Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis
Kidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predic...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-05-01
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| Series: | Animal Cells and Systems |
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| Online Access: | http://dx.doi.org/10.1080/19768354.2020.1760932 |
| _version_ | 1828749595035828224 |
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| author | Huiming Jiang Haibin Chen Nanhui Chen |
| author_facet | Huiming Jiang Haibin Chen Nanhui Chen |
| author_sort | Huiming Jiang |
| collection | DOAJ |
| description | Kidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predicting overall survival (OS) in patients with KIRC. The mRNA expression profile and clinical data of patients with KIRC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Prognosis-associated genes were identified, and a prognostic gene signature was constructed. Then, the prognostic efficiency of the gene signature was assessed. The results obtained using data from the TCGA were validated using those from the ICGC and other online databases. Gene set enrichment analyses (GSEA) were performed to explore potential molecular mechanisms. A seven-gene signature (PODXL, SLC16A12, ZIC2, ATP2B3, KRT75, C20orf141, and CHGA) was constructed, and it was found to be effective in classifying KIRC patients into high- and low-risk groups, with significantly different survival based on the TCGA and ICGC validation data set. Cox regression analysis revealed that the seven-gene signature had an independent prognostic value. Then, we established a nomogram, including the seven-gene signature, which had a significant clinical net benefit. Interestingly, the seven-gene signature had a good performance in distinguishing KIRC from normal tissues. GSEA revealed that several oncological signatures and GO terms were enriched. This study developed a novel seven-gene signature and nomogram for predicting the OS of patients with KIRC, which may be helpful for clinicians in establishing individualized treatments. |
| first_indexed | 2024-12-10T20:24:19Z |
| format | Article |
| id | doaj.art-e693177485ca43b796cc7418c2819aad |
| institution | Directory Open Access Journal |
| issn | 1976-8354 2151-2485 |
| language | English |
| last_indexed | 2024-12-10T20:24:19Z |
| publishDate | 2020-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Animal Cells and Systems |
| spelling | doaj.art-e693177485ca43b796cc7418c2819aad2022-12-22T01:34:55ZengTaylor & Francis GroupAnimal Cells and Systems1976-83542151-24852020-05-0124316017010.1080/19768354.2020.17609321760932Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysisHuiming Jiang0Haibin Chen1Nanhui Chen2Department of Urology, Meizhou People’s Hospital (Huangtang Hospital), Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka PopulationDepartment of Histology and Embryology, Shantou University Medical CollegeDepartment of Urology, Meizhou People’s Hospital (Huangtang Hospital), Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka PopulationKidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predicting overall survival (OS) in patients with KIRC. The mRNA expression profile and clinical data of patients with KIRC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Prognosis-associated genes were identified, and a prognostic gene signature was constructed. Then, the prognostic efficiency of the gene signature was assessed. The results obtained using data from the TCGA were validated using those from the ICGC and other online databases. Gene set enrichment analyses (GSEA) were performed to explore potential molecular mechanisms. A seven-gene signature (PODXL, SLC16A12, ZIC2, ATP2B3, KRT75, C20orf141, and CHGA) was constructed, and it was found to be effective in classifying KIRC patients into high- and low-risk groups, with significantly different survival based on the TCGA and ICGC validation data set. Cox regression analysis revealed that the seven-gene signature had an independent prognostic value. Then, we established a nomogram, including the seven-gene signature, which had a significant clinical net benefit. Interestingly, the seven-gene signature had a good performance in distinguishing KIRC from normal tissues. GSEA revealed that several oncological signatures and GO terms were enriched. This study developed a novel seven-gene signature and nomogram for predicting the OS of patients with KIRC, which may be helpful for clinicians in establishing individualized treatments.http://dx.doi.org/10.1080/19768354.2020.1760932kidney renal clear cell carcinomatcgaicgcgene signatureprognosis |
| spellingShingle | Huiming Jiang Haibin Chen Nanhui Chen Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis Animal Cells and Systems kidney renal clear cell carcinoma tcga icgc gene signature prognosis |
| title | Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| title_full | Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| title_fullStr | Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| title_full_unstemmed | Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| title_short | Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| title_sort | construction and validation of a seven gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis |
| topic | kidney renal clear cell carcinoma tcga icgc gene signature prognosis |
| url | http://dx.doi.org/10.1080/19768354.2020.1760932 |
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