Personalized identification of tumor-associated immunogenic neoepitopes in hepatocellular carcinoma in complete remission after sorafenib treatment

Neoantigens and their clinical applications in human gastrointestinal cancers

Background

Tumor-specific neoantigens are ideal targets for cancer immunotherapy. As research findings have proved, neoantigen-specific T cell activity is immunotherapy’s most important determinant.

Main text

There is sufficient evidence showing the role of neoantigens in clinically successful immunotherapy, providing a justification for targeting. Because of the significance of the pre-existing anti-tumor immune response for the immune checkpoint inhibitor, it is believed that personalized neoantigen-based therapy may be an imperative approach for cancer therapy. Thus, intensive attention is given to strategies targeting neoantigens for the significant impact with other immunotherapies, such as the immune checkpoint inhibitor. Today, several algorithms are designed and optimized based on Next-Generation Sequencing and public databases, including dbPepNeo, TANTIGEN 2.0, Cancer Antigenic Peptide Database, NEPdb, and CEDAR databases for predicting neoantigens in silico that stimulates the development of T cell therapies, cancer vaccine, and other ongoing immunotherapy approaches.

Conclusions

In this review, we deliberated the current developments in understanding and recognition of the immunogenicity of newly found gastrointestinal neoantigens as well as their functions in immunotherapies and cancer detection. We also described how neoantigens are being developed and how they might be used in the treatment of GI malignancies.

Therapeutic Vaccines against Hepatocellular Carcinoma in the Immune Checkpoint Inhibitor Era: Time for Neoantigens?

Immune checkpoint inhibitors (ICI) have been used as immunotherapy for hepatocellular carcinoma (HCC) with promising but still limited results. Identification of immune elements in the tumor microenvironment of individual HCC patients may help to understand the correlations of responses, as well as to design personalized therapies for non-responder patients. Immune-enhancing strategies, such as vaccination, would complement ICI in those individuals with poorly infiltrated tumors. The prominent role of responses against mutated tumor antigens (neoAgs) in ICI-based therapies suggests that boosting responses against these epitopes may specifically target tumor cells. In this review we summarize clinical vaccination trials carried out in HCC, the available information on potentially immunogenic neoAgs in HCC patients, and the most recent results of neoAg-based vaccines in other tumors. Despite the low/intermediate mutational burden observed in HCC, data obtained from neoAg-based vaccines in other tumors indicate that vaccines directed against these tumor-specific antigens would complement ICI in a subset of HCC patients.

4-methylumbelliferone-mediated polarization of M1 macrophages correlate with decreased hepatocellular carcinoma aggressiveness in mice

Hepatocellular carcinoma (HCC) arises in the setting of advanced liver fibrosis, a dynamic and complex inflammatory disease. The tumor microenvironment (TME) is a mixture of cellular components including cancer cells, cancer stem cells (CSCs), tumor-associated macrophages (TAM), and dendritic cells (DCs), which might drive to tumor progression and resistance to therapies. In this work, we study the effects of 4-methylumbelliferone (4Mu) on TME and how this change could be exploited to promote a potent immune response against HCC. First, we observed that 4Mu therapy induced a switch of hepatic macrophages (Mϕ) towards an M1 type profile, and HCC cells (Hepa129 cells) exposed to conditioned medium (CM) derived from Mϕ treated with 4Mu showed reduced expression of several CSCs markers and aggressiveness. HCC cells incubated with CM derived from Mϕ treated with 4Mu grew in immunosuppressed mice while presented delayed tumor progression in immunocompetent mice. HCC cells treated with 4Mu were more susceptible to phagocytosis by DCs, and when DCs were pulsed with HCC cells previously treated with 4Mu displayed a potent antitumoral effect in therapeutic vaccination protocols. In conclusion, 4Mu has the ability to modulate TME into a less hostile milieu and to potentiate immunotherapeutic strategies against HCC.

Anti-angiogenic Agents in Combination With Immune Checkpoint Inhibitors: A Promising Strategy for Cancer Treatment

Advances in cancer immunity have promoted a major breakthrough in the field of cancer therapy. This is mainly associated with the successful development of immune checkpoint inhibitors (ICIs) for multiple types of human tumors. Blockade with different ICIs, including programmed cell death 1 (PD-1), programmed cell death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors, may activate the immune system of the host against malignant cells. However, only a subgroup of patients with cancer would benefit from immune checkpoint blockade. Some patients experience primary resistance to initial immunotherapy, and a majority eventually develop acquired resistance to ICIs. However, the mechanisms involved in the development of drug resistance to immune checkpoint blockade remain unclear. Recent studies supported that combination of ICIs and anti-angiogenic agents could be a promising therapeutic strategy for overcoming the low efficacy of ICIs. Moreover, through their direct anti-cancer effect by inhibiting tumor growth and metastasis, anti-angiogenic drugs reprogram the tumor milieu from an immunosuppressive to an immune permissive microenvironment. Activated immunity by immune checkpoint blockade also facilitates anti-angiogenesis by downregulating the expression of vascular endothelial growth factor and alleviating hypoxia condition. Many clinical trials showed an improved anti-cancer efficacy and prolonged survival following the addition of anti-angiogenic agents to ICIs. This review summarizes the current understanding and clinical development of combination therapy with immune checkpoint blockade and anti-angiogenic strategy.

Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors

In the last years, immunotherapies have shown tremendous success as treatments for multiple types of cancer. However, there are still many obstacles to overcome in order to increase response rates and identify effective therapies for every individual patient. Since there are many possibilities to boost a patient's immune response against a tumor and not all can be covered, this review is focused on T cell receptor-mediated therapies. CD8+ T cells can detect and destroy malignant cells by binding to peptides presented on cell surfaces by MHC (major histocompatibility complex) class I molecules. CD4+ T cells can also mediate powerful immune responses but their peptide recognition by MHC class II molecules is more complex, which is why the attention has been focused on CD8+ T cells. Therapies based on the power of T cells can, on the one hand, enhance T cell recognition by introducing TCRs that preferentially direct T cells to tumor sites (so called TCR-T therapy) or through vaccination to induce T cells in vivo. On the other hand, T cell activity can be improved by immune checkpoint inhibition or other means that help create a microenvironment favorable for cytotoxic T cell activity. The manifold ways in which the immune system and cancer interact with each other require not only the use of large omics datasets from gene, to transcript, to protein, and to peptide but also make the application of machine learning methods inevitable. Currently, discovering and selecting suitable TCRs is a very costly and work intensive in vitro process. To facilitate this process and to additionally allow for highly personalized therapies that can simultaneously target multiple patient-specific antigens, especially neoepitopes, breakthrough computational methods for predicting antigen presentation and TCR binding are urgently required. Particularly, potential cross-reactivity is a major consideration since off-target toxicity can pose a major threat to patient safety. The current speed at which not only datasets grow and are made available to the public, but also at which new machine learning methods evolve, is assuring that computational approaches will be able to help to solve problems that immunotherapies are still facing.

Immunotherapy in hepatocellular carcinoma: the complex interface between inflammation, fibrosis, and the immune response

Hepatocellular carcinoma (HCC) is the third leading cause of cancer deaths worldwide and confers a poor prognosis. Beyond standard systemic therapy with multikinase inhibitors, recent studies demonstrate the potential for robust and durable responses from immune checkpoint inhibition in subsets of HCC patients across disease etiologies. The majority of HCC arises in the context of chronic inflammation and from within a fibrotic liver, with many cases associated with hepatitis virus infections, toxins, and fatty liver disease. Many patients also have concomitant cirrhosis which is associated with both local and systemic immune deficiency. Furthermore, the liver is an immunologic organ in itself, which may enhance or suppress the immune response to cancer arising within it. Here, we explore the immunobiology of the liver from its native state to chronic inflammation, fibrosis, cirrhosis and then to cancer, and summarize how this unique microenvironment may affect the response to immunotherapy.