Cholangiocarcinoma is a rare but highly lethal cancer of the biliary epithelium, marked by heterogeneous molecular subtypes, unclear etiology, and poor five-year survival, highlighting the need for new diagnostic and therapeutic strategies; therefore, this study integrates genomic, transcriptomic, single-cell, methylomic, and molecular-dynamics data to pinpoint pathogenic variants. We performed an integrative multi-omics analysis of publicly available datasets. Somatic variants from 23 tumor samples in The Cancer Genome Atlas were annotated with 11 pathogenicity tools (AUC ≥ 0.86 across EVE, REVEL, SIFT, AlphaMissense, DEOGEN2 were the most stringent). Differential gene expression was assessed in matched bulk RNA-seq (tumor vs. non-tumor) using DESeq2 with Benjamini–Hochberg FDR correction. A single-cell RNA-seq dataset comprising 23,782 cells from an intrahepatic cholangiocarcinoma was clustered with marker genes identified by Wilcoxon rank-sum tests. Illumina 450 K methylation arrays (52 tumors, 12 normal livers) were analyzed with limma and DMRcate to detect differentially methylated probes and regions. AlphaFold3 models of wild-type and MAP2K1R49C were subjected to 50 ns all-atom molecular-dynamics simulations in GROMACS; conformational shifts were quantified by RMSD/RMSF and stability tested with FoldX5. Twenty-four tumor-specific missense variants were detected. The four highest-confidence pathogenic substitutions (EVE, REVEL, SIFT, AlphaMissense, DEOGEN2) occurred in TUBB3, FLNC, ABCA1, and MAP2K1. Bulk RNA-seq confirmed significant dysregulation of these genes and enrichment of extracellular-matrix organization, cytoskeletal remodeling, MAPK signaling, and cholesterol-efflux pathways. Single-cell analysis resolved 23 transcriptionally distinct clusters; proliferative malignant cholangiocytes selectively over-expressed ABCA1 and MAP2K1, indicating tumor-cell specificity. Methylome profiling identified 148,928 DMPs and 7040 DMRs; promoter hypomethylation of TUBB3 and ABCA1 correlated with their transcriptional activation. Substituting Arg-49 with Cys in MAP2K1 dismantles the Arg-centred hydrogen-bond/salt-bridge cluster, reduces hydrophobic packing, and, corroborated by 50 ns MD (Welch’s t = −58.06, p = 3.17 × 10−230) and FoldX5 (ΔΔG = +2.3 kcal mol−1), significantly destabilises the protein, manifesting as higher backbone RMSD and increased local flexibility relative to wild type. This multi-omics, public data-driven synthesis delineates a coherent network of genomic, epigenomic, transcriptomic, and structural vulnerabilities, offering a rational framework for therapeutic targeting of cholangiocarcinoma. This study reveals novel bile duct-associated variations that expand our understanding of cholangiocarcinoma pathogenesis and provide potential targets for precision medicine approaches.

HerCanPred, a machine-learning-based pathogenicity classifier specifically optimized for 63 cancer-predisposition genes, was developed to improve the interpretation of missense variants in hereditary cancer syndromes. This model integrates sequence conservation with structural features derived from AlphaFold2 (AF2) structures. HerCanPred achieved a strong performance, outperforming 23 established predictors. SHAP analysis identified AF2-derived structural features, specifically local pLDDT confidence scores and relative solvent accessible area, as the strongest predictors of variant impact. Benchmarking the strengths and limitations of HerCanPred against existing methods showed that misclassification of pathogenic variants was concentrated in disordered and surface-exposed regions, whereas benign failures were more broadly distributed. HerCanPred and three established predictors were also applied to over 57,000 variants of uncertain significance (VUS) from the same gene set. Notably, 166 VUS were reassigned as pathogenic and 75 as benign, with an enrichment of the NF1, FH, and MLH1 genes. By combining gene-specific training with 3D structural information, HerCanPred provides a robust framework for reducing diagnostic uncertainty. Our findings demonstrate that targeted, structure-aware tools can contribute to resolving VUS, providing a rational basis for systematic variant reinterpretation and more informed medical management in hereditary cancer care.

Mitochondria generate energy through cellular respiration and regulate various cellular processes such as heat production, generation and detoxification of reactive oxygen species, metabolism, apoptosis, and calcium homeostasis. In human cells, large numbers of mitochondria are present, each containing multiple copies of mitochondrial DNA. Variations in mitochondrial DNA have been associated with the onset and progression of various diseases, including neurological, cardiovascular, and metabolic disorders and also several cancers. These variants can be important drivers of cancer and may play a crucial role in tumor development. Additionally, mitochondrial copy number changes and structural variations, such as deletions can be associated with different types of cancer. Therefore, understanding the fundamental mechanisms is highly crucial. The molecular genetic correlations of mitochondrial DNA alterations and cancer, emphasize the importance of mitochondrial integrity in maintaining cellular homeostasis. Gaining knowledge of these associations can help us comprehend cancer processes as well as potential routes for targeted treatments and prevention, while further investigation is still required.