Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia

The effect of smoking on tumor immunoediting: Friend or foe?

The recognition of smoking as an independent risk factor for lung cancer has become a widely accepted within the realm of respiratory medicine. The emergence of tumor immunotherapy has notably enhanced the prognosis for numerous late-stage cancer patients. Nevertheless, some studies have noted a tendency for lung cancer patients who smoke to derive greater benefit from immunotherapy. This observation has sparked increased interest in the interaction between smoking and the immune response to tumors in lung cancer. The concept of cancer immunoediting has shed light on the intricate and nuanced relationship between the immune system and tumors. Starting from the perspectives of immune surveillance, immune equilibrium, and immune evasion, this narrative review explores how smoking undermines the immune response against tumor cells and induces the generation of tumor neoantigens, and examines other behaviors that trigger tumor immune evasion. By elucidating these aspects, the review concludes that smoking is not conducive to tumor immunoediting.

Targeting Pivotal Hallmarks of Cancer for Enhanced Therapeutic Strategies in Triple-Negative Breast Cancer Treatment-In Vitro, In Vivo and Clinical Trials Literature Review

This literature review provides a comprehensive overview of triple-negative breast cancer (TNBC) and explores innovative targeted therapies focused on specific hallmarks of cancer cells, aiming to revolutionize breast cancer treatment. TNBC, characterized by its lack of expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), presents distinct features, categorizing these invasive breast tumors into various phenotypes delineated by key elements in molecular assays. This article delves into the latest advancements in therapeutic strategies targeting components of the tumor microenvironment and pivotal hallmarks of cancer: deregulating cellular metabolism and the Warburg effect, acidosis and hypoxia, the ability to metastasize and evade the immune system, aiming to enhance treatment efficacy while mitigating systemic toxicity. Insights from in vitro and in vivo studies and clinical trials underscore the promising effectiveness and elucidate the mechanisms of action of these novel therapeutic interventions for TNBC, particularly in cases refractory to conventional treatments. The integration of targeted therapies tailored to the molecular characteristics of TNBC holds significant potential for optimizing clinical outcomes and addressing the pressing need for more effective treatment options for this aggressive subtype of breast cancer.

mRNA-based therapeutics: looking beyond COVID-19 vaccines

Recent advances in mRNA technology and its delivery have enabled mRNA-based therapeutics to enter a new era in medicine. The rapid, potent, and transient nature of mRNA-encoded proteins, without the need to enter the nucleus or the risk of genomic integration, makes them desirable tools for treatment of a range of diseases, from infectious diseases to cancer and monogenic disorders. The rapid pace and ease of mass-scale manufacturability of mRNA-based therapeutics supported the global response to the COVID-19 pandemic. Nonetheless, challenges remain with regards to mRNA stability, duration of expression, delivery efficiency, and targetability, to broaden the applicability of mRNA therapeutics beyond COVID-19 vaccines. By learning from the rapidly expanding preclinical and clinical studies, we can optimise the mRNA platform to meet the clinical needs of each disease. Here, we will summarise the recent advances in mRNA technology; its use in vaccines, immunotherapeutics, protein replacement therapy, and genomic editing; and its delivery to desired specific cell types and organs for development of a new generation of targeted mRNA-based therapeutics.

Mechanical forces amplify TCR mechanotransduction in T cell activation and function

Adoptive T cell immunotherapies, including engineered T cell receptor (eTCR) and chimeric antigen receptor (CAR) T cell immunotherapies, have shown efficacy in treating a subset of hematologic malignancies, exhibit promise in solid tumors, and have many other potential applications, such as in fibrosis, autoimmunity, and regenerative medicine. While immunoengineering has focused on designing biomaterials to present biochemical cues to manipulate T cells ex vivo and in vivo, mechanical cues that regulate their biology have been largely underappreciated. This review highlights the contributions of mechanical force to several receptor-ligand interactions critical to T cell function, with central focus on the TCR-peptide-loaded major histocompatibility complex (pMHC). We then emphasize the role of mechanical forces in (i) allosteric strengthening of the TCR-pMHC interaction in amplifying ligand discrimination during T cell antigen recognition prior to activation and (ii) T cell interactions with the extracellular matrix. We then describe approaches to design eTCRs, CARs, and biomaterials to exploit TCR mechanosensitivity in order to potentiate T cell manufacturing and function in adoptive T cell immunotherapy.

Recent advances in immunopeptidomic-based tumor neoantigen discovery

The role of aberrantly expressed proteins in tumors in driving immune-mediated control of cancer has been well documented for more than five decades. Today, we know that both aberrantly expressed normal proteins as well as mutant proteins (neoantigens) can function as tumor antigens in both humans and mice. Next-generation sequencing (NGS) and high-resolution mass spectrometry (MS) technologies have made significant advances since the early 2010s, enabling detection of rare but clinically relevant neoantigens recognized by T cells. MS profiling of tumor-specific immunopeptidomes remains the most direct method to identify mutant peptides bound to cellular MHC. However, the need for use of large numbers of cells or significant amounts of tumor tissue to achieve neoantigen detection has historically limited the application of MS. Newer, more sensitive MS technologies have recently demonstrated the capacities to detect neoantigens from fewer cells. Here, we highlight recent advancements in immunopeptidomics-based characterization of tumor-specific neoantigens. Various tumor antigen categories and neoantigen identification approaches are also discussed. Furthermore, we summarize recent reports that achieved successful tumor neoantigen detection by MS using a variety of starting materials, MS acquisition modes, and novel ion mobility devices.

Neo-intline: integrated pipeline enables neoantigen design through the in-silico presentation of T-cell epitope

Neoantigen vaccines are one of the most effective immunotherapies for personalized tumour treatment. The current immunogen design of neoantigen vaccines is usually based on whole-genome sequencing (WGS) and bioinformatics prediction that focuses on the prediction of binding affinity between peptide and MHC molecules, ignoring other peptide-presenting related steps. This may result in a gap between high prediction accuracy and relatively low clinical effectiveness. In this study, we designed an integrated in-silico pipeline, Neo-intline, which started from the SNPs and indels of the tumour samples to simulate the presentation process of peptides in-vivo through an integrated calculation model. Validation on the benchmark dataset of TESLA and clinically validated neoantigens illustrated that neo-intline could outperform current state-of-the-art tools on both sample level and melanoma level. Furthermore, by taking the mouse melanoma model as an example, we verified the effectiveness of 20 neoantigens, including 10 MHC-I and 10 MHC-II peptides. The in-vitro and in-vivo experiments showed that both peptides predicted by Neo-intline could recruit corresponding CD4+ T cells and CD8+ T cells to induce a T-cell-mediated cellular immune response. Moreover, although the therapeutic effect of neoantigen vaccines alone is not sufficient, combinations with other specific therapies, such as broad-spectrum immune-enhanced adjuvants of granulocyte-macrophage colony-stimulating factor (GM-CSF) and polyinosinic-polycytidylic acid (poly(I:C)), or immune checkpoint inhibitors, such as PD-1/PD-L1 antibodies, can illustrate significant anticancer effects on melanoma. Neo-intline can be used as a benchmark process for the design and screening of immunogenic targets for neoantigen vaccines.

Unraveling tumor specific neoantigen immunogenicity prediction: a comprehensive analysis

Introduction

Identification of tumor specific neoantigen (TSN) immunogenicity is crucial to develop peptide/mRNA based anti-tumoral vaccines and/or adoptive T-cell immunotherapies; thus, accurate in-silico classification/prioritization proves critical for cost-effective clinical applications. Several methods were proposed as TSNs immunogenicity predictors; however, comprehensive performance comparison is still lacking due to the absence of well documented and adequate TSN databases.

Methods

Here, by developing a new curated database having 199 TSNs with experimentally-validated MHC-I presentation and positive/negative immune response (ITSNdb), sixteen metrics were evaluated as immunogenicity predictors. In addition, by using a dataset emulating patient derived TSNs and immunotherapy cohorts containing predicted TSNs for tumor neoantigen burden (TNB) with outcome association, the metrics were evaluated as TSNs prioritizers and as immunotherapy response biomarkers.

Results

Our results show high performance variability among methods, highlighting the need for substantial improvement. Deep learning predictors were top ranked on ITSNdb but show discrepancy on validation databases. In overall, current predicted TNB did not outperform existing biomarkers.

Conclusion

Recommendations for their clinical application and the ITSNdb are presented to promote development and comparison of computational TSNs immunogenicity predictors.

Immunosurveillance shapes the emergence of neo-epitope landscapes of sarcomas, revealing prime targets for immunotherapy

T cells recognize tumor-derived mutated peptides presented on MHC by tumors. The recognition of these neo-epitopes leads to rejection of tumors, an event that is critical for successful cancer immunosurveillance. Determination of tumor-rejecting neo-epitopes in human tumors has proved difficult, though recently developed systems approaches are becoming increasingly useful at evaluating their immunogenicity. We have used the differential aggretope index to determine the neo-epitope burden of sarcomas and observed a conspicuously titrated antigenic landscape, ranging from the highly antigenic osteosarcomas to the low antigenic leiomyosarcomas and liposarcomas. We showed that the antigenic landscape of the tumors inversely reflected the historical T cell responses in the tumor-bearing patients. We predicted that highly antigenic tumors with poor antitumor T cell responses, such as osteosarcomas, would be responsive to T cell-based immunotherapy regimens and demonstrated this in a murine osteosarcoma model. Our study presents a potentially novel pipeline for determining antigenicity of human tumors, provides an accurate predictor of potential neo-epitopes, and will be an important indicator of which cancers to target with T cell-enhancing immunotherapy.

Oncogenic drivers dictate immune control of acute myeloid leukemia

Acute myeloid leukemia (AML) is a genetically heterogeneous, aggressive hematological malignancy induced by distinct oncogenic driver mutations. The effect of specific AML oncogenes on immune activation or suppression is unclear. Here, we examine immune responses in genetically distinct models of AML and demonstrate that specific AML oncogenes dictate immunogenicity, the quality of immune response and immune escape through immunoediting. Specifically, expression of Nras^G12D alone is sufficient to drive a potent anti-leukemia response through increased MHC Class II expression that can be overcome with increased expression of Myc. These data have important implications for the design and implementation of personalized immunotherapies for patients with AML.

Preliminary clinical study of personalized neoantigen vaccine therapy for microsatellite stability (MSS)-advanced colorectal cancer

Immunotherapy based on immune checkpoint inhibitors (ICIs) has provided revolutionary results in treating various cancers. However, its efficacy in colorectal cancer (CRC), especially in microsatellite stability-CRC, is limited. This study aimed to observe the efficacy of personalized neoantigen vaccine in treating MSS-CRC patients with recurrence or metastasis after surgery and chemotherapy. Candidate neoantigens were analyzed from whole-exome and RNA sequencing of tumor tissues. The safety and immune response were assessed through adverse events and ELISpot. The clinical response was evaluated by progression-free survival (PFS), imaging examination, clinical tumor marker detection, circulating tumor DNA (ctDNA) sequencing. Changes in health-related quality of life were measured by the FACT-C scale. A total of six MSS-CRC patients with recurrence or metastasis after surgery and chemotherapy were administered with personalized neoantigen vaccines. Neoantigen-specific immune response was observed in 66.67% of the vaccinated patients. Four patients remained progression-free up to the completion of clinical trial. They also had a significantly longer progression-free survival time than the other two patients without neoantigen-specific immune response (19 vs. 11 months). Changes in health-related quality of life improved for almost all patients after the vaccine treatment. Our results shown that personalized neoantigen vaccine therapy is likely to be a safe, feasible and effective strategy for MSS-CRC patients with postoperative recurrence or metastasis.

The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia

Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.

CAR T-cells for colorectal cancer immunotherapy: Ready to go?

Chimeric antigen receptor (CAR) T-cells represent a new genetically engineered cell-based immunotherapy tool against cancer. The use of CAR T-cells has revolutionized the therapeutic approach for hematological malignancies. Unfortunately, there is a long way to go before this treatment can be developed for solid tumors, including colorectal cancer. CAR T-cell therapy for colorectal cancer is still in its early stages, and clinical data are scarce. Major limitations of this therapy include high toxicity, relapses, and an impermeable tumor microenvironment for CAR T-cell therapy in colorectal cancer. In this review, we summarize current knowledge, highlight challenges, and discuss perspectives regarding CAR T-cell therapy in colorectal cancer.

Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma

Background

Recent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.

Methods

In this study, we comprehensively investigated the expression, prognostic value, and immune significance of FNDC3B in glioma using several databases and a variety of machine learning algorithms. RNA expression data and clinical information of 529 patients from the Cancer Genome Atlas (TCGA) and 1319 patients from Chinese Glioma Genome Atlas (CGGA) databases were downloaded for further investigation. To evaluate whether FNDC3B expression can predict clinical prognosis of glioma, we constructed a clinical nomogram to estimate long-term survival probabilities. The predicted nomogram was validated by CGGA cohorts. Differentially expressed genes (DEGs) were detected by the Wilcoxon test based on the TCGA-LGG dataset and the weighted gene co-expression network analysis (WGCNA) was implemented to identify the significant module associated with the expression level of FNDC3B. Furthermore, we investigated the correlation between FNDC3B with cancer immune infiltrates using TISIDB, ESTIMATE, and CIBERSORTx.

Results

Higher FNDC3B expression displayed a remarkably worse overall survival and the expression level of FNDC3B was an independent prognostic indicator for patients with glioma. Based on TCGA LGG dataset, a co-expression network was established and the hub genes were identified. FNDC3B expression was positively correlated to the tumor-infiltrating lymphocytes and immune infiltration score, and high FNDC3B expression was accompanied by the increased expression of B7-H3, PD-L1, TIM-3, PD-1, and CTLA-4. Moreover, expression of FNDC3B was significantly associated with infiltrating levels of several types of immune cells and most of their gene markers in glioma.

Conclusion

This study demonstrated that FNDC3B may be involved in the occurrence and development of glioma and can be regarded as a promising prognostic and immunotherapeutic biomarker for the treatment of glioma.

Comprehensive Viral Genotyping Reveals Prognostic Viral Phylogenetic Groups in HPV16-Associated Squamous Cell Carcinoma of the Oropharynx

Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States and is primarily caused by HPV subtype 16 (HPV16). Favorable treatment outcomes have led to increasing interest in treatment deescalation to reduce treatment-related morbidity. Prognostic biomarkers are needed to identify appropriately low-risk patients for reduced treatment intensity. Targeted DNA sequencing including all HPV16 open reading frames was performed on tumors from 104 patients with HPV16+ OPSCC treated at a single center. Genotypes closely related to the HPV16-A1 reference were associated with increased numbers of somatic copy-number variants in the human genome and poor recurrence-free survival (RFS). Genotypes divergent from HPV16-A1 were associated with favorable RFS. These findings were independent of tobacco smoke exposure. Total RNA sequencing was performed on a second independent cohort of 89 HPV16+ OPSCC cases. HPV16 genotypes divergent from HPV16-A1 were again validated in this independent cohort, to be prognostic of improved RFS in patients with moderate (less than 30 pack-years) or low (no more than 10 pack-years) of tobacco smoke exposure. In summary, we show in two independent cohorts that viral sequence divergence from the HPV16-A1 reference is correlated with improved RFS in patients with moderate or low tobacco smoke exposure.

IMPLICATIONS

HPV16 genotype is a potential biomarker that could be easily adopted to guide therapeutic decision-making related to deescalation therapy.

Single-cell sequencing reveals CD133+CD44−-originating evolution and novel stemness related variants in human colorectal cancer

Background

Tumor heterogeneity of human colorectal cancer (CRC)-initiating cells (CRCICs) in cancer tissues often represents aggressive features of cancer progression. For high-resolution examination of CRCICs, we performed single-cell whole-exome sequencing (scWES) and bulk cell targeted exome sequencing (TES) of CRCICs to investigate stemness-specific somatic alterations or clonal evolution.

Methods

Single cells of three subpopulations of CRCICs (CD133⁺CD44⁺, CD133⁻CD44⁺, and CD133⁺CD44⁻ cells), CRC cells (CRCCs), and control cells from one CRC tissue were sorted for scWES. Then, we set up a mutation panel from scWES data and TES was used to validate mutation distribution and clonal evolution in additional 96 samples (20 patients) those were also sorted into the same three groups of CRCICs and CRCCs. The knock-down experiments were used to analyze stemness-related mutant genes. Neoantigens of these mutant genes and their MHC binding affinity were also analyzed.

Findings

Clonal evolution analysis of scWES and TES showed that the CD133⁺CD44⁻ CRCICs were the likely origin of CRC before evolving into other groups of CRCICs/CRCCs. We revealed that AHNAK2, PLIN4, HLA-B, ALK, CCDC92 and ALMS1 genes were specifically mutated in CRCICs followed by the validation of their functions. Furthermore, four predicted neoantigens of AHNAK2 were identified and validated, which might have applications in immunotherapy for CRC patients.

Interpretation

All the integrative analyses above revealed clonal evolution of CRC and new markers for CRCICs and demonstrate the important roles of CRCICs in tumorigenesis and progression of CRCs.

Funding

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Comprehensive Analysis of the Immunogenomics of Triple-Negative Breast Cancer Brain Metastases From LCCC1419

Background

Triple negative breast cancer (TNBC) is an aggressive variant of breast cancer that lacks the expression of estrogen and progesterone receptors (ER and PR) and HER2. Nearly 50% of patients with advanced TNBC will develop brain metastases (BrM), commonly with progressive extracranial disease. Immunotherapy has shown promise in the treatment of advanced TNBC; however, the immune contexture of BrM remains largely unknown. We conducted a comprehensive analysis of TNBC BrM and matched primary tumors to characterize the genomic and immune landscape of TNBC BrM to inform the development of immunotherapy strategies in this aggressive disease.

Methods

Whole-exome sequencing (WES) and RNA sequencing were conducted on formalin-fixed, paraffin-embedded samples of BrM and primary tumors of patients with clinical TNBC (n = 25, n = 9 matched pairs) from the LCCC1419 biobank at UNC—Chapel Hill. Matched blood was analyzed by DNA sequencing as a comparison for tumor WES for the identification of somatic variants. A comprehensive genomics assessment, including mutational and copy number alteration analyses, neoantigen prediction, and transcriptomic analysis of the tumor immune microenvironment were performed.

Results

Primary and BrM tissues were confirmed as TNBC (23/25 primaries, 16/17 BrM) by immunohistochemistry and of the basal intrinsic subtype (13/15 primaries and 16/19 BrM) by PAM50. Compared to primary tumors, BrM demonstrated a higher tumor mutational burden. TP53 was the most frequently mutated gene and was altered in 50% of the samples. Neoantigen prediction showed elevated cancer testis antigen- and endogenous retrovirus-derived MHC class I-binding peptides in both primary tumors and BrM and predicted that single-nucleotide variant (SNV)-derived peptides were significantly higher in BrM. BrM demonstrated a reduced immune gene signature expression, although a signature associated with fibroblast-associated wound healing was elevated in BrM. Metrics of T and B cell receptor diversity were also reduced in BrM.

Conclusions

BrM harbored higher mutational burden and SNV-derived neoantigen expression along with reduced immune gene signature expression relative to primary TNBC. Immune signatures correlated with improved survival, including T cell signatures. Further research will expand these findings to other breast cancer subtypes in the same biobank. Exploration of immunomodulatory approaches including vaccine applications and immune checkpoint inhibition to enhance anti-tumor immunity in TNBC BrM is warranted.

Therapeutic Cancer Vaccines—Antigen Discovery and Adjuvant Delivery Platforms

For decades, vaccines have played a significant role in protecting public and personal health against infectious diseases and proved their great potential in battling cancers as well. This review focused on the current progress of therapeutic subunit vaccines for cancer immunotherapy. Antigens and adjuvants are key components of vaccine formulations. We summarized several classes of tumor antigens and bioinformatic approaches of identification of tumor neoantigens. Pattern recognition receptor (PRR)-targeting adjuvants and their targeted delivery platforms have been extensively discussed. In addition, we emphasized the interplay between multiple adjuvants and their combined delivery for cancer immunotherapy.

Therapeutic cancer vaccines: From biological mechanisms and engineering to ongoing clinical trials

Therapeutic vaccines are currently at the forefront of medical innovation. Various endeavors have been made to develop more consolidated approaches to producing nucleic acid-based vaccines, both DNA and mRNA vaccines. These innovations have continued to propel therapeutic platforms forward, especially for mRNA vaccines, after the successes that drove emergency FDA approval of two mRNA vaccines against SARS-CoV-2. These vaccines use modified mRNAs and lipid nanoparticles to improve stability, antigen translation, and delivery by evading innate immune activation. Simple alterations of mRNA structure- such as non-replicating, modified, or self-amplifying mRNAs- can provide flexibility for future vaccine development. For protein vaccines, the use of long synthetic peptides of tumor antigens instead of short peptides has further enhanced antigen delivery success and peptide stability. Efforts to identify and target neoantigens instead of antigens shared between tumor cells and normal cells have also improved protein-based vaccines. Other approaches use inactivated patient-derived tumor cells to elicit immune responses, or purified tumor antigens are given to patient-derived dendritic cells that are activated in vitro prior to reinjection. This review will discuss recent developments in therapeutic cancer vaccines such as, mode of action and engineering new types of anticancer vaccines, in order to summarize the latest preclinical and clinical data for further discussion of ongoing clinical endeavors in the field.

Physicochemical Heuristics for Identifying High Fidelity, Near-Native Structural Models of Peptide/MHC Complexes

There is long-standing interest in accurately modeling the structural features of peptides bound and presented by class I MHC proteins. This interest has grown with the advent of rapid genome sequencing and the prospect of personalized, peptide-based cancer vaccines, as well as the development of molecular and cellular therapeutics based on T cell receptor recognition of peptide-MHC. However, while the speed and accessibility of peptide-MHC modeling has improved substantially over the years, improvements in accuracy have been modest. Accuracy is crucial in peptide-MHC modeling, as T cell receptors are highly sensitive to peptide conformation and capturing fine details is therefore necessary for useful models. Studying nonameric peptides presented by the common class I MHC protein HLA-A*02:01, here we addressed a key question common to modern modeling efforts: from a set of models (or decoys) generated through conformational sampling, which is best? We found that the common strategy of decoy selection by lowest energy can lead to substantial errors in predicted structures. We therefore adopted a data-driven approach and trained functions capable of predicting near native decoys with exceptionally high accuracy. Although our implementation is limited to nonamer/HLA-A*02:01 complexes, our results serve as an important proof of concept from which improvements can be made and, given the significance of HLA-A*02:01 and its preference for nonameric peptides, should have immediate utility in select immunotherapeutic and other efforts for which structural information would be advantageous.

Cancer vaccines: past, present and future; a review article

Immunotherapy and vaccines have revolutionized disease treatment and prevention. Vaccines against infectious diseases have been in use for several decades. In contrast, only few cancer vaccines have been approved for human use. These include preventative vaccines against infectious agents associated with cancers, and therapeutic vaccines used as immunotherapy agents to treat cancers. Challenges in developing cancer vaccines include heterogeneity within and between cancer types, screening and identification of appropriate tumour-specific antigens, and the choice of vaccine delivery platforms. Recent advances in all of these areas and the lessons learnt from COVID-19 vaccines have significantly boosted interest in cancer vaccines. Further advances in these areas are expected to facilitate development of effective novel cancer vaccines. In this review, we aim to discuss the past, the present, and the future of cancer vaccines.

NeoSplice: a bioinformatics method for prediction of splice variant neoantigens

Motivation

Splice variant neoantigens are a potential source of tumor-specific antigen (TSA) that are shared between patients in a variety of cancers, including acute myeloid leukemia. Current tools for genomic prediction of splice variant neoantigens demonstrate promise. However, many tools have not been well validated with simulated and/or wet lab approaches, with no studies published that have presented a targeted immunopeptidome mass spectrometry approach designed specifically for identification of predicted splice variant neoantigens.

Results

In this study, we describe NeoSplice, a novel computational method for splice variant neoantigen prediction based on (i) prediction of tumor-specific k-mers from RNA-seq data, (ii) alignment of differentially expressed k-mers to the splice graph and (iii) inference of the variant transcript with MHC binding prediction. NeoSplice demonstrates high sensitivity and precision (>80% on average across all splice variant classes) through in silico simulated RNA-seq data. Through mass spectrometry analysis of the immunopeptidome of the K562.A2 cell line compared against a synthetic peptide reference of predicted splice variant neoantigens, we validated 4 of 37 predicted antigens corresponding to 3 of 17 unique splice junctions. Lastly, we provide a comparison of NeoSplice against other splice variant prediction tools described in the literature. NeoSplice provides a well-validated platform for prediction of TSA vaccine targets for future cancer antigen vaccine studies to evaluate the clinical efficacy of splice variant neoantigens.

Availability and implementation

https://github.com/Benjamin-Vincent-Lab/NeoSplice.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Hallmarks of Resistance to Immune-Checkpoint Inhibitors

Immune-checkpoint inhibitors (ICI), although revolutionary in improving long-term survival outcomes, are mostly effective in patients with immune-responsive tumors. Most patients with cancer either do not respond to ICIs at all or experience disease progression after an initial period of response. Treatment resistance to ICIs remains a major challenge and defines the biggest unmet medical need in oncology worldwide. In a collaborative workshop, thought leaders from academic, biopharma, and nonprofit sectors convened to outline a resistance framework to support and guide future immune-resistance research. Here, we explore the initial part of our effort by collating seminal discoveries through the lens of known biological processes. We highlight eight biological processes and refer to them as immune resistance nodes. We examine the seminal discoveries that define each immune resistance node and pose critical questions, which, if answered, would greatly expand our notion of immune resistance. Ultimately, the expansion and application of this work calls for the integration of multiomic high-dimensional analyses from patient-level data to produce a map of resistance phenotypes that can be utilized to guide effective drug development and improved patient outcomes.

mRNA cancer vaccines: Advances, trends and challenges

Patients exhibit good tolerance to messenger ribonucleic acid (mRNA) vaccines, and the choice of encoded molecules is flexible and diverse. These vaccines can be engineered to express full-length antigens containing multiple epitopes without major histocompatibility complex (MHC) restriction, are relatively easy to control and can be rapidly mass produced. In 2021, the U.S. Food and Drug Administration (FDA) approved the first mRNA-based coronavirus disease 2019 (COVID-19) vaccine produced by Pfizer and BioNTech, which has generated enthusiasm for mRNA vaccine research and development. Based on the above characteristics and the development of mRNA vaccines, mRNA cancer vaccines have become a research hotspot and have undergone rapid development, especially in the last five years. This review analyzes the advances in mRNA cancer vaccines from various perspectives, including the selection and expression of antigens/targets, the application of vectors and adjuvants, different administration routes, and preclinical evaluation, to reflect the trends and challenges associated with these vaccines.

Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation

Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment.

Noncoding RNAs and Their Response Predictive Value in Azacitidine-treated Patients With Myelodysplastic Syndrome and Acute Myeloid Leukemia With Myelodysplasia-related Changes

BACKGROUND/AIM

Prediction of response to azacitidine (AZA) treatment is an important challenge in hematooncology. In addition to protein coding genes (PCGs), AZA efficiency is influenced by various noncoding RNAs (ncRNAs), including long ncRNAs (lncRNAs), circular RNAs (circRNAs), and transposable elements (TEs).

MATERIALS AND METHODS

RNA sequencing was performed in patients with myelodysplastic syndromes or acute myeloid leukemia before AZA treatment to assess contribution of ncRNAs to AZA mechanisms and propose novel disease prediction biomarkers.

RESULTS

Our analyses showed that lncRNAs had the strongest predictive potential. The combined set of the best predictors included 14 lncRNAs, and only four PCGs, one circRNA, and no TEs. Epigenetic regulation and recombinational repair were suggested as crucial for AZA response, and network modeling defined three deregulated lncRNAs (CTC-482H14.5, RP11-419K12.2, and RP11-736I24.4) associated with these processes.

CONCLUSION

The expression of various ncRNAs can influence the effect of AZA and new ncRNA-based predictive biomarkers can be defined.

Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets.

Clonal Evolution of High-Risk Chronic Lymphocytic Leukemia: A Contemporary Perspective

Clonal evolution represents the natural process through which cancer cells continuously search for phenotypic advantages that enable them to develop and expand within microenvironmental constraints. In chronic lymphocytic leukemia (CLL), clonal evolution underpins leukemic progression and therapeutic resistance, with differences in clonal evolutionary dynamics accounting for its characteristically diverse clinical course. The past few years have witnessed profound changes in our understanding of CLL clonal evolution, facilitated by a maturing definition of high-risk CLL and an increasing sophistication of next-generation sequencing technology. In this review, we offer a modern perspective on clonal evolution of high-risk CLL, highlighting recent discoveries, paradigm shifts and unresolved questions. We appraise recent advances in our understanding of the molecular basis of CLL clonal evolution, focusing on the genetic and non-genetic sources of intratumoral heterogeneity, as well as tumor-immune dynamics. We review the technological innovations, particularly in single-cell technology, which have fostered these advances and represent essential tools for future discoveries. In addition, we discuss clonal evolution within several contexts of particular relevance to contemporary clinical practice, including the settings of therapeutic resistance to CLL targeted therapy and immunotherapy, as well as Richter transformation of CLL to high-grade lymphoma.

Targeting the DNA damage response in immuno-oncology: developments and opportunities

Immunotherapy has revolutionized cancer treatment and substantially improved patient outcome with regard to multiple tumour types. However, most patients still do not benefit from such therapies, notably because of the absence of pre-existing T cell infiltration. DNA damage response (DDR) deficiency has recently emerged as an important determinant of tumour immunogenicity. A growing body of evidence now supports the concept that DDR-targeted therapies can increase the antitumour immune response by (1) promoting antigenicity through increased mutability and genomic instability, (2) enhancing adjuvanticity through the activation of cytosolic immunity and immunogenic cell death and (3) favouring reactogenicity through the modulation of factors that control the tumour-immune cell synapse. In this Review, we discuss the interplay between the DDR and anticancer immunity and highlight how this dynamic interaction contributes to shaping tumour immunogenicity. We also review the most innovative preclinical approaches that could be used to investigate such effects, including recently developed ex vivo systems. Finally, we highlight the therapeutic opportunities presented by the exploitation of the DDR-anticancer immunity interplay, with a focus on those in early-phase clinical development.

Individualized Proteogenomics Reveals the Mutational Landscape of Melanoma Patients in Response to Immunotherapy

Simple Summary

Melanoma is the most aggressive form of skin cancer, with a rapidly increasing incidence rate. Due to ineffective treatment options in the late stage melanoma, patients have an overall poor prognosis. Over the last decades, the role of the immune system in the control of tumor progression has been established and immune checkpoint inhibitors (ICi) have shown remarkable clinical activity. While current trials suggest durable responses in patient under ICi therapy, there is increasing evidence pointing towards existence of innate and acquired resistance to ICi therapy; and it is now clear that personalized medicine will be critical for effective patient therapy. Proteogenomics is a powerful tool to study the mode of action of disease-associated mutations at the genome, transcriptome, proteome and PTM level. Here, we applied a proteogenomic workflow to study melanoma samples from human tumors. Such workflow may be applicable to other patient-derived samples and different cancer types.

Abstract

Immune checkpoint inhibitors are used to restore or augment antitumor immune responses and show great promise in the treatment of melanoma and other types of cancers. However, only a small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by the accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development, tumor heterogeneity and resistance mechanisms. Using this approach, we characterized the mutational landscape of four clinical melanoma patients. This enabled the quantification of hundreds of sample-specific amino acid variants, among them many that were previously not reported in melanoma. Changes in abundance at the protein and phosphorylation site levels revealed patient-specific over-represented pathways, notably linked to melanoma development (MAPK1 activation) or immunotherapy (NLRP1 inflammasome). Personalized data integration resulted in the prediction of protein drug targets, such as the drugs vandetanib and bosutinib, which were experimentally validated and led to a reduction in the viability of tumor cells. Our study emphasizes the potential of proteogenomic approaches to study personalized mutational landscapes, signaling networks and therapy options.

Proteogenomics Reveals Perturbed Signaling Networks in Malignant Melanoma Cells Resistant to BRAF Inhibition

Analysis of nucleotide variants is a cornerstone of cancer medicine. Although only 2% of the genomic sequence is protein coding, mutations occurring in these regions have the potential to influence protein structure or modification status and may have severe impact on disease aetiology. Proteogenomics enables the analysis of sample-specific nonsynonymous nucleotide variants with regard to their effect at the proteome and phosphoproteome levels. Here, we developed a proof-of-concept proteogenomics workflow and applied it to the malignant melanoma cell line A375. Initially, we studied the resistance to serine/threonine-protein kinase B-raf (BRAF) inhibitor (BRAFi) vemurafenib in A375 cells. This allowed identification of several oncogenic nonsynonymous nucleotide variants, including a gain-of-function variant on aurora kinase A (AURKA) at F31I. We also detected significant changes in abundance among (phospho)proteins, which led to reactivation of the MAPK signaling pathway in BRAFi-resistant A375 cells. Upon reconstruction of the multiomic integrated signaling networks, we predicted drug therapies with the potential to disrupt BRAFi resistance mechanism in A375 cells. Notably, we showed that AURKA inhibition is effective and specific against BRAFi-resistant A375 cells. Subsequently, we investigated amino acid variants that interfere with protein posttranslational modification (PTM) status and potentially influence A375 cell signaling irrespective of BRAFi resistance. Mass spectrometry (MS) measurements confirmed variant-driven PTM changes in 12 proteins. Among them was the runt-related transcription factor 1 (RUNX1) displaying a variant on a known phosphorylation site S(Ph)276L. We confirmed the loss of phosphorylation site by MS and demonstrated the impact of this variant on RUNX1 interactome.

Targeting the p53 Pathway in CLL: State of the Art and Future Perspectives

The p53 pathway is a desirable therapeutic target, owing to its critical role in the maintenance of genome integrity. This is exemplified in chronic lymphocytic leukemia (CLL), one of the most common adult hematologic malignancies, in which functional loss of p53 arising from genomic aberrations are frequently associated with clonal evolution, disease progression, and therapeutic resistance, even in the contemporary era of CLL targeted therapy and immunotherapy. Targeting the 'undruggable' p53 pathway therefore arguably represents the holy grail of cancer research. In recent years, several strategies have been proposed to exploit p53 pathway defects for cancer treatment. Such strategies include upregulating wild-type p53, restoring tumor suppressive function in mutant p53, inducing synthetic lethality by targeting collateral genome maintenance pathways, and harnessing the immunogenicity of p53 pathway aberrations. In this review, we will examine the biological and clinical implications of p53 pathway defects, as well as our progress towards development of therapeutic approaches targeting the p53 pathway, specifically within the context of CLL. We will appraise the opportunities and pitfalls associated with these therapeutic strategies, and evaluate their place amongst the array of new biological therapies for CLL.

The Role of Neoantigens in Cancer Immunotherapy

Somatic mutation-derived neoantigens, expressed only on tumor cells, may elicit antitumor T-cell responses in cancer immunotherapies with minimal immune tolerance. Neoantigens can be identified by multiple bioinformatics technologies, mainly based on whole-exome sequencing. Personalized cancer vaccines and adoptive T cell therapies are two primary treatment modalities targeting neoantigens, and both of them have shown promising therapeutic effects. This review, summarizes the history of neoantigen-related tumor control, introduces recent neoantigen screening and identification methods, and discusses the role of neoantigen in cancer immunotherapies. Moreover, we propose the challenges of targeting neoantigens for cancer treatment.

An Integrated Approach for Discovering Noncanonical MHC-I Peptides Encoded by Small Open Reading Frames

MHC-I peptides are a group of important immunopeptides presented by major histocompatibility complex (MHC) on the cell surface for immune recognition. The majority of reported MHC-I peptides are derived from protein coding sequences, and noncanonical peptides translated from small open reading frames (sORF) are largely unknown due to the lack of accurate and sensitive detection methods. Herein we report an efficient approach that implements complementary bioinformatic strategies to improve the identification of noncanonical MHC-I peptides. In a database search strategy, noncanonical immunopeptides mapping was optimized by combining three complementary pipelines to construct predicted sORF databases from Ribo-seq data. In a de novo peptide sequencing strategy, MS data search results were filtered against sORF databases to pin down additional noncanonical immunopeptides. In total, 308 noncanonical immunopeptides were identified from two tumor cell lines with selected ones vigorously validated. Our approach is a handy solution to identify noncanonical MHC peptides with Ribo-seq and MS data. Meanwhile, the novel noncanonical immunopeptides identified with this method could shed insights on fundamental immunology as well as cancer immunotherapies.

Distinct evolutionary paths in chronic lymphocytic leukemia during resistance to the graft-versus-leukemia effect

Leukemic relapse remains a major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis for relapse of advanced lymphoid malignancies remains incompletely understood and may involve escape from the graft-versus-leukemia (GvL) effect. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features influence transplant outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic, and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics. Early relapses after allo-HSCT exhibited notable genetic stability; single CLL cell transcriptional analysis demonstrated a cellular heterogeneity that was static over time. In contrast, CLL cells relapsing late after allo-HSCT displayed notable genetic evolution and evidence of neoantigen depletion, consistent with marked single-cell transcriptional shifts that were unique to each patient. We observed a greater rate of epigenetic change for late relapses not seen in early relapses or relapses after chemotherapy alone, suggesting that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for human leukocyte antigen (HLA) loss was observed, even when present in pretransplant subpopulations. Gain of stem cell modules was a common signature associated with leukemia relapse regardless of posttransplant relapse kinetics. These data elucidate the biological pathways that underlie GvL resistance and posttransplant relapse.

Landscape and selection of vaccine epitopes in SARS-CoV-2

BACKGROUND

Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE).

METHODS

We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites.

RESULTS

From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8+ and 284 CD4+ T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides.

CONCLUSIONS

Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.

Identification of biomarkers complementary to homologous recombination deficiency for improving the clinical outcome of ovarian serous cystadenocarcinoma

Ovarian cancer patients with homologous recombination deficiency (HRD) tumors would benefit from PARP inhibitor (PARPi) therapy. However, patients with HRD tumors account for less than 50% of the whole cohort, so new biomarkers still need to be developed. Based on the data from the SNP array and somatic mutation profiles in the ovarian cancer genome, we found that high frequency of actionable mutations existed in patients with non-HRD tumors. Through transcriptome analysis, we identified that a downstream target of the cGAS-STING pathway, CXCL11, was upregulated in HRD tumors and could be used as a predictor of survival outcome. Further comprehensive analysis of the tumor immune microenvironment (TIME) revealed that CXCL11 expression signature was closely correlated with cytotoxic cells, neoantigen load and immune checkpoint blockade (ICB). Clinical trial data confirmed that the expression of CXCL11 could be used as a biomarker for anti-PD-1/PD-L1 therapy. Finally, in vivo and in vitro experiments showed that cancer cells with PARPi treatment increased the expression of CXCL11. Collectively, our study not only provides biomarkers of ovarian cancer complementary to the HRD score but also introduces a potential new perspective for identifying prognostic biomarkers of immunotherapy.

Construction of an immune-related LncRNA signature with prognostic significance for bladder cancer

Bladder cancer (BLCA) is one of the most common urological cancer with increasing cases and deaths every year. In the present study, we aim to construct an immune‐related prognostic lncRNA signature (IRPLS) in bladder cancer (BLCA) patients and explore its immunogenomic implications in pan‐cancers. First, the immune‐related differentially expressed lncRNAs (IRDELs) were identified by ‘limma’ R package and the score of IRPLS in every patient were evaluated by Cox regression. The dysregulation of IRDELs expression between cancer and para‐cancer normal tissues was validated through RT‐qPCR. Then, we further explore the biological functions of a novel lncRNA from IRPLS, RP11‐89 in BLCA using CCK8 assay, Transwell assay and Apoptosis analysis, which indicated that RP11‐89 was able to promote cell proliferation and invasive capacity while inhibits cell apoptosis in BLCA. In addition, we performed bioinformatic methods and RIP to investigate and validate the RP11‐89/miR‐27a‐3p/PPARγ pathway in order to explore the mechanism. Next, CIBERSORT and ESTIMATE algorithm were used to evaluate abundance of tumour‐infiltrating immune cells and scores of tumour environment elements in BLCA with different level of IRPLS risk scores. Finally, multiple bioinformatic methods were performed to show us the immune landscape of these four lncRNAs for pan‐cancers. In conclusion, this study first constructed an immune‐related prognostic lncRNA signature, which consists of RP11‐89, PSORS1C3, LINC02672 and MIR100HG and might shed lights on novel targets for individualized immunotherapy for BLCA patients.

Advances in the development of personalized neoantigen-based therapeutic cancer vaccines

Within the past decade, the field of immunotherapy has revolutionized the treatment of many cancers with the development and regulatory approval of various immune-checkpoint inhibitors and chimeric antigen receptor T cell therapies in diverse indications. Another promising approach to cancer immunotherapy involves the use of personalized vaccines designed to trigger de novo T cell responses against neoantigens, which are highly specific to tumours of individual patients, in order to amplify and broaden the endogenous repertoire of tumour-specific T cells. Results from initial clinical studies of personalized neoantigen-based vaccines, enabled by the availability of rapid and cost-effective sequencing and bioinformatics technologies, have demonstrated robust tumour-specific immunogenicity and preliminary evidence of antitumour activity in patients with melanoma and other cancers. Herein, we provide an overview of the complex process that is necessary to generate a personalized neoantigen vaccine, review the types of vaccine-induced T cells that are found within tumours and outline strategies to enhance the T cell responses. In addition, we discuss the current status of clinical studies testing personalized neoantigen vaccines in patients with cancer and considerations for future clinical investigation of this novel, individualized approach to immunotherapy.

Advances in the development of personalized neoantigen-based therapeutic cancer vaccines

Within the past decade, the field of immunotherapy has revolutionized the treatment of many cancers with the development and regulatory approval of various immune-checkpoint inhibitors and chimeric antigen receptor T cell therapies in diverse indications. Another promising approach to cancer immunotherapy involves the use of personalized vaccines designed to trigger de novo T cell responses against neoantigens, which are highly specific to tumours of individual patients, in order to amplify and broaden the endogenous repertoire of tumour-specific T cells. Results from initial clinical studies of personalized neoantigen-based vaccines, enabled by the availability of rapid and cost-effective sequencing and bioinformatics technologies, have demonstrated robust tumour-specific immunogenicity and preliminary evidence of antitumour activity in patients with melanoma and other cancers. Herein, we provide an overview of the complex process that is necessary to generate a personalized neoantigen vaccine, review the types of vaccine-induced T cells that are found within tumours and outline strategies to enhance the T cell responses. In addition, we discuss the current status of clinical studies testing personalized neoantigen vaccines in patients with cancer and considerations for future clinical investigation of this novel, individualized approach to immunotherapy.

P22 virus-like particles as an effective antigen delivery nanoplatform for cancer immunotherapy

As a new strategy for cancer immunotherapy, therapeutic cancer vaccines have been greatly improved in recent years. However, addressing the needs to quickly and efficiently elicit a high-intensity immune response against neoantigen peptides, especially to induce an effective cytotoxic lymphocyte (CTL) reaction, remain challenges in this field. In this study, virus-like particles (VLPs) derived from the phage P22 were adopted to load peptide antigens on the surface, to test whether VLP technology can be used as a platform for efficient peptide antigen delivery by therapeutic cancer vaccines. The B and T epitopes (OVA_B peptide and OVA_T peptide) of ovalbumin (OVA) were used here as model antigens and fused individually at the C terminus of the coat protein (CP), which allowed display on the surface of P22 particles to form two types of vaccine particles (VLP-OVA_B and VLP-OVA_T). Subsequent experiments showed that VLP-OVA_B induced an antibody titer against the peptide antigen as high as 5.0 × 10⁵ and that VLP-OVA_T induced highly effective cross-presentation and then strongly activated a T epitope-specific CTL response. Mouse tumor model experiments showed that VLP-OVA_T could significantly inhibit tumor growth by increasing the proportions of CD4⁺ T cells, CD8⁺ T cells and effector memory T cells (T_EM cells) and lowering the proportion of myeloid-derived suppressor cells (MDSCs) among tumor-infiltrating lymphocytes and splenocytes. Compared with other chemically synthesized nanomaterials, VLPs have obvious advantages as vaccine carriers due to their clear chemical composition, fixed spatial structure, excellent biocompatibility, and relatively high potential for clinical translation. Therefore, this platform may lay a solid foundation for the design and preparation of personalized therapeutic vaccines based on neoantigen peptides.

Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting

CD8+ T cell recognition of peptide epitopes plays a central role in immune responses against pathogens and tumors. However, the rules that govern which peptides are truly recognized by existing T cell receptors (TCRs) remain poorly understood, precluding accurate predictions of neo-epitopes for cancer immunotherapy. Here, we capitalize on recent (neo-)epitope data to train a predictor of immunogenic epitopes (PRIME), which captures molecular properties of both antigen presentation and TCR recognition. PRIME not only improves prioritization of neo-epitopes but also correlates with T cell potency and unravels biophysical determinants of TCR recognition that we experimentally validate. Analysis of cancer genomics data reveals that recurrent mutations tend to be less frequent in patients where they are predicted to be immunogenic, providing further evidence for immunoediting in human cancer. PRIME will facilitate identification of pathogen epitopes in infectious diseases and neo-epitopes in cancer immunotherapy.

T Cells in Chronic Lymphocytic Leukemia: A Two-Edged Sword

Chronic lymphocytic leukemia (CLL) is a malignancy of mature, antigen-experienced B lymphocytes. Despite great progress recently achieved in the management of CLL, the disease remains incurable, underscoring the need for further investigation into the underlying pathophysiology. Microenvironmental crosstalk has an established role in CLL pathogenesis and progression. Indeed, the malignant CLL cells are strongly dependent on interactions with other immune and non-immune cell populations that shape a highly orchestrated network, the tumor microenvironment (TME). The composition of the TME, as well as the bidirectional interactions between the malignant clone and the microenvironmental elements have been linked to disease heterogeneity. Mounting evidence implicates T cells present in the TME in the natural history of the CLL as well as in the establishment of certain CLL hallmarks e.g. tumor evasion and immune suppression. CLL is characterized by restrictions in the T cell receptor gene repertoire, T cell oligoclonal expansions, as well as shared T cell receptor clonotypes amongst patients, strongly alluding to selection by restricted antigenic elements of as yet undisclosed identity. Further, the T cells in CLL exhibit a distinctive phenotype with features of “exhaustion” likely as a result of chronic antigenic stimulation. This might be relevant to the fact that, despite increased numbers of oligoclonal T cells in the periphery, these cells are incapable of mounting effective anti-tumor immune responses, a feature perhaps also linked with the elevated numbers of T regulatory subpopulations. Alterations of T cell gene expression profile are associated with defects in both the cytoskeleton and immune synapse formation, and are generally induced by direct contact with the malignant clone. That said, these abnormalities appear to be reversible, which is why therapies targeting the T cell compartment represent a reasonable therapeutic option in CLL. Indeed, novel strategies, including CAR T cell immunotherapy, immune checkpoint blockade and immunomodulation, have come to the spotlight in an attempt to restore the functionality of T cells and enhance targeted cytotoxic activity against the malignant clone.

Triggering interferon signaling in T cells with avadomide sensitizes CLL to anti-PD-L1/PD-1 immunotherapy

Cancer treatment has been transformed by checkpoint blockade therapies, with the highest anti-tumor activity of anti-programmed death 1 (PD-1) antibody therapy seen in Hodgkin lymphoma. Disappointingly, response rates have been low in the non-Hodgkin lymphomas, with no activity seen in relapsed/refractory chronic lymphocytic leukemia (CLL) with PD-1 blockade. Thus, identifying more powerful combination therapy is required for these patients. Here, we preclinically demonstrate enhanced anti-CLL activity following combinational therapy with anti-PD-1 or anti-PD-1 ligand (PD-L1) and avadomide, a cereblon E3 ligase modulator (CELMoD). Avadomide induced type I and II interferon (IFN) signaling in patient T cells, triggering a feedforward cascade of reinvigorated T-cell responses. Immune modeling assays demonstrated that avadomide stimulated T-cell activation, chemokine expression, motility and lytic synapses with CLL cells, as well as IFN-inducible feedback inhibition through upregulation of PD-L1. Patient-derived xenograft tumors treated with avadomide were converted to CD8+ T cell-inflamed tumor microenvironments that responded to anti-PD-L1/PD-1-based combination therapy. Notably, clinical analyses showed increased PD-L1 expression on T cells, as well as intratumoral expression of chemokine signaling genes in B-cell malignancy patients receiving avadomide-based therapy. These data illustrate the importance of overcoming a low inflammatory T-cell state to successfully sensitize CLL to checkpoint blockade-based combination therapy.

The Role of cis- and trans-Acting RNA Regulatory Elements in Leukemia

RNA molecules are a source of phenotypic diversity and an operating system that connects multiple genetic and metabolic processes in the cell. A dysregulated RNA network is a common feature of cancer. Aberrant expression of long non-coding RNA (lncRNA), micro RNA (miRNA), and circular RNA (circRNA) in tumors compared to their normal counterparts, as well as the recurrent mutations in functional regulatory cis-acting RNA motifs have emerged as biomarkers of disease development and progression, opening avenues for the design of novel therapeutic approaches. This review looks at the progress, challenges and future prospects of targeting cis-acting and trans-acting RNA elements for leukemia diagnosis and treatment.

Overcoming the Hurdles of Autologous T-Cell-Based Therapies in B-Cell Non-Hodgkin Lymphoma

Simple Summary

The activity of novel therapies that utilize patient’s own T-cells to induce remission of B-cell non-Hodgkin lymphoma (B-NHL), including chronic lymphocytic leukemia (CLL), is still suboptimal. In this review, we summarize the clinical efficacy of T-cell-based therapies in B-NHL and provide a biologic rationale for the observed (lack of) responses. We describe and compare the acquired T-cell dysfunctions that occur in the different subtypes of B-NHL. Furthermore, we discuss new insights that could enhance the efficacy of T-cell-based therapies for B-NHL and CLL.

Abstract

The next frontier towards a cure for B-cell non-Hodgkin lymphomas (B-NHL) is autologous cellular immunotherapy such as immune checkpoint blockade (ICB), bispecific antibodies (BsAbs) and chimeric antigen receptor (CAR) T-cells. While highly successful in various solid malignancies and in aggressive B-cell leukemia, this clinical success is often not matched in B-NHL. T-cell subset skewing, exhaustion, expansion of regulatory T-cell subsets, or other yet to be defined mechanisms may underlie the lack of efficacy of these treatment modalities. In this review, a systematic overview of results from clinical trials is given and is accompanied by reported data on T-cell dysfunction. From these results, we distill the underlying pathways that might be responsible for the observed differences in clinical responses towards autologous T-cell-based cellular immunotherapy modalities between diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), mantle cell lymphoma (MCL), and marginal zone lymphoma (MZL). By integration of the clinical and biological findings, we postulate strategies that might enhance the efficacy of autologous-based cellular immunotherapy for the treatment of B-NHL.

Pan-cancer analysis of genomic properties and clinical outcome associated with tumor tertiary lymphoid structure

How the genomic landscape of a tumor shapes the formation of tertiary lymphoid structure (TLS) and how might TLS alter the clinical outcome or response to immunotherapy had not been systematically explored. Utilizing the genomic and transcriptome data of solid tumors on TCGA, we quantified TLS based on a previous identified 12-chemokine signature and evaluated its correlation with mutation/neoantigen burden, functional mutation of oncogenes and the presence of viral infection. Clinical data was integrated to decide the prognostic significance of TLS for different cancers after surgical treatment. Publicly available data (clinical and transcriptome data) of immunotherapy clinical trials involving melanoma and lung cancer were also collected to evaluate TLS’s association with therapeutic outcome. Mutation burden and predicted neoantigen counts were positively correlated with TLS scoring in multiple cancer types. Mutation in tumor suppressor genes (KEAP1, PBRM1) and genes involved in extrinsic apoptosis (CASP8), antigen-presentation (HLA-A, HLA-B), immune regulation (SMAD4) or DNA repair (BRCA1, BRCA2, TP53BP1) correlated with TLS alteration in multiple tumor types, indicating the interaction between mutation landscape and TLS formation. Epstein-Barr virus (EBV) infection in gastric cancer and human papillomavirus (HPV) infection in Head and Neck squamous cell carcinoma were associated with increased TLS scoring. High TLS scoring predicted favorable prognosis in certain cancer after surgical treatment and improved response to immunotherapy in lung cancer and melanoma. Our findings unraveled the genomic properties associated with TLS formation in different solid tumors and highlighted the prognostic and predictive significance of TLS in surgical treatment and immunotherapy.