Identification and strategies for triple-negative breast cancer subtypes
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Feb 28, 2023
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Abstract
Triple-Negative Breast Cancer (TNBC) is a subtype of Breast Cancer (BC) with high mortality, early recurrence, more frequent, poor prognosis, and comparative data have shown that women with the TNBC phenotype have a 5-year overall 19 % survival lower and 18% lower disease-free survival than non-TNBC counterparts. The purpose of this study is to find out some of the identification and strategic management of Triple Negative Breast Cancer (TNBC). This research method used descriptive qualitative through the Systematic Literature Review (SLR) approach. The identifications obtained seven TNBC subtypes categorized and labeled differently such as Basal-Like 1 (BL1), Basal-Like 2 (BL2), Immunomodulatory (IM), Mesenchymal (M), Mesenchymal Stem–Like (MSL), Luminal Androgen Receptor (LAR), and Unstable (UNS). The strategy used the Development of a Breast Cancer Prediction Model with PPI Data and Support Vector Machines, Robust Identification of Target Genes and Outliers in TNBC data, and Sensitivity of Cell Lines to Heat Shock Protein 90 Inhibitor (Hsp90i). Based on the several strategies that have been described, there are various kinds of tests to determine TNBC according to the needs of each test. However, there is still no optimal solution that is suitable for all conditions.
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How to Cite
Suryadi, R., Supriyo, B. and Mawardy, R. (2023) “Identification and strategies for triple-negative breast cancer subtypes”, Science Midwifery, 10(6), pp. 4775-4779. doi: 10.35335/midwifery.v10i6.1086.
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Ramdhani, A., Ramdhani, M. A., & Amin, A. S. (2014). Writing a Literature Review Research Paper : A step-by-step approach Writing a Literature Review Research Paper : A step - by - step approach. December 2016.
Segaert, P., Lopes, M. B., Casimiro, S., Vinga, S., & Rousseeuw, P. J. (2019). Robust identification of target genes and outliers in triple-negative breast cancer data. https://doi.org/10.1177/0962280218794722
Shee, K., Wells, J. D., Ung, M., Hampsch, R. A., Traphagen, N. A., Yang, W., Liu, S., Zeldenrust, M. A., Wang, L., Kalari, K. R., Boughey, J. C., Demidenko, E., Kettenbach, A. N., Cheng, C., Goetz, M. P., & Miller, T. W. (2020). A transcriptionally-definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to HSP90 inhibition. 26(1), 159–170. https://doi.org/10.1158/1078-0432.CCR-18-2213.A
Shield, K. D., Soerjomataram, I., & Building, L. (2016). Alcohol Use and Breast Cancer : A Critical Review. 40(6), 1166–1181. https://doi.org/10.1111/acer.13071
Shiovitz, S., & Korde, L. A. (2015). Genetics of breast cancer: a topic in evolution. Annals of Oncology, 26(7), 1291–1299. https://doi.org/10.1093/annonc/mdv022
Veruscka Leso * , Maria Luigia Ercolano, D. L. C. and I. I. (2019). Occupational Chemical Exposure and Breast Cancer Risk According to Hormone Receptor Status : A Systematic Review.
Almansour, N. M. (2022). Triple-Negative Breast Cancer : A Brief Review About Epidemiology, Risk Factors, Signaling Pathways, Treatment and Role of Artificial Intelligence. 9(January), 1–15. https://doi.org/10.3389/fmolb.2022.836417
Brian D Lehmann, J. A. P. (2014). Identification and use of biomarkers in treatment strategies for triple negative breast cancer subtypes. 232(2), 142–150. https://doi.org/10.1002/path.4280.Identification
Checka, Cristina M, Jennifer E. Chun, Freya R. Schnabel, Jiyon Lee, H. T. (n.d.). The Relationship of Mammographic Density and Age: Implications for Breast Cancer Screening.
Criscitiello, C., Azim, H. A., Schouten, P. C., Linn, S. C., & Sotiriou, C. (2012). research article Understanding the biology of triple-negative breast cancer research article. Triple-Negative Breast Cancer in Focus: From Biology to Novel Therapeutics, 23(Supplement 6), vi13–vi18. https://doi.org/10.1093/annonc/mds188
Dent, R., Trudeau, M., Pritchard, K. I., Hanna, W. M., Kahn, H. K., Sawka, C. A., Lickley, L. A., Rawlinson, E., Sun, P., & Narod, S. A. (2007). riple-Negative Breast Cancer : Clinical Features and Patterns of Recurrence. 13(15), 4429–4434. https://doi.org/10.1158/1078-0432.CCR-06-3045
Finetti, P., Cervera, N., Esterni, B., Hermitte, F., Viens, P., & Birnbaum, D. (2009). SHORT REPORT How basal are triple-negative breast cancers ? Franc. 240(February 2008), 236–240. https://doi.org/10.1002/ijc.23518
Herschkowitz, J. I., Simin, K., Weigman, V. J., Mikaelian, I., Usary, J., Hu, Z., Rasmussen, K. E., Jones, L. P., Assefnia, S., Chandrasekharan, S., Backlund, M. G., Yin, Y., Khramtsov, A. I., Bastein, R., Quackenbush, J., Glazer, R. I., Brown, P. H., Green, J. E., Kopelovich, L., … Perou, C. M. (2007). Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. 8(5), 1–17. https://doi.org/10.1186/gb-2007-8-5-r76
Hormones, E., Cancer, B., & Group, C. (n.d.). Sex hormones and risk of breast cancer in premenopausal women : a collaborative reanalysis of individual participant. Lancet Oncology, 14(10), 1009–1019. https://doi.org/10.1016/S1470-2045(13)70301-2
Id, D. A. H., Id, E. R. P., Id, M. R., & Nibbe, A. (2019). Temporal trends in breast cancer survival by race and ethnicity : A population-based cohort study. 1–14.
Lehmann, B. D., Bauer, J. A., Chen, X., Sanders, M. E., Chakravarthy, A. B., Shyr, Y., & Pietenpol, J. A. (n.d.). Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. https://doi.org/10.1172/JCI45014DS1
Li, M., Guo, Y., Feng, Y., & Zhang, N. (2019). Identification of Triple-Negative Breast Cancer Genes and a Novel High-Risk Breast Cancer Prediction Model Development Based on PPI Data and Support Vector Machines. 10(March), 1–12. https://doi.org/10.3389/fgene.2019.00180
Livasy, C. A., Karaca, G., Nanda, R., Tretiakova, M. S., Olopade, O. I., Moore, D. T., & Perou, C. M. (2006). Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. 264–271. https://doi.org/10.1038/modpathol.3800528
Love, R., Mangu, P. B., Mcshane, L., Miller, K., Osborne, C. K., & Paik, S. (2010). J OURNAL OF C LINICAL O NCOLOGY American Society of Clinical Oncology / College of American Pathologists Guideline Recommendations for Immunohistochemical Testing of Estrogen and Progesterone Receptors in Breast Cancer. 28(16). https://doi.org/10.1200/JCO.2009.25.6529
Mallika Siva Donepudi, K., & Kondapalli, Seelam Jeevan Amos, P. V. (2014). Breast cancer statistics and markers. 10(3). https://doi.org/10.4103/0973-1482.137927
Milanezi, F., Steele, D., Savage, K., Simpson, P. T., Nesland, J. M., Pereira, E. M., Lakhani, S. R., & Schmitt, F. C. (2006). Metaplastic breast carcinomas are basal-like tumours. 10–21. https://doi.org/10.1111/j.1365-2559.2006.02467.x
Mudavanhu, Y. (2017). Quality of literature review and discussion of findings in selected papers on integration of ICT in teaching , role of mentors , and teaching science through science , technology , engineering , and mathematics ( STEM ). 12(4), 189–201. https://doi.org/10.5897/ERR2016.3088
Nabieva, E., Jim, K., Agarwal, A., & Chazelle, B. (2005). Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps. 21, 302–310. https://doi.org/10.1093/bioinformatics/bti1054
Nwagu, G. C., Bhattarai, S., Swahn, M., Ahmed, S., & Aneja, R. (2022). Prevalence and Mortality of Triple-Negative Breast Cancer in West Africa : Biologic and Sociocultural Factors. 1129–1140. https://doi.org/10.1200/GO.21.00082
Oliver, G. R., Hart, S. N., & Klee, E. W. (2015). Reviews Bioinformatics for Clinical Next Generation Sequencing. 135. https://doi.org/10.1373/clinchem.2014.224360
P. Freres, J. Collignon, C. gennigens, i. sCagnol, a. rorive, a. BarBeaux, P.a. CouCke, g. J. (2010). Triple Negatif. 1, 120–126.
Ramdhani, A., Ramdhani, M. A., & Amin, A. S. (2014). Writing a Literature Review Research Paper : A step-by-step approach Writing a Literature Review Research Paper : A step - by - step approach. December 2016.
Segaert, P., Lopes, M. B., Casimiro, S., Vinga, S., & Rousseeuw, P. J. (2019). Robust identification of target genes and outliers in triple-negative breast cancer data. https://doi.org/10.1177/0962280218794722
Shee, K., Wells, J. D., Ung, M., Hampsch, R. A., Traphagen, N. A., Yang, W., Liu, S., Zeldenrust, M. A., Wang, L., Kalari, K. R., Boughey, J. C., Demidenko, E., Kettenbach, A. N., Cheng, C., Goetz, M. P., & Miller, T. W. (2020). A transcriptionally-definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to HSP90 inhibition. 26(1), 159–170. https://doi.org/10.1158/1078-0432.CCR-18-2213.A
Shield, K. D., Soerjomataram, I., & Building, L. (2016). Alcohol Use and Breast Cancer : A Critical Review. 40(6), 1166–1181. https://doi.org/10.1111/acer.13071
Shiovitz, S., & Korde, L. A. (2015). Genetics of breast cancer: a topic in evolution. Annals of Oncology, 26(7), 1291–1299. https://doi.org/10.1093/annonc/mdv022
Veruscka Leso * , Maria Luigia Ercolano, D. L. C. and I. I. (2019). Occupational Chemical Exposure and Breast Cancer Risk According to Hormone Receptor Status : A Systematic Review.