Subhajyoti De
Associate Professor
Research Interests
My research group develops and applies genomics, systems biology, and mathematical modeling approaches to understand the biology of cancer and use that knowledge for better diagnosis, stratification, and treatment of the disease. We work in four overlapping areas.
Genomic instability in cancer
We have recently shown that nuclear localization, DNA replication timing and genomic context play critical roles in shaping the landscape of amplifications, deletions, point mutations, and loss of heterozygosity in cancer genomes. Our findings provide insights into different mutagenic processes, and has implications for identifying driver and passenger mutations in the cancer genomes.
Pedersen et al. Nucleic Acids Res. 2013
Liu et al. Nature Comm. 2013
Podlaha et al. Trends Genet. 2012
De et al. Nature Biotech.. 2011
De et al. Nature Str. Mol. Biol. 2011
Regulatory alterations in cancer
Genomic and epigenetic abnormalities leading to deregulated oncogenic pathways are found in many types of cancer. We found a novel signature of accelerated somatic evolution in many types of cancer, which is marked by significant excess of somatic mutations in a genomic region in multiple cancer genomes. The signature is frequently associated with non-coding regulatory changes leading to deregulation of oncogenic pathways and adverse clinical outcome. In another project, we found that epigenetic heterogeneity in B cell lymphoma is increases markedly with disease aggressiveness, and is associated with unfavorable clinical outcome. Our findings provide mechanistic insights into the biology of regulatory alterations in cancer.
Smith KS et al. Nucleic Acids Res. 2015
Shaknovich, De, Michor. Biochim Biophys Acta. 2014.
De, Shaknovich, Riester et al. PLoS Genetics. 2013
Shaknovich et al. Blood. 2011
Evolutionary dynamics of cancer
We use a combination of computational, genomics, and mathematical tools to study evolutionary dynamics of cancer, including order of mutation events and emergence of resistance. We found that not only the driver mutations are important, but the order in which they arise is also important. Although there is no obligatory order of events, we found that loss of PTEN is the most common first event and is associated with basal-like subtype, whereas in the majority of luminal tumors, mutation of TP53 occurs first and mutant PIK3CA is rarely detected. Furthermore, resistant mutations are often present at low frequency during treatment. Our results have important implications for the design of chemopreventive and therapeutic interventions in this high-risk patient population.
Martins et al. Cancer Discovery. 2012.(cover story)
Smith et al. Bioinformatics. 2016
Hintzsche J et al. JAMIA (2016)
Somatic mutations in benign human tissues
From the fertilization of an egg until the death of an individual, somatic cells can accumulate genetic changes, such that cells from different tissues or even within the same tissue differ genetically. The presence of multiple cell clones with distinct genotypes in the same individual is referred to as ‘somatic mosaicism’. Many endogenous factors such as mobile elements, DNA polymerase slippage, DNA double-strand break, inefficient DNA repair, unbalanced chromosomal segregation and some exogenous factors such as nicotine and UV exposure can contribute to the generation of somatic mutations, thereby leading to somatic mosaicism. Such changes can potentially affect the epigenetic patterns and levels of gene expression, and ultimately the phenotypes of cells. Although recent studies suggest that somatic mosaicism is widespread during normal development and aging, its implications for heightened disease risks are incompletely understood. We found that somatic mutations in benign somatic tissues carry signatures of relaxed purifying selection.
Yadav et al. Nucleic Acids Res. 2016
Aghili et al. Cell Rep. 2014
De. Trends Genet 2011 (cover story)
Clinical or Educational Responsibilities
My group is part of the Rutgers CINJ Precision Medicine Initiative and Center for Systems and Computational Biology at Rutgers Cancer Institute of New Jersey. I participate in the weekly tumor board for the Rutgers CINJ Precision Medicine Initiative.
Contact Subhajyoti
📍 CINJ-Sys Biol-Gen Instabil-SD
195 Little Albany Street
New Brunswick, NJ
08901, 08901