GSG2 promotes progression of human endometrial cancer by regulating PD-1/PD-L1 expression via PI3K-AKT pathway.

Cell cycle dysregulation leading to uncontrolled growth is a primary characteristic of malignancy. GSG2, a mitosis-related kinase, affects the normal cell cycle by interfering with the normal dissociation of centromere cohesion, and its overexpression has been shown to play an important role in cancer cells. Here, we investigated the function of GSG2 as a tumor promoter in endometrial carcinoma and its relationship with the immunological microenvironment. We used immunohistochemistry to identify a correlation between the development and prognosis of GSG2 and endometrial cancer. Cell and animal experiments confirmed that GSG2 has a protumorigenic phenotype in endometrial cancer cell lines. Furthermore, using GeneChip analysis and a tumor-immune coculture model, we observed a link between GSG2 expression and the composition of the immune microenvironment. Therefore, we concluded that the activation of the PI3K/AKT pathway by GSG2 may impact DNA repair, disrupt the cell cycle, and regulate the immune response, all of which could increase the ability of EC cells to proliferate malignantly. Consequently, it is anticipated that GSG2 will be a viable therapeutic target in endometrial carcinoma.

The feature of cervical microbiota associated with the progression of cervical cancer among reproductive females.

OBJECTIVES: The aim of this study was to characterize cervical microbiome feature of reproductive-age women in the progression of squamous intraepithelial lesions (SIL) to cervical cancer. METHODS: We characterized the 16S rDNA cervical mucus microbiome in 94 participants (age from 18 to 52), including 13 cervical cancer (CA), 31 high-grade SIL (HSIL), 10 low-grade SIL (LSIL), 12 HPV-infected (NH) patients and 28 healthy controls (NN). Alpha (within sample) diversity was examined by Shannon and Simpson index, while Beta (between sample) diversity by principle coordinate analysis (PCoA) of weighted Unifrac distances. Relative abundance of microbial taxa was compared using Linear Discriminant Analysis Effect Size (LEfSe). Co-occurrence analysis was performed to identify correlation among marker genera, and Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) to explore functional features and pathways of cervical microbiota. RESULTS: Alpha diversity(p < 0.05) was higher in severer cervical pathology with lower relative abundance of Lactobacillus as well as higher of anaerobes. Beta diversity (p < 0.01) was significantly different. Marker genera were identified including Porphyromonas, Prevotella and Campylobacter of CA and Sneathia of HSIL. The correlation of differential functional pathways with Prevotella was opposite to that with Lactobacillus. CONCLUSION: Our study suggests differences in cervical microbiota diversity and relative abundance of reproductive-age females in different stages of cervical carcinogenesis. Marker genera might participate in the lesion progression and will be helpful for diagnosis, prevention and treatment. These findings may lead the way to further study of the cervical microbiome in development of cervical cancer.

Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis.

INTRODUCTION: Colorectal cancer (CRC) is the fourth most common cause of cancer-related mortality worldwide. The tumor, node, metastasis (TNM) stage remains the standard for CRC prognostication. Identification of meaningful microRNA (miRNA) and gene modules or representative biomarkers related to the pathological stage of colon cancer helps to predict prognosis and reveal the mechanisms behind cancer progression. MATERIALS AND METHODS: We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA) to detect the pathological stage-related miRNA and gene modules and construct a miRNA-gene network. The Cancer Genome Atlas (TCGA) colon adenocarcinoma (CAC) RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and characterize the results of WGCNA. RESULTS: Two gene modules (Gmagenta and Ggreen) and one miRNA module were associated with the pathological stage. Six hub genes (COL1A2, THBS2, BGN, COL1A1, TAGLN and DACT3) were related to prognosis and validated to be associated with the pathological stage. Five hub miRNAs were identified to be related to prognosis (hsa-miR-125b-5p, hsa-miR-145-5p, hsa-let-7c-5p, hsa-miR-218-5p and hsa-miR-125b-2-3p). A total of 18 hub genes and seven hub miRNAs were predominantly expressed in tumor stroma. Proteoglycans in cancer, focal adhesion, extracellular matrix (ECM)-receptor interaction and so on were common pathways of the three modules. Hsa-let-7c-5p was located at the core of miRNA-gene network. CONCLUSION: These findings help to advance the understanding of tumor stroma in the progression of CAC and provide prognostic biomarkers as well as therapeutic targets.