Supplementary Figure S17 shows Kaplan-Meier (KM) survival curves for relapse-free survival stratified by NS-LUAD expression subtypes in (A) patients with stage IA tumors, (B) patients with stage I tumors harboring no EGFR mutations or ALK fusions, or with no clinical records indicating treatment with tyrosine kinase inhibitor (non-TKI subset). P-values and hazard ratios (HR) were calculated using Cox proportional hazards models adjusted for age and sex. The number of samples in each subgroup is indicated on the KM curves. Unless otherwise specified, p-values are based on 10-year overall survival; for comparisons involving the chaotic subtype, 5-year overall survival rates were used owing to its association with advanced tumor stage. For the non-TKI subset, comparisons between the chaotic and steady subtypes were based on 10-year overall survival due to the absence of death events within the 5-year time window.

Pathogenic germline variants (PGVs) in dyskerin pseudouridine synthase 1 (DKC1) cause X-linked recessive dyskeratosis congenita (DC), a telomere biology disorder. Females with heterozygous DKC1 PGVs rarely exhibit DC phenotypes due to favorable X chromosome inactivation (XCI). We report a female with classic DC, pigmentary mosaicism and bone marrow failure associated with a novel de novo DKC1 variant (c.190 G > C, p.Val64Leu) with reduced expression of DKC1 and TERC along with downregulated signatures associated with aberrant telomere biology and ribosome function. Markedly skewed XCI was detected with expression of the mutated allele in skin fibroblasts and wild-type DKC1 expression in the bone marrow. We hypothesize that selective pressure in the bone marrow favored wild type expressing cells which acquired a trisomy 9 but were unable to resume normal hematopoiesis. This study demonstrates DKC1 c. 190 G > C as a likely PGV causing classic DC and highlights the molecular and clinical complexities associated with skewed XCI.

Supplementary Figure S16 shows proportions of (A) interchromosome and intrachromosome fusions and (B) fusions supported by structural variants (SV) across NS-LUAD expression subtypes. (C) Summary of types of genes involved in fusions. Circle sizes indicate the numbers of genes. D-E, (D) Numbers of protein-coding gene fusions per sample and (E) numbers of in-frame gene fusions per sample across NS-LUAD expression subtypes. Mean values are indicated by the yellow lines. P-values from two-sided Mann-Whitney U-test are shown.

Supplementary Table S5 shows gene signatures of hallmark genes and lung developmental pathways.

Motivation The accurate and sensitive identification of de novo variants, which are unique to an individual and not found in the parents' germlines, is critical for understanding the genetic basis of rare diseases, developmental disorders, and evolutionary processes. Existing de novo variant detection pipelines often lack the flexibility to handle multiple variant types, struggle with speed and reproducibility across computational environments, demand extensive manual configuration, or require bioinformatics expertise for downstream curation and analysis, limiting their scalability and usability for large genomic studies. Accordingly, there is a pressing need to better address these challenges.Results We introduce TriosCompass, an open-source Snakemake workflow that addresses these challenges by providing a modular, accelerated, and environmentally-configurable end-to-end solution for comprehensive de novo variant discovery. It integrates state-of-the-art tools into a reproducible framework, empowering researchers to discover novel genetic insights with greater efficiency and reliability.Availability TriosCompass is implemented as a Snakemake workflow and is freely available at https://github.com/NCI-CGR/TriosCompass_v2 or on Zenodo (10.5281/zenodo.17981062).Supplementary information Supplementary data is available on GitHub at https://github.com/NCI-CGR/TriosCompass_v2/tree/manuscript/report_dashboards. Supplementary methods on DeepTrio benchmark runs can be viewed at: https://github.com/NCI-CGR/TriosCompass_v2/blob/manuscript/TriosCompass_Supp_Methods_deeptrio_benchmark.md

Abstract Mosaic chromosomal alterations (mCAs), a type of age-related clonal hematopoiesis, arise from postzygotic chromosomal gains, losses, or copy-neutral loss of heterozygosity (CN-LOH) in hematopoietic cells. DNA methylation serves as a molecular measure of biological aging and can be quantified through methylation-based epigenetic clocks. The extent to which mCAs accelerate epigenetic aging or induce local methylation remodeling is poorly understood. We analyzed 482 cancer-free participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial aged 54-77 at sample collection. Selection was based on mCA status (mCA carriers=261), prior genotyping, adequate DNA age and sex. Illumina MethylationEPIC array data raw IDATs were processed using the ChAMP pipeline with BMIQ normalization and ComBat batch correction. Six established methylation clocks (Horvath2013 and 2018, Hannum, PhenoAge, GrimAge, and DunedinPACE) were implemented using the dnaMethyAge R package to compute residual-based age acceleration. Multivariable linear models adjusted for age, sex, ancestry, smoking, and BMI compared mCA carriers to mCA-free individuals, as well as autosomal, mLOY, mLOX, and multi-mCA subtypes. Immune cell composition was estimated with EpiDISH using the IDOL-optimized FlowSorted.BloodExtended.EPIC reference. To identify local methylation effects, ordinary least squares regression tested per-CpG β-values for differential methylation within mCA-affected regions and functional enrichment was performed using Ingenuity Pathway Analysis (IPA). Across six epigenetic clocks, mCA carriers showed higher epigenetic age acceleration vs mCA-free (e.g., PhenoAge β=3.46, 95% CI 1.670-5.22, p=1.32x10-4), with the largest effect sizes observed for autosomal mCAs. Methylation-based deconvolution of whole blood revealed shifts in leukocyte composition, including higher memory B-cell and lower CD4memory-cell proportions in participants with multiple mCAs (B-cell: β=0.024, p=2.0x10-8; CD4: β=-0.017, p=0.017). Analyses of methylation levels at each CpG site within mCA regions identified 2,553 significant probes (1,973 hypo- and 580 hyper-methylated) with significant clusters visible across several CN-LOH and Gain regions. IPA revealed subtype-specific pathway perturbations, including growth-factor/GPCR signaling in Loss events , NAD biosynthesis and circadian regulation in CN-LOH, and suppressed interferon and TLR signaling in Gain events, with TGFB1 and TNF emerging as key upstream regulators. These findings suggest mCAs are associated with accelerated epigenetic aging, altered immune-cell composition, and localized epigenetic remodeling, with subtype-specific pathway disruptions that may reflect distinct compensatory mechanisms permitting clonal expansion in hematopoietic cells. Citation Format: Corey D. Young, Charles Breeze, Derek W. Brown, Rebecca Lynn Kelly, Kara Marie Barnao, Aubrey K. Hubbard, Amy Hutchinson Hutchinson, BELYNDA HICKS, Aurélie L. Vogt, Wen-Yi Huang, Steven C. Moore, Stephen J. Chanock, Mitchell J. Machiela. Clonal expansion of leukocytes harboring mosaic chromosomal alterations accelerates epigenetic aging and reshapes local DNA methylation [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 1949.

Understanding tumor cell dynamics can improve prognosis and treatment but remains limited for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA sequencing data from 684 NS-LUAD cases and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histologic data further characterized the subtypes. "Steady," marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver gene alterations, is linked to prolonged survival and low immune evasion. "Proliferative" shows high proliferation markers, TP53 mutations, and gene fusions. "Chaotic," with high epithelial-to-mesenchymal transition markers, has the worst prognosis, even within stage I tumors. Lacking known molecular or histologic characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the classification and predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving early-stage NS-LUAD prognostication in clinical settings. SIGNIFICANCE:The transcriptome of 684 NS-LUAD identifies three subtypes with different cellular dynamics and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a potential clinically applicable tool for treatment decision-making in patients with NS-LUAD. See related commentary by Azizi et al., p. 423.

Supplementary Table S10 shows NS-LUAD expression subtypes predicted by the 60-gene signature in the GIS cohort.

Supplementary Figure S3 shows consensus matrix for NMF rank 2 to 10.

Supplementary Table S8 shows centroids of the 60-gene signature for the classification of NS-LUAD expression subtype.

Approximately 10% of cutaneous malignant melanoma cases are familial. Variants in CDKN2A account for up to 40% of melanoma-prone families, with an additional ~10% explained by other genes. Many CDKN2A mutation-negative families show linkage to chromosome-band 9p21, which harbors CDKN2A, suggesting non-coding variants may contribute to familial risk. Here, whole-genome sequencing revealed a novel 100 kb deletion mapping to 9p21 in a gene-desert region, 205 kb from CDKN2A, cosegregating in a four-case family from Genoa, Italy. The deletion overlaps melanocyte enhancers that interact with the promoters of CDKN2A p16 and p14 transcripts and is predicted to reduce p16 expression. Using a nearby rare exonic variant in MTAP (rs755147810) on the deletion haplotype, we searched for deletion carriers in WES data from high-risk melanoma patients and controls and identified 22 cases and a single control carrying rs755147810 and the deletion. The association with melanoma in case-control analysis was highly significant (3,319 cases and 5,680 controls; P=1.27x10-6; OR=27.50). We observe loss-of-heterozygosity of the wild-type allele in a carrier’s tumor sample. The founder haplotype with the most recent common ancestor dates approximately 26 generations, broadly overlapping the period when Italy was struck by devastating outbreaks of plague that decimated the population creating a genetic bottleneck. Our results provide evidence of a high-penetrance intergenic variant conferring melanoma susceptibility, with potential for genetic screening of high-risk individuals.

Supplementary Figure S12 shows violin plots that depict signature genes for (A-B) fibroblasts (COL1A1, PDGFRA), (C) epithelial cells (EPCAM), (D-E) AT2 cells (SFTPB, SFTPC), (F-G) basal cells (KRT17, FHL2), (H-I) COL10A1+ and COL4A1+ cancer associated fibroblasts (COL10A1, COL4A1) and (J) non-malignant fibroblasts (VEGFD). Mean values are indicated by the yellow lines. P-values from two-sided Mann-Whitney U-test are shown.

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 Background: The tumor immune microenvironment (TIME) reflects both tumor-intrinsic biology and host-modifiable factors. Characterizing how tumor features, body mass index (BMI), and reproductive history relate to immune activity may help explain heterogeneity in breast cancer and inform precision prevention and survivorship strategies. Methods: We analyzed 461 invasive breast tumors from Kenyan patients using a custom NanoString nCounter® immune-focused gene panel. Intrinsic subtypes were assigned with PAM50, and immune cell composition (relative proportions for 22 immune cells) was estimated by CIBERSORTx. Composite immune activity scores were derived to represent functional modules: z_hot (CD8+, M1 macrophages, NK activated, T follicular helper) and z_suppression (Treg + M2 macrophages) from CIBERSORTx; z_cytotoxic (GZMB, PRF1), z_exhaustion (PDCD1, LAG3, CTLA4), and z_checkpoint (PDCD1, PDCD1LG2, CTLA4, LAG3) from GSVA signatures. Associations between immune scores and tumor features (PAM50 subtypes, risk of recurrence (ROR), RNA-based TP53 status, tumor grade) or host factors (BMI, menopausal status, parity, breastfeeding) were evaluated in age-adjusted linear regression models. Independent effects of host factors were further examined in multivariable regression models adjusted for tumor characteristics and lifestyle covariates. Multiple testing was accommodated using a false discovery rate adjusted p-values. Results: Participants had a mean age of 50.3 years; 43.8% of tumors were luminal A and 21.5% basal-like. Most women were overweight/obese (BMI ≥ 25, 73.1%) and 65.7% had ≥ 3 children. High-grade, basal-like, high-ROR, and TP53 mutant-like tumors showed strong evidence of elevated z_hot, z_cytotoxic, z_checkpoint, and z_exhaustion scores (BH-adjusted p < 0.001), along with modestly lower z_suppression in basal-like and TP53 mutant-like tumors (p < 0.05), indicating an active TIME characteristic of aggressive tumors. In contrast, established BC risk factors showed weaker influence on TIME. Overweight/obese patients were more likely to have cold TIME (lower CD8 (p = 0.09), T follicular helper (p < 0.05), and z_hot score (p < 0.05)), while patients with longer duration of breastfeeding had more active TIME (higher T follicular helper and z_cytotoxicity; lower M2 macrophages and z_suppression (all p < 0.05)). Conclusions: Tumor-intrinsic subtype classification remains the dominant determinant of immune heterogeneity, while established BC risk factors (BMI and reproductive risk factors) may modulate immune responsiveness. Integrating tumor, reproductive, and lifestyle data can help clarify immune variation across diverse populations. Citation Format: Li Feng, Amber N. Hurson, Shahin Sayed, Hela Koka, Viviane Oluoch, Veronica Ngundo, Alfred Mburu Githuka, Zaitun Ajuoga, Shaoqi Fan, Kristine Jones, Belynda Hicks, Amy Hutchinson, Maria Brown, Petra Lenz, Aaron M. Rozeboom, Difei Wang, Francis Makokha, Stefan Ambs, Jonine D. Figueroa, Ruth M. Pfeiffer, Xiaohong Rose Yang. Tumor and Host Determinants of the Breast Tumor Immune Microenvironment in Kenyan Breast Cancer Women [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 7606.

10556 Background: Mosaic chromosomal alterations (mCAs) are age-associated clonal events detectable in peripheral blood and have been linked to hematologic malignancy risk and adverse clinical outcomes. Whether mCAs are associated with accelerated biological aging, as measured by DNA methylation–based epigenetic clocks, remains poorly understood. Methods: We analyzed peripheral blood DNA methylation data generated using the Illumina EPIC array from 482 participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. mCAs were identified from SNP array data and classified by subtype, including autosomal copy-neutral loss of heterozygosity (CN-LOH), gains, losses, and loss of the sex chromosome . Epigenetic age was estimated using six established DNA methylation clocks: Hannum, Horvath pan-tissue/skin and blood, PhenoAge, GrimAge & DunedinPACE. Associations between mCA presence, mCA subtype, clonal burden, and epigenetic age acceleration were evaluated using multivariable linear regression models adjusted for age, sex, smoking status, body mass index, and genetic ancestry. Results: Among 482 participants, 261 were mCA-free and 221 had at least one detectable mCA. Individuals with any detectable mCA exhibited higher epigenetic age acceleration than mCA-free individuals across multiple clocks, with the most consistent effect sizes across mCA subtypes observed for GrimAge. Although age acceleration was directionally higher among individuals with mCAs across all non–rate-based clocks, statistically significant differences were observed only for the Hannum, PhenoAge, and GrimAge clocks. For GrimAge, estimated effects for mCA-positive individuals were uniformly positive, except for gain-only events, with effect sizes ranging from 1.2 to 1.9 years of age acceleration. Age acceleration increased with clonal burden: participants with multiple mCAs (n = 51) exhibited greater age acceleration than those with a single mCA (n = 170), particularly for GrimAge and PhenoAge. Higher cellular fraction was also associated with increased age acceleration, with significant associations observed for GrimAge (β = 2.97, 95% CI 0.82–5.12, p = 0.007) and Hannum (β = 4.25, 95% CI 1.14–7.37, p = 0.008) clocks. Conclusions: Mosaic chromosomal alterations, particularly CN-LOH and higher clonal burden states, are associated with accelerated biological aging in peripheral blood leukocytes. Epigenetic age acceleration was most consistently observed using GrimAge, a mortality- and healthspan-associated clock, with more variable and less consistent associations observed for chronological age-trained and rate-based clocks. These findings suggest that epigenetic age acceleration may represent a clinically relevant feature of clonal hematopoiesis, warranting further investigation in aging populations. Funded by NCI Contract No. 75N91019D00024.

Despite growing evidence on the impact of intra-tumoral heterogeneity (ITH) in breast cancer (BC), its biological drivers and clinically relevant mitigation strategies remain poorly characterized, particularly in low-resource settings where spatial profiling is rarely applied. To address this gap, we conducted a comprehensive, multiplatform spatial profiling study of BC in a Kenyan population. Using the NanoString GeoMx™ Digital Spatial Profiler, we quantified 44 protein markers across 707 spatially defined, PanCK-segmented Areas of Illumination (AOIs) from 31 tumors. All tumors exhibited measurable ITH, with one-third showing marked heterogeneity. Sixteen patients exhibited two or more intrinsic subtypes within their tumors, three of whom had three subtypes. Immune-related ITH was particularly pronounced for CD8 and CD68. AOI phenotype (epithelium- vs. stroma-rich) emerged as the primary driver of marker variability. Linear mixed-effects (LME) modeling further revealed that intrinsic subtype influenced not only classical subtyping markers (ER, PR, HER2) but also immune and signaling markers including IDO1, S100B, PTEN, and BCL-2. Tissue morphology and spatial neighborhood contributed additional variance, particularly in stroma-rich AOIs, while incorporating AOI spatial coordinates improved model fit and revealed further spatially structured heterogeneity. Nonetheless, over 25

Supplementary Table S7 shows fusion events detected in the Sherlock cohort.

Abstract We previously identified diverse genetic evolutionary patterns in whole-genome sequencing of paired normal tissue adjacent to tumor (NAT) and tumor tissues from Hong Kong breast cancer (HKBC) patients. Here, we investigated whether DNA methylation (DNAm) contributes to NAT heterogeneity and shapes the tumor microenvironment (TME). Genome-wide DNAm profiling was performed on paired NAT and tumor tissues from 188 HKBC patients using the Infinium 850 K array. RNA-seq data were available for 76 NATs and 177 tumors. Cellular composition was inferred using MethylCIBERSORT, CIBERSORTx, and EpiDISH, and histopathologic features were assessed on 115 H&E-stained sections. Unsupervised clustering identified two distinct NAT subtypes with divergent TME characteristics. Cluster 1 ( N = 139) showed higher epithelial and fibroblast content and enrichment of estrogen response pathways. Cluster 2 ( N = 49) exhibited an immune-metabolic phenotype characterized by increased fat and immune cells, stromal disruption, inflammatory pathway activation, and greater macrophage infiltration. Cluster 2 patients also demonstrated significantly younger epigenetic age estimated using multiple epigenetic clocks. These DNAm-defined NAT subtypes and associated TME features were validated in 97 NAT samples from TCGA breast cancer patients. Overall, our findings identify DNAm-driven NAT heterogeneity with distinct TME landscapes, providing new insights into field cancerization and tumor evolution in breast cancer.

Abstract Radioactive fallout from the 1986 Chornobyl accident increased papillary thyroid carcinoma (PTC) risk after childhood exposure. Radiation-induced versus sporadic tumors cannot be distinguished by clinical characteristics, histologic features, or known COSMIC signatures. A recent analysis examined the pattern of DNA damage that generated PTC oncogenic drivers from Chornobyl-exposed and unexposed individuals because such patterns reflect DNA repair mechanisms, e.g., healthy cells engage efficient DNA double-strand break (DSB) repair without substantial DNA loss. PTC with fusion/structural variant (SV) drivers generated from two breakpoints and <20 basepairs (bp) breakpoint gain/loss (Fusion2B<20bp) were consistent with having been caused by radiation (higher frequency with increasing radiation dose, even distribution by sex), whereas fusion/SV-driven PTC with ≥3 breakpoints and ≥1000 bp breakpoint loss (Fusion3B≥1000bp) and BRAFV600E-driven PTC exhibited no radiation dose association and strong female predominance. To investigate radiation dose and sex distributions for additional fusion/SV driver categories and replicate the previous report, we reconstructed thyroid radiation doses and sequenced 244 histologically-confirmed PTCs (Table). Radiation doses were significantly higher for all fusion/SV-driven PTC with <1000 bp breakpoint loss (P=0.0084 to 7.1×1-10), regardless of the number of fusion/SV driver breakpoints, compared with BRAFV600E-PTC, while doses were comparably low for fusion/SV-driven PTC with ≥1000 bp breakpoint loss, albeit based on small numbers. Only the Fusion2B<20bp-PTC replication group had a lower female predominance compared with BRAFV600E-PTC (67.1% vs. 79.0%, P=0.068). These results provide evidence that the amount of gain/loss at the fusion/SV driver breakpoint is a more informative feature than the number of DNA DSBs for distinguishing radiation-induced from sporadic tumors in this dose range. Citation Format: Danielle M. Karyadi, Tetiana I. Bogdanova, Stephen W. Hartley, Vladimir Drozdovitch, Sergii Masiuk, Belynda Hicks, Kristine Jones, Amy Hutchinson, Petra Lenz, Maria Brown, Aaron M. Rozeboom, Elizabeth K. Cahoon, Mykola Chepurny, Liudmyla Yu Zurnadzhy, Vibha Vij, Cari M. Kitahara, Michael Dean, Gayle E. Woloschak, Dale A. Ramsden, Mykola D. Tronko, Stephen J. Chanock, Lindsay M. Morton. Distinguishing radiation-induced from sporadic thyroid cancers after the Chornobyl nuclear power plant accident [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 6293.

Supplementary Figure S9 shows violin plots that depict the LUAD histology scores across tumor stages in (A) all tumors and (B) within steady, proliferativeand chaotic subtypes, respectively. Mean values are indicated by the yellow lines. P-values from ordinal test are shown.