Background: Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant cancers worldwide, with poor survival. Experimental evidence implies that glycolysis/hypoxia is associated with HNSCC. In this study, we aimed to construct a novel glycolysis-/hypoxia-related gene (GHRG) signature for survival prediction of HNSCC.
Methods: A multistage screening strategy was used to establish the GHRG prognostic model by univariate/least absolute shrinkage and selection operator (LASSO)/step multivariate Cox regressions from The Cancer Genome Atlas cohort. A nomogram was constructed to quantify the survival probability. Correlations between risk score and immune infiltration and chemotherapy sensitivity were explored.
Results: We established a 12-GHRG mRNA signature to predict the prognosis in HNSCC patients. Patients in the high-risk score group had a much worse prognosis. The predictive power of the model was validated by external HNSCC cohorts, and the model was identified as an independent factor for survival prediction. Immune infiltration analysis showed that the high-risk score group had an immunosuppressive microenvironment. Finally, the model was effective in predicting chemotherapeutic sensitivity.
Conclusions: Our study demonstrated that the GHRG model is a robust prognostic tool for survival prediction of HNSCC. Findings of this work provide novel insights for immune infiltration and chemotherapy of HNSCC, and may be applied clinically to guide therapeutic strategies.
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http://dx.doi.org/10.1002/jgm.3670 | DOI Listing |
IUBMB Life
January 2025
Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
Triple-negative breast cancer (TNBC) remains a significant global health challenge, emphasizing the need for precise identification of patients with specific therapeutic targets and those at high risk of metastasis. This study aimed to identify novel therapeutic targets for personalized treatment of TNBC patients by elucidating their roles in cell cycle regulation. Using weighted gene co-expression network analysis (WGCNA), we identified 83 hub genes by integrating gene expression profiles with clinical pathological grades.
View Article and Find Full Text PDFUnited European Gastroenterol J
January 2025
"Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania.
The rising incidence of pancreatic diseases, including acute and chronic pancreatitis and various pancreatic neoplasms, poses a significant global health challenge. Pancreatic ductal adenocarcinoma (PDAC) for example, has a high mortality rate due to late-stage diagnosis and its inaccessible location. Advances in imaging technologies, though improving diagnostic capabilities, still necessitate biopsy confirmation.
View Article and Find Full Text PDFInt J Gynaecol Obstet
January 2025
Department of Gynecology and Obstetrics, West China Second Hospital, Sichuan University, Chengdu, People's Republic of China.
Background: In 2013, The Cancer Genome Atlas Research Network suggested that endometrial carcinoma patients may be reclassified into four molecular prognostic groups.
Objective: To compare survival of endometrial carcinoma patients with different mutational profiles.
Search Strategy: Studies reporting survival of endometrial carcinoma patients were identified through systematic searches of four databases.
Eur J Med Res
January 2025
Department of Rehabilitation Medicine, The Affiliated Hospital of Yunnan University, No. 176 Qingnian Road, Wuhua District, Kunming, Yunnan, China.
Background: Stress hyperglycemia ratio (SHR) has been linked to prognosis of cerebrovascular diseases. Nevertheless, the association between SHR and severe disturbance of consciousness (DC) and mortality among patients with cerebral infarction remains explored. This study seeks to assess the predictive potential of SHR for severe DC and mortality among patients with cerebral infarction.
View Article and Find Full Text PDFBMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
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