Molecular heterogeneity in urothelial carcinoma and determinants of clinical benefit to PD-L1 blockade

被引：2

作者：

Hamidi, Habib ^{[1
]}

Senbabaoglu, Yasin ^{[1
]}

Beig, Niha ^{[1
]}

Roels, Juliette ^{[1
]}

Manuel, Cyrus ^{[1
]}

Guan, Xiangnan ^{[1
]}

Koeppen, Hartmut ^{[1
]}

Assaf, Zoe June ^{[1
]}

Nabet, Barzin Y. ^{[1
]}

Waddell, Adrian ^{[1
]}

Yuen, Kobe ^{[1
]}

Maund, Sophia ^{[1
]}

Sokol, Ethan ^{[2
]}

Giltnane, Jennifer M. ^{[1
]}

Schedlbauer, Amber ^{[1
]}

Fuentes, Eloisa ^{[1
]}

Cowan, James D. ^{[1
]}

Kadel, Edward E. ^{[1
]}

Degaonkar, Viraj ^{[1
]}

Andreev-Drakhlin, Alexander ^{[1
]}

Williams, Patrick ^{[1
]}

Carter, Corey ^{[1
]}

Gupta, Suyasha ^{[1
]}

Steinberg, Elizabeth ^{[1
]}

Loriot, Yohann ^{[3
]}

Bellmunt, Joaquim ^{[4
]}

Grivas, Petros ^{[5
]}

Rosenberg, Jonathan ^{[6
]}

van der Heijden, Michiel S. ^{[7
]}

Galsky, Matthew D.

Powles, Thomas

Mariathasan, Sanjeev ^{[1
]}

Banchereau, Romain ^{[1
,8
]}

机构：

[1] Genentech Inc, South San Francisco, CA 94080 USA

[2] Fdn Med, Cambridge, MA USA

[3] Univ Paris Saclay, Inst Cancerol Gustave Roussy, Villejuif, France

[4] Dana Farber Canc Inst, Boston, MA USA

[5] Fred Hutchinson Canc Ctr, Seattle, WA USA

[6] Mem Sloan Kettering Canc Ctr, New York, NY USA

[7] Netherlands Canc Inst, Amsterdam, Netherlands

[8] BART Canc Inst, London, England

来源：

CANCER CELL | 2024年 / 42卷 / 12期

关键词：

SINGLE-ARM; OPEN-LABEL; MULTICENTER; PEMBROLIZUMAB; ATEZOLIZUMAB; PHASE-2; CHEMOTHERAPY; NIVOLUMAB; THERAPY; PLACEBO;

D O I：

10.1016/j.ccell.2024.10.016

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Checkpoint inhibitors targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) have revolutionized cancer therapy across many indications including urothelial carcinoma (UC). Because many patients do not benefit, a better understanding of the molecular mechanisms underlying response and resistance is needed to improve outcomes. We profiled tumors from 2,803 UC patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab by RNA sequencing (RNA-seq), a targeted DNA panel, immunohistochemistry, and digital pathology. Machine learning identifies four transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care is observed in immune and basal tumors, through different response mechanisms. A self-supervised digital pathology approach can classify molecular subtypes from H&E slides with high accuracy, which could accelerate tumor molecular profiling. This study represents a large integration of UC molecular and clinical data in randomized trials, paving the way for clinical studies tailoring treatment to specific molecular subtypes in UC and other indications.

引用

页码：2098 / 2112.e4

页数：20

共 53 条

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