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  • 1
    In: Leukemia & Lymphoma, Informa UK Limited, Vol. 60, No. 13 ( 2019-11-10), p. 3214-3224
    Type of Medium: Online Resource
    ISSN: 1042-8194 , 1029-2403
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2019
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  • 2
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 13, No. 5 ( 2023-05-04), p. 1144-1163
    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. Significance: 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
    Type of Medium: Online Resource
    ISSN: 2159-8274 , 2159-8290
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 5557-5557
    Abstract: Background: Cancers often overexpress multiple clinically relevant oncogenes. However, it is not known if multiple oncogenes within a cancer combineuniquely in specific cellular sub-populations to influence clinical outcome.We studied this phenomenon using the prognostically relevantoncogenes MYC, BCL2 and BCL6 in Diffuse Large B-Cell Lymphoma(DLBCL). Methods: Quantitative multispectral imaging simultaneously measured oncogene co-expression at single-cell resolution in reactive lymphoid tissue (n=12)and four independent cohorts (n=409) of DLBCL. Mathematically derived co-expression phenotypes were evaluated in DLBCLs with immunohistochemistry (n=316) and nine DLBCL cohorts with gene expression data (n=3974). Bulk and single-cell RNA sequencing was performed on patient-derived B-cells with induced co-expression of MYC,BCL2 and BCL6. Results: Unlike in non-malignant lymphoid tissue where the co-expression of MYC, BCL2 and BCL6 in a B-cell is limited, DLBCLs show multiple permutations of oncogenic co-expression in malignant B-cells. The percentage of cells with a unique combination MYC+BCL2+BCL6-(M+2+6-) consistently predicts survival in contrast to that of other combinations (including M+2+6+). An estimated percentage of M+2+6-cells can be derived from any quantitative measurement of the component individual oncogenes, and correlates with survival in immunohistochemistry and gene expression datasets. Comparative transcriptomic analysis of DLBCLs and transformed patient-derived B-cells identifies cyclin D2 (CCND2) as a potential BCL6-repressedregulator of proliferation in the M+2+6- population. Conclusions: Unique patterns of oncogene co-expression at single-cell resolution affect clinical outcomes in DLBCL. Similar analyses evaluating oncogenic combinations at the cellular level may impact diagnostics and target discovery in other cancers. Citation Format: Michal M. Hoppe, Patrick Jaynes, Shuangyi Fan, Yanfen Peng, Shruti Sridhar, Phuong Mai Hoang, Xin Liu, Sanjay de Mel, Limei Poon, Esther 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, Pedro Farinha, Anja Mottok, David W. Scott, Carl Harris, Alessia Bottos, Gayatri Kumar, Kasthuri Kannan, Laura J. Gay, Hendrik F. Runge, Ilias Moutsopoulos, Irina Mohorianu, Daniel J. Hodson, Yen-Chee Lin, Wee-Joo Chng, Siok-Bian Ng, Claudio Tripodo, Anand D. Jeyasekharan. Patterns of oncogene co-expression at single cell resolution influence survival in diffuse large B-cell lymphoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5557.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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