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Novel bio-marker discovery for stratification and prognosis of breast cancer patients

ABSTRACT: The study entails novel bio-marker discovery of Tumor Aggressive Grade signature (TAGs) genes and their role in recurrence free survival of breast cancer (BC) patients. Current BC dataset was used for co-expression analysis of TAGs genes and their role in BC progression. Additionally, recent findings have suggested an importance of structural organization of sense-antisense gene pairs (SAGPs) for transcription, post-transcriptional and post-translational events and their associations with cancer and disease. We studied SAGPs in which both gene partners are protein encoding genes (coding-coding SAGPs), their role in human BC development and demonstrated their potential for BC stratification and prognosis. Based on gene expression and correlation analyses we identified the robust set of breast cancer-relevant SAGPs (BCR-SAGPs). We isolated and characterized the sense-antisense gene signature (SAGS) and evaluated its prognostic potential in various gene expression datasets comprising 1161 BC patients. The methods used included the Cox proportional survival analysis, statistical analysis of clinicopathologic parameters and differential gene expression. The SAGS was effective in identification of BC patients with the most aggressive disease. Independently, we validated the SAGS using 58 RNA samples of breast cancer tumors purchased from OriGene Technologies (Rockville, MD).

ORGANISM(S): Homo sapiens

PROVIDER: GSE61304 | GEO | 2015/05/10

SECONDARY ACCESSION(S): PRJNA260713

REPOSITORIES: GEO

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Novel bio-marker discovery for stratification and prognosis of breast cancer patients

Project description:The study entails novel bio-marker discovery of Tumor Aggressive Grade signature (TAGs) genes and their role in recurrence free survival of breast cancer (BC) patients. Current BC dataset was used for co-expression analysis of TAGs genes and their role in BC progression. Additionally, recent findings have suggested an importance of structural organization of sense-antisense gene pairs (SAGPs) for transcription, post-transcriptional and post-translational events and their associations with cancer and disease. We studied SAGPs in which both gene partners are protein encoding genes (coding-coding SAGPs, ccSAGPs), their role in human BC development and demonstrated their potential for BC stratification and prognosis. Based on gene expression and correlation analyses we identified the robust set of breast cancer-relevant ccSAGPs (BCR-ccSAGPs). We isolated and characterized the sense-antisense gene classifier (SAGC) and evaluated its prognostic potential in various gene expression datasets comprising 1161 BC patients. The methods used included the Cox proportional survival analysis, statistical analysis of clinicopathologic parameters and differential gene expression.The SAGC was effective in identification of BC patients with the most aggressive disease. Independently, we validated the SAGC using 58 RNA samples of breast cancer tumors purchased from OriGene Technologies (Rockville, MD). Sixty two total RNA samples from breast tumors and normal breast epithelium have been purchased from OriGene Technologies in March, 2011. Four RNA samples were obtained from normal individuals. Among 58 breast tumors (58 patients) 56 were diagnosed as ductal breast adenocarcinoma, 1 - as lobular breast adenocarcinoma and 1 - as squamous cell carcinoma. Gene expression data for all the samples were quantified by using whole-genome RNA microarrays (HG-U133 plus 2.0, Affymetrix).

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López-Cortés2020 - Prediction of Breast Cancer (BC) proteins involved in cancer immunotherapy using molecular descriptors and Multi Layer Perceptron (MLP) neural network

Project description:This study introduces a predictive classifier for breast cancer-related proteins, utilising a combination of protein sequence descriptors and machine learning techniques. The best-performing classifier is a Multi Layer Perceptron (artificial neural network) with 300 features, achieving an average Area Under the Receiver Operating Characteristics (AUROC) score of 0.984 through 3-fold cross-validation. Notably, the model identified top-ranked cancer immunotherapy proteins associated with breast cancer that should be studied for further biomarker discovery and therapeutic targeting. Please note that in this model, the output '0' means BC non-related protein and '1' means BC related protein. The original GitHub repository can be accessed at https://github.com/muntisa/neural-networks-for-breast-cancer-proteins

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Functional analyses of miR-210 involvement in the aggressive phenotype of high grade breast tumors

Project description:As miR-210 expression is correlated to poor prognosis both in estrogen-positive and in estrogen-negative breast cancer (BC) patients, we aimed to investigate the biological processes regulated by miR-210 and which may elucidate its function in the aggressive phenotype of high grade breast cancer. We performed in silico functional analyses of the genes deregulated upon miR-210 overexpression in MCF7 BC cell line and upon miR-210 repression in MDA-MB-231 BC cell line using lentiviral transduction. Gene expression profiling analysis of these cells revealed the deregulation of genes involved in several biological pathways including cell adhesion, extracellular structure organization, epithelial cell proliferation, cell division, cell cycle and immune response.

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Project description:High throughput RNA sequencing has revealed pervasive transcription of human genome than previously anticipated. However, the extent of natural antisense transcripts (NATs) expression, their regulation of cognate sense genes, and the role of NATs in cancer remain poorly understood. Here, we use strand-specific paired-end RNA sequencing (ssRNASeq) data from 376 cancer patients covering 9 tissue types to comprehensively characterize the landscape of antisense expression. We found consistent antisense expression in at least 38% of annotated transcripts, which in general is positively correlated with sense gene expression. Investigations of sense/antisense pair expression across tissue types revealed lineage-specific, ubiquitous and cancer-specific antisense loci transcription. Comparisons between tumor and normal samples identified both concordant (same direction) and discordant (opposite direction) sense/antisense expression patterns. Finally, we provide oncoNAT, a catalog of cancer related genes with significant antisense transcription, which will enable future investigations of sense/antisense regulation in cancer. Using oncoNAT we identified several functional NATs, including NKX2-1-AS that regulates the NKX2-1 oncogene and cell proliferation in lung cancer cells. Overall, this study provides a comprehensive account of NATs and supports a role for NATs regulation of tumor suppressors and oncogenes in cancer biology.

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