Correlation of HER2, p95HER2 and HER3 Expression and Treatment Outcome of Lapatinib plus Capecitabine in her2-Positive Metastatic Breast Cancer

Background

Lapatinib plus capecitabine is an effective treatment option for trastuzumab-refractory HER2-positive metastatic breast cancer. We have investigated the correlation between quantitative measures of HER2, p95HER2, and HER3 and treatment outcomes using lapatinib and capecitabine.

Methods

Total HER2 (H2T), p95HER2 (p95), and total HER3 (H3T) expression were quantified in formalin-fixed paraffin-embedded samples using the VeraTag assays. Patients received lapatinib and capecitabine treatment following trastuzumab failure according to the Lapatinib Expanded Access Program. The association between the protein expression levels and clinical outcomes was analyzed.

Results

A total of 52 patients were evaluable. H2T level was significantly higher in responders (median 93.49 in partial response, 47.66 in stable disease, and 17.27 in progressive disease; p = 0.020). Longer time-to-progression (TTP) was observed in patients with high H2T [p = 0.018, median 5.2 months in high (>14.95) vs. 1.8 in low (<14.95)] and high H3T [p = 0.017, median 5.0 months in high (>0.605) vs. 2.2 in low (<0.605)]. Patients having both high H2T and high H3T had significantly longer TTP [adjusted hazard ratio (HR) 0.38 (95% CI 0.20–0.73), p = 0.004] and overall survival [adjusted HR 0.46 (95% CI 0.24–0.89), p = 0.020]. No significant association between p95 and response or survival was observed.

Conclusions

These data suggest a correlation between high HER2 and high HER3 expression and treatment outcome, while no significant difference was observed between clinical outcome and p95 expression level in this cohort of HER2-positive, trastuzumab-refractory metastatic breast cancer patients treated with lapatinib and capecitabine.     

SubcloneSeeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization

Many tumors are composed of genetically divergent cell subpopulations. We report SubcloneSeeker, a package capable of exhaustive identification of subclone structures and evolutionary histories with bulk somatic variant allele frequency measurements from tumor biopsies. We present a statistical framework to elucidate whether specific sets of mutations are present within the same subclones, and the order in which they occur. We demonstrate how subclone reconstruction provides crucial information about tumorigenesis and relapse mechanisms; guides functional study by variant prioritization, and has the potential as a rational basis for informed therapeutic strategies for the patient. SubcloneSeeker is available at: https://github.com/yiq/SubcloneSeeker.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0443-x) contains supplementary material, which is available to authorized users.     

HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics

Background  

Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata.