Yujiao Deng

MicroRNA-139-5p (miR-139) has been shown to play important roles in hepatocellular carcinoma (HCC) development. However, the exact mechanism of miR-139 in HCC remains largely unknown. We investigated the function in human cell lines and patient tissue samples by experimental techniques in molecular biology including Co-IP assay, cell viability assay, quantitative real-time-PCR, et al. In addition, datasets were used to verify the results by database analysis. Statistical analysis was performed by using the GraphPad Prism 6 (GraphPad Software Inc., USA). A P value < 0.05 was defined as statistically significant. In this study, we found that miR-139 was significantly down-regulated in HCC. MiR-139 level was negatively associated with the stage of HCC, and HCC patients with higher miR-139 level had longer overall survival (OS) than these having lower miR-139 expression. Overexpression of miR-139 led to reduced cell viability, elevated apoptosis, and decreased colony forming, migratory and invasive capacities in HCC cells, while down-regulation of miR-139 led to opposite phenotypes. MiR-139 also inhibited HCC growth in a xenograft mouse model. We identified karyopherin alpha 2 (KPNA2) as a direct target of miR-139. KPNA2 is up-regulated in HCC and higher KPNA2 level is associated with poor patient prognosis. Silencing of KPNA2 expression led to similar phenotypic changes as miR-139 overexpression. Restoration of KPNA2 attenuated the suppressive effects of miR-139 overexpression on cell viability, apoptosis, colony formation, migration and invasion. In addition, miR-139 overexpression and KPNA2 depletion led to decreased nucleus level of POU class 5 homeobox 1 (POU5F1) and c-myc, two well-known pro-oncogenes. In together, these data revealed the essential roles of the miR-139/KPNA2 axis in HCC.

It is well known that hepatocellular carcinoma (HCC) has been one of the most life-threatening diseases all over the world. Plenty of internal and extrinsic factors have been proven to be related to HCC, such as gene mutation, viral hepatitis, and Nitrosamines. Though previous studies demonstrated that glutathione S-transferase (GST) genotypes are associated with HCC, the conclusions are inconsistent. Therefore, we carried on a renewed meta-analysis to expound the connection between the null GSTM1, GSTT1 polymorphisms and the risk of HCC. We searched PubMed, Web of Science, Embase, and CNKI databases to select qualified researches which satisfied the inclusion criteria up to July 31, 2018. Finally, we selected 41 articles with 6124 cases and 9781 controls in this meta-analysis. We use ORs and 95% confidence interval (CI) to evaluate the correlation intension between the GSTM1 and GSTT1 null genes and the risk of HCC. All the statistical processes were executed by Stata (version 12.0). The pooled analysis showed that both GSTM1 null genotypes (OR = 1.37, 95% CI = 1.18–1.59) and GSTT1 null genotypes (OR = 1.43, 95% CI = 1.23–1.66) increased the risk of HCC. And GSTM1–GSTT1 dual-null genotypes also increased the risk of HCC (OR = 1.58, 95% CI = 1.22–2.05). In the subgroup analysis, we obtained significant results among Asians when stratified by race, and the results are GSTM1 null OR = 1.44, 95% CI = (1.22–1.71), GSTT1 null OR = 1.48, 95% CI = (1.25–1.77), GSTM1–GSTT1 null OR = 1.58, 95% CI = (1.19–2.09), while we didn’t obtain significant results among Caucasians or Africans. Stratified analyses on the type of control indicated a higher risk of HCC associated with GSTM1, GSTT1 single null genotypes and GSTM1–GSTT1 dual-null genotypes in healthy people. No evidence of significant connection was discovered in chronic liver disease (CLD) except in GSTT1 single null. Our study indicated that an individual who carries the GSTM1, GSTT1 single null genotypes and GSTT1–GSTM1 dual-null genotypes is more likely to develop HCC.

Estrogen exposure is a widely known risk factor for BC. And the interaction of estrogen with estrogen receptor (ER) plays an important role in breast cancer development. This case–control study aims to assess the association of genetic polymorphisms in the estrogen receptor genes with breast cancer (BC) susceptibility in Chinese Han women. Four polymorphisms (rs2881766, rs9383951, rs9340799 in ESR1 and rs3020449 in ESR2) were genotyped in 459 patients and 549 healthy controls using the Sequenom MassARRAY method. Odds ratio (OR) and 95% confidence intervals (95% CI) were calculated to evaluate the associations. False-positive report probability (FPRP) was utilized to examine the noteworthiness of significant findings. We observed that rs2881766 was associated with a decreased BC risk (GG vs. TT: OR = 0.63, 95% CI = 0.44–0.91; GG vs. TT/GT: OR = 0.68, 95% CI = 0.49–0.95), while rs3020449 was associated with an increased risk of BC (CT vs. TT: OR = 1.58, 95% CI = 1.21–2.06; CT/CC vs. TT: OR = 1.54, 95% CI = 1.20–1.98; TT/CC vs. CT: OR = 1.48, 95% CI = 1.15–1.90). The other two polymorphisms have no relation with BC susceptibility. In addition, rs2881766 was correlated with lymph node metastasis and ER expression, and rs3020449 was related to tumor size, histological grade and ER expression. The values of false-positive report probability indicated that the significant associations of BC risk with both rs2881766 and rs3020449 were noteworthy. Our study suggests that polymorphisms rs2881766 and rs3020449 in estrogen receptor genes were associated with BC susceptibility as well as clinical features in Chinese women. These findings need further validation in a large population.

Triple-negative breast cancer (TNBC) is a particular breast cancer subtype with poor prognosis due to its aggressive biological behavior and lack of targets for therapy. This study aimed to explore the expression profile and potential function of lncRNAs in TNBC through bioinformatic methods. Two microarrays of TNBC were obtained from the Gene Expression Omnibus database. Differentially expressed lncRNAs and mRNAs were screened out and the expressions of top lncRNAs and overlapping lncRNAs were validated using data from The Cancer Genome Atlas database. The co-expression analysis of lncRNAs and mRNAs was conducted using R software and functional enrichment analysis for was performed by Metascape. Kaplan–Meier Plotter was used for survival analysis. A total of 1034 dysregulated lncRNAs were found in the two microarrays, and there were 8 overlapped lncRNAs. Among them, 537 lncRNAs were significantly correlated with 451 protein-coding genes (PCGs). The co-expressed PCGs were mainly enriched in terms including cell division, cell cycle, and protein/DNA binding, and were involved in pathways in cancer and other pathways such as PI3K-Akt, MAPK, ErbB and p53 signaling pathways. Hub-genes in the co-expression network were identified, and 7 of them were associated with relapse-free survival of TNBC (MAGI2-AS3: HR = 0.51; GGTA1P: HR = 0.54; NAP1L2: HR = 0.59; CRABP2: HR = 0.41; SYNPO2: HR = 0.50; MKI67: HR = 2.23; COL4A6: HR = 1.91; all P < 0.05). Numerous lncRNAs were dysregulated in TNBC, and many of them are possibly involved in cancer biology. Several of these lncRNAs were associated with of TNBC prognosis, which can be promising biomarkers.