Mapping Bromodomains in breast cancer and association with clinical outcome.

A specific family of proteins that participate in epigenetic regulation is the bromodomain (BRD) family of proteins. In this work, we aimed to explore the expression of the BRD family at a transcriptomic level in breast cancer, and its association with patient survival. mRNA level data from normal breast and tumor tissues were extracted from public datasets. Gene set enrichment analysis (GSEA) was performed to identify relevant biological functions. The KM Plotter Online tool was used to evaluate the relationship between the presence of different genes and patient clinical outcome. mRNA level data from HER2+ breast cancer patients sensible and resistant to trastuzumab were also evaluated. The BRD family was an enriched function. In HER2 positive tumors the combined analyses of BRD2, BAZ1A, TRIM33 and ZMYND8 showed a detrimental relapse free survival (RFS). Similarly, the combined analysis of BRD2, BAZ1A, PHIP, TRIM33, KMT2A, ASH1L, PBRM1, correlated with an extremely poor overall survival (OS). The prognosis was confirmed using an independent dataset from TCGA. Finally, no relation between expression of BRD genes and response to trastuzumab was observed in the HER2 population. Upregulation of some BRD genes is associated with detrimental outcome in HER2 positive tumors, regardless trastuzumab treatment.

A Transcriptomic Immunologic Signature Predicts Favorable Outcome in Neoadjuvant Chemotherapy Treated Triple Negative Breast Tumors.

Limited therapeutic options exist for the treatment of patients with triple negative breast cancer (TNBC). Neoadjuvant chemotherapy is currently the standard of care treatment in the early stages of the disease, although reliable biomarkers of response have been scarcely described. In our study we explored whether immunologic signatures associated with inflamed tumors or hot tumors could predict the outcome to neoadjuvant chemotherapy. Publicly available transcriptomic data of more than 2,000 patients were evaluated. ROC plots were generated to assess the response to therapy. Cox proportional hazards regression was computed. Kaplan-Meier plots were drawn to visualize the survival differences. Higher expression of IDO1, CXCL9, CXCL10, HLA-DRA, HLA-E, STAT1, and GZMB were associated with a higher proportion without relapse in the first 5 y after chemotherapy in TNBC. The expression of these genes was associated with a high presence of CD8 T cells in responder patients using the EPIC bioinformatic tool. The strongest effect was observed for STAT1 (p = 1.8e-05 and AUC 0.69, p = 2.7e-06). The best gene-set signature to predict favorable RFS was the combination of IDO1, LAG3, STAT1, and GZMB (HR = 0.28, CI = 0.17-0.46, p = 9.8 E-08, FDR = 1%). However, no influence on pathological complete response (pCR) was observed. Similarly, no benefit was identified in any other tumor subtype: HER2 or estrogen receptor positive. In conclusion, we describe a set of immunologic genes that predict the outcome to neoadjuvant chemotherapy in TNBC, but not pCR, suggesting that this non-time to event endpoint is not a good surrogate marker to detect the long term outcome for immune activated tumors.

Functional transcriptomic annotation and protein-protein interaction analysis identify EZH2 and UBE2C as key upregulated proteins in ovarian cancer.

Although early stage ovarian cancer is in most cases a curable disease, some patients relapse even with appropriate adjuvant treatment. Therefore, the identification of patient and tumor characteristics to better stratify risk and guide rational drug development is desirable. Using transcriptomic functional annotation followed by protein-protein interacting (PPI) network analyses, we identified functions that were upregulated and associated with detrimental outcome in patients with early stage ovarian cancer. Some of the identified functions included cell cycle, cell division, signal transduction/protein modification, cellular response to extracellular stimuli or transcription regulation, among others. Genes within these functions included AURKA, AURKB, CDK1, BIRC5, or CHEK1 among others. Of note, the histone-lysine N-methyltransferase (EZH2) and the ubiquitin-conjugating enzyme E2C (UBE2C) genes were found to be upregulated and amplified in 10% and 6% of tumors, respectively. Of note, EZH2 and UBE2C were identified as principal interacting proteins of druggable networks. In conclusion, we describe a set of genes overexpressed in ovarian cancer with potential for therapeutic intervention including EZH2 and UBE2C.

DNA-damage related genes and clinical outcome in hormone receptor positive breast cancer.

BACKGROUND: Control of DNA damage is frequently deregulated in solid tumors. Upregulation of genes within this process can be indicative of a more aggressive phenotype and linked with worse outcome. In the present article we identify DNA damage related genes associated with worse outcome in breast cancer. RESULTS: 2286 genes were differentially expressed between normal breast tissue and basal-like tumors, and 62 included in the DNA metabolic process function. Expression of RAD51, GINS1, TRIP13 and MCM2 were associated with detrimental relapse free survival (RFS) and overall survival (OS) in luminal tumors. The combined analyses of TRIP13+RAD51+MCM2 showed the worse association for RFS (HR 2.25 (1.51-3.35) log rank p= 4.1e-05) and TRIP13+RAD51 for OS (HR 5.13 (0.6-44.17) log rank p=0.098) in ER+/HER2- tumors. TRIP13 is amplified in 3.1% of breast cancers. METHODS: Transcriptomic analyses using public datasets evaluating expression values between normal breast tissue and TNBC identified upregulated genes. Genes included in the DNA metabolic process were selected and confirmed using data contained at oncomine (www.oncomine.org). Evaluation of the selected genes with RFS and OS was performed using the KM Plotter Online Tool (http://www.kmplot.com). Evaluation of molecular alterations was performed using cBioportal (www.cbioportal.org). CONCLUSIONS: Expression of DNA metabolic related genes RAD51, GINS1, TRIP13 and MCM2 are associated with poor outcome. Combinations of some of these genes are linked to poor RFS or OS in luminal A, B and ER+HER2- tumors. Evaluation of its predictive capacity in prospective studies is required.

Mitotic read-out genes confer poor outcome in luminal A breast cancer tumors.

Luminal breast tumors have been classified into A and B subgroups, with the luminal A being associated with a more favorable clinical outcome. Unfortunately, luminal A tumors do not have a universally good prognosis. We used transcriptomic analyses using public datasets to evaluate the differential expression between normal breast tissue and breast cancer, focusing on upregulated genes included in cell cycle function. Association of selected genes with relapse free survival (RFS) and overall survival (OS) was performed using the KM Plotter Online Tool (http://www.kmplot.com). Seventy-seven genes were differentially expressed between normal and malignant breast tissue. Only five genes were associated with poor RFS and OS. The mitosis-related genes GTSE1, CDCA3, FAM83D and SMC4 were associated with poor outcome specifically in Luminal A tumors. The combination of FAM83D and CDCA3 for RFS and GTSE1 alone for OS showed the better prediction for clinical outcome. CDCA3 was amplified in 3.4% of the tumors, and FAM83D and SMC4 in 2.3% and 2.2%, respectively. In conclusion, we describe a set of genes that predict detrimental outcome in Luminal A tumors. These genes may have utility for stratification in trials of antimitotic agents or cytotoxic chemotherapy, or as candidates for direct target inhibition.