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The main gene involved in gastric cancer (GC) predisposition is , the pathogenic variants of which are associated with diffuse-type gastric cancer (DGC) and lobular breast cancer (LBC). only explains a fraction (10-50%) of patients suspected of DGC/LBC genetic predisposition. To identify novel susceptibility genes, thus improving the management of families at risk, we performed a multigene panel testing on selected patients. We searched for germline pathogenic variants in 94 cancer-related genes in 96 GC or LBC Italian patients with early-onset and/or family history of GC. We found pathogenic variants in 10.4% of patients. In 11.5% of cases, we identified loss-of-function variants in , , , and breast/ovarian cancer susceptibility genes, as well as in , , , , and genes. In 78.1% of patients, we did not find any variants with clear-cut clinical significance; however, 37.3% of these cases harbored rare missense variants predicted to be damaging by bioinformatics tools. Multigene panel testing decreased the number of patients that would have otherwise remained genetically unexplained. Besides , our results demonstrated that GC pathogenic variants are distributed across a number of susceptibility genes and reinforced the emerging link between gastric and breast cancer predisposition.
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http://dx.doi.org/10.3390/cancers11091340 | DOI Listing |
Circ Genom Precis Med
September 2025
Feinberg School of Medicine, Northwestern University, Chicago, IL (Z.C., P.G., A.G., G.W.).
Background: Genetic variation contributes to atrial fibrillation (AF), but its impact may vary with age. The Research Program contains whole-genome sequencing of data from 100 574 adult participants with linked electronic health records.
Methods: We assessed clinical, monogenic, and polygenic associations with AF in a cross-sectional analysis, stratified by age: <45 years (n=22 290), 45 to 60 years (n=26 805), and >60 years (n=51 659).
Biotechnol J
September 2025
Department of Molecular Biosciences and Bioengineering, University of Hawai'i at Mānoa, Honolulu, Hawai'i, USA.
CRISPR technologies are rapidly transforming agriculture by enabling precise and programmable modifications across a wide range of organisms. This review provides an overview of CRISPR applications in crops, livestock, aquaculture, and microbial systems, highlighting key advances in sustainable agriculture. In crops, CRISPR has accelerated the improvement of traits such as drought tolerance, nutrient efficiency, and pathogen resistance.
View Article and Find Full Text PDFHGG Adv
September 2025
Department of Medicine IV, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany; Medizinische Genetik Mainz, Limbach Genetics, Mainz, Germany. Electronic address:
Cystic kidney disease and related ciliopathies are caused by pathogenic variants in genes that commonly result in ciliary dysfunction. For a substantial number of individuals affected by those cilia-related diseases, the causative gene still remains unknown. Using massively parallel sequencing, we here identified a pathogenic bi-allelic variant in the gene encoding PALS1-Associated Tight Junction Protein (PATJ; also known as Inactivation-No-Afterpotential D-Like, INADL) in an individual with ciliopathy.
View Article and Find Full Text PDFGynecol Endocrinol
December 2025
National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Objective: To expand the clinical phenotype associated with MYRF mutations in disorders of sex development (DSDs).
Methods: We present a case of a 17-year-old patient with a female phenotype who presented with primary amenorrhea.
Results: The patient's external genitalia was entirely female in appearance, though there was no opening of vagina below the orifice of urethra.
Immunol Res
September 2025
Department of Immunology and Allergy, Faculty of Medicine, Necmettin Erbakan University, Konya, Türkiye.
Background: Variants of uncertain significance (VUS) represent a major diagnostic challenge in the interpretation of genetic testing results, particularly in the context of inborn errors of immunity such as severe combined immunodeficiency (SCID). The inconsistency among computational prediction tools often necessitates expensive and time-consuming wet-lab analyses.
Objective: This study aimed to develop disease-specific, multi-class machine learning models using in silico scores to classify SCID-associated genetic variants and improve the interpretation of VUS.