Delayed disease progression after allogeneic cell vaccination in hormone-resistant prostate cancer and correlation with immunologic variables

Cancer Vaccines in the Immunotherapy Era: Promise and Potential

Therapeutic vaccines are a promising alternative for active immunotherapy for different types of cancers. Therapeutic cancer vaccines aim to prevent immune system responses that are not targeted at the tumors only, but also boost the anti-tumor immunity and promote regression or eradication of the malignancy without, or with minimal, adverse events. Clinical trial data have pushed the development of cancer vaccines forward, and the US Food and Drug Administration authorized the first therapeutic cancer vaccine. In the present review, we discuss the various types of cancer vaccines and different approaches for the development of therapeutic cancer vaccines, along with the current state of knowledge and future prospects. We also discuss how tumor-induced immune suppression limits the effectiveness of therapeutic vaccinations, and strategies to overcome this barrier to design efficacious, long-lasting anti-tumor immune responses in the generation of vaccines.

Potential of Personalized Dendritic Cell-Based Immunohybridoma Vaccines to Treat Prostate Cancer

Prostate cancer (PCa) is the most commonly diagnosed cancer and the second most common cause of death due to cancer. About 30% of patients with PCa who have been castrated develop a castration-resistant form of the disease (CRPC), which is incurable. In the last decade, new treatments that control the disease have emerged, slowing progression and spread and prolonging survival while maintaining the quality of life. These include immunotherapies; however, we do not yet know the optimal combination and sequence of these therapies with the standard ones. All therapies are not always suitable for every patient due to co-morbidities or adverse effects of therapies or both, so there is an urgent need for further work on new therapeutic options. Advances in cancer immunotherapy with an immune checkpoint inhibition mechanism (e.g., ipilimumab, an anti-CTLA-4 inhibitor) have not shown a survival benefit in patients with CRPC. Other immunological approaches have also not given clear results, which has indirectly prevented breakthrough for this type of therapeutic strategy into clinical use. Currently, the only approved form of immunotherapy for patients with CRPC is a cell-based medicine, but it is only available to patients in some parts of the world. Based on what was gained from recently completed clinical research on immunotherapy with dendritic cell-based immunohybridomas, the aHyC dendritic cell vaccine for patients with CRPC, we highlight the current status and possible alternatives that should be considered in the future.

Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy

The rapid development of artificial intelligence (AI) technologies in the context of the vast amount of collectable data obtained from high-throughput sequencing has led to an unprecedented understanding of cancer and accelerated the advent of a new era of clinical oncology with a tone of precision treatment and personalized medicine. However, the gains achieved by a variety of AI models in clinical oncology practice are far from what one would expect, and in particular, there are still many uncertainties in the selection of clinical treatment options that pose significant challenges to the application of AI in clinical oncology. In this review, we summarize emerging approaches, relevant datasets and open-source software of AI and show how to integrate them to address problems from clinical oncology and cancer research. We focus on the principles and procedures for identifying different antitumor strategies with the assistance of AI, including targeted cancer therapy, conventional cancer therapy, and cancer immunotherapy. In addition, we also highlight the current challenges and directions of AI in clinical oncology translation. Overall, we hope this article will provide researchers and clinicians with a deeper understanding of the role and implications of AI in precision cancer therapy, and help AI move more quickly into accepted cancer guidelines.

Machine Learning for Endometrial Cancer Prediction and Prognostication

Endometrial cancer (EC) is a prevalent uterine cancer that remains a major contributor to cancer-associated morbidity and mortality. EC diagnosed at advanced stages shows a poor therapeutic response. The clinically utilized EC diagnostic approaches are costly, time-consuming, and are not readily available to all patients. The rapid growth in computational biology has enticed substantial research attention from both data scientists and oncologists, leading to the development of rapid and cost-effective computer-aided cancer surveillance systems. Machine learning (ML), a subcategory of artificial intelligence, provides opportunities for drug discovery, early cancer diagnosis, effective treatment, and choice of treatment modalities. The application of ML approaches in EC diagnosis, therapies, and prognosis may be particularly relevant. Considering the significance of customized treatment and the growing trend of using ML approaches in cancer prediction and monitoring, a critical survey of ML utility in EC may provide impetus research in EC and assist oncologists, molecular biologists, biomedical engineers, and bioinformaticians to further collaborative research in EC. In this review, an overview of EC along with risk factors and diagnostic methods is discussed, followed by a comprehensive analysis of the potential ML modalities for prevention, screening, detection, and prognosis of EC patients.

Cancer Vaccines: Promising Therapeutics or an Unattainable Dream

The advent of cancer immunotherapy has revolutionized the field of cancer treatment and offers cancer patients new hope. Although this therapy has proved highly successful for some patients, its efficacy is not all encompassing and several cancer types do not respond. Cancer vaccines offer an alternate approach to promote anti-tumor immunity that differ in their mode of action from antibody-based therapies. Cancer vaccines serve to balance the equilibrium of the crosstalk between the tumor cells and the host immune system. Recent advances in understanding the nature of tumor-mediated tolerogenicity and antigen presentation has aided in the identification of tumor antigens that have the potential to enhance anti-tumor immunity. Cancer vaccines can either be prophylactic (preventative) or therapeutic (curative). An exciting option for therapeutic vaccines is the emergence of personalized vaccines, which are tailor-made and specific for tumor type and individual patient. This review summarizes the current standing of the most promising vaccine strategies with respect to their development and clinical efficacy. We also discuss prospects for future development of stem cell-based prophylactic vaccines.

Standardization of esophageal adenocarcinoma in vitro model and its applicability for model drug testing

FLO-1 cell line represents an important tool in esophageal adenocarcinoma (EAC) research as a verified and authentic cell line to study the disease pathophysiology and antitumor drug screenings. Since in vitro characteristics of cells depend on the microenvironment and culturing conditions, we performed a thorough characterization of the FLO-1 cell line under different culturing conditions with the aim of (1) examining the effect of serum-free growth medium and air–liquid interface (A–L) culturing, which better reflect physiological conditions in vivo and (2) investigating the differentiation potential of FLO-1 cells to mimic the properties of the in vivo esophageal epithelium. Our study shows that the composition of the media influenced the morphological, ultrastructural and molecular characteristics of FLO-1 cells, such as the expression of junctional proteins. Importantly, FLO-1 cells formed spheres at the A–L interface, recapitulating key elements of tumors in the esophageal tube, i.e., direct contact with the gas phase and three-dimensional architecture. On the other hand, FLO-1 models exhibited high permeability to model drugs and zero permeability markers, and low transepithelial resistance, and therefore poorly mimicked normal esophageal epithelium. In conclusion, the identified effect of culture conditions on the characteristics of FLO-1 cells should be considered for standardization, data reproducibility and validity of the in vitro EAC model. Moreover, the sphere-forming ability of FLO-1 cells at the A–L interface should be considered in EAC tumor biology and anticancer drug studies as a reliable and straightforward model with the potential to increase the predictive efficiency of the current in vitro approaches.

Computational Approaches in Theranostics: Mining and Predicting Cancer Data

The ability to understand the complexity of cancer-related data has been prompted by the applications of (1) computer and data sciences, including data mining, predictive analytics, machine learning, and artificial intelligence, and (2) advances in imaging technology and probe development. Computational modelling and simulation are systematic and cost-effective tools able to identify important temporal/spatial patterns (and relationships), characterize distinct molecular features of cancer states, and address other relevant aspects, including tumor detection and heterogeneity, progression and metastasis, and drug resistance. These approaches have provided invaluable insights for improving the experimental design of therapeutic delivery systems and for increasing the translational value of the results obtained from early and preclinical studies. The big question is: Could cancer theranostics be determined and controlled in silico? This review describes the recent progress in the development of computational models and methods used to facilitate research on the molecular basis of cancer and on the respective diagnosis and optimized treatment, with particular emphasis on the design and optimization of theranostic systems. The current role of computational approaches is providing innovative, incremental, and complementary data-driven solutions for the prediction, simplification, and characterization of cancer and intrinsic mechanisms, and to promote new data-intensive, accurate diagnostics and therapeutics.

Improving Cancer Vaccine Efficiency by Nanomedicine

Cancer vaccines, which have been widely investigated in the past few decades, are one of the most attractive strategies for cancer immunotherapy. Through the precise delivery of antigens and adjuvants to lymphoid organs or lymphocytes via nanotechnology, innate and adaptive immunity can be boosted to prevent the growth and relapse of malignant tumors. Indeed, nanomedicine offers great opportunities to improve the efficiency of vaccines. Various functional platforms are used to deliver small molecules, peptides, nucleic acids, and even whole cell antigens to the target area of interest, achieving enhanced antitumor immunity and durable therapeutic benefits. Herein, the recent progress in cancer vaccines based on nanotechnology is summarized. Novel platforms used for delivering tumor antigens, promoting adjuvant functions, and combining other therapeutic strategies are discussed. Moreover, possible striving directions and major challenges of nanomedicine for vaccination are also reviewed.

Prospective Immunophenotyping of CD8+ T Cells and Associated Clinical Outcomes of Patients With Oligometastatic Prostate Cancer Treated With Metastasis-Directed SBRT

PURPOSE

This study examined the effects of metastasis-directed stereotactic body radiation therapy (mdSBRT) on CD8⁺ T-cell subpopulations and correlated post-mdSBRT immunophenotypic responses with clinical outcomes in patients with oligometastatic prostate cancer (OPCa).

METHODS AND MATERIALS

Peripheral blood mononuclear cells were prospectively isolated from 37 patients with OPCa (≤3 metastases) who were treated with mdSBRT. Immunophenotyping identified circulating CD8⁺ T-cell subpopulations, including tumor-reactive (T_TR), effector memory, central memory (T_CM), effector, and naïve T cells from samples collected before and after mdSBRT. Univariate Cox proportional hazards regression was used to assess whether changes in these T-cell subpopulations were potential risk factors for death and/or progression. The Kaplan-Meier method was used for survival. Cumulative incidence for progression and new distant metastasis weas estimated, considering death as a competing risk.

RESULTS

Median follow-up was 39 months (interquartile range, 34-43). Overall survival at 3 years was 78.2%. Cumulative incidence for local progression and new distant metastasis at 3 years was 16.5% and 67.6%, respectively. Between baseline and day 14 after mdSBRT, an increase in the T_CM cell subpopulation was associated with the risk of death (hazard ratio, 1.22 [95% confidence interval, 1.02-1.47]; P = .033), and an increase in the T_TR cell subpopulation was protective against the risk of local progression (hazard ratio, 0.80 [95% confidence interval, 0.65-0.98]; P = .032).

CONCLUSIONS

An increase in the T_TR cell subpopulation was protective against the risk of disease progression, and an increase in the T_CM cell subpopulation was associated with the risk of death in patients with OPCa treated with mdSBRT. Disease control may be further improved by better understanding the CD8⁺ T-cell subpopulations and by enhancing their antitumor effect.

Methods for improving the immunogenicity and efficacy of cancer vaccines

INTRODUCTION

Cancer vaccines represent one of the oldest immunotherapy strategies. A variety of tumor-associated antigens have been exploited to investigate their immunogenicity as well as multiple strategies for vaccine administration. These efforts have led to the development of several clinical trials in tumors with different histological origins to test the clinical efficacy of cancer vaccines. However, suboptimal clinical results have been reported mainly due to the lack of optimized strategies to induce strong and sustained systemic tumor antigen-specific immune responses.

AREAS COVERED

We provide an overview of different types of cancer vaccines that have been developed and used in the context of clinical studies. Moreover, we review different preclinical and clinical strategies pursued to enhance the immunogenicity, stability, and targeting at tumor site of cancer vaccines.

EXPERT OPINION

Additional and appropriate preclinical studies are warranted to optimize the immunogenicity and delivery of cancer vaccines. The appropriate choice of target antigens is challenging; however, the exploitation of neoantigens generated from somatic mutations of tumor cells represents a promising approach to target highly immunogenic tumor-specific antigens. Remarkably, the investigation of the combination of cancer vaccines with immunomodulating agents able to skew the tumor microenvironment from immunosuppressive to immunostimulating will dramatically improve their clinical efficacy.

Multidimensional Analysis Integrating Human T-Cell Signatures in Lymphatic Tissues with Sex of Humanized Mice for Prediction of Responses after Dendritic Cell Immunization

Mice transplanted with human cord blood-derived hematopoietic stem cells (HSCs) became a powerful experimental tool for studying the heterogeneity of human immune reconstitution and immune responses in vivo. Yet, analyses of human T cell maturation in humanized models have been hampered by an overall low immune reactivity and lack of methods to define predictive markers of responsiveness. Long-lived human lentiviral induced dendritic cells expressing the cytomegalovirus pp65 protein (iDCpp65) promoted the development of pp65-specific human CD8⁺ T cell responses in NOD.Cg-Rag1^tm1Mom-Il2rγ^tm1Wj humanized mice through the presentation of immune-dominant antigenic epitopes (signal 1), expression of co-stimulatory molecules (signal 2), and inflammatory cytokines (signal 3). We exploited this validated system to evaluate the effects of mouse sex in the dynamics of T cell homing and maturation status in thymus, blood, bone marrow, spleen, and lymph nodes. Statistical analyses of cell relative frequencies and absolute numbers demonstrated higher CD8⁺ memory T cell reactivity in spleen and lymph nodes of immunized female mice. In order to understand to which extent the multidimensional relation between organ-specific markers predicted the immunization status, the immunophenotypic profiles of individual mice were used to train an artificial neural network designed to discriminate immunized and non-immunized mice. The highest accuracy of immune reactivity prediction could be obtained from lymph node markers of female mice (77.3%). Principal component analyses further identified clusters of markers best suited to describe the heterogeneity of immunization responses in vivo. A correlation analysis of these markers reflected a tissue-specific impact of immunization. This allowed for an organ-resolved characterization of the immunization status of individual mice based on the identified set of markers. This new modality of multidimensional analyses can be used as a framework for defining minimal but predictive signatures of human immune responses in mice and suggests critical markers to characterize responses to immunization after HSC transplantation.

Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Mobilan: a recombinant adenovirus carrying Toll-like receptor 5 self-activating cassette for cancer immunotherapy

Toll-like receptor 5 (TLR5) is considered an attractive target for anticancer immunotherapy. TLR5 agonists, bacterial flagellin and engineered flagellin derivatives, have been shown to have potent antitumor and metastasis-suppressive effects in multiple animal models and to be safe in both animals and humans. Anticancer efficacy of TLR5 agonists stems from TLR5-dependent activation of nuclear factor-κB (NF-κB) that mediates innate and adaptive antitumor immune responses. To extend application of TLR5-targeted anticancer immunotherapy to tumors that do not naturally express TLR5, we created an adenovirus-based vector for intratumor delivery, named Mobilan that drives expression of self-activating TLR5 signaling cassette comprising of human TLR5 and a secreted derivative of Salmonella flagellin structurally analogous to a clinical stage TLR5 agonist, entolimod. Co-expression of TLR5 receptor and agonist in Mobilan-infected cells established an autocrine/paracrine TLR5 signaling loop resulting in constitutive activation of NF-κB both in vitro and in vivo. Injection of Mobilan into primary tumors of the prostate cancer-prone transgenic adenocarcinoma of the mouse prostate (TRAMP) mice resulted in a strong induction of multiple genes involved in inflammatory responses and mobilization of innate immune cells into the tumors including neutrophils and NK cells and suppressed tumor progression. Intratumoral injection of Mobilan into subcutaneously growing syngeneic prostate tumors in immunocompetent hosts improved animal survival after surgical resection of the tumors, by suppression of tumor metastasis. In addition, vaccination of mice with irradiated Mobilan-transduced prostate tumor cells protected mice against subsequent tumor challenge. These results provide proof-of-concept for Mobilan as a tool for antitumor vaccination that directs TLR5-mediated immune response toward cancer cells and does not require identification of tumor antigens.

Employing dynamical computational models for personalizing cancer immunotherapy

INTRODUCTION

Recently, cancer immunotherapy has shown considerable success, but due to the complexity of the immune-cancer interactions, clinical outcomes vary largely between patients. A possible approach to overcome this difficulty may be to develop new methodologies for personal predictions of therapy outcomes, by the integration of patient data with dynamical mathematical models of the drug-affected pathophysiological processes.

AREAS COVERED

This review unfolds the story of mathematical modeling in cancer immunotherapy, and examines the feasibility of using these models for immunotherapy personalization. The reviewed studies suggest that response to immunotherapy can be improved by patient-specific regimens, which can be worked out by personalized mathematical models. The studies further indicate that personalized models can be constructed and validated relatively early in treatment.

EXPERT OPINION

The suggested methodology has the potential to raise the overall efficacy of the developed immunotherapy. If implemented already during drug development it may increase the prospects of the technology being approved for clinical use. However, schedule personalization, per se, does not comply with the current, 'one size fits all,' paradigm of clinical trials. It is worthwhile considering adjustment of the current paradigm to involve personally tailored immunotherapy regimens.

The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

Prostate cancer (PC) is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

Asymptotic dynamics of some t-periodic one-dimensional model with application to prostate cancer immunotherapy

In the case of some specific cancers, immunotherapy is one of the possible treatments that can be considered. Our study is based on a mathematical model of patient-specific immunotherapy proposed in Kronik et al. (PLoS One 5(12):e15,482, 2010). This model was validated for clinical trials presented in Michael et al. (Clin Cancer Res 11(12):4469–4478, 2005). It consists of seven ordinary differential equations and its asymptotic dynamics can be described by some t-periodic one-dimensional dynamical system. In this paper we propose a generalised version of this t-periodic system and study the dynamics of the proposed model. We show that there are three possible types of the model behaviour: the solution either converges to zero, or diverges to infinity, or it is periodic. Moreover, the periodic solution is unique, and it divides the phase space into two sub-regions. The general results are applied to the PC specific case, which allow to derive conditions guaranteeing successful as well as unsuccessful treatment. The results indicate that a single vaccination is not sufficient to cure the cancer.

Effects of oxygen on the antigenic landscape of prostate cancer cells

Background

Use of allogeneic cancer cells-based immunotherapy for treatment of established prostate cancer (PCa) has only been marginally effective. One reason for failure could stem from the mismatch of antigenic signatures of vaccine cells and cancer in situ. Hence, it is possible that vaccine cells expressed antigens differently than tumor cells in situ. We hypothesized that cells grown in vitro at low oxygen tension (pO₂) provide a better antigen match to tumors in situ and could reveal a more relevant antigenic landscape than cells grown in atmospheric pO₂.

Methods

We tested this hypothesis by comparing PCa cells propagated at pO₂ = 2 kPa and 20 kPa. To identify potential tumor-associated antigens (TAAs), we prepared PCa cell lysates, resolved them by two-dimensional electrophoresis and immunoblotting using spontaneous antibodies from plasma derived from PCa patients and control subjects. Antibody-labeled spots were analyzed by MALDI-TOF mass spectrometry and validated by ELISA. We selected hypoxia-regulated HSP70 and hnRNP L and hypoxia-independent HSP60 and determined the frequency of plasma samples reacting with these molecules.

Results

Frequency of HSP60-reactive plasma was low in healthy controls [1.3 % (1/76)], while it was elevated in PCa patients [13.0 % (7/54); p < 0.05]. These data suggest a humoral immune response to HSP60 in PCa. Levels of autoantibodies to HSP70 did not differ from healthy controls [3.7 % (2/54)] in PCa patients [5.3 % (2/38)]. Similarly, hnRNP L autoantibodies did no differ between healthy controls [6.1 % (3/49)] and PCa patients [5.3 % (2/38)].

Conclusions

Overall our results suggest the value of hypoxia as a modifier of the cellular and antigenic landscape of PCa cells. By modifying the immune reactivity of PCa cells in culture, manipulation of pO₂ can be proposed as a new avenue for improving diagnosis, prognosis and immunotherapy for PCa.

Vaccines versus immunotherapy: overview of approaches in deciding between options

This review compares the optimal use of vaccines vs. other forms of immunotherapy, which includes cytokines, such as IL-2, monoclonal antibodies, such as the 'checkpoint inhibitors', against CTLA-4 and PD-1. The review includes both prophylactic and therapeutic vaccines using a variety of technologies. It is already established that vaccines can be enhanced by other immunotherapies, such as cytokines (IL-2) and there is scope for combining both of these with the 'checkpoint' antibodies. Moreover, both can be enhanced with other modalities, such as radiotherapy, ablative therapy and both high and low dose chemotherapies.

Personalizing immunotherapy: Balancing predictability and precision

Despite great expectations and research efforts, anticancer immunotherapy has not yet become a definitive cure. Perhaps, this is because past reductionist approaches were too simplistic for the patient-specific complex system of co-evolving tumor cells and host immunity. Recent efforts based on a systems-based approach promise improved clinical outcomes engendered by a dynamic modification of personalized therapeutic regimens.

Cancer vaccines: Looking to the future

These are exciting times for the field of cancer immunotherapy. Although the clinical efficacy of monoclonal antibodies has been demonstrated since the early 1990s, the therapeutic profile of other immunotherapeutic approaches-especially vaccines-has not yet been formally clarified. However, the recent success of several immunotherapeutic regimens in cancer patients has boosted the development of this treatment modality. These achievements stemmed from recent scientific advances demonstrating the tolerogenic nature of cancer and the fundamental role of the tumor immune microenvironment in the suppression of antitumor immunity. New immunotherapeutic strategies against cancer attempt to promote protective antitumor immunity while disrupting the immunoregulatory circuits that contribute to tumor tolerance. Cancer vaccines differ from other anticancer immunotherapeutics in that they initiate the dynamic process of activating the immune system so as to successfully re-establish a state of equilibrium between tumor cells and the host. This article reviews recent clinical trials involving several different cancer vaccines and describes some of the most promising immunotherapeutic approaches that harness antitumor T-cell responses. In addition, we describe strategies whereby cancer vaccines can be exploited in combination with other therapeutic approach to overcome-in a synergistic fashion-tumor immunoevasion. Finally, we discuss prospects for the future development of broad spectrum prophylactic anticancer vaccines.

Phase II trial of a GM-CSF-producing and CD40L-expressing bystander cell line combined with an allogeneic tumor cell-based vaccine for refractory lung adenocarcinoma

We created a vaccine in which irradiated allogeneic lung adenocarcinoma cells are combined with a bystander K562 cell line transfected with hCD40L and hGM-CSF. By recruiting and activating dendritic cells, we hypothesized that the vaccine would induce tumor regression in metastatic lung adenocarcinoma. Intradermal vaccine was given q14 days×3, followed by monthly ×3. Cyclophosphamide (300 mg/m IV) was administered before the first and fourth vaccines to deplete regulatory T cells. All-trans retinoic acid was given (150/mg/m/d) after the first and fourth vaccines to enhance dendritic cell differentiation. Twenty-four participants were accrued at a single institution from October 2006 to June 2008, with a median age 64 years and median of 4 previous lines of systemic therapy. A total of 101 vaccines were administered. Common toxicities were headache (54%) and site reaction (38%). No radiologic responses were observed. Median overall survival was 7.9 months and median progression-free survival was 1.7 months. Of 14 patients evaluable for immunological study, 5 had peptide-induced CD8 T-cell activation after vaccination. Overall, vaccine administration was feasible in an extensively pretreated population of metastatic lung cancer. Despite a suggestion of clinical activity in the subset with immune response, the trial did not meet the primary endpoint of inducing radiologic tumor regression.

Cellular immunotherapy using irradiated lung cancer cell vaccine co-expressing GM-CSF and IL-18 can induce significant antitumor effects

Background

Although the whole tumor cell vaccine can provide the best source of immunizing antigens, there is still a limitation that most tumors are not naturally immunogenic. Tumor cells genetically modified to secrete immune activating cytokines have been proved to be more immunogenic. IL-18 could augment proliferation of T cells and cytotoxicity of NK cells. GM-CSF could stimulate dendritic cells, macrophages and enhance presentation of tumor antigens. In our study, we used mouse GM-CSF combined with IL-18 to modify Lewis lung cancer LL/2, then investigated whether vaccination could suppress tumor growth and promote survival.

Methods

The Lewis lung cancer LL/2 was transfected with co-expressing mouse GM-CSF and IL-18 plasmid by cationic liposome, then irradiated with a sublethal dose X ray (100 Gy) to prepare vaccines. Mice were subcutaneously immunized with this inactivated vaccine and then inoculated with autologous LL/2 to estimate the antitumor efficacy.

Results

The studies reported here showed that LL/2 tumor cell vaccine modified by a co-expressing mouse GM-CSF and IL-18 plasmid could significantly inhibit tumor growth and increased survival of the mice bearing LL/2 tumor whether prophylactic or adoptive immunotherapy in vivo. A significant reduction of proliferation and increase of apoptosis were also observed in the tumor treated with vaccine of co-expressing GM-CSF and IL-18. The potent antitumor effect correlated with higher secretion levels of pro-inflammatory cytokines such as IL-18, GM-CSF, interferon-γ in serum, the proliferation of CD4⁺ IFN-γ⁺, CD8⁺ IFN-γ⁺ T lymphocytes in spleen and the infiltration of CD4⁺, CD8⁺ T in tumor. Furthermore, the mechanism of tumor-specific immune response was further proved by ⁵¹Cr cytotoxicity assay in vitro and depletion of CD4, CD8, NK immune cell subsets in vivo. The results suggested that the antitumor mechanism was mainly depended on CD4⁺, CD8⁺ T lymphocytes.

Conclusions

These results provide a new insight into therapeutic mechanisms of IL-18 plus GM-CSF modified tumor cell vaccine and provide a potential clinical cancer immunotherapeutic agent for improved antitumor immunity.

Allogeneic tumor cell vaccines: the promise and limitations in clinical trials

The high mortality rate associated with cancer and its resistance to conventional treatments such as radiation and chemotherapy has led to the investigation of a variety of anti-cancer immunotherapies. The development of novel immunotherapies has been bolstered by the discovery of tumor-associated antigens (TAAs), through gene sequencing and proteomics. One such immunotherapy employs established allogeneic human cancer cell lines to induce antitumor immunity in patients through TAA presentation. Allogeneic cancer immunotherapies are desirable in a clinical setting due to their ease of production and availability. This review aims to summarize clinical trials of allogeneic tumor immunotherapies in various cancer types. To date, clinical trials have shown limited success due potentially to extensive degrees of inter- and intra-tumoral heterogeneity found among cancer patients. However, these clinical results provide guidance for the rational design and creation of more effective allogeneic tumor immunotherapies for use as monotherapies or in combination with other therapies.

Prostate cancer vaccines

In 2010, the US FDA approved the first therapeutic cancer vaccine for the treatment of castration refractory prostate cancer - sipuleucel-T. Prostate cancer is an ideal model for cancer vaccine development based on the ready demonstration of humoral and cellular immunity to a range of cancer antigens as well as often slow progression which means that patients who are otherwise well may have a radiologically evaluable minor progression, after conventional treatment and can undergo vaccine therapy over sufficient periods of time, so as to allow the generation of a robust antitumor response. The association of prostate cancer with one of the few serum cancer biomarkers in general use has also allowed assessment of response and risk stratification of patients. In this review, we will examine key aspects of the evolution of prostate cancer vaccines, which provides an accurate prototype for other cancers, and the challenges we face.

Therapeutic cancer vaccines: why so few randomised phase III studies reflect the initial optimism of phase II studies

Immunotherapy is showing promise for the treatment of a range of tumours including prostate cancer, melanoma and non small-cell lung cancer. Phase II trial data has been extremely encouraging with regards both clinical outcome and the investigation of the underlying immunological mode-of-action. However, despite the positive phase II data there remains a high failure rate in late stage clinical trials which, in many cases can be ascribed to inappropriate trial design, poor patient selection and inconsistency in patient management. The potential impact of standard cancer treatments and other factors which may vary within patient populations is discussed. A perspective is provided on the failure of late-stage clinical trials across a range of platforms focusing particularly on melanoma and prostate cancer.

Monitoring cytokine profiles during immunotherapy

Measuring cytokine production is an integral part of measuring immune response during immunotherapy. Current technologies allow the simultaneous quantification of multiple cytokines in a variety of tissues. Patterns of cytokine response can be referred to as cytokine profiles. This article discusses the experimental design and data analysis of a number of studies that examined cytokine profiles in humans. We highlight potential sources of variability, both due to assay nuances and the diversity of human populations. We present strategies for analyzing data, emphasizing both multidimensional analysis and the value of treating each donor as his or her own control.

Predicting outcomes of prostate cancer immunotherapy by personalized mathematical models

BACKGROUND

Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.

METHODOLOGY/PRINCIPAL FINDINGS

We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2) = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.

CONCLUSIONS/SIGNIFICANCE

Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols.

Translating tumor antigens into cancer vaccines

Vaccines represent a strategic successful tool used to prevent or contain diseases with high morbidity and/or mortality. However, while vaccines have proven to be effective in combating pathogenic microorganisms, based on the immune recognition of these foreign antigens, vaccines aimed at inducing effective antitumor activity are still unsatisfactory. Nevertheless, the effectiveness of the two licensed cancer-preventive vaccines targeting tumor-associated viral agents (anti-HBV [hepatitis B virus], to prevent HBV-associated hepatocellular carcinoma, and anti-HPV [human papillomavirus], to prevent HPV-associated cervical carcinoma), along with the recent FDA approval of sipuleucel-T (for the therapeutic treatment of prostate cancer), represents a significant advancement in the field of cancer vaccines and a boost for new studies in the field. Specific active immunotherapies based on anticancer vaccines represent, indeed, a field in continuous evolution and expansion. Significant improvements may result from the selection of the appropriate tumor-specific target antigen (to overcome the peripheral immune tolerance) and/or the development of immunization strategies effective at inducing a protective immune response. This review aims to describe the vast spectrum of tumor antigens and strategies to develop cancer vaccines.

Vaccines as monotherapy and in combination therapy for prostate cancer

Prostate cancer is the second leading cause of cancer death among men in the United States. Standard-of-care chemotherapy for metastatic castration-resistant prostate cancer is associated with significant but modest survival benefit, indicating a need for alternative and/or additional approaches. The use of therapeutic cancer vaccines for the treatment of prostate cancer represents a novel targeted therapeutic approach. Whereas vaccine strategies are being developed for the treatment of various stages of prostate cancer, this article focuses on novel vaccine strategies for castration-resistant prostate cancer that have been translated into late-stage clinical studies.

Immunotherapy for prostate cancer: an emerging treatment modality

This article examines prostate cancer as a target for immunotherapy and investigates active immunotherapy for prostate cancer, combining conventional therapy with active immunotherapy, immune modulators (brakes and accelerators), and monoclonal antibodies.

Role of vaccine therapy in cancer: biology and practice

Vaccines constitute a potential new therapeutic approach for a range of human cancers. Unlike other therapeutics, vaccines initiate a dynamic process in the host immune system that can be exploited with subsequent therapies. Indeed, recent preclinical and clinical studies with cancer vaccines have provided evidence that this unique therapeutic modality should lead to consideration of new paradigms in both clinical trial design and endpoints and in combination therapies. The present article reviews and sets out a rationale for these new paradigms, with a focus on prostate cancer.

Cellular immunotherapy of cancer

Standard therapies for many common cancers remain toxic and are often ineffective. Cellular immunotherapy has the potential to be a highly targeted alternative, with low toxicity to normal tissues but a high capacity to eradicate tumor. In this chapter we describe approaches that generate cellular therapies using active immunization with cells, proteins, peptides, or nucleic acids, as well as efforts that use adoptive transfer of effector cells that directly target antigens on malignant cells. Many of these approaches are proving successful in hematologic malignancy and in melanoma. In this chapter we discuss the advantages and limitations of each and how over the next decade investigators will attempt to broaden their reach, increase their efficacy, and simplify their application.

Pretreatment frequency of circulating IL-17+ CD4+ T-cells, but not Tregs, correlates with clinical response to whole-cell vaccination in prostate cancer patients

The aim of this study was to determine the prognostic implications of the pretreatment level of Th17 cells compared with regulatory T-cell status in prostate cancer patients receiving active whole cell immunotherapy. Ten-color flow cytometry was used to analyze IL-17-producing CD4(+) T-cells in the peripheral blood of hormone-resistant non-bone metastatic prostate cancer patients prior to immunotherapy with an allogeneic whole-cell vaccine. Surface expression of the chemokine receptors CCR4 and CCR6 was used to further subdivide IL-17-producing cells into subsets with distinct homing properties. The frequency of circulating regulatory T-cells (Tregs), defined as CD3(+)CD4(+)CD127(lo)Foxp3(+)CD25(+) was compared in the same patients. The frequency of CCR4(-)IL-17(+)CD4(+) T-cells prevaccination inversely correlated with time to disease progression (TTP) in 23 prostate cancer patients. Furthermore, responder (R) patients with statistically significant reductions in PSA velocity (PSAV) in response to the immunotherapy (n = 9), showed a Th17 profile similar to healthy male controls and significantly different from non-responder (NR) patients (n = 14) (i.e., those without any significant reduction in PSAV). In contrast, the frequency of Tregs in peripheral blood in PSA-R (n = 11) and -NR (n = 14) patients was similar (but in both cases, significantly higher than in age-matched healthy men). Accordingly, there was no significant correlation between frequency of Tregs and TTP in these late-stage prostate cancer patients undergoing active immunotherapy. These data imply an important role for IL-17-producing helper T-cells in cancer immunology and highlight their potential use as a pretreatment screen to ensure appropriate treatment is offered to hormone-resistant prostate cancer patients.

Overview of Tumor Cell–Based Vaccines

Whole-cell tumor vaccines have been investigated for more than 20 years for their efficacy in both preclinical models and in clinical trials in humans. There are clear advantages of whole-cell/polyepitope vaccination over those types of immunotherapy that target specific epitopes. Multiple and unknown antigens may be targeted to both the innate and adaptive immune system, and this may be further augmented by genetic modification of the vaccine cells to provide cytokines and costimulation. In this review, we give an overview of the field including the preclinical and clinical advances using unmodified and modified tumor-cell vaccines.