Citations

Objectives: Modifiable lifestyle factors are associated with morbidity and mortality in hematopoietic stem cell transplant (HSCT) survivors. The aims of the study were to examine: (a) receipt of provider advice to change behaviors, (b) health behavior change, and (c) how modifiable lifestyle factors might cluster together. Methods: Patients within a large HSCT program completed a survey (N =870) of lifestyle factors at pre-HSCT evaluation. The survey assessed self-reported adherence to American Cancer Society and HSCT guidelines for cancer survivorship in the year prior to a pre-HSCT evaluation. Lifestyle factors of interest were physical activity, fruit and vegetable consumption, tobacco use, alcohol use, and height/weight to calculate Body Mass Index (BMI). Results: Among patients not meeting all five guidelines (98%), 31% received provider advice to change. Between 10% and 42% reported healthy behavior change since diagnosis. Physical activity, fruit and vegetable consumption, and BMI were the most commonly clustered lifestyle behaviors. Conclusions: A considerable proportion of patients did not meet national guidelines for lifestyle factors. Results highlight an immediate opportunity to improve health care delivery and transplant outcomes via pre-HSCT lifestyle screening and implementation of effective health behavior change interventions.

Abstract Most disease-associated single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWASs) reside in noncoding regions. There is increasing evidence that they play regulatory roles through epigenetic mechanisms by altering local chromatin state, 3D chromatin structure, and looping interactions. We and others have identified 42 CLL risk loci from GWASs. At 12 risk loci located outside of gene promoters, we previously demonstrated that functional SNPs are highly enriched in enhancers and super-enhancers that mostly target BCL2 family genes and transcriptional regulators. However, the study was limited by using only public epigenomic data generated in lymphoblastoid cell lines (LCL) and normal immune related cell types. To gain a better understanding of how the functional SNPs alter local chromatin state and modulate target gene expression in CLL, we generated RNA-seq data (n=588) and transposase-accessible chromatin with sequencing (ATAC-seq) data (n=69) in CLL tumor B cells. We performed molecular quantitative trait loci (QTL) analysis with index and correlated SNPs (R2 0.5) at 41 risk loci (excluding the HLA locus). The analyses identified cis expression QTLs (eQTLs), within 1Mb of genes’ transcription start site, at 25 risk loci and chromatin accessibility QTLs (caQTLs, within peak) at 11 risk loci, with both eQTLs and caQTLs at 8 risk loci. We identified a total of 54 eGenes, for which the expression is affected by nearby SNPs within 1Mb, including 40 novel eGenes at 16 CLL risk loci not previously reported. Notably, based on publicly available chromosome interaction data from CLL, LCL, and normal B cells, for over 70% of the novel eGenes, their promoters showed looping interactions with the regions carrying the eQTLs. Further, 13 SNPs were identified as both caQTL and eQTL, with the associated novel eGenes including CD81 at 11p15.5, IPCEF1 at 6q25.2, as well as CXXC1 and MBD1 at 18q21.1. The result suggests that these SNPs play a role in altering chromatin accessibility contributed to gene expression variation. At 11p15.5 risk locus, SNP rs2651823 (A/G) represents a novel caQTL and eQTL. The alternative G allele is associated with increased chromatin accessibility and CD81 expression. Hi-C data from GM12878 and CD20+ B cells supported interaction between the open chromatin region carrying rs2651823 and CD81 promoter. CD81 facilitates the trafficking of CD19 to the surface of activated B cells, and CD81-null mice showed impaired immune response. In a mouse model, CD81 contributes to tumor progression and metastasis in Lewis lung carcinoma. In summary, our molecular QTL analysis revealed that functional SNPs, located in CLL risk loci, modulate chromatin accessibility and expression of downstream target genes that could impact CLL risk. Citation Format: Huihuang Yan, Zhiquan Wang, Mingma Hoel, Cristine Allmer, Chantal McCabe, Daniel O’Brien, Dennis Robinson, James Cerhan, Sameer Parikh, Esteban Braggio, Susan Slager. Molecular QTL analyses identify functional variants at inherited risk loci in chronic lymphocytic leukemia [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 2763.

Abstract Family history of hematologic malignancy (FHHM) is an established risk factor for developing lymphoma, but studies examining associations between self-reported FHHM and lymphoma prognosis during the recent treatment era are limited. Utilizing a prospective cohort study, we evaluated associations between FHHM and prognosis for common lymphoma subtypes, including diffuse large B-cell (DLBCL), follicular (FL), marginal zone (MZL), mantle cell (MCL), Hodgkin (HL), and T-cell (TCL) lymphomas. We used the Mayo Clinic component of the Molecular Epidemiology Resource, a prospective cohort study of newly diagnosed lymphoma patients enrolled from 2002 to 2015. Self-reported FHHM (HL, NHL, leukemia, or multiple myeloma) in a first-degree relative was obtained via questionnaire. Primary outcomes were overall survival (OS) and event-free survival (EFS; time from diagnosis to disease progression, initiation of second-line therapy, or all-cause death). Secondary outcomes were failure to achieve 24 months of event-free survival (EFS24; associated with aggressive disease and poor outcomes) and lymphoma-specific survival (LSS; time from diagnosis to death from lymphoma or lymphoma treatment-related complications). We used multivariable Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for the association of FHHM with OS, EFS, and LSS, and logistic regression to estimate odds ratios (ORs) and 95% CI for the association with failure to achieve EFS24. All models were adjusted for sex and a lymphoma subtype specific prognostic index. The cohort consisted of 650 DLBCL, 679 FL, 291 MZL, 178 MCL, 254 HL, and 196 TCL patients. The prevalence of FHHM ranged from 9.7% in TCL to 14% in FL. FHHM was not associated with OS in any subtype, but MCL patients with FHHM showed an inferior EFS (HR=1.70, 95% CI 1.02-2.85; p=0.04). For EFS24, FHHM was associated with failure to achieve EFS24 only in FL (OR=1.57, 95% CI 0.99-2.48; p=0.05). Similarly, FHHM was associated with inferior LSS in FL patients (HR=1.98, 95% CI 1.11-3.53; p=0.02). In a treatment subgroup analysis of FL patients, the FHHM associations with failure to achieve EFS24 (OR=2.48, 95% CI 1.04-5.74; p=0.04) and inferior LSS (HR=2.68, 95% CI 1.09-6.58; p=0.03) strengthened among those treated with frontline immunochemotherapy (IC). In summary, there were no evidence of associations between FHHM and OS across lymphoma subtypes, but MCL patients with FHHM displayed inferior EFS. FL patients with FHHM were more likely to not achieve EFS24 and to ultimately die of their lymphoma or a lymphoma treatment-related complication. This finding was stronger in more aggressive FL requiring frontline IC. This novel finding would suggest that genetic or environmental factors associated with FHHM may underlie pathways that impact disease aggressiveness and early clinical failure in FL. Citation Format: George Cholack, Raphael Mwangi, Thomas M. Habermann, Verena Hinder, Rosalie Griffen, Dennis Robinson, Andrew L. Feldman, Thomas E. Witzig, Stephen M. Ansell, Brian K. Link, Yucai Wang, Carrie A. Thompson, Susan L. Slager, Matthew Maurer, Anne J. Novak, James R. Cerhan. Family history of hematologic malignancy and prognosis across lymphoma subtypes: Novel association with poor outcomes in follicular lymphoma [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 7344.

ABSTRACTObjectiveTo explore pre–hematopoietic stem cell transplant (HSCT) demographic, disease, and psychological factors predictive of future transplant regret and to determine post‐HSCT variables associated with regret.Patients and MethodsHSCT candidates participated in a prospective cohort study (June 2008–October 2013) examining health behaviors and HSCT outcomes, including completion of standardized surveys at pre‐HSCT (baseline) and 1‐year post‐HSCT. Cases were participants that endorsed regret at 1‐year post‐HSCT follow‐up, and controls were participants without regret at 1 year, matched on age, sex, and transplant type. For cases and controls, pre‐HSCT psychosocial evaluations were abstracted from the electronic health record and coded to determine the Psychosocial Assessment of Candidates for Transplantation score, psychosocial stressors, and mental health diagnoses. The association of selected factors with regret was estimated with odds ratios and 95% confidence intervals from conditional logistic regression models.ResultsAt post‐HSCT, 49 participants of 638 endorsed transplant regret (8%) and formed the case group; 98 controls were matched from remaining participants. Cases and controls were well matched on age (56.6 vs. 57.2 years), sex (both groups 34.7% female), and transplant type (both groups 81.6% autologous). After controlling for the number of hospitalizations and active treatment status, conditional logistic regression revealed that patients who endorsed regret were 3.7 times (95% CI = 1.37–9.69, p = 0.008) more likely to not be in remission compared to controls at 1‐year post‐HSCT.ConclusionMatched case–control analyses revealed that no pre‐HSCT variables collected during the pre‐HSCT evaluation period were predictive of transplant regret, while poorer outcomes at 1‐year after transplant were associated with regret.

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is clinically heterogeneous, and gene expression profiling has identified at least two biologically distinct DLBCL subtypes defined by their cell of origin (COO): germinal center B cell (GCB) and activate B cell (ABC) or non-GCB. We evaluated a variety of putative DLBCL risk factors for etiologic heterogeneity by the COO in a clinic-based study of newly diagnosed DLBCL cases (N = 638) and frequency-matched controls (N = 2,253). Methods: The COO was determined on formalin-fixed, paraffin-embedded tumor tissue, with DLBCL classified as GCB (N = 283), non-GCB (N = 188), or undetermined/missing (N = 167; mainly because of lack of tissue). Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Results: We identified heterogeneity by the COO for low socioeconomic status (SES), which was only associated with non-GCB DLBCL (OR = 1.88 for low vs. average SES; 95% CI, 1.08–3.27); alcohol use, which was only associated with GCB DLBCL (OR = 0.48 for former drinkers; 95% CI, 0.29–0.80 and OR = 0.47 for current drinkers; 95% CI, 0.32–0.71); and borderline heterogeneity for the regular use of regular/extra-strength aspirin, which was only associated with non-GCB DLBCL (OR = 0.36; 95% CI, 0.16–0.85). In contrast, there was no significant heterogeneity by the COO for family history, medical history, or other lifestyle factors. Conclusions: Although requiring confirmation, most risk factors for DLBCL did not show etiologic heterogeneity by the COO, with some notable exceptions including alcohol use, SES, and perhaps regular use of regular/extra-strength aspirin showing associations. Impact: Mechanistically, these findings suggest that most of the DLBCL risk factors evaluated here influence lymphomagenesis prior to differentiation into COO subtypes, with selected factors acting later.

Abstract Objective The fast accumulation of vast pharmacogenomics data of cancer cell lines provide unprecedented opportunities for drug sensitivity prediction (DSP), a crucial prerequisite for the advancement of precision oncology. Recently, Generative Large Language Models (LLM) have demonstrated performance and generalization prowess across diverse tasks in the field of natural language processing (NLP). However, the structured format of the pharmacogenomics data poses challenge for the utility of LLM in DSP. Therefore, the objective of this study is multi-fold: to adapt prompt engineering for structured pharmacogenomics data toward optimizing LLM’s DSP performance, to evaluate LLM’s generalization in real-world DSP scenarios, and to compare LLM’s DSP performance against that of state-of-the-science baselines. Methods We systematically investigated the capability of the Generative Pre-trained Transformer (GPT) as a DSP model on four publicly available benchmark pharmacogenomics datasets, which are stratified by five cancer tissue types of cell lines and encompass both oncology and non-oncology drugs. Essentially, the predictive landscape of GPT is assessed for effectiveness on the DSP task via four learning paradigms: zero-shot learning, few-shot learning, fine-tuning and clustering pretrained embeddings. To facilitate GPT in seamlessly processing the structured pharmacogenomics data, domain-specific novel prompt engineering is employed by implementing three prompt templates (i.e., Instruction, Instruction-Prefix, Cloze) and integrating pharmacogenomics-related features into the prompt. We validated GPT’s performance in diverse real-world DSP scenarios: cross-tissue generalization, blind tests, and analyses of drug-pathway associations and top sensitive/resistant cell lines. Furthermore, we conducted a comparative evaluation of GPT against multiple Transformer-based pretrained models and existing DSP baselines. Results Extensive experiments on the pharmacogenomics datasets across the five tissue cohorts demonstrate that fine-tuning GPT yields the best DSP performance (28% F1 increase, p-value= 0.0003) followed by clustering pretrained GPT embeddings (26% F1 increase, p-value= 0.0005), outperforming GPT in-context learning (i.e., few-shot). However, GPT in the zero-shot setting had a big F1 gap, resulting in the worst performance. Within the scope of prompt engineering, performance enhancement was achieved by directly instructing GPT about the DSP task and resorting to a concise context format (i.e., instruction-prefix), leading to F1 performance gain of 22% (p-value=0.02); while incorporation of drug-cell line prompt context derived from genomics and/or molecular features further boosted F1 score by 2%. Compared to state-of-the-science DSP baselines, GPT significantly asserted superior mean F1 performance (16% gain, p-value<0.05) on the GDSC dataset. In the crosstissue analysis, GPT showcased comparable generalizability to the within-tissue performances on the GDSC and PRISM datasets, while statistically significant F1 performance improvements on the CCLE (8%, p-value=0.001) and DrugComb (19%, p-value=0.009) datasets. Evaluation on the challenging blind tests suggests GPT’s competitiveness on the CCLE and DrugComb datasets compared to random splitting. Furthermore, analyses of the drug-pathway associations and log probabilities provided valuable insights that align with previous DSP findings. Conclusion The diverse experiment setups and in-depth analysis underscore the importance of generative LLM, such as GPT, as a viable in silico approach to guide precision oncology. Availability https://github.com/bioIKEA/SensitiveCancerGPT

Purpose The Sangre Por Salud (SPS) Biobank was established to facilitate biomedical research opportunities for the Latino community by creating an easily accessible prospective cohort for scientists interested in studying health conditions and health disparities in this population. Participants Individuals self-identifying as Latino, aged 18–85 years, were prospectively recruited from the primary care Internal Medicine clinic at Mountain Park Health Center in Phoenix, Arizona. After obtaining informed consent, detailed medical history questionnaires were captured, and blood samples were obtained for common laboratory tests. Participants authorised the research team to access their electronic health records for research purposes. In addition, participants had serum, plasma and DNA samples isolated and stored at the Mayo Clinic Arizona Biorepository Laboratory for long-term storage and future access. As part of the study, participants consented and agreed to be contacted for potential participation in future research studies. Findings to date 3756 participants provided informed consent, of whom 3733 completed all study questionnaires, an oral glucose tolerance test and had blood collected and stored. The SPS cohort is predominantly composed of females (72%), with a median age at time of consent of 42 years. All participants self-identified as Hispanic/Latino, 45% were married, 53% were employed for wages and 60% had less than a high school degree. Around 25% of participants met diagnostic criteria for overweight (BMI 25–29 kg/m 2 ), and 49% met for obesity (BMI≥30 kg/m 2 ). At time of recruitment, hypertension, hyperlipidaemia and depression affected 22%, 20% and 13% of the cohort, respectively. Future plans We plan to regularly update the participants’ electronic health records and self-reported health data to longitudinal research. Additionally, we plan to obtain a more comprehensive genomic analysis on the entire cohort, ensuring greater research interest and investigation into the underlying genetic factors that contribute to disease susceptibility in this cohort.

ABSTRACT Rituximab, gemcitabine, and oxaliplatin (R‐GemOx) is a commonly used chemoimmunotherapy regimen for relapsed or refractory (R/R) diffuse large B‐cell lymphoma (DLBCL), but there are limited real‐world data. In a multicenter retrospective study from a cohort of eight US academic centers (LEO CReWE), we evaluated 183 patients with R/R DLBCL and high‐grade B cell lymphoma treated with R‐GemOx, including subgroups treated without intent for consolidation with autologous stem cell transplant (ASCT) or chimeric antigen receptor (CAR) T cell therapy ( n = 100), those utilizing R‐GemOx as a bridge to ASCT or CAR T ( n = 83), and those aged 70 and older ( n = 71). Overall response rates (ORRs) for all patients treated with R‐GemOx were 45% with a complete response (CR) rate of 29%. The median event‐free survival (EFS) was 2.3 months, and the median overall survival (OS) was 13.5 months. Patients receiving R‐GemOx without intent for ASCT or CAR T had ORR and CR rates of 33% and 18%, respectively, with median EFS and OS of 2.0 and 9.5 months, respectively. Patients receiving R‐GemOx as a bridge to ASCT or CAR T had ORR and CR rates of 57% and 36%, respectively, with median EFS and OS of 3.5 and 17.4 months, respectively. Patients receiving R‐GemOx aged 70 and older had ORR and CR rates of 53% and 33%, respectively, with median EFS and OS of 2.2 and 13.9 months, respectively. These data provide a benchmark for R‐GemOx in the rapidly evolving landscape of R/R DLBCL therapies.

PURPOSE Lymphomas are a heterogeneous group of diseases that develop in individuals of all ages and have variable prognoses. Improved survival resulting from therapy advances has led to the emergence of diverse late effects. Although several (US)–based organizations have developed survivorship guidelines, the distinct features of lymphoma subtypes and diverse therapies used raise concerns regarding their applicability to lymphoma survivors. We compared survivorship recommendations (outside primary disease monitoring) between US clinical guidelines. METHODS We extracted information from 17 guidelines from five US-based organizations: ASCO (n = 11), American Cancer Society (n = 1), Children's Oncology Group (n = 1), Center for International Blood and Marrow Transplant Research (n = 1), and the National Comprehensive Cancer Network (n = 3). Guidelines were evaluated to determine whether they offer recommendations on physical effects , psychosocial and quality of life ( QOL ), and health promotion and prevention . Comparisons were focused on second primary malignancy, cardiovascular complications, and vaccination. RESULTS Survivorship recommendations on physical effects and psychosocial and QOL mainly differ in the timing and approaches for screening. Vaccination recommendations were primarily derived from other cancer populations. Identified research gaps were a lack of understanding of the risk of late effects across lymphoma subtypes, the role of social determinants of health in survivorship, and the lack of a survivorship care model that integrates lymphoma subtypes and treatment exposures. CONCLUSION This study raises awareness about the complexity and challenges of managing survivors under the umbrella diagnosis of lymphoma. The inconsistency and incompleteness of existing guidelines may lead to suboptimal survivorship care. We propose expert-based research priorities to address gaps and unmet needs to help develop risk-based follow-up recommendations to optimize survivorship care for lymphoma survivors.