapped computational resources to discover and rigorously validate novel constitutional cancer risk genes in one of the largest Familial Myeloma clinical and genetic resources in the world. We will use an innovative tiered whole exome and full genome sequencing strategy of well- characterized Familial Myeloma probands and available biospecimens to help discover, prioritize and validate causative constitutional mutation candidates. Our overall goal is to discover and validate the first constitutional Familial Myeloma risk genes in clinically well- characterized kindreds. This is anticipated to increase the number of patients and their at-risk family members who can benefit from increased cancer surveillance, early detection and cancer prevention.
Despite intensive study, the etiology of Multiple Myeloma is unknown. Here, we will use an innovative strategy incorporating previously untapped computational resources to discover and rigorously validate novel constitutional cancer risk genes in one of the largest Familial Myeloma clinical and genetic resources in the world. Our overall goal is to discover and validate the first constitutional Familial Myeloma risk genes in clinically well-characterized kindreds.
|Guo, Yu; Alexander, Katherine; Clark, Andrew G et al. (2016) Integrated network analysis reveals distinct regulatory roles of transcription factors and microRNAs. RNA 22:1663-1672|
|Bastos de Oliveira, Francisco Meirelles; Kim, Dongsung; Cussiol, JosÃ© Renato et al. (2015) Phosphoproteomics reveals distinct modes of Mec1/ATR signaling during DNA replication. Mol Cell 57:1124-32|
|Das, Jishnu; Gayvert, Kaitlyn M; Bunea, Florentina et al. (2015) ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers. BMC Genomics 16:263|
|Pu, Mintie; Ni, Zhuoyu; Wang, Minghui et al. (2015) Trimethylation of Lys36 on H3 restricts gene expression change during aging and impacts life span. Genes Dev 29:718-31|
|Das, Jishnu; Lee, Hao Ran; Sagar, Adithya et al. (2014) Elucidating common structural features of human pathogenic variations using large-scale atomic-resolution protein networks. Hum Mutat 35:585-93|
|Das, Jishnu; Fragoza, Robert; Lee, Hao Ran et al. (2014) Exploring mechanisms of human disease through structurally resolved protein interactome networks. Mol Biosyst 10:9-17|
|Wei, Xiaomu; Das, Jishnu; Fragoza, Robert et al. (2014) A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations. PLoS Genet 10:e1004819|
|Das, Jishnu; Gayvert, Kaitlyn M; Yu, Haiyuan (2014) Predicting cancer prognosis using functional genomics data sets. Cancer Inform 13:85-8|
|Khurana, Ekta; Fu, Yao; Colonna, Vincenza et al. (2013) Integrative annotation of variants from 1092 humans: application to cancer genomics. Science 342:1235587|
|Das, Jishnu; Vo, Tommy V; Wei, Xiaomu et al. (2013) Cross-species protein interactome mapping reveals species-specific wiring of stress response pathways. Sci Signal 6:ra38|
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