He Xiangjun, Lei Shu, Zhang Qi, Ma Liping, Li Na, Wang Jianliu
Central Laboratory and Institute of Clinical Molecular Biology, Peking University People's Hospital, Beijing 100044, P.R. China.
Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing 100044, P.R. China.
Oncol Lett. 2020 Mar;19(3):1906-1914. doi: 10.3892/ol.2020.11295. Epub 2020 Jan 13.
Cell adhesion molecules (CAMs) determine the behavior of cancer cells during metastasis. Although some CAMs are dysregulated in certain types of cancer and are associated with cancer progression, to the best of our knowledge, a comprehensive study of CAMs has not been undertaken, particularly in endometrial cancer (EC). In the present study the expression of 225 CAMs in EC patients with various clinicopathological phenotypes were evaluated by statistical analysis using publicly available data from The Cancer Genome Atlas database. The Kaplan-Meier method, and univariate and multivariate Cox proportional hazards regression models were used for survival analyses. Among the differentially expressed CAMs that were associated with aggressive clinicopathological phenotypes, 10 CAM genes were independent prognostic factors compared with other clinicopathological prognostic factors, including stage, grade, age, lymph node status, peritoneal cytology and histological subtype. A total of six genes (L1 cell adhesion molecule, mucin 15, cell surface associated, cell adhesion associated, oncogene regulated, immunoglobulin superfamily member 9B, protocadherin 9 and protocadherin β1) were selected for integrative analysis. The six-gene signature was demonstrated to be an independent prognostic factor and could effectively stratify patients with different risks. Patients with more high-expression CAMs had a higher risk of poor overall survival (OS) rate. The mortality risk for patients with elevation of >4 CAMs was 11 times of that in those without elevation of these 6 CAMs. Similar results were obtained when relapse-free survival (RFS) time was used during the analysis. Prognostic reliability of the six-gene model was validated using data of an independent cohort from the International Cancer Genome Consortium. In conclusion, a combination of CAM alterations contributed to progression and aggressiveness of EC. The six-gene signature was effective for predicting worse OS and RFS in patients with EC and could be complementary to the present clinical prognostic criteria.
细胞黏附分子(CAMs)决定癌细胞在转移过程中的行为。尽管某些CAMs在特定类型的癌症中表达失调并与癌症进展相关,但据我们所知,尚未对CAMs进行全面研究,尤其是在子宫内膜癌(EC)中。在本研究中,利用来自癌症基因组图谱数据库的公开可用数据,通过统计分析评估了具有各种临床病理表型的EC患者中225种CAMs的表达。采用Kaplan-Meier法以及单因素和多因素Cox比例风险回归模型进行生存分析。在与侵袭性临床病理表型相关的差异表达CAMs中,与包括分期、分级、年龄、淋巴结状态、腹腔细胞学和组织学亚型等其他临床病理预后因素相比,有10个CAM基因是独立的预后因素。总共选择了6个基因(L1细胞黏附分子、黏蛋白15、细胞表面相关、细胞黏附相关、癌基因调控、免疫球蛋白超家族成员9B、原钙黏蛋白9和原钙黏蛋白β1)进行综合分析。这6个基因的特征被证明是一个独立的预后因素,并且可以有效地对具有不同风险的患者进行分层。具有更多高表达CAMs的患者总体生存率(OS)较差的风险更高。>4种CAMs升高的患者的死亡风险是未升高这6种CAMs患者的11倍。在分析过程中使用无复发生存期(RFS)时间时也获得了类似的结果。使用来自国际癌症基因组联盟的独立队列数据验证了六基因模型的预后可靠性。总之,CAMs改变的组合促成了EC的进展和侵袭性。这6个基因的特征对于预测EC患者较差的OS和RFS有效,并且可以补充当前的临床预后标准。