Variant of SNPs at lncRNA NEAT1 contributes to gastric cancer susceptibility in Chinese Han population

Evaluation of polygenic risk score for risk prediction of gastric cancer

Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated.

Association Between Genetic Polymorphisms of lncRNA NEAT1 and Pulmonary Tuberculosis Risk, Clinical Manifestations in a Chinese Population

Background

Recent studies have shown that abnormal expression of lncRNA NEAT1 is associated with the progression of pulmonary tuberculosis (PTB). The aim of our study was to analyze the relationship between single nucleotide polymorphisms (SNPs) of NEAT1 gene and susceptibility to PTB.

Methods

Four SNPs (rs2239895, rs3741384, rs3825071, rs512715) in NEAT1 gene were genotyped in 479 patients with PTB and 476 controls by improved multiple ligase detection reaction (iMLDR) in a Chinese population.

Results

We found no significant differences in allele and genotype frequencies of NEAT1 gene rs2239895, rs3741384, rs3825071, rs512715 between PTB patients and controls (all P > 0.05). There was no statistically significant association between genotype frequency distribution of dominant model, as well as recessive model, and genetic susceptibility to PTB patients (all P > 0.05). The TT genotype, T allele frequencies of rs3825071 were significantly increased in sputum smear-positive PTB patients when compared to sputum smear-negative PTB patients (P = 0.010, P = 0.003, respectively). Haplotype analysis shown that NEAT1 haplotype frequency was not associated with PTB susceptibility.

Conclusion

NEAT1 gene polymorphisms were not associated with the risk of PTB in Chinese population, and rs3825071 polymorphism might be related to sputum smear-positive in PTB patients.

Role of Long Non-Coding RNA Polymorphisms in Cancer Chemotherapeutic Response

Genetic polymorphisms are defined as the presence of two or more different alleles in the same locus, with a frequency higher than 1% in the population. Since the discovery of long non-coding RNAs (lncRNAs), which refer to a non-coding RNA with a length of more than 200 nucleotides, their biological roles have been increasingly revealed in recent years. They regulate many cellular processes, from pluripotency to cancer. Interestingly, abnormal expression or dysfunction of lncRNAs is closely related to the occurrence of human diseases, including cancer and degenerative neurological diseases. Particularly, their polymorphisms have been found to be associated with altered drug response and/or drug toxicity in cancer treatment. However, molecular mechanisms are not yet fully elucidated, which are expected to be discovered by detailed studies of RNA–protein, RNA–DNA, and RNA–lipid interactions. In conclusion, lncRNAs polymorphisms may become biomarkers for predicting the response to chemotherapy in cancer patients. Here we review and discuss how gene polymorphisms of lncRNAs affect cancer chemotherapeutic response. This knowledge may pave the way to personalized oncology treatments.