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Association between the LINC00673 rs11655237 C> T polymorphisms with cancer risk in the Chinese population: A meta-analysis

Objectives: The present study aimed to conduct a meta-analysis of previously published studies in order to clarify the association of long noncoding RNA (lncRNAs) LINC00673 rs11655237 C> T polymorphism with… Click to show full abstract

Objectives: The present study aimed to conduct a meta-analysis of previously published studies in order to clarify the association of long noncoding RNA (lncRNAs) LINC00673 rs11655237 C> T polymorphism with cancer risk. Design: Systematic review and meta-analysis. Setting: Electronic databases of PubMed, EMBASE, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, and Wanfang Database were used to search relevant studies. Studies published up to October 20, 2019 were included. The included studies were assessed in the following genetic model: allelic model, homozygote model, Heterozygote model, dominant model, recessive model. Data syntheses were conducted using STATA 12.0. Participants: Participants with various types cancers were included. Primary and secondary outcome measures: Odds ratio (ORs) and 95% confidence interval (CIs) were calculated to assess the risk of tumor. Results: Seven articles including 7 case-control studies, 7423 cases and 11,049 controls were adopted for meta-analysis. Our result demonstrated that LINC00673 rs11655237 C> T was related to the cancer among all model including allelic model (T vs C: pooled OR = 1.24, 95% CI = 1.16–1.41, P < .001), homozygous model (TT vs CC: pooled OR=1.54, 95% CI = 1.36–1.76, P < .001), heterozygous model (CT vs CC: pooled OR=1.24, 95% CI = 1.16–1.32, P < .001), dominant model (CT + TT vs CC: pooled OR=1.28, 95% CI = 1.20–1.36, P < .001) and recessive model (TT vs CT+ CC: pooled OR=1.42, 95% CI = 1.25–1.61, P < .001). Subgroup analysis also demonstrated that polymorphisms at this site also increased the risk of neuroblastoma. Conclusions: Our results find that rs11655237 contributed to occurrence of cancer in all models in Chinese population.

Keywords: meta analysis; linc00673 rs11655237; risk; analysis; model; cancer

Journal Title: Medicine
Year Published: 2022

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