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Matrix metalloproteinases (MMPs) are involved in the cleavage of several components of the extracellular matrix and serve important roles in tumor growth, metastasis and invasion. Previous studies have focused on the expression of one or several MMPs in esophageal squamous cell carcinoma (ESCC); however, in the present study, the transcriptomics of all 23 MMPs were systematically investigated with a focus on the prognostic value of the combination of MMPs. In this study, 8 overlapping differentially expressed genes of the MMP family were identified based on data obtained from Gene Expression Omnibus and The Cancer Genome Atlas. The prognostic value of these MMPs were investigated; the receiver operating characteristic curves, survival curves and nomograms showed that the combination of 6 selected MMPs possessed a good predictive ability, which was more accurate than the prediction model based on Tumor-Node-Metastasis stage. Gene set enrichment analysis and gene co-expression analysis were performed to investigate the potential mechanism of action of MMPs in ESCC. The MMP family was associated with several signaling pathways, such as epithelial-mesenchymal transition (EMT), Notch, TGF-β, mTOR and P53. Cell Counting Kit-8, colony formation, wound healing assays and western blotting were used to determine the effect of BB-94, a pan-MMP inhibitor, on proliferation and migration of ESCC cells. BB-94 treatment decreased ESCC cell growth, migration and EMT. Therefore, MMPs may serve both as diagnostic and prognostic biomarkers of ESCC, and MMP inhibition may be a promising preventive and therapeutic strategy for patients with ESCC.

Background Esophageal squamous cell carcinoma (ESCC) is a subtype of esophageal cancer with high incidence and mortality. Due to the poor 5-year survival rates of patients with ESCC, exploring novel diagnostic markers for early ESCC is emergent. Collagen, the abundant constituent of extracellular matrix, plays a critical role in tumor growth and epithelial-mesenchymal transition. However, the clinical significance of collagen genes in ESCC has been rarely studied. In this work, we systematically analyzed the gene expression of whole collagen family in ESCC, aiming to search for ideal biomarkers. Methods Clinical data and gene expression profiles of ESCC patients were collected from The Cancer Genome Atlas and the gene expression omnibus databases. Bioinformatics methods, including differential expression analysis, survival analysis, gene sets enrichment analysis (GSEA) and co-expression network analysis, were performed to investigate the correlation between the expression patterns of 44 collagen family genes and the development of ESCC. Results A total of 22 genes of collagen family were identified as differentially expressed genes in both the two datasets. Among them, COL1A1, COL10A1 and COL11A1 were particularly up-regulated in ESCC tissues compared to normal controls, while COL4A4, COL6A5 and COL14A1 were notably down-regulated. Besides, patients with low COL6A5 expression or high COL18A1 expression showed poor survival. In addition, a 7-gene prediction model was established based on collagen gene expression to predict patient survival, which had better predictive accuracy than the tumor-node-metastasis staging based model. Finally, GSEA results suggested that collagen genes might be tightly associated with PI3K/Akt/mTOR pathway, p53 pathway, apoptosis, cell cycle, etc. Conclusion Several collagen genes could be potential diagnostic and prognostic biomarkers for ESCC. Moreover, a novel 7-gene prediction model is probably useful for predicting survival outcomes of ESCC patients. These findings may facilitate early detection of ESCC and help improves prognosis of the patients.

PI3K pathway is an important anti-tumor target, but its effect and mechanism is not clear in esophageal squamous cell carcinoma (ESCC). By analysis of the Cancer Genome Atlas (TCGA) datasets, we found that PI3Ks level were significantly upregulated in human esophageal cancer tissues compared with that in non-cancer tissues. The alteration of PI3K can significantly affect the overall patient survival in ESCC but not in esophageal adenocarcinoma (EAC). We found that the classic PI3K inhibitor LY294002 obviously inhibited the canonical mammalian target of rapamycin (mTOR) pathway and restrained the growth of ESCC with less toxicity to normal cells. Besides, LY294002 inhibited noncanonical PKR-like ER kinase (PERK)/elF2α/ATF4 pathway as well. Both siRNA and the small molecule inhibitor GSK2656157 against PERK/elF2α/ATF4 pathway can significantly inhibit the growth of ESCC. More importantly, GSK2656157 aggravated the inhibitory effect of LY294002 on cell growth, colony formation, and apoptosis induction of ESCC. In addition of dual high expression of PI3K and PERK pathways in the ESCC patients, the difference of overall survival (OS) was more significant than using PI3K alone. These results indicated that dual targeting of PI3K and PERK pathways might improve clinical prognosis and enhance the treatment of ESCC patients.