Archives in Cancer Research

  • ISSN: 2254-6081
  • Journal h-index: 14
  • Journal CiteScore: 3.77
  • Journal Impact Factor: 4.09
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days
Awards Nomination 20+ Million Readerbase
Indexed In
  • China National Knowledge Infrastructure (CNKI)
  • CiteFactor
  • OCLC- WorldCat
  • Publons
  • Geneva Foundation for Medical Education and Research
  • Euro Pub
  • Google Scholar
  • J-Gate
  • Secret Search Engine Labs
  • International Committee of Medical Journal Editors (ICMJE)
  • Zenodo
Share This Page

Mini Review - (2023) Volume 11, Issue 4

Breast Cancer Subtypes and SARS-Cov-2 M Protein Encourage the Malignant Transformation of Breast Cancer Cells

Elijah Edward*
University of Texas Southwestern Medical Center, United States
*Correspondence: Elijah Edward, University of Texas Southwestern Medical Center, United States, Email:

Received: 01-Jul-2023, Manuscript No. ipacr-23-13717; Editor assigned: 03-Jul-2023, Pre QC No. P-13717; Reviewed: 17-Jul-2023, QC No. Q-13717; Revised: 22-Jul-2023, Manuscript No. R-13717; Published: 28-Jul-2023


Breast cancer is the most typical malignancy among women. Bosom illness subgroups are categorised by histologic features, such as receptor status and shape. Clinical decisions can be made using information on the declaration of the oestrogen receptor (emergency room), progesterone receptor, human epidermal development factor receptor 2 (HER2), and the multiplication record Ki67 (in early phase illness). Molecular testing are now accessible to further divide the illness into subgroups, stratify risk, or calculate the advantages of therapies. Triple-negative breast cancer (TNBC) is a very diverse disorder with poor clinical results due to the overexpression of the human epidermal growth factor receptor 2 (HER2), the lack of expression of the oestrogen and progesterone receptors, and the lack of targeted therapies. Improved stratification methods that take into account inherent and clinically significant variations between TNBC tumours would therefore help to focus treatment plans and improve clinical outcomes.


The lack of a logical TNBC categorization system has an influence on both existing and future therapy choices. The quantity of genomic, epigenomic, transcriptomic, and proteomic information has grown tremendously as a result of the use of bioinformatics, high-throughput sequencing, and microarray technologies. Over the last few years, various innovative ways of stratifying TNBC have been developed as a result. New TNBC subtypes are thus being researched in an effort to better treat this challenging illness. However, the heterogeneous nature of the molecular data, the inadequate integration of the many approaches, and the lack of affordable methods for systematic categorization have prevented the broad use of these encouraging findings. On the other hand, it is anticipated that the use of artificial intelligence in translational oncology will clarify some TNBC subtypes. This review provides a thorough overview of the available order strategies. In order to define definitive and clinically significant TNBC subtypes, it also takes into account evaluating the crossover between the sub-atomic, immunohistochemical, and clinical features across these techniques [1-5].

The most prevalent malignant development in women is called bosom disease (BC), and the number of cases being studied on a regular basis is growing. Typically, oestrogen receptor (emergency room), progesterone receptor (PR), and human epidermal development factor receptor 2 (HER2) articulation are taken into consideration while ordering and treating BC. The development of targeted and efficient medicines has been made feasible by these markers. Chemotherapy is the only systemic treatment for triple-negative breast cancer (TNBC), which refers to tumours that do not express ER, PR, or HER2. TNBC is more common in younger individuals than the other BC subtypes, has a faster rate of proliferation, and more commonly metastasizes to the brain, liver, and lungs. The coronavirus disease 2019 (COVID-19) pandemic has hit the majority of countries since its initial identification in December 2019, causing about 250 million illnesses and 5 million fatalities. Coronavirus is a highly contagious infection from the same coronaviridae family as SARSCoV and MERS-CoV-2 that causes severe, uncontrollable respiratory illness. A significant death rate and severe acute inflammation are the outcomes of SARS-CoV-2 infection. Although severe immunisation campaigns in many countries have reduced the number of new cases and the severity of their side effects, the long-term impact of the SARS-CoV-2 illness on human wellness really needs to be investigated.

The vulnerability of COVID-19 patients with cancer appears to be greater than that of other COVID-19 patients. Cancer patients experience more severe symptoms, a greater death rate, and a higher risk of infection than noncancer patients. According to earlier investigations, cancer patients fared worse than the general populace and were more frequently incidentally diagnosed with SAR2-CoV-2 infection. Their immune systems are weakened as a result of chemotherapy and radiation, which makes it simpler for them to get SARS-CoV-2 and more difficult for them to benefit from the protective benefits of the COVID-19 immunisation. Chronic cancer-related inflammation makes symptoms worse when patients do get an infection. In COVID-19 and cancer, inflammation is a common aspect of the pathogenesis. Cytokine storm, a systemic hyperactive immunological state characterised by excessive cytokine production, is a feature of both cancer and SARSCoV- 2 infection. During a severe COVID-19 infection, the proinflammatory cytokines interleukin-6 (IL-6) and tumour necrosis factor (TNF) are crucial to the cytokine storm and the initial immunological response. In cancer cells, IL6 promotes proliferation, mesenchymal transition, metastasis, stemness, and immune evasion. In addition, the SARS-CoV-2 infection's cytokine storm and systemic inflammation can harm healthy cells through oxidative stress, DNA damage, and genetic instability, which can promote the development of benign tumours and malignant transformation in the presence of oncoviruses. Furthermore, COVID-19's protracted inflammation, leukocyte hyper activation, T-cell impairment, and thrombocytosis may produce a favourable microenvironment for the reawakening of dormant cancer cells, particularly stemlike cells that survive chemotherapy or radiotherapy and have the potential to cause recurrence or metastasis. This is according to Francescangeli et al. additionally; Wei et al. discovered a relationship between carcinogenesis and SARS-CoV-2 infection when they discovered a substantial increase in the blood levels of cancer biomarkers in critical COVID-19 patients. Therefore, there is an urgent need for study into how COVID-19 influences the preventative management of cancer patients [6-10].


Breast cancer is one of the most prevalent kinds of cancer among cancer patients who have SARS-CoV-2 infection. Due to tumour growth, SARS-CoV-2-infected breast cancer patients may develop new metastases, advance, or pass away. In this work, we wanted to evaluate the relationship between SARS-CoV-2 infection and the development of breast cancer by investigating the effects of SARS-CoV-2 proteins on the phenotypes of different kinds of human breast cancer cells (BCC). Gene Expression Pattern-Based BC Subtyping's Legacy Using gene expression profiling and ontology studies, Lehmann et al. (2011) discovered six TNBC subtypes (the TNBCtype-6 categorization). Two of the unique categories were basal-like (BL) 1 and BL 2, which were enriched in cell cycle genes and growth factor signalling, respectively. Mesenchymal stem-like (MSL), with low proliferation and mesenchymal characteristics, immunomodulatory (IM), with a high expression of immune system-related pathways, mesenchymal differentiation and proliferation genes, and the luminal androgen receptor (LAR), which is known to activate hormone-related pathways. Importantly, the relapse-free survival rates for the LAR and M subtypes were considerably lower than those of the other subtypes. Latest research Transcriptomic profiling was used to use the fuzzy clustering approach to identify three unique TNBC subtypes (C1, C2, and C3). While basal-like traits were more common in the C2 and C3 clusters, TNBC tumours with a molecular apocrine phenotype had a better prognosis in the C1 cluster. While C3 demonstrated the adaptable safe reaction and upregulation of the resistant specified location, C2 demonstrated organic forcefulness and an impervious suppressive aggregation. Metabolites and DNA for TNBC Clustering With the advancement of next-generation sequencing, computational systems, and an exponential rise in the amount of available data sources over time, new stratification techniques for TNBC patients have been developed. In keeping with this, TNBC has been arranged into distinct subtypes using new information types. Single nucleotide variation (SNV) patterns can be found in both TNBC tumours and the circulating DNA of TNBC patients.


  1. Kachnic LA, Pugh SL, Tai P, et al. RTOG 0518: Randomized Phase III Trial to Evaluate Zoledronic Acid for Prevention of Osteoporosis and Associated Fractures in Prostate Cancer Patients. Prostate Cancer Prostatic Dis. 2013; 16(2): 1-10.
  2. Indexed at, Google Scholar, Crossref

  3. Hage WD, Aboulafia AJ, Aboulafia DM. Incidence, location, and diagnostic evaluation of metastatic bone disease. Orthop Clin North Am. 2000; 31(7): 515-528.
  4. Indexed at, Google Scholar, Crossref

  5. Bauer HC. Controversies in the surgical management of skeletal metastases. J Bone Joint Surg Br. 2005; 87(7): 608-617.
  6. Indexed at, Google Scholar, Crossref

  7. Coleman RE, Lipton A, Roodman GD, et al. Metastasis and bone loss: advancing treatment and prevention. Cancer Treat Rev. 2010; 36(9): 615-620.
  8. Indexed at, Google Scholar, Crossref

  9. Ruggieri P, Mavrogenis AF, Casadei R, et al. Protocol of surgical treatment of long bone pathological fractures. Injury. 2010; 41(6): 1161-1167.
  10. Indexed at, Google Scholar, Crossref

  11. Forsberg JA, Sjoberg D, Chen QR, et al. Treating metastatic disease: Which survival model is best suited for the clinic? Clin Orthop Relat Res. 2013; 471(6): 843-850.
  12. Indexed at, Google Scholar, Crossref

  13. Selvaggi G, Scagliotti GV. Management of bone metastases in cancer: a review. Critical reviews in oncol hematol. 2005; 56(8): 365-378.
  14. Indexed at, Google Scholar, Crossref

  15. Kumar S, Kashyap P. Antiproliferative activity and nitric oxide production of amrthanolic extract of Fraxicus micrantha on michigan cancer foundation-7 mammalian breast cancinoma cell line. J Intercult Ethnopharmacol. 2015; 4(8): 109-113.
  16. Indexed at, Google Scholar, Crossref

  17. Oboma YI, Susan BE, Elesha SO, et al. Breast cancer biomarkers at Niger delta University hospital: Comparisons with national and International trends and clinical significance. J Patphy. 2017; 903(7): 1-6.
  18. Indexed at, Google Scholar, Crossref

  19. Adler RA, Gill RS. Clinical utility of denosumab for treatment of bone loss in men and women. Clin Interv Aging. 2011; 6(6): 119-124.
  20. Indexed at, Google Scholar, Crossref