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Record W4379981851 · doi:10.1002/hon.3163_146

IMMUNE CONTEXTURE ANALYSIS IN POLARIX SUGGESTS RESPONSE TO POLA‐R‐CHP TREATMENT REDUCES TUMOR MICROENVIRONMENT DEPENDENCY

2023· article· en· W4379981851 on OpenAlexaff
Franck Morschhauser, Katerina Hatzi, Georg Lenz, Alex F. Herrera, Christopher R. Flowers, Marek Trněný, John M. Burke, Jian Hou, Philipp B. Staber, Eliza A. Hawkes, Koji Izutsu, Steven Le Gouill, David Belada, Alessandra Tucci, M. Yan, W. Harris, Jamie Hirata, Chengkuo Lee, Yanwen Jiang, Fabrice Jardin

Bibliographic record

VenueHematological Oncology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsRoche (Canada)
Fundersnot available
KeywordsInternational Prognostic IndexRituximabVincristineMedicineDiffuse large B-cell lymphomaCyclophosphamideInternal medicinePrednisoneCHOPTumor microenvironmentImmune systemLymphomaOncologyHazard ratioCD20GastroenterologyCancer researchImmunologyChemotherapy

Abstract

fetched live from OpenAlex

Introduction: The lymphoma microenvironment contributes to clinical treatment outcome. Previously, we showed that enrichment in M1 macrophages was associated with improved clinical outcome in patients with diffuse large B-cell lymphoma (DLBCL) treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP; Yan et al., 2020). In the POLARIX study (NCT03274492), polatuzumab vedotin in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) demonstrated prolonged progression-free survival (PFS) versus R-CHOP in patients with previously untreated DLBCL (Tilly et al., 2022). Here, we investigate the relationship between the lymphoma microenvironment at baseline and clinical outcomes in patients treated with Pola-R-CHP or R-CHOP in POLARIX. Methods: Global gene expression patterns of baseline tumor biopsies from patients treated with Pola-R-CHP or R-CHOP in POLARIX were generated by RNA-seq. Immune and stromal cell tumor content was estimated using the xCell and QuanTIseq algorithms. Association of the infiltration scores with PFS was evaluated. Hazard ratios (HR) were adjusted for International Prognostic Index score (2 vs. 3–5), age (≤60 vs. >60 years), and cell of origin (activated B cell, germinal center B cell, unclassified, unknown). Results: Gene expression data were generated from 665 patients in POLARIX (Pola-R-CHP, n = 331; R-CHOP, n = 334). M1 macrophage infiltration levels were comparable between treatment arms. Quantity of M1 macrophage infiltration was the primary immune-related positive prognostic factor for PFS in patients treated with R-CHOP. High levels (above median) of M1 macrophages were associated with improved PFS when quantified by either QuanTIseq (HR 0.60, 95% confidence interval [CI]: 0.41–0.88) or xCell (HR 0.57, 95% CI: 0.39–0.84). In contrast, M1 macrophage infiltration did not impact clinical activity of the Pola-R-CHP regimen when quantified by either QuanTIseq (HR 0.90, 95% CI: 0.58–1.38) or xCell (HR 0.95, 95% CI: 0.62–1.46); the treatment benefit in patients with lymphomas with low M1 macrophage levels was similar to that of patients with high M1 macrophage levels (Figure). Enrichment in various immune infiltrates was linked to either improved or poor survival outcomes in the R-CHOP arm; however, PFS appeared to be largely independent of immune infiltration in the Pola-R-CHP arm. The research was funded by: The POLARIX study (NCT03274492) was sponsored by F. Hoffmann-La Roche Ltd and Genentech, Inc. Third-party editorial assistance, under the direction of the authors, was provided by Anna Nagy, BSc, of Ashfield MedComms, an Inizio company, and was funded by F. Hoffmann-La Roche Ltd. Keywords: aggressive B-cell non-Hodgkin lymphoma, targeting the tumor microenvironment Conflicts of interests pertinent to the abstract F. Morschhauser Consultant or advisory role: F. Hoffmann-La Roche Ltd/Genentech, Inc., Gilead Sciences, Celgene, Bristol-Myers Squibb, AbbVie, Epizyme, Servier, AstraZeneca, Novartis, Genmab Honoraria: F. Hoffmann-La Roche Ltd/Genentech, Inc., Chugai, Eisai Other remuneration: F. Hoffmann-La Roche Ltd/Genentech, Inc. (Expert Testimony) K. Hatzi Employment or leadership position: Genentech, Inc. Stock ownership: F. Hoffmann-La Roche Ltd G. Lenz Consultant or advisory role: F. Hoffmann-La Roche Ltd, Gilead Sciences, Janssen, Bristol-Myers Squibb, Novartis, AbbVie, Incyte, Genmab, Constellation, ADC Therapeutics, Karyopharm, Miltenyi, PentixaPharm, Sobi, Immagene, Genase, Hexal/Sandoz, Eli Lilly Research funding: Janssen, Bayer, AstraZeneca, MorphoSys Educational grants: AbbVie, Janssen, F. Hoffmann-La Roche Ltd Other remuneration: F. Hoffmann-La Roche Ltd, Gilead Sciences, Novartis, Takeda, Bristol-Myers Squibb, AbbVie, Incyte, ADC Therapeutics, Sobi, Hexal/Sandoz (Speaker's Bureau); F. Hoffmann-La Roche Ltd (Expert Testimony) A. F. Herrera Consultant or advisory role: Bristol-Myers Squibb, Seattle Genetics, Merck, Genentech, Inc./F. Hoffmann-La Roche Ltd, AstraZeneca/MedImmune, Karyopharm Therapeutics, ADC Therapeutics, Takeda, Regeneron, Genmab, Tubulis GmbH, Pfizer, Adicet Bio, Caribou Biosciences, AbbVie Research funding: Bristol-Myers Squibb, Merck, Genentech, Inc./F. Hoffmann-La Roche Ltd, Kite (a Gilead company), AstraZeneca, Seattle Genetics, Gilead Sciences, ADC Therapeutics Educational grants: Bristol-Myers Squibb C. R. Flowers Consultant or advisory role: Bayer, Gilead Sciences, Spectrum Pharmaceuticals, AbbVie, Celgene, Denovo Biopharma, BeiGene, Karyopharm Therapeutics, Pharmacyclics, Janssen, Genentech, Inc./F. Hoffmann-La Roche Ltd, Epizyme, Genmab, Seattle Genetics, Foresight Diagnostics, Bristol-Myers Squibb/Celgene, Curio Science, AstraZeneca, MorphoSys Stock ownership: Foresight Diagnostics, npower Research funding: Acerta Pharma, Janssen Oncology, Gilead Sciences, Celgene, TG Therapeutics, Genentech, Inc./F. Hoffmann-La Roche Ltd, Pharmacyclics, AbbVie, Millennium, Alimera Sciences, Xencor, 4D Pharma, Adaptimmune, Amgen, Bayer, Cellectis, EMD Serono, Guardant Health, Iovance Biotherapeutics, Kite/Gilead Sciences, MorphoSys, Nektar, Novartis, Pfizer, Sanofi, Takeda, Ziopharm Oncology M. Trněný Consultant or advisory role: Takeda, Bristol-Myers Squibb, Incyte, AbbVie, Amgen, F. Hoffmann-La Roche Ltd, Gilead Sciences, Janssen, MorphoSys, Novartis Honoraria: Janssen, Gilead Sciences, Takeda, Bristol-Myers Squibb, Amgen, AbbVie, F. Hoffmann-La Roche Ltd, MorphoSys, Novartis Educational grants: Gilead Sciences, Takeda, Bristol-Myers Squibb, F. Hoffmann-La Roche Ltd, Janssen, AbbVie J. M. Burke Consultant or advisory role: Adaptive Biotechnologies, AstraZeneca, BeiGene, Epizyme, Kura, Kymera, Morphosys, Nurix, F. Hoffmann-La Roche Ltd/Genentech, Inc., Seattle Genetics, TG Therapeutics, Verastem, X4 Pharmaceuticals Research funding: Novartis Other remuneration: Bristol-Myers Squibb, Seattle Genetics (Speaker’s Bureau) J. Hou Consultant or advisory role: AstraZeneca, AbbVie Research funding: AstraZeneca P. B. Staber Consultant or advisory role: F. Hoffmann-La Roche Ltd, AbbVie, Gilead Sciences, Janssen, AstraZeneca, Takeda, MSD, Bristol-Myers Squibb, Incyte, BeiGene, Eli Lilly Honoraria: F. Hoffmann-La Roche Ltd, AbbVie, Gilead Sciences, Janssen, AstraZeneca, Takeda, MSD, Bristol-Myers Squibb, Incyte, BeiGene, Eli Lilly Research funding: F. Hoffmann-La Roche Ltd Educational grants: F. Hoffmann-La Roche Ltd, AbbVie E. A. Hawkes Consultant or advisory role: Bristol-Meyers Squibb, F. Hoffmann-La Roche Ltd, Gilead Sciences, Antengene, Link, Novartis, BeiGene, MSD Research funding: AstraZeneca, Merck, Bristol-Myers Squibb, F. Hoffmann-La Roche Ltd Educational grants: AstraZeneca Other remuneration: Regeneron, Janssen, Merck, AstraZeneca, F. Hoffmann-La Roche Ltd K. Izutsu Consultant or advisory role: Genmab, BeigGene, Kyowa Kirin, Ono Pharmaceutical, Mitsubishi Tanabe Pharma, Eisai, Zenyaku Kogyo Honoraria: Bristol-Myers Squibb, AstraZeneca, Eisai, Zenyaku Kogyo, Kyowa Kirin, Takeda, Chugai, Novartis, MSD, SymBio, Nihon Shinyaku, AbbVie, Ono Pharmaceutical, Pfizer, Genmab, Eli Lilly, Meiji Seika Pharma, Daiichi Sankyo Research funding: MSD, AstraZeneca, AbbVie, Eisai, Incyte, Novartis, Pfizer, Janssen, Yakult, Kyowa Kirin, Ono Pharmaceutical, Daiichi Sankyo, Chugai, BeiGene, Genmab, LOXO Oncology, Otsuka, Regeneron S. Le Gouill Employment or leadership position: F. Hoffmann-La Roche Ltd D. Belada Consultant or advisory role: F. Hoffmann-La Roche Ltd Research funding: F. Hoffmann-La Roche Ltd Educational grants: F. Hoffmann-La Roche Ltd A. Tucci Consultant or advisory role: Janssen, Gentili, Sanofi Honoraria: Takeda, Kiowa Kyrin, MSD, Incyte M. Yan Employment or leadership position: Hoffmann-La Roche Ltd Stock ownership: Hoffmann-La Roche Ltd W. Harris Employment or leadership position: Genentech, Inc. Stock ownership: F. Hoffmann-La Roche Ltd J. Hirata Employment or leadership position: Genentech, Inc. Stock ownership: F. Hoffmann-La Roche Ltd C. Lee Employment or leadership position: F. Hoffmann-La Roche Ltd Stock ownership: F. Hoffmann-La Roche Ltd Y. Jiang Employment or leadership position: F. Hoffmann-La Roche Ltd/Genentech, Inc. Stock ownership: F. Hoffmann-La Roche Ltd/Genentech, Inc. F. Jardin Consultant or advisory role: F. Hoffmann-La Roche Ltd Honoraria: F. Hoffmann-La Roche Ltd, Celgene, Janssen, AbbVie, Genentech, Inc. Educational grants: F. Hoffmann-La Roche Ltd

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.005

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 head0.020
GPT teacher head0.305
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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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Citations2
Published2023
Admission routes1
Has abstractyes

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