Tumor Characterization in Breast Cancer Identifies Immune-Relevant Gene Signatures Associated With Prognosis

Here we describe the comprehensive gene expression profiles of each cell type composing normal breast tissue and in situ and invasive breast carcinomas using serial analysis of gene expression. Based on these data, we determined that extensive gene expression changes occur in all cell types during cancer progression and that a significant fraction of altered genes encode secreted proteins and receptors. Despite the dramatic gene expression changes in all cell types, genetic alterations were detected only in cancer epithelial cells. The CXCL14 and CXCL12 chemokines overexpressed in tumor myoepithelial cells and myofibroblasts, respectively, bind to receptors on epithelial cells and enhance their proliferation, migration, and invasion. Thus, chemokines may play a role in breast tumorigenesis by acting as paracrine factors.

Gene prognostic meta-analyses should benefit from breast tumour genomic data obtained during the last decade. The aim was to develop a user-friendly, web-based application, based on DNA microarrays results, called "breast cancer Gene-Expression Miner" (bc-GenExMiner) to improve gene prognostic analysis performance by using the same bioinformatics process. bc-GenExMiner was developed as a web-based tool including a MySQL relational database. Survival analyses are performed with R statistical software and packages. Molecular subtyping was performed by means of three single sample predictors (SSPs) and three subtype clustering models (SCMs). Twenty-one public data sets have been included. Among the 3,414 recovered breast cancer patients, 1,209 experienced a pejorative event. Molecular subtyping by means of three SSPs and three SCMs was performed for 3,063 patients. Furthermore, three robust lists of stable subtyped patients were built to maximize reliability of molecular assignment. Gene prognostic analyses are done by means of univariate Cox proportional hazards model and may be conducted on cohorts split by nodal (N), oestrogen receptor (ER), or molecular subtype status. To evaluate independent prognostic impact of genes relative to Nottingham Prognostic Index and Adjuvant! Online, adjusted Cox proportional hazards models are performed. bc-GenExMiner allows researchers without specific computation skills to easily and quickly evaluate the in vivo prognostic role of genes in breast cancer by means of Cox proportional hazards model on large pooled cohorts, which may be split according to different prognostic parameters: N, ER, and molecular subtype. Prognostic analyses by molecular subtype may also be performed in three robust molecular subtype classifications.

Emerging evidence indicates that angiogenesis and immunosuppression frequently occur simultaneously in response to diverse stimuli. Here, we describe a fundamental biological programme that involves the activation of both angiogenesis and immunosuppressive responses, often through the same cell types or soluble factors. We suggest that the initiation of these responses is part of a physiological and homeostatic tissue repair programme, which can be co-opted in pathological states, notably by tumours. This view can help to devise new cancer therapies and may have implications for aseptic tissue injury, pathogen-mediated tissue destruction, chronic inflammation and even reproduction.