Amos, Christopher I.

ABSTRACT Background Most genomic studies of adult-type diffuse gliomas have focused on predominantly European ancestry populations, limiting the generalizability of molecular classifications and precision medicine approaches. We assembled a multi-institutional glioma cohort of diverse patients to investigate how germline ancestry, molecular subtypes, and mutational processes shape tumor biology and clinical outcomes. Methods We analyzed 1,102 adults with WHO 2021–classified diffuse gliomas (IDH-mutant, 1p/19q-codeleted oligodendroglioma; IDH-mutant astrocytoma; IDH-wildtype glioma) from seven U.S. institutions. Whole-exome sequencing (WES) of FFPE tumors identified somatic alterations and COSMIC SBS v3.2 mutational signatures. Genetic ancestry was estimated from WES using 1000 Genomes reference populations. Overall survival was assessed using Kaplan–Meier and multivariable models. Results The cohort included 66.9% European (EUR), 21.1% Admixed American/Hispanic (AMR), 10.3% Admixed African (AFR), and 1.6% Asian (AS) ancestry. Survival followed expected molecular hierarchy (median overall survival: oligodendroglioma 15.7 years, astrocytoma 10.6 years, IDH-wildtype glioma 1.9 years). Within oligodendroglioma, AMR patients showed improved survival versus EUR (HR 0.67, 95% CI 0.48–0.94; p=0.011), with similar trends across subtypes. Somatic profiling confirmed canonical subtype-defining alterations and revealed higher ATRX alterations in AFR and AMR IDH-wildtype tumors compared with EUR. ATRX alterations were associated with improved survival only in AFR (p=0.003). Mutational signature analysis identified subtype-specific signatures, including therapy-associated signatures. Chemotherapy-related signatures were more frequent in EUR and AMR than in AFR. Conclusions This ancestrally diverse glioma cohort confirms established molecular classifications and identifies ancestry-associated differences in survival, somatic alterations, and mutational processes, indicating the critical need for broad representation to inform precision neuro-oncology. Key Points A multi-institutional glioma cohort validates subtype and survival patterns across ancestries. Therapy-associated mutational signatures differ by ancestry, suggesting distinct treatment-related mutational processes. Admixed American patients show improved survival, particularly in oligodendroglioma. Importance of the Study Most genomic studies of adult-type diffuse glioma have focused on populations of predominantly European ancestry which limits the ability to examine variation in tumor biology and clinical outcomes across populations. In this study, we assembled one of the largest ancestrally diverse cohorts of molecularly characterized adult diffuse gliomas, integrating germline ancestry inference with tumor whole-exome sequencing and mutational signature analysis. We confirm that established molecular classifications and survival hierarchies remain robust across ancestry groups. However, we also identified ancestry-associated differences in survival within specific tumor subtypes, higher ATRX alteration frequencies in African American and admixed American patients with IDH-wildtype tumors, and variation in therapy-associated mutational signatures across ancestry groups. These findings highlight the importance of incorporating population differences into genomic studies of glioma and provide a resource for future multi-ancestry investigations of glioma risk, tumor evolution, and treatment response, ultimately supporting more inclusive precision neuro-oncology.

Abstract Background: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide. Prognostic models for HCC primarily rely on tumor burden and liver function, with limited consideration of inherited genetic contributions to survival variability. Identifying germline variants associated with survival could refine prognosis and reveal biological mechanisms underlying disease progression. Methods: We conducted a genome-wide association study (GWAS) of overall survival among 864 patients with HCC from the M.D. Anderson Cancer Center cohort. Genotyping, quality control, and imputation procedures followed previously described protocols (PMID: 38381705). Associations between genetic variants and overall survival were assessed using Cox proportional hazards models adjusted for age, sex, and the first five principal components. Genome-wide significance was defined as P < 5×10-8. Functional annotation and pathway enrichment analyses (MAGMA) were employed to investigate the biological relevance of the identified loci. Results: After quality control, 8,525,017 single-nucleotide polymorphisms (SNPs) were analyzed. We identified seven new loci associated with HCC survival at the genome-wide significance level. Five out of seven loci are associated with anthropometric traits and hematological measurement traits, reflecting metabolism, hematopoiesis, immune function, and inflammation. A variant in the 3′ untranslated region (UTR3) of STX7 showed a genome-wide significant association with overall survival (HR = 3.23; P = 2.56 ×10-8). Carriers of the risk allele had significantly shorter survival times compared with noncarriers. Pathway analysis revealed enrichment in biologically relevant processes, including liver growth and regeneration (growth hormone and Interleukin-6 (IL-6) signaling pathway), implicating hepatocyte proliferation and IL-6/STAT3-mediated inflammatory signaling. Immune-related pathways, such as regulation of T cell activation and myeloid leukocyte migration, highlight the role of germline variation in immune surveillance. Moreover, pathways governing vascular remodeling and metabolic stress response (e.g., JAK activation, mitochondrial dynamics) suggest that inherited determinants of microenvironmental structure and hepatocyte resilience influence patient outcomes. Conclusion: This germline GWAS of HCC survival identifies seven new genome-wide significant loci and implicates pathways involved in liver regeneration, inflammation, and tissue remodeling. These findings support a role for inherited genetic variation in shaping HCC prognosis and underscore the potential of integrating germline genetics into prognostic modelling and therapeutic target discovery. Citation Format: Younghun Han, Jinyoung Byun, Lewis R. Roberts, Katherine A. McGlynn, Manal M. Hassan, Christopher I. Amos. Identification of survival-associated germline variants in hepatocellular carcinoma [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 3606.

Abstract Chromosome 5p15.33 harbors several independent association signals which demonstrate antagonistic pleiotropy across cancer types, with causal mechanisms largely unresolved. To identify functional variants and enhancer elements at this locus, we performed statistical fine-mapping followed by massively parallel reporter assays (MPRA) and proliferation based CRISPRi screens. This approach identified eight multi-cancer functional variants (MCFVs) across three GWAS signals. Targeting rs421629 (part of the CLPTM1L signal marked by rs465498) with CRISPRi revealed opposing effects on TERT expression in pancreatic versus lung cancer cells, consistent with the antagonistic pleiotropy observed for this signal. Furthermore, CRISPRi nominated an intronic CLPTM1L variable number tandem repeat (VNTR) as a potent enhancer. Long-read sequencing established VNTR polymorphisms as potential causal variants for the rs465498 signal. We showed that Hippo-pathway transcription factors mediate VNTR enhancer activity in lung and pancreatic cancer cells. Together, these findings indicate that cancer susceptibility at 5p15.33 may be mediated by both SNPs and VNTRs and provide an integrated framework for resolving complex pleiotropic loci.

Background and Aims: Cholangiocarcinoma (CCA) is a rare but aggressive malignancy with poorly understood genetic susceptibility. To date, genome-wide association studies (GWAS) investigating germline variants associated with CCA risk remain limited. We aimed to identify genetic risk loci for CCA and its clinical subtypes through comprehensive GWAS and post-GWAS analyses. Approach and Results: We conducted a GWAS of 2366 CCA cases and 11,750 controls of European ancestry. Genome-wide significant loci ( p <5×10 −8 ) were identified and further examined through fine-mapping, functional annotation, and HLA imputation. Subgroup analyses were conducted by CCA subtypes and primary sclerosing cholangitis (PSC) status. Cross-trait linkage disequilibrium score regression and Mendelian randomization were employed to investigate the shared genetic architecture and potential causal relationships with a diverse range of traits. We identified 1 new genome-wide significant variant, rs535777 (OR=1.44), near HLA-DRB1/DQA1 associated with CCA, and 2 variants associated with extrahepatic CCA: rs116224263 (OR=0.17) in LINC02506 at 4p15.1 and rs6914950 (OR=1.63) near HLA-DRB1/DQB1 . Stratified analyses revealed rs2395184 (OR=3.51) near HLA-DRA/DRB5 associated with PSC-related CCA, and rs142674434 (OR=2.98) in THSD7A at 7p21.3 associated with non-PSC-related CCA. HLA imputation uncovered new amino acid residues associated with disease risk. Cross-trait analyses identified shared genetic signals between CCA and anthropometric, lipidemic, lifestyle, and medical traits. Mendelian randomization supported putative causal associations for 12 traits with CCA or its subtypes. Conclusions: Our large-scale GWAS highlights new genetic variants and HLA-linked mechanisms underlying CCA susceptibility. Integrating multi-step post-GWAS approaches enhances understanding of CCA pathogenesis and may facilitate the development of risk biomarkers for early detection and precision prevention strategies.

Abstract Hepatocellular carcinoma (HCC) mortality is increasing globally, partly due to the growing prevalence of nonviral liver diseases. Genome‐wide association studies (GWAS) have identified genetic variants associated with HCC development. Leveraging GWAS summary statistics and linkage disequilibrium score regression (LDSR), we investigated disease co‐development with hepatitis C virus‐negative (HCV‐negative) HCC to provide unique insights into HCC etiology and prioritize relationships for further causal inquiry. We utilized the LDSR statistical framework to estimate the genetic correlation and heritability between HCV‐negative HCC with 901 epidemiologic, behavioral, and clinical traits from the United Kingdom Biobank (UKBB). First, we set the threshold for observed scale heritability of each trait at 0.02 to ensure reliable inferences with adequate study power. Next, we observed significant positive genetic correlations between HCV‐negative HCC and blood‐based biomarkers of liver injury (ALT, GGT) and allostatic load (including glycated hemoglobin, blood pressure, and total albumin). We also identified a positive genetic correlation between HCV‐negative HCC and diseases associated with metabolic dysfunction‐associated steatotic liver disease (MASLD), including diabetes, hypertension, chronic ischemic heart disease, and others. Taken together, our results help to identify polygenic and pleiotropic signals related to different phenotypic traits associated with HCC and support further exploration of the predictive power of blood‐based biomarkers identified in this study for inferring HCC development among HCV‐negative individuals.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Abstract Hepatocellular carcinoma (HCC) mortality is increasing globally, partly due to the growing prevalence of non-viral liver diseases. Genome-wide association studies (GWAS) have identified genetic variants associated with HCC development. Leveraging GWAS summary statistics and linkage disequilibrium score regression (LDSR), we investigated disease co-development with non-viral HCC to provide unique insights into HCC etiology and prioritize relationships for further causal inquiry. We utilized the LDSR statistical framework to estimate the genetic correlation and heritability between non-viral HCC with 923 epidemiologic, behavioral, and clinical traits from the United Kingdom Biobank (UKBB) cohort. We observed a SNP-array heritability (h2 obs) of 0.20 for non-viral HCC. Next, we estimated the pairwise genetic correlation between non-viral HCC and heritable (h2 obs &gt; 0.02) UKBB traits, identifying significant positive genetic correlations between non-viral HCC and blood-based biomarkers of liver injury (ALT, GGT) and allostatic load (including glycated hemoglobin, blood pressure, and total albumin). We also identified a positive genetic correlation between non-viral HCC and diseases associated with metabolic dysfunction-associated steatotic liver disease (MASLD), including diabetes, hypertension, chronic ischemic heart disease, and others. Non-viral HCC was negatively associated with filtered coffee intake but positively associated with instant coffee intake. In addition, smoking behavior and the amount of alcohol consumption in the UKBB cohort showed a positive association with non-viral HCC. Our study provides an atlas of cross-trait genetic correlations in non-viral HCC. Taken together, our results demonstrate possible polygenic pleiotropy between non-viral HCC and different phenotypic traits. The results support further exploration of the predictive power of blood-based biomarkers and selected behaviors for inferring HCC development among non-viral individuals. Citation Format: Younghun Han, Vikram Shaw, Jinyoung Byun, Rikita Hatia, Katherine McGlynn, Lewis Roberts, Manal Hassan, Christopher I. Amos. Linkage disequilibrium score regression identifies genetic correlations between hepatocellular carcinoma and clinically relevant traits [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 2284.

Background and Aims: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). Approach and Results: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP, rs9842969, (0.51, [0.40–0.65]); 5p15.33, TERT, rs2242652, (0.70, (0.62–0.79]); 19q13.11, TM6SF2, rs58542926, (1.49, [1.29–1.72]); 19p13.11 MAU2, rs58489806, (1.53, (1.33–1.75]); and 22q13.31, PNPLA3, rs738409, (1.66, [1.51–1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74–0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. Conclusions: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Abstract Background: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. Methods: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Results: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P &lt; 5 × 10−8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear &gt; 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. Conclusions: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Impact: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

AbstractBackgroundRecent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk‐prediction model (called SPLC‐RAT) was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. The predictive performance of SPLC‐RAT was evaluated in a hospital‐based cohort of lung cancer survivors.MethodsThe authors analyzed data from 8448 ever‐smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997–2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC‐RAT and further explored the potential of improving SPLC detection through risk model‐based surveillance using SPLC‐RAT versus existing clinical surveillance guidelines.ResultsOf 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person‐years. The application of SPLC‐RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10‐year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC‐RAT development cohort), the observed SPLC incidence was significantly elevated in the high‐risk versus low‐risk subgroup (13.1% vs. 1.1%, p < 1 × 10–6). The risk‐based surveillance through SPLC‐RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow‐ups needed to detect one SPLC (162 vs. 202).ConclusionIn a large, hospital‐based cohort, the authors validated the predictive performance of SPLC‐RAT in identifying high‐risk survivors of SPLC and showed its potential to improve SPLC detection through risk‐based surveillance.Plain Language Summary Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence‐based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk‐prediction model was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. Using a large, real‐world cohort of lung cancer survivors, we showed the high predictive accuracy and risk‐stratification ability of the SPLC risk‐prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model‐based surveillance strategies compared to the existing consensus‐based clinical guidelines, including the National Comprehensive Cancer Network.