96119 20260217205445.0 doi 10.3390/cancers12102974 sideral 120699 ART-2020-120699 eng Sesma, Andrea From tumor mutational burden to blood T cell receptor: Looking for the best predictive biomarker in lung cancer treated with immunotherapy 2020 Access copy available to the general public Unrestricted 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. info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 6.639 2020 ONCOLOGY 51 / 241 = 0.212 2020 Q1 T1 1.818 2020 Oncology 2020 Q1 Cancer Research 2020 Q1 info:eu-repo/semantics/review info:eu-repo/semantics/publishedVersion Pardo, Julián Universidad de Zaragoza (orcid)0000-0003-0154-0730 Cruellas, Mara Gálvez, Eva M. Universidad de Zaragoza Gascón, Marta (orcid)0000-0002-6811-6654 Isla, Ddolores Martínez-Lostao, Luis Universidad de Zaragoza (orcid)0000-0003-3043-147X Ocáriz, Maitane Paño, José Ramón Universidad de Zaragoza (orcid)0000-0002-9600-8116 Quílez, Elisa Ramírez, Ariel (orcid)0000-0002-3888-7036 Torres-Ramón, Irene Universidad de Zaragoza (orcid)0000-0003-3387-0558 Yubero, Alfonso Zapata, Maria Lastra, Rodrigo 1006 255 Universidad de Zaragoza Dpto. Fisiatría y Enfermería Área Enfermería 1011 566 Universidad de Zaragoza Dpto. Microb.Ped.Radio.Sal.Pú. Área Inmunología 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 12, 10 (2020), 2974 [19 pp] Cancers Cancers 2072-6694 259711 http://zaguan.unizar.es/record/96119/files/texto_completo.pdf Versión publicada 501648 http://zaguan.unizar.es/record/96119/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:96119 articulos driver 2026-02-17-20:17:33 ARTICLE