Molecular analysis of a male breast cancer patient with prolonged stable disease under mTOR/PI3K inhibitors BEZ235/everolimus

Unfolding the role of the PI3K/AKT/MTOR pathway in male breast cancer: A pragmatic appraisal

Breast cancer in men is rare, but a relevant public health issue, yielding a 25% higher risk of mortality comparing to female counterparts. The representation of males in clinical trials has been scarce and treatment decisions are based mainly on extrapolations from data in females. In the setting of estrogen-dependent metastatic disease, the use of everolimus has been seldom reported, although the PI3K/AKT/mTOR pathway seems to be a critical oncogenic driver. This paper dissects hallmark biological features of ER+/HER2-advanced male breast cancer, setting a comprehensive basis to promote personalized care, focusing on the potential of targeting the PI3K/AKT/mTOR pathway.

Mechanisms of resistance to mTOR inhibitors

In several tumors the PI3K/AKT/mTOR pathway is frequently disrupted, an event that results in uncontrolled cell proliferation and tumor growth. Through the years, several compounds have been developed to inhibit the pathway at different steps: the mammalian target of rapamycin (mTOR) seemed to be the most qualified target. However, this kinase has such a key role in cell survival that mechanisms of resistance are rapidly developed. Nevertheless, clinical results obtained with mTOR inhibitors in breast cancer, renal cell carcinoma, neuroendocrine tumors and mantle cell lymphoma push oncologists to actively further develop these drugs, maybe by better selecting the population to which they are offered, through the research of predictive factors of responsiveness. In this review, we aim to describe mechanisms of resistance to mTOR inhibitors, from preclinical and clinical perspectives.

A Case-Matched Gender Comparison Transcriptomic Screen Identifies eIF4E and eIF5 as Potential Prognostic Markers in Male Breast Cancer

Purpose: Breast cancer affects both genders, but is understudied in men. Although still rare, male breast cancer (MBC) is being diagnosed more frequently. Treatments are wholly informed by clinical studies conducted in women, based on assumptions that underlying biology is similar.Experimental Design: A transcriptomic investigation of male and female breast cancer was performed, confirming transcriptomic data in silico Biomarkers were immunohistochemically assessed in 697 MBCs (n = 477, training; n = 220, validation set) and quantified in pre- and posttreatment samples from an MBC patient receiving everolimus and PI3K/mTOR inhibitor.Results: Gender-specific gene expression patterns were identified. eIF transcripts were upregulated in MBC. eIF4E and eIF5 were negatively prognostic for overall survival alone (log-rank P = 0.013; HR = 1.77, 1.12-2.8 and P = 0.035; HR = 1.68, 1.03-2.74, respectively), or when coexpressed (P = 0.01; HR = 2.66, 1.26-5.63), confirmed in the validation set. This remained upon multivariate Cox regression analysis [eIF4E P = 0.016; HR = 2.38 (1.18-4.8), eIF5 P = 0.022; HR = 2.55 (1.14-5.7); coexpression P = 0.001; HR = 7.04 (2.22-22.26)]. Marked reduction in eIF4E and eIF5 expression was seen post BEZ235/everolimus, with extended survival.Conclusions: Translational initiation pathway inhibition could be of clinical utility in MBC patients overexpressing eIF4E and eIF5. With mTOR inhibitors that target this pathway now in the clinic, these biomarkers may represent new targets for therapeutic intervention, although further independent validation is required. Clin Cancer Res; 23(10); 2575-83. ©2016 AACR.

PureCN: copy number calling and SNV classification using targeted short read sequencing

Background

Matched sequencing of both tumor and normal tissue is routinely used to classify variants of uncertain significance (VUS) into somatic vs. germline. However, assays used in molecular diagnostics focus on known somatic alterations in cancer genes and often only sequence tumors. Therefore, an algorithm that reliably classifies variants would be helpful for retrospective exploratory analyses. Contamination of tumor samples with normal cells results in differences in expected allelic fractions of germline and somatic variants, which can be exploited to accurately infer genotypes after adjusting for local copy number. However, existing algorithms for determining tumor purity, ploidy and copy number are not designed for unmatched short read sequencing data.

Results

We describe a methodology and corresponding open source software for estimating tumor purity, copy number, loss of heterozygosity (LOH), and contamination, and for classification of single nucleotide variants (SNVs) by somatic status and clonality. This R package, PureCN, is optimized for targeted short read sequencing data, integrates well with standard somatic variant detection pipelines, and has support for matched and unmatched tumor samples. Accuracy is demonstrated on simulated data and on real whole exome sequencing data.

Conclusions

Our algorithm provides accurate estimates of tumor purity and ploidy, even if matched normal samples are not available. This in turn allows accurate classification of SNVs. The software is provided as open source (Artistic License 2.0) R/Bioconductor package PureCN (http://bioconductor.org/packages/PureCN/).

Electronic supplementary material

The online version of this article (doi:10.1186/s13029-016-0060-z) contains supplementary material, which is available to authorized users.