The use of patient-derived xenografts and patient-derived organoids in the search for new therapeutic regimens for pancreatic carcinoma. A review.

Patient-derived organoids (PDOs) and xenografts (PDXs) are powerful tools for personalized medicine in pancreatic cancer (PC) research. This study explores the complementary strengths of PDOs and PDXs in terms of practicality, genetic fidelity, cost, and labor considerations. Among other models like 2D cell cultures, spheroids, cancer-on-chip systems, cell line-derived xenografts (CDX), and genetically engineered mouse models (GEMMs), PDOs and PDXs uniquely balance genetic fidelity and personalized medicine potential, offering distinct advantages over the simplicity of 2D cultures and the advanced, but often resource-intensive, GEMMs and cancer-on-chip systems.

Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BID variant with an increased risk of developing the disease (OR = 1.

Targeted panel sequencing of pharmacogenes and oncodrivers in colorectal cancer patients reveals genes with prognostic significance.

Background: Colorectal cancer is still the second leading cause of cancer-related deaths and thus biomarkers allowing prediction of the resistance of patients to therapy and estimating their prognosis are needed. We designed a panel of 558 genes with pharmacogenomics records related to 5-fluorouracil resistance, genes important for sensitivity to other frequently used drugs, major oncodrivers, and actionable genes. We performed a target enrichment sequencing of DNA from tumors and matched blood samples of patients, and compared the results with patient prognosis stratified by systemic adjuvant chemotherapy.

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

Introduction: In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide variants (nsSNVs). When appropriately selected for the purpose of the study, a high predictive performance can be expected. In this feasibility study, we investigate the distribution of nsSNVs with an allele frequency below 5%.

Genes divided according to the relative position of the longest intron show increased representation in different KEGG pathways.

Despite the fact that introns mean an energy and time burden for eukaryotic cells, they play an irreplaceable role in the diversification and regulation of protein production. As a common feature of eukaryotic genomes, it has been reported that in protein-coding genes, the longest intron is usually one of the first introns. The goal of our work was to find a possible difference in the biological function of genes that fulfill this common feature compared to genes that do not.