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. 2024 Apr 9;8(7):1600-1611.
doi: 10.1182/bloodadvances.2023011225.

CD8 effector T cells enhance teclistamab response in BCMA-exposed and -naïve multiple myeloma

Ross S Firestone  1 , Devin McAvoy  2 , Tala Shekarkhand  1 , Edith Serrano  1 , Issam Hamadeh  1 , Alice Wang  1 , Menglei Zhu  3 , Wei Ge Qin  3 , Dhwani Patel  1 , Carlyn R Tan  1 , Malin Hultcrantz  1 , Sham Mailankody  1   4 , Hani Hassoun  1 , Urvi S Shah  1 , Neha Korde  1 , Kylee H Maclachlan  1 , Heather J Landau  4   5 , Michael Scordo  4   5 , Gunjan L Shah  4   5 , Oscar B Lahoud  4   5 , Sergio Giralt  4   5 , Kazunori Murata  3 , Kinga K Hosszu  2 , David J Chung  4   5 , Alexander M Lesokhin  1   4 , Saad Z Usmani  1   4   5
Affiliations

CD8 effector T cells enhance teclistamab response in BCMA-exposed and -naïve multiple myeloma

Ross S Firestone et al. Blood Adv. .

Abstract

Teclistamab, a B-cell maturation antigen (BCMA)- and CD3-targeting bispecific antibody, is an effective novel treatment for relapsed/refractory multiple myeloma (R/RMM), but efficacy in patients exposed to BCMA-directed therapies and mechanisms of resistance have yet to be fully delineated. We conducted a real-world retrospective study of commercial teclistamab, capturing both clinical outcomes and immune correlates of treatment response in a cohort of patients (n = 52) with advanced R/RMM. Teclistamab was highly effective with an overall response rate (ORR) of 64%, including an ORR of 50% for patients with prior anti-BCMA therapy. Pretreatment plasma cell BCMA expression levels had no bearing on response. However, comprehensive pretreatment immune profiling identified that effector CD8+ T-cell populations were associated with response to therapy and a regulatory T-cell population associated with nonresponse, indicating a contribution of immune status in outcomes with potential utility as a biomarker signature to guide patient management.

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Conflict of interest statement

Conflict-of-interest disclosure: T.S. reports receiving honoraria from Roche-Genentech. M.Z. has received advisory or consulting fees from Leica Biosystems. C.R.T. reports research funding from Janssen and Takeda; personal fees from Physician Educations Resource and MJH Life Sciences; and has participated in advisory boards for Janssen and Sanofi, outside of the submitted work. M.H. reports research funding from GlaxoSmithKline, BeiGene, AbbVie, and Daiichi Sankyo, and has received honoraria for consultancy/participated in the advisory boards for Curio Science LLC, Intellisphere LLC, Bristol Myers Squibb, Janssen and GlaxoSmithKline. S.M. received consulting fees from EviCore, Optum, BioAscend, Janssen Oncology, Bristol Myers Squibb, AbbVie, HMP Education, and Legend Biotech, and honoraria from OncLive, Physician Education Resource, MJH Life Sciences, and Plexus Communications. Memorial Sloan Kettering Cancer Center receives research funding from the NCI, Janssen Oncology, Bristol Myers Squibb, Allogene Therapeutics, Fate Therapeutics, Caribou Therapeutics, and Takeda Oncology for conducting research. U.A.S. reports research support from Celgene/Bristol Myers Squibb and Janssen; personal fees from ACCC, MashUp MD, Janssen Biotech, Sanofi, Bristol Myers Squibb, MJH LifeSciences, Intellisphere, Phillips Gilmore Oncology Communications, i3 health, and RedMedEd; and nonfinancial support from American Society of Hematology Clinical Research Training Institute and TREC Training Workshop (R25CA203650; PI: Melinda Irwin). N.K. reports research funding through Amgen; participates in the advisory board with MedImmune and Janssen; and reports research funding through Amgen, Janssen, Epizyme, and AbbVie; consults for CCO, OncLive, and Intellisphere Remedy Health. H.J.L. has served as a paid consultant for Takeda, Genzyme, Janssen, Karyopharm, Pfizer, Celgene, and Caelum Biosciences, and has received research support from Takeda. M.S. served as a paid consultant for McKinsey & Company, Angiocrine Bioscience, Inc, and Omeros Corporation; received research funding from Angiocrine Bioscience, Inc, Omeros Corporation, and Amgen; served on ad hoc advisory boards for Kite, a Gilead company; and received honoraria from i3 Health, Medscape, and Cancer Network for CME-related activity. G.L.S. reports research funding from Janssen, Amgen, Bristol Myers Squibb, Beyond Spring, and serves on the data safety monitoring board for ArcellX. G.S. reports research funding to the instiution from Janssen, Amgen, Bristol Myers Squibb, BeyondSpring, and GPCR, and serving on a data safety monitoring board for ArcellX. O.B.L. reports serving on the advisory board for MorphoSys. S.G. reports personal fees from and an advisory role (scientific advisory board) for Actinium, Celgene, Bristol Myers Squibb, Sanofi, Amgen, Pfizer, GlaxoSmithKline, Jazz, Janssen, Omeros, Takeda, and Kite, outside the submitted work. D.J.C. receives research funding from Genentech. A.M.L. reports nonfinancial support from Pfizer; grants and personal fees from Janssen, outside the submitted work; and patent US20150037346A1 with royalties paid. S.U. reports grants and personal fees from AbbVie, Amgen, Bristol Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Merck, Mundipharma, OncopeptidesPharmacyclics, Sanofi, Seattle Genetics, SkylineDX, and Takeda. The remaining authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Clinical outcomes with commercial teclistamab. (A) Swimmer plot for patients responding to teclistamab colored by treatment response according to IMWG criteria, with “→” designating ongoing treatment response as of the data cutoff. (B) PFS for all patients treated with commercial teclistamab. (C) PFS with teclistamab stratified by BCMA therapy exposure. (D) PFS for patients exposed to BCMA therapy with >200 days since their most recent anti-BCMA therapy vs <200 days since their most recent anti-BCMA therapy. IMWG, International Myeloma Working Group.
Figure 2.
Figure 2.
BCMA-expression profiles of plasma cells. (A-B) BCMA expression measured as a percentage of total plasma cell BCMA expression comparing (A) teclistamab nonresponders and responders and (B) patients with and without prior anti-BCMA exposure. (C-D) Plasma cell BCMA expression measured by BCMA staining intensity by IHC (scale, 0-3) comparing (C) teclistamab nonresponders with responders, and (D) patients with and without prior anti-BCMA exposure. (E-F) Pretreatment bone marrow biopsies showing positive BCMA staining (brown) by IHC for representative patients including (E) a patient refractory to both belantamab mafodotin and idecabtagene-vicleucel but responding to teclistamab, and (F) a patient who achieved MRD-CR after idecabtagene-vicleucel now responding to teclistamab after relapse. CR, complete response; MRD, minimal residual disease.
Figure 3.
Figure 3.
Absolute lymphocyte count trend and cytokine release syndrome incidence associate with teclistamab clinical outcomes. (A) Pretreatment absolute lymphocyte count for patients responding to teclistamab includes several patients with grade 3 or grade 4 lymphopenia. (B) ALC level changes during step-up dosing for teclistamab patients. (C) PFS with teclistamab stratified by patients with and without CRS during step-up dosing. (D) Response rates by IMWG classification for patients with and without CRS during step-up dosing. ALC, absolute lymphocyte count; IMWG, International Myeloma Working Group.
Figure 4.
Figure 4.
High–dimensional spectral cytometry of pretreatment PBMCs. (A) Immune profiling workflow. (B) The spectral cytometry flow panel including subset, lineage, exhaustion markers, and activation markers is shown with (A) designating markers not included in dimensionality reduction analysis. (C) Dimensionality reduction analysis of pretreatment PB T cells identified 12 unique T-cell populations. (D) T-cell populations separated by teclistamab responders and nonresponders.
Figure 5.
Figure 5.
Effector CD8+ T cells are enriched in teclistamab responders. T-cell gating for CD4 and CD8 for (A) teclistamab nonresponders and (B) responders. (C) CD8+:CD4+ T-cell ratios in teclistamab nonresponders vs responders. (D) TEM and (E) TEMRA cell abundance in teclistamab responders vs nonresponders. (F) Feature plots highlighting the differential expression of TIGIT, PD1, CTLA4, LAG3, and TIM3 by TEM and TEMRA CD8+ T-cell subpopulations.
Figure 6.
Figure 6.
TIGIT+ Tregs are increased in teclistamab nonresponders. T-cell gating of the CD4+ subpopulation identifies CD25+CD127lo Tregs in (A) teclistamab nonresponders and (B) teclistamab responders. Values shown in panels A and B refer to percentage of total T cells, whereas contour plots refer to percentage of total CD4+ T cells. (C) CD4+ central memory T cells and (D) Treg abundance in teclistamab nonresponders vs responders. (E) Feature plots highlighting the differential expression of TIGIT, PD1, CTLA4, LAG3, TIM3, and CD38 by CD4+ TCM and Treg subpopulations.
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