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Record W3215615180 · doi:10.1182/blood-2021-154506

Normalization of the Immune Microenvironment during Lenalidomide Maintenance Is Associated with Sustained MRD Negativity in Patients with Multiple Myeloma

2021· article· en· W3215615180 on OpenAlexaff
David G. Coffey, Francesco Maura, Edgar Gonzalez‐Kozlova, Javier Diaz-Mejia, Ping Luo, Yong Zhang, Yuexin Xu, Edus H. Warren, Eric L. Smith, Hearn Jay Cho, Alexander M. Lesokhin, Benjamin Diamond, Dickran Kazandjian, Trevor J. Pugh, Damian J. Green, Sacha Gnjatic, Ola Landgren

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsLenalidomideMultiple myelomaMedicineBone marrowMinimal residual diseaseMaintenance therapyImmune systemOncologyInternal medicineHematologyImmunologyChemotherapy

Abstract

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Abstract Background: The progression of multiple myeloma (MM) during ongoing therapy is driven by a complex interplay between tumor cells and their surrounding immune microenvironment. We were motivated to conduct a comprehensive and orthogonal investigation of the cellular and humoral immunity of patients with MM treated with lenalidomide maintenance therapy. We compared patients who achieved sustained minimal residual disease (MRD) negativity during the first year of maintenance therapy to those who lost or were unable to attain an MRD negative state. Methods: As part of our prospective phase II clinical trial designed to investigate the MRD dynamics and the efficacy of continuous lenalidomide maintenance in MM (NCT02538198, Lancet Haematology 2021; 8:e422-32), we conducted a pre-planned correlative investigation to elucidate the roles of cellular and humoral immunity. We leveraged single-cell RNA sequencing (scRNAseq) coupled with V(D)J sequencing of peripheral blood mononuclear cells and CyTOF mass cytometry of bone marrow samples collected before and approximately one year after starting maintenance therapy (median 342 days). Proteomic analysis of 92 immuno-oncology related proteins within bone marrow plasma was performed using Olink. Reference-based mapping was used to perform automated cell classification of 31 immune cell subtypes using scRNAseq. A custom 38-marker panel enabled the identification of 21 immune cell subtypes by CyTOF. A total of 40 peripheral blood samples from 20 patients were analyzed by scRNAseq, 28 bone marrow aspirates from 14 patients were analyzed by CyTOF, and 34 plasma samples from 16 patients were analyzed by Olink. Results: Prior to maintenance therapy, 11 (46%) patients completed planned induction therapy and high-dose melphalan (HDM) followed by autologous stem cell transplantation (ASCT); 13 (54%) received planned induction therapy without HDM-ASCT. Through the integration of scRNAseq and CyTOF by bioinformatic analyses, we were able to characterize the cellular composition and phenotypic states of the immune microenvironment before maintenance therapy and after exposure to lenalidomide. Profound and sustained immunosuppression was observed among patients exposed to HDM-ASCT, which associated with accelerated seeding of MM recurrence (Nature Communications 2020;11:3617). Independent of prior exposure to HDM-ASCT, we found differential abundance of immune cell composition to be associated with sustained versus unsustained MRD negativity. Additionally, patients who achieved and sustained MRD negativity (compared to patients with unsustained MRD negativity) had increased frequency of circulating naïve CD8+ T cells in their baseline sample, as well as elevated levels of circulating naïve CD4+ T cells during therapy. When investigating the dynamics of the immune microenvironment longitudinally, circulating regulatory T cells were found to increase during maintenance therapy among patients who had early progression. In the bone marrow, NK cells were more abundant in patients who achieved but could not sustain MRD negativity while vascular endothelial growth factor (VEGF) levels were increased in patients with sustained MRD negativity. We compared our results to a separate report describing the immune microenvironment in patients with MM and healthy donors (Zavidij et al. Nature Cancer 2020;1:493-506) and found the immune landscape of MM patients with sustained MRD negativity to gradually normalize. In contrast, immunosuppression remained present at baseline and during follow-up in MM patients with unsustained MRD negativity. Conclusions: Our findings represent the first detailed characterization of the longitudinal dynamics of the immune microenvironment in relation to low-burden disease in patients with MM treated with lenalidomide maintenance therapy. As expected, HDM-ASCT exposure translated into long-term cellular and humoral immunosuppression, which correlated with dynamics of MM recurrence. Independent of the profound impact of HDM-ASCT on host immunity, the composition of the immune microenvironment varied according to the depth of response. Patients with unsustained MRD negativity had hallmarks of immune dysregulation at baseline and during lenalidomide maintenance, while those who achieved and sustained MRD negativity showed gradual normalization of the immune microenvironment. Disclosures Maura: Medscape: Consultancy, Honoraria; OncLive: Honoraria. Smith: BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties: CAR T cells for MM; Sanofi: Patents & Royalties: GPRC5D antibody based therapies; Novarits: Consultancy; Chimeric Therapeutics: Consultancy; Fate Therapeutics: Research Funding; Eureka Therapeutics: Consultancy. Lesokhin: bristol myers squibb: Research Funding; Genetech: Research Funding; Trillium Therapeutics: Consultancy; pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding; Serametrix, Inc: Patents & Royalties; Behringer Ingelheim: Honoraria; Iteos: Consultancy. Kazandjian: Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Green: Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Cellectar Biosciences: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees; JANSSEN Biotech: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Therapeutics: Patents & Royalties, Research Funding; Legend Biotech: Consultancy; Neoleukin Therapeutics: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; SpringWorks Therapeutics: Research Funding. Landgren: Celgene: Research Funding; Janssen: Other: IDMC; Janssen: Honoraria; Janssen: Research Funding; Amgen: Honoraria; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.202
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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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Citations7
Published2021
Admission routes1
Has abstractyes

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