Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma
Abstract Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCE...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-11-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.1806 |
| _version_ | 1797681452241911808 |
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| author | Yizi Wang Fang Ren Peng Chen Shuang Liu Zixuan Song Xiaoxin Ma |
| author_facet | Yizi Wang Fang Ren Peng Chen Shuang Liu Zixuan Song Xiaoxin Ma |
| author_sort | Yizi Wang |
| collection | DOAJ |
| description | Abstract Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P‐value <0.01 in the training set. Next, using robust likelihood‐based survival modeling, we developed a six‐gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six‐gene signature. According to the Kaplan‐Meier curve, patients in the high‐risk group had significantly poorer overall survival (OS) outcomes than those in the low‐risk group (log‐rank test P‐value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six‐gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC. |
| first_indexed | 2024-03-11T23:45:01Z |
| format | Article |
| id | doaj.art-7d8169d5284841b88766ab4b0e1904ec |
| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-03-11T23:45:01Z |
| publishDate | 2018-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cancer Medicine |
| spelling | doaj.art-7d8169d5284841b88766ab4b0e1904ec2023-09-19T11:30:57ZengWileyCancer Medicine2045-76342018-11-017115632564210.1002/cam4.1806Identification of a six‐gene signature with prognostic value for patients with endometrial carcinomaYizi Wang0Fang Ren1Peng Chen2Shuang Liu3Zixuan Song4Xiaoxin Ma5Department of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaDepartment of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaDepartment of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaDepartment of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaDepartment of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaDepartment of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang ChinaAbstract Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P‐value <0.01 in the training set. Next, using robust likelihood‐based survival modeling, we developed a six‐gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six‐gene signature. According to the Kaplan‐Meier curve, patients in the high‐risk group had significantly poorer overall survival (OS) outcomes than those in the low‐risk group (log‐rank test P‐value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six‐gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.https://doi.org/10.1002/cam4.1806gene signatureprognosisrbsurvThe Cancer Genome Atlasuterine corpus endometrial carcinoma |
| spellingShingle | Yizi Wang Fang Ren Peng Chen Shuang Liu Zixuan Song Xiaoxin Ma Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma Cancer Medicine gene signature prognosis rbsurv The Cancer Genome Atlas uterine corpus endometrial carcinoma |
| title | Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma |
| title_full | Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma |
| title_fullStr | Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma |
| title_full_unstemmed | Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma |
| title_short | Identification of a six‐gene signature with prognostic value for patients with endometrial carcinoma |
| title_sort | identification of a six gene signature with prognostic value for patients with endometrial carcinoma |
| topic | gene signature prognosis rbsurv The Cancer Genome Atlas uterine corpus endometrial carcinoma |
| url | https://doi.org/10.1002/cam4.1806 |
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