PURPOSE: Neoadjuvant chemotherapy for advanced breast cancer may improve the radicality for a subset of patients, but others may suffer from severe adverse drug reactions without any benefit. To predict the responses to chemotherapy, we performed a phase II trial of neoadjuvant chemotherapy using a weekly PCb [paclitaxel (Taxol) plus carboplatin] regimen for stage II/III breast cancer and assessed the correlation between baseline gene expression and the tumor response to treatment. METHODS: A total of 61 patients with stage II-III breast cancer were included and administered four cycles of preoperative PCb. We performed a gene expression analysis using Affymetrix HG-U133 Plus 2.0 GeneChip arrays in 31 breast cancer tissues. Differentially expressed genes (DEGs) were identified by the significance analysis of microarrays (SAM) program using a false discovery rate of 0.05. The Functional Annotation Tool in the DAVID Bioinformatics Resources was used to perform the gene functional enrichment analysis. The other 30 patients (15 pCR and 15 non-pCR patients) were available as an independent validation set to test the selected DEGs by quantitative real-time PCR analysis (qRT-PCR). RESULTS: By analyzing six pathological complete response (pCR) patients and 25 patients with non-pCR, 300 probes (231 genes) were identified as differentially expressed between pCR and residual disease by the SAM program when the fold change was >2. The gene functional enrichment analysis revealed 15 prominent gene categories that were different between pCR and non-pCR patients, most notably the genes involved in the peroxisome proliferator-activated receptor (PPAR), DNA repair and ER signal pathways and in the immune-related gene cluster. The qRT-PCR analysis results for the genes in the PPAR pathway (LPL, SORBS1, PLTP, SCD5, MMP1 and CSTA) in independent validation set were consistent with the results from the microarray data analysis. CONCLUSION: In the present study, we identified a number of gene categories pertinent to the therapeutic response. We believe that the PPAR pathway may be an important predictor of genes that are involved in the chemotherapy response.
PURPOSE: Neoadjuvant chemotherapy for advanced breast cancer may improve the radicality for a subset of patients, but others may suffer from severe adverse drug reactions without any benefit. To predict the responses to chemotherapy, we performed a phase II trial of neoadjuvant chemotherapy using a weekly PCb [paclitaxel (Taxol) plus carboplatin] regimen for stage II/III breast cancer and assessed the correlation between baseline gene expression and the tumor response to treatment. METHODS: A total of 61 patients with stage II-III breast cancer were included and administered four cycles of preoperative PCb. We performed a gene expression analysis using Affymetrix HG-U133 Plus 2.0 GeneChip arrays in 31 breast cancer tissues. Differentially expressed genes (DEGs) were identified by the significance analysis of microarrays (SAM) program using a false discovery rate of 0.05. The Functional Annotation Tool in the DAVID Bioinformatics Resources was used to perform the gene functional enrichment analysis. The other 30 patients (15 pCR and 15 non-pCR patients) were available as an independent validation set to test the selected DEGs by quantitative real-time PCR analysis (qRT-PCR). RESULTS: By analyzing six pathological complete response (pCR) patients and 25 patients with non-pCR, 300 probes (231 genes) were identified as differentially expressed between pCR and residual disease by the SAM program when the fold change was >2. The gene functional enrichment analysis revealed 15 prominent gene categories that were different between pCR and non-pCR patients, most notably the genes involved in the peroxisome proliferator-activated receptor (PPAR), DNA repair and ER signal pathways and in the immune-related gene cluster. The qRT-PCR analysis results for the genes in the PPAR pathway (LPL, SORBS1, PLTP, SCD5, MMP1 and CSTA) in independent validation set were consistent with the results from the microarray data analysis. CONCLUSION: In the present study, we identified a number of gene categories pertinent to the therapeutic response. We believe that the PPAR pathway may be an important predictor of genes that are involved in the chemotherapy response.
Authors: Anna Trebo; Nina Ditsch; Tom Degenhardt; Christina Kuhn; Martina Rahmeh; Elisa Schmoeckel; Doris Mayr; Bastian Czogalla; Thomas Kolben; Sarah Meister; Sven Mahner; Udo Jeschke; Anna Hester Journal: Int J Mol Sci Date: 2021-02-18 Impact factor: 5.923
Authors: Matthew P Shupe; Lindsey J Graham; Erika J Schneble; Frederick L Flynt; Michael N Clemenshaw; Aaron D Kirkpatrick; Alexander Stojadinovic; George E Peoples; Nathan M Shumway Journal: J Cancer Date: 2014-01-05 Impact factor: 4.207
Authors: Ivan V Ozerov; Ksenia V Lezhnina; Evgeny Izumchenko; Artem V Artemov; Sergey Medintsev; Quentin Vanhaelen; Alexander Aliper; Jan Vijg; Andreyan N Osipov; Ivan Labat; Michael D West; Anton Buzdin; Charles R Cantor; Yuri Nikolsky; Nikolay Borisov; Irina Irincheeva; Edward Khokhlovich; David Sidransky; Miguel Luiz Camargo; Alex Zhavoronkov Journal: Nat Commun Date: 2016-11-16 Impact factor: 14.919