Identification of Breast Cancer subtype specific MicroRNAs using Survival Analysis to find their role in transcriptomic regulation

The microRNA (miRNA) biomolecules have a significant role in the development of breast cancer, and their expression profile is different in each subtype of breast cancer. Thus, our goal is to use the Next Generation Sequencing provided high-throughput miRNA expression and clinical data in an integrated fashion to perform survival analysis in order to identify breast cancer subtype specific miRNAs, and analyze associated genes and transcription factors. We select top 100 miRNAs for each of the four subtypes, based on the value of hazard ratio and p-value, thereafter, identify 44 miRNAs that are related to all four subtypes, which we call as 4-star miRNAs. Moreover, 12, 14, 9 and 15 subtype specific, viz. 1-star miRNAs, are also identified. [Read More]

Genome-wide analysis of NGS data to compile cancer-specific panels of miRNA biomarkers

MicroRNAs are small non-coding RNAs that influence gene expression by binding to the 3' UTR of target mRNAs in order to repress protein synthesis. Soon after discovery, microRNA dysregulation has been associated to several pathologies. In particular, they have often been reported as differentially expressed in healthy and tumor samples. This fact suggested that microRNAs are likely to be good candidate biomarkers for cancer diagnosis and personalized medicine. With the advent of Next-Generation Sequencing (NGS), measuring the expression level of the whole miRNAome at once is now routine. Yet, the collaborative effort of sharing data opens to the possibility of population analyses. This context motivated us to perform an in-silico study to distill cancer-specific panels of microRNAs that can serve as biomarkers. [Read More]

Survival Analysis with the Integration of RNA-Seq and Clinical Data to Identify Breast Cancer Subtype specific Genes

Breast cancer is one of the most widespread forms of cancer that affects a significant portion of the female population today. Its early detection and subsequent treatment can be life saving. However, it is difficult clinically and computationally to detect breast cancer and its subtypes in their early stages. On the other hand, Next Generation Sequencing (NGS) techniques have significantly accelerated the process of mapping the human genomes by providing high-throughput expression data of RNA. In this work, we study such NGS based expression data of mRNAs with the clinical data in order to (a) rank the genes based on their importance in survival of breast cancer subtypes and (b) find the relation between the up/down regulation of genes and survival probability of a population. [Read More]

Identification of Epigenetic Biomarkers with the use of Gene Expression and DNA Methylation for Breast Cancer Subtypes

Breast cancer is one of the most deadly cancers. It has four subtypes: Luminal A (LA), Luminal B (LB), HER2-enriched (HER2-E) and Basal-like (BL). For the cause of breast cancer subtypes, there are different genetic and epigenetic factors involved in its progression and susceptibility. Thus, the identification of genetic and/or epigenetic biomarkers can be helpful to understand the biological mechanisms better and to improve the diagnostic processes of this disease and its subtypes. Hence, this fact motivated us to investigate the epigenetic factor, such as DNA Methylation, with the integration of gene expression in order to find epigenetic biomarkers for breast cancer subtypes. [Read More]