Identifying Comprehensive Genomic Alterations and Potential Neoantigens for Cervical Cancer Immunotherapy in a Cohort of Chinese Squamous Cell Carcinoma of the Cervix

Objective Genomic alterations and potential neoantigens for cervical cancer immunotherapy were identified in a cohort of Chinese patients with cervical squamous cell carcinoma(CSCC).Methods Whole-exome sequencing was used to identify genomic alterations and potential neoantigens for CSCC immunotherapy.RNA Sequencing was performed to analyze neoantigen expression.Results Systematic bioinformatics analysis showed that C>T/G>A transitions/transversions were dominant in CSCCs.Missense mutations were the most frequent types of somatic mutation in the coding sequence regions.Mutational signature analysis detected signature 2,signature 6,and signature 7 in CSCC samples.PIK3CA,FBXW7,and BICRA were identified as potential driver genes,with BICRA as a newly reported gene.Genomic variation profiling identified 4,960 potential neoantigens,of which 114 were listed in two neoantigen-related databases.Conclusion The present findings contribute to our understanding of the genomic characteristics of CSCC and provide a foundation for the development of new biotechnology methods for individualized immunotherapy in CSCC.

Prediction of neoantigens and their application in cancer treatment

Tumor antigens can be divided into tumor-associated antigens and tumor-specific antigens according to their specificity. Tumorassociated antigens are not unique to tumor cells, and can also be synthesized in small amounts by normal cells. Tumor-specific antigens, also called neoantigens, are formed by peptides that are entirely absent from the normal human genome [1]. Neoantigens are

Colorectal cancer vaccines: Tumor-associated antigens vs neoantigens

Therapeutic options for the treatment of colorectal cancer(CRC) are diverse but still not always satisfying. Recent success of immune checkpoint inhibition treatment for the subgroup of CRC patients suffering from hypermutated tumors suggests a permanent role of immune therapy in the clinical management of CRC. Substantial improvement in treatment outcome could be achieved by development of efficient patient-individual CRC vaccination strategies. This mini-review summarizes the current knowledge on the two general classes of targets: tumor-associated antigens(TAAs) and tumorspecific antigens. TAAs like carcinoembryonic antigen and melanoma associated antigen are present in and shared by a subgroup of patients and a variety of clinical studies examined the efficacy of different TAA-derived peptide vaccines. Combinations of several TAAs as the next step and the development of personalized TAA-based peptide vaccines are discussed. Improvements of peptidebased vaccines achievable by adjuvants and immunestimulatory chemotherapeutics are highlighted. Finally, we sum up clinical studies using tumor-specific antigens-in CRC almost exclusively neoantigens-which revealed promising results; particularly no severe adverse events were reported so far. Critical progress for clinical outcomes can be expected by individualizing neoantigen-based peptide vaccines and combining them with immunestimulatory chemotherapeutics and immune checkpoint inhibitors. In light of these data and latest developments, truly personalized neoantigen-based peptide vaccines can be expected to fulfill modern precision medicine's requirements and will manifest as treatment pillar for routine clinical management of CRC.

Profiling of hepatocellular carcinoma neoantigens reveals immune microenvironment and clonal evolution related patterns

Objective: Neoantigens derived from tumor-specific genomic alterations have demonstrated great potential for immunotherapeutic interventions in cancers. However, the comprehensive profile of hepatocellular carcinoma(HCC) neoantigens and their complex interplay with immune microenvironment and tumor evolution have not been fully addressed.Methods: Here we integrated whole exome sequencing data, transcriptome sequencing data and clinical information of 72 primary HCC patients to characterize the HCC neoantigen profile, and systematically explored its interactions with tumor clonal evolution, driver mutations and immune microenvironments.Results: We observed that higher somatic mutation/neoantigen load was associated with better clinical outcomes and HCC patients could be further divided into two subgroups with distinct prognosis based on their neoantigen expression patterns. HCC subgroup with neoantigen expression probability high(NEP-H) showed more aggressive pathologic features including increased incidence of tumor thrombus(P=0.038), higher recurrence rate(P=0.029),more inclined to lack tumor capsule(P=0.026) and with more microsatellite instability sites(P=0.006). In addition,NEP-H subgroup was also characterized by higher chance to be involved in tumor clonal evolution [odds ratio(OR)=46.7, P<0.001]. Gene set enrichment analysis revealed that upregulation of MYC and its targets could suppress immune responses, leading to elevated neoantigen expression proportion in tumor cells. Furthermore, we discovered an immune escape mechanism that tumors could become more inconspicuous by evolving subclones with less immunogenicity. We observed that smaller clonal mutation clusters with higher immunogenicity in tumor were more likely to involve in clonal evolution. Based on identified neoantigen profiles, we also discovered series of neoantigenic hotspot genes, which could serve as potential actionable targets in future.Conclusions: Our results revealed the landscape of HCC neoantigens and discovered two clinically relevant subgroups with distinct neoantigen expression patterns, suggesting the neoantigen expression should be fully considered in future immunotherapeutic interventions.

NeoHunter:Flexible software for systematically detecting neoantigens from sequencing data

Complicated molecular alterations in tumors generate various mutant peptides.Some of these mutant peptides can be presented to the cell surface and then elicit immune responses,and such mutant peptides are called neoantigens.Accurate detection of neoantigens could help to design personalized cancer vaccines.Although some computational frameworks for neoantigen detection have been proposed,most of them can only detect SNV-and indel-derived neoantigens.In addition,current frameworks adopt oversimplified neoantigen prioritization strategies.These factors hinder the comprehensive and effective detection of neoantigens.We developed NeoHunter,flexible software to systematically detect and prioritize neoantigens from sequencing data in different formats.NeoHunter can detect not only SNV-and indel-derived neoantigens but also gene fusion-and aberrant splicing-derived neoantigens.NeoHunter supports both direct and indirect immunogenicity evaluation strategies to prioritize candidate neoantigens.These strategies utilize binding characteristics,existing biological big data,and T-cell receptor specificity to ensure accurate detection and prioritization.We applied NeoHunter to the TESLA dataset,cohorts of melanoma and non-small cell lung cancer patients.NeoHunter achieved high performance across the TESLA cancer patients and detected 79%(27 out of 34)of validated neoantigens in total.SNV-and indel-derived neoantigens accounted for 90%of the top 100 candidate neoantigens while neoantigens from aberrant splicing accounted for 9%.Gene fusion-derived neoantigens were detected in one patient.NeoHunter is a powerful tool to‘catch all’neoantigens and is available for free academic use on Github(XuegongLab/NeoHunter).

Ionizable polymeric nanocarriers for the codelivery of bi-adjuvant and neoantigens in combination tumor immunotherapy

Ionizable lipid nanocarriers have made historical contribution to COVID-19 mRNA vaccines.Here,we report ionizable polymeric nanoparticles that co-deliver bi-adjuvant and neoantigen peptides for cancer immunotherapy in combination with immune checkpoint blockade(ICB).Current cancer ICB benefits only a small subset of patients,largely due to a lack of pre-existing target cells and checkpoint targets for ICB,tumor antigenic heterogeneity,and tumor immunosuppression.Therapeutic vaccines hold the potential to enhance ICB therapeutic efficacy by expanding antitumor cell repertoires,upregulating immune checkpoint levels and hence sensitizing ICB,and reducing tumor immunosuppression.Chemically defined peptide vaccines are attractive,but their current therapeutic efficacy has been limited due to 1)poor vaccine delivery to immunomodulatory lymph nodes(LNs)and antigen(Ag)-presenting cells(APCs),2)poor immunostimulant adjuvant efficacy with restricted target cell subsets in humans,3)limited adjuvant/Ag codelivery to enhance Ag immunogenicity,and 4)limited ability to overcome tumor antigenic heterogeneity.Here,we developed nanovaccines(NVs)using pH-responsive polymeric micellular nanoparticles(NPs)for the codelivery of bi-adjuvant[Toll-like receptor(TLR)7/8 agonist R848 and TLR9 agonist CpG]and peptide neoantigens(neoAgs)to draining LNs for efficient Ag presentation in a broad range of APC subsets.These NVs potentiated the immunogenicity of peptide Ags and elicits robust antitumor T cell responses with memory,and remodeled the tumor immune milium with reduced tumor immunosuppression.As a result,NVs significantly enhanced ICB therapeutic efficacy for murine colorectal tumors and orthotopic glioblastoma multiforme(GBM).These results suggest marked potential of bi-adjuvant/neoAg-codelivering NVs for combination cancer immunotherapy.

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.

TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis

Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database （TSNAdb v1.0）, based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen （HLA） allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas （TCGA） and The Cancer Immunome Atlas （TCIA）. We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients,which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy.TSNAdb is freely available at http：//biopharm.zju.edu.cn/tsnadb.

Neoantigens in precision cancer immunotherapy:from identification to clinical applications

Immunotherapies targeting cancer neoantigens are safe,effective,and precise.Neoantigens can be identified mainly by genomic techniques such as next-generation sequencing and high-throughput single-cell sequencing;proteomic techniques such as mass spectrometry;and bioinformatics tools based on high-throughput sequencing data,mass spectrometry data,and biological databases.Neoantigen-related therapies are widely used in clinical practice and include neoantigen vaccines,neoantigen-specific CD8+and CD4+T cells,and neoantigen-pulsed dendritic cells.In addition,neoantigens can be used as biomarkers to assess immunotherapy response,resistance,and prognosis.Therapies based on neoantigens are an important and promising branch of cancer immunotherapy.Unremitting efforts are needed to unravel the comprehensive role of neoantigens in anti-tumor immunity and to extend their clinical application.This review aimed to summarize the progress in neoantigen research and to discuss its opportunities and challenges in precision cancer immunotherapy.

Combination immunotherapy of glioblastoma with dendritic cell cancer vaccines,anti-PD-1 and poly I:C

Glioblastoma(GBM)is a lethal cancer with limited therapeutic options.Dendritic cell(DC)-based cancer vaccines provide a promising approach for GBM treatment.Clinical studies suggest that other immunotherapeutic agents may be combined with DC vaccines to further enhance antitumor activity.Here,we report a GBM case with combination immunotherapy consisting of DC vaccines,anti-programmed death-1(anti-PD-1)and poly I:C as well as the chemotherapeutic agent cyclophosphamide that was integrated with standard chemoradiation therapy,and the patient remained disease-free for 69 months.The patient received DC vaccines loaded with multiple forms of tumor antigens,including mRNA-tumor associated antigens(TAA),mRNA-neoantigens,and hypochlorous acid(HOCl)-oxidized tumor lysates.Furthermore,mRNA-TAAs were modified with a novel TriVac technology that fuses TAAs with a destabilization domain and inserts TAAs into full-length lysosomal associated membrane protein-1 to enhance major histocompatibility complex(MHC)class I and II antigen presentation.The treatment consisted of 42 DC cancer vaccine infusions,26 anti-PD-1 antibody nivolumab administrations and 126 poly I:C injections for DC infusions.The patient also received 28 doses of cyclophosphamide for depletion of regulatory T cells.No immunotherapy-related adverse events were observed during the treatment.Robust antitumor CD4t and CD8t T-cell responses were detected.The patient remains free of disease progression.This is the first case report on the combination of the above three agents to treat glioblastoma patients.Our results suggest that integrated combination immunotherapy is safe and feasible for long-term treatment in this patient.A large-scale trial to validate these findings is warranted.

Targeted therapy or immunotherapy? Optimal treatment in hepatocellular carcinoma

Hepatocellular carcinoma(HCC) is the fifth leading cause of cancer mortality in the United States and the second leading cause of cancer mortality worldwide. Sorafenib is the only food and drug administration(FDA) approved as first line systemic treatment in HCC. Regorafenib and nivolumab are the only FDA approved second line treatment after progression on sorafenib. We will discuss all potential first and second line options in HCC. In addition, we also will explore sequencing treatment options in HCC, and examine biomarkers that can potentially predict benefits from treatments such as immune checkpoint inhibitor. This minireview summarizes potential treatments in HCC based on clinical trials that have been published in manuscript or abstract format from 1994-2018.

Personalized immunotherapy in cancer precision medicine

With the significant advances in cancer genomics using next-generation sequencing technologies,genomic and molecular profilingbased precision medicine is used as a part of routine clinical test for guiding and selecting the most appropriate treatments for individual cancer patients.Although many molecular-targeted therapies for a number of actionable genomic alterations have been developed,the clinical application of such information is still limited to a small proportion of cancer patients.In this review,we summarize the current status of personalized drug selection based on genomic and molecular profiling and highlight the challenges how we can further utilize the individual genomic information.Cancer immunotherapies,including immune checkpoint inhibitors,would be one of the potential approaches to apply the results of genomic sequencing most effectively.Highly cancer-specific antigens derived from somatic mutations,the so-called neoantigens,occurring in individual cancers have been in focus recently.Cancer immunotherapies,which target neoantigens,could lead to a precise treatment for cancer patients,despite the challenge in accurately predicting neoantigens that can induce cytotoxic T cells in individual patients.Precise prediction of neoantigens should accelerate the development of personalized immunotherapy including cancer vaccines and T-cell receptor-engineered T-cell therapy for a broader range of cancer patients.

Nanomaterial-based delivery vehicles for therapeutic cancer vaccine development

Nanomaterial-based delivery vehicles such as lipid-based,polymer-based,inorganics-based,and bio-inspired vehicles often carry distinct and attractive advantages in the development of therapeutic cancer vaccines.Based on various delivery vehicles,specifically designed nanomaterials-based vaccines are highly advantageous in boosting therapeutic and prophylactic antitumor immunities.Specifically,therapeutic vaccines featuring unique properties have made major contributions to the enhancement of antigen immunogenicity,encapsulation efficiency,biocompatibility,and stability,as well as promoting antigen cross-presentation and specific CD8^(+)T cell responses.However,for clinical applications,tumor-associated antigen-derived vaccines could be an obstacle,involving immune tolerance and deficiency of tumor specificities,in achieving maximum therapeutic indices.However,when using bioinformatics predictions with emerging innovations of in silico tools,neoantigen-based therapeutic vaccines might become potent personalized vaccines for tumor treatments.In this review,we summarize the development of preclinical therapeutic cancer vaccines and the advancements of nanomaterial-based delivery vehicles for cancer immunotherapies,which provide the basis for a personalized vaccine delivery platform.Moreover,we review the existing challenges and future perspectives of nanomaterial-based personalized vaccines for novel tumor immunotherapies.

Neoantigen vaccine:An emerging immunotherapy for hepatocellular carcinoma

Tumor-specific neoantigens,which are expressed on tumor cells,can induce an effective antitumor cytotoxic T-cell response and mediate tumor regression.Among tumor immunotherapies,neoantigen vaccines are in early human clinical trials and have demonstrated substantial efficiency.Compared with more neoantigens in melanoma,the paucity and inefficient identification of effective neoantigens in hepatocellular carcinoma(HCC)remain enormous challenges in effectively treating this malignancy.In this review,we highlight the current development of HCC neoantigens in its generation,screening,and identification.We also discuss the possibility that there are more effective neoantigens in hepatitis B virus(HBV)-related HCC than in non-HBV-related HCC.In addition,since HCC is an immunosuppressive tumor,strategies that reverse immunosuppression and enhance the immune response should be considered for the practical exploitation of HCC neoantigens.In summary,this review offers some strategies to solve existing problems in HCC neoantigen research and provide further insights for immunotherapy.

抗原改造联合纳米肿瘤疫苗用以克服肿瘤新抗原短缺及在多种肿瘤类型上激起强效抗肿瘤免疫反应

Neoantigen cancer vaccines have been envisioned as one of the most promising means for cancer therapies.However,identifying neoantigens for tumor types with low tumor mutation burdens continues to limit the effectiveness of neoantigen vaccines.Herein,we proposed a "hit-and-run" vaccine strategy which primes T cells to attack tumor cells decorated with exogenous "neo-antigens".This vaccine strategy utilizes a peptide nanovaccine to elicit antigen-specific T cell responses after tumor-specific decoration with a nanocarrier containing the same peptide antigens.We demonstrated that a poly(2-oxazoline)s(POx) conjugated with OVA_(257-264) peptide through a matrix metalloprotease 2(MMP-2) sensitive linker could efficiently and selectively decorate tumor cells with OVA peptides in vivo.Then,a POx-based nanovaccine containing OVA_(257-264) peptides to elicit OVA-specific T cell responses was designed.In combination with this hit-and-run vaccine system,an effective vaccine therapy was demonstrated across tumor types even without OVA antigen expression.This approach provides a promising and uniform vaccine strategy against tumors with a low tumor mutation burden.

In Silico Pipeline to Identify Tumor‑Specific Antigens for Cancer Immunotherapy Using Exome Sequencing Data

Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells.Some of these molecules can induce an immune response,and therefore,their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored.Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies.However,there is no universal nor straightforward bioinformatic protocol to discover neoan-tigens using DNA sequencing data.Thus,we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants(SNVs)or“mutations”in tumoral tissues.For this purpose,we used publicly available data to build our model,including exome sequencing data from colorectal cancer and healthy cells obtained from a single case,as well as frequent human leukocyte antigen(HLA)class I alleles in a specific population.HLA data from Costa Rican Central Valley population was selected as an example.The strategy included three main steps:(1)pre-processing of sequencing data;(2)variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue;and(3)prediction and characterization of peptides(protein fragments,the tumor-specific antigens)derived from the variants,in the context of their affinity with frequent alleles of the selected population.In our model data,we found 28 non-silent SNVs,present in 17 genes in chromosome one.The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population.Although the analyses were performed as an example to implement the pipeline,to our knowledge,this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles.It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices.

TSNAdb v2.0:The Updated Version of Tumor-specific Neoantigen Database

In recent years,neoantigens have been recognized as ideal targets for tumor immunotherapy.With the development of neoantigen-based tumor immunotherapy,comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies.We have built the tumor-specific neoantigen database(TSNAdb)previously,which has attracted much attention.In this study,we provide TSNAdb v2.0,an updated version of the TSNAdb.TSNAdb v2.0 offers several new features,including(1)adopting more stringent criteria for neoantigen identification,(2)providing predicted neoantigens derived from three types of somatic mutations,and(3)collecting experimentally validated neoantigens and dividing them according to the experimental level.

mRNA cancer vaccines:Advances,trends and challenges

Patients exhibit good tolerance to messenger ribonucleic acid(m RNA)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 m RNA-based coronavirus disease 2019(COVID-19)vaccine produced by Pfizer and Bio NTech,which has generated enthusiasm for m RNA vaccine research and development.Based on the above characteristics and the development of m RNA vaccines,m RNA cancer vaccines have become a research hotspot and have undergone rapid development,especially in the last five years.This review analyzes the advances in m RNA 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.

Glycoproteogenomics: Setting the Course for Next-generation Cancer Neoantigen Discovery for Cancer Vaccines

Molecular-assisted precision oncology gained tremendous ground with high-throughput next-generation sequencing(NGS),supported by robust bioinformatics.The quest for genomicsbased cancer medicine set the foundations for improved patient stratification,while unveiling a wide array of neoantigens for immunotherapy.Upfront pre-clinical and clinical studies have successfully used tumor-specific peptides in vaccines with minimal off-target effects.However,the low mutational burden presented by many lesions challenges the generalization of these solutions,requiring the diversification of neoantigen sources.Oncoproteogenomics utilizing customized databases for protein annotation by mass spectrometry(MS)is a powerful tool toward this end.Expanding the concept toward exploring proteoforms originated from post-translational modifications(PTMs)will be decisive to improve molecular subtyping and provide potentially targetable functional nodes with increased cancer specificity.Walking through the path of systems biology,we highlight that alterations in protein glycosylation at the cell surface not only have functional impact on cancer progression and dissemination but also originate unique molecular fingerprints for targeted therapeutics.Moreover,we discuss the outstanding challenges required to accommodate glycoproteomics in oncoproteogenomics platforms.We envisage that such rationale may flag a rather neglected research field,generating novel paradigms for precision oncology and immunotherapy.

Finding neoepitopes in mouse models of personalized cancer immunotherapy

BACKGROUND： Cancer immunotherapy uses one＇s own immune system to fight cancerous cells. As immune system is hard- wired to distinguish self and non-self, cancer immunotherapy is predicted to target cancerous cells specifically, therefore is less toxic than chemotherapy and radiation therapy, two major treatments for cancer. Cancer immunologists have spent decades to search for the specific targets in cancerous cells. METHODS： Due to the recent advances in high throughput sequencing and bioinformatics, evidence has merged that the neoantigens in cancerous cells are probably the cancer-specific targets that lead to the destruction of cancer. We will review the transplantable murine tumor models for cancer immunotherapy and the bioinformatics tools used to navigate mouse genome to identify tumor-rejecting neoantigens. RESULTS： Several groups have independently identified point mutations that can be recognized by T cells of host immune system. It is consistent with the note that the formation ofpeptide-MHC I-TCR complex is critical to activate T cells. Both anchor residue and TCR-facing residue mutations have been reported. While TCR-facing residue mutations may directly activate specific T cells, anchor residue mutations improve the binding of peptides to MHC I molecules, which increases the presentation of peptides and the T cell activation indirectly. CONCLUSIONS： Our work indicates that the affinity of neoepitopes for MHC I is not a predictor for anti-tumor immune responses in mice. Instead differential agretopic index （DAI）, the numerical difference of epitope-MHC I affinities between the mutated and un-mutated sequences is a significant predictor. A similar bioinformatics pipeline has been developed to generate personalized vaccines to treat human ovarian cancer in a Phase I clinical trial.