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Background: Small cell lung cancer (SCLC) is an aggressive lung malignancy with high relapse rates and poor survival outcomes. Ferroptosis is a recently identified type of cell death caused by excessive intracellular iron accumulation and lipid peroxidation, which may mediate tumor-infiltrating immune cells to influence anti-cancer immunity. But prognostic value of ferroptosis-related genes and its relationship with the treatment response of immunotherapies in SCLC have not been elucidated.
Methods: The RNA-sequencing and clinical data of SCLC patients were downloaded from the cBioPortal database. A ferroptosis-related prognostic risk-scoring model was constructed based on univariable and multivariable Cox-regression analysis. Kaplan-Meier (K-M) survival curves and receiver operating characteristics (ROC) curves were constructed to assess the sensitivity and specificity of the risk-scoring model. And the correlations between ferroptosis-related prognostic genes and immune microenvironment were explored. The IC50 values of anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC) database and the correlation analysis with the key gene thioredoxin-interacting protein () was performed. In addition, immunohistochemistry (IHC) staining was employed to detect the expression of in 20 SCLC patients who received first-line chemo-immunotherapy. Immunotherapeutic response according to iRECIST (Response Evaluation Criteria in Solid Tumours for immunotherapy trials) were recorded.
Results: We constructed a risk-score successfully dividing patients in the low- and high-risk groups (with better and worse prognosis, respectively). The area under the curve (AUC) of this risk-scoring model was 0.812, showing it had good utility in predicting the prognosis of SCLC. Moreover, ferroptosis-related genes were associated with the degree of immune infiltration of SCLC. Most importantly, we found that the expression was highly correlated with the degree of immune invasion and the efficacy of chemotherapy in combination with immunotherapy in SCLC patients.
Conclusions: The ferroptosis-related prognostic risk-scoring model proposed in this study can potentially predict the prognosis of SCLC patients. may serve as a potential biomarker to predict the prognosis and efficacy of chemotherapy combined with immunotherapy in SCLC patients.
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http://dx.doi.org/10.21037/tlcr-22-408 | DOI Listing |
Am J Prev Cardiol
September 2025
Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, No. 167, North Lishi Road, Xicheng District, Beijing 100037, China.
Background: The Framingham Risk Score for Cardiovascular Disease (FRSCVD), based on the Framingham Heart Study, serves as a foundation for many prediction models. However, its applicability in predicting the long-term prognosis of patients experiencing myocardial infarction with nonobstructive coronary arteries (MINOCA) remains uncertain.
Methods: A cohort of 1158 MINOCA patients was enrolled and stratified into three groups based on 10-year FRSCVD risk.
Environ Pollut
September 2025
Department of Geriatrics, Tianjin Medical University General Hospital, Anshan Road No. 154, Tianjin, 300052, China; Key Laboratory of Post-Trauma Neuro-Repair and Regeneration in Central Nervous System, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin Neurol
This study systematically investigated the association between triclosan (TCS) exposure and Alzheimer's disease (AD) risk via integrated bioinformatics approaches. TCS-AD-related genes were identified using bioinformatics tools and public databases, followed by the screening of key genes through multi-model machine learning algorithms (LASSO, SVM-RFE, RF) to mitigate random errors in small sample sizes. DRD2 was confirmed as the most robust core gene by LASSO confidence interval analysis and SHAP evaluation, while APP and SLC6A3 were validated through cross-method intersection.
View Article and Find Full Text PDFIntroduction: Our study aimed to identify risk factors associated with the survival of gastric cancer patients with Type 2 diabetes mellitus (T2DM) and create a risk-scoring system for predicting their survival probabilities.
Methods: We gathered data from 1,912 individuals with both gastric cancer and T2DM from the Hong Kong Hospital Authority Data Collaboration Laboratory (HADCL), spanning from 2000 to 2020. We used conventional Cox proportional hazards regression and tree-based machine learning algorithms to construct models for prognosis risk prediction.
Catheter Cardiovasc Interv
September 2025
Department of Cardiovascular Medicine, Kyushu University Hospital, Fukuoka, Japan.
Background: Cardiac computed tomography (CT) is a well-established process used to diagnose coronary artery disease; however, its specific advantages in predicting the use of atherectomy devices during percutaneous coronary intervention (PCI) for moderate to severe calcified lesions remain to be determined. This study aimed to develop a risk scoring system for predicting the use of atherectomy devices in PCI on the basis of morphological findings obtained by preoperative cardiac CT.
Methods: In this retrospective, multicenter, observational study, we screened patients who underwent cardiac CT 6 months before PCI for the target lesion.
Pain Med
September 2025
Department of Pharmacy, Inner Mongolia Autonomous Region People's Hospital, Hohhot, 010017, Inner Mongolia, China.
Objective: The transition from hospital to home is a high-risk period for medication errors, particularly in patients receiving opioids. We constructed and validated a Medication Deviation Risk Prediction Model (MDRP) in cancer pain patients during hospital-to-home transition.
Methods: The medication deviation assessment table was constructed to determine whether there was a medication deviation in the MDRP modeling group.