Carpten, John D.

Abstract Background: Multiple myeloma is the second most common adult blood cancer and remains incurable, despite recent advances. The IMWG/IMS recently published updated risk criteria, Consensus Genomic Staging (CGS), combining genomic events with clinical measures to identify high-risk patients (Avet-Loiseau, et al. JCO 2025). We applied CGS risk criteria to baseline samples from the Multiple Myeloma Research Foundation CoMMpass Study (NCT01454297), a prospective, longitudinal observational study that enrolled more than1100 participants between 2011-2017. Methods: We assessed patient risk following CGS criteria. Criteria 1: del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation. Criteria 2: an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32). Criteria 3: monoallelic del(1p32) along with 1q+ or biallelic del(1p32). Criteria 4: beta-2 microglobulin >= 5.5 mg/L with normal creatinine. Patients meeting one or more criteria were classified as High Risk. To test if risk showed association with genetic ancestry, we grouped patients into those with high African genetic ancestry and those with low African genetic ancestry. Genetic ancestry was measured using ADMIXTURE in comparison to 1000 Genomes. Results: We evaluated the CGS risk status of 877 CoMMpass patients, finding 69.2% (573/828) to be Standard Risk (SR) and 30.8% (255/828) to be High Risk (HR). HR patients showed worse progression-free survival (median PFS 26.3 months vs. 42.5 months; log rank test, p < 0.0001) and overall survival (median OS 63.9 months vs. median not reached; p < 0.0001). 10.6% (91/858) of patients met Criteria 1, 10.7% (93/873) met Criteria 2, 5.6% (49/877) met Criteria 3, and 8.7% (73/835) met Criteria 4. We found 14.2% (123/867) of patients to have high African-like genetic ancestry (AFR-high) and 85.8% (744/867) to have low African-like genetic ancestry (AFR-low). We observed significantly fewer HR patients within the AFR-high group (20%, 23/115) than in the AFR-low group (32.4%, 231/712) (Fisher’s exact test, p = 0.0065). The AFR-high group met HR criteria at a lower rate across all criteria, but only with Criteria 3 was the difference significant (p-value = 0.03). Higher levels of creatinine in AFR-high patients may have impacted meeting the normal creatinine requirement of Criteria 4. Conclusions: HR patients comprise 30.8% of CoMMpass subjects and show significantly worse PFS and OS than SR patients. AFR-high patients met HR criteria at a lower rate than AFR-low patients according to the CGS criteria. Clinical trials that utilize CGS criteria to determine patient eligibility may be challenged to enroll a representative patient population, including AFR-high patients. Screening and eligibility criteria should be carefully considered to mitigate potential enrollment disparities. Citation Format: Steven M. Foltz, Chaitanya R. Acharya, Alexander Gout, Yuxin Jin, David E. Avigan, Ravi Vij, Shaji Kunnathu Kumar, Sagar Lonial, Hearn Cho, Katie Wozniak, Jonathan J. Keats, Craig Cole, John D. Carpten, George J. Mulligan. Multiple myeloma risk classification of CoMMpass using Consensus Genomic Staging identifies differences between patients with high and low African genetic ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3887.

Objectives Black/African American (B/AA) pancreatic ductal adenocarcinoma (PDAC) patients have worse clinical outcomes than White patients and are underrepresented in genomic databases. We aimed to expand our understanding of the PDAC somatic landscape from a diverse cohort. Materials and Methods Formalin-fixed paraffin-embedded specimens from 24 surgically resected PDAC cases were collected, with self-reported race/ethnicity. Whole exome sequencing was performed on malignant and benign tissue. Bioinformatics analysis included deduction of genetic ancestry and somatic mutational analysis, with comparisons to public datasets. Results Out of 24 cases, 17 identified as B/AA race; genetic ancestry analysis confirmed proportions of Sub-Saharan African ancestry greater than 47%. The most commonly mutated genes included KRAS , TP53 , SMAD4 , and CDKN2A . Comparison of mutations in our cohort versus publicly available, predominantly White datasets showed higher mutation frequencies of ATM, RREB1, BRCA1/2, KDM6A, ARID1A, BRAF, and MYC ( P < 0.04). When cohorts were combined and analyzed by race, no mutation frequencies differences were observed, including KRAS . Conclusions Genomic analysis of PDAC tumors from B/AA and White patients demonstrate similarities in mutation frequencies. Larger studies are needed to further understand molecular characterizations across continental subpopulations. This study provides further rationale for equitable representation of diverse patients in genomic databases and clinical trials.

Introduction: HIV-associated diffuse large B-cell lymphoma (HIV-DLBCL) is a significant complication in HIV-positive individuals, presenting unique clinical challenges and a poorer prognosis compared to patients with de novo DLBCL. Epstein-Barr Virus (EBV) status is a critical factor influencing the pathogenesis, clinical behavior, and therapeutic responses in these lymphomas. Plasmablastic lymphomas (PBL) have shared some overlapping genomic abnormalities with HIV-DLBCL including MYC rearrangements. This study aims to elucidate the differences in the genetic profiles and pathway activations between EBV(+) and EBV(-) HIV-DLBCL through comprehensive genomic profiling. Methods: Cases of DLBCL were identified in patients living with HIV from a multi-institute cooperative group. Cases of Burkitt lymphoma and PBL were excluded. We performed whole exome sequencing (WES) on 106 tumors of HIV-DLBCL and RNA sequencing on 39 tumors and mapped the reads to hg38 reference genome using BWA and STAR, respectively. EBV status of cases was determined by in situ hybridization and/or reads mapped on EBV genome in sequencing data. Somatic mutations were identified using variant callers (Strelka2, Mutect2) with WES data. For those mutated genes in COSMIC, allele frequency cutoff was set at 0.03. Mutations with an artifact score larger than 0.7 in SOBDetector and those located in segmental duplications were further removed. They were annotated with Ensembl Variant Effect Predictor, manually checked, and plotted with maftools. RNAseq read counts aligned to each gene were obtained by featureCounts and DEseq2 was used for differential expression (DE) analysis between EBV positive and negative groups. Pathway analysis with the DE genes was performed using GSEA. FISH analysis was performed using MYC, BCL2, and BCL6 break-apart probes. Results: There were 41 cases of EBV(+) HIV-DLBCL and 65 cases of EBV(-) HIV-DLBCL. FISH of EBV(+) HIV-DLBCL identified 42% (3/7) with MYC rearrangement (MYCr), none with BCL2 rearrangements (BCL2r) (0/6), and 33% (2/6) positive for BCL6 rearrangement (BCL6r) with 1 tumor having a MYCr/BCL6r. For EBV(-) HIV-DLBCL, there were 35% with a MYCr (6/17), 18% with BCL2r (2/11), and 27% with a BCL6r (3/11) with 2 tumors with MYCr/BCL6r, and 1 tumor with MYCr/BCL2r/BCL6r. The most frequent mutations seen in EBV(+) HIV-DLBCL were STAT3 (32%), DDX3X (22%), and TP53 (15%). For EBV(-) HIV-DLBCL, the most frequent mutations were KMT2D (25%), TP53 (23%), GNA13 (22%), and TET2 (22%). Pathways that were most commonly associated with EBV(+) HIV-DLBCL were JAK/STAT (42%) (STAT3, JAK1) and NF-kB (39%)(DDX3X, TNFAIP3) while EBV(-) HIV-DLBCL was associated with epigenetic modifiers (62%)(KMT2D, TET2, EP300), JAK/STAT (45%)(SOCS1, JAK3) and PI3K/mTOR (40%)(GNA13, MTOR). Significant disparities between EBV(+) and EBV(-) were KMT2D (24% vs 50%, P=0.0025), TET2 (10% vs 26%, P=0.008), SOCS1 (29% vs 39%, P=0.04), DDX3X (15% vs 5%, P=0.03), and GNA13 (5% vs 24%, P=0.001). RAS mutations (KRAS, NRAS) were infrequent in HIV-DLBCL (EBV(+), 12%; EBV(-), 6%), in contrast to prior studies of PBL. Gene expression profiling showed enrichment of MYC targets, oxidative phosphorylation, and the mTORC pathway in EBV(+) as compared to EBV(-) HIV-DLBCL. Conclusion: EBV(+) HIV-DLBCL show a distinct mutational profile compared to EBV(-) HIV-DLBCL, with EBV(+) cases showing frequent mutations with STAT3 and DDX3X in contrast to EBV(-) cases with frequent mutations associated with epigenetic modification pathways (KMT2D, TET2). These genetic profiles underscore the need for tailored therapeutic approaches depending on EBV status. Although the analysis is limited and requires confirmation in a larger cohort, this is the largest study at present evaluating these tumors.

Introduction The Florida-California Cancer Research, Education, and Engagement (CaRE 2 ) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE 2 triad partnership. Methods CaRE 2 serves diverse populations in Florida and California using a “molecule to the community and back” model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. Results Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE 2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE 2 -related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE 2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. Conclusion The CaRE 2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.

Abstract Background: Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network's research. Methods: PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network's research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities. Results: Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants. Conclusions: PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries. Impact: Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement.

This prospective phase II clinical trial (Side Out 2) explored the clinical benefits of treatment selection informed by multi‐omic molecular profiling (MoMP) in refractory metastatic breast cancers (MBCs). Core needle biopsies were collected from 32 patients with MBC at trial enrollment. Patients had received an average of 3.94 previous lines of treatment in the metastatic setting before enrollment in this study. Samples underwent MoMP, including exome sequencing, RNA sequencing (RNA‐Seq), immunohistochemistry, and quantitative protein pathway activation mapping by Reverse Phase Protein Microarray (RPPA). Clinical benefit was assessed using the previously published growth modulation index (GMI) under the hypothesis that MoMP‐selected therapy would warrant further investigation for GMI ≥ 1.3 in ≥ 35% of the patients. Of the 32 patients enrolled, 29 received treatment based on their MoMP and 25 met the follow‐up criteria established by the trial protocol. Molecular information was delivered to the tumor board in a median time frame of 14 days (11–22 days), and targetable alterations for commercially available agents were found in 23/25 patients (92%). Of the 25 patients, 14 (56%) reached GMI ≥ 1.3. A high level of DNA topoisomerase I (TOPO1) led to the selection of irinotecan‐based treatments in 48% (12/25) of the patients. A pooled analysis suggested clinical benefit in patients with high TOPO1 expression receiving irinotecan‐based regimens (GMI ≥ 1.3 in 66.7% of cases). These results confirmed previous observations that MoMP increases the frequency of identifiable actionable alterations (92% of patients). The MoMP proposed allows the identification of biomarkers that are frequently expressed in MBCs and the evaluation of their role as predictors of response to commercially available agents. Lastly, this study confirmed the role of MoMP for informing treatment selection in refractory MBC patients: more than half of the enrolled patients reached a GMI ≥ 1.3 even after multiple lines of previous therapies for metastatic disease.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P&lt;1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P&lt;0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Abstract Background Tumor heterogeneity underlies resistance and disease progression in glioblastoma (GBM), and tumors most commonly recur adjacent to the surgical resection margins in contrast non-enhancing (NE) regions. To date, no targeted therapies have meaningfully altered overall patient survival in the up-front setting. The aim of this study was to characterize intratumoral heterogeneity in recurrent GBM using bulk samples from primary resection and recurrent samples taken from contrast-enhancing (EN) and contrast NE regions. Methods Whole exome and RNA sequencing were performed on matched bulk primary and multiple recurrent EN and NE tumor samples from 16 GBM patients who received standard of care treatment alone or in combination with investigational clinical trial regimens. Results Private mutations emerge across multi-region sampling in recurrent tumors. Genomic clonal analysis revealed increased enrichment in gene alterations regulating the G2M checkpoint, Kras signaling, Wnt signaling, and DNA repair in recurrent disease. Subsequent functional studies identified augmented PI3K/AKT transcriptional and protein activity throughout progression, validated by phospho-protein levels. Moreover, a mesenchymal transcriptional signature was observed in recurrent EN regions, which differed from the proneural signature in recurrent NE regions. Conclusions Subclonal populations observed within bulk resected primary GBMs transcriptionally evolve across tumor recurrence (EN and NE regions) and exhibit aberrant gene expression of common signaling pathways that persist despite standard or targeted therapy. Our findings provide evidence that there are both adaptive and clonally mediated dependencies of GBM on key pathways, such as the PI3K/AKT axis, for survival across recurrences.

Abstract Chromosome 13 (Δ13) abnormalities are found in greater than 50% of patients with Multiple Myeloma (MM). MM is most commonly defined by chromosome 13 monosomy or 13q loss (85%). Interstitial deletions comprise the remaining 15%. Many studies have revealed that Δ13 in MM are associated with poor survival and reduced response to therapy. Genes mapping to chromosome 13 may be involved in pathogenesis and/or progression of the disease due to loss of function from gene mutation or from epigenetic effects such as haploinsufficiency. In this study, array-based comparative genomic hybridization coupled with microarray technology (aCGH) is used to detect gene copy number loss on chromosome 13 from nine MM patient samples. Whole genome long-oligo microarrays constructed by Agilent Technologies were used which contain 40,000 genes that span the human genome with an average spatial resolution of ~75 kb. Using genomic DNA isolated from MM patients with interstitial deletions on chromosome 13, DNA was amplified, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays were analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts. A common region of loss of 2.2 Mb, at 13q14.2 was detected. Additionally, we investigated the correlation between genomic copy number change and the expression level for MM patients in the13q region. From an independent gene expression data set whose expression measurements were conducted with Affymetrix HG-U133A v2 microarrays, data was selected that corresponded to the samples used for current aCGH. Expression values from MM samples were divided by the mean expression values from 12 normal bone marrow samples for each gene and the resulting values were treated as surrogate ratios between MM and normal samples. Probes from both microarrays were then aligned according to their chromosomal positions and merged if their chromosomal positions overlapped. Composite chromosomal maps were generated that displayed the expression levels and copy number changes. The maps were used to differentiate chromosomal regions in 13q where copy number changes and expression levels show high correlation and regions where such correlation was not observed. Although the number of probes sampled in the expression microarray was much smaller than those in aCGH microarray, a chromosomal region of great interest, that encompasses 13q14.2, arose naturally from this analysis. Although the mechanism by which loss of 13q effects tumorigenesis in MM could be a haploinsufficiency model, we are not ruling out the presence of a tumor suppressor gene in this region. We are evaluating candidate tumor suppressor genes in the region for loss of function by mutational analysis and hypermethylation studies.

Abstract Chromosome 13 deletion (Δ13) is one the most common genetic abnormalities observed in multiple myeloma (MM) and confers a poor prognosis. Studies to identify critical tumor suppressor genes in MM till date have lack adequate resolution, and the molecular phenotype associated with Δ13 has not been established. In this study we seek to establish a molecular profile for Δ13 and to finely map the minimal common region of deletion (CDR) on chromosome 13 by using gene expression profiling (GEP) and array comparative genomic hybridization (aCGH). GEP was performed on RNA from purified plasma cells of 72 newly diagnosed MM and 50 human myeloma cell lines (HMCLs) using the Affymetrix U133A chip and U133plus chip (Affymetrix, Santa Clara, CA) respectively. Patients were assigned TC classes which correlates with underlying genetic subtypes. In addition, aCGH was performed on 79 MM samples (36 with GEP data) and 50 myeloma cell lines (HMCLs; 48 with GEP data) using a platform utilizing 60-mer oligonucleotides (Human Genome CGH 44B Oligo Microarrays, Agilent Technologies), which have a resolution of about 70Kb. Raw data was extracted using the Feature Extraction 8.1 and visualized using CGH Analytics 3.2 (Agilent Technologies). To define a signature that reflects the biological consequences of Δ13 and not its close association with some genetic subtypes of MM (example, t(4;14) and t(14;16)), we selected a training cohort consisting of cases belonging to D1, D2, 11q13 and none TC class such that cases with and without Δ13 are balanced for ploidy and TC classes (n=28). A 152-gene Δ13 signature was identified. Its specificity was confirmed by leave-one-out cross validation using the K-nearest neighbor (KNN) class prediction algorithm (predictive accuracy of 100% in the training cohort). It was subsequently validated in a validation cohort that includes t(4;14) and t(14;16) that were not use to derive this gene signature, maintaining a high predictive accuracy (88%). This gene-set may therefore reflect core transcriptional consequences of Δ13 and is enriched for genes involved in the cell cycle and apoptosis. Using aCGH, 20 patients have Δ13 (mostly whole chromosome) all involving the 13q14–q21 region. Of the 32 HMCLs with Δ13 (whole chromosome or interstitial), 22 have mono-allelic loss of RB1 whereas 4 had bi-allelic loss. Besides RB1, bi-allelic loss of several other genes in the 13q14–q21 region (CYSLTR2, CDADC1, ITM2B, PCDH9) was also observed. As the CDR is large and contains a number of genes, we utilized a set of criteria (bi-allelic loss in HMCLs, within 13q14–q21 CDR, gene expression significantly correlated with copy number, and loss could explain molecular phenotype) to narrow down the potential candidates. Only RB1 and ITM2B fulfilled these criteria. Furthermore, RB protein levels correlated well with mRNA levels and DNA copy suggesting that even in absence of mutations resulting in bi-allelic loss, mono-allelic loss of RB1 could be tumorigenic through a haploinsufficiency mechanism.