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Effectiveness of Gene Expression Profiling for Response Prediction of Rectal Adenocarcinomas to Preoperative Chemoradiotherapy

作者
Β. Michael Ghadimi,Marian Grade,Michael J. Difilippantonio,Sudhir Varma,Richard M Simon,Cristina Montagna,LASZLO FÜZESI,Claus Langer,Heinz Becker A,Torsten Liersch,Thomas Ried
出处
期刊:Journal of Clinical Oncology [Lippincott Williams & Wilkins]
卷期号:23 (9): 1826-1838 被引量:348
标识
DOI:10.1200/jco.2005.00.406
摘要

PURPOSE: There is a wide spectrum of tumor responsiveness of rectal adenocarcinomas to preoperative chemoradiotherapy ranging from complete response to complete resistance. This study aimed to investigate whether parallel gene expression profiling of the primary tumor can contribute to stratification of patients into groups of responders or nonresponders. PATIENTS AND METHODS: Pretherapeutic biopsies from 30 locally advanced rectal carcinomas were analyzed for gene expression signatures using microarrays. All patients were participants of a phase III clinical trial (CAO/ARO/AIO-94, German Rectal Cancer Trial) and were randomized to receive a preoperative combined-modality therapy including fluorouracil and radiation. Class comparison was used to identify a set of genes that were differentially expressed between responders and nonresponders as measured by T level downsizing and histopathologic tumor regression grading. RESULTS: In an initial set of 23 patients, responders and nonresponders showed significantly different expression levels for 54 genes (P < .001). The ability to predict response to therapy using gene expression profiles was rigorously evaluated using leave-one-out cross-validation. Tumor behavior was correctly predicted in 83% of patients (P = .02). Sensitivity (correct prediction of response) was 78%, and specificity (correct prediction of nonresponse) was 86%, with a positive and negative predictive value of 78% and 86%, respectively. CONCLUSION: Our results suggest that pretherapeutic gene expression profiling may assist in response prediction of rectal adenocarcinomas to preoperative chemoradiotherapy. The implementation of gene expression profiles for treatment stratification and clinical management of cancer patients requires validation in large, independent studies, which are now warranted.

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