Keming Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Keming Li has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Guiying Sun
Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
1 shared publication - Hua Ye
College of Public Health, Zhengzhou University, Zhengzhou 450001, China
1 shared publication - Jianxiang Shi
Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
1 shared publication - Jianying Zhang
Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Los Angeles, California
1 shared publication - Jinyu Wu
Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
1 shared publication - Peng Wang
College of Public Health, Zhengzhou University, Zhengzhou, China
1 shared publication
Latest Publications
- Open Access
The Relationship between MALAT1 Polymorphism rs3200401 C > T and the Risk of Overall Cancer: A Meta-Analysis
Background and Objectives: At present, the association between the long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) polymorphism rs3200401 C > T and cancer risk remain controversial. The aim of this meta-analysis was to assess the association between rs3200401 C > T and cancer susceptibility. Materials and Methods: The databases of PubMed, EMBASE and Web of Science were searched for literature published in English until 1 September 2021. The odd ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the strength of association in five genetic models. Heterogeneity was assessed using the Q-test and I2 test. Begg’s funnel plot and Egger’s linear regression test were conducted to assess publication bias. Meta-regression analysis was used to explore potential sources of heterogeneity. Trial sequential analysis (TSA) was performed to validate the reliability of the results. Results: A total of 10 case–control studies involving 6630 cases and 7457 controls were included in this study. The pooled ORs showed no significant association between MALAT1 rs3200401 C > T and cancer risk in five genetic models. Similarly, the association was not found in the subgroups of control source, ethnicity and study quality. In the cancer type subgroup, the results demonstrated that the T allele increased the risk of colorectal cancer (CRC) compared with the C allele. (C vs. T: OR, 1.16; 95% CI, 1.01–1.33). Conclusion: In the current meta-analysis, we found no significant association between MALAT1 polymorphism rs3200401 C > T and overall cancer risk. However, the rs3200401 C > T may be linked to a higher risk of CRC, which needs more studies to be further confirmed.
Open AccessThe Relationship between MALAT1 Polymorphism rs3200401 C > T and the Risk of Overall Cancer: A Meta-Analysis
Background and Objectives: At present, the association between the long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) polymorphism rs3200401 C > T and cancer risk remain controversial. The aim of this meta-analysis was to assess the association between rs3200401 C > T and cancer susceptibility. Materials and Methods: The databases of PubMed, EMBASE and Web of Science were searched for literature published in English until 1 September 2021. The odd ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the strength of association in five genetic models. Heterogeneity was assessed using the Q-test and I2 test. Begg’s funnel plot and Egger’s linear regression test were conducted to assess publication bias. Meta-regression analysis was used to explore potential sources of heterogeneity. Trial sequential analysis (TSA) was performed to validate the reliability of the results. Results: A total of 10 case–control studies involving 6630 cases and 7457 controls were included in this study. The pooled ORs showed no significant association between MALAT1 rs3200401 C > T and cancer risk in five genetic models. Similarly, the association was not found in the subgroups of control source, ethnicity and study quality. In the cancer type subgroup, the results demonstrated that the T allele increased the risk of colorectal cancer (CRC) compared with the C allele. (C vs. T: OR, 1.16; 95% CI, 1.01–1.33). Conclusion: In the current meta-analysis, we found no significant association between MALAT1 polymorphism rs3200401 C > T and overall cancer risk. However, the rs3200401 C > T may be linked to a higher risk of CRC, which needs more studies to be further confirmed.