Alteration in DNA methylation is one of the major significant molecular changes in carcinogenesis. Adenomatous polyposis coli (APC) and retinoic acid receptors-2 (RARb2) methylated promoters were discovered in 93.4% and 95.6% of blood samples from females having breast cancer, respectively, but not in healthy people (Swellam et al., 2015). All methylation variations surpassed the conventional markers CEA and CA 15–3 in detecting early breast cancer, low-grade tumors, and Triple Negative Breast Cancer (NBC). Utilizing a human methylation DNA study BeadChip. Yang et al. revealed that hypomethylation of S100 calcium-binding protein P (S100P) and hyalurono glucosaminidase 2 (HYAL2) in the peripheral blood is linked with breast cancer (Yang et al., 2015; Yang et al., 2017). Both genes with lower methylation have been proven to be possible biomarkers circulating in blood, for the diagnosis of breast cancer, specifically in adolescent girls in the initial stages (Bleyer and Welch, 2012; Fleming and Powers, 2012).

The latest study has found that aberrant DNA methylation is significantly linked to breast cancer, and suggesting that DNA methylation testing can aid in predicting the prognosis of breast cancer patients. MAST1, PRDM14, and ZNF177 irregular DNA methylation variants were found and verified as prospective breast cancer molecular indicators by X Mao et al. X Mao et al. also showed that the DNA methylation range of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177. In essence, these findings point to the development of novel epigenetic prognosis systems that might assist in the detection and prediction of breast cancer therapy (Uehiro et al., 2016). An exceptionally sensitive mobile cell-free DNA (cfDNA) system with epigenetic biomarkers and droplet digital methylation-specific PCR (ddMSP) has been created for the early diagnosis of breast cancer. Ras-specific guanine nucleotide-releasing factor 1 (RASGRF1), carboxypeptidase X (CPXM1), Hox-A10 (HOXA10), and Dachshund homolog 1 (DACH1) were the four methylation markers employed in the efficient screening method (Uehiro et al., 2016). This epigenetic-marker-based technique was able to reliably discriminate women with breast cancer from healthy controls, hinting that it might be utilized for breast cancer screening and therapy (Uehiro et al., 2016).

Circulating protein has been considered as the second choice as a biological marker for the recognition and analysis of Breast cancer (BC). Blood proteomics and mass spectrometry have analyzed the systemic and comprehensive visualization of the blood proteomics pathologically and physiologically, resulting in the finding of numerous protein biomarkers in blood that can be used as effective diagnostic biomarkers in breast cancer detection. A panel of trefoil factor (TFF) 1, TFF2, and TFF3 have been stated as promising biomarkers for BC screening as they can express specific proteins differentially in the serum of BC patients that cannot be produced by healthy cells (Ishibashi et al., 2017). The two well-known groups such as Cks of intermediate filaments and glycoprotein (MUC) family can produce several classical breast cancer biomarkers. The CA 15–3 assay, for example, is currently used for tracking purposes in treatment (Duffy, 2006), while CKs have been proposed as early-stage BC markers, but their efficacy is masked due to poor sensitivity (Levenson, 2007). The serum epithelial membrane antigen/CK1 concentration ratio is recommended as possible diagnostic marker, especially for initial stage breast cancer diagnosis. The diagnostic capability of this new combination was assessed better than CA 15–3 (Attallah et al., 2014).

Besides, some other proteinaceous biological markers with promising diagnostic capability have been revealed by ELISA. Among these proteins, a single diagnostic marker model of pleiotrophin (PTN) (Ma et al., 2017a), and double diagnostic marker models such as integration of microRNA (miRNA) miR-127-3p with human epididymis secretory protein 4 (HE4) (Lu et al., 2017), human anterior gradient (AGR) 2 with AGR3 (Garczyk et al., 2015) and vascular endothelial growth factor (VEGF) with CA 15–3 (Ławicki et al., 2016). Serum apolipoprotein C-I (apoC-I) has demonstrated promise results in prognosis and diagnosis of triple-negative Breast cancer (TNBC), as it could distinguish TNBC from non-TNBC cases by greater ApoC-I mRNA and protein expression in the former when compared to both non-TNBC affected individuals and controls (Song et al., 2016).

Autoantibodies are reported as another approach used as diagnostic biomarkers with the potential of multiple targets, short time-frames, and minimalist hardware (Soler et al., 2016). The associated antigens of these antibodies are synthesized by the body’s cells; in healthy cells, it is expressed at a modest level, while it is overexpressed in malignant cells. The immune system determines this expression, using toll-like receptors (TLRs) for the innate response, thus reverting tumor growth. MUC1, an integral membrane protein, is overexpressed in 90% of adenocarcinomas and has been linked to tumor aggressiveness (Zaenker et al., 2016). Antibodies that target oncogenic and tumor suppressor proteins are considered as the significant diagnostic biomarkers for the efficient detection of breast cancer. The presence of autoantibodies before the medical diagnosis of the disorder in paraneoplastic syndrome and systemic autoimmune diseases has raised the prospect that the medical diagnosis of BC could also be carried out through detection of auto-immunoglobulins (Fernández Madrid, 2005). As a result, extensive research has revealed the detection of tumor-associated antigens by autoantibodies that were detected in the patient blood sample. The integration of modern proteomics, advanced genomics, high-throughput technology, and traditional immunological approaches has significantly aided advancement in this area (Fernández Madrid, 2005).

miRNAs are single-stranded, non-coding, small (20–25 nucleotide) RNAs that suppress the post-transcriptional expression of specifically selected genes via mRNA breakdown or mRNA expression. The detection and persistence of miRNAs in the bloodstream and their role in diagnostic and therapeutic approaches have been studied thoroughly (Schwarzenbach et al., 2011). Since miRNAs are soluble and observable in cancer cells (Shen et al., 2013), blood, plasma, and patients’ saliva, they can be used as biological markers for non-invasive early diagnosis, detection, and treatment of breast cancer (Mitchell et al., 2008; Schwarzenbach et al., 2014). miRNAs are released into the bloodstream by apoptotic cells (Schwarzenbach et al., 2011). miRNAs can travel through the bloodstream in two forms: cell-free (Ago2-related) or embedded in membrane vesicles, microvesicles, or exosomes (Simpson et al., 2009). miRNAs profiling studies can classify dysregulated miRNAs and categorize patients of breast cancer for therapies, highlighting their potential to be used as a predictive and therapeutic biomarker (McGuire et al., 2015). Furthermore, like oncogenes (oncomiRNAs) and tumor suppressors, unregulated miRNA is responsible for tumor growth, development, cell death, invasion, and cell proliferation. Recently, numerous suspected candidates, for example, miR-221, miR-21, and miR-145, have appeared in the blood serum or plasma of BC-affected individuals. Blood-based identities containing miR-221 and/or miR-21 have been shown to have higher diagnostic susceptibility than CEA and CA 15–3 for all stages of cancer, distinguishing BC subjects from patients with benign tumors and healthy people and doing better in distinguishing the TNBC subtype from healthy subjects (Gao et al., 2013; Motawi et al., 2016; Thakur et al., 2016). Exosomal miR-21 expression has also been shown to be elevated in Breast cancer patients’ plasma-derived exosomes. The exosomal miR-21 and miR-1246 form modest diagnostic (Hannafon et al., 2016).

In terms of diagnosis, Iorio et al. (2005) discovered a 13-miRNA hallmark that could differentiate affected Breast cancer from healthy breast tissues with 100% precision. Blenkiron et al. (2007) discovered 133 miRNAs with abnormal expression patterns in breast tumor tissues irrespective of normal breast tissues. Despite the discovery of miRNAs with abnormal expression in BC tissues, there are still inconsistencies between the variously identified miRNA signatures. Roth et al. introduced single circulating miRNAs as diagnostic and prognostic instruments after discovering miR-155 in the serum of Breast cancer affected individuals but not in stable controls, and Heneghan et al. identified elevated miR-195 activity in the bloodstream of only affected subjects with BC (Heneghan et al., 2010; Roth et al., 2010). Some miRNAs, such as miR-21and miR-29a or 4-miRNA signature, have been found in the plasma of BC patients (miR-222, miR-16, miR-25, and miR-324-3p) (Wu et al., 2011; Hu et al., 2012).

A vast number of other miRNAs have been reported that overexpress in Breast cancer a few examples are miR-29a, miR-146a, miR-373, miR589, miR-221/222 cluster, miR-9, miR10b, miR-96, miR-181, miR-375, and miR-520c. These miRNAs are linked with treatment, diagnosis, and prognosis of Breast cancer (Polytarchou et al., 2012; Khoshnaw et al., 2013; Sandhu et al., 2014).

Circular RNAs (circRNAs) are recently identified non-coding RNAs that are classified as tiny endogenous RNAs with a broad distribution, various forms, and several regulatory applications (Ashwal-Fluss et al., 2014). Sanger et al. (1976) were the first to find cricRNA in the viroids. Up till now, a large number of circRNAs have been found in various cell lines and organisms (Bleyer and Welch, 2012; Pace and Keating, 2014; Oeffinger et al., 2015), namely protozoa, fungi, worms, plants, fish, mice, insects, and humans (Wang et al., 2014; Westholm et al., 2014). CircRNAs are present in large numbers, about 1/8th of the human genome’s transcriptome can generate observable circRNAs, and their expression levels are much more than tenfold higher than that of the comparable linear mRNAs (Salzman et al., 2012; Jeck et al., 2013). Furthermore, as a result of their covalent closed-loop configuration and absence of free terminal ends, circRNAs are much more stable unlike linear RNAs, conferring susceptibility to deterioration by endonuclease R (RNase R) (Chen and Yang, 2015). CircRNAs can also be used to distinguish and recognize various tumor types due to their ability to express particular cell types, tissues, and developmental stages, as well as the fact that different subtypes of circRNAs can be generated (Salzman et al., 2013; Smid et al., 2019). Given the above, we conclude that circRNAs have growing research potential. Various biochemical roles of circRNAs have been discovered as science has progressed. CircRNAs may serve as “sponges” for microRNAs (miRNAs), influencing the role of miRNA target genes (Hansen et al., 2013). Furthermore, circRNAs can be attached to various RNA binding proteins (RBPs), influencing the role of the parental genes (Zeng et al., 2017; Kristensen et al., 2019). Surprisingly, provided evidence suggests that circRNAs may express proteins/peptides playing a role in tumor development and progression (Legnini et al., 2017; Zheng et al., 2019). CircRNAs’ special properties and biological roles show the role of circRNAs in tumor growth, replication, metastasis, invasion, and drug tolerance, implying that circRNAs can be used as biological markers and tumor therapeutic goals (Liu et al., 2018a; Kun-Peng et al., 2018). Circular RNAs can avoid exonuclease-induced degradation and are more soluble in blood or plasma than linear RNAs because of their closed continuous loop structure (Alhasan et al., 2016). It has been shown that ncRNAs, such as miRNAs and non-coding RNAs, can serve as reliable biological markers for hepatocellular carcinoma (Li et al., 2015). CircRNAs are regaining attention among researchers as high-throughput sequencing and bioinformatics technology improves. Due to their stability and tissue specificity, circRNAs have been established as suitable biological markers for the diagnosis of gastric cancer (Simon, 2015), hepatocellular carcinoma, and other cancers (Qin et al., 2016). Evidence have revealed that circRNAs can cause tumorigenesis, providing a new approach for identifying diagnostic biomarkers (Kulcheski et al., 2016; Zhu et al., 2017).

Using the circRNA microarray method, Lu et al. determined the circRNA expression pattern in breast cancer and normal tissues and discovered that hsa circ 103110, hsa circ 104689, and hsa circ 104821 levels were upregulated in breast cancer cells with area under the curve (AUC) value of 0.63 (0.52–0.74), 0.61 (0.50–0.73), and 0.60 (0.49–0.71) respectively, while hsa circ 006054, hsa circ 100219, and hsa circ 406697 were downregulated with the area under the curve (AUC) value of 0.71 (0.61–0.81), 0.78 (0.69–0.88) and 0.64 (0.52–0.75) respectively. As a result, mixing hsa circ 006054, hsa circ 100219, and hsa circ 406697 yielded successful diagnostic results as mentioned in table 1 (Lü et al., 2017). Similarly, Yin et al. found that in the plasma of breast cancer patients, 19 circRNAs were upregulated and 22 were downregulated as opposed to stable controls (Maselli et al., 2019). Further investigation found that the plasma hsa circ 0001785 had a higher diagnostic accuracy than CEA and CA15-3. Furthermore, hsa circ 0001785 plasma levels were correlated with histological grade (p = 0.013), TNM stage (p = 0.008), and remote metastasis (p = 0.016), indicating a possible biomarker for breast cancer diagnosis. The expression levels of hsa circ 0001785 were shown to be lower in post-operative BC patients’ plasma samples relative to pre-operative patients (Sarkar and Diermeier, 2021).

Exosomes are extracellular membrane-bound vesicles that are nano-sized (30–100 nm) and actively released by cancer cells and neighboring cells present in the tumor microenvironment (TME) (Taylor and Gercel-Taylor, 2013; Gajos-Michniewicz et al., 2014). They are surrounded by a lipid bilayer composed up of phosphoglycerides, ceramides, sphingolipids, and cholesterols (Vlassov et al., 2012) and comprise a diverse array of molecules such as DNA, sugars, proteins, peptides, lipids, mRNAs, miRNAs, as well as other types of ncRNAs (Moreno-Gonzalo et al., 2014). Exosomes like miRNAs, are present in a variety of human bodily fluids, including blood, sweat, urine, and breastfeeding (Vlassov et al., 2012; Raposo and Stoorvogel, 2013).

Exosomes can facilitate tumor development, angiogenesis, immunosuppression, and metastasis by promoting intermodulation between tumor cells and healthy or cancer-affected stromal cells (Alderton, 2012; Moon et al., 2016a). The surface proteins present on circulating extracellular vesicle (EVs), developmental endothelial locus-1 protein (Del-1) (Moon et al., 2016a), and fibronectin (Moon et al., 2016b), are promising materials for cancer detection. Fibronectin, a matrix protein present extracellularly, binds to several integrins and activates a variety of signaling proteins, including FAK, Src, and Akt (Moon et al., 2016b). Fibronectin levels rose dramatically (p < 0.0001) throughout all phases of breast cancer and went back to normal after the tumors were removed. The clinical diagnostic efficacy for fibronectin recognition outside the cellular vesicles was better than that in plasma (Moon et al., 2016b). This underscores the significance of extracellular matrix proteins in breast cancer. The high amount of Del-1 in patients’ circulating exosomes (p 0.0001) resulted in excellent diagnostic success in distinguishing patients with early-stage breast cancer from the control system (Moon et al., 2016a).

There are several miRNAs whose expressions were downregulated in drug resistance BC. In BC-affected tissues and cells resistant to taxol, the increased expression of nuclear receptor co-activator 3 (NCOA3) results in decreased expression of miR-17 and miR-20b. This shows that these three NCOA3, miR-17, and miR-20b may function as active biological markers and therapeutic targets in breast cancer resistance to taxol (Ao et al., 2016).

Another study reported the overexpression of miR-18a in TNBC cells patients who had received neoadjuvant paclitaxel, thus inhibiting dicer expression and increasing paclitaxel resistance in TNBC cells (Sha et al., 2016). There are four miRNAs; miR-90b, 130a, 200b, and 452 that can regulate drug-related cellular pathways, thus leading to chemoresistance as shown in Figure 1 (Jayaraj et al., 2019).

In adriamycin-resistant cell lines and tissues sensitive to Adriamycin, a high-level expression of hsa_circ_00006528 was discovered by Gao et al. (Ma et al., 2017b) by using circRNA microarray expression profiles. The hsa_circ_00006528-miR-7–5p-Raf1 axis has a regulatory effect on breast cancer resistance to adriamycin. This highlights the possibility of the use of hsa_circ_00006528 in controlling the factor of drug resistance. This concludes that for breast cancer treatment, circRNAs come up with novel and reliable therapeutic strategies (Ma et al., 2017b).

has-circ_00006428, a circular RNA, can be used as a promising therapeutic candidate due to its role in reducing drug resistance. This statement can be supported by its overexpression in Adriamycin-resistant cells while expression in Adriamycin-sensitive cells. Besides, the regulatory role of hsa_circ_00006528-miR-7-5p-Rafl axis in Adriamycin resistant breast cancer was revealed (Ma et al., 2017b).

New progress in RNA-based therapies plus aberrant expression of circRNAs in breast cancer makes them more potential therapeutic sites (Lei et al., 2019). One solution may be to create synthetic circRNAs with several binding sites for certain oncogenic proteins or miRNAs that could be inserted exogenously to restore the natural regulatory network in the cell and reduce cancer development (Tay et al., 2015; Liu et al., 2018c). On the other hand, endogenous circRNAs can be useful for the treatment of cancer (Dragomir and Calin, 2018). Any of the tumor-suppressor circRNAs discussed above are prime candidates for further development as therapeutic instruments. CircFOXO3, circCCNB1, circKDM4C, circFBXW, and circTADA2A were all shown to be downregulated in patient samples, related to a bad diagnosis and treatment, and biologically linked to cancer etiology (Meganck et al., 2018). CircRNA overexpression constructs transferred by adeno-associated virus (AAV) vectors, which do not incorporate into the genome and are presently used in clinical studies, are recently used as a therapeutic solution. On another side, tumorigenic circRNAs, such as the TNBC-specific circAGFG1 and circANKS1B, may be used as new therapeutic targets for TNBC, which currently have few treatment choices and a weak prognosis (Bianchini et al., 2016). To target overexpressed circRNA expression therapeutically, effective approaches have been designed, including degradation mediated by siRNA, shRNA, or altered antisense oligonucleotides (ASOs) complementary to the back-splice junction (Cortés-López and Miura, 2016; Santer et al., 2019). More steady knockout methods, such as CRISPR/Cas genome editing, have also been evaluated. The CRISPR/Cas13 system is a new addition that achieves circRNA silencing by attacking Cas13 to the circRNA’s back-splice junction via a specific guide RNA that can differentiatedifferentiate between linear transcripts and circRNAs (Li et al., 2021). Cas13d, a small version of Cas13 (Konermann et al., 2018), in particular, may be packaged into an AAV vector for transmission into primary cells and rodents (Konermann et al., 2018; Zhang, 2021). However, since the side effects of Cas13 expression are currently uncertain, the drawbacks of this system in a clinical sense are not known (Li et al., 2021).