A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon

A genetic inference on cancer immune responsiveness

A cancer immune signature implicating good prognosis and responsiveness to immunotherapy was described that is observed also in other aspects of immune-mediated, tissue-specific destruction (TSD). Its determinism remains, however, elusive. Based on limited but unique clinical observations, we propose a multifactorial genetic model of human cancer immune responsiveness.

Status of Immune Oncology: Challenges and Opportunities

This volume is intended to review the methods used to identify biomarkers predictive of cancer responsiveness to immunotherapy. The successful development of clinically actionable biomarkers depends upon three features: (a) their biological role with respect to malignant transformation and tumor progression; (b) the ability to detect them with robust, reliable, and clinically applicable assays; and (c) their prognostic or predictive value, as validated in clinical trials.Identifying biomarkers that have predictive value for patient selection based on the likelihood of benefiting from anticancer immunotherapy is a lengthy and complex process. To date, few predictive biomarkers for anticancer immunotherapy have been robustly analytically and clinically validated (i.e., PD-L1 expression as measured by IHC assays and microsatellite instability (MSI)/dMMR as measured by PCR or IHC, respectively).This introductory chapter to this book focuses on scientific and technical aspects relevant to the identification and validation of predictive biomarkers for immunotherapy. We emphasize that methods should address both the biology of the tumor and the tumor microenvironment. Moreover, the identification of biomarkers requires highly sensitive, multiplexed, comprehensive techniques, especially for application in clinical care. Thus, in this chapter, we will define the outstanding questions related to the immune biology of cancer as a base for development of the biomarkers and assays using diverse methodologies. These biomarkers will likely be identified through research that integrates conventional immunological approaches along with high-throughput genomic and proteomic screening and the host immune response of individual patients that relates to individual tumor biology and immune drugs' mechanism of action.Checkpoint inhibitor therapy (CIT) is by now an accepted modality of cancer treatment. However, immune resistance is common, and most patients do not benefit from the treatment. The reasons for resistance are diverse, and approaches to circumvent it need to consider genetic, biologic, and environmental factors that affect anticancer immune response. Here, we propose to systematically address fundamental concepts based on the premise that malignant cells orchestrate their surroundings by interacting with innate and adaptive immune sensors. This principle applies to most cancers and governs their evolution in the immune-competent host. Understanding the basic requirement(s) for this evolutionary process will guide biomarker discovery and validation and ultimately guide to effective therapeutic choices. This volume will also discuss novel biomarker approaches aimed at informing an effective assay development from a mechanistic point of view, as well as the clinical implementation (i.e., patient enrichment) for immune therapies.

The prognostic value of cytotoxic T-lymphocyte antigen 4 in cancers: a systematic review and meta-analysis

The outcomes of studies analyzing the prognostic role of CTLA-4 in cancers are controversial. Therefore, the aim of our meta-analysis was to clarify the correlation between CTLA-4 expression and OS in different cancer cases. Relevant literature was searched using PubMed, EMBASE, Web of Science, and the Cochrane Library. The clinicopathological features, hazard ratio (HR) and 95% confidence intervals (CI) were collected from these studies and were analyzed using Stata version 12.0 software. The pooled HR values showed no significant correlation between CTLA-4 expression levels and OS in relation to tumors (HR: 1.24, 95% CI: 0.98–1.56, I2 = 71.7%, P = 0.000). Further subgroup analyses were conducted and categorized by experimental methods, CTLA-4 sources and cancer types. The survey showed a significant correlation (HR: 1.47, 95% CI: 1.14–1.89) between high expression of CTLA-4 and OS in the SNP subgroup, and subgroups analyzing by PCR (HR: 1.50, 95% CI: 1.20–1.86) and flow cytometry (HR: 2.76, 95% CI: 1.49–5.14). In addition, our analysis observed significant differences between patients and controls in inCTLA-4+CD4+ lymphocytes, surCTLA-4+CD4+ lymphocytes, inCTLA-4+CD8+ lymphocytes, and surCTLA-4+CD8+ lymphocytes. Knowledge of the effects of CTLA-4 could potentially be used to effectively guide appropriate prognosis and therapeutic strategies in cancer patients.

Challenges in the harmonization of immune monitoring studies and trial design for cell-based therapies in the context of hematopoietic cell transplantation for pediatric cancer patients

Clinical trials aimed at improving results of hematopoietic cell transplantation (HCT) by adjuvant cell-based interventions in children have been limited by small numbers and pediatric-specific features. The need for a larger number of pediatric HCT centers to participate in trials has resulted in a demand for harmonization of disease-specific clinical trials and immune-monitoring. Thus far, most phase I/II trials select different end points evaluated at disparate time points, making inter-study comparisons difficult and, sometimes, impossible. In this review, we discuss the various aspects that are important to consider for harmonizing clinical trial design as well as the critical elements for standardized (immune)-monitoring protocols in cell-based intervention trials in the context of HCT. Comparison data from trials applying harmonized trial design will lead to optimized immunotherapeutic treatment protocols to maximize clinical efficacy while minimizing toxicity.

Disentangling the relationship between tumor genetic programs and immune responsiveness

Correlative studies in humans have demonstrated that an active immune microenvironment characterized by the presence of a T-helper 1 immune response typifies a tumor phenotype associated with better outcome and increased responsiveness to immune manipulation. This phenotype also signifies the counter activation of immune-regulatory mechanisms. Variables modulating the development of an effective anti-tumor immune response are increasingly scrutinized as potential therapeutic targets. Genetic alterations of cancer cells that functionally influence intratumoral immune response include mutational load, specific mutations of genes involved in oncogenic pathways and copy number aberrations involving chemokine and cytokine genes. Inhibiting oncogenic pathways that prevent the development of the immune-favorable cancer phenotype may complement modern immunotherapeutic approaches.

A new mathematical model for the interpretation of translational research evaluating six CTLA-4 polymorphisms in high-risk melanoma patients receiving adjuvant interferon

Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic “dominant model”, the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graph-representation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival.

Marker utility for combination therapy

Melanoma is a heterogeneous disease for which monotherapies are likely to fail in the majority of patients due to genomic variations between individuals. Novel treatments, such as vemurafenib and ipilimumab, offer clinical promise in metastatic melanoma and the increased potential for combined therapeutic strategies, necessary given the differences in response between patients. Together with these new approaches, the development of clinically relevant biomarkers that predict treatment outcomes are required to ensure these new therapies are targeted at those patients most likely to benefit. Here we review the utility of some potential biomarkers of treatment response in patients with metastatic melanoma.

New developments in biomarkers for melanoma

PURPOSE OF REVIEW

Therapy of malignant melanoma recently experienced remarkable advances with the introduction of two treatment regimens, gene mutation-based therapies with signaling pathway inhibitors (kinase inhibitors) and treatments with immune modulators. Both strategies prolong patients' survival but still have specific limitations, demanding the identification of additional genetic and immunological biomarkers as predictors of treatment response and prognosis. New developments in that field are summarized in this review.

RECENT FINDINGS

Activating oncogene mutations are important melanoma biomarkers. They predict responsiveness to kinase inhibitor therapies and have therapy independent prognostic relevance. Epigenetic alterations (DNA methylation, chromatin remodeling, and noncoding RNA) in melanoma are emerging as potentially valuable biomarkers. With the successful introduction of immunotherapies for melanoma, interest in immunological biomarkers has grown. Tumor-reactive cytotoxic T cells from patients' peripheral blood were recently proposed to predict prognosis and response to immunotherapy. A superior immune profile assessment could be achieved by combining a detailed characterization of a tumor's immune cell infiltrate with its (immune) gene signature.

SUMMARY

Genetic melanoma markers have already become clinically relevant. We expect both their role and that of immunological biomarkers to increase significantly in the next few years, enabling personalized therapy with optimal treatment selection for individual tumors.

Future perspectives in melanoma research. Meeting report from the "Melanoma Bridge. Napoli, December 2nd-4th 2012"

Recent insights into the genetic and somatic aberrations have initiated a new era of rapidly evolving targeted and immune-based treatments for melanoma. After decades of unsuccessful attempts to finding a more effective cure in the treatment of melanoma now we have several drugs active in melanoma. The possibility to use these drugs in combination to improve responses to overcome the resistance, to potentiate the action of immune system with the new immunomodulating antibodies, and identification of biomarkers that can predict the response to a particular therapy represent new concepts and approaches in the clinical management of melanoma. The third "Melanoma Research: "A bridge from Naples to the World" meeting, shortened as "Bridge Melanoma Meeting" took place in Naples, December 2 to 4th, 2012. The four topics of discussion at this meeting were: advances in molecular profiling and novel biomarkers, combination therapies, novel concepts toward integrating biomarkers and therapies into contemporary clinical management of patients with melanoma across the entire spectrum of disease stage, and the knowledge gained from the biology of tumor microenvironment across different tumors as a bridge to impact on prognosis and response to therapy in melanoma. This international congress gathered more than 30 international faculty members who in an interactive atmosphere which stimulated discussion and exchange of their experience regarding the most recent advances in research and clinical management of melanoma patients.