| Literature DB >> 32522712 |
Lynette M Sholl1, Fred R Hirsch2, David Hwang3, Johan Botling4, Fernando Lopez-Rios5, Lukas Bubendorf6, Mari Mino-Kenudson7, Anja C Roden8, Mary Beth Beasley9, Alain Borczuk10, Elisabeth Brambilla11, Gang Chen12, Teh-Ying Chou13, Jin-Haeng Chung14, Wendy A Cooper15, Sanja Dacic16, Sylvie Lantuejoul17, Deepali Jain18, Dongmei Lin19, Yuko Minami20, Andre Moreira10, Andrew G Nicholson21, Masayuki Noguchi22, Mauro Papotti23, Giuseppe Pelosi24, Claudia Poleri25, Natasha Rekhtman26, Ming-Sound Tsao27, Erik Thunnissen28, William Travis26, Yasushi Yatabe29, Akihiko Yoshida29, Jillian B Daigneault30, Ahmet Zehir25, Solange Peters31, Ignacio I Wistuba32, Keith M Kerr33, John W Longshore34.
Abstract
Immune checkpoint inhibitor (ICI) therapies have revolutionized the management of patients with NSCLC and have led to unprecedented improvements in response rates and survival in a subset of patients with this fatal disease. However, the available therapies work only for a minority of patients, are associated with substantial societal cost, and may lead to considerable immune-related adverse events. Therefore, patient selection must be optimized through the use of relevant biomarkers. Programmed death-ligand 1 protein expression by immunohistochemistry is widely used today for the selection of programmed cell death protein 1 inhibitor therapy in patients with NSCLC; however, this approach lacks robust sensitivity and specificity for predicting response. Tumor mutation burden (TMB), or the number of somatic mutations derived from next-generation sequencing techniques, has been widely explored as an alternative or complementary biomarker for response to ICIs. In theory, a higher TMB increases the probability of tumor neoantigen production and therefore, the likelihood of immune recognition and tumor cell killing. Although TMB alone is a simplistic surrogate of this complex interplay, it is a quantitative variable that can be relatively readily measured using currently available sequencing techniques. A large number of clinical trials and retrospective analyses, employing both tumor and blood-based sequencing tools, have evaluated the performance of TMB as a predictive biomarker, and in many cases reveal a correlation between high TMB and ICI response rates and progression-free survival. Many challenges remain before the implementation of TMB as a biomarker in clinical practice. These include the following: (1) identification of therapies whose response is best informed by TMB status; (2) robust definition of a predictive TMB cut point; (3) acceptable sequencing panel size and design; and (4) the need for robust technical and informatic rigor to generate precise and accurate TMB measurements across different laboratories. Finally, effective prediction of response to ICI therapy will likely require integration of TMB with a host of other potential biomarkers, including tumor genomic driver alterations, tumor-immune milieu, and other features of the host immune system. This perspective piece will review the current clinical evidence for TMB as a biomarker and address the technical sequencing considerations and ongoing challenges in the use of TMB in routine practice.Entities:
Keywords: Biomarker; Immunotherapy; NSCLC; PD-L1; TMB
Mesh:
Year: 2020 PMID: 32522712 DOI: 10.1016/j.jtho.2020.05.019
Source DB: PubMed Journal: J Thorac Oncol ISSN: 1556-0864 Impact factor: 15.609