Over the last 50 years, most cancer research has focused on determining how tumor cells vary from normal cells in gene expression (Zhang et al., 1997). These distinctions might have a significant impact on several human illnesses, including Hepatitis (Asselah et al., 2009), Alzheimer (Theuns and Van Broeckhoven, 2000), Diabetes (Das and Rao, 2007), MS (Tajouri, Fernandez and Griffiths, 2007), and some different human cancer types, including Liver cancer (Chen et al., 2002), Colorectal cancer (Kheirelseid et al., 2013), Retinoblastoma (Kapatai et al., 2013), Lung cancer (Petty et al., 2004), Head and Neck cancer (Nagai, 1999), and Breast cancer (Bao and Davidson, 2008; Reis-Filho and Pusztai, 2011; Arpino et al., 2013; Guler, 2017). An extensive study on gene expression patterns in many pathogenic illnesses, such as breast cancer, can assist in speeding up the treatment of these diseases and forecast their emergence.
Breast cancer is the most common malignancy among women, with 1.8 million new cases identified in 2013, accounting for 12 percent of all malignancies. Although breast cancer incidence is lower among Iranian women, epidemiological research shows that the number of newly diagnosed breast cancer patients has lately grown (Assad Samani et al., 2019). According to Cancer Statistics 2018, BC is the most frequent female malignancy, and the primary cause of cancer mortality in women, with over 2.1 million females diagnosed each year and over 62,000 fatalities. Developing countries account for over 60% of BC deaths (Bray et al., 2018). While early detection and recent advances in anti-cancer therapy have improved crucial outcomes for BC patients, the recurrence rate of the disease remains high (Kim et al., 2018; N. Li et al., 2019; Siegel, Miller, and Jemal, 2020). As a result, measuring the expression of genes linked to breast cancer, discovering diagnostic and prognostic biomarkers, and comprehending gene expression patterns in various clinical and pathological circumstances linked to breast cancer might provide valuable information about the illness and aid in its prevention.
Scientists have created several techniques to monitor gene expression. Two powerful technologies for assessing gene expression are real-time PCR and microarray. Gene expression profiling and genome-wide gene expression analysis utilizing DNA microarray might provide data on the expression level and relative expression of genes and RNAs in different groups, such as "tumor" and "control," or "treated" and "untreated" (Dufva, 2009).
Among some various genes involved in Breast cancer, ID1 was selected by integrated microarray analysis. The roles of ID1 in regulating cell differentiation during neurogenesis, lymphoid, angiogenesis, cell growth, and cell cycle progression have been studied. There are four inhibitors of DNA-binding (ID1, 2, 3, 4) proteins which are members of basic helix-loop-helix (bHLH), as they form transcriptionally inactive Id-bHLH protein complexes (Maw, Fujimoto and Tamaya, 2008). Based on bioinformatics analyses, it is hypothesized that abnormal changes in ID1 expression in the Breast could effectively develop breast cancer status.
LncRNAs are RNA molecules with a length of more than 200 nucleotides that can be found in the nucleus or cytoplasm. Only a few can encode a tiny number of polypeptides, while the remainder does not code for proteins. LncRNAs influence a wide range of biological events at the pre-transcriptional and transcriptional phases, including tumor invasion, metastasis, and apoptosis. As a result, lncRNA abnormalities in BC patients' peripheral blood may aid in the development and progression of the disease, allowing for early detection and therapy (Mercer, Dinger, and Mattick, 2009; Fang and Fullwood, 2016; Bin et al., 2018). In this study, evaluation of the ID1 and two relevant lncRNAs was the main aim. Also, investigation about the correlation of this three RNA and the possible roles of breast cancer.