Angiopoietin-2 gene polymorphisms are biomarkers for the development and progression of colorectal cancer in Han Chinese
INTERNATIONAL JOURNAL OF MEDICAL SCIENCES
Authors: Du, Zhang; Tang, Chih-Hsin; Li, Li-Jun; Kang, Le; Zhao, Jin; Jin, Lulu; Wang, Chao-Qun; Su, Chen-Ming
Colorectal cancer (CRC) is one of the most common cancers in Han Chinese and is characterized by low rates of early diagnosis and poor survival rates. Angiopoietin-2 (Ang2), an endothelial tyrosine kinase, is involved in CRC progression, but little is known about the association between single nucleotide polymorphisms (SNPs) and diagnosis or prognosis of CRC. This study reports on the association between 5 SNPs of the Angpt2 gene (rs2442598, rs734701, rs1823375, 11137037, and rs12674822) and CRC susceptibility as well as clinical outcomes in 379 patients with CRC and in 1,043 cancer-free healthy controls. Carriers of the CG allele at rs1823375 and those with the GT+TT allele of the variant rs12674822 were at greater risk of CRC than their respective wild-type counterparts. Moreover, carriers of the GT or GT+TT allele in rs12674822 were significantly more likely to have tumor involvement in both the colon and rectum compared with wild-type (GG) carriers, while 5-year progression-free survival was also significantly worse in those carrying the GT+TT allele in rs12674822 compared with wild-type carriers. Our study is the first to describe correlations between Angpt2 polymorphisms and CRC development and progression in people of Chinese Han ethnicity.
Weighted correlation gene network analysis reveals a new stemness index-related survival model for prognostic prediction in hepatocellular carcinoma
Authors: Zhang, Qiujing; Wang, Jia; Liu, Menghan; Zhu, Qingqing; Li, Qiang; Xie, Chao; Han, Congcong; Wang, Yali; Gao, Min; Liu, Jie
In this study, we constructed a new survival model using mRNA expression-based stemness index (mRNAsi) for prognostic prediction in hepatocellular carcinoma (HCC). Weighted correlation network analysis (WGCNA) of HCC transcriptome data (374 HCC and 50 normal liver tissue samples) from the TCGA database revealed 7498 differentially expressed genes (DEGs) that clustered into seven gene modules. LASSO regression analysis of the top two gene modules identified ANGPT2, EMCN, GLDN, USHBP1 and ZNF532 as the top five mRNAsi-related genes. We constructed our survival model with these five genes and tested its performance using 243 HCC and 202 normal liver samples from the ICGC database. Kaplan-Meier survival curve and receive operating characteristic curve analyses showed that the survival model accurately predicted the prognosis and survival of high- and low-risk HCC patients with high sensitivity and specificity. The expression of these five genes was significantly higher in the HCC tissues from the TCGA, ICGC, and GEO datasets (GSE25097 and GSE14520) than in normal liver tissues. These findings demonstrate that a new survival model derived from five strongly correlating mRNAsi-related genes provides highly accurate prognoses for HCC patients.