Integration of ATAC-seq and RNA-seq identifies typing and prognosis evaluation target molecules of triple negative breast cancer
Molecular subtyping plays a vital role in the treatment of breast cancer, however, current clinical outcomes remain unsatisfactory despite having multiple molecular subtypes available, particularly for triple-negative breast cancers. Henceforth, our research primarily focuses on traditional molecular subtyping by utilizing transcriptome sequencing and ATAC-seq sequencing techniques to classify both tumor tissues and adjacent tissues from patients with breasts cancers into distinct groups. Through this process, we aim to identify key gene expressions involved in the development of breasts cancers as well as epigenetic characteristics influenced by alterations in chromatin accessibility patterns. Subsequently, employing conventional methods used for classifying breasts cancers into different molecular types enables us to further investigate significant variations observed specifically within triple-negative breasts cancers regarding their gene expression profiles and chromatin accessibility patterns. Lastly, utilizing data from TCGA database pertaining exclusively to cases involving triple-negative breasts cancers allows us to conduct regression analyses concerning our aforementioned findings while simultaneously selecting relevant molecular models closely associated with this particular subtype of breasts malignancy. Additionally evaluating how these differentially expressed genes influence prognosis through prognostic modeling analysis tailored towards predicting outcomes solely within cases involving individuals diagnosed with triple negative-breast malignancies will enable us ultimately construct an innovative model incorporating both gene expressions along with chromatin accessibility patterns as distinguishing features providing more substantial guidance towards improving clinical treatments targeting individuals afflicted by such conditions. Overall design: We performed transposase-accessible chromatin sequencing (ATAC-seq) analysis of breast cancer samples, including ER-positive(+) human epidermal growth factor receptor 2 (HER2)-negative(-) and triple-negative tumors. We also reanalysed ATAC-seq data of tumors in the Cancer Genome Atlas (TCGA) BC cohort to validate our observations. Breast cancer tissue and adjacent paracancerous tissue