{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T08:00:53Z","timestamp":1761897653098},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T00:00:00Z","timestamp":1646265600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T00:00:00Z","timestamp":1646265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Cancer"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined using a number of well-established molecular subsets. Application of non-negative matrix factorization (NMF) to whole exome sequence data has previously been used to identify six distinct molecular clusters in DLBCL with potential clinical relevance. In this study, we applied NMF-clustering to targeted sequencing data utilizing the FoundationOne Heme\u00ae panel from the Phase III GOYA (NCT01287741) and Phase Ib\/II CAVALLI studies (NCT02055820) in <jats:italic>de novo<\/jats:italic> DLBCL. Biopsy samples, survival outcomes, RNA-Seq and targeted exome-sequencing data were available for 423 patients in GOYA (obinutuzumab [G]-cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP] vs rituximab [R]-CHOP) and 86 patients in CAVALLI (venetoclax+[G\/R]-CHOP).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>When the NMF algorithm was applied to samples from the GOYA study\u00a0analyzed using a comprehensive genomic profiling platform, four of the six groups previously reported were observed: <jats:italic>MYD88\/CD79B<\/jats:italic>, <jats:italic>BCL2\/EZH2<\/jats:italic>, <jats:italic>NOTCH2\/TNFAIP3<\/jats:italic>, and no mutations. Mutation profiles, cell-of-origin subset distributions and clinical associations of <jats:italic>MYD88\/CD79B<\/jats:italic> and <jats:italic>BCL2\/EZH2<\/jats:italic> groups were similar to those described in previous NMF studies. In contrast, application of NMF to the CAVALLI study yielded only three; <jats:italic>MYD88\/CD79B<\/jats:italic>-, <jats:italic>BCL2\/EZH2<\/jats:italic>-like clusters, and a no mutations group, and there was a trend towards improved outcomes for <jats:italic>BCL2\/EZH2<\/jats:italic> over <jats:italic>MYD88\/CD79B<\/jats:italic>.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>This analysis supports the utility of NMF used in conjunction with targeted sequencing platforms for identifying patients with different prognostic subsets. The observed trend for improved overall survival in the <jats:italic>BCL2\/EZH2<\/jats:italic> group is consistent with the mechanism of action of venetoclax, suggesting that targeting sequencing and NMF has potential for identifying patients who are more likely to gain benefit from venetoclax therapy.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12885-022-09237-5","type":"journal-article","created":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T03:02:53Z","timestamp":1646276573000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Prognostic mutational subtyping in de novo diffuse large B-cell lymphoma"],"prefix":"10.1186","volume":"22","author":[{"given":"Eugene","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanwen","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandra","family":"Bazeos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"Knapp","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher R.","family":"Bolen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kathryn","family":"Humphrey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tina G.","family":"Nielsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elicia","family":"Penuel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph N.","family":"Paulson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,3]]},"reference":[{"key":"9237_CR1","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1073\/pnas.1205299110","volume":"110","author":"J Zhang","year":"2013","unstructured":"Zhang J, Grubor V, Love CL, Banerjee A, Richards KL, Mieczkowski PA, et al. 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The GOYA and CAVALLI protocols were approved by the ethics committees of participating centers; further details of these are provided in Supplementary Table InternalRef removedA and InternalRef removedB. Both protocols are registered at ClinicalTrials.gov. All patients provided written informed consent.The real-world DLBCL cohort was drawn from the nationwide (US only) Flatiron Health-Foundation Medicine clinic-genomic database (FH-FMI CGDB). The de-identified data originated from approximately 280 cancer clinics (~800 sites of care) in the US; data for this analysis were derived from a subset of patients who underwent FMI F1H [CitationRef removed] comprehensive genomic profiling based on their electronic health record [CitationRef removed, CitationRef removed]. Retrospective longitudinal clinical data were derived from electronic health record data, comprising patient-level structured and unstructured data, curated via technology-enabled abstraction, and linked to genomic data derived from FMI comprehensive genomic profiling tests in the FH-FMI CGDB by de-identified, deterministic matching [CitationRef removed, CitationRef removed].","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"E.K: employment (Genentech Inc.), ownership interests (F. Hoffmann La-Roche Ltd). T.X: employment (F. Hoffmann La-Roche Ltd). C.R.B: employment (Genentech Inc.), ownership interests (F. Hoffmann La-Roche Ltd). A.B: employment and ownership interests (Roche Products Ltd). Y.J: employment (Genentech Inc.), ownership interests (Genentech, Inc., F. Hoffmann La-Roche Ltd). A.K. employment (F. Hoffmann-La Roche Ltd). K.H: employment (Roche Products Ltd). T.G.N: employment and ownership interests (F. Hoffmann-La Roche Ltd). E.P: employment (Genentech, Inc.), ownership interests (F. Hoffmann La-Roche Ltd). J.N.P: employment (Genentech, Inc.), ownership interests (F. Hoffmann La-Roche Ltd).","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"231"}}