Citations

Abstract Glioblastoma, IDH-wildtype (GBM), and primary central nervous system lymphoma (PCNSL) are two aggressive brain tumors with distinct treatment strategies but overlapping imaging features on MRI. Accurate preoperative differentiation remains a clinical challenge, due to their overlapping imaging features, even when advanced MRI techniques are employed. This study explored deep learning approaches leveraging multi-sequence MRI to distinguish GBM from PCNSL. Models were developed utilizing 146 PCNSL cases, which were matched to146 GBM by age, sex and year of diagnosis. A 3D-DenseNet121 convolutional neural network was trained using two analytical strategies: (i) loss-based model selection and (ii) ensemble prediction using five-fold cross-validation. Model performance was evaluated on an independent validation set of 256 GBM and 37 PCNSL from the same institution as well as 36 PCNSL cases from an external institution. All MRIs were preprocessed using the FeTS pipeline. Using the independent validation cohort, area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI) were computed overall and stratified by demographic characteristics. Using both T1 post-contrast (T1Gd) and T2-weighted images, the loss-based model achieved AUC=0.83 (95% CI: 0.77-0.88) and the ensemble model yielded an AUC=0.82 (95% CI: 0.76-0.89). Model performance was similar across males and females; however, model performance was better for subjects older than 50 years of age versus younger than 50. When using only T1Gd images, the loss-based model dropped to AUC=0.55 (95% CI: 0.48-0.63), whereas the ensemble model had AUC=0.79 (95% CI: 0.72-0.85). Models trained with only T2 images achieved AUCs of 0.67 (95% CI: 0.60-0.73) (loss-based) and 0.75 (95% CI: 0.69-0.82) (ensemble). These results highlight the added value of the multi-sequence input. Our results confirm the feasibility of using automated deep learning models to differentiate GBM from PCNSL. Notably, the model generalized well to external MRI data, emphasizing its potential utility as a diagnostic aid in real-world clinical workflows.

Abstract Obesity has been associated with non‐Hodgkin lymphoma (NHL), but the evidence is inconclusive. We examined the association between genetically determined adiposity and four common NHL subtypes: diffuse large B‐cell lymphoma (DLBCL), follicular lymphoma, chronic lymphocytic leukemia, and marginal zone lymphoma, using eight genome‐wide association studies of European ancestry ( N = 10,629 cases, 9505 controls) and constructing polygenic scores for body mass index (BMI), waist‐to‐hip ratio (WHR), and waist‐to‐hip ratio adjusted for BMI (WHRadjBMI). Higher genetically determined BMI was associated with an increased risk of DLBCL [odds ratio (OR) per standard deviation (SD) = 1.18, 95% confidence interval (95% CI): 1.05–1.33, p = .005]. This finding was consistent with Mendelian randomization analyses, which demonstrated a similar increased risk of DLBCL with higher genetically determined BMI (OR per SD = 1.12, 95% CI: 1.02–1.23, p = .03). No significant associations were observed with other NHL subtypes. Our study demonstrates a positive link between a genetically determined BMI and an increased risk of DLBCL, providing additional support for increased adiposity as a risk factor for DLBCL.

Abstract We investigated the influence of 55 583 autophagy-related single-nucleotide polymorphisms (SNPs) on chronic lymphocytic leukemia (CLL) risk across 4 independent populations comprising 5472 CLL cases and 726 465 controls. We also examined their impact on overall survival (OS), time to first treatment (TTFT), autophagy flux, and immune responses. A meta-analysis of the 4 populations identified, to our knowledge, for the first time, significant associations between CDKN2A (rs3731204) and BCL2 (rs4940571, rs12457371, and rs1026825) SNPs and CLL risk, with CDKN2A showing the strongest association (P = 1.57 × 10−12). We also validated previously reported associations for FAS, BCL2, and BAK1 SNPs with CLL risk (P = 4.73 × 10−21 to 3.39 × 10−9). The CDKN2Ars3731204 and FASrs1926194 SNPs associated with increased CDKN2A and ACTA2 messenger RNA expression levels in the whole blood and/or lymphocytes (P = 5.1 × 10−7, P = 1.58 × 10−21, and P = 7.8 × 10−41), although no significant effect on autophagy flux was observed. However, associations were found between CDKN2A, BCL2, and FAS SNPs and various T-cell subsets, cytokine production, and circulating concentrations of interferon gamma, tumor necrosis factor–related apoptosis-inducing ligand, CD40, chemokine ligand 20, and interleukin-2 receptor subunit β proteins (P ≤ .005). No significant association was detected between autophagy variants and OS or TTFT, suggesting that these variants drive disease initiation rather than progression. In conclusion, this study identified 4 novel associations for CLL and provided insights into the biological pathways that influence CLL development.

Summary Among individuals of European Ancestry (EA), genome‐wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) and polygenic risk scores (PRSs) associated with non‐Hodgkin lymphoma (NHL) risk. We evaluated subtype‐specific PRSs, based on established EA‐SNPs, in Israeli Jews (IJ) and Palestinian Arabs (PA) and performed a GWAS in the combined ethnic groups to identify new loci. We included three common pathologically confirmed subtypes: diffuse large B‐cell (DLBCL), follicular (FL) and marginal zone (MZL) lymphomas. Controls were frequency matched to cases by age and sex. Among 752 IJ (201—DLBCL; 130—FL; 54—MZL/367—controls) and 593 PA (203—DLBCL; 41—FL/349‐controls), we computed PRSs weighted by EA‐derived effect estimates and used logistic regression models adjusted for confounders. In the combined ethnic groups of IJ and PA, subtype‐specific PRSs were significantly associated with the corresponding subtype, with a 1.69‐fold, 2.21‐fold and 2.26‐fold risk for DLBCL, FL and MZL, respectively; however, these effect sizes were attenuated compared to those reported in EA and varied by ethnicity. In the GWAS of the combined ethnic groups, two novel SNPs in the 6p21.32 locus were associated with DLBCL risk. Additional GWAS studies are needed among Jewish and Arab populations to improve genetic risk prediction for NHL in these ethnic groups.

SummaryIn individuals with high‐count monoclonal B‐cell lymphocytosis (MBL), we investigated if lymphadenopathy or splenomegaly found by imaging was associated with shorter time to first chronic lymphocytic leukaemia (CLL) therapy (TTFT) and overall survival (OS). Individuals with MBL seen at Mayo Clinic (2002–2019) were retrospectively divided into three cohorts based on imaging studies within 1 year of diagnosis: no imaging studies (Cohort A); imaging with no evidence of lymphadenopathy/splenomegaly (Cohort B); imaging with evidence of lymphadenopathy/splenomegaly (Cohort C). We compared baseline characteristics, TTFT and OS across the MBL cohorts to a cohort of individuals with small lymphocytic lymphoma (SLL). A total of 1078 patients were included: 640 with MBL and 438 with SLL. Compared to Cohort B, individuals in Cohort C were more likely to have unmutated immunoglobulin heavy chain variable region (IGHV) (43% vs. 25% p = 0.016), high‐risk fluorescence in situ hybridization (FISH) (del17p and del11q in 15% vs. 4%, p = 0.038) and higher expression of CD38 (31% vs. 16%; p = 0.011). After adjusting for sex and CLL‐International Prognostic Index (IPI), lymphadenopathy/splenomegaly was associated with a shorter TTFT (hazard ratio [HR] = 2.04, 95% confidence interval [CI]: 1.02–4.04, p = 0.042) but not OS (HR = 1.09, 95% CI: 0.62–1.92, p = 0.775). Lymphadenopathy/splenomegaly on imaging in individuals with high‐count MBL is associated with a more unfavourable risk profile and shorter time to first CLL‐directed therapy.

Abstract Clonal hematopoiesis (CH) of indeterminate potential (CHIP), driven by somatic mutations in leukemia-associated genes, confers increased risk of hematologic malignancies, cardiovascular disease, and all-cause mortality. In blood of healthy individuals, small CH clones can expand over time to reach 2% variant allele frequency (VAF), the current threshold for CHIP. Nevertheless, reliable detection of low-VAF CHIP mutations is challenging, often relying on deep targeted sequencing. Here, we present UNISOM, a streamlined workflow for enhancing CHIP detection from whole-genome and whole-exome sequencing data that are underpowered, especially for low VAFs. UNISOM utilizes a meta-caller for variant detection, in couple with machine learning models which classify variants into CHIP, germline, and artifact. In whole-exome sequencing data, UNISOM recovered nearly 80% of the CHIP mutations identified via deep targeted sequencing in the same cohort. Applied to whole-genome sequencing data from Mayo Clinic Biobank, it recapitulated the patterns previously established in much larger cohorts, including the most frequently mutated CHIP genes and predominant mutation types and signatures, as well as strong associations of CHIP with age and smoking status. Notably, 30% of the identified CHIP mutations had < 5% VAFs, demonstrating its high sensitivity toward small mutant clones. This workflow is applicable to CHIP screening in population genomic studies. The UNISOM pipeline is freely available at https://github.com/shulanmayo/UNISOM and https://ngdc.cncb.ac.cn/biocode/tool/7816.

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.