Klippel-Feil syndrome (KFS) is characterized by the developmental failure of the cervical spine and has two dominantly inherited subtypes. Affected individuals who are the children of a consanguineous marriage are extremely rare in the medical literature, but the gene responsible for this recessive trait subtype of KFS has recently been reported.

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.

Amaç: Hücre için başta enerji metabolizması ve yapı taşlarının üretimi olmak üzere oldukça önemli bir role sahip olan mitokondrinin kanserdeki rolü henüz tam olarak bilinmemektedir. Mitokondriyal genomdaki varyasyonlar ve polimorfizm kombinasyonları kullanılarak belirlenen haplogrupların farklı kanserlerdeki etkisi araştırılmaya devam edilmektedir. Bu nedenle, mitokondriyal genomu çoğaltarak yeni nesil yöntemlerle dizileme protokolünü optimize ederek kanser çalışmalarında kullanmayı amaçladık.Materyal ve Metod: Gliom tümör örneklerinden elde edilmiş genomik DNAlar’dan mitokondriyal genom iki ayrı reaksiyon halinde Takara LA Taq DNA polimeraz ile çoğaltılmıştır. “Nextera XT DNA Library Prep Kit” kullanılarak kütüphane oluşturulmuş ve yeni nesil dizileme MiSeq FGx cihazında gerçekleştirilmiştir. Elde edilen veriler “mtDNA Server” veritabanı kullanılarak mitokondriyal varyasyonlar, heteroplazmi oranları ve haplogruplar açısından analiz edilmiştir.Bulgular: Mitokondriyal genom için yeni nesil dizileme protokolü optimize edilmiştir. Detaylı analiz edilen iki tümör örneğinde çeşitli varyasyonlar ve bunların heteroplazmi oranları tespit edilebilmiştir. Ayrıca, örneklere ait haplogruplar da saptanmıştır.Sonuç: Mitokondriyal varyasyonların kanser biyolojisi üzerindeki etkisi hala araştırılmaktadır. Yeni nesil dizileme teknolojileri özellikle heteroplazmi oranı düşük tümörlerin analizinde kullanılabilecek güvenilir bir yöntemdir.