Lee, Holly

ABSTRACT Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell–associated transcriptional programs, a phenomenon we term “plasma cell identity escape.” This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

Abstract Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). Although they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor-cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, we analyzed whole-genome and whole-exome sequencing data from patients 701 newly diagnosed MM, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse after anti-CD38 antibodies. We report a loss of CD38 in 10 of 50 patients (20%) after CD38 therapy, 3 of whom exhibited a loss of both copies. Two of these cases showed convergent evolution in which distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that 2 variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies daratumumab and isatuximab. However, a third mutation, R140G, conferred selective resistance to daratumumab, while retaining sensitivity to isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies after disease progression and these data suggest that next-generation sequencing may play a role in subsequent treatment selection for a subset of patients.

Introduction Monoclonal antibodies (MoAbs) directed against CD38 are a mainstay in multiple myeloma (MM). Downregulation of CD38 expression is a resistance mechanism of antigenic escape, however, cell surface expression may return. While this tumor cell plasticity is likely driven by epigenetic mechanisms, it is unknown if MM cells can develop permanent resistance to anti-CD38 MoAb by acquiring genomic events leading to biallelic disruption of CD38 thus precluding re-treatment. Here, we report biallelic loss of CD38 as a recurrent mechanism of resistance, often via convergent evolution where distinct subclones are advantaged towards the same selective pressure. Methods We interrogated two sets of patients (Mayo Clinic; n = 31, Calgary University; n =19) with relapse following anti-CD38 MoAbs. Two additional cases of interest were selected from Heidelberg University. Whole genome sequencing (WGS, 60-100x) or whole exome sequencing (WXS), flow cytometry (flow), and bulk RNAseq were used to validate the effect of genomic events on CD38. Missense mutations predicted to affect CD38 MoAb binding were validated with site-directed mutagenesis of a CD38 plasmid, transduction into K562 MM cells, and CD38 MoAb binding assays. Results The prevalence of biallelic inactivation of CD38 at anti-CD38 MoAb relapse was 6% (3/50). An additional selected biallelic event was noted in the Heidelberg set. Each case is described in detail: MM-19 (Calgary) received daratumumab (Dara), lenalidomide, and dexamethasone (Dex), and then had a second exposure to Dara, following relapse. At this second relapse, WGS was performed on two independent extramedullary disease localizations in the liver. Both samples had unique, large deletions (>3 Mb) on chromosome 4 coupled with additional unique focal deletions involving CD38. Flow confirmed the presence of CD138+/CD38- plasma cell populations in both sites. A second case of convergent evolution was seen in a patient (Mayo) after seventh-line Dara/Len/Dex. WGS revealed a common deletion encompassing CD38. On the remaining allele, one subclone had a structural variation-mediated loss of CD38(cancer cell fraction; CCF 40%) while another harbored an L153H missense mutation (CCF 60%). Flow confirmed presence of two CD138+ clones; one with diminished CD38 expression. L153H was functionally validated to abrogate Dara binding, while maintaining CD38 expression. The third sample was collected after fifth-line Dara and sixth-line Dara/Bortezomib/Dex (Heidelberg) and represents another case of convergent evolution with a common loss of chromosome 4 and two subclones detected by WGS (P98Lfs*12, CCF 39% resulting in biallelic inactivation; R140G, CCF 61%). Bulk RNAseq revealed, in comparison to NDMM from CoMMpass, CD38 expression below the first decile. Notably, the R140G variant reduced binding affinity to Dara but not to Isatuximab (Isa). A fourth case (Mayo) relapsing after 6 months of Dara-based therapy similarly had a focal deletion of CD38 with an L18Sfs*16 frameshift deletion on the remaining allele associated with a 4.35-fold reduction in CD38 expression by RNAseq compared to pre-treatment. Interestingly, in 3/4 cases the CD38-negative clone emerged after a second exposure to anti-CD38 MoAb, suggesting emergence with the first exposure and then selection during the second. One other monoallelic event (C275Y; Heidelberg) was detected post-Isa. Copy number of the alternate allele is not known given targeted sequencing methodology, but the variant was seen to reduce binding affinity to both Dara and Isa. The prevalence of monoallelic loss of CD38 in newly diagnosed MM from MMRF CoMMpass was 7% (50/701) and two patients had mutations in CD38, but there were no cases of biallelic loss suggesting these events are driven by treatment pressure. Conclusion Distinction of the mode of CD38 loss is valuable for predicting outcome of re-challenge to anti-CD38 MoAbs. We see here an estimated 5-10% of anti-CD38 MoAb relapses are characterized by genomic antigen escape. Results here are in line with antigen escape to BCMA- and GPRC5D-directed immunotherapies (Lee et al, Nat Med 2023), suggesting that acquired antigen escape resulting from prolonged exposure to the selective pressures of immunotherapy is a recurrent mechanism of resistance in MM. Moreover, in select cases, non-overlapping resistance mutations provide rationale for switching agents at second exposure.

Abstract Immunomodulatory drugs (IMiD) are a backbone therapy for multiple myeloma (MM). Despite their efficacy, most patients develop resistance, and the mechanisms are not fully defined. Here, we show that IMiD responses are directed by IMiD-dependent degradation of IKZF1 and IKZF3 that bind to enhancers necessary to sustain the expression of MYC and other myeloma oncogenes. IMiD treatment universally depleted chromatin-bound IKZF1, but eviction of P300 and BRD4 coactivators only occurred in IMiD-sensitive cells. IKZF1-bound enhancers overlapped other transcription factor binding motifs, including ETV4. Chromatin immunoprecipitation sequencing showed that ETV4 bound to the same enhancers as IKZF1, and ETV4 CRISPR/Cas9-mediated ablation resulted in sensitization of IMiD-resistant MM. ETV4 expression is associated with IMiD resistance in cell lines, poor prognosis in patients, and is upregulated at relapse. These data indicate that ETV4 alleviates IKZF1 and IKZF3 dependency in MM by maintaining oncogenic enhancer activity and identify transcriptional plasticity as a previously unrecognized mechanism of IMiD resistance. Significance: We show that IKZF1-bound enhancers are critical for IMiD efficacy and that the factor ETV4 can bind the same enhancers and substitute for IKZF1 and mediate IMiD resistance by maintaining MYC and other oncogenes. These data implicate transcription factor redundancy as a previously unrecognized mode of IMiD resistance in MM. See related article by Welsh, Barwick, et al., p. 34. See related commentary by Yun and Cleveland, p. 5. This article is featured in Selected Articles from This Issue, p. 4

Introduction: Light chain deposition disease (LCDD) is a rare complication of monoclonal gammopathies, defined by non-amyloid linear monoclonal light chain (most commonly kappa) deposits in the kidney and other organs. The rarity of LCDD has hampered clinical studies and staging systems and response criteria are lacking. The International Kidney Myeloma Working Group (IKMG) started a clinical data collection from all participating centers in order to define the natural history of LCDD, and to establish prognostic factors and response criteria in a large, international, unselected patient population. Methods: Eight referral centers have yet participated in the data collection at the data lock of July 31, 2020. Patient inclusion is ongoing and expected accrual is 500 patients. The diagnosis of LCDD had to be biopsy-proven. The patients were diagnosed between 1992 to 2020. Response was assessed 6 months after treatment initiation according to the criteria used in light chain (AL) amyloidosis. Renal survival (RS) was defined as time from diagnosis to dialysis or last follow-up. Patients who died without requiring dialysis were censored at the time of death. The analysis of factors predicting RS was performed in patients whose baseline estimated glomerular filtration rate (eGFR) was >15 mL/min. The cutoffs of baseline variables, as well as the cutoffs measured at the time of response, best predicting RS or OS at 12 months were identified by means of Receiver Operator Characteristics (ROC) analyses. All patients gave written informed consent for their clinical data to be used for research purposes. Results: Overall, 359 patients have been included in this first analysis. Sixteen (4%) subjects had concomitant cast nephropathy. The main clinical characteristics are reported in the Table. Median overall survival (OS) was 13 years and RS was 12 years (Figure1 A and 1B) and median survival of living patients is 4.5 years. At univariate analysis the only baseline variables predicting RS were proteinuria [best cutoff 2.5 g/24h, HR 2.25 (95%CI 1.13-4.60), P=0.02], and eGFR [best cutoff >30 mL/min, HR 0.50 (95%CI 0.26-0.96) P=0.037], but at multivariate analysis only proteinuria predicted RS [HR 2.17 (95% CI 1.08, 4.33), P=0.027]. At univariate analysis, a higher bone marrow plasma cell infiltrate (best cutoff ≥20%) at diagnosis was associated with a significantly lower OS [HR 1.96 (95% CI 1.23-3.13) P=0.004], as was having end stage renal disease (ESRD) defined as an eGFR <15 mL/min [HR 1.81 (95%CI 1.11-2.92) P=0.015]. We then tested the ability of the hematologic response criteria for AL amyloidosis to discriminate groups with different survival after treatment in a 6 months landmark analysis. Our choice of adopting the amyloidosis response criteria was corroborated by the results of the ROC analysis showing that the difference between involved and uninvolved free light chains (dFLC) cutoff (40 mg/L) used in AL amyloidosis to define very good partial response (VGPR) had 87% sensitivity and 65% specificity in identifying patients who needed dialysis within 12 months. Partial response (PR, 19% requiring dialysis at 3 years) was not associated with a RS benefit over no-response (29% requiring dialysis at 3 years, P=0.511). However, VGPR conferred a significant RS advantage (10% requiring dialysis at 3 years) over PR (P=0.002). No significant difference in RS was seen between complete response (CR, 0% requiring dialysis at 3 years) and VGPR (P=0.178). Thus, achieving VGPR or CR by amyloidosis response criteria [post-treatment dFLC<40 mg/L (VGPR by AL criteria), with or without negative serum and urine immunofixation and normal FLC-ratio (CR by AL criteria)] was adopted as a provisional criterion for hematologic response in LCDD (Figure 1D). LCDD response was also associated with prolonged OS (Figure 1C). Conclusions: Almost one-third of patients with LCDD are diagnosed when they already have ESRD resulting in shorter OS. The degree of proteinuria and of bone marrow plasma cell infiltration predict RS and OS, respectively. Achievement of post treatment dFLC <40 mg/L or negative serum and urine immunofixation at 6 months is proposed as a provisional criterion for hematologic response, being able to predict both improved RS and OS. Planned expanded recruitment might allow a validation analysis of the results, the analysis of organ response data and the evaluation of different time-points for response assessment. Disclosures Milani: Celgene: Other: Travel support; Janssen: Other: Speaker honoraria; Pfizer: Other: Speaker honoraria. Kastritis:Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Consultancy, Honoraria. Schönland:Janssen, Prothena, Takeda: Honoraria, Other: travel support to meetings, Research Funding. Bridoux:Baxter: Consultancy; Janssen: Honoraria; Celgene: Honoraria. Tuchman:Celgene: Honoraria, Research Funding, Speakers Bureau; Oncopeptides: Consultancy; Amgen: Research Funding; Caelum: Honoraria; Sanofi: Honoraria, Research Funding; Janssen: Research Funding; Roche: Research Funding; Karyopharm: Honoraria, Research Funding. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Palladini:Jannsen Cilag: Honoraria, Other; Celgene: Other: Travel support. Wechalekar:Celgene: Honoraria; Caelum: Other: Advisory; Janssen: Honoraria, Other: Advisory; Takeda: Honoraria, Other: Travel.