Dataset Information

Impact of exploratory biomarkers on the treatment effect of bevacizumab in metastatic breast cancer.

ABSTRACT:

Purpose

The addition of bevacizumab to cytotoxic chemotherapy has demonstrated a progression-free survival (PFS) benefit in the first-line and second-line treatment of advanced or metastatic breast cancer (MBC). However, the addition of bevacizumab to capecitabine in heavily pretreated MBC patients did not show a PFS benefit (AVF2119g phase III trial). The aim of this study was to evaluate the expression of novel putative biomarkers as predictors of benefit from bevacizumab in retrospective subset analyses of the AVF2119g trial.

Experimental design

In the AVF2119g trial, 462 patients with MBC were randomly assigned to receive capecitabine or capecitabine plus bevacizumab. Primary tumor tissue and outcome data were available for 223 patients. Biomarker expression was assessed by in situ hybridization (VEGF-A, VEGF-B, thrombospondin-2 and Flt4) or immunohistochemistry (VEGF-C, PDGF-C, neuropilin-1, delta-like ligand (Dll) 4, Bv8, p53 and thymidine phosphorylase) on formalin-fixed, paraffin-embedded tissue. PFS was associated with these variables in retrospective subset analyses.

Results

Patients with low scores for Dll4, VEGF-C, and neuropilin-1 showed trends toward improvement in PFS associated with the addition of bevacizumab to capecitabine (P values = 0.01, 0.05, and 0.07, respectively). These observations were not statistically significant following correction for multiple hypothesis testing.

Conclusion

These retrospective subset analyses suggest that expression of Dll4, VEGF-C, and neuropilin-1 may predict benefit from bevacizumab. Such observations are not conclusive but warrant additional testing.

SUBMITTER: Jubb AM

PROVIDER: S-EPMC3023787 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Publications

Impact of exploratory biomarkers on the treatment effect of bevacizumab in metastatic breast cancer.

Jubb Adrian M AM Miller Kathy D KD Rugo Hope S HS Harris Adrian L AL Chen Dafeng D Reimann James D JD Cobleigh Melody A MA Schmidt Maike M Langmuir Virginia K VK Hillan Kenneth J KJ Chen Daniel S DS Koeppen Hartmut H

Clinical cancer research : an official journal of the American Association for Cancer Research 20110111 2

<h4>Purpose</h4>The addition of bevacizumab to cytotoxic chemotherapy has demonstrated a progression-free survival (PFS) benefit in the first-line and second-line treatment of advanced or metastatic breast cancer (MBC). However, the addition of bevacizumab to capecitabine in heavily pretreated MBC patients did not show a PFS benefit (AVF2119g phase III trial). The aim of this study was to evaluate the expression of novel putative biomarkers as predictors of benefit from bevacizumab in retrospect ...[more]

PMID: 21224365

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Project description:Background: Biomarkers predicting response to bevacizumab in breast cancer are still missing. Since epigenetic modifications can contribute to an aberrant regulation of angiogenesis and treatment resistance, we investigated the influence of DNA methylation patterns on bevacizumab efficacy. Methods: Genome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip was performed in archival FFPE specimens of 36 patients with HER2-negative metastatic breast cancer treated with chemotherapy in combination with bevacizumab as first-line therapy (learning set). Based on objective response and progression-free survival (PFS) and considering ER expression, patients were divided in responders (R) and non-responders (NR). Significantly differentially methylated gene loci (CpGs) with a strong change in methylation levels (Δβ>0.15 or Δβ<-0.15) between R and NR were identified and further investigated in 80 bevacizumab-treated breast cancer patients (optimization set) and in 15 patients treated with chemotherapy alone (control set) using targeted deep amplicon bisulfite sequencing. Methylated gene loci were considered predictive if there was a significant association with outcome (PFS) in the optimization set but not in the control set using Spearman rank correlation, Cox regression, and logrank test. Results: Differentially methylated loci in 48 genes were identified, allowing a good separation between R and NR (odds ratio (OR) 101, p<0.0001). Methylation of at least one cytosine in 26 gene-regions was significantly associated with progression-free survival (PFS) in the optimization set, but not in the control set. Using information from the optimization set, the panel was reduced to a 9-gene signature, which could divide patients from the learning set into 2 clusters, thereby predicting response with an OR of 40 (p<0.001) and an AUC of 0.91 (LOOCV). A further restricted 3-gene methylation model showed a significant association of predicted responders with longer PFS in the learning and optimization set even in multivariate analysis with an excellent and good separation of R and NR with AUC=0.94 and AUC=0.86, respectively. Conclusion: Both a 9-gene and 3-gene methylation signature can discriminate between R and NR to a bevacizumab-based therapy in MBC and could help identify patients deriving greater benefit from bevacizumab.

Dataset Information

Impact of exploratory biomarkers on the treatment effect of bevacizumab in metastatic breast cancer.

Purpose

Experimental design

Results

Conclusion

Publications

Impact of exploratory biomarkers on the treatment effect of bevacizumab in metastatic breast cancer.

Similar Datasets

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