Data from Patterns of Oncogene Coexpression at Single-Cell Resolution Influence Survival in Lymphoma

Abstract

<div>Abstract<p>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 <i>MYC</i>, <i>BCL2</i>, and <i>BCL6</i> in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination <i>MYC</i>+<i>BCL2</i>+<i>BCL6</i>− (M+2+6−) consistently predicts survival across four independent cohorts (<i>n</i> = 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 (<i>n</i> = 316) and gene expression (<i>n</i> = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and <i>MYC</i>/<i>BCL2</i>/<i>BCL6</i>-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.</p>Significance:<p>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.</p></div>