A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy
Abstract Background In this study we aimed to identify a prognostic signature in BRCA1/2 mutations to predict disease progression and the efficiency of chemotherapy ovarian cancer (OV), the second most common cause of death from gynecologic cancer in women worldwide. Methods Univariate Cox proportio...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-09-01
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| Series: | Journal of Ovarian Research |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13048-020-00712-w |
| _version_ | 1828078051889512448 |
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| author | Yinglian Pan Li Ping Jia Yuzhu Liu Yiyu Han Qian Li Qin Zou Zhongpei Zhang Jin Huang Qingchun Deng |
| author_facet | Yinglian Pan Li Ping Jia Yuzhu Liu Yiyu Han Qian Li Qin Zou Zhongpei Zhang Jin Huang Qingchun Deng |
| author_sort | Yinglian Pan |
| collection | DOAJ |
| description | Abstract Background In this study we aimed to identify a prognostic signature in BRCA1/2 mutations to predict disease progression and the efficiency of chemotherapy ovarian cancer (OV), the second most common cause of death from gynecologic cancer in women worldwide. Methods Univariate Cox proportional-hazards and multivariate Cox regression analyses were used to identifying prognostic factors from data obtained from The Cancer Genome Atlas (TCGA) database. The area under the curve of the receiver operating characteristic curve was assessed, and the sensitivity and specificity of the prediction model were determined. Results A signature consisting of two long noncoding RNAs(lncRNAs), Z98885.2 and AC011601.1, was selected as the basis for classifying patients into high and low-risk groups (median survival: 7.2 years vs. 2.3 years). The three-year overall survival (OS) rates for the high- and low-risk group were approximately 38 and 100%, respectively. Chemotherapy treatment survival rates indicated that the high-risk group had significantly lower OS rates with adjuvant chemotherapy than the low-risk group. The one-, three-, and five-year OS were 100, 40, and 15% respectively in the high-risk group. The survival rate of the high-risk group declined rapidly after 2 years of OV chemotherapy treatment. Multivariate Cox regression associated with other traditional clinical factors showed that the 2-lncRNA model could be used as an independent OV prognostic factor. Analyses of data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) indicated that these signatures are pivotal to cancer development. Conclusion In conclusion, Z98885.2 and AC011601.1 comprise a novel prognostic signature for OV patients with BRCA1/2 mutations, and can be used to predict prognosis and the efficiency of chemotherapy. |
| first_indexed | 2024-04-11T02:41:25Z |
| format | Article |
| id | doaj.art-b887684a7f9841699031b4a6b82692f0 |
| institution | Directory Open Access Journal |
| issn | 1757-2215 |
| language | English |
| last_indexed | 2024-04-11T02:41:25Z |
| publishDate | 2020-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Ovarian Research |
| spelling | doaj.art-b887684a7f9841699031b4a6b82692f02023-01-02T19:02:28ZengBMCJournal of Ovarian Research1757-22152020-09-0113111010.1186/s13048-020-00712-wA novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapyYinglian Pan0Li Ping Jia1Yuzhu Liu2Yiyu Han3Qian Li4Qin Zou5Zhongpei Zhang6Jin Huang7Qingchun Deng8Department of Medical Oncology, The First Affiliated Hospital of Hainan Medical UniversityDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical UniversityDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical UniversityDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical UniversityDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology WuhanDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology WuhanDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology WuhanDepartment of Clinical Laboratory, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology WuhanDepartment of Gynecology, The Second Affiliated Hospital of Hainan Medical UniversityAbstract Background In this study we aimed to identify a prognostic signature in BRCA1/2 mutations to predict disease progression and the efficiency of chemotherapy ovarian cancer (OV), the second most common cause of death from gynecologic cancer in women worldwide. Methods Univariate Cox proportional-hazards and multivariate Cox regression analyses were used to identifying prognostic factors from data obtained from The Cancer Genome Atlas (TCGA) database. The area under the curve of the receiver operating characteristic curve was assessed, and the sensitivity and specificity of the prediction model were determined. Results A signature consisting of two long noncoding RNAs(lncRNAs), Z98885.2 and AC011601.1, was selected as the basis for classifying patients into high and low-risk groups (median survival: 7.2 years vs. 2.3 years). The three-year overall survival (OS) rates for the high- and low-risk group were approximately 38 and 100%, respectively. Chemotherapy treatment survival rates indicated that the high-risk group had significantly lower OS rates with adjuvant chemotherapy than the low-risk group. The one-, three-, and five-year OS were 100, 40, and 15% respectively in the high-risk group. The survival rate of the high-risk group declined rapidly after 2 years of OV chemotherapy treatment. Multivariate Cox regression associated with other traditional clinical factors showed that the 2-lncRNA model could be used as an independent OV prognostic factor. Analyses of data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) indicated that these signatures are pivotal to cancer development. Conclusion In conclusion, Z98885.2 and AC011601.1 comprise a novel prognostic signature for OV patients with BRCA1/2 mutations, and can be used to predict prognosis and the efficiency of chemotherapy.http://link.springer.com/article/10.1186/s13048-020-00712-wOvarian cancerLong non-coding RNAPrognostic biomarkerMutationsBRCA1/2 geneChemotherapy |
| spellingShingle | Yinglian Pan Li Ping Jia Yuzhu Liu Yiyu Han Qian Li Qin Zou Zhongpei Zhang Jin Huang Qingchun Deng A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy Journal of Ovarian Research Ovarian cancer Long non-coding RNA Prognostic biomarker Mutations BRCA1/2 gene Chemotherapy |
| title | A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| title_full | A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| title_fullStr | A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| title_full_unstemmed | A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| title_short | A novel signature of two long non-coding RNAs in BRCA mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| title_sort | novel signature of two long non coding rnas in brca mutant ovarian cancer to predict prognosis and efficiency of chemotherapy |
| topic | Ovarian cancer Long non-coding RNA Prognostic biomarker Mutations BRCA1/2 gene Chemotherapy |
| url | http://link.springer.com/article/10.1186/s13048-020-00712-w |
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