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Horbinski, Craig

Mayo Clinic

Northwestern University

Citations 2

Multi-Omics Study of Ancestry in Adults with Intracranial Cancers – Glioma (MOSAIC)
Noor, Humaira, Tsavachidis, Spiridon, Fukumura, Kazutaka , Ostrom, Quinn T., Muzny, Donna M. , Korchina, Viktoriya , Norberg, Lisa, Desjardins, Annick , Horbinski, Craig, Tadimeti, Vasudev, Mandel, Jacob, Wrensch, Margaret, Hu, Jianhong, Doddapaneni, Harsha, Liu, Xiuping , Momin, Zeineen , Motewar, Pryanka, Armstrong, Georgina , Woods, Meghan , Bernstein, Jonine L. , Amos, Christopher I., Huse, Jason T., Bondy, Melissa L. , Ostrom, Quinn T. , Walsh, Kyle M. , Peng, Bo , Nabors, Burt , Norberg, Lisa M. , Ritchie, Jennifer , Horbinski, Craig , Perez, Alejandro, Mandel, Jacob , Wrensch, Margaret , Bale, Tejus , Orlow, Irene , Hu, Jianhong , Doddapaneni, HarshaVardhan , Amos, Christopher I. , Huse, Jason T.

No container title available | June 26, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.06.24.733669 Get It

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.
A multimodal foundation model linking histopathology and DNA methylation
Wang, Dianyu , Zhang, J, Chen, Chen, Zhang, Wei , Wang, Song , Guru, Sonpavde, Horbinski, Craig, Tian, Yu , Meng, Yanda , Sonpavde, Guru , Horbinski, Craig

No container title available | June 14, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.06.11.731518 Get It

Abstract Hematoxylin and eosin (H&E) slides are routinely available in cancer care, but molecular profiling often requires additional tissue processing and turnaround time. We introduce HistoMethyl, a DNA methylation-aware pathology foundation model that aligns whole-slide histopathology with matched genome-scale methylation beta-value profiles during pre-training while requiring only an H&E slide at inference. We evaluated HistoMethyl across four task groups: gene mutation prediction, morphology-associated classification, overall survival prediction, and direct DNA methylation beta-value recovery. Evaluation spanned TCGA cross-validation, a disease-held-out lower-grade glioma cohort, and external cohort validation in CPTAC glioblastoma and SurGen rectal adenocarcinoma, totaling 14 cancer cohorts and 81 gene mutation tasks. The best-performing configuration improved mean mutation AUROC by 5.03 percentage points. By converting DNA methylation supervision into an H&E-only representation, His-toMethyl could support an early molecular triage layer that helps prioritize cases for confirmatory sequencing, methylation profiling, immunohistochemistry, and molecular tumor board review. These image-only predictions are intended to accelerate downstream molecular testing and tissue allocation while leaving final diagnosis and treatment selection anchored in validated molecular assays.