Immediate Gene Expression Changes After the First Course of Neoadjuvant Chemotherapy in Patients with Primary Breast Cancer Disease

Purpose: Our goal was to identify genes undergoing expressional changes shortly after the beginning of neoadjuvant chemotherapy for primary breast cancer. Experimental Design: The biopsies were taken from patients with primary breast cancer prior to any treatment and 24 hours after the beginning of...

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Bibliographic Details
Published in:Clinical cancer research 2004-10, Vol.10 (19), p.6418-6431
Main Authors: MODLICH, Olga, PRISACK, Hans-Bernd, MUNNES, Marc, AUDRETSCH, Werner, BOJAR, Hans
Format: Article
Language:English
Subjects:
Adult
Aged
Algorithms
Antineoplastic agents
Antineoplastic Combined Chemotherapy Protocols - therapeutic use
Biological and medical sciences
Breast Neoplasms - drug therapy
Breast Neoplasms - genetics
Breast Neoplasms - pathology
Cluster Analysis
Cyclophosphamide - administration & dosage
Epirubicin - administration & dosage
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic - drug effects
Humans
Medical sciences
Middle Aged
Neoadjuvant Therapy
Oligonucleotide Array Sequence Analysis - methods
Pharmacology. Drug treatments
Reverse Transcriptase Polymerase Chain Reaction - methods
Time Factors
Tumors
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Summary:Purpose: Our goal was to identify genes undergoing expressional changes shortly after the beginning of neoadjuvant chemotherapy for primary breast cancer. Experimental Design: The biopsies were taken from patients with primary breast cancer prior to any treatment and 24 hours after the beginning of the neoadjuvant chemotherapy. Expression analyses from matched pair samples representing 25 patients were carried out with Clontech filter arrays. A subcohort of those 25 paired samples were additionally analyzed with the Affymetrix GeneChip platform. All of the transcripts from both platforms were queried for expressional changes. Results: Performing hierarchical cluster analysis, we clustered pre- and posttreatment samples from individual patients more closely to each other than the samples taken from different patients. This reflects the rather low number of transcripts responding directly to the drugs used. Although transcriptional drug response occurring during therapy differed between individual patients, two genes ( p21 WAF1/CIP1 and MIC-1 ) were up-regulated in posttreatment samples. This could be validated by semiquantitative and real-time reverse transcription-PCR. Partial least- discriminant analysis based on approximately 25 genes independently identified by either Clontech or Affymetrix platforms could clearly discriminate pre- and posttreatment samples. However, correlation of certain gene expression levels as well as of differential patterns and clusters as determined by a different platform was not always satisfying. Conclusions: This study has demonstrated the potential of monitoring posttreatment changes in gene expression as a measure of the pharmacodynamics of drugs. As a clinical laboratory model, it can be useful to identify patients with sensitive and reactive tumors and to help for optimized choice for sequential therapy and obviously improve relapse- free and overall survival.
ISSN:1078-0432
1557-3265
DOI:10.1158/1078-0432.CCR-04-1031