The genetic architecture of lung cancer (LC) varies substantially across populations. However, the limited ancestral diversity of existing discovery cohorts hampers comprehensive characterization of ancestry-specific risk mechanisms and limits the transferability of polygenic risk scores (PRSs) across populations. In addition, the interplay between germline variants and somatic mutations in LC remains poorly characterized. We performed a cross-ancestry genome-wide association meta-analysis (GWMA) studies comprising 53,650 LC cases and 486,210 controls of East Asian (EAS) and European (EUR) ancestry. PRSs of cross-ancestry were developed and validated in the UK Biobank (UKB) and China Kadoorie Biobank (CKB). Fine-mapping and expression quantitative trait locus (eQTL) colocalization were conducted to prioritize candidate susceptibility genes. Gene-set based PRSs were calculated based on pathway enrichment analyses, telomere and smoking-related GWASs and supporting literature, and their association with somatic mutations and prognostic metrics were studied. Functional validation of novel locus was performed to elucidate the mechanisms of LC. Cross-ancestry GWMA identified 36 independent variants across 30 loci, including one novel locus, and revealed remarkable differences in genetic correlations with smoking behaviors between East Asians and Europeans. PRS-CSx derived from the meta-analysis outperformed previous models in both the two biobanks (UKB: HR = 1.27, 95%CI: 1.23-1.31; CKB: HR = 1.26, 95%CI: 1.19-1.34). Susceptibility genes were grouped into four pathways: telomere maintenance, smoking behavior, epithelial cell biology, and DNA damage response. Corresponding gene-set-based PRSs were significantly associated with tumor mutation burden, mutational signatures, key driver mutations, and patient survival. Finally, functional assays further demonstrated that two variants at the novel locus at 16q23.3 regulate MPHOSPH6 expression and protein function, influencing telomere length and LC risk. Our study systematically elucidates the shared and distinct genetic architectures of LC between EAS and EUR populations, introduces PRS-CSx for effective LC risk stratification underscoring its clinical implications across diverse ancestries. Additionally, we uncover a novel mechanism by which functional genetic variants located in MPHOSPH6 contribute to LC susceptibility, and provide comprehensive insights into the interplay between germline and somatic mutations in LC.

Many breast cancer predisposition genes are involved in DNA damage repair, leading to genome instability that can impact immunosurveillance, neoantigen formation, and the composition of the tumor immune microenvironment. Here, we explored associations between germline protein truncating variants (PTVs) in 34 (putative) breast cancer predisposition genes, of which 26 involved in DNA damage repair, with the abundance of four immune cell markers, i.e., CD8 + , FOXP3 + , CD20 + and CD163 + , across 7,969 invasive breast tumors of women of European ancestry. The most apparent associations were those of CD163, a marker of M2-like tumor-associated macrophages, with genes involved in double- and single-strand break DNA repair, and with the 12 known breast cancer predisposition genes combined. Specifically, DNA damage repair genes, BRCA1, BRCA2, PALB2, RAD51D, and MSH6 were associated with a 1.3 to twofold abundance of CD163-positive cells. Estrogen receptor status was found to mediate associations to a limited extent. Our findings support a role of rare pathogenic germline variants involved in DNA damage repair, and particularly those predisposing to breast cancer, in the immune landscape of breast tumors. These insights may help guide the development of immunomodulatory strategies for breast cancer prevention and treatment.

Compared to European American women, African American women are more likely to be diagnosed with triple-negative breast cancer (TNBC). This difference may be partially due to genetic factors. This study aims to investigate associations of African ancestry and risk variants with TNBC among African American women. We used data from 2,335 TNBC cases, 8,159 estrogen receptor (ER)-positive cases, and 9,814 controls included in the African-ancestry Breast Cancer Genetics (AABCG) Consortium. The proportion of African ancestry (%AFR) and local ancestry were estimated using samples from the 1000 Genomes Project as reference. Logistic regressions were performed for case-control (TNBC vs. control) and case-case (TNBC vs. ER-positive) comparisons, adjusted for age, study, genotype principal components 2-5, body mass index, and reproductive factors. Local ancestry-aware association analyses were conducted in 12 TNBC risk loci to identify ancestry-specific risk variants. In case-control analyses, no statistically significant association was found between %AFR and TNBC risk after adjustment for potential confounders. However, TNBC cases had a significantly higher mean % AFR (mean = 0.811, standard deviation, SD = 0.104) compared to ER-positive cases (mean = 0.798, SD = 0.110, P < 0.001). Females with %AFR of ≥ 95% had 1.62 times higher odds (95% confidence interval, CI: 1.16-2.25) of having TNBC rather than ER-positive breast cancer, compared to those with %AFR of 55.0-64.9%. Local ancestry-aware association analyses identified seven subtype-informative variants in or near MDM4, RP11-19E11.1, TERT, MRPL36, TCF7L2, C11orf65, and ANKLE1. All of them were significantly associated with TNBC as compared with ER-positive cases, and six of them were also associated with TNBC risk in case-control analyses. Large allelic odds ratios of 1.25 or higher were found in association with TNBC risk or subtype classification. The risk allele frequency for five of them is substantially higher in haplotypes of African ancestry than those of European ancestry. These findings support a significant role of African-ancestry specific genetic factors in determining breast cancer subtypes and highlight the need for future research to uncover possible pathways driving TNBC susceptibility.

Treating autosomal dominant gene mutations remains challenging, particularly when mutations convey a gain-of-function or a dominant-negative effect, as standard gene supplementation strategies often fail to counteract the pathogenic allele. In this study, we employed human induced pluripotent stem cell-derived retinal pigment epithelium (hiPSC-RPE) to investigate allele-specific CRISPR/Cas9 genome editing as a potential treatment for Best disease (BD), an autosomal dominant macular dystrophy caused by over 250 distinct mutations in the bestrophin-1 (BEST1) gene. We designed and evaluated single guide RNAs (sgRNA) targeting three known BEST1 mutations (p.(R218C), p.(A243V), and p.(I295del)), assessing their impact on BD-associated hiPSC-RPE phenotypes and BEST1 channel function. Computationally predicted sgRNAs were rigorously tested for on-target efficiency, allele specificity and genome-wide off-target activities. We found that shortening sgRNA length improved specificity in some cases, while introducing an additional mismatch generally compromised editing efficiency. Notably, only one of the three mutations yielded an sgRNA with both high cleavage efficiency and undetectable off-target effects in hiPSC-RPE cells. We then explored the consequences of allele-specific editing on BEST1 expression and function in clonal BD hiPSC-RPE lines. Eliminating the mutant BEST1 transcript led to enhanced BEST1 localization, improved protein stability and restoration of anion transport function. Taken together, our findings support allele-specific gene editing as a viable therapeutic strategy for selected BEST1 mutations, while underscoring the necessity for rigorous testing of computationally designed sgRNAs, given their mutation- and context-dependent variability.

Molecular subtypes of lung adenocarcinoma (LUAD) with varying prognosis and characteristics have been proposed based on one or two-dimensional studies but are not yet implemented into clinical routine. Epigenetic modifications in cancer cells are independent of sequence variants, directly linked to gene and genome regulation, and thus provide important information to guide subclassification efforts. We performed in-depth epigenomic profiling of 95 primary LUAD samples from a Swedish discovery cohort with comprehensive clinicopathological, epigenomic, genomic, transcriptomic, proteomic, and metabolomic data. Additionally, we estimated pure tumor cell methylomes using a computational approach. We subdivided the discovery cohort into four epigenetic subtypes, the epitypes, reflecting distinct tumor cell methylation states. Resulting epitypes were contrasted based on clinicopathological and molecular features, and our main findings were validated in two additional primary tumor cohorts totaling over 700 samples. Of the four DNA methylation epitypes, M1-M4, M1 and M4 were associated with the previously proposed mRNA subtypes Terminal Respiratory Unit and Proximal Proliferative, respectively. Epitypes M2 and M3 showed similar mRNA/protein subtype composition but differed with respect to e.g., higher expression of the LUAD histology-associated NAPSA/surfactant metabolism expression metagene in M3. Genes included in this metagene showed lower DNA methylation in M3, counter to a global tendency towards promoter hypermethylation in this epitype. To further delineate tumor intrinsic links between the epigenomic and expression phenotypes, 62 LUAD cell lines classified into the four epitypes were investigated and recapitulated several characteristics from the tumor epitypes, such as methylation and expression pattens of NAPSA/surfactant genes, highlighting epigenetic states as likely drivers or maintainers of broad tumor phenotypes and differentiation states. Dissecting LUAD based on combined biological characteristics using multiomics data has deepened our understanding of the heterogeneity in this complex disease and the mechanisms underlying phenotype formation and maintenance. There remains a critical need for large, publicly accessible, well-annotated multiomic LUAD cohorts to support rigorous subtype discovery and validation, particularly those linked to targeted therapy trial outcomes.