SINGLE CELL TRANSCRIPTOMIC ANALYSES OF HUMAN MAMMARY GLAND AND BREAST TUMORS

Breast cancer is the most frequently diagnosed cause of death from cancer in women world-wide, and the second cause of death from cancer in women in developed countries. Besides a significant family history of breast or ovarian cancer, the risk of breast cancer increases with age. This correlation with age could be linked to the continuous and progressive endocrine proliferative stimulus that the mammary epithelium undergoes over the years, together with the progressive damage to DNA and accumulation of epigenetic changes that modifies the balance in the expression of oncogenes and tumor suppressor genes. The purpose of our study is to collect normal samples of human mammary gland that will be used as healthy controls for pathological tissue specimens from breast primary tumors and metastases. Through a transcriptional characterization of cells, we would try to get a more comprehensive evaluation of mammary cell diversity. To do this, all the samples will be analyzed through two different sequencing strategies: single cell RNA sequencing of both epithelial, stromal and microenvironmental cells of the breast tissue, and RNA sequencing of a bulk population of only epithelial breast cells. The samples were obtained from five consenting healthy patients (between 47 and 63 years old), during reductive mammoplasties, and they were processed through mechanical and enzymatic tissue dissociation to reach single cell suspensions. Three of the human mammary gland samples were destined to single-cell RNA analyses, following Chromium Next GEM protocol. Cells were loaded into a microfluidic chip that enables to encapsulate each cell into reaction vesicles where reactions occur. After reverse transcription inside each reaction droplet ends, all the cDNA were tagged with various oligos specific for each different cell (10x Barcodes), and for each distinct transcript within the cell (UMIs). Thanks to this barcoding, during data analysis, after sequencing (by Illumina sequencer), each transcript can be mapped back to the origin cell, and all transcripts from a single cell can be quantified. On the other hand, three samples (also one that was processed through scRNA-sequencing) were assigned to RNA analyses in bulk of epithelial cell population, that were previous selected through cell sorting (FACSAria flow cytometer), to obtain a higher resolution of the sequencing data, than that coming from scRNA-seq. RNA sequencing and data analyses of our healthy samples is still in progress. Single-cell RNA sequencing technique allows to detect and sequence the higher expressed genes of the processed cells at a single-cell level. Sequencing of bulk populations will offer a deeper analysis of the gene expression of our samples, with a higher number of detected genes (not only the more expressed) but limited to sorted epithelial cells. The resulting output will be analyzed and used as a healthy control for pathological samples from breast primary tumor and brain metastasis. At the moment, this study is investigating the gene expression of normal samples that will be used as the baseline from which pathological tissues can be explored. Certainly, further studies will be continued to make useful what has been collected up until now, with the purpose of trying to understand the molecular mechanisms and the various pathways that guide breast primary tumors development and spreading within the human body.