Photo of Chris Sander,  PhD

Chris Sander, PhD

Dana-Farber Cancer Institute

Dana-Farber Cancer Institute
Phone: (617) 582-9717


chris@sanderlab.org

Chris Sander, PhD

Dana-Farber Cancer Institute

EDUCATIONAL TITLES

  • Professor, Cell Biology, Harvard Medical School
  • Director, cBio Center, Dana-Farber Cancer Institute

DF/HCC PROGRAM AFFILIATION

Research Abstract

The overall goal of the work in the Sander lab is to solve biological problems using quantitative methods from bioinformatics, statistical physics, data sciences, statistics, computer science, and mathematics. We apply these computational methods to build predictive network models of molecular and cell-cell interactions, to support cancer precision medicine, and to make discoveries in structural and evolutionary biology.

Sander is an internationally recognized expert in computational and systems biology, cancer biology, and structural biology. He has extensive experience in cancer genomics, is a leader in The Cancer Genome Atlas (TCGA) project, and his group created the cBioPortal for Cancer Genomics. Sander’s laboratory has developed quantitative computational network models of cancer cells, which are predictive of drug response. His group has developed algorithms for pathway analysis and the design of combination therapies, with translational collaborations in melanoma, sarcoma, glioblastoma, kidney cancer, and prostate cancer.

His current research includes: (1) deriving quantitatively predictive network models from high-throughput molecular profiling; (2) discovering molecular processes responsible for oncogenesis and response to therapy across different cancer types; (3) rendering human biological knowledge computable and accessible, as an aid to biomedical discovery (cBioPortal, Pathway Commons); and (4) using evolutionary constraints derived from rich sequence information to predict previously unknown 3D structures of proteins and RNAs and to identify functional sites on both known and unknown structures.

Publications

Powered by Harvard Catalyst
  • Sinha R, Winer AG, Chevinsky M, Jakubowski C, Chen YB, Dong Y, Tickoo SK, Reuter VE, Russo P, Coleman JA, Sander C, Hsieh JJ, Hakimi AA. Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection. Nat Commun 2017; 8:15165. PubMed
  • Hopf TA, Ingraham JB, Poelwijk FJ, Schärfe CP, Springer M, Sander C, Marks DS. Mutation effects predicted from sequence co-variation. Nat Biotechnol 2017; 35:128-135. PubMed
  • Gao J, Chang MT, Johnsen HC, Gao SP, Sylvester BE, Sumer SO, Zhang H, Solit DB, Taylor BS, Schultz N, Sander C. 3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets. Genome Med 2017; 9:4. PubMed
  • Reznik E, Wang Q, La K, Schultz N, Sander C. Mitochondrial respiratory gene expression is suppressed in many cancers. Elife 2017. PubMed
  • Şenbabaoğlu Y, Gejman RS, Winer AG, Liu M, Van Allen EM, de Velasco G, Miao D, Ostrovnaya I, Drill E, Luna A, Weinhold N, Lee W, Manley BJ, Khalil DN, Kaffenberger SD, Chen Y, Danilova L, Voss MH, Coleman JA, Russo P, Reuter VE, Chan TA, Cheng EH, Scheinberg DA, Li MO, Choueiri TK, Hsieh JJ, Sander C, Hakimi AA. Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures. Genome Biol 2016; 17:231. PubMed
  • Weinreb C, Riesselman AJ, Ingraham JB, Gross T, Sander C, Marks DS. 3D RNA and Functional Interactions from Evolutionary Couplings. Cell 2016; 165:963-75. PubMed
  • Luna A, Rajapakse VN, Sousa FG, Gao J, Schultz N, Varma S, Reinhold W, Sander C, Pommier Y. rcellminer: exploring molecular profiles and drug response of the NCI-60 cell lines in R. Bioinformatics 2016; 32:1272-4. PubMed
  • Luna A, Babur Ö, Aksoy BA, Demir E, Sander C. PaxtoolsR: pathway analysis in R using Pathway Commons. Bioinformatics 2016; 32:1262-4. PubMed
  • Reznik E, Miller ML, Şenbabaoğlu Y, Riaz N, Sarungbam J, Tickoo SK, Al-Ahmadie HA, Lee W, Seshan VE, Hakimi AA, Sander C. Mitochondrial DNA copy number variation across human cancers. Elife 2016. PubMed
  • Şenbabaoğlu Y, Sümer SO, Sánchez-Vega F, Bemis D, Ciriello G, Schultz N, Sander C. A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers. PLoS Comput. Biol. 2016; 12:e1004765. PubMed
  • Gauthier NP, Reznik E, Gao J, Sumer SO, Schultz N, Sander C, Miller ML. MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer. Nucleic Acids Res 2016; 44:D986-91. PubMed
  • Miller ML, Reznik E, Gauthier NP, Aksoy BA, Korkut A, Gao J, Ciriello G, Schultz N, Sander C. Pan-Cancer Analysis of Mutation Hotspots in Protein Domains. Cell Syst 2016; 1:197-209. PubMed
  • Korkut A, Wang W, Demir E, Aksoy BA, Jing X, Molinelli EJ, Babur Ö, Bemis DL, Onur Sumer S, Solit DB, Pratilas CA, Sander C. Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells. Elife 2015. PubMed
  • Babur Ö, Gönen M, Aksoy BA, Schultz N, Ciriello G, Sander C, Demir E. Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations. Genome Biol 2015; 16:45. PubMed
  • Kaushik P, Molinelli EJ, Miller ML, Wang W, Korkut A, Liu W, Ju Z, Lu Y, Mills G, Sander C. Spatial normalization of reverse phase protein array data. PLoS ONE 2014; 9:e97213. PubMed
Hide