Novel Insights into PGM2L1 as a Prognostic Biomarker in Cholangiocarcinoma: Implications for Metabolic Reprogramming and Tumor Microenvironment Modulation DOI Creative Commons

Guo-Wei Wu,

Yi‐Hsien Hsieh,

Yi‐Chung Chien

et al.

International Journal of Medical Sciences, Journal Year: 2025, Volume and Issue: 22(5), P. 1158 - 1166

Published: Feb. 11, 2025

Cholangiocarcinoma (CCA) is a highly lethal malignancy and the most common adenocarcinoma of hepatobiliary system. PGM2L1 belongs to α-D-phosphohexomutase superfamily functions as glucose 1,6-bisphosphate (G16BP) synthase. There growing evidence provide an association its function cancer metabolism progression. However, molecular mechanisms in CCA development remain lacking evidence. In this study, we found that patients with high expression had poorest prognosis. We identified two methylation sites (cg15214137 cg03699633) within gene their prognostic relevance. further investigated relationship between tumor-infiltrating immune cells, particular focus on neutrophils CCA. Functional enrichment analyses revealed was associated Wnt signaling pathway, glycolytic metabolism, recruitment neutrophils. Collectively, these findings suggest may serve independent biomarker closely linked tumor infiltration metabolic reprogramming

Language: Английский

Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer DOI Creative Commons
Yuan Zeng, Yuhao Chen, Dandan Zhu

et al.

BMC Cancer, Journal Year: 2025, Volume and Issue: 25(1)

Published: Feb. 7, 2025

Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it particularly find a suitable way predict the risk occurrence DVT GC This study aims explore effectiveness using machine learning (ML) assisted radiomics build imaging models for prediction surgery. Included this retrospective were eligible who underwent surgery GC. CT data from these collected and divided into training set validation set. The least absolute shrinkage selection operator (LASSO) algorithm was applied reduce dimensionality variables Four algorithms, known as random forest (RF), extreme gradient boosting (XGBoost), support vector (SVM) naive Bayes (NB), used develop predicting These subsequently validated internal external cohort. LASSO analysis identified 10 variables, based on four ML established, then incorporated with clinical characteristics Among models, RF NB demonstrated highest predictive performance, achieving AUC 0.928, while SVM XGBoost achieved slightly 0.915 0.869, respectively. algorithms information may prove be novel non-invasive

Language: Английский

Citations

0

Knowledge, attitudes, and practices regarding whole-course management among patients with gastrointestinal cancers: a cross-sectional study DOI Creative Commons
Min Huang, Lei Feng,

Huiling Ren

et al.

World Journal of Surgical Oncology, Journal Year: 2025, Volume and Issue: 23(1)

Published: Feb. 10, 2025

This study aimed to investigate the knowledge, attitudes, and practices (KAP) regarding whole-course management among patients with gastrointestinal (GI) cancers. cross-sectional enrolled GI cancers at Inner Mongolia Hospital of Peking University Cancer between November 2023 April 2024. Data were collected through a self-administered questionnaire, which captured demographic information scores on KAP. A total 408 participants included in this study. The mean KAP 10.62 ± 3.14 (out maximum 15), 39.11 4.94 50), 31.35 5.60 40), respectively. Knowledge was positively correlated attitudes (r = 0.307, P < 0.001) 0.417, 0.001), while 0.383, 0.001). structural equation model indicated that knowledge influenced (β 0.573, 0.466, 0.525, Patients demonstrated insufficient moderate suboptimal management. Improvements practice could be achieved by enhancing specialized health education.

Language: Английский

Citations

0

CNPY2 expression as a diagnostic and prognostic biomarker in non-small cell lung cancer DOI
Jiang Xiao, Jun Chen,

Shujun Ding

et al.

Clinical Biochemistry, Journal Year: 2025, Volume and Issue: unknown, P. 110895 - 110895

Published: Feb. 1, 2025

Language: Английский

Citations

0

Optimal early endpoint for second-line or subsequent immune checkpoint inhibitors in previously treated advanced solid cancers: a systematic review DOI Creative Commons

Jingqiu Li,

Xiaoding Zhou,

Lei Wu

et al.

BMC Cancer, Journal Year: 2025, Volume and Issue: 25(1)

Published: Feb. 18, 2025

The administration of second-line or subsequent immune checkpoint inhibitors (ICIs) in previously treated patients with advanced solid cancers has been clinically investigated. However, previous clinical trials lacked an appropriate primary endpoint for efficacy assessment. This systematic review aimed to explore the most optimal early such trials. Phase 2 3 involving disease progression following standard first-line therapy receiving ICI administration, adequate survival outcome data, were included from PubMed, Embase, Web Science, and Cochrane Library databases before February 2023. Quality assessment was conducted using tool Newcastle–Ottawa Assessment Scale Cohort Studies randomized controlled (RCTs) non-randomized trials, respectively. Objective response rate (ORR) progression-free (PFS) at 3, 6, 9 months investigated as potential candidates 12-month overall (OS), a strong correlation defined Pearson's coefficient r ≥ 0.8. A total 64 RCTs comprising 22,725 106 prospective 10,608 participants eligible modeling external validation, examined 15 different cancer types, predominantly non-small-cell lung (NSCLC) (17, 28%), melanoma (9, 14%), esophageal squamous cell carcinoma (5, 8%). median sample size 124 patients, follow-up time 3.2–57.7 months. ORR (r = 0.38; 95% confidence interval [CI], 0.18–0.54) PFS 0.42; CI, 0.14–0.64) exhibited weak trial-level correlations OS. Within treatment arms, values 3-, 6-, 9-month OS 0.61 (95% 0.37–0.79), 0.78 0.62–0.88), 0.84 0.77–0.90), 0.86 0.79–0.90), External validation 6-month indicated acceptable discrepancy between actual predicted In phase on cancers, could serve endpoint. endpoints are not recommended replace

Language: Английский

Citations

0

Novel Insights into PGM2L1 as a Prognostic Biomarker in Cholangiocarcinoma: Implications for Metabolic Reprogramming and Tumor Microenvironment Modulation DOI Creative Commons

Guo-Wei Wu,

Yi‐Hsien Hsieh,

Yi‐Chung Chien

et al.

International Journal of Medical Sciences, Journal Year: 2025, Volume and Issue: 22(5), P. 1158 - 1166

Published: Feb. 11, 2025

Cholangiocarcinoma (CCA) is a highly lethal malignancy and the most common adenocarcinoma of hepatobiliary system. PGM2L1 belongs to α-D-phosphohexomutase superfamily functions as glucose 1,6-bisphosphate (G16BP) synthase. There growing evidence provide an association its function cancer metabolism progression. However, molecular mechanisms in CCA development remain lacking evidence. In this study, we found that patients with high expression had poorest prognosis. We identified two methylation sites (cg15214137 cg03699633) within gene their prognostic relevance. further investigated relationship between tumor-infiltrating immune cells, particular focus on neutrophils CCA. Functional enrichment analyses revealed was associated Wnt signaling pathway, glycolytic metabolism, recruitment neutrophils. Collectively, these findings suggest may serve independent biomarker closely linked tumor infiltration metabolic reprogramming

Language: Английский

Citations

0