| Literature DB >> 29884728 |
Rong Lu1,2, Payal Kapur3,4, Bijay S Jaiswal5, Tao Wang6,3,7, Raquibul Hannan3,8, Ze Zhang1, Ivan Pedrosa3,9, Jason J Luke10, He Zhang2, Leonard D Goldstein5, Qurratulain Yousuf3,11, Yi-Feng Gu3,11, Tiffani McKenzie3, Allison Joyce3,11, Min S Kim3,2, Xinlei Wang12, Danni Luo2, Oreoluwa Onabolu3,11, Christina Stevens3,11, Zhiqun Xie1, Mingyi Chen4, Alexander Filatenkov4, Jose Torrealba4, Xin Luo2, Wenbin Guo1, Jingxuan He1, Eric Stawiski5,13, Zora Modrusan5, Steffen Durinck5,13, Somasekar Seshagiri14, James Brugarolas15,11.
Abstract
By leveraging tumorgraft (patient-derived xenograft) RNA-sequencing data, we developed an empirical approach, DisHet, to dissect the tumor microenvironment (eTME). We found that 65% of previously defined immune signature genes are not abundantly expressed in renal cell carcinoma (RCC) and identified 610 novel immune/stromal transcripts. Using eTME, genomics, pathology, and medical record data involving >1,000 patients, we established an inflamed pan-RCC subtype (IS) enriched for regulatory T cells, natural killer cells, TH1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. IS is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. The IS subtype correlated with systemic manifestations of inflammation such as thrombocytosis and anemia, which are enigmatic predictors of poor prognosis. Furthermore, IS was a strong predictor of poor survival. Our analyses suggest that tumor cells drive the stromal immune response. These data provide a missing link between tumor cells, the TME, and systemic factors.Significance: We undertook a novel empirical approach to dissect the renal cell carcinoma TME by leveraging tumorgrafts. The dissection and downstream analyses uncovered missing links between tumor cells, the TME, systemic manifestations of inflammation, and poor prognosis. Cancer Discov; 8(9); 1142-55. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1047. ©2018 American Association for Cancer Research.Entities:
Mesh:
Year: 2018 PMID: 29884728 PMCID: PMC6125163 DOI: 10.1158/2159-8290.CD-17-1246
Source DB: PubMed Journal: Cancer Discov ISSN: 2159-8274 Impact factor: 39.397