PD-1+ T lymphocyte proportions and hospitalized exacerbation of COPD: a prospective cohort study.

OBJECTIVE: To evaluate the predictive value of PD-1 expression in T lymphocytes for rehospitalization due to acute exacerbations of COPD (AECOPD) in discharged patients. METHODS: 115 participants hospitalized with COPD (average age 71.8 ± 6.0 years) were recruited at Fujian Provincial Hospital. PD1+T lymphocytes proportions (PD1+T%), baseline demographics and clinical data were recorded at hospital discharge. AECOPD re-admission were collected at 1-year follow-up. Kaplan-Meier analysis compared the time to AECOPD readmissions among groups stratified by PD1+T%. Multivariable Cox proportional hazards regression and stratified analysis determined the correlation between PD1+T%, potential confounders, and AECOPD re-admission. ROC and DCA evaluated PD1+T% in enhancing the clinical predictive values of Cox models, BODE and CODEX. RESULTS: 68 participants (59.1%) were AECOPD readmitted, those with AECOPD readmission exhibited significantly elevated baseline PD-1+CD4+T/CD4+T% and PD-1+CD8 + T/CD8 + T% compared to non-readmitted counterparts. PD1+ T lymphocyte levels statistically correlated with BODE and CODEX indices. Kaplan-Meier analysis demonstrated that those in Higher PD1+ T lymphocyte proportions had reduced time to AECOPD readmission (logRank p < 0.05). Cox analysis identified high PD1+CD4+T and PD1+CD8+T ratios as risk factors of AECOPD readmission, with hazard ratios of 1.384(95%CI [1.043-1.725]) and 1.401(95%CI [1.013-1.789]), respectively. Notably, in patients aged < 70 years and with fewer than twice AECOPD episodes in the previous year, high PD1+T lymphocyte counts significantly increased risk for AECOPD readmission(p < 0.05). The AECOPD readmission predictive model, incorporating PD1+T% exhibited superior discrimination to the Cox model, BODE index and CODEX index, AUC of ROC were 0.763(95%CI [0.633-0.893]) and 0.734(95%CI [0.570-0.899]) (DeLong's test p < 0.05).The DCA illustrates that integrating PD1+T% into models significantly enhances the utility in aiding clinical decision-making. CONCLUSION: Evaluation of PD1+ lymphocyte proportions offer a novel perspective for identifying high-risk COPD patients, potentially providing insights for COPD management. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR, URL: www.chictr.org.cn/ ), Registration number: ChiCTR2200055611 Date of Registration: 2022-01-14.

A 4-miRNA signature act as a novel prognostic biomarker in patients with Sarcoma.

BACKGROUND: A sarcoma is a rare form of cancer that can develop throughout the body and has a poor prognosis. Micro RNA may be used as molecular markers in sarcoma patients to predict patient outcomes. METHODS: In this study, miRNA expression data of sarcoma tissues samples were downloaded from The Cancer Genome Atlas (TCGA) database. The univariable cox regression and log likelihood were performed to screen the miRNAs related with prognosis. The Cox proportional hazard regression model was used to establish a multi-gene prognostic model based on the expression value of the miRNAs. The survival curve was created by the KM method. The interaction network and function annotation of the target genes were analyzed to investigate the mechanism of the key miRNAs. RESULTS: Hsa-miR-190b, hsa-miR-3170, hsa-miR-4762, hsa-miR-18a were identified and used to establish the prediction model. The target genes of the 4 miRNAs were involved in cancer signaling pathways as revealed by KEGG. Cox regression analysis showed that the prognostic model of miRNA was an independent influencing factor in Sarcoma patients (P<0.05). Survival analysis confirmed that the overall survival rate of sarcoma patients with low risk scores was significantly higher than those with high risk scores (P<0.01). CONCLUSIONS: The miRNA prognosis model established in this study can be used to predict the prognosis of Sarcoma patients, and these 4 miRNAs may involve in cancer signaling pathways by regulating these target genes.