Networks as Biomarkers: Uses and Purposes

Networks-based approaches are often used to analyze gene expression data or protein-protein interactions but are not usually applied to study the relationships between different biomarkers. Given the clinical need for more comprehensive and integrative biomarkers that can help to identify personalized therapies, the integration of biomarkers of different natures is an emerging trend in the literature. Network analysis can be used to analyze the relationships between different features of a disease; nodes can be disease-related phenotypes, gene expression, mutational events, protein quantification, imaging-derived features and more. Since different biomarkers can exert causal effects between them, describing such interrelationships can be used to better understand the underlying mechanisms of complex diseases. Networks as biomarkers are not yet commonly used, despite being proven to lead to interesting results. Here, we discuss in which ways they have been used to provide novel insights into disease susceptibility, disease development and severity.

Soluble PD-L1 as a Prognostic Factor for Immunotherapy Treatment in Solid Tumors: Systematic Review and Meta-Analysis

Blocking the Programmed Cell Death Protein 1 (PD-1)/programmed death ligand-1 (PD-L1) axis has demonstrated great efficacy in cancer immunotherapy treatment and remains the central modality of immune targeting. To support the rational and tailored use of these drugs, it is important to identify reliable biomarkers related to survival. The role of the soluble form of the PD-L1 (sPD-L1) as a prognostic biomarker related to survival in solid cancer patients treated with immunotherapy has not yet been consistently evaluated. A systematic literature search of original articles in PubMed, MEDLINE and Scopus was conducted. Studies reporting hazard ratios (HRs) with a 95% confidence interval (CI) or Kaplan−Meier curves or individual patient data for overall survival (OS) or progression-free survival (PFS) associated with baseline levels of sPD-L1 in cancer patients undergoing immunotherapy treatment were considered eligible. Twelve studies involving 1076 patients and different tumor types treated with immunotherapy were included in the analysis. High blood levels of sPD-L1 correlated with poorer OS and PFS in cancer patients treated with immunotherapy (HR = 1.49, 95%CI: 1.15, 1.93, p < 0.01, I2 = 77% for OS; HR = 1.59, 95%CI: 1.20, 2.12, p < 0.01, I2 = 82% for PFS). A subgroup analysis highlighted that high levels of sPD-L1 were associated with worse survival in patients affected by NSCLC (HR = 1.81 95%CI: 1.09−3.00, p = 0.02, I2 = 83% for OS; HR = 2.18, 95%CI: 1.27−3.76, p < 0.01, I2 = 88% for PFS). An HR > 1 indicated that patients with low levels of sPD-L1 have the highest rates of OS/PFS. In this meta-analysis, we clarified the role of sPD-L1 in different solid cancers treated exclusively with Immune checkpoint inhibitors (ICIs). sPD-L1 could represent a non-invasive biomarker that is easily dosable in the blood of patients. The pooled data from the selected studies showed that a high circulating concentration of sPD-L1 in cancer patients correlates with worse survival, suggesting that it may be a helpful prognostic biomarker for the selection of cancer patients before immunotherapy, thus improving the efficacy of ICIs and avoiding unnecessary treatment.

Non-Invasive Biomarkers for Immunotherapy in Patients with Hepatocellular Carcinoma: Current Knowledge and Future Perspectives

Simple Summary

The search for non-invasive biomarkers is a hot topic in modern oncology, since a tissue biopsy has significant limitations in terms of cost and invasiveness. The treatment perspectives have been significantly improved after the approval of immunotherapy for patients with hepatocellular carcinoma; therefore, the quick identification of responders is crucial to define the best therapeutic strategy. In this review, the current knowledge on the available non-invasive biomarkers of the response to immunotherapy is described.

Abstract

The treatment perspectives of advanced hepatocellular carcinoma (HCC) have deeply changed after the introduction of immunotherapy. The results in responders show improved survival compared with Sorafenib, but only one-third of patients achieve a significant benefit from treatment. As the tumor microenvironment exerts a central role in shaping the response to immunotherapy, the future goal of HCC treatment should be to identify a proxy of the hepatic tissue condition that is easy to use in clinical practice. Therefore, the search for biomarkers that are accurate in predicting prognosis will be the hot topic in the therapeutic management of HCC in the near future. Understanding the mechanisms of resistance to immunotherapy may expand the patient population that will benefit from it, and help researchers to find new combination regimens to improve patients’ outcomes. In this review, we describe the current knowledge on the prognostic non-invasive biomarkers related to treatment with immune checkpoint inhibitors, focusing on serological markers and gut microbiota.

Role of Exosomes in Immunotherapy of Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma is one of the most lethal malignancies, having a significantly poor prognosis. Immunotherapy, as an emerging tumor treatment option, provides new hope for many cancer patients. However, a large proportion of patients do not benefit from immunotherapy. As a critical cell-to-cell communication mediator in the tumor immune microenvironment, exosomes may play a unique role in hepatocellular carcinoma immune response and thus affect the efficiency of immunotherapy. In this review, we discuss related research on the roles of exosomes in the current immunotherapy resistance mechanism of hepatocellular carcinoma. Furthermore, we also clarify the excellent predictive value of exosomes and the roles they play in improving immunotherapy efficacy for hepatocellular carcinoma patients. We hope that our review can help readers to gain a more comprehensive understanding of exosomes’ roles in hepatocellular carcinoma immunotherapy.

Abstract

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies, having a significantly poor prognosis and no sufficiently efficient treatments. Immunotherapy, especially immune checkpoint inhibitors (ICIs), has provided new therapeutic approaches for HCC patients. Nevertheless, most patients with HCC do not benefit from immunotherapy. Exosomes are biologically active lipid bilayer nano-sized vesicles ranging in size from 30 to 150 nm and can be secreted by almost any cell. In the HCC tumor microenvironment (TME), numerous cells are involved in tumor progression, and exosomes—derived from tumor cells and immune cells—exhibit unique composition profiles and act as intercellular communicators by transporting various substances. Showing the dual characteristics of tumor promotion and suppression, exosomes exert multiple functions in shaping tumor immune responses in the crosstalk between tumor cells and surrounding immune cells, mediating immunotherapy resistance by affecting the PD-1/PD-L1 axis or the anti-tumor function of immune cells in the TME. Targeting exosomes or the application of exosomes as therapies is involved in many aspects of HCC immunotherapies (e.g., ICIs, tumor vaccines, and adoptive cell therapy) and may substantially enhance their efficacy. In this review, we discuss the impact of exosomes on the HCC TME and comprehensively summarize the role of exosomes in immunotherapy resistance and therapeutic application. We also discuss the potential of exosomes as biomarkers for predicting the efficacy of immunotherapy to help clinicians in identifying HCC patients who are amenable to immunotherapies.