Screening and identification of potential target genes in head and neck cancer using bioinformatics analysis

Deregulation of purinergic ectoenzyme activity in head and neck cancer promotes immunosuppression

BACKGROUND

Head and neck cancer (HNC) comprises a spectrum of neoplasms that affect the upper aerodigestive tract and are the sixth most common cancers worldwide. Individuals with HNC exhibit various symptoms and metabolic changes, including immune alterations and alterations of the purinergic pathway, which may signal worse outcomes. Therefore, the purpose of this research was to measure the activity of purinergic ectoenzymes and interleukins in patients with HNC, oral cavity cancer, and larynx cancer.

METHODS AND RESULTS

We recruited 32 patients and 33 healthy control subjects and performed the laboratory analyses. We identified dysregulation in the purinergic signaling pathway characterized by an increase in adenosine triphosphate (ATP) and adenosine monophosphate (AMP) hydrolysis and a decrease in the deamination of adenosine to inosine in these cancers (p < 0.05). These alterations were likely caused by increased activity of the ectoenzymes E-NTPDase and ecto-5'-nucleotidase and reduced adenosine deaminase activity. This dysregulation was associated with immune alterations, increased levels of IL-10, and decreased myeloperoxidase activity (p < 0.05), suggesting immunosuppression in these patients and suggesting possible accumulation of adenosine in the extracellular environment.

CONCLUSIONS

Adenosine is a potent immunosuppressive molecule associated with tumor progression and immune evasion. Our findings suggest a relationship between extracellular purines and the development and progression of the tumor microenvironment and poor outcomes. These findings increase the understanding of biological mechanisms related to HNC and demonstrate that these components are potential diagnostic markers and therapeutic targets for future management strategies and improvement in the quality of life.

Identification of key regulators associated with colon cancer prognosis and pathogenesis

Colon cancer (CC) is the fourth deadliest cancer in the world. New insights into prognostication might be helpful to define the optimal adjuvant treatments for patients in routine clinical practice. Here, a microarray dataset with 30 primary tumors and 30 normal samples was analyzed using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG, ChEA and X2K were used to analyze DEGs-related Gene Ontology, pathways, transcription factors (TFs) and kinases, respectively. Protein-protein interaction (PPI) networks were constructed using the STRING database and Cytoscape. The modules and hub genes of DEGs was determined through MCODE and CytoHubba plugins, and the expression of hub genes was verified using GEPIA. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 233 and 373 genes were upregulated and downregulated in CC, respectively. GO analysis showed that the upregulated DEGs were mainly involved in mitotic nuclear division and cell division. Top 10 hub genes were identified, including AURKB, CDK1, DLGAP5, AURKA, CCNB2, CCNB1, BUB1B, CCNA2, KIF20A and BUB1. Whereas, FOMX1, E2F7, E2F1, E2F4 and AR were identified as top 5 TFs in CC. Moreover, CDK1, CDC2, MAPK14, ATM and CK2ALPHA was identified as top 5 kinases in CC. miRNAs analysis showed that Hsa-miR-215-5p hsa-miR-193b-3p, hsa-miR-192-5p and hsa-miR-16-5p could target the largest number of CC genes. Taken together, CC-related genes, especially the hub genes, TFs, and metabolites might be used as novel biomarkers for CC, as well as for diagnosis and guiding therapeutic strategies for CC.

Differential gene expression and network analysis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have collected genomic data of HNSCC patients from The Cancer Genome Atlas (TCGA) and analyzed them to get deeper insights into the gene expression pattern. Initially, 793 differentially expressed genes (DEGs) were categorized, and their enrichment analysis was performed. Later, a protein-protein interaction network for the DEGs was constructed using the STRING plugin in Cytoscape to study their interactions. A set of 10 hub genes was selected based on Maximal Clique Centrality score, and later their survival analysis was studied. The elucidated set of 10 genes, i.e., PRAME, MAGEC2, MAGEA12, LHX1, MAGEA3, CSAG1, MAGEA6, LCE6A, LCE2D, LCE2C, referred to as potential candidates to be explored as HNSCC biomarkers. The Kaplan-Meier overall survival of the selected genes suggested that the alterations in the candidate genes were linked to the decreased survival of the HNSCC patients. Altogether, the results of this study signify that the genomic alterations and differential expression of the selected genes can be explored in therapeutic interpolations of HNSCC, exploiting early diagnosis and target-propelled therapy.

Network pharmacology reveals the potential mechanism of Baiying Qinghou decoction in treating laryngeal squamous cell carcinoma

Context: Baiying Qinghou as a traditional Chinese medicine decoction shows anticancer property on laryngeal squamous cell carcinoma. However, little is known about the precise mechanism of Baiying Qinghou detection against laryngeal squamous cell carcinoma.

Objective: This study was aimed to explore potential mechanism of therapeutic actions of Baiying Qinghou decoction on laryngeal squamous cell carcinoma.

Materials and Methods: The active chemical components of Baiying Qinghou decoction were predicted, followed by integrated analysis of network pharmacology and molecular docking approach. The network pharmacology approach included target protein prediction, protein-protein interaction network construction and functional enrichment analysis.

Results: Sitosterol and quercetin were predicted to be the overlapped active ingredients among three Chinese herbs of Baiying Qinghou decoction. The target proteins were closely associated with response to chemical, response to drug related biological process and cancer related pathways such as PI3K-Akt signaling, HIF-1 signaling and Estrogen signaling pathway. The target proteins of TP53, EGFR, PTGS2, NOS3 and IL1B as the key nodes in PPI network were cross-validated, among which EGFR, IL1B, NOS3 and TP53 were significantly correlated with the prognosis of patients with laryngeal squamous cell carcinoma. Finally, the binding modes of EGFR, IL1B, NOS3 and TP53 with quercetin were visualized.

Discussion and Conclusion: Quercetin of Baiying Qinghou decoction showed therapeutic effect against laryngeal squamous cell carcinoma by regulating TP53, EGFR, NOS3 and IL1B involved with drug resistance and PI3K-AKT signaling pathway. TP53, EGFR, NOS3 and IL1B may be the candidate targets for the treatment of laryngeal squamous cell carcinoma.

Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer

The role of an extracellular matrix- (ECM-) receptor interaction signature has not been fully clarified in gastric cancer. This study performed comprehensive analyses on the differentially expressed ECM-related genes, clinicopathologic features, and prognostic application in gastric cancer. The differentially expressed genes between tumorous and matched normal tissues in The Cancer Genome Atlas (TCGA) and validation cohorts were identified by a paired t-test. Consensus clusters were built to find the correlation between clinicopathologic features and subclusters. Then, the least absolute shrinkage and selection operator (lasso) method was used to construct a risk score model. Correlation analyses were made to reveal the relation between risk score-stratified subgroups and clinicopathologic features or significant signatures. In TCGA (26 pairs) and validation cohort (134 pairs), 25 ECM-related genes were significantly highly expressed and 11 genes were downexpressed in gastric cancer. ECM-based subclusters were slightly related to clinicopathologic features. We constructed a risk score model = 0.081∗log₂ (CD36) + 0.043∗log₂ (COL5A2) + 0.001∗log₂ (ITGB5) + 0.039∗log₂ (SDC2) + 0.135∗log₂ (SV2B) + 0.012∗log₂ (THBS1) + 0.068∗log₂ (VTN) + 0.023∗log₂ (VWF). The risk score model could well predict the outcome of patients with gastric cancer in both training (n = 351, HR: 1.807, 95% CI: 1.292-2.528, P = 0.00046) and validation (n = 300, HR: 1.866, 95% CI: 1.347-2.584, P = 0.00014) cohorts. Besides, risk score-based subgroups were associated with angiogenesis, cell adhesion molecules, complement and coagulation cascades, TGF-beta signaling, and mismatch repair-relevant signatures (P < 0.0001). By univariate (1.845, 95% CI: 1.382-2.462, P < 0.001) and multivariate (1.756, 95% CI: 1.284-2.402, P < 0.001) analyses, we regarded the risk score as an independent risk factor in gastric cancer. Our findings revealed that ECM compositions became accomplices in the tumorigenesis, progression, and poor survival of gastric cancer.