2.3.2 Tumor Mutation Burden
Tumor has been described as a genomic disease driven by an accumulation of both germline derived and somatic mutations.Recent advances in molecular techniques have allowed the evaluation of the impact of germline and tumor mutational status on overall cancer risk, patient prognosis and treatment response.Tumor mutation frequency varies widely among cancer types and between tumors of the same histotype.Tumor mutational burden (TMB) can be analyzed by various methods and is reported as the total number of sequence variants or mutations per tumor genomic region analyzed.High mutational burden is typical of cancers developed as a result of exposure to powerful carcinogens, such as tobacco smoke and polycyclic aromatic hydrocarbons in lung cancers and bladder cancers, as well as exposure to mutagens, such as ultraviolet light in melanoma [40, 41].
In 2019, the interest in TMB by physicians and researchers has increased as tumors with higher TMB can be more responsive to immune checkpoint inhibitor therapies, which may be due to their increased inherent immunogenicity.An effective host anti-tumor immune response requires tumor cell surface antigen recognition followed by priming and activation of immune cells that can ultimately mediate tumor cell killing.However, inhibitory receptor interactions on immune cells are often hijacked by tumors to dampen cytotoxic T cell responses against transformed cells thereby avoiding immune surveillance.For example, programmed death ligand 1 (PD-L1)expressed on tumors engages the immune checkpoint PD-1 on cytotoxic T lymphocytes to block their action against tumor cells.Likewise, Cytotoxic T lymphocyte antigen 4 (CTLA-4)engagement by B7-1 (CD80)/B7-2 (CD86) ligands constitutes another key inhibitory checkpoint signal that limits T-cell activation.Immune checkpoint modulating drugs aim to remove these inhibitory signals to boost the immune response against cancer cells and relieve innate as well as adaptive immune resistance developed by tumors.It has been suggested that patients who do not derive benefit from immune checkpoint inhibitor therapies lack pre-existing anti-tumor T-cell responses, in part due to low immunogenicity of their underlying disease.Mutational load, in particular, nonsynonymous mutations, in cancer cells may generate novel antigens (termed neoantigens) that are not subject to immune tolerance and allow for an adaptive immune response by the host.The observation that nonsynonymous mutation burden is associated with efficacy of the anti-PD-1 antibody pembrolizumab is consistent with this hypothesis.Moreover, several preclinical and clinical reports have demonstrated that neoantigen-specific effector T cell response lies at the core of recognizing and eliminating established tumors [41-46].As shown in Figure 2.2, it describes tumor cell with high TMB and its relationship with the immune system
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Figure 2.2 Schematic diagram of tumor cell with high TMB and its relationship with the immune system.(Please scan the QR code on the Preface to get original color figures.)
Source: Galuppini F, Pozzo C A D, Deckert J, Loupakis F, Baffa R.“Tumor Mutation Burden: From Comprehensive Mutational Screening to the Clinic”.CancerCellInternational, 2019, 19: 209.
The translational significance of TMB assessment is derived from its link to tumor immunogenicity and its subsequent prognostic and predictive values.In fact, several recent studies have demonstrated that TMB can be exploited as a biomarker, especially in order to predict patient responses to immune checkpoint modulatory agents [41].
The development of drugs against well-described PD-1/PD-L1 and CTLA-4/B7 checkpoints interactions have proven effective in unleashing a cytotoxic response against malignant cells and have revolutionized the therapeutic approaches to various solid tumors, including those typically marked by strong resistance to traditional chemotherapeutics.This is illustrated by the particular effectiveness of both nivolumab, and pembrolizumab (targeting PD-1) and ipilimumab (targeting CTLA-4) against a subset of patients with Non-Small Cell Lung Cancer (NSCLCs) and melanoma.Despite the significant benefit potentially achievable with these new therapies, response rates vary widely between cancer types and there is a particular need for predictive biomarkers that can be applied upfront to identify patients more likely to respond to immune checkpoint modulators.To this end, the predictive value of various features of tumors, host immune cells and the tumor microenvironment have been further explored including PD-L1 expression in both tumor and immune cells, selected single gene mutational status, peripheral-blood lymphocyte count, tumor infiltrating lymphocyte count, markers of T-cell activation and evaluation of inflammatory cytokines.Nevertheless, none of these have been unambiguously associated with patient outcome endpoints including Overall Survival (OS), Progression Free Survival (PFS), and Objective Response Rate (ORR) across multiple tumor types.Microsatellite instability-high (MSI-H) status,mismatch repair deficiency and PD-L1 expression constitute the only predictive biomarkers successfully used for patient selection in select malignancies [41, 47].Since TMB assessment is not exempt from economical and technical issues, it is important to establish a list of malignancies that are more likely to be highly mutated and, thus, to be priority candidates for this analysis.Here the etiology of the diverse neoplastic pathologies plays a critical role.In principle, TMB is likely to be high especially in two categories of tumors: (i) those arising from the exposure to powerful carcinogenic and mutagenic agents (e.g.tobacco smoke and UV-A), and (ii) those caused by germline mutations in genes encoding for proteins involved in DNA repair and replication[41].