From tumor mutational burden to blood T cell receptor: Looking for the best predictive biomarker in lung cancer treated with immunotherapy

Sesma, A. ; Pardo, J. (Universidad de Zaragoza) ; Cruellas, M. ; Gálvez, E.M. ; Gascón, M. ; Isla, D. ; Martínez-Lostao, L. (Universidad de Zaragoza) ; Ocáriz, M. ; Paño, J.R. (Universidad de Zaragoza) ; Quílez, E. ; Ramírez, A. ; Torres-Ramón, I. (Universidad de Zaragoza) ; Yubero, A. ; Zapata, M. ; Lastra, R.

Resumen: Despite therapeutic advances, lung cancer (LC) is one of the leading causes of cancer morbidity and mortality worldwide. Recently, the treatment of advanced LC has experienced important changes in survival benefit due to immune checkpoint inhibitors (ICIs). However, overall response rates (ORR) remain low in unselected patients and a large proportion of patients undergo disease progression in the first weeks of treatment. Therefore, there is a need of biomarkers to identify patients who will benefit from ICIs. The programmed cell death ligand 1 (PD-L1) expression has been the first biomarker developed. However, its use as a robust predictive biomarker has been limited due to the variability of techniques used, with different antibodies and thresholds. In this context, tumor mutational burden (TMB) has emerged as an additional powerful biomarker based on the observation of successful response to ICIs in solid tumors with high TMB. TMB can be defined as the total number of nonsynonymous mutations per DNA megabases being a mechanism generating neoantigens conditioning the tumor immunogenicity and response to ICIs. However, the latest data provide conflicting results regarding its role as a biomarker. Moreover, considering the results of the recent data, the use of peripheral blood T cell receptor (TCR) repertoire could be a new predictive biomarker. This review summarises recent findings describing the clinical utility of TMB and TCR (TCRB) and concludes that immune, neontigen, and checkpoint targeted variables are required in combination for accurately identifying patients who most likely will benefit of ICIs.

Idioma: Inglés

DOI: 10.3390/cancers12102974

Año: 2020

Publicado en: Cancers 12, 10 (2020), 2974 [19 pp]
ISSN: 2072-6694

Factor impacto JCR: 6.639 (2020)

Categ. JCR: ONCOLOGY rank: 51 / 242 = 0.211 (2020) - Q1 - T1

Factor impacto SCIMAGO: 1.818 - Oncology (Q1) - Cancer Research (Q1)

Tipo y forma: Revisión (Versión definitiva)

Área (Departamento): Área Inmunología (Dpto. Microb.Ped.Radio.Sal.Pú.)
Área (Departamento): Area Medicina (Dpto. Medicina, Psiqu. y Derm.)