Citations

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.

This review explores how multimodal foundation models (MFMs) are transforming biliary tract cancer (BTC) research. BTCs are aggressive malignancies with poor prognosis, presenting unique challenges due to difficult diagnostic methods, molecular complexity, and rarity. Importantly, intrahepatic cholangiocarcinoma (iCCA), perihilar cholangiocarcinoma (pCCA), and distal bile duct cholangiocarcinoma (dCCA) represent fundamentally distinct clinical entities, with iCCA presenting as mass-forming lesions amenable to biopsy and targeted therapies, while pCCA manifests as infiltrative bile duct lesions with challenging diagnosis and primarily palliative management approaches. MFMs offer potential to advance research by integrating radiological images, histopathology, multi-omics profiles, and clinical data into unified computational frameworks, with applications tailored to these distinct BTC subtypes. Key applications include enhanced biomarker discovery that identifies previously unrecognizable cross-modal patterns, potential for improving currently limited diagnostic accuracy—though validation in BTC-specific cohorts remains essential—accelerated drug repurposing, and advanced patient stratification for personalized treatment. Despite promising results, challenges such as data scarcity, high computational demands, and clinical workflow integration remain to be addressed. Future research should focus on standardized data protocols, architectural innovations, and prospective validation studies. The integration of artificial intelligence (AI)-based methodologies offers new solutions for these historically challenging malignancies. However, current evidence for BTC-specific applications remains largely theoretical, with most studies limited to proof-of-concept designs or related cancer types. Comprehensive clinical validation studies and prospective trials demonstrating patient benefit are essential prerequisites for clinical implementation. The timeline for evidence-based clinical adoption likely extends 7–10 years, contingent on successful completion of validation studies addressing current evidence gaps.

The integration of artificial intelligence (AI) in medical imaging has revolutionized diagnostic capabilities, yet the black-box nature of deep learning models poses significant challenges for clinical adoption. Current explainable AI (XAI) approaches, including SHAP, LIME, and Grad-CAM, predominantly focus on post hoc explanations that may inadvertently undermine clinical decision-making by providing misleading confidence in AI outputs. This paper presents a systematic review and meta-analysis of 67 studies (covering 23 radiology, 19 pathology, and 25 ophthalmology applications) evaluating XAI fidelity, stability, and performance trade-offs across medical imaging modalities. Our meta-analysis of 847 initially identified studies reveals that LIME achieves superior fidelity (0.81, 95% CI: 0.78–0.84) compared to SHAP (0.38, 95% CI: 0.35–0.41) and Grad-CAM (0.54, 95% CI: 0.51–0.57) across all modalities. Post hoc explanations demonstrated poor stability under noise perturbation, with SHAP showing 53% degradation in ophthalmology applications (ρ = 0.42 at 10% noise) compared to 11% in radiology (ρ = 0.89). We demonstrate a consistent 5–7% AUC performance penalty for interpretable models but identify modality-specific stability patterns suggesting that tailored XAI approaches are necessary. Based on these empirical findings, we propose a comprehensive three-pillar accountability framework that prioritizes transparency in model development, interpretability in architecture design, and a cautious deployment of post hoc explanations with explicit uncertainty quantification. This approach offers a pathway toward genuinely accountable AI systems that enhance rather than compromise clinical decision-making quality and patient safety.

ABSTRACT The International Consensus Conference “Optimising Performance of the Elite Athlete,” held in November 2024, brought together 29 scientists, some coaches, and athletes to establish evidence‐based consensus statements aimed at enhancing elite athletic performance and health. The conference addressed critical themes including training strategies, nutrition, female athlete considerations, injury management, and emerging technologies. Key conclusions emphasize individualized, sport‐specific approaches to training and nutrition, integrating concurrent training modalities to improve endurance, resilience, and efficiency. Nutrition strategies highlight the importance of tailored energy and macronutrient periodization, recognition of low energy availability risks, and cautious use of dietary supplements. Special attention was directed to female athletes, advocating for improved monitoring of menstrual cycles and hormonal status, while acknowledging current knowledge gaps in hormonal influences on performance and injury risk. Injury prevention remains a challenge, with tendon overuse and Achilles tendon ruptures significantly impacting athlete careers; rehabilitation should rely on criteria‐based progression and multidisciplinary input. Emerging technologies, including wearable sensors and multi‐omics analyses, hold promise for personalized training and nutrition but require further validation in elite contexts. Despite robust consensus, the panel identified substantial research gaps, particularly regarding female athletes, longitudinal training effects, and efficacy of novel interventions. This consensus provides a practical, scientifically grounded framework to optimize elite athlete performance and health, while underscoring the need for continued research to address outstanding questions and promote inclusive evidence‐based practices.

Congenital myopathies are a vast group of genetic muscle diseases. Among the causes are mutations in the MYH2 gene resulting in truncated type IIa myosin heavy chains (MyHCs). The precise cellular and molecular mechanisms by which these mutations induce skeletal muscle symptoms remain obscure. Hence, in the present study, we aimed to explore whether such genetic defects would alter the presence as well as the post-translational modifications of MyHCs and the functionality of myosin molecules. For this, we dissected muscle fibers from four myopathic patients with MYH2 truncating mutations and from five human healthy controls. We then assessed 1) MyHCs presence/post-translational modifications using LC/MS; 2) relaxed myosin conformation and concomitant ATP consumption with a loaded Mant-ATP chase setup; 3) myosin activation with an unloaded in vitro motility assay; and 4) cellular force production with a myofiber mechanical setup. Interestingly, the type IIa MyHC with one additional acetylated lysine (Lys35-Ac) was present in the patients. This was accompanied by 1) a higher ATP demand of myosin heads in the disordered-relaxed conformation; 2) faster actomyosin kinetics; and 3) reduced muscle fiber force. Overall, our findings indicate that MYH2 truncating mutations impact myosin presence/functionality in human adult mature myofibers by disrupting the ATPase activity and actomyosin complex. These are likely important molecular pathological disturbances leading to the myopathic phenotype in patients.

Intrahepatic cholangiocarcinoma remains a highly heterogeneous malignancy that has eluded effective patient stratification to date. The extent to which such heterogeneity can be influenced by individual driver mutations remains to be evaluated. Here, we analyzed genomic (whole‐exome sequencing, targeted exome sequencing) and epigenomic data from 496 patients and used the three most recurrently mutated genes to stratify patients ( IDH , KRAS , TP53 , “undetermined”). Using this molecular dissection approach, each subgroup was determined to possess unique mutational signature preferences, comutation profiles, and enriched pathways. High‐throughput drug repositioning in seven patient‐matched cell lines, chosen to reflect the genetic alterations specific for each patient group, confirmed in silico predictions of subgroup‐specific vulnerabilities linked to enriched pathways. Intriguingly, patients lacking all three mutations (“undetermined”) harbored the most extensive structural alterations, while isocitrate dehydrogenase mutant tumors displayed the most extensive DNA methylome dysregulation, consistent with previous findings. Conclusion : Stratification of intrahepatic cholangiocarcinoma patients based on occurrence of mutations in three classifier genes ( IDH , KRAS , TP53 ) revealed unique oncogenic programs (mutational, structural, epimutational) that influence pharmacologic response in drug repositioning protocols; this genome dissection approach highlights the potential of individual mutations to induce extensive molecular heterogeneity and could facilitate advancement of therapeutic response in this dismal disease. (H epatology 2018).

Abstract Cholangiocarcinomas are rare but aggressive cancers, with an increasing incidence and a dismal 5-year survival rate of less than 5%. Mutations in the genes encoding isocitrate dehydrogenase, IDH1 and IDH2, have been reported in ∼70% of gliomas, ∼20% of myeloid leukemias, ∼56% of chondrosarcomas, and ∼10% of melanomas. We discovered IDH1 and IDH2 mutations in 29 of 305 (9%) intrahepatic cholangiocarcinomas. Tumors with mutations in IDH1 or IDH2 had lower 5-hydroxymethylcytosine and higher 5-methylcytosine levels, as well as increased dimethylation of histone H3K79. Mutations in IDH1 or IDH2 were independently associated with longer time to recurrence of cholangiocarcinoma in multivariate analysis (p = 0.046). We identified 2,267 genes that were significantly hypermethylated in tumors with mutations in IDH1 or IDH2. Hypermethylated CpG sites were significantly enriched in CpG shores and in the 1500 bp upstream of annotated transcription start sites, suggesting a global regulation of transcriptional potential. Gene expression profiling of 7 IDH1/2-mutant and 20 IDH1/2-wildtype tumors revealed increased expression of citric acid cycle and oxidative phosphorylation enzymes, as well as decreased expression of cytoskeleton organization genes. Integrated analyses of DNA methylation and gene expression identified interleukin-6 and several of its downstream targets as candidates for silencing by DNA methylation. Conclusions: Cholangiocarcinomas with mutations in IDH1 or IDH2 represent a molecular subclass with distinct signaling pathway alterations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1058. doi:1538-7445.AM2012-1058