Affiliation:
1. Pirogov Russian National Research Medical University
2. Blokhin National Medical Research Center of Oncology
Abstract
With an increasing number of alternative effective therapies available for patients, there is an increasing need for a more accurate selection for therapy (compared to observation, for example, after radical surgical treatment), selection of the optimal therapy (prediction of primary resistance or, conversely, high sensitivity), and criteria for stopping treatment (complete tumor elimination) or changing therapy (molecular, i.e. preclinical and preradiological progression). We look for answers to all these questions in a variety of biomarkers. Many clinical markers (e.g. ECOG performance status or disease prevalence), molecular genetic (e.g. such as mutations in the BRAF gene, NRAS, NF1, TMB), immunological (e.g. tumor infiltration by lymphocytes and expression of PDl1, PDl2, PD1 or other «immune checkpoints» on tumor cells and microenvironmental cells), as well as factors circulating in the blood and plasma (e.g., blood cell-to-cell ratio, circulating tumor DNA or cytokines in the peripheral blood). In this study, we have tried to analyze the data accumulated so far and attempt to relate them both to current clinical practice and available therapies, as well as to outline the prospects for upcoming research in this area. In our opinion, the available data may influence the current routine practice of oncologists and allow for a more careful choice of first-line therapy to maximize benefit and minimize harm. Although it is likely that some organizational effort will be needed to change established clinical practice in order to identify such biomarkers.
Reference93 articles.
1. Hodi F.S., O’Day S.J., McDermott D.F., Weber R.W., Sosman J.A., Haanen J.B. et al. Improved Survival with Ipilimumab in Patients with Metastatic Melanoma. N Engl J Med. 2010;363(8):711–723. https://doi.org/10.1056/NEJMoa1003466.
2. Tarhini A., Kudchadkar R.R. Predictive and On-Treatment Monitoring Biomarkers in Advanced Melanoma: Moving toward Personalized Medicine. Cancer Treat Rev. 2018;71:8–18. https://doi.org/10.1016/j.ctrv.2018.09.005.
3. Bastian B., de la Fouchardiere A., Elder D., Gerami P., Lazar A., Massi D. et al. Genomic Landscapes of Melanoma. In: Elder D., Massi D., Scolyer R., Willemze R. (eds.). World Health Organisation classification of skin tumours. 4th ed. Lion, France International Agency for Research on Cancer; 2018, pp. 72–75.
4. Flaherty K.T., Lee S.J., Zhao F., Schuchter L.M., Flaherty L., Kefford R. et al. Phase III Trial of Carboplatin and Paclitaxel with or without Sorafenib in Metastatic Melanoma. J Clin Oncol. 2013;31(3):373–379. https://doi.org/10.1200/JCO.2012.42.1529.
5. Hauschild A., Agarwala S.S., Trefzer U., Hogg D., Robert C., Hersey P. et al. Results of a Phase III, Randomized, Placebo-Controlled Study of Sorafenib in Combination with Carboplatin and Paclitaxel as Second-Line Treatment in Patients with Unresectable Stage III or Stage IV Melanoma. J Clin Oncol. 2009;27(17):2823–2830. https://doi.org/10.1200/JCO.2007.15.7636.
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