{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T08:06:28Z","timestamp":1789027588969,"version":"build-2803163510"},"reference-count":55,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Drug Development Research"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Aberrant expression of mitochondrial quality regulation genes (MQRGs) is intricately linked to mitochondrial dysfunction and the progression of hepatocellular carcinoma (HCC), highlighting the urgent need for reliable prognostic biomarkers. In this study, we aimed to identify differentially expressed MQRGs from 20 candidate genes by analyzing transcriptomic profiles and clinical records from the TCGA (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009371) and GEO (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009167) datasets. The identified prognostic MQRGs, along with associated subtype differentially expressed genes (DEGs,\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009156), underwent LASSO and multivariate Cox regression analyses to construct a risk model, which was subsequently validated through time\u2010dependent ROC analysis, Kaplan\u2010Meier curves, and in vitro RT\u2010qPCR. Our findings established a robust 4\u2010MQRG signature comprising ANXA10, BAMBI, AKR1B15, and SPINK1, which revealed that patients classified as high risk had significantly shorter overall survival compared to their low\u2010risk counterparts (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001). The predictive accuracy of this signature was noteworthy, yielding 1\u2010, 3\u2010, and 5\u2010year AUCs of 0.725, 0.696, and 0.747 in the training cohort (n\u2009=\u2009243) and 0.676, 0.627, and 0.592 in the testing cohort (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009242), respectively. Furthermore, high\u2010risk scores were associated with distinct immunosuppressive tumor microenvironments and varying sensitivity to systemic therapies. The dysregulated expression of the four genes was corroborated by RT\u2010qPCR and analysis of the HPA database. In conclusion, this validated MQRG\u2010based prognostic signature serves as an accurate tool for survival prediction and risk stratification, thus offering valuable biomarker support for personalized therapeutic approaches in HCC.\n                  <\/jats:p>","DOI":"10.1002\/ddr.70372","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T07:49:38Z","timestamp":1788421778000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mitochondrial Quality Regulation Genes as Prognostic Markers in Hepatocellular Carcinoma: Tumor Microenvironment, Therapeutic Response, and Drug Sensitivity Analysis"],"prefix":"10.1002","volume":"87","author":[{"given":"Binbin","family":"Li","sequence":"first","affiliation":[{"name":"Department of Medical Oncology The Third People's Hospital of Yongzhou Yongzhou 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