Yang Chun-Wei, Wang Shu-Fang, Yang Xiang-Li, Wang Lin, Niu Lin, Liu Ji-Xiang
Department of Otorhinolaryngology Head and Neck Surgery, Tianjin Union Medical Center Intensive Care Unit, General Hospital Airport Hospital, Tianjin Medical University, Tianjin, China.
Medicine (Baltimore). 2018 Feb;97(7):e9738. doi: 10.1097/MD.0000000000009738.
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.
喉鳞状细胞癌（LSCC）是最常见的头颈癌之一。LSCC死亡率高，预后较差。尽管在基因和治疗方面取得了进展，生存率有所提高，但导致LSCC发生和发展的分子机制仍不完全清楚。在本研究中，从LSCC样本中筛选出总共116个差异表达基因（DEG），包括11个上调基因和105个下调基因，并与相邻的非癌组织进行比较。在本研究中发现肿瘤和非肿瘤喉组织样本之间的表达存在统计学显著差异（log 2倍差异>0.5且调整后的P值<0.05）。发现9个癌症枢纽基因对区分肿瘤和非肿瘤喉组织样本具有较高的预测能力。有趣的是，它们似乎还通过Jak-STAT信号通路和粘着斑促进LSCC的进展和恶性肿瘤的发生。仅使用mRNA特征的表达水平时，该模型可以成功地将患者分为高风险和低风险组。在加权共表达网络中为DEG筛选出总共4个模块（蓝色、灰色、绿松石色和黄色）。蓝色模型包括癌症特异性途径，如胰腺癌、膀胱癌、非小细胞肺癌、结直肠癌、神经胶质瘤、Hippo信号通路、黑色素瘤、慢性粒细胞白血病、前列腺癌和癌症中的蛋白聚糖。内分泌抵抗（CCND1、RAF1、RB1和SMAD2）和Hippo信号通路（CCND1、LATS1、SMAD2和TP53BP2）在LSCC中可能很重要，因为它们在蓝色模块中具有较高的连接度。本研究结果提供了一个强大的生物标志物发现平台，以增进对LSCC进展的理解，并揭示LSCC治疗中的潜在治疗靶点。这些信息可能会改善对LSCC的监测并从而改善LSCC的治疗。
