ABSTRACT
The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic ß-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting ß-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to ß-cell dysfunction, we investigated single-cell gene expression changes in ß-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.
ABSTRACT
BACKGROUND: Molecular analysis of advanced tumors can increase tumor heterogeneity and selection bias. We developed a robust prognostic signature for gastric cancer by comparing RNA expression between very rare early gastric cancers invading only mucosal layer (mEGCs) with lymph node metastasis (Npos) and those without metastasis (Nneg). METHODS: Out of 1003 mEGCs, all Npos were matched to Nneg using propensity scores. Machine learning approach comparing Npos and Nneg was used to develop prognostic signature. The function and robustness of prognostic signature was validated using cell lines and external datasets. RESULTS: Extensive machine learning with cross-validation identified the prognostic classifier consisting of four overexpressed genes (HDAC5, NPM1, DTX3, and PPP3R1) and two downregulated genes (MED12 and TP53), and enabled us to develop the risk score predicting poor prognosis. Cell lines engineered to high-risk score showed increased invasion, migration, and resistance to 5-FU and Oxaliplatin but maintained sensitivity to an HDAC inhibitor. Mouse models after tail vein injection of cell lines with high-risk score revealed increased metastasis. In three external cohorts, our risk score was identified as the independent prognostic factor for overall and recurrence-free survival. CONCLUSION: The risk score from the 6-gene classifier can successfully predict the prognosis of gastric cancer.
Subject(s)
Biomarkers, Tumor , Gastric Mucosa , Stomach Neoplasms , Stomach Neoplasms/genetics , Stomach Neoplasms/pathology , Stomach Neoplasms/mortality , Humans , Prognosis , Animals , Mice , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Gastric Mucosa/pathology , Gastric Mucosa/metabolism , Lymphatic Metastasis/genetics , Female , Male , Cell Line, Tumor , Gene Expression Regulation, Neoplastic , Machine Learning , Middle AgedABSTRACT
Immature oocytes enclosed in primordial follicles stored in female ovaries are under constant threat of DNA damage induced by endogenous and exogenous factors. Checkpoint kinase 2 (CHEK2) is a key mediator of the DNA damage response in all cells. Genetic studies have shown that CHEK2 and its downstream targets, p53 and TAp63, regulate primordial follicle elimination in response to DNA damage, however the mechanism leading to their demise is still poorly characterized. Single-cell and bulk RNA sequencing were used to determine the DNA damage response in wildtype and Chek2-deficient ovaries. A low but oocyte-lethal dose of ionizing radiation induces a DNA damage response in ovarian cells that is solely dependent on CHEK2. DNA damage activates multiple ovarian response pathways related to apoptosis, p53, interferon signaling, inflammation, cell adhesion, and intercellular communication. These pathways are differentially employed by different ovarian cell types, with oocytes disproportionately affected by radiation. Novel genes and pathways are induced by radiation specifically in oocytes, shedding light on their sensitivity to DNA damage, and implicating a coordinated response between oocytes and pre-granulosa cells within the follicle. These findings provide a foundation for future studies on the specific mechanisms regulating oocyte survival in the context of aging, as well as therapeutic and environmental genotoxic exposures.