Application of Single-Cell Omics in Breast Cancer

The dynamics and heterogeneity of breast cancer undergoing clonal evolution produce cells with varying degrees of drug resistance and metastatic potential. Breast cancer is well known for different clinical behaviors and patient outcomes, in spite of common histopathological features at diagnosis. Currently, single-cell analysis has made remarkable advances, overshadowing the problem of heterogeneity linked with huge populations. Rapid progression in sequencing methods now permits unbiased, high-output, and high-resolution interpretation of heterogeneity from individual cells within a population. Conventional treatment strategies for individual patients are directed by the presence and absence of expression pattern of the estrogen and progesterone receptors (ER and PR) and human epidermal growth factor receptor 2 (HER2). Though such approaches for clinical classification have usefulness in selection of targeted therapies and short-term patient responses, they are unable to predict long-term survival. In any phenotypic alterations, like breast cancer disease, the molecular signature has proven its significance, as we know that an individual cell's state is controlled at diverse levels, such as DNA, RNA, and protein, by a multifaceted interplay of intrinsic biomolecule pathways existing in the organism and extrinsic stimuli such as the ambient environment. Thus for comprehensive understanding, complete profiling of a single-cell requires synchronous investigations from different levels (multiomics) to circumvent incomplete information produced from single-cells. In this chapter, initially we present current updates on the various methods available to explore omics and then we focus on omics (i.e., genomics, transcriptomics, epigenomics, proteomics, and metabolomics) data available from various studies that can be used for better management of breast cancer patients.