Open AccessIdentification of gene expression models for laryngeal squamous cell carcinoma using co-expression network analysis
Author(s) -
Chao Yang,
Shufang Wang,
Xiangli Yang,
Lin Wang,
Lin Niu,
Jixiang Liu
Publication year - 2018
Publication title -
medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 148
eISSN - 1536-5964
pISSN - 0025-7974
DOI - 10.1097/md.0000000000009738
Subject(s) - medicine , cancer research , cancer , head and neck squamous cell carcinoma , malignancy , hippo signaling pathway , pathology , oncology , head and neck cancer , immunology , effector
One of the most common head and neck cancers is laryngeal squamous cell carcinoma (LSCC). LSCC exhibits high mortality rates and has a poor prognosis. The molecular mechanisms leading to the development and progression of LSCC are not entirely clear despite genetic and therapeutic advances and increased survival rates. In this study, a total of 116 differentially expressed genes (DEGs), including 11 upregulated genes and 105 downregulated genes, were screened from LSCC samples and compared with adjacent noncancerous. Statistically significant differences (log 2-fold difference > 0.5 and adjusted P- value < .05) were found in this study in the expression between tumor and nontumor larynx tissue samples. Nine cancer hub genes were found to have a high predictive power to distinguish between tumor and nontumor larynx tissue samples. Interestingly, they also appear to contribute to the progression of LSCC and malignancy via the Jak-STAT signaling pathway and focal adhesion. The model could separate patients into high-risk and low-risk groups successfully when only using the expression level of mRNA signatures. A total of 4 modules (blue, gray, turquoise, and yellow) were screened for the DEGs in the weighted co-expression network. The blue model includes cancer-specific pathways such as pancreatic cancer, bladder cancer, nonsmall cell lung cancer, colorectal cancer, glioma, Hippo signaling pathway, melanoma, chronic myeloid leukemia, prostate cancer, and proteoglycans in cancer. Endocrine resistance (CCND1, RAF1, RB1, and SMAD2) and Hippo signaling pathway (CCND1, LATS1, SMAD2, and TP53BP2) could be of importance in LSCC, because they had high connectivity degrees in the blue module. Results from this study provide a powerful biomarker discovery platform to increase understanding of the progression of LSCC and to reveal potential therapeutic targets in the treatment of LSCC. Improved monitoring of LSCC and resulting improvement of treatment of LSCC might result from this information.