Immune biomarkers: how well do they serve prognosis in human cancers?

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Review

Immune biomarkers: how well do they serve prognosis in human cancers? Expert Rev. Mol. Diagn. 15(1), 49–59 (2015)

Constantin N Baxevanis*, Eleftheria A Anastasopoulou, Ioannis F Voutsas, Michael Papamichail, Sonia A Perez Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, Athens 11522, Greece *Author for correspondence: Tel.: +30 210 640 9380 [email protected]

In order to be optimally efficacious, therapeutic cancer vaccines must induce robust tumor-specific CD8+ cytotoxic T cells, which are responsible for tumor cell lysis. Unlike cytotoxic drugs, which act directly on the tumor, cancer vaccines demonstrate new kinetics involving the generation of specific cellular immune responses, which need to be translated into antitumor responses to delay tumor progression and improve survival. These delayed kinetics of action establish a new concept of benefit in the long term, which implies a slow down in tumor growth rates, than a marked reduction in tumor size. Therefore, there is a significant need to identify intermediate biomarkers so that clinical responses can be evaluated in a timely manner. Therapeutic vaccination as a modality for cancer treatment has received significant attention with multiple clinical trials demonstrating improvements in overall survival. Significant challenges to this modality remain, including increasing vaccine potency and minimizing treatment-related toxicities and identifying prognostic and predictive biomarkers of clinical benefit that may guide to select and optimize the therapeutic strategies for patients most likely to gain benefit. KEYWORDS: biomarkers • cancer immunotherapy • cancer vaccines • gene signature • immune monitoring • immunoediting • tumor infiltrating lymphocytes

In light of the mechanism of action of therapeutic cancer vaccines, a cascade of immune reactions and cell–cell interactions triggered by tumor antigens and resulting in proper activation of the immune system have been considered for predicting clinical responses. Hence, the measurement of immune responses in the course of immunotherapy could represent a suitable ‘proof-of-principle’ biomarker that could be tested before clinical end points can be evaluated. Identifying immunologic biomarkers would not only guide the development of immunotherapy trials, but they themselves could also act as surrogates for clinical benefit. This latter is of particular importance, in light of recent immunotherapy trials in prostate cancer, which have demonstrated clinical improvements in terms of overall survival (OS) but not in progression-free survival [1]. Until surrogates for OS are developed, the clinical efficacy of immunotherapies will likely have to be validated in advanced disease stages so that OS can be assessed in a timely fashion. The use of accurate and reproducible assays is a strict requirement for reliable biomarker

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10.1586/14737159.2015.965684

measurement during immunotherapies. Assays to evaluate tumor antigen-specific responses include estimations of frequencies of tumorspecific T-cell clones through multimer staining, IFN-g-based ELISPOT assays, cell proliferation assays and cytotoxicity assays, as well as delayedtype hypersensitivity (DTH) [2–5]. These assays are being studied in various clinical trials. Although the results which have emerged from such bioassay studies have shown to some extent an association with clinical responses, they are still far from pointing to one bioassay as a surrogate for clinical outcomes [6]. The reason underlying this may reflect the mechanistic complexity of an immune response and the high degree of variability which characterizes immunological assays for T-cell immunity. As a consequence, the results from various clinical centers participating in multicenter clinical studies show a high range of variation and often are non-reproducible. Inevitably, this has contributed to the inability to accurately correlate immunological with clinical responses. Another potential reason for this failure could be the source from which the

2015 Informa UK Ltd

ISSN 1473-7159

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Baxevanis, Anastasopoulou, Voutsas, Papamichail & Perez

lymphocytes included in the above assays is derived. Thus, analyses made with mononuclear cells isolated from peripheral blood, may not necessarily reflect immune cells at the tumor site. However, intratumoral lymphocytes are not easily accessible and can be tested only once, thereby not allowing long-term follow-up. Moreover, many immunotherapeutic modalities are currently being applied in the adjuvant setting where malignant tissue is not available after standard treatment. Another issue that hinders the utilization of immunologic assays as surrogates for clinical responses is the fact that these actually may not address responses to the proper tumor antigen. Hence, while most of the studies examine vaccine-specific immunity, few have analyzed the ‘epitope spreading’ phenomenon, where the true immunologic biomarker may be represented by T-cell responses to tumor antigens other than those included in the vaccine. In this case, tumor cells act as ‘inducers’ of an ‘antigen cascade’ with the generation of T cells specific for other tumor-associated antigens [7,8]. Therefore, ‘epitope spreading’ requires the presence of tumor cells, once again rendering questionable its applicability in the adjuvant setting. Even so, there are reports demonstrating that it is feasible to develop peripheral blood-derived immunologic biomarkers able to predict clinical responses. This review focuses on the identification of pre-existing or therapy-induced immunologic markers that may predict response to immunotherapies. These markers may also be prognostic and/or predictive for clinical outcome. Immune signatures as predictors of survival

The observation that vaccine-induced immunological responses in the peripheral blood were not consistently correlated with clinical benefit led to the suggestion that pre-existing and/or induced antitumor responses within the tumor microenvironment play a key role in human cancer progression. As a result, the possibility has emerged that immunological signatures within the tumor may be indicative of established interactions between immune and tumor cells, predisposing patients toward clinical benefit following vaccination or after treatment with immune checkpoint inhibitors [9]. Thus, intratumoral immune measures could serve as biomarkers or surrogates for clinical efficacy. However, despite significant progress in immunological monitoring, at least initially, it was difficult to correlate the profile of immunological changes during immunotherapies with clinical end points [10]. Such a failure could be attributed to the complexity of interactions between immune cells and the tumor, mostly derived from tumor heterogeneity [11,12], and the composition of the tumor microenvironment [13,14]. Additionally, there were problems in the standardization of assays measuring cellular immune responses, which were mostly appropriate for identifying immunological biomarkers [15–17]. Nevertheless, recent advances in our understanding of cellular and molecular mechanisms underlying the development of antitumor immunity, progress made in genomics and gene expression profiling and harmonization of cellular immune assays have shed new light on the identification and selection of 50

appropriate immune end points based on immune phenotypes, molecular and biological targets. Intratumoral gene signatures

Gene expression profiling is a validated method for studying histological heterogeneity and for also identifying gene signatures (GS) useful for classifying patients with different survival outcomes. Increasing our understanding of the immune GS within the tumor microenvironment and in this way obtaining biologic insights of tumor phenotypes has certainly provided a source for the rational development of cancer immunotherapeutic approaches. In general, the applicability of GS has not been easy to establish mostly due to the small number of subjects examined and inclusion of heterogeneous tumor types [18–20]. Nevertheless, individual gene analysis using FNA material from metastatic lesions of melanoma patients undergoing active immunotherapies [21–24] supported the hypothesis that immune responsiveness against a tumor may be predetermined and not solely dependent on the capacity of a given immunotherapy to elicit antitumor immunity. In these studies, it was observed that melanoma metastases likely to regress following immunotherapy, express a heterogeneous array of inflammatory cytokines and growth factors. Thus, an endogenously existing inflammation-driven adaptive as well as innate immunity at the tumor site in some tumors predisposes to immune rejection by patients’ immune systems. There were also results from microarray analyses from other tumor types (e.g., breast and lung cancer) revealing the important role of the tumor’s immunologic microenvironment in a patient’s response to cancer immunotherapy [25,26]. Most recently, results from a study analyzing a pre-treatment gene expression signature predictive (PreGS) of response to MAGE-A3 immunotherapy in patients with metastatic melanoma, pointed to the existence of a cancer immune phenotype supportive of immune responsiveness. In this Phase II study in advanced melanoma [27], microarray analysis and hierarchic clustering was performed to identify a PreGS for response to recombinant MAGE-A3 vaccination plus an adjuvant (AS15). This signature, consisting of 84 genes, was associated with clinical benefit: median OS in PreGS-positive patients was almost 54 versus 16 months median OS in PreGS-negative patients. The PreGS included immune-related genes, involving MHC class I and II, T-cell markers such as CD3D and CD8 (known to be regulated by IFN-g) and downstream targets of STAT1 and interferon regulatory factor 1. Additionally, it contained genes involved in antigen processing and also a chemokine signature including CCL5, CXCL2, CXCL9 and CXCL10, suggesting that this PreGS may predict a specific tumor microenvironment, which favors the infiltration of immune effector lymphocytes and immunotherapy efficacy. The same PreGS was then used to predict the outcome for patients with resected nonsmall cell lung cancer (NSCLC) treated similarly with MAGEA3 plus the AS15 adjuvant; actively treated GS-positive patients showed a favorable disease-free interval compared with placebo-treated GS-positive patients [25]. Prospective validation Expert Rev. Mol. Diagn. 15(1), (2015)


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of the PreGS was added as a co-primary end point in the Phase III MAGRIT and DERMA studies [28,29]. The confirmation of such a hypothesis could have a substantial effect on future strategies for optimizing the choice of therapy for individual patients. An interesting point to be addressed in the future will be whether this PreGS has a dual role, that is, if it is also prognostic (ProGS). To be precise, will patients who are PreGS-positive do clinically better than those who are PreGSnegative, regardless of the treatment received? Although, so far, there is no evidence to substantiate this, there are common functional clusters of genes between this PreGS and other ProGS identified mostly in colon but also other types of cancer [21,30–35]. As recently suggested [36], there might be an overlap between ProGS and PreGS, with ProGS acting early during immunosurveillance by slowing down tumor growth rates. Then, when the tumor reaches a stage of resistance to immunosurveillance via immunoediting, the ProGS is no longer active but can be reactivated by immune interventions which render it predictive. The prognostic role of tumor infiltrating lymphocytes

Many studies involving a wide variety of human cancers have indicated that infiltration of the tumor microenvironment by lymphocytes (TIL) constitutes a robust prognostic indicator. The identification of cancer types characterized by elevated infiltration of TIL has suggested that some patients may benefit from immune-based therapies. Recently, a large body of reports has revealed the importance of TIL in regulating the clinical progression of various epithelial cancers [37]. Thus, in some solid tumors, high levels of tumor-infiltrating CD4+ T helper (Th), CD8+ T cytotoxic and CD45RO+ memory T lymphocytes have been associated with favorable clinical outcomes [14,38]. Conversely, a high density of tumor-infiltrating FOXP3+ Tregs often represents an unfavorable prognostic factor [14], although recent studies have challenged this paradigm by showing that Tregs exhibit heterogeneous phenotypes and, in some types of cancer, are associated with favorable prognosis [39]. These data, notwithstanding recent accumulating evidence, suggest that the dynamic relationship between effector and regulatory TIL may act either as an inauspicious or favorable prognostic factor having serious implications for disease outcome [14,36,40]. Thus, the relative intensity of tumor-promoting and antitumor immune responses, as well as the type and density of tumor-infiltrating immune cells, constitute important prognostic markers [36,41]. In a large study utilizing tumors from ovarian cancer patients, it was demonstrated that the presence or absence of intratumoral T cells correlated with the clinical outcome after surgical debulking and adjuvant chemotherapy [42]. Levels of lymphocyte-attracting chemokines, and IFN-g-induced monokines were high in tumors from patients with prolonged remission and survival, indicating that they may be implicated in mechanisms affecting clinical outcome. The presence of TIL has been shown to be an independent factor predicting improved survival, as demonstrated in multivariate analyses, for various types of cancer also including melanoma, informahealthcare.com

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mesothelioma, endometrial, bile duct, renal cell and esophageal carcinoma [43–49]. In the majority of these reports, CD8+ TIL appeared to correlate with clinical benefit. In breast cancer, two large series, both in newly diagnosed or early stage breast cancer, support a correlation between immune gene signature and better clinical outcomes [50,51]. Unsupervised gene expression profiling of breast cancer-associated stroma has also revealed a gene signature predictive of good prognosis (>98% 5-year survival) that was enriched for cytotoxic CD8+ T-cell and NK cell activity genes [52]. CD3+ TIL counts were also shown to predict outcome of neoadjuvant chemotherapy [50,53]. Intratumoral B cells have also been associated with favorable prognosis in breast cancer. In lymph node-negative breast cancer patients, mRNA levels for immunoglobulin heavy- and light-chain genes were associated with metastasis-free survival [54]. Importantly, immunoglobulin k mRNA levels were demonstrated to define prognosis in a comprehensive analysis of available breast cancer data sets and to predict response to neoadjuvant anthracyclinebased therapy [55]. In the same study, it was also shown that immunoglobulin k mRNA levels have prognostic relevance in NSCLC and colorectal cancer (CRC). Detailed genomic and in situ immunohistochemistry analyses of tumors from CRC patients [34,56] also provided evidence for a role of adaptive immune responses within CRC as predictors of prolonged survival. Both studies identified a dominant cluster of genes for type 1 immunity, which was correlated with low frequencies of tumor recurrences among CRC patients. These patients also had higher frequencies of CD3+, CD8+, CD45RO+ TIL than did patients whose tumors had recurred. Salama et al. [57] reported that FoxP3+ Treg density in normal and tumor tissue had stronger prognostic significance in CRC compared with CD8+ and CD45RO+ lymphocytes. In any case, the results from these studies suggested that TIL, as mediators of adaptive immune responses within the tumor, represent a predictive marker for survival in CRC. In another study, Tosolini et al. [40] identified expression of genes for T-lymphocyte subpopulations in frozen tumor samples from CRC patients. They reported that patients with high expression of a Th17 gene cluster (IL-17A, RORgt) had poor prognosis, whereas high expression of a type 1 immunity gene cluster (various genes also including those coding for granzyme B, IL-27, CD8 and IFN-g) was associated with significantly enhanced disease-free survival. Numerous studies have established that the presence of TIL represents a predictive as well as prognostic biomarker in patients with cancer. Although different populations of lymphocytes were studied and different methods were used to assess the presence of TIL, several studies have demonstrated a strong association between high TIL numbers with disease outcome. The role of TIL as a predictive biomarker may increase with the introduction of new agents into therapy targeting key molecules in molecular pathways. The study of pathways underlying the mechanism of action of TIL offers unique insights into the role of the immune response in malignancy and in response to therapy providing ample evidence 51

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supporting the significance of the host antitumor response as one of the principal factors determining the outcome of neoplastic disease. It should also be considered that the characteristics of tumor cells may influence the potential of TIL-mediated immune responses to serve as useful biomarkers of prognosis.


Immune measures in peripheral blood

The development of a therapeutic cancer vaccine in the adjuvant setting aims to prevent disease recurrence through the reduction or even elimination of tumor micrometastases, given that in the majority of cases the primary tumor has been removed and patients have completed post-surgery standard chemotherapies. In more advanced stages (i.e., metastasis), cancer vaccines aim to control further disease progression. Therapeutic immunization against cancer utilizing tumorpeptide-specific vaccines attempts to directly stimulate both CD4+ Th1 and CD8+ T cells [58,59] that would be primed by dendritic cells in the lymph nodes. The vaccine-induced antigen-specific T cells would then traffic to tumor distal metastases, secreting the appropriate type I cytokines, to begin reversing a potential local Th2 phenotype to Th1, while also causing tumor lysis [60]. The ability to achieve this reversal would be dependent on the potency of the vaccine to elicit high levels of a type 1 immune environment in the periphery with CD4+ Th1 and CD8+ T cells capable of homing to the cancer site. Thus, the numbers and functions (Th1 vs Th2) of circulating T lymphocytes in cancer patients during and after immunotherapies have also been analyzed as potential biomarkers [60,58]. Assays to assess such tumor peptide-specific responses include MHC-peptide tetramer staining, T-cell proliferation, cytotoxicity assays, ELISPOT assays, intracellular staining for cytokines and so on [59,61]. Quantitation of Th1 versus Th2 cell subsets in peripheral blood has been widely used in an effort to validate surrogates for clinical outcome. In this regard, there is controversy in the literature with studies demonstrating correlations between the levels of vaccine-specific T-cell responses and clinical benefit, whereas others failed to show such correlations [6,60,58]. The most obvious explanations for this are: vaccine-specific memory T cells, either central or effector, are sequestered at draining lymph nodes or tissues, respectively, and therefore not circulating at the instance the blood is collected and the T-cell responses measured are not relevant to antitumor immunity. Another practical reason which could account for the lack of correlations between immunological and clinical results, thus rendering some of the above listed bioassays inappropriate to function as surrogates for clinical responses, is the significant variability in results among laboratories participating in multicenter trials. This thwarted data reproducibility and prevented meaningful comparisons among studies [6,15,16]. Careful review of these assays will be essential in order to obtain reproducible results, which can contribute to the establishment of cellular immune responses as meaningful biomarkers for immunotherapy trials thus enabling reliable correlations with clinical outcomes. Another interesting issue which should be addressed 52

when performing immunologic measurements in peripheral blood, especially in advanced disease with significant tumor volume, is the epitope spreading phenomenon during which T cells respond to multiple tumor-antigens, which are not included in the vaccine formulation. Such a situation could result from immunotherapy-induced tumor lysis and endogenous priming with new tumor-derived antigens [62]. This would suggest that immunological monitoring detecting T lymphocytes specific for the vaccine-included epitope(s) would not represent a true biomarker and will produce false correlations with clinical outcome. Nevertheless, epitope spreading itself in some studies including patients with metastatic melanoma has been demonstrated to represent a biomarker and to play an important role for clinical responses to immunotherapy [63–65]. In a limited number of metastatic renal cell carcinoma patients, epitope spreading also appeared to be a biomarker of clinical response [66]. Epitope spreading was also reported in patients with HER-2/neu overexpressing breast, ovarian or NSCLC, who were vaccinated with peptides derived from Th epitopes, also encompassing cytotoxic epitopes, of the HER-2/neu protein admixed with granulocytemacrophage colony-stimulating factor [7]. The AE37 paradigm

When selecting a bioassay to detect vaccine-specific T cells acting as a biomarker, it is important that this assay not only detect levels of this particular biomarker as a result of induction by the vaccine during immunotherapy, but also before initiation of immunotherapy, as pre-existing immunity, so as to be able to assess its utility as a prognostic factor as well. Postimmunotherapy analyses are also required to assess long-term antitumor immune memory and to confirm its predictive role, when detected during treatment. To date, IFN-g immunity and the DTH reaction are widely used to assess vaccineinduced immunological responses in vitro and in vivo, respectively. Both types of responses are consistent with a type 1 immunity, which defines the primary mode by which cancer can be identified and destroyed by the immune system [40,60,67,68]. In contrast, TGF-b supports a type 2 immunity which suppresses type 1 responses, thus preventing the elaboration of antitumor effectors [69]. In our recent Phase I trial [5], we demonstrated that the peptide HER2(776–790) chemically linked to a tetrapeptide from the invariant chain of MHC class II molecules (Ii-key/HER-2(776–790) hybrid peptide or AE37) is safe and induces HER-2/neu-specific immunity measured by increased DTH and IFN-g responses in a heterogeneous population of patients with HER-2/neu+ prostate cancer. Preceding studies from our laboratory demonstrated that AE37 induces more potent immunologic responses both in vitro and in vivo compared with the non-modified HER-2(776–790) peptide (AE36) [70,71]. In the same clinical trial, we showed that patients who received an AE37 booster developed long-term immunity, which was associated with clinical benefit [4]. By retrospectively analyzing our data from immunological determinations before, during and after a primary series of vaccinations with AE37, as well as after one AE37 booster injection, we Expert Rev. Mol. Diagn. 15(1), (2015)


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observed the relationship between immunological parameters and clinical outcome of our patients. Interestingly, pre-existing levels of plasma TGF-b and frequencies of IFN-g-producing vaccine-specific T cells could predict immunological responses during treatment, and even after a 4-year assessment (long-term memory); in addition, they had a prognostic and/or predictive role for OS [4,72]. Thus, patients with pre-existent INF-g immunity developed positive DTH reactions after primary vaccinations and booster. Moreover, we could detect a direct correlation between INF-g production and DTH reactions in response to vaccine challenge in our vaccinated patients. These patients also had increased OS. In contrast, we found that preexisting high TGF-b levels were correlated with shorter patients’ OS as well as decreased IFN-g and DTH responses (these results are illustrated in FIGURE 1). Based on the inverse relation between pre-existing TGF-b and INF-g immunity, we may suggest that expression levels of TGF-b, if low, may positively regulate patients’ type 1 immune status. This in turn could be decisive not only for enabling the generation of robust immunity during active immunotherapies, but also for improving patients’ benefit from standard therapies. In such a case, standard therapies could act synergistically with endogenous antitumor immunity producing measurable clinical benefits in addition to extending survival. Thus, less suppressed spontaneous immunity along with previous standard therapies may significantly contribute to patients’ survival benefit in combination with the immunity elicited by the AE37 vaccine. Expert commentary

The question of whether and how the host immune system influences cancer development has been debated for decades. While studies in animal models of cancer strongly support the role of antitumor immunity in cancer development, progression and therapy, evidence from human clinical trials is not clear or straightforward. Immune tolerance to tumor (self) antigens and tumor-derived and/or tumor-induced immune suppression, which provide obstacles to successful immunotherapy in humans, mostly account for this discrepancy. In addition, it seems that the mechanisms governing immune tolerance against tumor antigens are incomplete, and that in many instances, autoreactive T-cell precursors can escape deletion or immune suppression and that when activated appropriately, potent autoimmune or antitumor responses can be generated. Spontaneous tumor responses have been reported in melanoma and renal cell cancer, demonstrating that endogenous antitumor natural immunity in some instances may dominate over tumor immuno-inhibitory effects. Accordingly, measurements of immune suppression and of immune competence against the tumor may be used as biomarkers for response to treatment and survival. Thus, the levels of tumor-induced suppression and those of soluble mediators favoring the generation of type 2 immunity on the one hand, and the magnitude of antitumor immune responses on the other, may represent two large areas for detecting prognostic biomarkers at diagnosis, before the onset of any kind of treatment. The balance between informahealthcare.com

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immune suppression and endogenous antitumor immunity may exist long before the time of disease diagnosis. Thus, it is likely that a less suppressed endogenous antitumor immunity may effectively synergize with standard treatments for improved clinical efficacy. Moreover, pre-existing levels of suppression or antitumor immunity may have a key role for tipping the balance in favor of reduced suppression and for restoration of antitumor immune responses, both of which may take place during or after therapies. Given the plethora of quantitative assessments for suppressor circuits and for immunological responses against the tumor, the dilemma will be to determine which biomarkers have the greatest potential to be explored as accurate correlates to clinical response. The ideal immunologic biomarker would be one that most closely mirrors the effect of naturally or induced immunity against cancer. Assessment of adaptive immunity at the tumor site may be the best source of intermediate biomarkers of immune suppression as well as of biomarkers for therapy-induced immune recovery, both of which could more precisely predict disease outcome. However, one should consider that tumor sites are often inaccessible for sampling for clinical trial purposes. Nevertheless, when accessible, TIL accumulations have been linked to improved patient outcome and TIL are recognized as effectors of antitumor immune responses. We should consider that in addition to their phenotypic characterization, TIL should also be functionally identified. The inconsistent reports in the literature about the role of TIL in the control of cancer progression in humans seem to result from the fact that phenotypic rather than functional attributes of these cells are used for their identification and characterization. Functions of TIL are difficult to assess in vitro because of the necessity for their isolation from tissues and purification, which are labor intensive and require large tumor specimens. For these reasons, studies of TIL, including Treg subpopulations, have been largely confined to in situ examinations generally involving immunohistochemistry. The recently proposed immune classification of patients with colon cancer based on the density and immune cell location within the tumor as defined by immunohistochemistry and tissue arrays seems indeed to have a prognostic value that is superior to the standard TNM classification [41]. Taking into consideration that this immune classification theoretically defines the strength of anticancer immune responses, it is imperative to conduct studies to better characterize T-cell subsets present in tumor tissues by analysis of the surface markers as well as cytokine profile and function, thus providing a broader basis for the development of more reliable prognostic factors. Another limitation is the uncertainty, if and to which extent immune cells within the tumor microenvironment are involved in the control of tumor dissemination and prevention of metastases. By assuming that this may be the case, we should likely search for putative factors which may impede the potential of TIL to control tumor growth and dissemination. If local immune suppression or deficient T-cell activation (e.g., due to limited tumor antigen expression) are the main factors limiting TIL action, why would there be a correlation between the presence 53

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Figure1. The AE37 paradigm for identifying the role of TGF-b, IFN-g and DTH as prognostic/predictive biomarkers. In (A), the vaccination schedule and time-points of blood sampling for immunomonitoring, are shown. (B), ‘Pre-existing’, refers to circulating TGF-b levels measured before vaccinations, at month 0. ‘Pre-existing/induced’, refers to circulating frequencies of vaccine-specific IFN-g producing T cells before vaccinations at month 0 (i.e., pre-existing), and during vaccinations (i.e., induced). For details see Perez et al. [4]. DTH: Delayed-type hypersensitivity; LT: Long term; LTB: Long-term booster (i.e., 1 month post-LT); LTI: Long-term immunity (i.e., 36 months post-LTB); OS: Overall survival.

of TIL and a good prognosis? However, because there is now widespread evidence that such a correlation does exist, we may propose that the inflammatory context in which the immune contexture in human tumors is developed along with factors regulating tumor vascularization as well as expression of adhesion molecules and T-cell-attracting chemokines, orchestrate coordinated antitumor immunity within the tumors. If so, we tend to believe that spontaneous T-cell responses against the tumor, positively influenced by the immune contexture, indicate a better prognosis, provided that once these have been initiated during tumor evolution they should persist during the more advanced tumor stages. Thus, improvement of the immune score would result in better clinical outcome. There are many methods available to do so, by eliciting immunity in cancer patients and potentially modulating the tumor immune environment to synergize with standard therapies. For instance, it has been shown that certain chemotherapies, but also monoclonal antibodies targeting oncoproteins and interrupting oncogenic signalling, may have potent immune-stimulating effects further enhancing the endogenous immune response [73–76]. Further immune boosting might be achieved via active immunization and immune checkpoint inhibitors. Finally, novel 54

checkpoint blockade approaches could be used to ensure the immune response will evolve to complete eradication or stabilization of tumor [73]. In addition to scoring T cells at tumor sites, much effort has been placed on developing assays that will quantitate type 1 T-cell immunity in the peripheral blood generated in the context of clinical trials of cancer immunotherapy. The frequency and functions of T cells circulating in the peripheral blood of cancer patients have been examined as potential biomarkers. The development of tumor-specific IFN-g ELISPOT responses in peripheral blood has been demonstrated to predict which patients were likely to benefit clinically from active immunotherapies in various types of malignancies, including melanoma, prostate and breast cancer [26]. Immunological memory, measured by the persistence of T cells in the circulation producing IFN-g, has also been associated with prolonged survival and epitope spreading, which by itself has been occasionally found to correlate with good prognosis [26]. One approach to accumulate memory T cells in vivo is to provide a local antigenic challenge by means of a DTH reaction. Measuring the degree of induration on DTH has frequently been used to assess vaccine-related immune responses. A DTH reaction provides Expert Rev. Mol. Diagn. 15(1), (2015)


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information on the in vivo immune response induced by vaccination, and the appearance of DTH has been suggested to correlate with the clinical outcome. The presence of antigenspecific T cells in DTH biopsies has also been correlated with clinical outcome [77,78]. Now that several forms of cancer immunotherapy are achieving measureable clinical benefit, perhaps blood-based immune biomarkers that are predictors of clinical benefit can be defined. In summary, patients having their tumors inflamed by tumor peptide-specific CD8+ TIL may benefit from immunotherapies. An inflammatory milieu consisting mainly of chemokines and cytokines is capable of recruiting immune cells into the tumor microenvironment and eliciting immune cell-mediated antitumor effects. In contrast, non-inflamed tumors may predict poor clinical outcome, most likely due to the absence of chemokines and other signals which are required for T-cell infiltration into tumors. Thus, the identification of patients who may benefit from immunotherapies before treatment is an important issue, because personalized therapies may maximize clinical benefit while minimizing adverse effects from ineffective therapy. Given that most of the studies have focused on delineating important prognostic immune biomarkers in cancer tissue, presently it is not known whether these same biomarkers can be measured in the peripheral blood of cancer patients. Our retrospective analyses from the AE37 clinical study suggest that this may be the case, although it should be emphasized that at this point they are limited to speculation, since no final conclusions can be drawn due to the relatively small number of patients, the non-randomized trial design and the heterogeneity of the sampled patient population. Developing assays that will quantitate type 1 T-cell immunity in the peripheral blood generated in the context of clinical trials of cancer immunotherapy is an upcoming issue. Peripheral blood drawn at appropriate time points, before, during and after treatment, may be a better choice for biomarker identification due to the convenience of collection and analysis. Nevertheless, a prerequisite for defining blood-based immune biomarkers predicting clinical outcome is to have trials of cancer immunotherapy with measureable clinical benefit. Five-year view

The explication of clinical benefits achieved after immunotherapies in terms of a uniform pattern of biomarkers in cancer, at least presently, does not consider differences in the malignant phenotypes and biological behaviors of the tumor itself and therefore may challenge the desired hypothesis of a widely applicable immune signature (gene or cellular) in cancer patients. Even so, considering that the immune system through a selection process shapes the immunogenicity and tumorigenicity of cancer cells, as highlighted by the immunoediting theory [79], then, we may propose that this tumor cell selection process should be subjected to uniform immunological pathways, thus providing a common biomarker profile as a prior condition for tumor progression. Given the plasticity of the immune system, immunological biomarkers may occasionally informahealthcare.com

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have contradictory functions. Accordingly, the assumed uniform pattern of immunological pathways during the immunoediting process may be in conflict with the plasticity of the functional program of immune lymphocytes and their soluble mediators. Nevertheless, this could be explained as a uniform immunological selection process, at the later stages of equilibrium adapted to the pattern of genetic modifications allowing progress to the escape phase. Therefore, it is essential that the pattern of biological biomarkers have a strong prognostic and/or predictive implication and hence be connected with the later stages of cancer. Looking at the other side of the coin, we should ask how a consistent biomarker profile should comply with the genetic heterogeneity and, as a result of it, with the biological diversity of cancer. Given the abundance of clinical reports demonstrating common immunological pathways in patients with different types of cancer, we could propose that indeed, the individual tumor cell profile may determine the time frame for reaching the end-stage selection process during immunoediting (late equilibrium?). Once this stage is reached, the ‘shaped’ tumor cells will share common characteristics enabling the generation of consistent biomarker patterns as a result of uniform late-stage immunological selection maneuvers. At this point, we would like to introduce the term ‘countershape’ to denote the ability of the ‘shaped’ tumor cells to induce uniform mechanistic patterns of immunological responses (i.e., to ‘shape’ the host’s endogenous antitumor immunity). All the above emphasize the importance of having reliable and reproducible results from clinical trials consistent with uniform pathways of the anticancer immunologic response, as described by the immunoediting process mostly in preclinical tumor models. This translational process will provide a solid platform for exploring prognostic and therapeutic perspectives and establishing the corresponding biomarkers. The findings so far support the prospective validation of prognostic/predictive immune signatures in Phase III trials. The data from these trials will not only shed new light into the relationship between immunity and cancer, but they will also provide insights into the management of neoplastic disease. Studying the conditions favoring development of endogenous immunity against the tumor and defining appropriate biomarkers controlling interactions between tumor cells, the immune response and the tumor microenvironment, could accelerate the development of the most efficient treatments that aim to establish a long disease-free period and, ultimately, good overall survival. In the future, data from Phase III studies will considerably help to confirm mechanistic pathways and biomarkers which are emerging from preclinical models and early clinical trials. Moreover, the application of high-throughput molecular profiling approaches in cancer immunotherapy will be imperative to support the discovery of new therapeutic treatments. Application of ‘omics’ platforms such as gene and protein microarrays, mass spectrometry and deep sequencing will definitely serve as complementary approaches to conventional immunologic assays (i.e., ELISPOT, multicolor flow cytometry, etc.), for the detection and validation of immunologic 55


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biomarkers. As new findings have considerably advanced our understanding on the role of pre-existing antitumor responses as a platform for developing more successful therapeutic treatments in cancer, new therapies will be tested in clinical studies and new technologies for addressing the unique needs in immunotherapy will emerge. We, therefore, believe that it will be quite useful to bring together expertise from various scientific fields including those of cancer molecular biology, immunology and cancer immunotherapy, along with those of computational biology and statistics, to integrate and analyze the clinical, immunological and ‘omics’ data generated from multiple clinical trials. Such multidisciplinary consortia will be

essential to gain insight into mechanistic pathways and to identify the most suitable biomarkers that can be utilized in the clinical praxis for the benefit of cancer patients under treatment with immunotherapies. Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties. No writing assistance was utilized in the production of this manuscript.

Key issues • Therapeutic cancer vaccination comprises a series of immune reactions to either induce or activate T cells, thus promoting T-cell infiltration into the tumor, followed by tumor regression. • Identifying immunologic biomarkers would help not only guide the development of immunotherapy trials, but also act as surrogates for clinical benefit. • For improving clinical outcome, further to increasing vaccine potency and minimizing treatment-related toxicities, it is imperative to recognize prognostic/predictive biomarkers of clinical benefit. • Intratumoral immune measures may serve as prognostic and predictive biomarkers for overall survival and response to treatment, respectively. • The heterogeneity of tumors resulting from the immunoediting process, but also obstacles in the standardization of assays measuring cellular immune responses, contribute to inconsistencies in the identification of uniform biomarker signatures. • The numbers and functions of circulating T lymphocytes in cancer patients during and after immunotherapies have been also analyzed as potential biomarkers. • The AE37 vaccine paradigm proposes considering pre-existing systemic TGF-b levels and IFN-g immunity to the vaccine both as prognostic for overall survival and predictive factors for responses to vaccination. Delayed-type hypersensitivity reactions to the vaccine have also been found to correlate with clinical benefit. • The tumor cell selection process subjected to uniform immunological pathways during the later stages of immunoediting may provide a common biomarker profile as a prerequisite for tumor progression paving the way for therapeutic options. • Prospective validation of biomarker signatures defined in small-scale clinical trials in large Phase III studies is absolutely necessary.

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