Combined bioinformatics technology to explore pivot genes and related clinical prognosis in the development of gastric cancer

Comprehensive pan-carcinoma analysis of ITGB1 distortion and its potential clinical significance for cancer immunity

The human protein-coding gene ITGB1 (Integrin 1), also known as CD29, has a length of 58048 base pairs. The Integrin family's most prevalent subunit, it participates in the transmission of numerous intracellular signaling pathways. A thorough examination of ITGB1's functions in human malignancies, however, is inadequate and many of their relationships to the onset and development of human cancers remain unknown. In this work, we examined ITGB1's role in 33 human cancers. Finally, a multi-platform analysis revealed that three of the 33 malignancies had significantly altered ITGB1 expression in tumor tissues in comparison to normal tissues. In addition, it was discovered through survival analysis that ITGB1 was a stand-alone prognostic factor in a number of cancers. ITGB1 expression was linked to immune cell infiltration in colon cancer, according to an investigation of immune infiltration in pan-cancer. In the gene co-expression research, ITGB1 showed a positive connection with the majority of the cell proliferation and EMT indicators, indicating that ITGB1 may have an essential function in controlling cancer metastasis and proliferation. Our pan-cancer analysis of ITGB1 gives evidence in favor of a further investigation into its oncogenic function in various cancer types.

Identification of miR-143-3p as a diagnostic biomarker in gastric cancer

BACKGROUND

Gastric cancer (GC) is among the most common types of gastrointestinal cancers and has a high incidence and mortality around the world. To suppress the progression of GC, it is essential to develop diagnostic markers. MicroRNAs regulate GC development, but a clearer insight into their role is needed before they can be applied as a molecular markers and targets.

METHODS

In this study, we assessed the diagnostic value of differentially expressed microRNAs as potential diagnostic biomarkers for GC using data for 389 tissue samples from the Cancer Genome Atlas (TCGA) and 21 plasma samples from GC patients.

RESULTS

The expression of hsa-miR-143-3p (also known as hsa-miR-143) was significantly downregulated in GC according to the TCGA data and plasma samples. The 228 potential target genes of hsa-miR-143-3p were analyzed using a bioinformatics tool for miRNA target prediction. The target genes correlated with extracellular matrix organization, the cytoplasm, and identical protein binding. Furthermore, the pathway enrichment analysis of target genes showed that they were involved in pathways in cancer, the phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway, and proteoglycans in cancer. The hub genes in the protein-protein interaction (PPI) network, were matrix metallopeptidase 2 (MMP2), CD44 molecule (CD44), and SMAD family member 3 (SMAD3).

CONCLUSIONS

This study suggests that hsa-miR-143-3p may be used as a diagnostic marker for GC, contributing via the pathways involved in the development of GC.

Interfering with the Ubiquitin-Mediated Regulation of Akt as a Strategy for Cancer Treatment

The serine/threonine kinase Akt modulates the functions of numerous substrates, many of them being involved in cell proliferation and growth, metabolism, angiogenesis, resistance to hypoxia and migration. Akt is frequently deregulated in many types of human cancers, its overexpression or abnormal activation being associated with the increased proliferation and survival of cancer cells. A promising avenue for turning off the functionality of Akt is to either interfere with the K63-linked ubiquitination that is necessary for Akt membrane recruitment and activation or increase the K48-linked polyubiquitination that aims to target Akt to the proteasome for its degradation. Recent evidence indicates that targeting the ubiquitin proteasome system is effective for certain cancer treatments. In this review, the functions and roles of Akt in human cancer will be discussed, with a main focus on molecules and compounds that target various elements of the ubiquitination processes that regulate the activation and inactivation of Akt. Moreover, their possible and attractive implications for cancer therapy will be discussed.

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.