Ductal carcinoma in situ (DCIS) is a noninvasive precursor lesion to invasive breast carcinoma. We still have no understanding on why only some DCIS lesions evolve to invasive cancer whereas others appear not to do so during the life span of the patient. Here, we performed full exome (tumor vs. matching normal), transcriptome, and methylome analysis of 30 pure high-grade DCIS (HG-DCIS) and 10 normal breast epithelial samples. Sixty-two percent of HG-DCIS cases displayed mutations affecting cancer driver genes or potential drivers. Mutations were observed affecting PIK3CA (21% of cases), TP53 (17%), GATA3 (7%), MLL3 (7%) and single cases of mutations affecting CDH1, MAP2K4, TBX3, NF1, ATM, and ARID1A. Significantly, 83% of lesions displayed numerous large chromosomal copy number alterations, suggesting they might precede selection of cancer driver mutations. Integrated pathway-based modeling analysis of RNA-seq data allowed us to identify two DCIS subgroups (DCIS-C1 and DCIS-C2) based on their tumor-intrinsic subtypes, proliferative, immune scores, and in the activity of specific signaling pathways. The more aggressive DCIS-C1 (highly proliferative, basal-like, or ERBB2+) displayed signatures characteristic of activated Treg cells (CD4+/CD25+/FOXP3+) and CTLA4+/CD86+ complexes indicative of a tumor-associated immunosuppressive phenotype. Strikingly, all lesions showed evidence of TP53 pathway inactivation. Similarly, ncRNA and methylation profiles reproduce changes observed postinvasion. Among the most significant findings, we observed upregulation of lncRNA HOTAIR in DCIS-C1 lesions and hypermethylation of HOXA5 and SOX genes. We conclude that most HG-DCIS lesions, in spite of representing a preinvasive stage of tumor progression, displayed molecular profiles indistinguishable from invasive breast cancer.

In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules significantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identified meta-signature improves breast cancer patient stratification independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.

Biosimilars of granulocyte colony-stimulating factor (G-CSF) have been routinely introduced into clinical practice. However, not functional genomics characterization has been performed yet in comparison with the innovator G-CSF. This study aimed to evaluate the transcriptomic changes in an in vitro model of umbilical cord blood cells (UBC) exposed to G-CSF for the identification of their modulated pathways. Umbilical cord blood cells–derived mononuclear cells (MNCs) were treated with biosimilar and innovator G-CSF for further gene expression profiling analysis using a microarray-based platform. Comparative analysis of biosimilar and innovator G-CSF gene expression signatures allowed us to identify the most commonly modulated pathways by both drugs. In brief, we observed predominantly upmodulation of transcripts related to PI3K-Akt, NF-kappaB, and tumor necrosis factor (TNF) signaling pathways as well as transcripts related to negative regulation of apoptotic process among others. In addition, hematopoietic colony-forming cell assays corroborate the G-CSF phenotypic effects over UBC-derived MNCs. In conclusion, our study suggests that G-CSF impacts UBC-derived cells through the modulation of several signaling pathways associated with cell survival, migration, and proliferation. The concordance observed between biosimilar and innovator G-CSF emphasizes their similarity in regards to their specificity and biological responses.

BioPlat is a platform-independent software implemented in Java and supported on GNU/Linux and MS Windows, which is freely available for download at http://www.cancergenomics.net.

<p>Supplementary Figure S3: TP53 pathway activity in invasive breast carcinomas from the TCGA-BRCA dataset.</p>