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Pretreatment Gene Expression Profiles Can Be Used to Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

  • Gastrointestinal Oncology
  • Original Papers
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

The use of neoadjuvant therapy, in particular chemoradiotherapy (CRT), in the treatment of esophageal cancer (EC) remains controversial. The ability to predict treatment response in an individual EC patient would greatly aid therapeutic planning. Gene expression profiles of EC were measured and relationship to therapeutic response assessed.

Methods

Tumor biopsy samples taken from 46 EC patients before neoadjuvant CRT were analyzed on 10.5K cDNA microarrays. Response to treatment was assessed and correlated to gene expression patterns by using a support vector machine learning algorithm.

Results

Complete clinical response at conclusion of CRT was achieved in 6 of 21 squamous cell carcinoma (SCC) and 11 of 25 adenocarcinoma (AC) patients. CRT response was an independent prognostic factor for survival (P < .001). A range of support vector machine models incorporating 10 to 1000 genes produced a predictive performance of tumor response to CRT peaking at 87% in SCC, but a distinct positive prediction profile was unobtainable for AC. A 32-gene classifier was produced, and by means of this classifier, 10 of 21 SCC patients could be accurately identified as having disease with an incomplete response to therapy, and thus unlikely to benefit from neoadjuvant CRT.

Conclusions

Our study identifies a 32-gene classifier that can be used to predict response to neoadjuvant CRT in SCC. However, because of the molecular diversity between the two histological subtypes of EC, when considering the AC and SCC samples as a single cohort, a predictive profile could not be resolved, and a negative predictive profile was observed for AC.

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Acknowledgments

We thank David Bowtell and the staff of the Peter MacCallum Cancer Centre Microarray Facility for their help and support. We also thank Robert Chen, Rodney Hicks, Suzanne Lipshut, Anne Thompson, and the many surgeons and oncologists who provided patients for this study, for their valuable assistance. This work was supported in part by project grant 350414 from the National Health and Medical Research Council (NHMRC) of Australia to W.P. and R.T.

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Authors and Affiliations

  1. Division of Surgical Oncology, Peter MacCallum Cancer Centre, St. Andrew’s Place, East Melbourne, Victoria, 3002, Australia

    Cuong Duong, Danielle M. Greenawalt, Marianne L. Ciavarella, Wayne A. Phillips & Robert J. S. Thomas

  2. Life Sciences, National Information and Communications Technology Australia and Department Electrical & Electronic Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia

    Adam Kowalczyk & Garvesh Raskutti

  3. Department of Pathology, Peter MacCallum Cancer Centre, St. Andrew’s Place, East Melbourne, Victoria, 3002, Australia

    William K. Murray

  4. University of Melbourne Department of Surgery, St. Vincent’s Hospital, Fitzroy, Victoria, 3065, Australia

    Wayne A. Phillips & Robert J. S. Thomas

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  1. Cuong Duong
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Correspondence to Wayne A. Phillips.

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Duong, C., Greenawalt, D.M., Kowalczyk, A. et al. Pretreatment Gene Expression Profiles Can Be Used to Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer. Ann Surg Oncol 14, 3602–3609 (2007). https://doi.org/10.1245/s10434-007-9550-1

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  • DOI: https://doi.org/10.1245/s10434-007-9550-1

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