Computational cancer neoantigen prediction: current status and recent advances

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation

T cell alloreactivity against minor histocompatibility antigens (mHAgs)-polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms-is at the core of the therapeutic effect of allogeneic hematopoietic cell transplantation (allo-HCT). Despite the crucial role of mHAgs in graft-versus-leukemia (GvL) and graft-versus-host disease (GvHD) reactions, it remains challenging to consistently link patient-specific mHAg repertoires to clinical outcomes. Here we devise an analytic framework to systematically identify mHAgs, including their detection on HLA class I ligandomes and functional verification of their immunogenicity. The method relies on the integration of polymorphism detection by whole-exome sequencing of germline DNA from D-R pairs with organ-specific transcriptional- and proteome-level expression. Application of this pipeline to 220 HLA-matched allo-HCT D-R pairs demonstrated that total and organ-specific mHAg load could independently predict the occurrence of acute GvHD and chronic pulmonary GvHD, respectively, and defined promising GvL targets, confirmed in a validation cohort of 58 D-R pairs, for the prevention or treatment of post-transplant disease recurrence.

Transformers meets neoantigen detection: a systematic literature review

Cancer immunology offers a new alternative to traditional cancer treatments, such as radiotherapy and chemotherapy. One notable alternative is the development of personalized vaccines based on cancer neoantigens. Moreover, Transformers are considered a revolutionary development in artificial intelligence with a significant impact on natural language processing (NLP) tasks and have been utilized in proteomics studies in recent years. In this context, we conducted a systematic literature review to investigate how Transformers are applied in each stage of the neoantigen detection process. Additionally, we mapped current pipelines and examined the results of clinical trials involving cancer vaccines.

Nucleic acid-based drugs for patients with solid tumours

The treatment of patients with advanced-stage solid tumours typically involves a multimodality approach (including surgery, chemotherapy, radiotherapy, targeted therapy and/or immunotherapy), which is often ultimately ineffective. Nucleic acid-based drugs, either as monotherapies or in combination with standard-of-care therapies, are rapidly emerging as novel treatments capable of generating responses in otherwise refractory tumours. These therapies include those using viral vectors (also referred to as gene therapies), several of which have now been approved by regulatory agencies, and nanoparticles containing mRNAs and a range of other nucleotides. In this Review, we describe the development and clinical activity of viral and non-viral nucleic acid-based treatments, including their mechanisms of action, tolerability and available efficacy data from patients with solid tumours. We also describe the effects of the tumour microenvironment on drug delivery for both systemically administered and locally administered agents. Finally, we discuss important trends resulting from ongoing clinical trials and preclinical testing, and manufacturing and/or stability considerations that are expected to underpin the next generation of nucleic acid agents for patients with solid tumours.

Advances in lipid nanoparticle mRNA therapeutics beyond COVID-19 vaccines

The remarkable success of two lipid nanoparticle-mRNA vaccines against coronavirus disease (COVID-19) has placed the therapeutic and prophylactic potential of messenger RNA (mRNA) in the spotlight. It has also drawn attention to the indispensable role of lipid nanoparticles in enabling the effects of this nucleic acid. To date, lipid nanoparticles are the most clinically advanced non-viral platforms for mRNA delivery. This is thanks to their favorable safety profile and efficiency in protecting the nucleic acid from degradation and allowing its cellular uptake and cytoplasmic release upon endosomal escape. Moreover, the development of lipid nanoparticle-mRNA therapeutics was already a very active area of research even before the COVID-19 pandemic, which has likely only begun to bear its fruits. In this Review, we first discuss key aspects of the development of lipid nanoparticles as mRNA carriers. We then highlight promising preclinical and clinical studies involving lipid nanoparticle-mRNA formulations against infectious diseases and cancer, and to enable protein replacement or supplementation and genome editing. Finally, we elaborate on the challenges in advancing lipid nanoparticle-mRNA technology to widespread therapeutic use.

Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology

Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.

Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response

BACKGROUND

The HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize "non-self" antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.

METHODS

RNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.

RESULTS

The genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.

CONCLUSIONS

The integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient's tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

The crosstalk of CD8+ T cells and ferroptosis in cancer

Ferroptosis is an iron-dependent, novel form of programmed cell death characterized by lipid peroxidation and glutathione depletion and is widespread in a variety of diseases. CD8+ T cells are the most important effector cells of cytotoxic T cells, capable of specifically recognizing and killing cancer cells. Traditionally, CD8+ T cells are thought to induce cancer cell death mainly through perforin and granzyme, and Fas-L/Fas binding. In recent years, CD8+ T cell-derived IFN-γ was found to promote cancer cell ferroptosis by multiple mechanisms, including upregulation of IRF1 and IRF8, and downregulation of the system XC-, while cancer cells ferroptosis was shown to enhance the anti-tumor effects of CD8+ T cell by heating the tumor immune microenvironment through the exposure and release of tumor-associated specific antigens, which results in a positive feedback pathway. Unfortunately, the intra-tumoral CD8+ T cells are more sensitive to ferroptosis than cancer cells, which limits the application of ferroptosis inducers in cancer. In addition, CD8+ T cells are susceptible to being regulated by other immune cell ferroptosis in the TME, such as tumor-associated macrophages, dendritic cells, Treg, and bone marrow-derived immunosuppressive cells. Together, these factors build a complex network of CD8+ T cells and ferroptosis in cancer. Therefore, we aim to integrate relevant studies to reveal the potential mechanisms of crosstalk between CD8+ T cells and ferroptosis, and to summarize preclinical models in cancer therapy to find new therapeutic strategies in this review.

Historical perspective and future directions: computational science in immuno-oncology

Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.

Neoantigen cancer vaccines: a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy

Advancements in sequencing technologies and bioinformatics algorithms have expanded our ability to identify tumor-specific somatic mutation-derived antigens (neoantigens). While recent studies have shown neoantigens to be compelling targets for cancer immunotherapy due to their foreign nature and high immunogenicity, the need for increasingly accurate and cost-effective approaches to rapidly identify neoantigens remains a challenging task, but essential for successful cancer immunotherapy. Currently, gene expression analysis and algorithms for variant calling can be used to generate lists of mutational profiles across patients, but more care is needed to curate these lists and prioritize the candidate neoantigens most capable of inducing an immune response. A growing amount of evidence suggests that only a handful of somatic mutations predicted by mutational profiling approaches act as immunogenic neoantigens. Hence, unbiased screening of all candidate neoantigens predicted by Whole Genome Sequencing/Whole Exome Sequencing may be necessary to more comprehensively access the full spectrum of immunogenic neoepitopes. Once putative cancer neoantigens are identified, one of the largest bottlenecks in translating these neoantigens into actionable targets for cell-based therapies is identifying the cognate T cell receptors (TCRs) capable of recognizing these neoantigens. While many TCR-directed screening and validation assays have utilized bulk samples in the past, there has been a recent surge in the number of single-cell assays that provide a more granular understanding of the factors governing TCR-pMHC interactions. The goal of this review is to provide an overview of existing strategies to identify candidate neoantigens using genomics-based approaches and methods for assessing neoantigen immunogenicity. Additionally, applications, prospects, and limitations of some of the current single-cell technologies will be discussed. Finally, we will briefly summarize some of the recent models that have been used to predict TCR antigen specificity and analyze the TCR receptor repertoire.

Personalised neoantigen-based therapy in colorectal cancer

Colorectal cancer (CRC) has become one of the most common tumours with high morbidity, mortality and distinctive evolution mechanism. The neoantigens arising from the somatic mutations have become considerable treatment targets in the management of CRC. As cancer-specific aberrant peptides, neoantigens can trigger the robust host immune response and exert anti-tumour effects while minimising the emergence of adverse events commonly associated with alternative therapeutic regimens. In this review, we summarised the mechanism, generation, identification and prognostic significance of neoantigens, as well as therapeutic strategies challenges of neoantigen-based therapy in CRC. The evidence suggests that the establishment of personalised neoantigen-based therapy holds great promise as an effective treatment approach for patients with CRC.

Methods behind neoantigen prediction for personalized anticancer vaccines

Next to conventional cancer therapies, immunotherapies such as immune checkpoint inhibitors have broadened the cancer treatment landscape over the past decades. Recent advances in next generation sequencing and bioinformatics technologies have made it possible to identify a patient's own immunogenic neoantigens. These cancer neoantigens serve as important targets for personalized immunotherapy which has the benefit of being more active and effective in targeting cancer cells. This paper is a step-by-step guide discussing the different analyses and challenges encountered during in-silico neoantigen prediction. The protocol describes all the tools and steps required for the identification of immunogenic neoantigens.

Melanoma antigens recognized by T cells and their use for immunotherapy

Melanoma has been a prototype for cancer immunology research, and the mechanisms of anti-tumor T-cell responses have been extensively investigated in patients treated with various immunotherapies. Individual differences in cancer-immune status are defined mainly by cancer cell characteristics such as DNA mutations generating immunogenic neo-antigens, and oncogene activation causing immunosuppression, but also by patients' genetic backgrounds such as HLA types and genetic polymorphisms of immune related molecules, and environmental and lifestyle factors such as UV rays, smoking, gut microbiota and concomitant medications; these factors have an influence on the efficacy of immunotherapy. Recent comparative studies on responders and non-responders in immune-checkpoint inhibitor therapy using various new technologies including multi-omics analyses on genomic DNA, mRNA, metabolites and microbiota and single cell analyses of various immune cells have led to the advance of human tumor immunology and the development of new immunotherapy. Based on the new findings from these investigations, personalized cancer immunotherapies along with appropriate biomarkers and therapeutic targets are being developed for patients with melanoma. Here, we will discuss one of the essential subjects in tumor immunology: identification of immunogenic tumor antigens and their effective use in various immunotherapies including cancer vaccines and adoptive T-cell therapy.

Systems Biology Approaches for the Improvement of Oncolytic Virus-Based Immunotherapies

Oncolytic virus (OV)-based immunotherapy is mainly dependent on establishing an efficient cell-mediated antitumor immunity. OV-mediated antitumor immunity elicits a renewed antitumor reactivity, stimulating a T-cell response against tumor-associated antigens (TAAs) and recruiting natural killer cells within the tumor microenvironment (TME). Despite the fact that OVs are unspecific cancer vaccine platforms, to further enhance antitumor immunity, it is crucial to identify the potentially immunogenic T-cell restricted TAAs, the main key orchestrators in evoking a specific and durable cytotoxic T-cell response. Today, innovative approaches derived from systems biology are exploited to improve target discovery in several types of cancer and to identify the MHC-I and II restricted peptide repertoire recognized by T-cells. Using specific computation pipelines, it is possible to select the best tumor peptide candidates that can be efficiently vectorized and delivered by numerous OV-based platforms, in order to reinforce anticancer immune responses. Beyond the identification of TAAs, system biology can also support the engineering of OVs with improved oncotropism to reduce toxicity and maintain a sufficient portion of the wild-type virus virulence. Finally, these technologies can also pave the way towards a more rational design of armed OVs where a transgene of interest can be delivered to TME to develop an intratumoral gene therapy to enhance specific immune stimuli.

mRNA-Based Therapeutics in Cancer Treatment

Over the past two decades, significant technological innovations have led to messenger RNA (mRNA) becoming a promising option for developing prophylactic and therapeutic vaccines, protein replacement therapies, and genome engineering. The success of the two COVID-19 mRNA vaccines has sparked new enthusiasm for other medical applications, particularly in cancer treatment. In vitro-transcribed (IVT) mRNAs are structurally designed to resemble naturally occurring mature mRNA. Delivery of IVT mRNA via delivery platforms such as lipid nanoparticles allows host cells to produce many copies of encoded proteins, which can serve as antigens to stimulate immune responses or as additional beneficial proteins for supplements. mRNA-based cancer therapeutics include mRNA cancer vaccines, mRNA encoding cytokines, chimeric antigen receptors, tumor suppressors, and other combination therapies. To better understand the current development and research status of mRNA therapies for cancer treatment, this review focused on the molecular design, delivery systems, and clinical indications of mRNA therapies in cancer.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Proactive Immunotherapeutic Approaches against Inflammatory Breast Cancer May Improve Patient Outcomes

Inflammatory breast cancer (IBC) is highly metastatic at the onset of the disease with no IBC-specific treatments, resulting in dismal patient survival. IBC treatment is a clear unmet clinical need. This commentary highlights findings from a recent seminal approach in which pembrolizumab, a checkpoint inhibitor against programmed cell death protein 1 (PD-1), was provided to a triple-negative IBC patient as a neoadjuvant immune therapy combined with anthracycline-taxane-based chemotherapy. We highlight the findings of the case report and offer a perspective on taking a proactive approach to deploy approved immune checkpoint inhibitors. On the basis of our recently published research study, we propose in situ vaccination with direct injection of immunostimulatory agents into the tumor as an option to improve outcomes safely, effectively, and economically for IBC patients.