Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

Transcriptomic data of BT549 triple negative breast cancer cells treated with 20 µM NU7441, a DNA-dependent kinase inhibitor

DNA-dependent protein kinase catalytic subunit (DNA-PK) is a multifunctional serine‑threonine protein kinase that plays roles in non-homologous end joining of DNA repair in cells. NU7441 is a specific DNA-PKcs inhibitor. We investigated the effects of NU7441 on the transcriptome of BT549 triple negative breast cancer cells. Total RNA extracted from NU7441-treated or control BT549 cells was processed for preparation of sequencing libraries. Assessment of read quality was performed using fastqc tool. Trimming and filtering low-quality reads were performed using fastp. Reads were aligned by hisat2. SAM files were converted to BAM files using Samtools. The gene differential expression analysis, Gene Ontology (GO) analysis and KEGG pathway analysis were performed. After NU7441 treatment, total number of 2045 differential genes were selected according to |log2(FoldChange)| >= 1 & padj<= 0.05, among which 1365 genes were down-regulated and 680 genes were up-regulated. The differential expression genes in pattern recognition receptors (PRRs) immune responses signals, including NOD-like receptor signaling, Toll-like receptor signaling, RIG-I-like receptor signaling and cytosolic DNA-sensing pathways were noted in this paper.

Oxidative stress and autophagy-mediated immune patterns and tumor microenvironment infiltration characterization in gastric cancer

Recent years have seen a sharp rise in the amount of research on the connection between oxidative stress, autophagy, and cancer cells. However, the significant functions of oxidative stress and autophagy-related genes (OARGs) in gastric cancer (GC) are yet to be investigated integrally. Therefore, it will be a new and promising concept to search for novel OARG-related biomarkers to predict the prognosis and treatment response of GC. First, we assessed changes in prognosis and tumor microenvironment (TME) characteristics across the various oxidative stress and autophagy-related modification patterns based on a detailed analysis of 17 OARGs with prognostic significance of 808 GC samples. We identified three distinct OARG alteration patterns which displayed unique biological characteristics and immune cell infiltration features. Using principal component analysis methods, the OARGscore was developed to evaluate the OARG modification patterns of certain tumors. The negative connection between OARGscore and immune cells was statistically significant. Increased survival, a higher incidence of mutations, and a better response to immunotherapy were all predicted to be related to patients' high-OARGscore. In addition, the candidate chemotherapeutic drugs were predicted using the oncoPredict program. The low-OARGscore group was predicted to benefit more from Ribociclib, Alisertib, Niraparib, Epirubicin, Olaparib, and Axitinib, while patients in the high-OARGscore group were predicted to benefit more from Afatinib, Oxaliplatin, Paclitaxel, 5-Fluorouracil, Dabrafenib and Lapatinib. Our findings offer a specific method for predicting a patient's prognosis and susceptibility to immunotherapy, as well as a promising insight of oxidative stress and autophagy in GC.

Role of SPP1 in the diagnosis of gastrointestinal cancer

Recently, the incidence rate of digestive system tumors has increased in China and these tumors occur in a younger population. The present study aimed to determine the expression levels and potential clinical value of secreted phosphoprotein 1 (SPP1) in gastrointestinal cancer. The microarray datasets GSE104836, GSE189830 and GSE103236, obtained from the gene expression omnibus database, were analyzed to determine differentially expressed genes in patients with colorectal cancer (CRC), gastric cancer (GC) and esophageal cancer (EC). A total of 42 patients with CRC, GC or EC and 21 healthy controls were recruited to obtain blood and tissues samples. SPP1 expression levels were detected using reverse transcription-quantitative PCR. Moreover, levels of significance of SPP1 in patients with CRC, GC and EC were analyzed using receiver operating characteristic analysis. Potential correlations between SPP1 and carcinoembryonic antigen (CEA) were assessed using Pearson's correlation coefficient. SPP1 was significantly upregulated in the serum, plasma and tissue of patients with CRC, GC or EC. In addition, the area under the curve of SPP1 was >0.5 in the plasma, serum and cancer tissue of patients with early and late CRC, GC or EC. The present study further demonstrated that the specificity and sensitivity of SPP1 was higher in patients with late CRC, GC or EC compared with patients with early CRC, GC or EC. Moreover, SPP1 and CEA were significantly positively correlated in serum of patients with CRC, GC or EC. In conclusion, the current study demonstrated that SPP1 exhibited significant diagnostic value for gastrointestinal tumors, which suggested that SPP1 may exhibit potential as a diagnostic marker of CRC, GC and EC. The present study provided a novel theoretical basis for the role of SPP1 as a diagnostic marker of digestive system tumors.

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.