Increased phosphorylation on residue S795 of the retinoblastoma protein in esophageal adenocarcinoma

Integrated Bioinformatics Analysis Identifies Hub Genes Associated with the Pathogenesis and Prognosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, using bioinformatics analyses, we attempted to identify potential biomarkers and therapeutic targets for ESCC. Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained through comprehensive analysis of three publicly available gene expression profile datasets from the Gene Expression Omnibus database. The biological roles of the DEGs were identified by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Moreover, the Cytoscape 3.7.1 platform and subsidiary tools such as Molecular Complex Detection (MCODE) and CytoHubba were used to visualize the protein-protein interaction (PPI) network of the DEGs and identify hub genes. A total of 345 DEGs were identified between normal esophageal and ESCC samples, which were enriched in the KEGG pathways of the cell cycle, endocytosis, pancreatic secretion, and fatty acid metabolism. Two of the highest scoring models were selected from the PPI network using Molecular Complex Detection. Moreover, CytoHubba revealed 21 hub genes with a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of five genes-SPP1, SPARC, BGN, POSTN, and COL1A2-were associated with poor disease-free survival of ESCC patients, as indicated by survival analysis. Taken together, we identified that elevated expression of five hub genes, including SPP1, is associated with poor prognosis in ESCC patients, which may serve as potential prognostic biomarkers or therapeutic target for ESCC.

Inhibition of pRB Pathway Differentially Modulates Apoptosis in Esophageal Cancer Cells

Esophageal cancer is the sixth most common cause of cancer-related death worldwide. Current chemotherapy regimens include a combination of 5-fluorouracil (5-FU) and cisplatin, but more efficient therapy strategies are needed to increase 5-year survival. Alterations in the signaling pathway of the tumor suppressor gene Rb-1, which encodes a phosphoprotein (pRB) that negatively regulates the G1/S transition of the cell cycle, are present in 70% of all tumors, but its role in esophageal cancer is still unclear. Most of these are alterations leading to up-regulation of the activity of cyclin-dependent kinases (CDKs) to phosphorylate pRB, which suggests that keeping the wild type pRB phosphorylated might be advantageous. Besides proliferation, pRB also regulates apoptosis induced by tumor necrosis factor-alpha (TNF-α) and DNA-damage. We investigated the status of phosphorylation of pRB along esophageal tumorigenesis stages, as well as whether hyperphosphorylation of pRB could suppress apoptosis induced by cisplatin, 5-FU, or TNF-α in esophageal cancer cells. pRB phosphorylation increased progressively from normal esophageal tissue to metaplasia and adenocarcinoma, suggesting that pRB phosphorylation increases along esophageal tumor stages. When RB-1 was knocked down or CDK inhibitors reduced the levels of phosphorylated pRB, opposite apoptotic effects were observed, depending on the combination of drugs tested: whereas TNF-α- and cisplatin-induced apoptosis increased, 5-FU-induced apoptosis decreased. Taken together, these data suggest that pRB plays a role in esophageal adenocarcinoma and that, depending on the type of anti-cancer treatment, combining CDK inhibitors and chemotherapy has the potential to increase the sensitivity of esophageal cancer cells to cell death.

Esophageal cancer: Risk factors, genetic association, and treatment

The poor prognosis and rising incidence of esophageal cancer highlight the need for improved detection and prediction methods that are essential prior to treatment. Esophageal cancer is one of the most fatal malignancies worldwide, with a dramatic increase in incidence in the Western world occurring over the past few decades. Despite improvements in the management and treatment of esophageal cancer patients, the general outcome remains very poor for overall 5-year survival rates (∼10%) and 5-year postesophagectomy survival rates (∼15-40%). Esophageal cancer is often diagnosed during its advanced stages, the main reason being the lack of early clinical symptoms. In an attempt to improve the outcome of patients after surgery, such patients are often treated with neoadjuvent concurrent chemoradiotherapy (CCRT) in order to decrease tumor size. However, CCRT may enhance toxicity levels and possibly cause a delay in surgery for patients who respond poorly to CCRT. Thus, precise biomarkers that could predict or identify patients who may or may not respond well to CCRT can assist physicians in choosing the appropriate therapy for patients. Identifying susceptible gene and biomarkers can help in predicting the treatment response of patients while improving their survival rates.