Tumor Intrinsic and Antigen-Independent Resistance Mechanisms to Bispecific T Cell Engagers in Multiple Myeloma
Bibliographic record
Abstract
BCMA or GPRC5D targeted bispecific T cell engagers (TCE) yielded significant responses in refractory multiple myeloma (MM), however patients invariably relapse. Furthermore, subsequent salvage therapies post TCE with alternate antigen targeting TCEs or chimeric antigen receptor (CAR) T cells also resulted in suboptimal responses. While antigenic escape is demonstrated to mediate relapse in patients post-TCE, antigen independent tumor intrinsic mechanisms of acquired resistance to TCE or subsequent immune therapies, are yet to be defined. Serial genomic interrogation (by WGS) of TCE resistant primary MM cells (n=30 patients) identified enrichment of gene mutations in the NF-kB canonical and non-canonical pathways including TRAF3 or CYLD deletions and MAP3K14 amplifications. This led us to postulate that NF-kB activating mutations may facilitate the emergence of TCE resistant clones through target antigen dependent or independent mechanisms. To test this hypothesis, we generated a puromycin-resistant TRAF3 knock out OPM2 cells (TRAF3ko) and established an in vitro co-culture model to mimic chronic TCE exposures. In this model, TRAF3ko puromycin-resistant cells are co-cultured with healthy donor peripheral blood mononuclear cells (PBMC) alone or with anti-BCMA TCE teclistamab for up to 96 hours yielding a residual TRAF3ko MM cell survival of 10% in each round. After puromycin purging of co-cultured PBMCs, surviving residual TRAF3ko cells are re-expanded and retreated with PBMCs alone or with PBMCs and TCE. Post 10 iterations of PBMC+TCE coculture with TRAF3ko cells, a teclistamab resistant MM clone was successfully selected (TRAF3ko-R). In order to define the mechanisms of resistance to TCE, these TRAF3ko-R cells were interrogated phenotypically (flow cytometry), transcriptionally (scRNA analysis), and functionally (in vitro cytotoxicity of variable TCE cocultures). Cytotoxicity evaluation of anti-BCMA (teclistamab, elranatamab) or anti-GPRC5D (talquetamab) TCEs at E:T ratio of 1:1 against TRAF3ko MM cells (chronically exposed to PBMC only) versus the TRAF3ko-R cells demonstrated a ≥10 fold increase in the IC50 in TRAF3ko-R cells. This resistance of TRAF3ko-R cells was partially overcome by increasing E:T ratio (10:1), but not by increasing TCE concentrations (range 0.01 - 100 nM). Similarly, TRAF3ko-R also demonstrated 2-fold increased resistance to anti-BCMA CAR T. Phenotypic evaluation of TRAF3ko-R cells revealed retained surface BCMA expression (comparable MFI to TRAF3ko cells) with no genomic TNFRSF17 extracellular domain mutations, consistent with an acquired, antigenic independent, resistance mechanism. To define mediators of this TCE resistance, we performed scRNA transcriptome profiling of TRAF3ko vs TRAF3ko-R cells. Differential gene expression analysis and gene set enrichment analysis (scGSEA) revealed significant downregulation of genes involved in intrinsic apoptotic pathways including PMAIP1 and BBC3 (encoding PUMA and NOXA respectively), as well as the extrinsic pathway with TNFRSF10B (encoding death receptor 5). Notably, pathways mediating physiological and terminal unfolded protein response (UPR) were downregulated with decreased transcript levels of EEF1A2, ATF4 and ERN1, genes known to mediate the apoptotic integrated stress response downstream of PERK and IRE1α. Furthermore, downregulation of ATF4 dimerization partners (ATF3, CEBPB, DDIT, JUN) and ATF4 target genes such as PMAIP, BBC3, CHAC1 and TRIB3 was also noted in TRAF3ko-R cells. Of interest, similar downregulation of the UPR pathway was also previously observed in bone marrow MM cells 28 days post anti-BCMA CAR T cells (Dhodapkar et al. Blood Cancer Discovery 2022). Lastly, genes that mediate other immunogenic cell death such as ferroptosis (PCK2, CHAC1) were also decreased in TRAF3ko-R cells. We herein established an in vitro model of acquired resistance to TCE in MM. Importantly we identified novel tumor intrinsic and antigen independent mediators of resistance to TCEs. These studies revealed a surprising multimodal dynamic tumoral adaptation primarily driven by an attenuation of UPR signaling and ensuing downregulation of multiple intrinsic and extrinsic apoptotic pathways as well as mediators of non-apoptotic immunogenic cell death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".