Novel CpG-SNPs in the gastric acid secretion pathway GNAI3 and susceptibility to gastric cancer

CHI3L1 as a Prognostic Biomarker and Therapeutic Target in Glioma

The role of Chitinase-3-like protein 1 (CHI3L1) in tumor progression has been gradually clarified in different kinds of solid tumors. Hence, we aim to elucidate its prognostic value for glioma. In this study, we analyzed RNA sequencing data combined with corresponding clinical information obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Differentially expressed genes (DEGs) were acquired based on CHI3L1 expression profiles and were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Cox regression, least absolute shrinkage and selection operator (LASSO) regression methods, along with a nomogram, were employed to establish a predictive model. Compared with the corresponding non-tumor tissues, CHI3L1 expression was significantly upregulated in various types of solid tumors, correlating with poor clinical outcomes including glioma. GO analysis identified oxidative stress-related genes (ORGs) that were differentially expressed and modulated by CHI3L1, with 11 genes subsequently identified as potential predictors, using Univariate-Cox regression and LASSO regression. In addition, an index of oxidative stress-related genes (ORGI) was established, demonstrating its prognostic value in conjunction with CHI3L1 expression. The aberrant expression of CHI3L1 was proved in glioma patients through immunohistochemistry (IHC). Meanwhile, the knockdown of CHI3L1 inhibited glioma growth in vitro, and real-time Quantitative PCR (qPCR) confirmed decreased ORG expression upon CHI3L1 knockdown, suggesting the potential prognostic value of CHI3L1 as a therapeutic target for glioma.

Common Core Genes Play Vital Roles in Gastric Cancer With Different Stages

Background: Owing to complex molecular mechanisms in gastric cancer (GC) oncogenesis and progression, existing biomarkers and therapeutic targets could not significantly improve diagnosis and prognosis. This study aims to identify the key genes and signaling pathways related to GC oncogenesis and progression using bioinformatics and meta-analysis methods.

Methods: Eligible microarray datasets were downloaded and integrated using the meta-analysis method. According to the tumor stage, GC gene chips were classified into three groups. Thereafter, the three groups’ differentially expressed genes (DEGs) were identified by comparing the gene data of the tumor groups with those of matched normal specimens. Enrichment analyses were conducted based on common DEGs among the three groups. Then protein–protein interaction (PPI) networks were constructed to identify relevant hub genes and subnetworks. The effects of significant DEGs and hub genes were verified and explored in other datasets. In addition, the analysis of mutated genes was also conducted using gene data from The Cancer Genome Atlas database.

Results: After integration of six microarray datasets, 1,229 common DEGs consisting of 1,065 upregulated and 164 downregulated genes were identified. Alpha-2 collagen type I (COL1A2), tissue inhibitor matrix metalloproteinase 1 (TIMP1), thymus cell antigen 1 (THY1), and biglycan (BGN) were selected as significant DEGs throughout GC development. The low expression of ghrelin (GHRL) is associated with a high lymph node ratio (LNR) and poor survival outcomes. Thereafter, we constructed a PPI network of all identified DEGs and gained 39 subnetworks and the top 20 hub genes. Enrichment analyses were performed for common DEGs, the most related subnetwork, and the top 20 hub genes. We also selected 61 metabolic DEGs to construct PPI networks and acquired the relevant hub genes. Centrosomal protein 55 (CEP55) and POLR1A were identified as hub genes associated with survival outcomes.

Conclusion: The DEGs, hub genes, and enrichment analysis for GC with different stages were comprehensively investigated, which contribute to exploring the new biomarkers and therapeutic targets.

Functional Analysis of Haplotypes in Bovine PSAP Gene and Their Relationship with Beef Cattle Production Traits

Simple Summary

With the rapid development of information technology and molecular biotechnology, animal molecular breeding technology is playing an increasingly important role in beef cattle breeding. Prosaposin (PSAP) is involved in regulating the growth and development of animals, and it is reported that PSAP is an important marker-assisted selection (MAS) in cattle herd. The purpose of this study was to explore the novel variants in 3’ UTR of cattle PSAP and evaluate their effects on the morphological traits of four Chinese cattle breeds. In this study, 13 variants were identified in the PSAP 3’ UTR from 501 individuals belonging to four cattle breeds. In Nanyang cattle, the distribution of haplotypes was different from the other three breeds. Two groups of haplotypes had association with morphological traits by changing the secondary structures of PSAP 3’ UTR rather than the miR-184 target sites. This study not only expands the genetic variation spectrum of cattle PSAP but also contributes to MAS genetics and breeding of Chinese cattle breeds.

Abstract

The purpose of this study was to explore functional variants in the prosaposin (PSAP) three prime untranslated region (3’ UTR) and clarify the relationship between the variants and morphological traits. Through Sanger sequencing, 13 variations were identified in bovine PSAP in four Chinese cattle breeds, with six of them being loci in 3’ UTR. In particular, Nanyang (NY) cattle had a special genotype and haplotype distribution compared to the other three breeds. NY cattle with ACATG and GCGTG haplotypes had higher morphological traits than GTACA and GTACG haplotypes. The results of dual-luciferase reporter assay showed that ACATG and GCGTG haplotypes affected the morphological traits of NY cattle by altering the secondary structure of PSAP 3’ UTR rather than the miR-184 target sites. The findings of this study could be an evidence of a complex and varying mechanism between variants and animal morphological traits and could be used to complement candidate genes for molecular breeding.

Identification of Core Prognosis-Related Candidate Genes in Chinese Gastric Cancer Population Based on Integrated Bioinformatics

Background

Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. There are great geographical differences in the incidence of GC, and somatic mutation rates of driver genes are also different. The present study is aimed at screening core prognosis-related candidate genes in Chinese gastric cancer population based on integrated bioinformatics for the early diagnosis and prognosis of GC.

Methods

In the present study, the differentially expressed genes (DEGs) in GC were identified using four microarray datasets from the Gene Expression Omnibus (GEO) database. The samples of these datasets were all from China. Functional enrichment analysis of DEGs was conducted to evaluate the underlying molecular mechanisms involved in GC. Protein-protein interaction (PPI) network and cytoHubba were performed to determine hub genes associated with GC. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the hub genes.

Results

A total of 240 DEGs were obtained through the RRA method, including 80 upregulated genes and 160 downregulated genes. Upregulated genes were mainly enriched in extracellular matrix organization, extracellular matrix, and extracellular matrix structural constituent. The downregulated genes were mainly enriched in digestion, extracellular space, and oxidoreductase activity. The KEGG pathway enrichment analysis showed that the upregulated genes were mainly associated with ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. And downregulated genes were mainly associated with the metabolism of xenobiotics by cytochrome P450, metabolic pathways, and gastric acid secretion. The transcriptional and translational expression levels of the genes including COL1A1, COL5A2, COL12A1, and VCAN were higher in GC tissues than normal tissues.

Conclusion

A total of four genes including COL1A1, COL5A2, COL12A1, and VCAN were considered potential GC biomarkers in the Chinese population. And ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway were revealed to be important mechanisms of GC. Our findings provide novel insights into the occurrence and progression of GC in the Chinese population.

Selective expression of KCNA5 and KCNB1 genes in gastric and colorectal carcinoma

Background

Gastric and colorectal cancers are the most common malignant tumours, leading to a significant number of cancer-related deaths worldwide. Recently, increasing evidence has demonstrated that cancer cells exhibit a differential expression of potassium channels and this can contribute to cancer progression. However, their expression and localisation at the somatic level remains uncertain. In this study, we have investigated the expression levels of KCNB1 and KCNA5 genes encoding ubiquitous Kv2.1 and Kv1.5 potassium channels in gastric and colorectal tumours.

Methods

Gastric and colorectal tumoral and peritumoral tissues were collected to evaluate the expression of KCNB1 and KCNA5 mRNA by quantitative PCR. Moreover, the immunohistochemical staining profile of Kv2.1 and Kv1.5 was assessed on 40 Formalin-Fixed and Paraffin-Embedded (FFPE) gastric carcinoma tissues. Differences in gene expression between tumoral and peritumoral tissues were compared statistically with the Mann-Whitney U test. The association between the clinicopathological features of the GC patients and the expression of both Kv proteins was investigated with χ2 and Fisher’s exact tests.

Results

The mRNA fold expression of KCNB1 and KCNA5 genes showed a lower mean in the tumoral tissues (0.06 ± 0.17, 0.006 ± 0.009) compared to peritumoral tissues (0.08 ± 0.16, 0.16 ± 0.48, respectively) without reaching the significance rate (p = 0.861, p = 0.152, respectively). Interestingly, Kv2.1 and Kv1.5 immunostaining was detectable and characterised by a large distribution in peritumoral and tumoral epithelial cells. More interestingly, inflammatory cells were also stained. Surprisingly, Kv2.1 and Kv1.5 staining was undoubtedly and predominantly detected in the cytoplasm compartment of tumour cells. Indeed, the expression of Kv2.1 in tumour cells revealed a significant association with the early gastric cancer clinical stage (p = 0.026).

Conclusion

The data highlight, for the first time, the potential role of Kv1.5 and Kv2.1 in gastrointestinal-related cancers and suggests they may be promising prognostic markers for these tumours.