Stage III Colon Cancer Prognosis Prediction by Tumor Gene Expression Profiling

2006 ◽  
Vol 101 ◽  
pp. S221
Author(s):  
Alain J. Barrier ◽  
Antoinette Lemoine ◽  
Sandrine Dudoit
2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10590-10590
Author(s):  
A. Barrier ◽  
P. Boelle ◽  
D. Brault ◽  
S. Houry ◽  
F. Lacaine ◽  
...  

10590 Background and Aims: Postoperative chemotherapy has become part of the standard treatment for stage III colon cancer patients. Since approximately half of patients are cured by surgery alone, adjuvant chemotherapy should not be used in all patients. This study aimed to assess the possibility to use microarray-based gene expression profiles to predict the prognosis of stage III colon cancer patients. Material and Methods: Forty-two patients operated on for a stage III colon cancer were included in this study. Twenty-one patients have received an adjuvant chemotherapy, while the other 21 have received no treatment. Twenty patients have developed a liver metastasis, while the other 22 have remained disease-free for at least 5 years. Tumor mRNA samples were profiled using the Affymetrix HGU133A GeneChip. Two analyses were performed: one with the 42 patients, the other with the 21 patients who did not receive any adjuvant chemotherapy. For each analysis, patients were repeatedly and randomly divided into 10,000 training (TS) and validation sets (VS) of 10 different sizes. For each TS/VS split, a 30-gene prognosis predictor (PP), identified on the TS, was used to predict the prognosis of VS patients. Performances of a 15-gene PP and a 34-gene PP, proposed by another research team, were also assessed on the same TS and VS. Results: First analysis (42 patients). The 10,000 30-gene PP yielded the following average prognosis prediction performance measures: 73.8% accuracy, 74.6% sensitivity, and 73.0% specificity. Improvements in prognosis prediction were observed with increasing TS size. A total of 4,446 genes were included in the 10,000 PP. The 15-gene PP yielded a 69.7% accuracy; the 34-gene PP yielded a 71.2% accuracy. Second analysis (21 patients). The 10,000 30-gene PP yielded the following average prognosis prediction performance measures: 77.7% accuracy, 75.8% sensitivity, and 79.9% specificity. Improvements in prognosis prediction were observed with increasing TS size. A total of 5,478 genes were included in the 10,000 PP. The 15-gene PP yielded a 78.5% accuracy; the 34-gene PP yielded a 81.9% accuracy. Conclusion: Microarray gene expression profiling is able to predict the prognosis of stage III colon cancer patients and, thus, might be used for an appropriate use of adjuvant chemotherapy. No significant financial relationships to disclose.


Oncogene ◽  
2005 ◽  
Vol 24 (40) ◽  
pp. 6155-6164 ◽  
Author(s):  
Alain Barrier ◽  
Antoinette Lemoine ◽  
Pierre-Yves Boelle ◽  
Chantal Tse ◽  
Didier Brault ◽  
...  

2015 ◽  
Vol 11 (4) ◽  
pp. 273-277 ◽  
Author(s):  
Megan C. Roberts ◽  
Stacie B. Dusetzina

Gene expression profiling has diffused into clinical practice. Reimbursements by insurers have increased, and average out-of-pocket costs to patients have decreased, seemingly driven by improved coverage for testing over time.


2006 ◽  
Vol 24 (29) ◽  
pp. 4685-4691 ◽  
Author(s):  
Alain Barrier ◽  
Pierre-Yves Boelle ◽  
François Roser ◽  
Jennifer Gregg ◽  
Chantal Tse ◽  
...  

Purpose This study mainly aimed to identify and assess the performance of a microarray-based prognosis predictor (PP) for stage II colon cancer. A previously suggested 23-gene prognosis signature (PS) was also evaluated. Patients and Methods Tumor mRNA samples from 50 patients were profiled using oligonucleotide microarrays. PPs were built and assessed by random divisions of patients into training and validation sets (TSs and VSs, respectively). For each TS/VS split, a 30-gene PP, identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Two schemes were considered: single-split validation, based on a single random split of patients into two groups of equal size (group 1 and group 2), and Monte Carlo cross validation (MCCV), whereby patients were repeatedly and randomly divided into TS and VS of various sizes. Results The 30-gene PP, identified from group 1 patients, yielded an 80% prognosis prediction accuracy on group 2 patients. MCCV yielded the following average prognosis prediction performance measures: 76.3% accuracy, 85.1% sensitivity, and 67.5% specificity. Improvements in prognosis prediction were observed with increasing TS size. The 30-gene PS were found to be highly-variable across TS/VS splits. Assessed on the same random splits of patients, the previously suggested 23-gene PS yielded a 67.7% mean prognosis prediction accuracy. Conclusion Microarray gene expression profiling is able to predict the prognosis of stage II colon cancer patients. The present study also illustrates the usefulness of resampling techniques for honest performance assessment of microarray-based PPs.


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