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Current and upcoming therapeutic options are also impacted by the absence of a rational classification system for TNBC. Thanks to the use of bioinformatics, high-throughput sequencing, and microarray technology, the amount of genomic, epigenomic, transcriptomic, and proteomic information has increased exponentially, allowing for the development of several novel approaches to stratifying TNBC over the past few years. As a result, new TNBC subtypes are being studied, with the potential to improve treatment for this difficult condition. However, the widespread implementation of these promising developments has been hampered by the diverse nature of the molecular data, the poor integration of the various methods, and the absence of cost-effective methods for systematic classification. On the other hand, the application of artificial intelligence to translational oncology is expected to shed light on specific TNBC subtypes [1]. This survey gives a far-reaching rundown of the accessible order techniques. It incorporates assessing the cross-over between the sub-atomic, immunohistochemical, and clinical qualities between these methodologies and a point of view about the rising utilizations of man-made consciousness to distinguish conclusive and clinically important TNBC subtypes.

Presentation

Bosom disease (BC) is the most common malignant growth in ladies, with a consistently expanding number of cases analyzed consistently. Generally, BC is ordered and treated in light of the situation with estrogen receptor (emergency room), progesterone receptor (PR), and human epidermal development factor receptor 2 (HER2) articulation. These markers have made it possible to create therapies that are specific and effective. Triple-negative breast cancer (TNBC), or tumors that do not express ER, PR, or HER2, are not treated with targeted therapies, so chemotherapy is the only systemic treatment option Compared to the other BC subtypes, TNBC has a higher proliferation rate, a higher incidence of metastases to the brain, liver, and lungs, and more frequently affects younger patients [2].

Since its first detection in December 2019, the coronavirus disease 2019 (COVID-19) pandemic has affected most nations, resulting in approximately 250 million illnesses and 5 million deaths. Coronavirus is an extreme irresistible respiratory sickness brought about by SARSCoV- 2, another exceptionally infectious infection from the family coronaviridae, similar to SARS-CoV and MERS-CoV-2. SARS-CoV-2 infection results in severe acute inflammation and a high mortality rate. Albeit dire immunization programs in numerous nations have decreased the quantity of new cases and the seriousness of side effects in such cases, the drawn-out effect of SARS-CoV-2 disease on human wellbeing actually should be explored.

Cancer patients with COVID-19 infection appear to be more vulnerable than other COVID-19 patients. Compared to non-cancer patients, cancer patients have a higher mortality rate, a higher risk of infection, and symptoms that are more severe. Cancer patients had worse outcomes than the general population and had a high incidental diagnosis of SAR2-CoV-2 infection, according to previous studies. Their immune systems are compromised because of chemotherapy and radiotherapy, which makes it easier for them to become infected with SARS-CoV-2 and makes it harder for them to take advantage of the COVID-19 vaccination's protective effects. When patients do get infected, chronic inflammation caused by cancer also contributes to more severe symptoms.

Inflammation is a common feature of pathophysiology in cancer and COVID-19. SARS-CoV-2 infection and cancer both exhibit cytokine storm, a systemic hyperactive immune condition characterized by massive cytokine release. Interleukin-6 (IL6) and tumor necrosis factor (TNF) are important proinflammatory cytokines that are involved in the cytokine storm and play major roles in the acute immune response during severe COVID-19 infection. Proliferation, mesenchymal transformation, metastasis, stemness, and immune evasion are all stoked by IL6 in cancer cells. In addition, the cytokine storm caused by the SARS-CoV-2 infection and systemic inflammation can cause oxidative stress, DNA damage, and genetic instability in healthy cells, which can lead to the growth of benign tumors and malignant transformation when oncoviruses are present. Furthermore, Francescangeli et al. suggested that COVID-19's prolonged inflammation, leukocyte hyperactivation, T-cell impairment, and thrombocytosis may create a favorable microenvironment for the reawakening of dormant cancer cells, particularly stem-like cells that survive chemotherapy or radiotherapy and have the potential to cause recurrence or metastasis. In addition, Wei et al. also found a significant rise in serum levels of cancer biomarkers in critical COVID-19 cases, indicating a link between tumorigenesis and SARS-CoV-2 infection [3]. As a result, research into how COVID-19 affects cancer patients' preventative care is urgently required. One of the most common types of cancer among cancer patients with SARS-CoV-2 infection is breast cancer to tumor progression, breast cancer patients infected with SARS-CoV-2 may develop new metastases, progress, or die. By examining the effects of SARS-CoV-2 proteins on the phenotypes of various types of human breast cancer cells (BCC), we aimed to investigate the connection between SARS-CoV-2 infection and the progression of breast cancer in this study.

The Legacy of Gene Expression Pattern-Based BC Subtyping In 2011, Lehmann et al. based on gene expression profiling and ontology analyses, identified six TNBC subtypes (the TNBCtype-6 classification). Basal-like (BL) 1 and BL2, which were enriched in cell cycle genes and growth factor signaling, respectively, were two of the novel subtypes. Immunomodulatory (IM), with a high expression of pathways related to the immune system; mesenchymal (M), with genes for mesenchymal differentiation and proliferation being displayed; mesenchymal stemlike (MSL), with low proliferation and mesenchymal characteristics; and the luminal androgen receptor (LAR), which is known for triggering hormone-related pathways. Importantly, compared to the other subtypes, LAR and M subtypes had significantly lower relapsefree survival rates [4-6].

Most recent study Using the fuzzy clustering method, three distinct TNBC subtypes (C1, C2, and C3) were also identified by employing transcriptomic profiling. TNBC tumors with a molecular apocrine phenotype had a better prognosis in the C1 cluster, while basal-like characteristics were more prevalent in the C2 and C3 clusters. C2 showed organic forcefulness and an invulnerable suppressive aggregate, while C3 illustrated the versatile safe reaction and resistant designated spot upregulation. From DNA to Metabolites for TNBC Clustering New stratification methods for TNBC patients have emerged as a result of the development of next-generation sequencing, computing systems, and an exponential increase in the number of available data sources over the years. Along these lines, new information types have been utilized to order TNBC into novel subtypes. TNBC tumors and the circulating DNA of TNBC patients both contain a variety of single nucleotide variant (SNV) patterns.

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