Ferroptosis-Related Gene Model to Predict Overall Survival of Ovarian Carcinoma.
Ferroptosis-Related Gene Model to Predict Overall Survival of Ovarian Carcinoma.
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DOI：
10.1155/2021/6687391
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发表时间：
2021
影响因子：
--
通讯作者：
Zhang Q
中科院分区：
文献类型：
--
作者：
Yang L;Tian S;Chen Y;Miao C;Zhao Y;Wang R;Zhang Q
卵巢癌（OC）是世界上第八大最常见的癌症死亡原因，也是第二大妇科癌症死亡原因。铁下垂是一种铁依赖性调节细胞死亡，在许多癌症的发展中起着至关重要的作用。利用凋亡相关基因的表达预测肿瘤的进展，有助于癌症的治疗。然而，铁下垂相关基因与OC患者预后之间的关系仍然非常未知，这使得开发铁下垂治疗OC仍然是一个挑战。获取OC的癌症基因组图谱（Cancer Genome Atlas， TCGA）数据，随机分为训练数据集和测试数据集。根据训练队列，构建了一个与总生存（OS）相关的新铁衰相关基因特征。使用测试数据集和ICGC数据集验证该签名。我们构建了包含9个铁中毒相关基因LPCAT3、ACSL3、CRYAB、PTGS2、ALOX12、HSBP1、SLC1A5、SLC7A11、ZEB1的模型，预测TCGA OC的OS。在适当的截止点，将患者分为低危组和高危组。两组患者的OS曲线差异有统计学意义，时间依赖性受试者操作特征（roc）分别高达0.664。然后使用测试数据集和ICGC数据集对我们的模型进行评估，测试数据集的roc分别为0.667和0.777。此外，功能分析和相关分析显示免疫相关通路显著丰富。同时，我们还综合了其他临床因素，我们发现综合临床因素和残铁相关基因标记相对于单独残铁相关基因标记提高了预后的准确性。衰铁相关基因标记可预测OC患者的OS，改善治疗决策。
Ovarian cancer (OC) is the eighth most common cause of cancer death and the second cause of gynecologic cancer death in women around the world. Ferroptosis, an iron-dependent regulated cell death, plays a vital role in the development of many cancers. Applying expression of ferroptosis-related gene to forecast the cancer progression is helpful for cancer treatment. However, the relationship between ferroptosis-related genes and OC patient prognosis is still vastly unknown, making it still a challenge for developing ferroptosis therapy for OC. The Cancer Genome Atlas (TCGA) data of OC were obtained and the datasets were randomly divided into training and test datasets. A novel ferroptosis-related gene signature associated with overall survival (OS) was constructed according to the training cohort. The test dataset and ICGC dataset were used to validate this signature. We constructed a model containing nine ferroptosis-related genes, namely, LPCAT3, ACSL3, CRYAB, PTGS2, ALOX12, HSBP1, SLC1A5, SLC7A11, and ZEB1, and predicted the OS of OC in TCGA. At a suitable cutoff, patients were divided into low risk and high risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics (ROCs) were as high as 0.664, respectively. Then, the test dataset and the ICGC dataset were used to evaluate our model, and the ROCs of test dataset were 0.667 and 0.777, respectively. In addition, functional analysis and correlation analysis showed that immune-related pathways were significantly enriched. Meanwhile, we also integrated with other clinical factors and we found the synthesized clinical factors and ferroptosis-related gene signature improved prognostic accuracy relative to the ferroptosis-related gene signature alone. The ferroptosis-related gene signature could predict the OS of OC patients and improve therapeutic decision-making.
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DOI：
10.1158/1055-9965.epi-18-0346
发表时间：
2018-12
期刊：
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
影响因子：
--
作者：
Barnard ME;Hecht JL;Rice MS;Gupta M;Harris HR;Eliassen AH;Rosner BA;Terry KL;Tworoger SS
通讯作者：
Tworoger SS
影响因子：
5.6
作者：
Jakhar, Rekha;Sharma, Chanchal;Kang, Sun Chul
通讯作者：
Kang, Sun Chul
影响因子：
2.9
作者：
Liu H;Schreiber SL;Stockwell BR
通讯作者：
Stockwell BR
铁死亡相关基因特征预测神经胶质瘤细胞死亡和神经胶质瘤患者进展
影响因子：
5.5
作者：
Liu, Han-jie;Hu, Hui-min;Jiang, Tao
通讯作者：
Jiang, Tao
影响因子：
50.5
作者：
Eisenhauer, E. A.
通讯作者：
Eisenhauer, E. A.