TNF-receptor superfamily agonists as molecular adjuvants for cancer vaccines

TNFepitope: A webserver for the prediction of TNF-α inducing epitopes

Tumor Necrosis Factor alpha (TNF-α) is a pleiotropic pro-inflammatory cytokine that is crucial in controlling the signaling pathways within the immune cells. Recent studies reported that higher expression levels of TNF-α are associated with the progression of several diseases, including cancers, cytokine release syndrome in COVID-19, and autoimmune disorders. Thus, it is the need of the hour to develop immunotherapies or subunit vaccines to manage TNF-α progression in various disease conditions. In the pilot study, we proposed a host-specific in-silico tool for predicting, designing, and scanning TNF-α inducing epitopes. The prediction models were trained and validated on the experimentally validated TNF-α inducing/non-inducing epitopes from human and mouse hosts. Firstly, we developed alignment-free (machine learning based models using composition-based features of peptides) methods for predicting TNF-α inducing peptides and achieved maximum AUROC of 0.79 and 0.74 for human and mouse hosts, respectively. Secondly, an alignment-based (using BLAST) method has been used for predicting TNF-α inducing epitopes. Finally, a hybrid method (combination of alignment-free and alignment-based method) has been developed for predicting epitopes. Hybrid approach achieved maximum AUROC of 0.83 and 0.77 on an independent dataset for human and mouse hosts, respectively. We have also identified potential TNF-α inducing peptides in different proteins of HIV-1, HIV-2, SARS-CoV-2, and human insulin. The best models developed in this study has been incorporated in the webserver TNFepitope (https://webs.iiitd.edu.in/raghava/tnfepitope/), standalone package and GitLab (https://gitlab.com/raghavalab/tnfepitope).

Control of Memory Phenotype T Lymphocyte Homeostasis: Role of Costimulation

Foxp3⁺ T regulatory cells (Tregs), CD4⁺Foxp3^- T cells, and CD8⁺ T cells are composed of naive phenotype (NP) and memory phenotype (MP) subsets. Ten to 20% of each MP T cell population are cycling (Ki-67⁺) in vivo. We investigated the contribution of costimulatory (CD28) and coinhibitory (CTLA-4, PD-1) receptors on MP T cell homeostatic proliferation in vivo in the mouse. Blockade of CD28-CD80/CD86 signaling completely abolished MP Tregs and profoundly inhibited MP CD4⁺Foxp3^- T cell proliferation, but it did not affect MP CD8⁺ T cell proliferation. Marked enhancement of homeostatic proliferation of MP Tregs and MP CD4⁺Foxp3^- T cells was seen after blocking CTLA4-CD80/CD86 interactions and PD-1-PD-L1/2 interactions, and greater enhancement was seen with blockade of both pathways. The CD28 pathway also played an important role in the expansion of Tregs and MP T cells after treatment of mice with agonistic Abs to members of the TNF receptor superfamily, which can act directly (anti-GITR, anti-OX40, anti-4-1BB) or indirectly (anti-CD40) on T cells. Induction of a cytokine storm by blocking the interaction of NK inhibitory receptors with MHC class I had no effect on Treg homeostasis, enhanced MP CD4⁺ proliferation, and expansion in a CD28-dependent manner, but it enhanced MP CD8⁺ T cell proliferation in a CD28-independent manner. Because MP T cells exert potent biologic effects primarily before the induction of adaptive immune responses, these findings have important implications for the use of biologic agents designed to suppress autoimmune disease or enhance T effector function in cancer that may have negative effects on MP T cells.

Identification of important genes and drug repurposing based on clinical-centered analysis across human cancers

Identification of the functional impact of mutated and altered genes in cancer is critical for implementing precision oncology and drug repurposing. In recent years, the emergence of multiomics data from large, well-characterized patient cohorts has provided us with an unprecedented opportunity to address this problem. In this study, we investigated survival-associated genes across 26 cancer types and found that these genes tended to be hub genes and had higher K-core values in biological networks. Moreover, the genes associated with adverse outcomes were mainly enriched in pathways related to genetic information processing and cellular processes, while the genes with favorable outcomes were enriched in metabolism and immune regulation pathways. We proposed using the number of survival-related neighbors to assess the impact of mutations. In addition, by integrating other databases including the Human Protein Atlas and the DrugBank database, we predicted novel targets and anticancer drugs using the drug repurposing strategy. Our results illustrated the significance of multidimensional analysis of clinical data in important gene identification and drug development.

Fundamentals of Cancer Immunology and Their Application to Cancer Vaccines

The capacity of the immune system to influence tumor progression has been a long-standing notion that first generated clinical traction over a 100 years ago when Dr. William Coley injected disaggregated bacterial components into sarcomas and noted that the ensuing inflammation commonly associated with tumor regression.¹ Since then, our understanding of the individual components and the overall interaction of the immune system has expanded exponentially. This has led to the development of a robust understanding of how components of innate and adaptive immunity recognize and respond to tumors and leveraging this information for the development of tumor immunotherapies. However, clinical failures have also deepened our knowledge of how tumors might adapt/be selected to avoid or inhibit immune responses, which, in turn, has led to the further iteration of immunotherapies. In this tutorial, the established elements of tumor immunity are explained, and areas where our knowledge base is too thin is highlighted. The principles of tumor immunity that guide the development of cancer vaccines are further illustrated, and potential considerations of how to integrate cancer vaccines with conventional therapies and other immunotherapies are proposed.

Cancer vaccines: Targeting KRAS-driven cancers

Introduction: Mutant KRAS is a genetic driver of multiple cancers that has challenged clinical anti-cancer therapeutics in the last 3 decades. Neo-antigens encoded by KRAS mutations have been identified as tumor-specific with high immunogenicity and can be used to deliver precision cancer vaccines to promote anti-tumor immune responses. KRAS mutation-based cancer vaccines have produced encouraging preclinical and clinical results. Cancer vaccines represent a promising approach to treat KRAS-driven cancers.Areas covered: In this review, we summarize the development and progress of vaccines targeting KRAS and evaluate their potential benefits and obstacles in the current landscape of therapy for KRAS-driven cancers.Expert opinion: KRAS mutation-based cancer vaccines can induce immunogenicity in patients with KRAS-driven cancers. However, the mechanisms of tumor suppression including cellular and molecular factors within the tumor microenvironment may limit vaccine efficacy. Combining KRAS-driven therapeutic cancer vaccines with other methods and adjuvants can circumvent immunosuppression and promote therapeutic successes.

A Bioinformatic Approach for the Identification of Molecular Determinants of Resistance/Sensitivity to Cancer Thermotherapy

Application of heat above 43°C and up to 47°C, the so-called “thermal ablation” range, leads to tumor cell destruction either by apoptosis or by necrosis. However, tumor cells have developed mechanisms of defense that render them thermoresistant. Of importance, the in situ application of heat for the treatment of localized solid tumors can also prime specific antitumor immunity. Herein, a bioinformatic approach was employed for the identification of molecular determinants implicated in thermoresistance and immunogenic cell death (ICD). To this end, both literature-derived (text mining) and microarray gene expression profile data were processed, followed by functional enrichment analysis. Two important functional gene modules were detected in hyperthermia resistance and ICD, the former including members of the heat shock protein (HSP) family of molecular chaperones and the latter including immune-related molecules, respectively. Of note, the molecules HSP90AA1 and HSPA4 were found common between thermoresistance and damage signaling molecules (damage-associated molecular patterns (DAMPs)) and ICD. In addition, the prognostic potential of HSP90AA1 and HSPA4 overexpression for cancer patients' overall survival was investigated. The results of this study could constitute the basis for the strategic development of more efficient and personalized therapeutic strategies against cancer by means of thermotherapy, by taking into consideration the genetic profile of each patient.

Genetic landscape of hepatitis B virus-associated diffuse large B-cell lymphoma

Hepatitis B virus (HBV) infection is endemic in some parts of Asia, Africa, and South America and remains to be a significant public health problem in these areas. It is known as a leading risk factor for the development of hepatocellular carcinoma, but epidemiological studies have also shown that the infection may increase the incidence of several types of B-cell lymphoma. Here, by characterizing altogether 275 Chinese diffuse large B-cell lymphoma (DLBCL) patients, we showed that patients with concomitant HBV infection (surface antigen positive [HBsAg⁺]) are characterized by a younger age, a more advanced disease stage at diagnosis, and reduced overall survival. Furthermore, by whole-genome/exome sequencing of 96 tumors and the respective peripheral blood samples and targeted sequencing of 179 tumors from these patients, we observed an enhanced rate of mutagenesis and a distinct set of mutation targets in HBsAg⁺ DLBCL genomes, which could be partially explained by the activities of APOBEC and activation-induced cytidine deaminase. By transcriptome analysis, we further showed that the HBV-associated gene expression signature is contributed by the enrichment of genes regulated by BCL6, FOXO1, and ZFP36L1. Finally, by analysis of immunoglobulin heavy chain gene sequences, we showed that an antigen-independent mechanism, rather than a chronic antigenic simulation model, is favored in HBV-related lymphomagenesis. Taken together, we present the first comprehensive genomic and transcriptomic study that suggests a link between HBV infection and B-cell malignancy. The genetic alterations identified in this study may also provide opportunities for development of novel therapeutic strategies.