Background Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6‐methyladenosine‐related lncRNAs (m6A‐related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear. Methods Gene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A‐related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed. Results A total of 27 prognostic m6A‐related lncRNAs were identified. These m6A‐related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high‐risk m6A‐related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A‐related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD‐1, PD‐L1, CTLA‐4, LAG‐3, TIM‐3, and TIGIT were significantly increased in the high‐risk patients, and there was a correlation between the risk score and immune cell infiltration. Conclusions The seven m6A‐related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A‐related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.
ObjectivesThis meta-analysis aimed to systematically evaluate the efficacy of acupuncture in treating postsurgical gastroparesis syndrome (PGS) after thoracic or abdominal surgery.DesignSystematic review and meta-analysis.Data sourcesTwelve databases (PubMed, Embase, Cochrane Library Cochrane Central Register of Controlled Trials (CENTRAL), Medline (Ovid) (from 1946), Web of Science, EBSCO, Scopus, Open Grey, China National Knowledge Infrastructure (CNKI), Wanfang Database, Chinese Scientific Journals Database (VIP) and China Biology Medicine disc (CBM)) and three registration websites (WHO International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov, and Chinese Clinical Trial Registry (ChiCTR)) were searched from the inception to September 2022, and citations of the included literature were screened.Eligibility criteriaAll randomised controlled trials addressing invasive acupuncture for PGS.Data extraction and synthesisKey information on the included studies was extracted by two reviewers independently. Risk ratio (RR) with 95% CI was used for categorical data, and mean difference with 95% CI for continuous data. The quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation. Outcomes were conducted with trial sequential analysis (TSA).ResultsFifteen studies with 759 patients met the inclusion criteria. Subgroup analyses revealed that compared with the drug group, the drug and acupuncture group had a greater positive effect on the total effective rate (TER) (nine trials, n=427; RR=1.20; 95% CI 1.08 to 1.32; P-heterogeneity=0.20, I2=28%, p=0.0004) and the recovery rate (RCR) (six trials, n = 294; RR = 1.61; 95% CI 1.30 to 1.98; P-heterogeneity=0.29, I2=19%, p<0.0001) of PGS after abdominal surgery. However, acupuncture showed no significant advantages in terms of the TER after thoracic surgery (one trial, p=0.13) or thoracic/abdominal surgery-related PGS (two trials, n = 115; RR=1.18; 95% CI 0.89 to 1.57; P-heterogeneity=0.08, I2=67%, p=0.24) and the RCR after thoracic/abdominal surgery (two trials, n=115; RR=1.40; 95% CI 0.97 to 2.01; P-heterogeneity=0.96, I2=0%, p=0.07). The quality of evidence for TER and RCR was moderate certainty. Only one study reported an acupuncture-related adverse event, in the form of mild local subcutaneous haemorrhage and pain that recovered spontaneously. TSA indicated that outcomes reached a necessary effect size except for clinical symptom score.ConclusionBased on subgroup analysis, compared with the drug treatment, acupuncture combined drug has significant advantages in the treatment of PGS associated with abdominal surgery, but not with thoracic surgery.PROSPERO registration numberCRD42022299189.
Background: Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. This study uses bioinformatics analysis to identify N6-methyladenosine-related lncRNAs (m6A-related lncRNAs) as new prognostic biomarkers for ccRCC.Methods: Gene expression data and related clinical information of ccRCC patients were extracted from the Cancer Genome Atlas Database. m6A-related lncRNAs were obtained by co-expression analysis. Univariate Cox regression analysis was performed on these lncRNAs to find the prognostic-related m6A-related lncRNAs, and consensus clustering analysis was performed. The prognostic signature was screened by LASSO regression and a prognostic model was constructed. The predictive performance of the prognostic model was evaluated and validated by survival analysis and ROC curve analysis, etc. In addition, we also systematically analyzed the expression of immune checkpoints and immune cell infiltration in ccRCC patients.Results: First, 27 m6A-related lncRNAs associated with prognosis were identified, which were significantly differentially expressed between tumor and normal tissues. Consensus clustering analysis indicated that cluster 2 was associated with poor prognosis, low stromal score, high expression of PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, and immunosuppressive cell infiltration. The signaling pathways related to tumor progression, drug resistance, and angiogenesis and biological processes related to protein methylation and phosphatidic acid metabolism are significantly enriched in cluster 2. Subsequently, LASSO regression analysis was used to construct a prognostic risk model based on 7 m6A-related lncRNAs signature, which can be used as an independent prognostic indicator. After a series of analyses, it was shown that this model had good sensitivity and specificity, can predict the prognosis of patients with different clinical stratifications and was associated with the progression of ccRCC. The expression levels of immune checkpoints were significantly increased in high-risk patients, and there was a certain correlation between the risk score and immune cell infiltration. Conclusions: In summary, we constructed and validated a risk model that can independently predict the prognosis of ccRCC patients and reflect the immune microenvironment based on m6A-related lncRNAs; the model is conducive to the screening of biomarkers of ccRCC prognosis and may have the potential to reflect the response of ccRCCs to immunotherapy.
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