Yang Lin, Hong Shaodong, Wang Yan, He Zhenyu, Liang Shaobo, Chen Haiyang, He Shasha, Wu Shu, Song Libing, Chen Yong
Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China.
State Key Laboratory of Oncology in Southern China, Guangzhou 510060, China.
Oncotarget. 2016 Apr 19;7(16):22720-32. doi: 10.18632/oncotarget.8150.
The role of CDGSH iron sulfur domain 2 (CISD2) in laryngeal squamous cell carcinoma (LSCC) remains unclear.
CISD2 were up-regulated in LSCC tissues compared with adjacent noncancerous tissues both at mRNA and protein levels. CISD2 was significantly correlated with T stage, lymph node metastasis, clinical stage and disease progression. A prognostic model (C-N model) for PFS was subsequently constructed based on independent prognostic factors including CISD2 and N classification. This model significantly divided LSCC patients into three risk subgroups and was more accurate than the prediction efficacy of TNM classification in the training cohort (C-index, 0.710 vs 0.602, P = 0.027) and validation cohort (C-index, 0.719 vs 0.578, P = 0.014).
Real-time PCR and Western blotting were employed to examine the expression of CISD2 in eight fresh paired LSCC samples. Immunohistochemistry was performed to assess CISD2 expression in 490 paraffin-embedded archived LSCC samples. A prognostic model for progression-free survival (PFS) was built using independent factors. The concordance index (C-Index) was used to evaluate the prognostic ability of the model.
CISD2 was up-regulated in LSCC. The novel C-N model, which includes CISD2 levels and N classification, is more accurate than conventional TNM classification for predicting PFS in LSCC.
CDGSH铁硫结构域2(CISD2)在喉鳞状细胞癌(LSCC)中的作用尚不清楚。
与相邻正常组织相比,CISD2在LSCC组织中的mRNA和蛋白质水平均上调。CISD2与T分期、淋巴结转移、临床分期和疾病进展显著相关。随后基于包括CISD2和N分类在内的独立预后因素构建了无进展生存期(PFS)的预后模型(C-N模型)。该模型将LSCC患者显著分为三个风险亚组,在训练队列(C指数,0.710对0.602,P = 0.027)和验证队列(C指数,0.719对0.578,P = 0.014)中比TNM分类的预测效能更准确。
采用实时PCR和蛋白质印迹法检测8对新鲜LSCC样本中CISD2的表达。采用免疫组织化学法评估490例石蜡包埋存档LSCC样本中CISD2的表达。使用独立因素构建无进展生存期(PFS)的预后模型。一致性指数(C指数)用于评估模型的预后能力。
CISD2在LSCC中上调。包含CISD2水平和N分类的新型C-N模型在预测LSCC的PFS方面比传统TNM分类更准确。