Breast Cancer Neoantigens Can Induce CD8+ T-Cell Responses and Antitumor Immunity

Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens

Recent breakthroughs in cancer immunotherapies have emphasized the importance of harnessing the immune system for treating cancer. Vaccines, which have traditionally been used to promote protective immunity against pathogens, are now being explored as a method to target cancer neoantigens. Over the past few years, extensive preclinical research and more than a hundred clinical trials have been dedicated to investigating various approaches to neoantigen discovery and vaccine formulations, encouraging development of personalized medicine. Nucleic acids (DNA and mRNA) have become particularly promising platform for the development of these cancer immunotherapies. This shift towards nucleic acid-based personalized vaccines has been facilitated by advancements in molecular techniques for identifying neoantigens, antigen prediction methodologies, and the development of new vaccine platforms. Generating these personalized vaccines involves a comprehensive pipeline that includes sequencing of patient tumor samples, data analysis for antigen prediction, and tailored vaccine manufacturing. In this review, we will discuss the various shared and personalized antigens used for cancer vaccine development and introduce strategies for identifying neoantigens through the characterization of gene mutation, transcription, translation and post translational modifications associated with oncogenesis. In addition, we will focus on the most up-to-date nucleic acid vaccine platforms, discuss the limitations of cancer vaccines as well as provide potential solutions, and raise key clinical and technical considerations in vaccine development.

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

Public neoantigens in breast cancer immunotherapy (Review)

Among women globally, breast cancer is the most prevalent cancer and the leading cause of cancer‑related death. Interestingly, though genetic mutations contribute to the disease, <15% of women diagnosed with breast cancer have a family history of the disease, suggesting a prevalence of sporadic genetic mutations in breast cancer development. In the rapidly rising field of cancer genomics, neoantigen‑based immunotherapy has come to the fore. The investigation of novel proteins arising from unique somatic mutations or neoantigens have opened a new pathway for both individualized and public cancer treatments. Because they are shared among individuals with similar genetic changes, public neoantigens provide an opportunity for 'off‑the‑shelf' anticancer therapies, potentially extending the benefits to a wider patient group. The present review aimed to highlight the role of shared or public neoantigens as therapeutic targets for patients with breast cancer, emphasizing common hotspot mutations of certain genes identified in breast cancer. The clinical utilization of public neoantigen‑based therapies for breast cancer treatment were also discussed.

Targeting Neoantigens in Cancer: Possibilities and Opportunities in Breast Cancer

As one of the most prevalent forms of cancer worldwide, breast cancer has garnered significant attention within the clinical research setting. While traditional treatment employs a multidisciplinary approach including a variety of therapies such as chemotherapy, hormone therapy, and even surgery, researchers have since directed their attention to the budding role of neoantigens. Neoantigens are defined as tumor-specific antigens that result from a multitude of genetic alterations, the most prevalent of which is the single nucleotide variant. As a result of their foreign nature, neoantigens elicit immune responses upon presentation by Major Histocompatibility Complexes I and II followed by recognition by T cell receptors. Previously, researchers have been able to utilize these immunogenic properties and manufacture neoantigen-specific T-cells and neoantigen vaccines. Within the context of breast cancer, biomarkers such as tumor protein 53 (TP53), Survivin, Partner and Localizer of BRCA2 (PALB2), and protein tyrosine phosphatase receptor T (PTPRT) display exceeding potential to serve as neoantigens. However, despite their seemingly limitless potential, neoantigens must overcome various obstacles if they are to be fairly distributed to patients. For instance, a prolonged period between the identification of a neoantigen and the dispersal of treatment poses a serious risk within the context of breast cancer. Regardless of these current obstacles, it appears highly promising that future research into neoantigens will make an everlasting impact on the health outcomes within the realm of breast cancer. The purpose of this literature review is to comprehensively discuss the etiology of various forms of breast cancer and current treatment modalities followed by the significance of neoantigens in cancer therapeutics and their application to breast cancer. Further, we have discussed the limitations, future directions, and the role of transcriptomics in neoantigen identification and personalized medicine. The concepts discussed in the original and review articles were included in this review article.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Stimulating T cell responses against patient-derived breast cancer cells with neoantigen peptide-loaded peripheral blood mononuclear cells

Breast cancer stands as a formidable global health challenge for women. While neoantigens exhibit efficacy in activating T cells specific to cancer and instigating anti-tumor immune responses, the accuracy of neoantigen prediction remains suboptimal. In this study, we identified neoantigens from the patient-derived breast cancer cells, PC-B-142CA and PC-B-148CA cells, utilizing whole-genome and RNA sequencing. The pVAC-Seq pipeline was employed, with minor modification incorporating criteria (1) binding affinity of mutant (MT) peptide with HLA (IC50 MT) ≤ 500 nm in 3 of 5 algorithms and (2) IC50 wild type (WT)/MT > 1. Sequencing results unveiled 2513 and 3490 somatic mutations, and 646 and 652 non-synonymous mutations in PC-B-142CA and PC-B-148CA, respectively. We selected the top 3 neoantigens to perform molecular dynamic simulation and synthesized 9-12 amino acid neoantigen peptides, which were then pulsed onto healthy donor peripheral blood mononuclear cells (PBMCs). Results demonstrated that T cells activated by ADGRL1E274K, PARP1E619K, and SEC14L2R43Q peptides identified from PC-B-142CA exhibited significantly increased production of interferon-gamma (IFN-γ), while PARP1E619K and SEC14L2R43Q peptides induced the expression of CD107a on T cells. The % tumor cell lysis was notably enhanced by T cells activated with MT peptides across all three healthy donors. Moreover, ALKBH6V83M and GAAI823T peptides from PC-B-148CA remarkably stimulated IFN-γ- and CD107a-positive T cells, displaying high cell-killing activity against target cancer cells. In summary, our findings underscore the successful identification of neoantigens with anti-tumor T cell functions and highlight the potential of personalized neoantigens as a promising avenue for breast cancer treatment.

Reviewing the significance of dendritic cell vaccines in interrupting breast cancer development

Breast cancer is a heterogeneous disease and is the most prevalent cancer in women. According to the U.S breast cancer statistics, about 1 in every 8 women develop an invasive form of breast cancer during their lifetime. Immunotherapy has been a significant advancement in the treatment of cancer with multiple studies reporting favourable patient outcomes by modulating the immune response to cancer cells. Here, we review the significance of dendritic cell vaccines in treating breast cancer patients. We discuss the involvement of dendritic cells and oncodrivers in breast tumorigenesis, highlighting the rationale for targeting oncodrivers and neoantigens using dendritic cell vaccine therapy. We review different dendritic cell subsets and maturation states previously used to develop vaccines and suggest the use of DC vaccines for breast cancer prevention. Further, we highlight that the intratumoral delivery of type 1 dendritic cell vaccines in breast cancer patients activates tumor antigen-specific CD4+ T helper cell type 1 (Th1) cells, promoting an anti-tumorigenic immune response while concurrently blocking pro-tumorigenic responses. In summary, this review provides an overview of the current state of dendritic cell vaccines in breast cancer highlighting the challenges and considerations necessary for an efficient dendritic cell vaccine design in interrupting breast cancer development.

Immune evasion of dormant disseminated tumor cells is due to their scarcity and can be overcome by T cell immunotherapies

The period between "successful" treatment of localized breast cancer and the onset of distant metastasis can last many years, representing an unexploited window to eradicate disseminated disease and prevent metastases. We find that the source of recurrence-disseminated tumor cells (DTCs) -evade endogenous immunity directed against tumor neoantigens. Although DTCs downregulate major histocompatibility complex I, this does not preclude recognition by conventional T cells. Instead, the scarcity of interactions between two relatively rare populations-DTCs and endogenous antigen-specific T cells-underlies DTC persistence. This scarcity is overcome by any one of three immunotherapies that increase the number of tumor-specific T cells: T cell-based vaccination, or adoptive transfer of T cell receptor or chimeric antigen receptor T cells. Each approach achieves robust DTC elimination, motivating discovery of MHC-restricted and -unrestricted DTC antigens that can be targeted with T cell-based immunotherapies to eliminate the reservoir of metastasis-initiating cells in patients.

Induction of cancer neoantigens facilitates development of clinically relevant models for the study of pancreatic cancer immunobiology

Neoantigen burden and CD8 T cell infiltrate are associated with clinical outcome in pancreatic ductal adenocarcinoma (PDAC). A shortcoming of many genetic models of PDAC is the lack of neoantigen burden and limited T cell infiltrate. The goal of the present study was to develop clinically relevant models of PDAC by inducing cancer neoantigens in KP2, a cell line derived from the KPC model of PDAC. KP2 was treated with oxaliplatin and olaparib (OXPARPi), and a resistant cell line was subsequently cloned to generate multiple genetically distinct cell lines (KP2-OXPARPi clones). Clones A and E are sensitive to immune checkpoint inhibition (ICI), exhibit relatively high T cell infiltration, and have significant upregulation of genes involved in antigen presentation, T cell differentiation, and chemokine signaling pathways. Clone B is resistant to ICI and is similar to the parental KP2 cell line in terms of relatively low T cell infiltration and no upregulation of genes involved in the pathways noted above. Tumor/normal exome sequencing and in silico neoantigen prediction confirms successful generation of cancer neoantigens in the KP2-OXPARPi clones and the relative lack of cancer neoantigens in the parental KP2 cell line. Neoantigen vaccine experiments demonstrate that a subset of candidate neoantigens are immunogenic and neoantigen synthetic long peptide vaccines can restrain Clone E tumor growth. Compared to existing models, the KP2-OXPARPi clones better capture the diverse immunobiology of human PDAC and may serve as models for future investigations in cancer immunotherapies and strategies targeting cancer neoantigens in PDAC.

Genomic Landscape of Normal and Breast Cancer Tissues in a Hungarian Pilot Cohort

A limited number of studies have focused on the mutational landscape of breast cancer in different ethnic populations within Europe and compared the data with other ethnic groups and databases. We performed whole-genome sequencing of 63 samples from 29 Hungarian breast cancer patients. We validated a subset of the identified variants at the DNA level using the Illumina TruSight Oncology (TSO) 500 assay. Canonical breast-cancer-associated genes with pathogenic germline mutations were CHEK2 and ATM. Nearly all the observed germline mutations were as frequent in the Hungarian breast cancer cohort as in independent European populations. The majority of the detected somatic short variants were single-nucleotide polymorphisms (SNPs), and only 8% and 6% of them were deletions or insertions, respectively. The genes most frequently affected by somatic mutations were KMT2C (31%), MUC4 (34%), PIK3CA (18%), and TP53 (34%). Copy number alterations were most common in the NBN, RAD51C, BRIP1, and CDH1 genes. For many samples, the somatic mutational landscape was dominated by mutational processes associated with homologous recombination deficiency (HRD). Our study, as the first breast tumor/normal sequencing study in Hungary, revealed several aspects of the significantly mutated genes and mutational signatures, and some of the copy number variations and somatic fusion events. Multiple signs of HRD were detected, highlighting the value of the comprehensive genomic characterization of breast cancer patient populations.

The prognostic value and response to immunotherapy of immunogenic cell death-associated genes in breast cancer

Breast cancer (BRCA) remains the most prevalent cancer worldwide and the tumor microenvironment (TME) has been discovered to exert a wide influence on the overall survival and therapeutic response. Numerous lines of evidence reported that the effects of immunotherapy of BRCA were manipulated by TME. Immunogenic cell death (ICD) is a form of regulated cell death (RCD) that is capable of fueling adaptive immune responses and aberrant expression of ICD-related genes (ICDRGs) can govern the TME system by emitting danger signals or damage-associated molecular patterns (DAMPs). In the current study, we obtained 34 key ICDRGs in BRCA. Subsequently, using the transcriptome data of BRCA from the TCGA database, we constructed a risk signature based on 6 vital ICDRGs, which had a good performance in predicting the overall survival of BRCA patients. We also examined the efficacy of our risk signature in the validation dataset (GSE20711) in the GEO database and it performed excellently. According to the risk model, patients with BRCA were divided into high-risk and low-risk groups. Also, the unique immune characteristics and TME between the two subgroups and 10 promising small molecule drugs targeting BRCA patients with different ICDRGs risk have been investigated. The low-risk group had good immunity indicated by T cell infiltration and high immune checkpoint expression. Moreover, the BRCA samples could be divided into three immune subtypes according to immune response severity (ISA, ISB, and ISC). ISA and ISB predominated in the low-risk group and patients in the low-risk group exhibited a more vigorous immune response. In conclusion, we developed an ICDRGs-based risk signature that can predict the prognosis of BRCA patients and offer a novel therapeutic strategy for immunotherapy, which would be of great significance in the BRCA clinical setting.

A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1^high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I - but not PD-L1 - on tumor cells are strong distinguishing features between these environments.

Immunotherapy in triple negative breast cancer: beyond checkpoint inhibitors

The development of immunotherapy agents has revolutionized the field of oncology. The only FDA-approved immunotherapeutic approach in breast cancer consists of immune checkpoint inhibitors, yet several novel immune-modulatory strategies are being actively studied and appear promising. Innovative immunotherapeutic strategies are urgently needed in triple negative breast cancer (TNBC), a subtype of breast cancer known for its poor prognosis and its resistance to conventional treatments. TNBC is more primed to respond to immunotherapy given the presence of more tumor infiltrating lymphocytes, higher PD-L1 expression, and higher tumor mutation burden relative to the other breast cancer subtypes, and therefore, immuno-oncology represents a key area of promise for TNBC research. The aim of this review is to highlight current data and ongoing efforts to establish the safety and efficacy of immunotherapeutic approaches beyond checkpoint inhibitors in TNBC.

Identification of HLA class I-restricted immunogenic neoantigens in triple negative breast cancer

Immune checkpoint inhibitor (ICI)-based immunotherapy in triple negative breast cancer (TNBC) is achieving limited therapeutic results, requiring the development of more potent strategies. Combination of ICI with vaccination strategies would enhance antitumor immunity and response rates to ICI in patients having poorly infiltrated tumors. In heavily mutated tumors, neoantigens (neoAgs) resulting from tumor mutations have induced potent responses when used as vaccines. Thus, our aim was the identification of immunogenic neoAgs suitable as vaccines in TNBC patients. By using whole exome sequencing, RNAseq and HLA binding algorithms of tumor samples from a cohort of eight TNBC patients, we identified a median of 60 mutations/patient, which originated a putative median number of 98 HLA class I-restricted neoAgs. Considering a group of 27 predicted neoAgs presented by HLA-A*02:01 allele in two patients, peptide binding to HLA was experimentally confirmed in 63% of them, whereas 55% were immunogenic in vivo in HLA-A*02:01⁺ transgenic mice, inducing T-cells against the mutated but not the wild-type peptide sequence. Vaccination with peptide pools or DNA plasmids expressing these neoAgs induced polyepitopic T-cell responses, which recognized neoAg-expressing tumor cells. These results suggest that TNBC tumors harbor neoAgs potentially useful in therapeutic vaccines, opening the way for new combined immunotherapies.

Neoantigens and their clinical applications in human gastrointestinal cancers

Background

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

Main text

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

Conclusions

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

Recent Progress on Therapeutic Vaccines for Breast Cancer

Breast cancer remains the most frequently diagnosed malignancy worldwide. Advanced breast cancer is still an incurable disease mainly because of its heterogeneity and limited immunogenicity. The great success of cancer immunotherapy is paving the way for a new era in cancer treatment, and therapeutic cancer vaccination is an area of interest. Vaccine targets include tumor-associated antigens and tumor-specific antigens. Immune responses differ in different vaccine delivery platforms. Next-generation sequencing technologies and computational analysis have recently made personalized vaccination possible. However, only a few cases benefiting from neoantigen-based treatment have been reported in breast cancer, and more attention has been given to overexpressed antigen-based treatment, especially human epidermal growth factor 2-derived peptide vaccines. Here, we discuss recent advancements in therapeutic vaccines for breast cancer and highlight near-term opportunities for moving forward.

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Cancer vaccines have gradually attracted attention for their tremendous preclinical and clinical performance. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods have become mainstream in cancer antigen prediction; of particular focus are neoantigens, mutation peptides that only exist in tumor cells that lack central tolerance and have fewer side effects. The rapid prediction and filtering of neoantigen peptides are crucial to the development of neoantigen-based cancer vaccines. However, due to the lack of verified neoantigen datasets and insufficient research on the properties of neoantigens, neoantigen prediction algorithms still need to be improved. Here, we recruited verified cancer antigen peptides and collected as much relevant peptide information as possible. Then, we discussed the role of each dataset for algorithm improvement in cancer antigen research, especially neoantigen prediction. A platform, Cancer Antigens Database (CAD, http://cad.bio-it.cn/), was designed to facilitate users to perform a complete exploration of cancer antigens online.

Adoptive Cellular Therapy for Multiple Myeloma Using CAR- and TCR-Transgenic T Cells: Response and Resistance

Despite the substantial improvement of therapeutic approaches, multiple myeloma (MM) remains mostly incurable. However, immunotherapeutic and especially T cell-based approaches pioneered the therapeutic landscape for relapsed and refractory disease recently. Targeting B-cell maturation antigen (BCMA) on myeloma cells has been demonstrated to be highly effective not only by antibody-derived constructs but also by adoptive cellular therapies. Chimeric antigen receptor (CAR)-transgenic T cells lead to deep, albeit mostly not durable responses with manageable side-effects in intensively pretreated patients. The spectrum of adoptive T cell-transfer covers synthetic CARs with diverse specificities as well as currently less well-established T cell receptor (TCR)-based personalized strategies. In this review, we want to focus on treatment characteristics including efficacy and safety of CAR- and TCR-transgenic T cells in MM as well as the future potential these novel therapies may have. ACT with transgenic T cells has only entered clinical trials and various engineering strategies for optimization of T cell responses are necessary to overcome therapy resistance mechanisms. We want to outline the current success in engineering CAR- and TCR-T cells, but also discuss challenges including resistance mechanisms of MM for evading T cell therapy and point out possible novel strategies.

Intercepting Premalignant, Preinvasive Breast Lesions Through Vaccination

Breast cancer (BC) prevention remains the ultimate cost-effective method to reduce the global burden of invasive breast cancer (IBC). To date, surgery and chemoprevention remain the main risk-reducing modalities for those with hereditary cancer syndromes, as well as high-risk non-hereditary breast lesions such as ADH, ALH, or LCIS. Ductal carcinoma in situ (DCIS) is a preinvasive malignant lesion of the breast that closely mirrors IBC and, if left untreated, develops into IBC in up to 50% of lesions. Certain high-risk patients with DCIS may have a 25% risk of developing recurrent DCIS or IBC, even after surgical resection. The development of breast cancer elicits a strong immune response, which brings to prominence the numerous advantages associated with immune-based cancer prevention over drug-based chemoprevention, supported by the success of dendritic cell vaccines targeting HER2-expressing BC. Vaccination against BC to prevent or interrupt the process of BC development remains elusive but is a viable option. Vaccination to intercept preinvasive or premalignant breast conditions may be possible by interrupting the expression pattern of various oncodrivers. Growth factors may also function as potential immune targets to prevent breast cancer progression. Furthermore, neoantigens also serve as effective targets for interception by virtue of strong immunogenicity. It is noteworthy that the immune response also needs to be strong enough to result in target lesion elimination to avoid immunoediting as it may occur in IBC arising from DCIS. Overall, if the issue of vaccine targets can be solved by interrupting premalignant lesions, there is a potential to prevent the development of IBC.

Comprehensive Analysis of Pyroptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Breast Cancer

Background

Immunotherapy has emerged as a significant strategy to treat numerous tumors. The positive response to immunotherapy depends on the dynamic interaction between tumor cells and infiltrating lymphocytes in the tumor microenvironment (TME). Pyroptosis, inflammation-induced cell death, is intricately associated with several tumors. However, the relationship between pyroptosis and clinical prognosis, immune cell infiltration, and immunotherapy effect is unclear in breast cancer (BRCA).

Methods

We comprehensively evaluated 33 pyroptosis-related genes and systematically assessed the relationship between pyroptosis and tumor progression, prognosis, and immune cell infiltration. The PyroptosisScore was used to quantify the pyroptosis pattern of a single tumor patient. We then assessed their values for predicting prognoses and therapeutic responses in BRCA.

Results

Three different modes of PyroptosisClusters were determined. The characteristics of TME cell infiltration in these three PyroptosisClusters were highly consistent with three immunophenotypes of tumors, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Comprehensive bioinformatics analysis revealed that patients with a low PyroptosisScore had higher immune checkpoint expression, higher immune checkpoint inhibitor (ICI) scores, increased immune microenvironment infiltration, and were more sensitive to immunotherapy than those with a high PyroptosisScore.

Conclusions

Our findings revealed the crucial role of pyroptosis in maintaining the diversity and complexity of TME. Pyroptosis is closely related to tumor progression, tumor prognosis, and immunotherapy response. Evaluating the PyroptosisScore of a single tumor can assist in understanding the characteristics of TME infiltration and lead to the development of more effective immunotherapy strategies.

Neoantigens elicit T cell responses in breast cancer

Neoantigens are tumour-specific antigens that arise from non-synonymous mutations in tumour cells. However, their effect on immune responses in the tumour microenvironment remains unclear in breast cancer. We performed whole exome and RNA sequencing of 31 fresh breast cancer tissues and neoantigen prediction from non-synonymous single nucleotide variants (nsSNVs) among exonic mutations. Neoantigen profiles were determined by predictive HLA binding affinity (IC₅₀ < 500 nM) and mRNA expression with a read count of ≥ 1. We evaluated the association between neoantigen load and expression levels of immune-related genes. Moreover, using primary tumour cells established from pleural fluid of a breast cancer patient with carcinomatous pleurisy, we induced cytotoxic T lymphocytes (CTLs) by coculturing neoantigen peptide-pulsed dendritic cells (DCs) with autologous peripheral lymphocytes. The functions of CTLs were examined by cytotoxicity and IFN-γ ELISpot assays. Neoantigen load ranged from 6 to 440 (mean, 95) and was positively correlated to the total number of nsSNVs. Although no associations between neoantigen load and mRNA expression of T cell markers were observed, the coculture of neoantigen-pulsed DCs and lymphocytes successfully induced CTLs ex vivo. These results suggest that neoantigen analysis may have utility in developing strategies to elicit T cell responses.

Challenges targeting cancer neoantigens in 2021: a systematic literature review

Introduction: Cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction algorithms, and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. Unfortunately, results from preclinical studies and early phase clinical trials highlight important challenges to the successful clinical translation of neoantigen cancer vaccines.Areas covered: In this review, we provide an overview of current strategies for the identification and prioritization of cancer neoantigens with a particular emphasis on the two most common strategies used for neoantigen identification: (1) direct identification of peptide ligands eluted from peptide-MHC complexes, and (2) next-generation sequencing combined with neoantigen prediction algorithms. We highlight the limitations of current neoantigen prediction pipelines, and discuss broader challenges associated with cancer neoantigen vaccines including tumor purity/heterogeneity and the immunosuppressive tumor microenvironment.Expert opinion: Despite current limitations, neoantigen prediction is likely to improve rapidly based on advances in sequencing, machine learning, and information sharing. The successful development of robust cancer neoantigen prediction strategies is likely to have a significant impact, with the potential to facilitate cancer neoantigen vaccine design.

Stay on Target: Reengaging Cancer Vaccines in Combination Immunotherapy

Effective treatment of established tumors requires rational multicombination immunotherapy strategies designed to target all functions of the patient immune system and tumor immune microenvironment. While these combinations build on the foundation of successful immune checkpoint blockade antibodies, it is increasingly apparent that successful immunotherapy will also require a cancer vaccine backbone to engage the immune system, thereby ensuring that additional immuno-oncology agents will engage a tumor-specific immune response. This review summarizes ongoing clinical trials built upon the backbone of cancer vaccines and focusing on those clinical trials that utilize multicombination (3+) immuno-oncology agents. We examine combining cancer vaccines with multiple checkpoint blockade antibodies, novel multifunctional molecules, adoptive cell therapy and immune system agonists. These combinations and those yet to enter the clinic represent the future of cancer immunotherapy. With a cancer vaccine backbone, we are confident that current and coming generations of rationally designed multicombination immunotherapy can result in effective therapy of established tumors.

HIV-1 genomic RNA U3 region forms a stable quadruplex-hairpin structure

The U3 promoter region of the HIV-1 long terminal repeat (LTR) has previously been shown to fold into a series of dynamic G-quadruplex structures. Among the G-quadruplexes identified in the LTR sequence, LTR-III was shown to be the most stable in vitro. NMR studies of this 28-nucleotide (nt) DNA revealed a unique quadruplex-hairpin structure. Whether the hairpin forms in RNA element is unknown and the role of the hairpin in the structure and stability of quadruplexes has not been characterized. Here, we used optical and thermodynamic studies to address these questions. The wild-type LTR-III RNA formed a monomolecular quadruplex with a parallel topology using only propeller loops, including the hairpin loop element. By comparison to the WT and variant RNAs, LTR-III DNA structures were more heterogeneous and less stable. Increased stability of the RNA suggests that the RNA quadruplex-hairpin structure may be a more attractive therapeutic target than the analogous DNA element.

Immunotherapy for Breast Cancer Treatment

Breast cancer, as a heterogeneous disease, includes a wide range of pathological and clinical behaviors. Current treatment protocols, including radiotherapy, chemotherapy, and hormone replacement therapy, are mainly associated with poor response and high rate of recurrence. Therefore, more efforts are needed to develop alternative therapies for this type of cancer. Immunotherapy, as a novel strategy in cancer treatment, has a potential in treating breast cancer patients. Although breast cancer has long been considered problematic to treat with immunotherapy, as it is immunologically "cold," numerous newer preclinical and clinical reports now recommend that immunotherapy has the capability to treat breast cancer patients. In this review, we highlight the different immunotherapy strategies in breast cancer treatment.

Optimized polyepitope neoantigen DNA vaccines elicit neoantigen-specific immune responses in preclinical models and in clinical translation

BACKGROUND

Preclinical studies and early clinical trials have shown that targeting cancer neoantigens is a promising approach towards the development of personalized cancer immunotherapies. DNA vaccines can be rapidly and efficiently manufactured and can integrate multiple neoantigens simultaneously. We therefore sought to optimize the design of polyepitope DNA vaccines and test optimized polyepitope neoantigen DNA vaccines in preclinical models and in clinical translation.

METHODS

We developed and optimized a DNA vaccine platform to target multiple neoantigens. The polyepitope DNA vaccine platform was first optimized using model antigens in vitro and in vivo. We then identified neoantigens in preclinical breast cancer models through genome sequencing and in silico neoantigen prediction pipelines. Optimized polyepitope neoantigen DNA vaccines specific for the murine breast tumor E0771 and 4T1 were designed and their immunogenicity was tested in vivo. We also tested an optimized polyepitope neoantigen DNA vaccine in a patient with metastatic pancreatic neuroendocrine tumor.

RESULTS

Our data support an optimized polyepitope neoantigen DNA vaccine design encoding long (≥20-mer) epitopes with a mutant form of ubiquitin (Ubmut) fused to the N-terminus for antigen processing and presentation. Optimized polyepitope neoantigen DNA vaccines were immunogenic and generated robust neoantigen-specific immune responses in mice. The magnitude of immune responses generated by optimized polyepitope neoantigen DNA vaccines was similar to that of synthetic long peptide vaccines specific for the same neoantigens. When combined with immune checkpoint blockade therapy, optimized polyepitope neoantigen DNA vaccines were capable of inducing antitumor immunity in preclinical models. Immune monitoring data suggest that optimized polyepitope neoantigen DNA vaccines are capable of inducing neoantigen-specific T cell responses in a patient with metastatic pancreatic neuroendocrine tumor.

CONCLUSIONS

We have developed and optimized a novel polyepitope neoantigen DNA vaccine platform that can target multiple neoantigens and induce antitumor immune responses in preclinical models and neoantigen-specific responses in clinical translation.

Immunotherapy for Breast Cancer Treatment

Breast cancer, as a heterogeneous disease, includes a wide range of pathological and clinical behaviors. Current treatment protocols, including radiotherapy, chemotherapy, and hormone replacement therapy, are mainly associated with poor response and high rate of recurrence. Therefore, more efforts are needed to develop alternative therapies for this type of cancer. Immunotherapy, as a novel strategy in cancer treatment, has a potential in treating breast cancer patients. Although breast cancer has long been considered problematic to treat with immunotherapy, as it is immunologically "cold," numerous newer preclinical and clinical reports now recommend that immunotherapy has the capability to treat breast cancer patients. In this review, we highlight the different immunotherapy strategies in breast cancer treatment.

Humanized Mouse Models to Evaluate Cancer Immunotherapeutics

Immunotherapy is at the forefront of cancer treatment. The advent of numerous novel approaches to cancer immunotherapy, including immune checkpoint antibodies, adoptive transfer of CAR (chimeric antigen receptor) T cells and TCR (T cell receptor) T cells, NK (natural killer) cells, T cell engagers, oncolytic viruses, and vaccines, is revolutionizing the treatment for different tumor types. Some are already in the clinic, and many others are underway. However, not all patients respond, resistance develops, and as available therapies multiply there is a need to further understand how they work, how to prioritize their clinical evaluation, and how to combine them. For this, animal models have been highly instrumental, and humanized mice models (i.e., immunodeficient mice engrafted with human immune and cancer cells) represent a step forward, although they have several limitations. Here, we review the different humanized models available today, the approaches to overcome their flaws, their use for the evaluation of cancer immunotherapies, and their anticipated evolution as tools to help personalized clinical decision-making.

PPP2R2B downregulation is associated with immune evasion and predicts poor clinical outcomes in triple-negative breast cancer

Background

Although immune checkpoint blockade has emerged as a novel promising strategy for triple-negative breast cancer (TNBC), many patients fail response or acquire resistance to current agents. Consequently, our focus need to shift toward alternative inhibitory targets, predictor for responsiveness, and immune suppressive mechanisms.

Methods

In this study, we performed systematic bioinformatics analyses to identify PPP2R2B as a robust tumor suppressor in TNBC. Meanwhile, breast cancer progression cell line model was applied in our research. Quantitative real-time PCR assay (Q-PCR) was carried out to assess the role of PPP2R2B in the onset and progression of breast cancer. Furthermore, we validated the effect of PPP2R2B on immune activity via in vitro experiments based on macrophages. To further decipher the roles of PPP2R2B in TNBC, we investigated the transcriptome level, genomic profiles, and its clinical prognostic value.

Results

In TNBC tissues, PPP2R2B expression was significantly downregulated compared to normal breast tissues. Kaplan‐Meier survival analysis revealed that patients with low PPP2R2B expression had shorter survival time than those with high PPP2R2B expression. Q-PCR analysis suggested that PPP2R2B downregulation could play a key role in breast-cancer initiation and progression. Additionally, our findings showed that PPP2R2B was positively related with CD8 T cells, CD4 Th1 helper cells, and M1 macrophages, but negatively related with M2 macrophages. Subsequent results identified that PPP2R2B was strongly related with immune inhibitor genes (GZMA, PRF1, and IFNG), which could improve T lymphocytes antitumor function and restrict immune evasion. Meanwhile, T cell receptor signaling pathway and antigen processing and presentation signaling pathway were significantly suppressed in low PPP2R2B expression group. Afterwards, distinct subgroups based on PPP2R2B expression exhibited several unique features in somatic mutations, copy numbers alterations, extent of copy number burden, and promoter methylation level.

Conclusion

Our results indicated that PPP2R2B could serve as a promising biomarker for TNBC, and help predict immunotherapeutic response and guide personalized strategies in TNBC treatment.

The nature of triple-negative breast cancer classification and antitumoral strategies

Identifying the patterns of gene expression in breast cancers is essential to understanding their pathophysiology and developing anticancer drugs. Breast cancer is a heterogeneous disease with different subtypes determined by distinct biological features. Luminal breast cancer is characterized by a relatively high expression of estrogen receptor (ER) and progesterone receptor (PR) genes, which are expressed in breast luminal cells. In ~25% of invasive breast cancers, human epidermal growth factor receptor 2 (HER2) is overexpressed; these cancers are categorized as the HER2 type. Triple-negative breast cancer (TNBC), in which the cancer cells do not express ER/PR or HER2, shows highly aggressive clinical outcomes. TNBC can be further classified into specific subtypes according to genomic mutations and cancer immunogenicity. Herein, we discuss the brief history of TNBC classification and its implications for promising treatments.

Systematically Characterizing A-to-I RNA Editing Neoantigens in Cancer

A-to-I RNA editing can contribute to the transcriptomic and proteomic diversity of many diseases including cancer. It has been reported that peptides generated from RNA editing could be naturally presented by human leukocyte antigen (HLA) molecules and elicit CD8+ T cell activation. However, a systematical characterization of A-to-I RNA editing neoantigens in cancer is still lacking. Here, an integrated RNA-editing based neoantigen identification pipeline PREP (Prioritizing of RNA Editing-based Peptides) was presented. A comprehensive RNA editing neoantigen profile analysis on 12 cancer types from The Cancer Genome Atlas (TCGA) cohorts was performed. PREP was also applied to 14 ovarian tumor samples and two clinical melanoma cohorts treated with immunotherapy. We finally proposed an RNA editing neoantigen immunogenicity score scheme, i.e. REscore, which takes RNA editing level and infiltrating immune cell population into consideration. We reported variant peptide from protein IFI30 in breast cancer which was confirmed expressed and presented in two samples with mass spectrometry data support. We showed that RNA editing neoantigen could be identified from RNA-seq data and could be validated with mass spectrometry data in ovarian tumor samples. Furthermore, we characterized the RNA editing neoantigen profile of clinical melanoma cohorts treated with immunotherapy. Finally, REscore showed significant associations with improved overall survival in melanoma cohorts treated with immunotherapy. These findings provided novel insights of cancer biomarker and enhance our understanding of neoantigen derived from A-to-I RNA editing as well as more types of candidates for personalized cancer vaccines design in the context of cancer immunotherapy.

Wnt signaling in breast cancer: biological mechanisms, challenges and opportunities

Wnt signaling is a highly conserved signaling pathway that plays a critical role in controlling embryonic and organ development, as well as cancer progression. Genome-wide sequencing and gene expression profile analyses have demonstrated that Wnt signaling is involved mainly in the processes of breast cancer proliferation and metastasis. The most recent studies have indicated that Wnt signaling is also crucial in breast cancer immune microenvironment regulation, stemness maintenance, therapeutic resistance, phenotype shaping, etc. Wnt/β-Catenin, Wnt-planar cell polarity (PCP), and Wnt-Ca2+ signaling are three well-established Wnt signaling pathways that share overlapping components and play different roles in breast cancer progression. In this review, we summarize the main findings concerning the relationship between Wnt signaling and breast cancer and provide an overview of existing mechanisms, challenges, and potential opportunities for advancing the therapy and diagnosis of breast cancer.

Needle in a Haystack: The Naïve Repertoire as a Source of T Cell Receptors for Adoptive Therapy with Engineered T Cells

T cell engineering with antigen-specific T cell receptors (TCRs) has allowed the generation of increasingly specific, reliable, and versatile T cell products with near-physiological features. However, a broad applicability of TCR-based therapies in cancer is still limited by the restricted number of TCRs, often also of suboptimal potency, available for clinical use. In addition, targeting of tumor neoantigens with TCR-engineered T cell therapy moves the field towards a highly personalized treatment, as tumor neoantigens derive from somatic mutations and are extremely patient-specific. Therefore, relevant TCRs have to be de novo identified for each patient and within a narrow time window. The naïve repertoire of healthy donors would represent a reliable source due to its huge diverse TCR repertoire, which theoretically entails T cells for any antigen specificity, including tumor neoantigens. As a challenge, antigen-specific naïve T cells are of extremely low frequency and mostly of low functionality, making the identification of highly functional TCRs finding a "needle in a haystack." In this review, we present the technological advancements achieved in high-throughput mapping of patient-specific neoantigens and corresponding cognate TCRs and how these platforms can be used to interrogate the naïve repertoire for a fast and efficient identification of rare but therapeutically valuable TCRs for personalized adoptive T cell therapy.

Opportunities for Antigen Discovery in Metastatic Breast Cancer

Immune checkpoint inhibitor-based immunotherapy (ICI) of breast cancer is currently efficacious in a fraction of triple negative breast cancers (TNBC) as these cancers generally carry high tumor mutation burden (TMB) and show increased tumor infiltration by CD8+ T cells. However, most estrogen receptor positive breast cancers (ERBC) have low TMB and/or are infiltrated with immunosuppressive regulatory T cells (Tregs) and thus fail to induce a significant anti-tumor immune response. Our understanding of the immune underpinning of the anti-tumor effects of CDK4/6 inhibitor (CDKi) treatment coupled with new knowledge about the mechanisms of tolerance to self-antigens suggests a way forward, specifically via characterizing and exploiting the repertoire of tumor antigens expressed by metastatic ERBC. These treatment-associated tumor antigens (TATA) may include the conventional tumor neoantigens (TNA) encoded by single nucleotide mutations, TNA encoded by tumor specific aberrant RNA transcription, splicing and DNA replication induced frameshift (FS) events as well as the shared tumor antigens. The latter may include the conventional tumor associated antigens (TAA), cancer-testis antigens (CTA) and antigens encoded by the endogenous retroviral (ERV) like sequences and repetitive DNA sequences induced by ET and CDKi treatment. An approach to identifying these antigens is outlined as this will support the development of a multi-antigen-based immunotherapy strategy for improved targeting of metastatic disease with potential for minimal autoimmune toxicity against normal tissues.

Prevalence and clinical relevance of tumor-associated tissue eosinophilia (TATE) in breast cancer

BACKGROUND

Tumor-associated tissue eosinophilia (TATE) has been associated with outcomes in a variety of solid tumors; however, its role in breast cancer is not well defined. We hypothesized that tumor-associated tissue eosinophilia is associated with a high mutation and neoantigen load, and we assessed its correlation with cancer outcomes.

METHODS

The Cancer Genome Atlas was analyzed for eosinophil signatures in breast cancer specimens. Descriptive analyses were performed, including the tumor-infiltrating cell composition using CIBERSORT, cytolytic activity score, and gene set enrichment analysis. Overall survival and disease-free survival were calculated using the Kaplan-Meier method.

RESULTS

Out of 1069 cases analyzed, 40 (3.7%) had tissue eosinophils (the tumor-associated tissue eosinophilia group). Tumor-associated tissue eosinophilia was noted in 32.5% luminal, 5% HER2-positive, and 15% triple-negative breast cancer subtypes. The single nucleotide variant-neoantigen load was significantly higher in the tumor-associated tissue eosinophilia group (P = .005), with a higher nonsilent mutation rate (P = .01). The tumor-associated tissue eosinophilia group had lower cytolytic activity (P = .02) but had enriched MYC-targeted (P = .002), E2F-targeted (P = .04), deoxyribonucleic acid repair (P = .03), and unfolded protein response gene sets (P = .05). Tumor-associated tissue eosinophilia was associated with a trend toward improved disease-free survival (P = .06) but presented no differences in overall survival (P = .56).

CONCLUSION

Tumor-associated tissue eosinophilia was noted in 3.7% of breast cancers and was associated with a higher single nucleotide variant-neoantigen load and nonsilent mutation rate, similar to that of tumor-infiltrating lymphocytes in the triple-negative subtype. However, a lower cytolytic activity score and enriched cell proliferation-related gene sets implicate different roles for tumor-associated tissue eosinophilia than for tumor-infiltrating lymphocytes.

The Immune Landscape and Prognostic Immune Key Genes Potentially Involved in Modulating Synaptic Functions in Prostate Cancer

Background: Increasing evidence has indicated an association between differentially expressed genes (DEGs) in tumor-infiltrating immune cells (TIICs) and clinical outcome. The aim of this research is to investigate the influence of tumor microenvironment on the gene expression profile of TIICs and to identify their potential markers for modulating immune cell function in prostate cancer.

Methods: In our research, CIBERSORT algorithm was utilized to calculate the proportion of the TIICs in 164 tumor and 18 control samples from The Cancer Genome Atlas cohort. The differential expression analysis was conducted using R, and then the functional and the pathway enrichments of the DEGs were analyzed using Database for Annotation, Visualization, and Integrated Discovery, followed by integrated regulatory network analysis.

Results: As a result, nTreg, B cells, Th1, and DC cells were significantly increased, accompanied by largely decreased NK and NKT cells. The expressed immune-related gene correlation analysis showed that the signature gene expression extent of CD8 T cells was positively associated with CD4 memory activated T cells but negatively correlated with that of CD4 memory resting T cells. In addition, a total of 128 differentially expressed genes were identified. CytoHubba analysis obtained six hub genes, of which three prognostic-associated potential key molecules including CAV1, FLNA, and VCL were mainly involved in biological processes associated with the regulation of organic substance and synaptic connections.

Conclusions: This study provides a comprehensive understanding of the landscape of TIICs and the roles of the hub genes which may be valuable markers in prostate cancer diagnosis and immunotherapy.

Progress in Neoantigen Targeted Cancer Immunotherapies

Immunotherapies that harness the immune system to kill cancer cells have showed significant therapeutic efficacy in many human malignancies. A growing number of studies have highlighted the relevance of neoantigens in recognizing cancer cells by intrinsic T cells. Cancer neoantigens are a direct consequence of somatic mutations presenting on the surface of individual cancer cells. Neoantigens are fully cancer-specific and exempt from central tolerance. In addition, neoantigens are important targets for checkpoint blockade therapy. Recently, technological innovations have made neoantigen discovery possible in a variety of malignancies, thus providing an impetus to develop novel immunotherapies that selectively enhance T cell reactivity for the destruction of cancer cells while leaving normal tissues unharmed. In this review, we aim to introduce the methods of the identification of neoantigens, the mutational patterns of human cancers, related clinical trials, neoantigen burden and sensitivity to immune checkpoint blockade. Moreover, we focus on relevant challenges of targeting neoantigens for cancer treatment.

Neoantigen-Specific Adoptive Cell Therapies for Cancer: Making T-Cell Products More Personal

Mutation-derived neoantigens are taking central stage as a determinant in eliciting effective antitumor immune responses following adoptive T-cell therapies. These mutations are patient-specific, and their targeting calls for highly personalized pipelines. The promising clinical outcomes of tumor-infiltrating lymphocyte (TIL) therapy have spurred interest in generating T-cell infusion products that have been selectively enriched in neoantigen (or autologous tumor) reactivity. The implementation of an isolation step, prior to T-cell in vitro expansion and reinfusion, may provide a way to improve the overall response rates achieved to date by adoptive T-cell therapies in metastatic cancer patients. Here we provide an overview of the main technologies [i.e., peptide major histocompatibility complex (pMHC) multimers, cytokine capture, and activation markers] to enrich infiltrating or circulating T-cells in predefined neoantigen specificities (or tumor reactivity). The unique technical and regulatory challenges faced by such highly specialized and patient-specific manufacturing T-cell platforms are also discussed.

INeo-Epp: A Novel T-Cell HLA Class-I Immunogenicity or Neoantigenic Epitope Prediction Method Based on Sequence-Related Amino Acid Features

In silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g., proteasomal cleavage, transporter associated with antigen processing (TAP), and major histocompatibility complex (MHC) combination. To date, however, the mechanism for the immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties, and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including the amino acid physicochemical property of the epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score, and frequency score for an immunogenic peptide. Subsequently, a random forest classifier for T-cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC = 0.81, external validation data set AUC = 0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called "neoantigens." Based on mutation information and sequence-related amino acid characteristics, a prediction model of a neoantigen was established as well (the optimal AUC = 0.78). Further, an easy-to-use web-based tool "INeo-Epp" was developed for the prediction of human immunogenic antigen epitopes and neoantigen epitopes.

Antibodies specific for disease-associated antigens (DAA) expressed in non-malignant diseases reveal potential new tumor-associated antigens (TAA) for immunotherapy or immunoprevention

Immune responses to a large number of mutated and non-mutated tumor antigens have been studied in an attempt to unravel the highly complex immune response to cancer. Better understanding of both the effectors and the targets of successful immunosurveillance can inform various immunotherapeutic approaches, which can strengthen or replace natural immunosurveillance that a tumor has managed to escape. In this review we highlight targets of antibodies generated in the context of diseases other than cancer, such as asthma, allergies, autoimmune disorders, inflammation and infections, where the antibody presence correlates either with an increased or a reduced lifetime risk of cancer. We focus on their target antigens, self-molecules abnormally expressed on diseased cells or cross-reactive with exogenous antigens and found on cancer cells as tumor associated antigens (TAA). We refer to them as disease-associated antigens (DAA). We review 4 distinct categories of antibodies according to their target DAA, their origin and their reported impact on cancer risk: natural antibodies, autoantibodies, long-term memory antibodies and allergy-associated antibodies. Increased understanding and focus on their specific targets could enable a more rational choice of antigens for both therapeutic and preventative cancer vaccines and other more effective and less toxic cancer immunotherapies.

PDL1-targeted vaccine exhibits potent antitumor activity by simultaneously blocking PD1/PDL1 pathway and activating PDL1-specific immune responses

Despite the clinical success of immune checkpoint blockade, only a subset of people exhibits durable responses, suggesting that an alternative immunotherapeutic strategy is required. This paper reported a two-in-one cancer vaccine that targets programmed death ligand 1 (PDL1) that blocks the PD1/PDL1 pathway and also activates antitumor immune response. The PDL1- NitraTh vaccine, which consists of the extracellular domain of PDL1 and nitrated T cell epitope, effectively broke the immune tolerance of PDL1 and elicited PDL1-specific humoral and cellular immunity. The treatment of PDL1-NitraTh exhibited potent antitumor activity. Moreover, immunization of PDL1 vaccine increased the infiltration of tumor lymphocytes and decreased the proportion of Treg cells in tumor tissues, suggesting that the vaccine may remodel the tumor microenvironment. The upregulation of PDL1 in tumor tissues was induced by PDL1-NitraTh vaccine but not in spleen and lymphomas. This upregulation of PDL1 is beneficial to the antitumor activity of PDL1-specific humoral and cellular immunity induced by PDL1-NitraTh. In summary, PDL1-targeted vaccine exhibits potent antitumor activity and may provide an alternative immunotherapy strategy for patients who are not sensitive to PDL1 antibody drugs.

Immunotherapy: A Challenge of Breast Cancer Treatment

Breast cancer is the most commonly diagnosed cancer in women and is a leading cause of cancer death in women worldwide. Despite the significant benefit of the use of conventional chemotherapy and monoclonal antibodies in the prognosis of breast cancer patients and although the recent approval of the anti-PD-L1 antibody atezolizumab in combination with chemotherapy has been a milestone for the treatment of patients with metastatic triple-negative breast cancer, immunologic treatment of breast tumors remains a great challenge. In this review, we summarize current breast cancer classification and standard of care, the main obstacles that hinder the success of immunotherapies in breast cancer patients, as well as different approaches that could be useful to enhance the response of breast tumors to immunotherapies.

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

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

Tumor antigens heterogeneity and immune response-targeting neoantigens in breast cancer

Breast cancer is both the most common type of cancer and the most frequent cause of cancer mortality in women, mainly because of its heterogeneity and limited immunogenicity. The aim of specific active cancer immunotherapy is to stimulate the host's immune response against cancer cells directly using a vaccine platform carrying one or more tumor antigens. In particular, the ideal tumor antigen should be able to elicit T cell and B cell responses, be specific for the tumor and be expressed at high levels on cancer cells. Neoantigens are ideal targets for immunotherapy because they are exclusive to individual patient's tumors, are absent in healthy tissues and are not subject to immune tolerance mechanisms. Thus, neoantigens should generate a specific reaction towards tumors since they constitute the largest fraction of targets of tumor-infiltrating T cells. In this review, we describe the technologies used for neoantigen discovery, the heterogeneity of neoantigens in breast cancer and recent studies of breast cancer immunotherapy targeting neoantigens.

Tumor neoantigens: from basic research to clinical applications

Tumor neoantigen is the truly foreign protein and entirely absent from normal human organs/tissues. It could be specifically recognized by neoantigen-specific T cell receptors (TCRs) in the context of major histocompatibility complexes (MHCs) molecules. Emerging evidence has suggested that neoantigens play a critical role in tumor-specific T cell-mediated antitumor immune response and successful cancer immunotherapies. From a theoretical perspective, neoantigen is an ideal immunotherapy target because they are distinguished from germline and could be recognized as non-self by the host immune system. Neoantigen-based therapeutic personalized vaccines and adoptive T cell transfer have shown promising preliminary results. Furthermore, recent studies suggested the significant role of neoantigen in immune escape, immunoediting, and sensitivity to immune checkpoint inhibitors. In this review, we systematically summarize the recent advances of understanding and identification of tumor-specific neoantigens and its role on current cancer immunotherapies. We also discuss the ongoing development of strategies based on neoantigens and its future clinical applications.

Structure Based Prediction of Neoantigen Immunogenicity

The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8+ T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

Next-generation sequencing technologies accelerate advances in T-cell therapy for cancer

Next-generation sequencing has produced a large quantity of DNA or RNA sequences related to the processes occurring within tumors and their microenvironment in a reasonable time and cost. These data have been used to guide the identification of neoantigens and to determine their specific T-cell receptors. Furthermore, adoptive T-cell therapy targeting neoantigens is under development for cancer treatment. In this review, we first provide an overview of sequencing technologies and the updated findings concerning neoantigens related to adoptive T-cell therapy and then summarize the methods and principles underlying the development of next-generation sequencing-based neoantigen-reactive T-cell therapy for cancer.