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Record W4411333827 · doi:10.1002/hon.70094_184

184 | GENOMIC PROFILING OF EXTRANODAL DISEASE IN PATIENTS WITH DIFFUSE LARGE B‐CELL LYMPHOMA: A COMBINED ANALYSIS OF POLARIX AND GOYA

2025· article· en· W4411333827 on OpenAlexaff
Jennifer Kimberly Lue, F. Morschhauser, Hervé Tilly, Georg Lenz, Fabrice Jardin, Alex F. Herrera, Jeffrey P. Sharman, C. R. Flowers, Jonathan W. Friedberg, Marek Trněný, Charles Herbaux, M. Yan, Saibah Chohan, Matthew Sugidono, Lili Wang, Yizhou Jiang, Connie Lee Batlevi, Wing Leung, W. Harris, Gilles Salles, L. H. Sehn

Bibliographic record

VenueHematological Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSpinal Cord Injury BCUniversity of British ColumbiaRoche (Canada)
FundersNational Cancer InstituteGilead SciencesSeagenPfizer
KeywordsLymphomaDiffuse large B-cell lymphomaMedicineProfiling (computer programming)DiseasePathologyComputer science

Abstract

fetched live from OpenAlex

Introduction: DLBCL is characterized by genomic heterogeneity and EN dissemination impacts prognosis. Genomic analyses of pts with EN disease from POLARIX were previously presented (Lue et al. 2024). We performed a retrospective study of additional genomic analysis in pts with previously untreated DLBCL and EN disease from two Phase III studies. Methods: POLARIX (NCT03274492; Tilly et al. 2022) and GOYA (NCT01287741; Vitolo et al. 2017) have been previously described. For comparison with POLARIX, pts from GOYA were limited to those with an IPI score ≥ 2. EN disease was confirmed by presence of radiographic lesions or pathological reports. Mutation analysis and gene expression profiling (RNAseq) were performed centrally. Differential expression and gene set enrichment analysis (GSEA) were compared in pts with and without EN disease. Pts with multiple EN sites were counted once per site within analysis of each separate site. Results: EN disease was confirmed in 1222/1837 pts (67%; POLARIX, n = 558/779, 72%; GOYA, n = 664/1058, 63%). Among pts with EN disease, the most common EN sites were gastrointestinal (GI, 36.1%), thorax (25.7%) and bone marrow (BM, 24.5%). In pts with ≥ 2 distinct EN sites (n = 502), co-occurrence of GI and thorax involvement was common (POLARIX, 18.9%; GOYA, 24.6%). Mutational data (n = 583; POLARIX, n = 365; GOYA, n = 218) showed similar mutation spectrums within specific EN sites between studies. High frequencies of PIM1 and MYD88 mutations (MCD) were associated with urinary, endocrine/reproductive and head/neck presentations. EZB characterizing mutations were enriched in thorax and bone. TP53 mutations were seen in various EN sites. Pts with multiple EN sites showed enrichment in mutations for MCD, EZB and A53 subtypes. For RNAseq data (n = 656; POLARIX, n = 419; GOYA, n = 237), GSEA demonstrated a common downregulation of adaptive and innate immune responses, and an increase in proliferation-associated pathways (Figure). Upregulation of metabolic pathways was present in pts with thorax, endocrine/reproductive, GI, and urinary system disease. Downregulation of pathways characteristic of myeloid, natural killer and stromal cells in the lymphoma microenvironment was notable in pts with endocrine/reproductive, GI, head/neck and BM disease, suggestive of an ‘immune cold’ microenvironment. Notch-mediated pathways were downregulated in pts with endocrine/reproductive, GI, and urinary disease. Conclusions: This analysis represents the largest collection of pts with DLBCL and EN disease paired with detailed genomic analysis. Mutation analysis revealed differential enrichment of genetic subtypes associated with specific sites of EN involvement. RNAseq analysis suggested dysregulation of immune surveillance and proliferation were common, with unique pathway aberrations associated with specific EN sites, including impact on tumor microenvironment. These data can be leveraged to help develop novel and tailored therapeutics for difficult-to-treat populations. Research funding declaration: The POLARIX study was sponsored by F. Hoffmann La-Roche Ltd. Third-party editorial assistance, under the direction of the authors, was provided by Rachel Bell, PhD, of Ashfield MedComms, an Inizio company, and was funded by F. Hoffmann La-Roche Ltd. Keywords: genomics, epigenomics, and other -omics; aggressive B-cell non-Hodgkin lymphoma; diagnostic and prognostic biomarkers Potential sources of conflict of interest: J. K. Lue Consultant or advisory role: BMS, AbbVie, Genmab, ADC Therapeutics, Merck, Genentech Other remuneration: Research funding: Kymera Therapeutics F. Morschhauser Consultant or advisory role: BMS, AbbVie, Roche, Miltenyi, Janssen, Modex Therapeutics Honoraria: Takeda, Kite/Gilead, AstraZeneca Other remuneration: Research funding: Roche, BMS, Kite/Gilead H. Tilly Consultant or advisory role: Roche Educational grants: Janssen Other remuneration: Roche, AstraZeneca, BMS, Incyte, BeiGene, Daiichi Sankyo, Lilly, Novartis, Pharmacyclics, ADC Therapeutics, Epizyme (all via institution) G. Lenz Consultant or advisory role: Roche, Novartis, BMS, Abbvie, Sobi, Flindr, AstraZeneca, Gilead, Incyte, Genmab, ADC Therapeutics, PentixaPharm, Hexal-Sandoz, Lilly, MSD, Exscientia, Beigene, Pierre Fabre Honoraria: Roche, Novartis, BMS, AbbVie, Sobi, Flindr, AstraZeneca, Gilead, Incyte, Genmab, ADC Therapeutics, PentixaPharm, Hexal-Sandoz, Lilly, MSD, Exscientia, BeiGene, Pierre Fabre Educational grants: BeiGene, AbbVie, Sobi, Roche, Gilead Other remuneration: Research funding: AstraZeneca, AbbVie, Sobi; Speaker's bureau: Sobi, Roche, AbbVie, BMS, Gilead, Incyte, Lilly, BeiGene F. Jardin Honoraria: Roche, Gilead, Novartis, BMS, Johnson & Johnson Educational grants: AbbVie, Roche A. F. Herrera Consultant or advisory role: Bristol Myers Squibb, Genentech, Merck, Seagen, AstraZeneca, ADC Therapeutics, Takeda, Genmab, Pfizer, AbbVie, Allogene Therapeutics Other remuneration: Research funding: Bristol Myers Squibb, Genentech, Merck, Seagen, AstraZeneca J. P. Sharman Consultant or advisory role: AbbVie, AstraZeneca, BeiGene, Genentech, Genmab, Lilly, Janssen Honoraria: AbbVie, AstraZeneca, BeiGene, Genentech, Genmab, Lilly, Janssen C. R. Flowers Consultant or advisory role: AbbVie, Bayer, BeiGene, Celgene, Denovo Biopharma, Foresight Diagnostics, Genentech/Roche, Genmab, Gilead, Karyopharm, N-Power Medicine, Pharmacyclics/Janssen, Seagen, Spectrum Stock ownership: Foresight Diagnostics, N-Power Medicine Other remuneration: Research funding: 4D, AbbVie, Acerta, Adaptimmune, Allogene, Amgen, Bayer, BostonGene, Celgene, Cellectis EMD, Gilead, Genentech/Roche, Guardant, Iovance, Janssen Pharmaceutical, Kite, MorphoSys, Nektar, Novartis, Pfizer, Pharmacyclics, Sanofi, Takeda, TG Therapeutics, Xencor, Ziopharm, Burroughs Wellcome Fund, Eastern Cooperative Oncology Group, National Cancer Institute, V Foundation, Cancer Prevention and Research Institute of Texas (RR190079): CPRIT Scholar in Cancer Research J. W. Friedberg Other remuneration: Research funding: Enterome M. Trněný Consultant or advisory role: Takeda, Bristol Myers Squibb, Incyte, AbbVie, Amgen, Roche, Gilead Sciences, Janssen, MorphoSys, Novartis, Genmab, SOBI, Autolus, Caribou Biosciences Honoraria: Janssen, Gilead Sciences, Takeda, Bristol Myers Squibb, Amgen, AbbVie, Roche, MorphoSys, Novartis, SOBI, Swixx Educational grants: Gilead Sciences, Takeda, Roche, Janssen, AbbVie, SOBI C. Herbaux Consultant or advisory role: Roche, Janssen, AbbVie, Gilead/Kite, Incyte, Novartis Honoraria: Roche, Janssen, AbbVie, Gilead/Kite, Incyte, Novartis Educational grants: Roche, Janssen, AbbVie, Gilead/Kite, Incyte, Novartis Other remuneration: Research funding: AbbVie, Takeda M. Yan Employment or leadership position: Hoffmann-La Roche Stock ownership: Hoffmann-La Roche Other remuneration: Patents, royalties, other intellectual property: Hoffmann-La Roche S. Chohan Employment or leadership position: Hoffmann-La Roche M. Sugidono Employment or leadership position: Genentech, Inc. Stock ownership: Genentech/Roche L. Wang Employment or leadership position: Roche, Genentech Y. Jiang Employment or leadership position: Roche/Genentech Stock ownership: Roche Educational grants: Roche Other remuneration: Patents, royalties, other intellectual property: Roche C. L. Batlevi Employment or leadership position: Roche/Genentech Consultant or advisory role: BMS, Seattle Genetics, Kite, Karyopharm, TG Therapeutics, ADC Therapeutics, AbbVie, Genentech, Treeline Bioscience Stock ownership: Roche Honoraria: Dava Oncology, TouchIME, Medscape Other remuneration: Research funding: Epizyme, Autolus, Roche, Vincerx W. Leung Employment or leadership position: Roche/Genentech Stock ownership: Roche Educational grants: Roche/Genentech W. Harris Employment or leadership position: Genentech, Inc. Stock ownership: Roche Other remuneration: Patents, royalties, other intellectual property: Genentech, Inc. G. Salles Consultant or advisory role: AbbVie, ATB Therapeutics, BeiGene, Bristol Myers Squibb, Debiopharm, Genentech/Roche, Genmab, Innate Pharma, Incyte, Ipsen, Janssen, Kite/Gilead, Loxo/Lilly, Merck, Modex, Molecular Partners, Nordic Nanovector, Novartis, Nurix, Orna Therapeutics, Treeline Stock ownership: Owkin Honoraria: Genentech/Roche, Incyte, Merck Other remuneration: Speaker's bureau: Genentech/Roche, Incyte, Merck; Research funding from AbbVie, Genentech, Genmab, Janssen, Ipsen L. H. Sehn Consultant or advisory role: AbbVie, Amgen, AstraZeneca, BeiGene, Bristol Myers Squibb, Kite, Gilead, Incyte, Janssen, Merck, Seagen, Genentech/Roche Honoraria: AbbVie, Amgen, AstraZeneca, BeiGene, Bristol Myers Squibb, Kite, Gilead, Incyte, Janssen, Merck, Seagen, Genentech/Roche Other remuneration: Research funding: Genentech/Roche, Teva

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.262
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2025
Admission routes1
Has abstractyes

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