Determining clinical course of diffuse large B-cell lymphoma using targeted transcriptome and machine learning algorithms.

Autor: Albitar M; Genomic Testing Cooperative, LCA, Irvine, CA, 92618, USA. malbitar@genomictestingcooperative.com., Zhang H; Genomic Testing Cooperative, LCA, Irvine, CA, 92618, USA., Goy A; John Theurer Cancer Center at Hackensack University Medical Center, Hackensack, NJ, 07601, USA., Xu-Monette ZY; Duke University Medical Center, Durham, NC, 27710, USA., Bhagat G; Columbia University Medical Center, New York, NY, 10027, USA., Visco C; University of Verona, 37129, Verona, Italy., Tzankov A; Institute of Pathology, University Hospital Basel, 4054, Basel, Switzerland., Fang X; Duke University Medical Center, Durham, NC, 27710, USA., Zhu F; Duke University Medical Center, Durham, NC, 27710, USA., Dybkaer K; Aalborg University Hospital, Aalborg, 5000-5270, Denmark., Chiu A; Mayo Clinic, Rochester, MN, 55905, USA., Tam W; Weill Medical College of Cornell University, New York, NY, 10065, USA., Zu Y; The Methodist Hospital, Houston, TX, 77030, USA., Hsi ED; Wake Forest University Medical Center, Winston-Salem, NC, 77055, USA., Hagemeister FB; The University of Texas MD Anderson Cancer Center, Houston, TX, 22030, USA., Huh J; Asan Medical Center, Ulsan University College of Medicine, Seoul, 05505, Korea., Ponzoni M; San Raffaele H. Scientific Institute, 20132, Milan, Italy., Ferreri AJM; San Raffaele H. Scientific Institute, 20132, Milan, Italy., Møller MB; Odense University Hospital, Odense, 5000-5270, Denmark., Parsons BM; Gundersen Lutheran Health System, La Crosse, WI, 54601, USA., van Krieken JH; Radboud University Nijmegen Medical Centre, 6500, Nijmegen, Netherlands., Piris MA; Hospital Universitario Marqués de Valdecilla, 39008, Santander, Spain., Winter JN; Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA., Li Y; Baylor College of Medicine, Houston, TX, 77030, USA., Xu B; The First Affiliated Hospital of Xiamen University, 361004, Xiamen, Fujian, China. xubingzhangjian@126.com., Young KH; Duke University Medical Center, Durham, NC, 27710, USA. ken.young@duke.edu.; Duke Cancer Institute, Durham, NC, 27710, USA. ken.young@duke.edu.
Jazyk: angličtina
Zdroj: Blood cancer journal [Blood Cancer J] 2022 Feb 01; Vol. 12 (2), pp. 25. Date of Electronic Publication: 2022 Feb 01.
DOI: 10.1038/s41408-022-00617-5
Abstrakt: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology; however, these biological subgroups overlap clinically. Using machine learning, we developed an approach to stratify patients with DLBCL into four subgroups based on survival characteristics. This approach uses data from the targeted transcriptome to predict these survival subgroups. Using the expression levels of 180 genes, our model reliably predicted the four survival subgroups and was validated using independent groups of patients. Multivariate analysis showed that this patient stratification strategy encompasses various biological characteristics of DLBCL, and only TP53 mutations remained an independent prognostic biomarker. This novel approach for stratifying patients with DLBCL, based on the clinical outcome of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone therapy, can be used to identify patients who may not respond well to these types of therapy, but would otherwise benefit from alternative therapy and clinical trials.
(© 2022. The Author(s).)
Databáze: MEDLINE
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