Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer.
PURPOSE: The aim of this study was to build a molecular prognostic model based on gene signatures for patients with completely resected hepatic metastases from colorectal cancer (MCRC). METHODS: Using the Illumina HumanHT-12 gene chip, RNA samples from the liver metastases of 96 patients who underwe...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3858250?pdf=render |
| _version_ | 1828877270760030208 |
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| author | Hiromichi Ito Qianxing Mo Li-Xuan Qin Agnes Viale Shishir K Maithel Ajay V Maker Jinru Shia Peter Kingham Peter Allen Ronald P DeMatteo Yuman Fong William R Jarnagin Michael D'Angelica |
| author_facet | Hiromichi Ito Qianxing Mo Li-Xuan Qin Agnes Viale Shishir K Maithel Ajay V Maker Jinru Shia Peter Kingham Peter Allen Ronald P DeMatteo Yuman Fong William R Jarnagin Michael D'Angelica |
| author_sort | Hiromichi Ito |
| collection | DOAJ |
| description | PURPOSE: The aim of this study was to build a molecular prognostic model based on gene signatures for patients with completely resected hepatic metastases from colorectal cancer (MCRC). METHODS: Using the Illumina HumanHT-12 gene chip, RNA samples from the liver metastases of 96 patients who underwent R0 liver resection were analyzed. Patients were randomly assigned to a training (n = 60) and test (n = 36) set. The genes associated with disease-specific survival (DSS) and liver-recurrence-free survival (LRFS) were identified by Cox-regression and selected to construct a molecular risk score (MRS) using the supervised principle component method on the training set. The MRS was then evaluated in the independent test set. RESULTS: Nineteen and 115 genes were selected to construct the MRS for DSS and LRFS, respectively. Each MRS was validated in the test set; 3-year DSS/LRFS rates were 42/32% and 79/80% for patients with high and low MRS, respectively (p = 0.007 for DSS and p = 0.046 for LRFS). In a multivariate model controlling for a previously validated clinical risk score (CRS), the MRS remained a significant predictor of DSS (p = 0.001) and LRFS (p = 0.03). When CRS and MRS were combined, the patients were discriminated better with 3-year DSS/LRFS rates of 90/89% in the low risk group (both risk scores low) vs 42/26% in the high risk group (both risk scores high), respectively (p = 0.002/0.004 for DSS/LRFS). CONCLUSION: MRS based on gene expression profiling has high prognostic value and is independent of CRS. This finding provides a potential strategy for better risk-stratification of patients with liver MCRC. |
| first_indexed | 2024-12-13T08:37:28Z |
| format | Article |
| id | doaj.art-b8f2599a8b1443d98774a65a038ebe64 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T08:37:28Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-b8f2599a8b1443d98774a65a038ebe642022-12-21T23:53:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01812e8168010.1371/journal.pone.0081680Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer.Hiromichi ItoQianxing MoLi-Xuan QinAgnes VialeShishir K MaithelAjay V MakerJinru ShiaPeter KinghamPeter AllenRonald P DeMatteoYuman FongWilliam R JarnaginMichael D'AngelicaPURPOSE: The aim of this study was to build a molecular prognostic model based on gene signatures for patients with completely resected hepatic metastases from colorectal cancer (MCRC). METHODS: Using the Illumina HumanHT-12 gene chip, RNA samples from the liver metastases of 96 patients who underwent R0 liver resection were analyzed. Patients were randomly assigned to a training (n = 60) and test (n = 36) set. The genes associated with disease-specific survival (DSS) and liver-recurrence-free survival (LRFS) were identified by Cox-regression and selected to construct a molecular risk score (MRS) using the supervised principle component method on the training set. The MRS was then evaluated in the independent test set. RESULTS: Nineteen and 115 genes were selected to construct the MRS for DSS and LRFS, respectively. Each MRS was validated in the test set; 3-year DSS/LRFS rates were 42/32% and 79/80% for patients with high and low MRS, respectively (p = 0.007 for DSS and p = 0.046 for LRFS). In a multivariate model controlling for a previously validated clinical risk score (CRS), the MRS remained a significant predictor of DSS (p = 0.001) and LRFS (p = 0.03). When CRS and MRS were combined, the patients were discriminated better with 3-year DSS/LRFS rates of 90/89% in the low risk group (both risk scores low) vs 42/26% in the high risk group (both risk scores high), respectively (p = 0.002/0.004 for DSS/LRFS). CONCLUSION: MRS based on gene expression profiling has high prognostic value and is independent of CRS. This finding provides a potential strategy for better risk-stratification of patients with liver MCRC.http://europepmc.org/articles/PMC3858250?pdf=render |
| spellingShingle | Hiromichi Ito Qianxing Mo Li-Xuan Qin Agnes Viale Shishir K Maithel Ajay V Maker Jinru Shia Peter Kingham Peter Allen Ronald P DeMatteo Yuman Fong William R Jarnagin Michael D'Angelica Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. PLoS ONE |
| title | Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. |
| title_full | Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. |
| title_fullStr | Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. |
| title_full_unstemmed | Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. |
| title_short | Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer. |
| title_sort | gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer |
| url | http://europepmc.org/articles/PMC3858250?pdf=render |
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