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dc.contributor.authorLi, Boen_US
dc.contributor.authorSeverson, Ericen_US
dc.contributor.authorPignon, Jean-Christopheen_US
dc.contributor.authorZhao, Haoquanen_US
dc.contributor.authorLi, Taiwenen_US
dc.contributor.authorNovak, Jesseen_US
dc.contributor.authorJiang, Pengen_US
dc.contributor.authorShen, Huien_US
dc.contributor.authorAster, Jon C.en_US
dc.contributor.authorRodig, Scotten_US
dc.contributor.authorSignoretti, Sabinaen_US
dc.contributor.authorLiu, Jun S.en_US
dc.contributor.authorLiu, X. Shirleyen_US
dc.date.accessioned2016-10-11T20:27:20Z
dc.date.issued2016en_US
dc.identifier.citationLi, B., E. Severson, J. Pignon, H. Zhao, T. Li, J. Novak, P. Jiang, et al. 2016. “Comprehensive analyses of tumor immunity: implications for cancer immunotherapy.” Genome Biology 17 (1): 174. doi:10.1186/s13059-016-1028-7. http://dx.doi.org/10.1186/s13059-016-1028-7.en
dc.identifier.issn1474-7596en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:29002609
dc.description.abstractBackground: Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers. Results: We analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER. Conclusions: We develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1028-7) contains supplementary material, which is available to authorized users.en
dc.language.isoen_USen
dc.publisherBioMed Centralen
dc.relation.isversionofdoi:10.1186/s13059-016-1028-7en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4993001/pdf/en
dash.licenseLAAen_US
dc.subjectCancer immunityen
dc.subjectTumor immune infiltrationen
dc.subjectCancer immunotherapiesen
dc.subjectCancer vaccineen
dc.subjectCheckpoint blockadeen
dc.titleComprehensive analyses of tumor immunity: implications for cancer immunotherapyen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalGenome Biologyen
dash.depositing.authorLi, Boen_US
dc.date.available2016-10-11T20:27:20Z
dc.identifier.doi10.1186/s13059-016-1028-7*
dash.authorsorderedfalse
dash.contributor.affiliatedSeverson, Eric
dash.contributor.affiliatedLiu, Jun
dash.contributor.affiliatedLi, Bo
dash.contributor.affiliatedAster, Jon
dash.contributor.affiliatedRodig, Scott
dash.contributor.affiliatedPignon, Jean-Christophe
dash.contributor.affiliatedSignoretti, Sabina


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