Predicting response to primary chemotherapy: Gene expression profiling of paraffin-embedded core biopsy tissue

Department of Medicine, Indiana University, RT-473, Indianapolis, IN, 46202, USA.
Breast Cancer Research and Treatment (Impact Factor: 3.94). 07/2007; 103(2):197-208. DOI: 10.1007/s10549-006-9366-x
Source: PubMed


Primary chemotherapy provides an ideal opportunity to correlate gene expression with response to treatment. We used paraffin-embedded core biopsies from a completed phase II trial to identify genes that correlate with response to primary chemotherapy.
Patients with newly diagnosed stage II or III breast cancer were treated with sequential doxorubicin 75 mg/M2 q2 wks x 3 and docetaxel 40 mg/M2 weekly x 6; treatment order was randomly assigned. Pretreatment core biopsy samples were interrogated for genes that might correlate with pathologic complete response (pCR). In addition to the individual genes, the correlation of the Oncotype DX Recurrence Score with pCR was examined.
Of 70 patients enrolled in the parent trial, core biopsies samples with sufficient RNA for gene analyses were available from 45 patients; 9 (20%) had inflammatory breast cancer (IBC). Six (14%) patients achieved a pCR. Twenty-two of the 274 candidate genes assessed correlated with pCR (p < 0.05). Genes correlating with pCR could be grouped into three large clusters: angiogenesis-related genes, proliferation related genes, and invasion-related genes. Expression of estrogen receptor (ER)-related genes and Recurrence Score did not correlate with pCR. In an exploratory analysis we compared gene expression in IBC to non-inflammatory breast cancer; twenty-four (9%) of the genes were differentially expressed (p < 0.05), 5 were upregulated and 19 were downregulated in IBC.
Gene expression analysis on core biopsy samples is feasible and identifies candidate genes that correlate with pCR to primary chemotherapy. Gene expression in IBC differs significantly from noninflammatory breast cancer.

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    • "In 45 patients with stage II or stage III breast cancer with only 14% reaching a complete pathologic response, a 22-gene signature consisting of angiogenesis-, proliferation- and invasion-related genes was found to be predictive for complete pathological remission in patients neoadjuvantly treated with 3 cycles of doxorubicin and six cycles of docetaxel [76]. Indeed the study showed the feasibility of RT-PCR based methods to explore candidate genes that correlate with pathologic complete response, but the 22-gene signature was not validated in a second independent study. "
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    ABSTRACT: Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.
    09/2010; 1(3):421-37. DOI:10.1007/s13167-010-0044-z
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    ABSTRACT: Gene expression profiling has been increasingly used to determine new cancer markers. This technology holds major promises for improving the management of patients with breast cancer in which traditional clinicopathologic parameters do not account for all the heterogeneity of this disease and its distinct prognostic groups. Gene expression profiling has resulted in new classification of breast cancer and new assays are being developed and commercialized as prognostic and predictive tests. However, the use of these tests in a clinical setting presents many issues. The accuracy of this new technology is often overestimated and its limitations should be addressed. Although early results are promising, further validation and well designed clinical trials are required before incorporating these tests in routine clinical practice.
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