Immunotherapy of melanoma: efficacy and mode of action

Peritumoral Immune Infiltrate as a Prognostic Biomarker in Thin Melanoma

Thin melanomas are tumors less than 1 mm thick according to Breslow classification. Their prognosis is in most cases excellent. However, a small subset of these tumors relapses. These clinical findings emphasize the need of novel prognostic biomarkers to identify this subset of tumors. Characterization of tumor immune microenvironment (TIME) is currently investigated as a prognostic and predictive biomarker for cancer immunotherapy in several solid tumors including melanoma. Here, taking into account the limited availability of tumor tissues, by characterizing some of the characteristics of TIME such as number of infiltrating lymphocytes, HLA class I antigen and PD-L1 expression, we show that number of infiltrating CD8+ and FOXP3+ T cells as well as CD8+/FOXP3+ T cell ratio can represent a useful prognostic biomarker in thin melanoma. Although further investigations in a larger patient cohort are needed, these findings have potential clinical significance since they can be used to define subgroups of thin melanoma patients who have a worse prognosis and might need different treatment modalities.

Cell death-based treatments of melanoma:conventional treatments and new therapeutic strategies

The incidence of malignant melanoma has continued to rise during the past decades. However, in the last few years, treatment protocols have significantly been improved thanks to a better understanding of the key oncogenes and signaling pathways involved in its pathogenesis and progression. Anticancer therapy would either kill tumor cells by triggering apoptosis or permanently arrest them in the G1 phase of the cell cycle. Unfortunately, melanoma is often refractory to commonly used anticancer drugs. More recently, however, some new anticancer strategies have been developed that are “external” to cancer cells, for example stimulating the immune system’s response or inhibiting angiogenesis. In fact, the increasing knowledge of melanoma pathogenetic mechanisms, in particular the discovery of genetic mutations activating specific oncogenes, stimulated the development of molecularly targeted therapies, a form of treatment in which a drug (chemical or biological) is developed with the goal of exclusively destroying cancer cells by interfering with specific molecules that drive growth and spreading of the tumor. Again, after the initial exciting results associated with targeted therapy, tumor resistance and/or relapse of the melanoma lesion have been observed. Hence, very recently, new therapeutic strategies based on the modulation of the immune system function have been developed. Since cancer cells are known to be capable of evading immune-mediated surveillance, i.e., to block the immune system cell activity, a series of molecular strategies, including monoclonal antibodies, have been developed in order to “release the brakes” on the immune system igniting immune reactivation and hindering metastatic melanoma cell growth. In this review we analyze the various biological strategies underlying conventional chemotherapy as well as the most recently developed targeted therapies and immunotherapies, pointing at the molecular mechanisms of cell injury and death engaged by the different classes of therapeutic agents.

Integrated analysis of differential expression and alternative splicing of non-small cell lung cancer based on RNA sequencing

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with high morbidity and mortality rates. Numerous diagnosis and treatment methods have been proposed, and the prognosis of NSCLC has improved to a certain extent. However, the mechanisms of NSCLC remain largely unknown, and additional studies are required. In the present study, the RNA sequencing dataset of NSCLC was downloaded from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). The clean reads obtained from the raw data were mapped to the University of California Santa Cruz human genome (hg19), based on TopHat, and were assembled into transcripts via Cufflink. The differential expression (DE) and differential alternative splicing (DAS) genes were screened out through Cuffdiff and rMATS, respectively. The significantly enriched gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes pathways were obtained through the Database of Annotation, Visualization and Integrated Discovery (DAVID). Different numbers of DE and DAS genes were identified in different types of NSCLC samples, but a number of common functions and pathways were obtained, including biological processes associated with abnormal immune and cell activity. GO terms and pathways associated with substance metabolism, including the insulin signaling pathway and oxidative phosphorylation, were enriched in DAS genes rather than DE genes. Integrated analysis of differential expression and alternative splicing may be helpful in understanding the mechanisms of NSCLC, in addition to its early diagnosis and treatment.

Effectiveness and safety of PD-1/PD-L1 inhibitors in the treatment of solid tumors: a systematic review and meta-analysis

Background

PD-1/PD-L1 inhibitors have been implicated as potentially effective anti-cancer therapies. Some clinical randomized controlled trials (RCTs) have been completed for a variety of PD-1/PD-L1 inhibitors to treat various malignancies, and more RCTs are still under way. We carried out this systematic meta-analysis to evaluate the efficacy and safety of PD-1/PD-L1 inhibitors in the treatment of solid tumors.

Methods

We searched PubMed, EMBASE, clinical trial registers, conference reports, and related reviews. Eligible RCTs that compared PD-1/PD-L1 inhibitors with other chemotherapy agents or placebo in solid tumor patients were included. For each RCT, progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR), stable disease rate (SDR), progressive disease rate (PDR), and adverse events (AEs) were pooled for meta-analysis.

Findings

Based on an analysis of 10 eligible RCTs, PD-1/PD-L1 inhibitors were found to significantly improve PFS (Hazard ratio (HR), 0.65; 95% confidence interval (CI) 0.53 to 0.79, P<0.001), OS (HR, 0.69; 95%CI 0.62 to 0.76, P<0.001), and ORR (Risk Ratio (RR) 292; 95% confidence interval (CI) 2.06 to 4.15, P<0.00001) in all populations, including melanoma and NSCLC subgroups. However, they failed to increase the DCR of cancer patients (RR 1.15; 95%CI 0.91 to 1.45, P=0.25). Furthermore, less AEs were observed in the PD-1/PD-L1 inhibitor groups than the control groups.

Interpretation

PD-1 inhibitors are more effective for improving the PFS, OS, and ORR of cancer patients with little toxicity, despite having little effect on increasing of the DCR.

Targeting macrophage anti-tumor activity to suppress melanoma progression

By phagocytosing cancer cells and their cellular debris, macrophages play a critical role in nonspecific defense (innate immunity) and, as antigen presenters, they help initiate specific defense mechanisms (adaptive immunity). Malignant melanoma is a lethal disease due to its aggressive capacity for metastasis and resistance to therapy. For decades, considerable effort has gone into development of an effective immunotherapy for treatment of metastatic melanoma. In this review, we focus on the anti-tumor activities of macrophages in melanoma and their potential as therapeutic targets in melanoma. Although macrophages can be re-educated through intercellular signaling to promote tumor survival owing to their plasticity, we expect that targeting the anti-tumor activity of macrophages remains a promising strategy for melanoma inhibition. The combination of tumoricidal macrophage activation and other treatments such as surgery, chemotherapy, and radiotherapy, may provide an effective and comprehensive anti-melanoma strategy.

PD-L1+MDSCs are increased in HCC patients and induced by soluble factor in the tumor microenvironment

Myeloid-derived suppressor cells (MDSCs) could have important roles in immune regulation, and MDSCs can be induced in patients with various malignant tumors. The immune-suppressive functions of MDSCs in hepatocellular carcinoma (HCC) patients have not been clarified. Therefore, we tried to analyze the biological significance of MDSCs in HCC patients. We quantified PD-L1+MDSCs of HCC patients in various conditions by using multi-color flow cytometry analysis. PBMCs from HCC patients contained significantly higher percentages of PD-L1+MDSCs in comparison to those from healthy subjects (p < 0.001). The percentages of PD-L1+MDSCs were reduced by curative treatment for HCC (p < 0.05), and the percentages of PD-L1+MDSCs before treatment were inversely correlated with disease-free survival time. After we cocultivated PBMCs and several liver cancer cell lines in a transwell coculture system, the percentages of PD-L1+MDSCs were significantly increased compared with control (p < 0.05). The expression of M-CSF and VEGFA was higher in the cell lines that strongly induced PD-L1+MDSCs. Peripheral blood from HCC patients had significantly higher percentages of PD-L1+MDSCs in comparison to those of healthy subjects, and the percentages of PD-L1+MDSCs were reduced by HCC treatment, suggesting that we might use PD-L1+MDSCs as a new biomarker of HCC.

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.