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Open AccessReview

From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy

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Medical Oncology Department, University Hospital Lozano Blesa, 50009 Zaragoza, Spain
2
Aragon Health Research Institute (IIS Aragón), 50009 Zaragoza, Spain
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ARAID Foundation (IIS Aragón), 50009 Zaragoza, Spain
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Microbiology, Preventive Medicine and Public Health Department, Medicine, University of Zaragoza, 50009 Zaragoza, Spain
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Biomedical Research Center in Bioengineering, Biomaterials and Nanomedicine Network (CIBER-BBN), 28029 Madrid, Spain
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Instituto de Carboquímica (ICB-CSIC), Miguel Luesma 4, 50018 Zaragoza, Spain
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Immunology Department, University Hospital Lozano Blesa, 50009 Zaragoza, Spain
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Department of Microbiology, Pediatrics, Radiology and Public Health, University of Zaragoza, 50009 Zaragoza, Spain
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Aragon Nanoscience Institute, 50018 Zaragoza, Spain
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Aragon Materials Science Institute, 50009 Zaragoza, Spain
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Infectious Disease Department, University Hospital Lozano Blesa, 50009 Zaragoza, Spain
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Nanotoxicology and Immunotoxicology Unit (IIS Aragón), 50009 Zaragoza, Spain
*
Author to whom correspondence should be addressed.
Cancers 2020, 12(10), 2974; https://doi.org/10.3390/cancers12102974
Received: 3 September 2020 / Revised: 30 September 2020 / Accepted: 12 October 2020 / Published: 14 October 2020
(This article belongs to the Special Issue Diagnostic and Predictive Biomarkers in Lung Cancer)
Immune control inhibitor drugs (anti-PD1/PD-L1/CTLA-4) (ICIs) are showing efficacy in the treatment of lung cancer. Currently the only biomarker with clinical utility for ICIs, such as the expression of PDL1, does not appear to be perfect or effective. Our working group is conducting a pilot study in lung cancer patients receiving ICIs with the aim of analyze the factors that affect the sensitivity of the immunotherapy in lung Cancer. Tumor Mutational Burden (TMB) and the sequencing of the T Cell Receptor (TCR) repertoire in peripheral blood have been postulated as predictive biomarkers of efficacy of immunotherapy. The review focusses on the predictive value of TMB for clinical responses to ICIs and discusses its clinical need after a discussion of the limitations. TCR CDR3 beta analysis and parameters such as clonality and TCR convergence may be good alternatives. For the moment, the combination of biomarkers may be the optimal tool.
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 TCRβ (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. View Full-Text
Keywords: lung cancer; ICIs (immune checkpoint inhibitors); biomarker; TMB (tumor mutational burden); TCR (T cell receptor); TCRβ (TCRB); neoantigen lung cancer; ICIs (immune checkpoint inhibitors); biomarker; TMB (tumor mutational burden); TCR (T cell receptor); TCRβ (TCRB); neoantigen
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MDPI and ACS Style

Sesma, A.; Pardo, J.; Cruellas, M.; Gálvez, E.M.; Gascón, M.; Isla, D.; Martínez-Lostao, L.; Ocáriz, M.; Paño, J.R.; Quílez, E.; Ramírez, A.; Torres-Ramón, I.; Yubero, A.; Zapata, M.; Lastra, R. From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy. Cancers 2020, 12, 2974.

AMA Style

Sesma A, Pardo J, Cruellas M, Gálvez EM, Gascón M, Isla D, Martínez-Lostao L, Ocáriz M, Paño JR, Quílez E, Ramírez A, Torres-Ramón I, Yubero A, Zapata M, Lastra R. From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy. Cancers. 2020; 12(10):2974.

Chicago/Turabian Style

Sesma, Andrea; Pardo, Julián; Cruellas, Mara; Gálvez, Eva M.; Gascón, Marta; Isla, Dolores; Martínez-Lostao, Luis; Ocáriz, Maitane; Paño, José R.; Quílez, Elisa; Ramírez, Ariel; Torres-Ramón, Irene; Yubero, Alfonso; Zapata, María; Lastra, Rodrigo. 2020. "From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy" Cancers 12, no. 10: 2974.

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