Key Genes in Stomach Adenocarcinoma Identified via Network Analysis of RNA-Seq Data

Identification and characterization of ferroptosis-related genes in therapy-resistant gastric cancer

Therapy resistance in gastric cancer poses ongoing challenges, necessitating the identification of ferroptosis-related genes linked to overall survival for potential therapeutic insights. The purpose of the study was to identify ferroptosis-related genes contributing to therapy resistance in gastric cancer and explore their associations with overall survival. Differentially expressed ferroptosis-related genes were identified in therapy-resistant versus therapy-responsive gastric cancer patients. Hub genes were selected from these genes. Enrichment analysis focused on oxidative stress and ROS metabolism. Validation was conducted in a TCGA stomach adenocarcinoma dataset. A hub gene-based risk model (DUSP1/TNF/NOX4/LONP1) was constructed and assessed for overall survival prediction. Associations with the tumor immune microenvironment were examined using the ESTIMATE algorithm and correlation analysis. Ten hub genes were identified, enriched in oxidative stress and ROS metabolism. Validation confirmed their aberrant expressions in the TCGA dataset. The hub gene-based risk model effectively predicted overall survival. High G6PD/TNF expression and low NOX4/SREBF1/MAPK3/DUSP1/KRAS/SIRT3/LONP1 expression correlated with stromal and immune scores. KRAS/TNF/MAPK3 expression positively correlated with immune-related SREBF1/NOX4 expression. DUSP1/NOX4/SREBF1/TNF/KRAS expression was associated with immune cell infiltration. The hub gene-based risk model (DUSP1/TNF/NOX4/LONP1) shows promise as an overall survival predictor in gastric cancer. Ferroptosis-related hub genes represent potential therapeutic targets for overcoming therapy resistance in gastric cancer treatment.

Identification of stage-specific differentially expressed genes and SNPs in gastric cancer employing RNA-Seq based transcriptome profiling

We analysed over 400 million reads obtained from Illumina sequencing of six pairs of libraries representing two each of stage I, II, and III gastric tumors and corresponding normal tissues to identify differentially expressed genes (DEGs), single nucleotide polymorphisms (SNPs), and transcription factors (TFs). In total, 2207 DEGs including 972 upregulated genes and 1235 downregulated genes were detected. Of these, several stage-specific signature genes were identified. The protein-protein interaction networks involving DEGs and TFs were constructed. The KEGG pathway analysis of SNP harbouring genes revealed their involvement in different cancer related pathways like apoptosis, mTOR pathway, and MAPK signaling pathway. The SNP analysis showed implication of host genes in GO categories like immune system process, regulation of signaling, response to stress, and transport. A biased chromosomal distribution of DEGs and SNP harbouring genes was observed. Our study would provide further insights into the complex regulatory mechanisms operating during gastric tumorigenesis.

Investigation and verification of the clinical significance and perspective of natural killer group 2 member D ligands in colon adenocarcinoma

This study investigated and verified the diagnostic and prognostic values of natural killer group 2 member D ligand (NKG2DL) genes in colon adenocarcinoma (COAD). We downloaded NKG2DLs expression data and corresponding clinical parameters from The Cancer Genome Atlas (TCGA) and used bioinformatics techniques to investigate the values of NKG2DLs in COAD. Then, we used the GSE40967 cohort to verify the prognostic value of NKG2DLs. Finally, we verified the ULBP2 expression level in tissues, and also investigated the diagnostic and prognostic values of ULBP2 in COAD. The diagnostic receiver operating characteristic curves showed that ULBP1, ULBP2, ULBP3, and RAET1L had high diagnostic values in COAD [Area Under Curve (AUC) > 0.9]. In TCGA cohort, the univariate and multivariate survival analyses suggested that ULBP2 was correlated with the prognosis of COAD recurrence-free survival (RFS) and overall survival (OS). In GSE40967 cohort, ULBP2 was associated with CC RFS and OS. Reverse transcription-quantitative polymerase chain reaction and immunohistochemistry results showed that ULBP2 was highly expressed in COAD tumor tissues (P < 0.05) and both had diagnostic values (AUC > 0.7). Validated survival analysis showed that the high expression of ULBP2 had a worse prognosis in COAD OS and RFS. Thus, ULBP2 might be an independent diagnostic and prognostic biomarker of COAD.

Genome-wide analysis to identify a novel microRNA signature that predicts survival in patients with stomach adenocarcinoma

Objective: Using genome-wide screening, this study was aimed at identifying prognostic microRNA (miRNA) in those patients suffering from stomach adenocarcinoma (STAD).

Methods: A genome-wide miRNA sequencing dataset and relevant STAD clinical information was obtained via The Cancer Genome Atlas (TCGA). Prognostic miRNA selection was carried out through a whole genome multivariate Cox regression model in order to establish a prognostic STAD signature.

Results: Eleven miRNAs (hsa-mir-509-2, hsa-mir-3917, hsa-mir-495, hsa-mir-653, hsa-mir-3605, hsa-mir-2115, hsa-mir-1292, hsa-mir-137, hsa-mir-6511b-1, hsa-mir-145, and hsa-mir-138-2) were recognized as prognostic and used for the construction of a STAD prognostic signature. This signature exhibited good performance in predicting prognosis (adjusted P<0.0001, adjusted hazard ratio= 3.047, and 95% confidence interval=2.148-4.323). The time-dependent receiver operating characteristic examination exhibited area under curve values of 0.711, 0.697, 0.716, 0.733, 0.805, and 0.805, for 1-, 2-, 3-, 4-, 5-, and 10-year overall survival (OS) estimation, respectively. Comprehensive survival analysis suggests that the 11-miRNA prognostic signature acts as an independent feature of STAD prognosis and exhibits superior performance in OS prediction when compared to traditional clinical parameters. Furthermore, fourteen miRNA target genes were linked to STAD OS. These included SERPINE1, MLEC, ANGPT2, C5orf38, FZD7, MARCKS, PDGFD, DUSP6, IRS1, PSAT1, TENM3, TMEM127, BLMH, and TIRAP. Functional and gene set enrichment analysis suggested that target genes and the 11-miRNA prognostic signature were both participate in various biological processes and pathways, including the growth factor beta, Wnt, and Notch signaling pathways.

Conclusions: By means of a genome-wide analysis, an 11-miRNA expression signature that may serve as an underlying prognostic indicator for those patients suffering from STAD has been identified and described here.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.

Comparison of tumor related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma

Background

This study compared tumor‐related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma (LUAD) treatment.

Methods

Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses were performed based on LUAD differentially expressed genes from The Cancer Genome Atlas (TCGA) project and genotype‐tissue expression controls. These results were compared to various known compounds using the Connectivity Mapping dataset. The clinical significance of the hub genes identified by overlapping pathway enrichment analysis was further investigated using data mining from multiple sources. A drug‐pathway network for LUAD was constructed, and molecular docking was carried out.

Results

After the integration of 57 LUAD‐related pathways and 35 pathways affected by small molecules, five overlapping pathways were revealed. Among these five pathways, the p53 signaling pathway was the most significant, with CCNB1, CCNB2, CDK1, CDKN2A, and CHEK1 being identified as hub genes. The p53 signaling pathway is implicated as a risk factor for LUAD tumorigenesis and survival. A total of 88 molecules significantly inhibiting the five LUAD‐related oncogenic pathways were involved in the LUAD drug‐pathway network. Daunorubicin, mycophenolic acid, and pyrvinium could potentially target the hub gene CHEK1 directly.

Conclusion

Our study highlights the critical pathways that should be targeted in the search for potential LUAD treatments, most importantly, the p53 signaling pathway. Some compounds, such as ciclopirox and AG‐028671, may have potential roles for LUAD treatment but require further experimental verification.

Comprehensive investigation of a novel differentially expressed lncRNA expression profile signature to assess the survival of patients with colorectal adenocarcinoma

Growing evidence has shown that long non-coding RNAs (lncRNAs) can serve as prospective markers for survival in patients with colorectal adenocarcinoma. However, most studies have explored a limited number of lncRNAs in a small number of cases. The objective of this study is to identify a panel of lncRNA signature that could evaluate the prognosis in colorectal adenocarcinoma based on the data from The Cancer Genome Atlas (TCGA). Altogether, 371 colon adenocarcinoma (COAD) patients with complete clinical data were included in our study as the test cohort. A total of 578 differentially expressed lncRNAs (DELs) were observed, among which 20 lncRNAs closely related to overall survival (OS) in COAD patients were identified using a Cox proportional regression model. A risk score formula was developed to assess the prognostic value of the lncRNA signature in COAD with four lncRNAs (LINC01555, RP11-610P16.1, RP11-108K3.1 and LINC01207), which were identified to possess the most remarkable correlation with OS in COAD patients. COAD patients with a high-risk score had poorer OS than those with a low-risk score. The multivariate Cox regression analyses confirmed that the four-lncRNA signature could function as an independent prognostic indicator for COAD patients, which was largely mirrored in the validating cohort with rectal adenocarcinoma (READ) containing 158 cases. In addition, the correlative genes of LINC01555 and LINC01207 were enriched in the cAMP signaling and mucin type O-Glycan biosynthesis pathways. With further validation in the future, our study indicates that the four-lncRNA signature could serve as an independent biomarker for survival of colorectal adenocarcinoma.