Author
Sridhar Ramaswamy
Other affiliations: Broad Institute, Massachusetts Institute of Technology, Howard Hughes Medical Institute
Bio: Sridhar Ramaswamy is an academic researcher from Harvard University. The author has contributed to research in topics: Cancer & Metastasis. The author has an hindex of 68, co-authored 140 publications receiving 36102 citations. Previous affiliations of Sridhar Ramaswamy include Broad Institute & Massachusetts Institute of Technology.
Topics: Cancer, Metastasis, Cancer cell, Breast cancer, Circulating tumor cell
Papers published on a yearly basis
Papers
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TL;DR: A mechanistic link between Twist, EMT, and tumor metastasis is established, suggesting that Twist contributes to metastasis by promoting an epithelial-mesenchymal transition (EMT).
3,670 citations
TL;DR: Observations indicate that TBK1 and NF-κB signalling are essential in KRAS mutant tumours, and establish a general approach for the rational identification of co-dependent pathways in cancer.
Abstract: The proto-oncogene KRAS is mutated in a wide array of human cancers, most of which are aggressive and respond poorly to standard therapies. Although the identification of specific oncogenes has led to the development of clinically effective, molecularly targeted therapies in some cases, KRAS has remained refractory to this approach. A complementary strategy for targeting KRAS is to identify gene products that, when inhibited, result in cell death only in the presence of an oncogenic allele. Here we have used systematic RNA interference to detect synthetic lethal partners of oncogenic KRAS and found that the non-canonical IkappaB kinase TBK1 was selectively essential in cells that contain mutant KRAS. Suppression of TBK1 induced apoptosis specifically in human cancer cell lines that depend on oncogenic KRAS expression. In these cells, TBK1 activated NF-kappaB anti-apoptotic signals involving c-Rel and BCL-XL (also known as BCL2L1) that were essential for survival, providing mechanistic insights into this synthetic lethal interaction. These observations indicate that TBK1 and NF-kappaB signalling are essential in KRAS mutant tumours, and establish a general approach for the rational identification of co-dependent pathways in cancer.
2,438 citations
TL;DR: It is found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome, suggesting that the metastatic potential of human tumors is encoded in the bulk of aPrimary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.
Abstract: Metastasis is the principal event leading to death in individuals with cancer, yet its molecular basis is poorly understood. To explore the molecular differences between human primary tumors and metastases, we compared the gene-expression profiles of adenocarcinoma metastases of multiple tumor types to unmatched primary adenocarcinomas. We found a gene-expression signature that distinguished primary from metastatic adenocarcinomas. More notably, we found that a subset of primary tumors resembled metastatic tumors with respect to this gene-expression signature. We confirmed this finding by applying the expression signature to data on 279 primary solid tumors of diverse types. We found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome (P < 0.03). These results suggest that the metastatic potential of human tumors is encoded in the bulk of a primary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.
2,434 citations
TL;DR: It was found that mutated cancer genes were associated with cellular response to most currently available cancer drugs, and systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.
Abstract: Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.
2,187 citations
TL;DR: The Genomics of Drug Sensitivity in Cancer (GDSC) provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.
Abstract: Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.
2,158 citations
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TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
34,830 citations
TL;DR: In comparative timings, the new algorithms are considerably faster than competing methods and can handle large problems and can also deal efficiently with sparse features.
Abstract: We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include l(1) (the lasso), l(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
13,656 citations
TL;DR: A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
Abstract: Recent work has revealed the existence of a class of small non-coding RNA species, known as microRNAs (miRNAs), which have critical functions across various biological processes. Here we use a new, bead-based flow cytometric miRNA expression profiling method to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers. The miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. We observe a general downregulation of miRNAs in tumours compared with normal tissues. Furthermore, we were able to successfully classify poorly differentiated tumours using miRNA expression profiles, whereas messenger RNA profiles were highly inaccurate when applied to the same samples. These findings highlight the potential of miRNA profiling in cancer diagnosis.
9,470 citations
TL;DR: Processes similar to the EMTs associated with embryo implantation, embryogenesis, and organ development are appropriated and subverted by chronically inflamed tissues and neoplasias and the identification of the signaling pathways that lead to activation of EMT programs during these disease processes is providing new insights into the plasticity of cellular phenotypes.
Abstract: The origins of the mesenchymal cells participating in tissue repair and pathological processes, notably tissue fibrosis, tumor invasiveness, and metastasis, are poorly understood. However, emerging evidence suggests that epithelial-mesenchymal transitions (EMTs) represent one important source of these cells. As we discuss here, processes similar to the EMTs associated with embryo implantation, embryogenesis, and organ development are appropriated and subverted by chronically inflamed tissues and neoplasias. The identification of the signaling pathways that lead to activation of EMT programs during these disease processes is providing new insights into the plasticity of cellular phenotypes and possible therapeutic interventions.
8,587 citations
TL;DR: It is reported that the induction of an EMT in immortalized human mammary epithelial cells (HMLEs) results in the acquisition of mesenchymal traits and in the expression of stem-cell markers, and it is shown that those cells have an increased ability to form mammospheres, a property associated with mammARY epithelial stem cells.
8,052 citations