Kumar, Shaji

Genome-wide association studies (GWAS) of multiple myeloma (MM) in individuals of genetic European ancestry (EA) have identified 35 susceptibility loci. Co-heritability analyses have revealed a strong genetic correlation between MM and its precursor condition, monoclonal gammopathy of undetermined significance (MGUS). Previous research validated the association between a polygenic risk score (PRS) based on 23 MM risk loci and the risk of MGUS. Went and colleagues recently reported 12 new MM risk loci. We constructed a MM-PRS using all 35 MM risk variants and assessed its association with MGUS. Additionally, among individuals with MGUS, we assessed associations of MM-PRS with established prognostic factors [M-protein (<0.2 g/dL; 0.2-1.5 g/dL; >1.5 g/dL); isotype (IgG, IgA, IgM); free light chain (FLC) ratio (Normal (0.26-1.65), Abnormal (<0.26 or >1.65))]. Our study population included 1,723 individuals with MGUS seen at Mayo Clinic, Rochester, MN and 14,175 controls from the Mayo Clinic Biobank who lived in the 27-county region around Rochester, MN, and screened negative for MGUS using MALDI-TOF MS. The majority of MGUS patients and controls were of EA. We used logistic or multinomial regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs). All models were adjusted for age, sex, and the first three principal components. The MM-PRS was significantly associated with MGUS when assessed continuously (OR, 1.28 per standard deviation (SD); 95% CI, 1.22-1.35). When comparing to the middle quintile of the MM-PRS distribution, individuals in the highest quintile had 1.41-fold increased risk of MGUS (95% CI, 1.21-1.64), and individuals in the lowest quintile had 0.68 decreased risk of MGUS (95% CI, 0.57-0.81). Of the 35 SNPs evaluated, 27 demonstrated consistent directions of effect for risk of MGUS with published risk estimates for MM. The effect of MM-PRS differed by isotype (P = 2.2 x 105), with higher MM-PRS associated with IgA MGUS (OR, 1.40 per SD; 95% CI, 1.08-1.81) and a lower MM-PRS associated with IgM (OR, 0.66 per SD; 95% CI, 0.52-0.84) compared to IgG MGUS. The MM-PRS was higher in MGUS patients with M-protein > 1.5 g/dL compared to M-protein of size 0.2-1.5 g/dL, although not statistically significant (OR, 1.41 per SD; 95% CI, 0.95-2.08); there were no differences in the MM-PRS between MGUS patients with M-protein size <0.2 g/dL compared to 0.2-1.5 g/dL (OR, 1.01 per SD;95% CI, 0.81-1.26). There were also no differences in MM-PRS by FLC ratio, (OR, 0.95 per SD; 95% CI, 0.852-1.10 for abnormal vs. normal). Our findings of an association of the MM-PRS with risk of MGUS provides further evidence for shared heritability between MGUS and MM. Future studies are needed to examine whether the expanded MM-PRS adds to existing models for MGUS progression. Citation Format: Angelica Macauda, Alyssa Clay-Gilmour, Cristine Allmer, Danelle Moonen, Aaron D. Normann, Nicholas J. Boddicker, Joselle M. Cook, Linda Baughn, Elizabeth E. Brown, Vincent S. Rajkumar, Esteban Braggio, David L. Murray, Susan L. Slager, Shaji Kumar, Celine M. Vachon. Implications of multiple myeloma polygenic risk scores (PRS) for MGUS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2274.

Background: There is an increased risk of second primary malignancies including second hematological malignancies (SHM) in multiple myeloma (MM) patients undergoing autologous stem cell transplant (auto-SCT) followed by lenalidomide maintenance. We analyzed the characteristics and outcomes of patients who developed SHM after an auto- SCT for MM. Methods: A retrospective study of all MM patients who underwent auto- SCT at Mayo Clinic, Rochester between January 1, 1990, and 31 August 2023 and later developed SHM. Demographic, clinical and pathologic data were collected retrospectively. Overall survival (OS) was calculated from the date of auto-SCT to the date of last follow up. Statistical analyses were performed using GraphPad prism 9.0. Chi-square test was used to calculate the difference between categorical variables. Kaplan Meier method and log rank test were used to estimate OS. Results: Among 3513 patients who underwent at least 1 auto-SCT, 104 (2.9%) developed a SHM at a median follow up of 59 (range, 0.2-265) months. Patients who developed SHM, more frequently received pretransplant alkylating agents (37.5 vs 24.2 %, odds ratio [OR], 1.87; P=0.003) and topoisomerase II inhibitors (anthracyclines/etoposide) (17.3% vs 10.4%, OR [1.79]; P=0.03) compared to a control group of MM patients without SHM. Further, exposure to lenalidomide (77.8% vs 57.6%, OR[2.59]; P <0.0001) and radiation therapy (32.6% vs 23.1%, [1.54]; P=0.04) were more often seen in the SHM cohort compared to control group. Among the 381 patients who underwent > 1 auto- SCT, 3.1% developed SHM. Therapy related myeloid neoplasms (t-MN) accounted for 90.3% of cases [n=94; t-myelodysplastic syndrome (t-MDS=64), t-acute myeloid leukemia (t-AML=12), t-MDS transformed to AML(n=16), chronic myeloid leukemia (n=1), MDS/myeloproliferative neoplasm overlap syndrome (n=1)]. Eight patients (7.6%) developed therapy related B- cell acute lymphoblastic leukemia (t-ALL); Philadelphia (Ph) negative ALL (n=7) and Ph- like ALL (n=1). One patient each developed mixed phenotype acute leukemia and acute leukemia, not otherwise specified. Sixty patients (57.6%) were males and the median age at diagnosis of SHM was 70 (range, 43-84) years. The median time from auto-SCT to diagnosis of SHM was 58.5 (range, 7-236) months. In a multivariate analysis, receiving an alkylating agent (hazard ratio [95% confidence interval]: 2.51 [1.54 to 4.01]; P = 0.0002) and/or topoisomerase II inhibitor as induction for MM (3.12 [1.59 to 5.88]; P = 0.0006), exposure to lenalidomide (7.08 [3.92 to 13.50]; P = <0.0001) and radiation therapy (1.60 [1.02 to 2.44]; P = 0.03) were independent predictors of developing SHM. At diagnosis, 57% (n=37) of t-MDS and 71% (n=20) with t-AML had high risk disease per R-IPSS and 2022 European Leukemia Net respectively. Clonal abnormality in chromosome 5 and/or 7 was present in 45% (n=42) of patients. Complex and monosomal karyotype was seen in 32% (n=30) with t-MN. The most frequently mutated genes based on next generation sequencing data included TP53 (n=33), DNMT3A (n=9), RUNX1 (n=5), TET2 (n=4) and CEBPA (n=4). In the t-MDS/AML cohort, 3 patients (3.1%) underwent second auto-SCT and 9 (9.5%) received allogenic SCT (allo-SCT) for SHM. After a median follow-up of 27.2 months, the median OS from t-MDS/AML diagnosis was 8.04 months (95%CI, 6.1-11.0 months) and there was no difference in median OS for allo-SCT recipients versus nonrecipients (9.1 vs 6.8 months, P =0.19). In the t-ALL (n=8) cohort, all of them received lenalidomide based induction and five received lenalidomide maintenance. Most of the t-ALL patients had adverse risk cytogenetics [IKZF1 deletion (n=2), complex karyotype (n=2), TP53 mutation (n=1) and P2RY8-CRLF2 fusion (n=1)]. Three patients with t-ALL underwent allo-SCT and the median OS for allo-SCT recipients versus non recipients were 8.3 vs 7.9 months respectively, P=0.50. Among patients with SHM, 92.3% (n = 96) have died with SHM (72%) being the most common cause of death. MM patients who developed SHM had an inferior OS when compared to those without SHM (median OS, 75 vs 90 months, P =0.006). Conclusion: SHM following auto-SCT tends to have aggressive disease biology with poor outcomes. Short term follow up underestimates the risk of SHM and the higher incidence noted in our study may be due to longer follow up. As the OS in MM patients continues to improve, SHM remains an important challenge in improving long term outcomes.

Mutations in genes that code for RAS isozymes (N- and K-) are the most common (40-50%) somatic variations in multiple myeloma (MM). While ~46% of patients with newly diagnosed MM carry a RAS/Raf mutation, >64% of patients with refractory/relapsed MM carry these mutations. RAS activation can also occur from upstream signaling through receptor tyrosine kinases (RTK) or loss-of-function mutations in GTPase-activating proteins (GAPs), which are prevalent in MM. Although covalent inhibitors targeting KRAS alleles are in various stages of clinical development, multiple mechanisms of resistance have been reported. We discovered and developed a novel, highly potent, and selective pan-RAS inhibitor, ADT-007, capable of suppressing MAPK/AKT signaling by blocking GTP activation of RAS. Here, we show that ADT-007 is effective against MM, particularly those MM cell lines harboring KRAS and NRAS mutations that are representative of relapsed/refractory myeloma (RRMM). For these studies, we compiled a panel of over 50 human myeloma cell lines (HMCLs) with broad biological and genetic heterogeneity that represent innate drug-response/resistance (refractory disease), as well as 10 pairs of parental and clonally-derived proteasome inhibitor (PI)- and immunomodulatory drug (IMD)- resistant HMCLs as models of acquired resistance (relapse). Using CRISPR-cas-directed gene editing, we also have generated clonal NRAS and KRAS mutants of drug-sensitive myeloma lines that initially had two wild-type alleles. All cell lines have been authenticated using the GenePrint 24 System and tested for mycoplasma contamination. First, we performed predictive analysis using single-cell RNA sequencing (scRNAseq; 10X Genomics) on all MM cell lines and demonstrated the potential efficacy of ADT-007 based on the subclonal expression of the target genes/pathways. Using in vitro chemosensitivity assays, ADT-007 was highly potent and effective in killing chemo-resistant and RAS-mutant myeloma cells as a single agent with IC50 values ranging from 0.76 to 12 nM with synergistic benefits if combined with PIs and IMDs. Combination indices (CI) were found to be consistently below 0.9, indicating a synergistic drug interaction. (Drug synergy was determined by CalcuSyn software based on Chou-Talalay's CI method and the isobologram algorithm). Caspase 3/7 assay and flow cytometry (Annexin V-FITC + propidium iodide) confirmed apoptosis induction by ADT-007. Furthermore, the in vitro efficacy of ADT-007 was significantly better (nM vs. µM IC50) than cyclorasin B4-27, a bicyclic peptidyl that has been reported as a potent pan-RAS inhibitor against several other cancers, and RMC-6236, a multi-selective noncovalent RAS(on) inhibitor which is in clinical trial for patients with advanced solid tumors harboring G12X, G13X, and Q61X mutations. Pre-vs-post-treatment bulk-RNA sequencing followed by pathway analysis (using Ingenuity Pathway Analysis and Gene Set Enrichment Analysis) showed that ADT-007 suppressed KRAS and NRAS in a dose-dependent manner. Immunoblotting analysis confirmed the dose-dependent reduction of protein markers implicated in cell survival and chemotherapeutic resistance in myeloma, including c-myc, Ki-67, NFkB, IRF4, IKZF1 (Ikaros) and IKZF3 (Aiolos). Finally, we performed pre-vs-post-treatment single-cell transcriptomics analysis, which revealed a distinct shift in clusters representing myeloma single-cell subpopulations following ADT-007 treatment. High-dimensional mass cytometry (cytometry by time of flight or CyTOF) analysis using heavy metal-conjugated proteins in RRMM patient bone marrow-derived primary myeloma cells is currently underway to confirm the cytotoxic effect of ADT-007 ex vivo. ADT-1004 is an orally bioavailable prodrug of ADT-007 designed to improve water solubility and metabolic stability. ADT-1004 has shown strong antitumor activity in highly aggressive and clinically relevant mouse models of pancreatic cancer at dosages, is well tolerated, and is being developed by the NCI Stepping Stones program. Next, we plan to evaluate the antitumor activity of ADT-1004 in mouse xenograft models of human myeloma using immunocompromised mice. Our research will lay the groundwork for future development efforts needed to advance ADT-1004 to clinical trials involving patients with RRMM.

Background: Beside fibril-forming proteins, amyloid deposits contain other proteins which can influence organ toxicity, disease initiation and clearance. We investigated the association between the amyloid plaque proteomic signature of diagnostic renal biopsies from patients achieving deep and sustained hematologic remissions and renal organ response in AL amyloidosis. Methods: Retrospective study of newly diagnosed AL amyloidosis patients between 2010-2020. Patients were eligible if; (1) they had a baseline renal biopsy which had undergone laser micro-dissection and mass spectrometry, (2) were assessable for renal response [RenR, non-selective proteinuria ≥1g /24 hours, predominantly albumin], (3) were not on renal replacement therapy and did not experience renal progression within 3-months of diagnosis and (4) had RenR measurements, at least twice annually in the first year from treatment and annually thereafter. Patients who did not obtain a renal complete response (RenCR) required a hematologic very good partial response (VGPR) or better within 6 months of treatment initiation, sustained for a minimum of 6 months. Hematological and renal responses were graded according to consensus criteria. Overrepresentation analyses of differentially expressed proteins were performed using the WebGestalt 2019 and the reactome pathway database. A false detection rate corrected p value <0.05 was used to identify significantly overrepresented proteins and pathways. Results: We defined two organ response categories, to capture the extreme ends of the spectrum: renal suboptimal responders (n=24), patients for whom the best renal response was ≤partial response (RenPR), and renal complete responders (n=29), patients who obtained a RenCR at best response. Overall, the median follow-up was 6.7 years (IQR: 5.4-9.2), 6.6 years (IQR: 5.4-8.1) for complete responders, and 8.4 years (IQR: 6.1-11.3) for suboptimal responders. Between renal suboptimal responders and complete responders there was no significant difference in median age (63 vs 63 years, p=0.7), lambda light chain isotype (66% vs 79%, p=0.3), first-line therapy received and renal stage (Stage III: 14% vs 8%, p=0.9). The median time to RenCR was 52-months (IQR: 31-63). Protein pathways over-represented in renal complete responders included 14-3-3 proteins (YWHAG, YWHAH, YWHAQ, YWHAZ), early components of the complement cascade and complement regulatory proteins (C3, C4A, C4B, C8A, complement factor H), keratins, cytoskeletal proteins (tubulin, actin, filamen) and collagen IV. Protein pathways over-represented in renal suboptimal responders included terminal/effector components of the complement cascade (C5, C6, C8B, C9), amyloid signature proteins (ApoA1 and E, vitronectin, clusterin), proteoglycans (heparan sulfate proteoglycan), transgelin and metallopeptidase inhibitor 3. Proteins with the highest-fold increase in renal complete responders included serine protease inhibitor (SERPINA3) and F-box and leucine rich repeat protein (FBXL6), 9.0 x 106 & 7.7-fold, respectively. Proteins with the highest-fold increase in renal suboptimal responders included complement 6 and 8B, 3.5 & 3.6-fold, respectively. Conclusion: This is the first study to identify proteomic determinants of organ response in AL amyloidosis. Molecular chaperones involved in protein aggregate homeostasis, such as the 14-3-3 proteins are upregulated in renal complete responders, similar to what we have shown in our prior work. This suggests that organ responders may have a more favorable microenvironment which “primes” them for organ response after the amyloidogenic light chain has been cleared from the circulation. Renal suboptimal responders (≤RenPR) have elevated levels of terminal complement proteins including membrane attack complex proteins and reduced levels of early components or complement regulatory proteins, which may be responsible for reno-toxic and reno-protective effects, respectively.

Introduction: Light chain (AL) amyloidosis is a clonal plasma cell disorder characterized by tissue deposition of misfolded immunoglobulin light chains in the form of amyloid, leading to organ dysfunction. Halting the production of the amyloidogenic free light chains by achieving a deep hematologic response (HemR) is key to improving organ function, however, variation in organ responses exists. In this work, we investigated variables associated with liver response (LivR) in a large cohort of patients with AL amyloidosis. Methods: Retrospective study of newly diagnosed AL amyloidosis patients with liver involvement seen at Mayo Clinic within 90 days of diagnosis between January 2000 and December 2021. Patients were eligible if they (1) had liver involvement, defined as a baseline alkaline phosphatase (ALP) ≥ 1.5 x upper limit of normal (ULN) and (2) had LivR measurements at least twice annually in the first year from treatment and annually afterward. LivR was defined as a >50% reduction in alkaline phosphatase (ALP) from baseline value or normalization of ALP. LivR was recorded at 6, 12, and 24 months from treatment initiation and at the best LivR achieved. Patients who died prior to landmark assessment were considered non-responders at subsequent milestone assessments. Covariates associated with LivR were identified by univariate and multivariable logistic regression analyses and a proportional subdistribution hazard (Fine-Gray) model for competing risk (treating death as a competing event). Multivariable logistic regression models for LivR were created using best subset selection, with calculation of odds ratio (OR) and 95% confidence interval (CI). Results: A total of 130 patients were included, with a median age of 60 years (IQR 53-66), male predominance (69%), and a median follow-up of 8.8 years. Sixty percent of patients had lambda isotype, the median ALP was 368 IU/mL (IQR 279-589), with 48% of patients having ALP ≥3 fold the upper limit of normal (ULN). Median bilirubin was 0.7 mg/dL (IQR 0.5-1.1). Forty-three percent of patients received front-line autologous stem cell transplant (ASCT) with or without prior induction therapy, and 5% received daratumumab-based therapy as their front-line treatment. Liver response rate increased with time, with 36 patients (28%) achieving a LivR at 6 months, 47 (36%) at 12 months, 63 (48%) at 24 months, and 94 (72%) at best response. The median time to liver response was 14 months (7.22-32.67). At the 24-month landmark, age <60 years, ALP ≥3 fold ULN, and front-line ASCT were significantly associated with achieving a LivR on univariate logistic regression. On univariate logistic regression at best liver response, age <60 years, ALP ≥3 fold the ULN, kappa isotype, ≥HemVGPR within 6 months, and front-line ASCT were significantly associated with obtaining a LivR. On multivariable logistic regression, at 24 months, ALP ≥3 folds of ULN (OR=2.9, 95% CI 1.4-6.3, P=0.004) was significantly associated with an increased likelihood of LivR. Achieving ≥HemVGPR and front-line ASCT were also associated with increased LivR likelihood, although not statistically significant (p=0.094, p=0.078, respectively). At best liver response, achieving ≥HemVGPR within 6 months (OR=5.2, 95% CI 1.9-14.8), kappa isotype (OR=3.2, 95% CI 1.1-10.0), ALP ≥3 folds of ULN (OR=3.3, 95% CI 1.3-9.9), and front-line ASCT (OR=5.3, 95% CI 1.9-16.7) were factors significantly associated with LivR. The Fine-Gray model demonstrated kappa isotype (HR=1.7), baseline ALP ≥3 folds of ULN (HR=2.1), ≥HemVGPR within 6 months (HR=1.9), and age <60 years at diagnosis (HR=1.9) to be positively associated with achieving LivR (P<0.05). Conclusions: In this large cohort of liver AL amyloidosis, LivR was achieved in 72% of patients, and amongst responders, the median time to response was 14 months from therapy initiation. Predictors of LivR included kappa isotype, deep hematological response in the first 6 months of initial therapy, ASCT usage, and higher baseline ALP levels. These findings better inform clinicians on the likelihood of achievement of liver response and may enable ways to improve its achievement.

Background: AL amyloidosis is a potentially fatal plasma cell dyscrasia. In a randomized phase 3 study (Kastritis E et al, NEJM 2021;385:46-58), the addition of daratumumab to cyclophosphamide, bortezomib and dexamethasone (Dara-CyBorD) significantly improved hematological and organ responses, and prolonged event-free survival (EFS). There was no overall survival (OS) difference at a median follow-up of 11.4 months. Methods: A retrospective study of AL amyloidosis patients seen at our institution between January 2018 and December 2022 who received upfront Dara-CyBorD or CyBorD. We excluded patients who received other forms of upfront therapy (including modifications of the above regimens, such as bortezomib-dexamethasone or daratumumab-dexamethasone). We compared the hematologic and organ responses, EFS and OS between the two treatment groups. Hematologic response was assessed at 2 and 6 months from therapy initiation, while cardiac and renal responses at 6- and 12-month landmarks. In all response evaluations, we included responses up to autologous stem cell transplantation (ASCT) if used or second-line therapy for any reason. For EFS analysis, an event was defined as death of any cause, hematological progression, end-stage cardiac or renal failure, or need for subsequent anti-plasma cell therapy in the absence of hematological progression. OS was calculated from the time of treatment initiation to death or last follow-up. Results: Among 641 newly diagnosed patients seen at our center between 2018 and 2022, 361 patients (56%) were included on intention-to-treat analysis [Dara-CyBorD =147 (41% of the cohort); CyBorD=214 (59%)]. There was no difference in the baseline characteristics between the treatment groups, including age, sex, difference between involved and uninvolved light chains, bone marrow plasma cells percentage, NT-proBNP and 24-hour proteinuria. The 2-month hematologic complete response (hemCR; 15.3% vs 4.4%, P<0.001) and very good partial response or better (≥hemVGPR; 62.2% vs 32.5%, respectively; P<0.001) were higher with Dara-CyBorD compared to CyBorD. At 6 months, the hemCR and ≥hemVGPR were again in favor of the Dara-CyBorD group compared to CyBorD (32.0% vs 13.7%, and 72.8% vs 46.7%, respectively; P≤0.002). The 6- and 12-month cardiac response rate in the Dara-CyBorD and CyBorD groups were 40.2% vs 22.6% (P=0.01) and 44.1% vs 23.2%, respectively (P=0.006). Cardiac ≥VGPR at the 6- and 12-month landmarks were statistically higher with Dara-CyBorD compared to CyBorD and increased in both arms between 6 and 12 months [20.5 % vs 9.3% (P=0.03) and 34.3 % vs 20.0% (P=0.04), respectively]. The 6-month and 12-month renal response to first-line therapy were numerically higher with Dara-CyBorD compared to CyBorD but were not statistically significant (48% vs 31.3%, P=0.10; 54.1% vs 30.1%, P=0.05). The 6 month and 12 months, renal ≥VGPR were numerically higher with Dara-CyBorD compared to CyBorD, again without statistical significance (26% vs 19.6%, P=0.63; 35.7% vs 17.2%, P=0.11, respectively). Treatment with Dara-CyBorD was significantly associated with lower 6-month mortality rate compared to CyBorD (8.8% vs 16.3%, P=0.04). With a median follow-up of 43.3 months (30 vs 59.4 months for Dara-CyBorD vs CyBorD, respectively; P<0.001), the two-year EFS was superior in the Dara-CyBorD group compared to CyBorD (69.1% vs 30.3%, hazard ratio (HR) 0.36, 95% confidence interval (CI), 0.26 to 0.48, P<0.001). The 2-year OS was also statistically higher in the Dara-CyBorD group compared to CyBorD (82.0% vs 69.6%, HR 0.53, 95% CI, 0.36 to 0.79, P=0.003). 148 patients (40.9%) proceeded to second-line therapy with a median of 5.1 months from first line therapy. To adjust for difference in follow-up time between the two treatment groups, we analyzed the second line therapy utilization at the 12-month mark which was statistically higher with CyBorD compared to Dara-CyBorD (42.9% vs 14.9%, P<0.001). Also, at 12 months, a higher proportion of patients treated with CyBorD received ASCT compared to Dara-CyBorD (24.3% vs 13.6%, P= 0.01). Conclusions: In this cohort of newly diagnosed AL amyloidosis patients in a large referral center, we confirmed higher hematological and organ response rates with Dara-CyBorD compared to CyBorD. We have also demonstrated that these higher response rates translate into a survival advantage of Dara-CyBorD over CyBorD.

Introduction The tumor ecosystem in multiple myeloma (MM) involves complex interactions among various cell types, including clonal plasma cells (PCs) and immune cells. Previous research has indicated that the bone marrow (BM) microenvironment's metabolite and lipid profiles differ between MM patients and those with precursor conditions. This study aims to explore if differences in cell composition, metabolic phenotype of clonal PCs, and the spatial organization of various cell types are linked to the early versus late progression of high-risk smoldering MM (SMM) to MM. Methods We identified high-risk SMM patients using the IMWG 20-2-20 criteria, focusing on early progressors (EP), who progressed to MM within one year, and later progressors (LP), who progressed after more than four years. Using a high-dimensional single-cell spatial imaging platform, CODEX (CO-Detection by indEXing), we identified clonal PCs and immune cell types as well as their metabolic phenotypes at the single-cell level, in paired FFPE BM samples at SMM diagnosis and at the time of progression to MM. Our validated panel included markers such as CD3e, CD4, CD8, CD14, CD20, CD31, CD38, CD45, CD66a, CD68, CD138, HLA-DR, ASCT2, pNRF2, GLUT1, LDHA, ATPA5, CPT1A, and Citrate synthase. We employed single-cell segmentation, artifact cleanup, signal thresholding, and spatial analysis. Repeated measure models accommodated multiple regions of interest (ROIs) per patient and accounted for potential intrapatient correlation, while Poisson models estimated incidence rate ratios (RR) of cell types. Spatial statistical models evaluated cell type segregation and integration at the time of SMM diagnosis. Results Single cell events were acquired from 6 unique SMM patients who had paired FFPE BM samples from the time of their SMM diagnosis and at the time of their progression to MM. There were 3 EP SMM patients (Time to Progression (TTP):8, 8, 10 mos) and 3 LP SMM patients (TTP: 51, 58, 117 mos). The median number of single cell events identified per patient slide sample was 104,390 (Range: 24,357 - 314,877). We identified 8 main cell types: PCs, CD4+ T-cells, CD8+ T-cells, B-cells, granulocytes, Monocyte/Macrophages and two groups of other immune cells. The PCs and the remainder of the non-PCs were further classified based on the expression of the following metabolic markers: ASCT2 (Glutamine importer), CPT1A (Fatty acid metabolism), GLUT1 (Glucose importer), LDHA (Glycolysis), Citrate synthase and ATPA5 (Oxidative Phosphorylation). There was a higher RR of granulocytes (RR 2.1, CI 1.6-2.8, p<0.001) in EP compared to LP samples at the time of SMM diagnosis, but a lower RR of CD4 T cells (RR 0.40, CI 0.3-0.6, p< 0.001). Focusing on metabolic phenotypes of the PCs, we observed higher incidence RR of most metabolic markers: ASCT2 (RR=1.77; p=0.032), ATPA5 (RR=1.25; p<0.001), CPT1a (RR=2.42; p=0.015), and LDHA (RR 2.13; p<0.001) in EP compared to LP samples at the time of SMM diagnosis. However, GLUT1 had a lower incidence RR in EP patients (RR=0.79; p<0.001). The same modeling for non-PCs at the time of SMM diagnosis yielded higher expression of LDHA (RR=1.98; p<0.001) and ASCT2 (RR=3.3; p=0.002). Using the x and y coordinates and the corresponding phenotype classifications, we performed spatial statistical modeling based on spatial point processes to generate aggregated measures of how different types of cells of interest interacted. CD4 T cells were more isolated in LPs compared to EPs (p =0.046). Segregation indices for PCs and CD4 T cells indicated that they were more integrated/collocated in EPs. Granulocytes were more isolated in EPs although the difference was not as pronounced (p= 0.07). PCs were more integrated with granulocytes (p=0.06) and B cells (p=0.07) in LP patients. Further analyses of paired samples at the time of progression to MM will be reported at the time of the presentation. Conclusion This study is the first to provide whole-slide, single-cell, spatial proteomic characterization of clonal PCs and immune cells in the FFPE BMs of high-risk SMM patients with varying progression times to MM. Distinct metabolic pathway markers in clonal PCs and their spatial relationships with immune cell subsets are closely associated with the risk of progression to MM. These findings illuminate the complex interactions between the metabolic states of clonal PCs and their spatial orientation relative to immune cells in the pathogenesis of MM.

In 2023, Mayo Clinic in Rochester, MN, cared for over 20,000 patients with hematologic malignancies, roughly 42% of whom were rural. Patients residing in rural areas can face challenges in access to care, financial and time burdens due to treatment-related travel, and limited opportunities to participate in clinical trials. In 2021, The Leukemia & Lymphoma Society launched its IMPACT (Influential Medicine Providing Access to Clinical Trials) grant with Mayo Clinic being among its first recipients. The program provides funding to major cancer centers, in partnership with local community oncology centers, to help increase participation of patients traditionally underrepresented in clinical trials, including those who are rural, minority and/or economically disadvantaged. The award allowed significant changes to be made to clinical trial selection and facilitation models increasing access to trials within the rural setting and reducing the socioeconomic barriers noted above. This program included Rochester (IMPACT Hub) and Mayo Clinic Health System (MCHS) sites in Albert Lea, MN (65 miles to Hub), Eau Claire, WI (96 miles to hub), La Crosse, WI (73 miles to Hub), and Mankato, MN (84 miles to Hub). Methods: Two models were deployed; the full activation model where clinical trials were fully opened at MCHS sites, and the hybrid model where clinical trial participants are consented at the Hub and portions of participant care are conducted at MCHS sites. Initial barriers included limitations in clinical trials support staff, insufficient specimen processing equipment, medication storage and shipping limitations, MCHS catchment population unalignment with the Hub trials portfolio, and reduced bandwidth of providers due to patient care responsibilities. To address barriers to trial conduct, community center site champions were identified to streamline trial review and increase collaboration to better define site catchment areas, trial constraints, and site needs. A feasibility specialist was hired to support the program in trial design/implementation, barrier tracking, and to serve as a liaison between community site providers, study staff, and the program. Results: Since 2021, 20 clinical studies including 14 interventional treatment trials have been activated demonstrating 108 total patients accrued with 42 interventional accruals; 5 within the full activation model (13 accruals) and 15 in the hybrid model (29 accruals). Patients showed an average of 216 miles, with an estimated mileage cost of $142/trip based on the 2023 IRS mileage rate of $0.655/mile to the hub location. Nine of those patients traveled over 260 miles, with an estimated mileage cost of $170/visit to access clinical trials. Under the hybrid model, 8 patients transitioned portions of their care to their home city resulting in reduction of an average of 155 miles/visit, and 7 patients were able to reduce their travel time an average of 216 miles/visit. By estimating at least 10 study visits, the travel burden was reduced by 2,160 miles (4320 driving hours) and $1,420 in driving costs alone for participants. Using participant averages the 108 patients would spend a total of $15,336 in travel costs for just the initial visit, but when factoring in the 10-visit estimate, travel reduction could result in a net savings of $153,360. Based on travel data, it is estimated 11 of these patients would have required overnight accommodation using an average of $149/night hotel stay, a savings of $1,490/patient is estimated for the lifecycle of trial participation or $16,390 for the 11-patient cohort requiring accommodation. These results do not include travel companion and time off work costs. Efforts have been made to further develop the full activation model and 5 clinical trials are in activation. Data gathered from the program is being used to design strategies to reduce the administrative burden of clinical trial participation for community providers and launch screening programs. Conclusion: The Mayo Clinic LLS IMPACT program has demonstrated success in addressing barriers to opening clinical trials in the community-center setting and reduced the travel burden and financial impact to clinical trial participation in a cohort of trial participants. Centralized hub support of study activation and conduct and decentralized care to support treatment of patients in proximity of their home can be extended to other hospital systems and settings.

Background Multiple myeloma (MM) is a hematological cancer characterized by the proliferation of plasma cells (PC). Progressive disease (PD) criteria are primarily characterized by an increase in (1) serum M-protein (SPEP), (2) urinary M-protein (UPEP), (3) serum free light chains (sFLC), or (4) PC percentage in the bone marrow. An essential aspect of the PD criteria is the requirement for confirmatory results from blood or urine analyses. However, in many cases, patients may be taken off treatment in favor of a new therapy after only one assessment. This can introduce clinical trial endpoint inaccuracies when confirmatory values are missing, resulting in increased censoring and underestimation of the progression rate (if the second assessment is not done). Moreover, in subjects with high tumor burden and rapidly progressing disease, it is often urgent to confirm PD before starting a subsequent line of treatment. This study assessed the necessity of repeating biomarkers to confirm PD if two biomarkers meet the progression criteria. Methods In this retrospective study, between 2002 and 2020, we assessed all consecutive patients with relapsed MM enrolled in any therapeutic clinical trial at Mayo Clinic. We included patients with measurable disease if SPEP and sFLC were available at the time of assessment. Patients required at least two consecutive assessments (by the same method) to be included in our study. PD was based on the IMWG criteria. Relapse characterized by the development of new bone lesions or extramedullary relapse without meeting biochemical progression criteria was an exclusion criterion. Patients starting a new line of treatment after non-confirmed PD were also excluded. Furthermore, patients who did not meet simultaneous progression criteria and had unconfirmed PD (did not meet IMWG criteria at the second assessment) were excluded from the analysis (n=15). The probability of meeting the progression threshold with 1 and 2 consecutive assessments was calculated. We then examined the proportions of patients meeting PD by 2 biomarkers simultaneously at the first assessment. Results We evaluated episodes of treatment among 434 patients enrolled in clinical trials, including 601 episodes: 593 episodes of biochemical confirmed PD and 8 episodes when patients did not progress but who met simultaneous progression criteria at the same time with two different biomarkers. Per measurable disease criteria, MM isotypes were 71.0% IgG, 16.8% IgA, 0.9% IgM, 1.2% IgD, 0.3% biclonal, and 9.8% light chain. According to the standard IMWG response criteria (sequential criteria), 78% and 9% of episodes reached the progression threshold with serum and urine M-components, respectively, with two consecutive assessments. For the FLC, 21% of episodes met the progression criteria. No patients had a second bone marrow examination for confirmation of PD. At the first available assessment, 82%, 19%, and 2% of episodes met progression threshold, respectively, with serum M-protein, urine M-protein, and both (serum + urine M-protein). Additionally, 58%, and 19%, episodes met the progression threshold at the first assessment with FLC and bone marrow examination, respectively. Moreover, 67% of patients with IgA myeloma meet the progression threshold with the total quantitative IgA. With the simultaneous criteria at time of first assessment, 403 episodes meet progression threshold: 45% with SPEP+sFLC (n=269/593), 4% with SPEP+UPEP (n=21/593), 9% with sFLC+UPEP (n=55/593), 11% with BME only (n=66/593), and 0.3% with qIgA +dFLC/UPEP (n=2/593). Thus, among these 413 episodes, which meet progression criteria by 2 simultaneous values at the time of the first assessment, 98% (n=413/(413+8)) of these patients (positive predictive value of the new criteria) subsequently had confirmed progression by sequential value. Conclusions In summary, we showed that the simultaneous criteria allow to identify patients with true progressive disease without overestimating the progression rate of myeloma. Therefore, confirmatory results of progression for relapsed MM patients having two biomarkers meeting criteria of progression at the same time is useless for determining disease progression.

Introduction: Multiple myeloma (MM) with t(11;14)(q13;q32), resulting in CCND1;IGH rearrangement, remains the only subset amenable to targeted therapy with the BCL2 inhibitor, Venetoclax. Nevertheless, not all patients with this translocation respond to treatment and some progress early after initial response. The mechanisms behind this clinical heterogeneity are largely unknown. Methods: To investigate mechanisms of heterogeneity in response to Venetoclax, we interrogated 44 whole genome sequencing (WGS) and 24 whole exome sequencing data from a training cohort including 33 patients with t(11;14) MM treated with Venetoclax at the Mayo Clinic. In a validation cohort, we extracted single nucleotide variants (SNV) and indels from 17 MM patients with t(11;14) with available RNAseq data treated with Venetoclax at Emory University. Results: In the training cohort the median number of lines of therapy was 4 and Venetoclax drug regimens included combinations with dexamethasone, proteasome inhibitors, anti-CD38 agents, and immunomodulatory agents. After a median follow up of 30 months, the median progression free survival (PFS) was 9 months, and 13 patients (39%) achieved a complete remission (CR) to therapy, while 9 (27%) were refractory (i.e. no response or progressed within the first 60 days). For our driver discovery analysis, we integrated SNV, indels, copy number variants (CNV) and structural variants (SV). Deletion 17p (del17p) or TP53 mutation, MCL1 gain/amp, and hyper-APOBEC did not correlate with PFS in our cohort (p=0.59, p=0.71, and p=0.05, respectively). In contrast, mutations involving the MAPK pathway (NRAS, KRAS, BRAF, FGFR3) displayed the strongest association with short PFS, which was retained after adjusting for del17p/TP53 mutations, and 1q gain/amp (HR: 4.76, CI: 1.8-12.9, p=0.002). The association between suboptimal response and resistance to Venetoclax in MM patients with MAPK pathway mutations (n=7) was also observed in our validation cohort from Emory University (p=0.046). This is in line with what has been reported in functional studies in acute myeloid leukemia, where RAS pathway promotes MCL1 under the selective pressure of Venetoclax (Zhang et al. Signal Transduct Target Ther 2022). While MAPK mutations explained most cases of refractory patients (86%), the mechanisms through which initially responding patients subsequently progressed remain unclear. To investigate this, we interrogated 10 patients with pre- and post-treatment samples collected at disease progression (PD). We identified genomic events acquired/selected at PD of genes involved in the anti-apoptotic MCL1/BCL2 and MAPK pathways in 6/10 cases. One patient was refractory to Venetoclax and had double minutes involving BCL2, which caused multiple focal amplifications (>30 copies), likely reflecting extrachromosomal DNA. Another patient progressed with an acquired, focal deletion on BCL2L11. In two patients, the progressing clones harbored mutations in MAPK pathways (one BRAF and the other WNK2). Two patients who relapsed after sustained CR had major branching evolution where a previously undetectable focal deletion of PMAIP1 (NOXA) was seen at PD. Importantly, one of these deletions was a biallelic event. Venetoclax sensitivity assays conducted on PMAIP1 knockout in the MM t(11;14) cell line, KMS12PE, demonstrated significantly reduced cell death across all drug concentrations (p<0.05), validating the loss of NOXA as a mechanism of resistance to Venetoclax in MM. Finally, similarly with what was previously reported in chronic lymphocyte leukemia treated with Venetoclax (e.g., Herling et al Nat Comm 2018), CDKN2A/B monoallelic and biallelic focal deletions were selected post-Venetoclax, at PD in 4 patients while TP53 SNV/deletions were selected from subclonal to clonal in 2 patients at PD. Conclusion: In this study, we demonstrate that mutations involving the MAPK pathway identify a population of MM patients with t(11;14)(CCND1;IGH) who are unlikely to respond to Venetoclax. We also show that genomic events involving the MAPK and BCL2/MCL1 pathways are primarily responsible for disease progression after initial response. These findings highlight the critical role of comprehensive genomic profiling through WGS in identifying mechanisms of resistance to targeted therapies in MM, aiding patient selection for Venetoclax, and guiding the development of novel drug combinations.