dataset
posted on 2023-05-04, 08:20 authored by Michal Marek Hoppe, Patrick Jaynes, Fan Shuangyi, Yanfen Peng, Shruti Sridhar, Phuong Mai Hoang, Clementine Xin Liu, Sanjay De Mel, Limei Poon, Esther Hian Li Chan, Joanne Lee, Choon Kiat Ong, Tiffany Tang, Soon Thye Lim, Chandramouli Nagarajan, Nicholas F. Grigoropoulos, Soo-Yong Tan, Susan Swee-Shan Hue, Sheng-Tsung Chang, Shih-Sung Chuang, Shaoying Li, Joseph D. Khoury, Hyungwon Choi, Carl Harris, Alessia Bottos, Laura J. Gay, Hendrik F.P. Runge, Ilias Moutsopoulos, Irina Mohorianu, Daniel J. Hodson, Pedro Farinha, Anja Mottok, David W. Scott, Jason J. Pitt, Jinmiao Chen, Gayatri Kumar, Kasthuri Kannan, Wee Joo Chng, Yen Lin Chee, Siok-Bian Ng, Claudio Tripodo, Anand D. Jeyasekharan Multivariate analysis of continuous M+2+6− percentage extent at 5% increments as a predictor of OS in the NUH, SGH, and MDA cohorts of DLBCL (Cox proportional hazards model)
Funding
National Medical Research Council (NMRC)
National Research Foundation Singapore (NRF)
Singapore Ministry of Education
NIHR Cambridge Biomedical Research Centre (NIHR Cambridge BRC)
Cancer Research UK (CRUK)
Wellcome Trust (WT)
CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester (CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester)
Italian Foundation for Cancer Research (AIRC)
History
ARTICLE ABSTRACT
Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6− (M+2+6−) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6− percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6− unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance.
Using single-cell–resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer.This article is highlighted in the In This Issue feature, p. 1027
