elena edelman

I am currently a computational biology postdoctoral fellow in the laboratory of Dr. Sridhar Ramaswamy at the MGH Cancer Center. I am studying the genetic features of tumors that predict drug responsiveness using a large collection of human cancer cell lines. My work has involved developing analytical approaches to define signatures of drug sensitivity and resistance that integrate sequence variants, copy number, and gene expression data. I have identified novel markers of drugs sensitivity and resistance, and showed that heterogeneity in drug response can be explained in part by multi-gene interactions. I have also studied mechanisms of drug resistance to targeted therapeutics by a transposon based screening and high throughput genome wide sequencing. I have identified alternative pathways that when activated lead to drug resistance and combination therapies that can be used to prevent cancer relapse.

Thesis research topic: Modeling oncogenic pathways. Developed a statistical method to measure an individual’s pathway enrichment in an expression data set using a nonparametric correlation statistic and a modified Kolmogorov-Smirnov statistic. Models of tumor progression were built using hierarchical modeling with mixed effects. Have used ideas from pathway analysis, inverse regression, and Gaussian Markov graphical models in this research. Have also worked on finding subnetwork structures in modeling gene expression data and have refined regulatory pathways to core sets of genes relevant for a specific context. Although methods can be applied to a broad range of disease types, the focus here was on colon cancer, prostate cancer, and melanoma.

Investigated single nucleotide polymorphisms (SNPs) association with cardiovascular disease.

Performed independent research utilizing many microbial genetic techniques including PCR, RNA extraction, in-vitro expression and many others.

Estimated the effect of the local DNA-sequence context on mutation rate and determined ancestral relationships among organisms with computational methods to analyze mutational frequency.

Laboratory of Cerebral Metabolism: Researched methods to determine lag times and catheter wash-out rate constants in an arterial blood sampling system.