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| Status |
Public on Mar 31, 2023 |
| Title |
Molecular Markers for Predicting Treatment Outcome in Patients with Rectal Cancer: A Comprehensive Analysis from the German Rectal Cancer Trials |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.
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| Overall design |
Tumor samples from a total of 245 patients (198 samples for classifier training and 47 samples for validation)
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| Contributor(s) |
Gaedcke J, Jo P, Jung K, Grade M, Kitz J, Wolff HA, Salinas-Riester G, Sax U, Conradi LC, Rüschoff J, Matzel KE, Grünewald V, Schrader D, Burkowski I, Weyhe D, Hesterberg R, Kania U, Hohenberger W, Becker H, Sauer R, Hess CF, Rödel C, Ried T, Liersch T, Beißbarth T, Ghadimi M |
| Citation missing |
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| Submission date |
Aug 30, 2012 |
| Last update date |
Apr 21, 2023 |
| Contact name |
Tim Beissbarth |
| E-mail(s) |
tim.beissbarth@ams.med.uni-goettingen.de
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| Organization name |
University Medical Center Göttingen
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| Department |
Medical Statistics
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| Street address |
Humboldtallee 32
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| City |
Göttingen |
| ZIP/Postal code |
37073 |
| Country |
Germany |
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| Platforms (1) |
| GPL10332 |
Agilent-026652 Whole Human Genome Microarray 4x44K v2 (Feature Number version) |
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| Samples (245)
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| Relations |
| BioProject |
PRJNA174168 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE40492_RAW.tar |
536.1 Mb |
(http)(custom) |
TAR (of TXT) |
| Processed data included within Sample table |
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