CHAPTER 1
Translation in Immunology: The Role of Translational Biomarkers to Guide Clinical Use of Immunotherapy for Cancer
Saranya Chumsri1 and Keith L. Knutson2
1 Department of Hematology and Oncology, Mayo Clinic, Jacksonville, FL, USA
2 Department of Immunology, Mayo Clinic, Jacksonville, FL, USA
Introduction
For over a century, the role of the immune system in controlling and eradicating tumors has been a subject of intense debate. Since the 1800s, it has been recognized that the immune system also plays an important pathologic protumor role in tumor initiation and progression. Virchow commented on the interaction between inflammation, leukocytes, and cancer in his article from 1863 [1]. More than a hundred years later, we are still extricating the complexities of the interaction between cancers and the host immune system. More recently, Schreiber, Old, and Smyth described the process in which cancer and the immune system interact with each other, termed âcancer immunoeditingâ [2]. Cancer immunoediting describes a contiguous process that the immune system influences and shapes developing tumors. This process can result in successful rejection of the tumor or generate a tumor through immunologic evasion, the latter of which we now know can occur by multiple mechanisms and more often than not through any one of a number of immune suppressive pathways [3].
Despite the longâstanding interest in host antitumor immunity, it was only recently that immunotherapy emerged as one of the effective treatment options for cancer. In the past decade, several new immunotherapies, such as immune checkpoint blockade agents, tumor antigenâtargeted monoclonal antibodies, and a cellâbased dendritic vaccine, were approved by the U.S. Food and Drug Administration (FDA) for the treatment of multiple cancer types. In particular, the immune checkpoint blockade agents, which are treatments that target cytotoxic Tâlymphocyte associated protein 4 (CTLAâ4), programmed cell death protein 1 (PDâ1), and programmed cell death ligand 1 (PDLâ1), have gained impetus as potent anticancer therapies and have shown promising results across several tumor types, leading to a widespread revolution in cancer treatments and a massive shift in laboratory investigations. Since this form of therapy targets the hostâs regulatory components of the immune system rather than specific oncogenic mutations or tumor cells themselves, immune checkpoint blockade has been shown to be effective across multiple cancer types. Furthermore, given that the immune system has the capacity for longâterm memory, patients who respond to this form of immunotherapy frequently have durable responses, which can protect against disease progression for months and years [4â6].
While the early results of immune checkpoint blockade have been quite promising, only about a third of patients benefit from single agent therapy, accounting for both partial and complete responses, defined by the FDA as the objective response rate (ORR). Not all tumor types are equally responsive to immune checkpoint blockade, for reasons that as of yet remain unclear. Emerging studies suggest that combination treatments adding additional immunotherapies or other modalities to immune checkpoint blockade results in ORRs that appear to be higher in many cases. However, in most cases the superiority of combination therapy over monotherapy is still not well proven. Chen and Mellman et al. introduced the concept of the cancerâimmunity cycle, which describes the interactions and processes of how the immune system recognizes and eradicates cancer cells [7]. To ensure effective antitumor activities, a series of stepwise events, including release of cancer cell antigens, antigen presentation, priming and activation, trafficking of T cells to tumors, infiltration of T cells into tumors, recognition of cancer cells by T cells, and killing of cancer cells, must be initiated and properly expanded. This cancerâimmunity cycle hypothesis provides potential opportunities to intervene, and provides rationale for combination therapy consisting of multiple immunotherapies to improve clinical responses [8]. Additionally, several other combination approaches, including with chemotherapy, antiangiogenic therapy, and hormonal therapy, are being considered [5, 9, 10]. In this chapter, potential and established biomarkers that can be used as prognostic indicators or as identifiers of patients who will benefit more from these immune checkpoint blockade agents are reviewed. Thus, the impressive therapeutic activity of immune checkpoint blockade, seen in recent years, has solidified the science of translational biomarkers, which enable more rapid, sensible deployment of novel clinical approaches for the select groups of patients who are most likely to benefit.
Biomarkers for antiâCTLAâ4
Cytotoxic Tâlymphocyte associated protein 4 (CTLAâ4) is an immune checkpoint that downâregulates immune responses. CTLAâ4 functions predominantly early in the cancerâimmunity cycle during T cell activation and enhances the immunosuppressive activity of regulatory T cells (Treg cells) [11, 12]. In contrast to PDâ1 or PDLâ1, which is typically thought to modulate antigenâexperienced effector cells in inflammatory environments, CTLAâ4 engages in the priming phase and regulates the amplitude of early activation of naĂŻve and memory T cells [13]. Ipilimumab was the first immune checkpoint blockade agent approved by FDA, is a humanized monoclonal antibody against CTLAâ4, and is indicated for advanced melanoma. However, the response rate for singleâagent ipilimumab is merely 10%, and ipilimumab has several concerning mechanisticâbased toxicities [14]. Common serious toxicities associated with ipilimumab are dermatitis, enterocolitis, endocrinopathies, liver abnormalities, and uveitis [15]. Therefore, it is critical to identify biomarkers that can be used to select patients who are more likely to benefit from this toxic therapy.
Several serum biomarkers, such as lactate dehydrogenase (LDH), Câreactive protein (CRP), vascular endothelial growth factor (VEGF), and soluble CD25 (sCD25), have been shown to be associated with ipilimumab treatment in patients with advanced melanoma [16â19]. Higher baseline levels of LDH and VEGF were associated with reduced ipilimumab treatment response in patients with metastatic melanoma. However, subsequent reductions in LDH, CRP, and Tregs as well as an increase in absolute lymphocyte count after ipilimumab treatment were significantly associated with improved overall survival (OS) and disease control rate. sCD25 acts as a decoy receptor for ILâ2. While recombinant ILâ2 improves efficacy of ipilimumab, sCD25 inhibits the anticancer effects of ipilimumab, and the high level of baseline sCD25 appears to confer resistance to ipilimumab [16]. However, most of these studies were small retrospective database reviews, and at this time, no confirmatory clinical trials have been done to support the routine use of these biomarkers for the selection of patients who should receive ipilimumab.
Given that ipilimumab exerts its antitumor activity through activation and increasing proliferation of T cells, serial measurements of absolute lymphocyte counts (ALC) in the blood after treatment have also been investigated as a pharmacodynamic biomarker of ipilimumab [20, 21]. After ipilimumab therapy, an ALC â„ 1000/ÎŒL at week seven or an increase in ALC from baseline at week twelve was significantly associated with improved OS [18, 22, 23]. Besides a simple absolute count of lymphocytes, which can be heterogeneous, CD4+ICOS+ T cells, an activated T cell subset, have been used to track immune response after ipilimumab therapy as a pharmacodynamics marker. Four independent studies demonstrated that patients who had a sustained increase in CD4+ICOS+ T cells over twelve weeks after ipilimumab therapy had significant improvement in OS [24â28]. This consistent finding is intriguing because ICOS (inducible T cell costimulatory) costimulation is associated with Th2 immune responses, suggesting the possibility that antibodies are involved in the clinical activity of CTLAâ4 blockade [29].
Since T cells recognize processed peptides presented by host major histocompatibility complex molecules, mutations in cancers can produce unique peptides that can be recognized by T cells, termed mutated neoantigens [30]. The antigenicity of these neoantigens may affect the function of the protein, and a passenger mutation with no functional role may still generate sufficient immune responses, although the potential for immune escape based on antigen loss is still possible. However, a greater mutational load in the tumors can potentially produce more neoantigens, which will result in a larger repertoire of existing tumorâspecific T cells, and less chances of antigenâloss variant escape. Given the fact that immune checkpoint blockade agents exert their activity by unleashing these preexisting tumorâspecific T cells, it was initially hypothesized that tumors with higher mutational loads would respond better to this form of therapy [30]. This hypothesis was substantiated based on the early results of studies with ipilimumab, which has activity in the cancer with the highest mutational load, melanoma. In two melanoma studies of ipilimumab, patients who responded to ipilimumab had a statistically significant higher median mutation load in their tumors compared to patients who did not respond. However, there appeared to be no distinct cutoff that can be used to identify patients who would not benefit from ipilimumab therapy [31, 32]. The inability to establish a cutoff may reflect important variations such as HLA allelic variation and immunogenicity of the putative neoantigens, both of which may limit the utility of the mutational load as a response indicator [33].
Despite years of trials and retrospective studies, to date no companion diagnostic test has been approved by the FDA to identify patients who are more likely to benefit from ipilimumab. Thus, additional translational studies of patients undergoing therapy should be designed and implemented to aid in identifying the patients most likely to respond.
Biomarkers for antiâPDâ1/PDLâ1 therapies
Programmed cell death protein 1 or PDâ1 (also known as PDCD1) and its ligand PDâ1 ligand 1 or PDLâ1 (also known as B7âH1) are key immune checkpoints that downâregulate antitumor effects of T cells in the tumor microenvironment [34, 35]. PDLâ1 engages PDâ1 and inhibits proliferation and cytokine production of T cells [36]. Several preclinical studies demonstrated that inhibition of the PDâ1/PDLâ1 interaction enhances T cell responses and augments their antitumor activities [34, 37, 38]. The potential translational biomarkers for antiâPDâ1/PDLâ1 can be categorized into either immuneârelated or genomicârelated biomarkers [39].
Immuneârelated biomarkers
PDâ1 and PDLâ1 immune checkpoint blockade agents are thought to exert their activity mainly by enhancing the antitumor activities of preformed host immune responses [40]. Thus, the amount of preexisting immune infiltrate in the tumor at baseline prior to antiâPDâ1/PDLâ1 treatment was one of the first translational biomarker candidates to be explored. In melanoma, higher numbers of preexisting CD8+ T cells, particularly at the invasive tumor margin, have been shown to associate with tumor regression in patients treated with antiâPDâ1 therapy (pembrolizumab) [40]. Comparing between responders and nonresponders, responding patients had significantly higher numbers of CD8+, PDâ1+, and PDLâ1+ cells at the invasive tumor margin and a more clonal T cell antigen receptor repertoire. Furthermore, patients who respo...
