HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer

Identification of BRCA new prognostic targets and neoantigen candidates from fusion genes

Cancer-associated gene fusions serve as a potential source of highly immunogenic neoantigens. In this study, we identified fusion proteins from fusion genes and extracted fusion peptides to accurately predict Breast cancer (BRCA) neo-antigen candidates by high-throughput artificial intelligence computation. Firstly, Deepsurv was used to evaluate the prognosis of patients, providing a landscape of prognostic fusion genes in BRCA. Next, AGFusion was utilized to generate full-length fusion protein sequences and annotate functional domains. Advanced neural networks and Transformer-based analyses were implemented to predict the binding of fusion peptides to 112 types of HLA, thereby forming a new immunotherapy candidates' library of BRCA neo-antigens (n = 7791, covering 88.41% of patients). Among them, 15 neo-antigens were validated and factually translated into mass spectrometry data of BRCA patients. Finally, AlphaFold2 was applied to predict the binding sites of these neo-antigens to MHC (HLA) molecules. Notably, we identified a prognostic neoantigen from the TBC1D4-COMMD6 fusion that significantly improves patient prognosis and extensively binds to 16 types of HLA alleles. These highly immunogenic and tumor-specific neoantigens offer emerging targets for personalized cancer immunotherapies and act as prospective predictors for tumor survival prognosis and responses to immune checkpoint therapies.

Biomarkers to predict the benefits of immune‑checkpoint blockade‑based therapy in patients with malignant peritoneal mesothelioma (Review)

Malignant peritoneal mesothelioma (MPeM) is a type of rare and highly lethal tumor. Immune checkpoint blockade (ICB)-based therapy has shown encouraging clinical activity for MPeM. However, no definitive biomarkers have been identified for predicting which patients with MPeM will benefit from ICB-based therapy. At present, there are several novel potential biomarkers proposed for predicting the response to ICB-based therapy, and biomarkers available in MPeM cells and in the tumor microenvironment have been identified with the potential to predict the efficacy of ICB-based therapy in MPeM. According to the molecular characteristics of MPeM itself, the feasibility of biomarkers in practice, and the body of available evidence, we hypothesize that the following five types of biomarkers can be used to predict the response of ICB-based therapy in patients with MPeM: Tertiary lymphoid structures, immune checkpoints and their ligands, fusion gene neoantigen burden, BRCA1-associated protein-1 haploinsufficiency and transcriptome-based biomarkers. The present review discusses the value and limitations of each type of biomarker, and potential solutions to address the limitations are proposed. The aim of the present review is to provide a background for future studies on ICB-based therapy for MPeM.

Breast cancer, viruses, and human leukocyte antigen (HLA)

Several viruses have been implicated in breast cancer, including human herpes virus 4 (HHV4), human herpes virus 5 (HHV5), human papilloma virus (HPV), human JC polyoma virus (JCV), human endogenous retrovirus group K (HERVK), bovine leukemia virus (BLV) and mouse mammary tumor virus (MMTV). Human leukocyte antigen (HLA) is involved in virus elimination and has been shown to influence breast cancer protection/susceptibility. Here we investigated the hypothesis that the contribution of a virus to development of breast cancer would depend on the presence of the virus, which, in turn, would be inversely related to the success of its elimination. For that purpose, we estimated in silico predicted binding affinities (PBA) of proteins of the 7 viruses above to 127 common HLA alleles (69 Class I [HLA-I] and 58 Class II HLA-II]) and investigated the association of these binding affinities to the breast cancer-HLA (BC-HLA) immunogenetic profile of the same alleles. Using hierarchical tree clustering, we found that, for HLA-I, viruses BLV, JCV and MMTV were grouped with the BC-HLA, whereas, for HLA-II, viruses BLV, HERVK, HPV, JCV, and MMTV were grouped with BC-HLA. Finally, for both HLA classes, the average PBAs of the viruses grouped with the BC-HLA profile were significantly lower than those of the other, non BC-HLA associated viruses. Assuming that low PBAs are likely associated with slower viral elimination, these findings support the hypothesis that a defective/slower elimination and, hence, longer persistence and inefficient/delayed production of antibodies against them underlies the observed association of the low-PBA group with breast cancer.

RNA vaccines for cancer: Principles to practice

Vaccines are the most impactful medicines to improve health. Though potent against pathogens, vaccines for cancer remain an unfulfilled promise. However, recent advances in RNA technology coupled with scientific and clinical breakthroughs have spurred rapid discovery and potent delivery of tumor antigens at speed and scale, transforming cancer vaccines into a tantalizing prospect. Yet, despite being at a pivotal juncture, with several randomized clinical trials maturing in upcoming years, several critical questions remain: which antigens, tumors, platforms, and hosts can trigger potent immunity with clinical impact? Here, we address these questions with a principled framework of cancer vaccination from antigen detection to delivery. With this framework, we outline features of emergent RNA technology that enable rapid, robust, real-time vaccination with somatic mutation-derived neoantigens-an emerging "ideal" antigen class-and highlight latent features that have sparked the belief that RNA could realize the enduring vision for vaccines against cancer.

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.

Comprehensive profiling of cancer neoantigens from aberrant RNA splicing

BACKGROUND

Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings.

METHODS

First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays.

RESULTS

We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus.

CONCLUSIONS

SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.

Global research landscape and trends of cancer radiotherapy plus immunotherapy: A bibliometric analysis

The aim of this study was to present current research trends on the synergistic use of radiotherapy and immunotherapy (IRT) for cancer treatment. On March 1, 2023, we conducted a literature search for IRT papers using the Web of Science database. We extracted information and constructed two databases - the Core Database (CD) with 864 papers and Generalized Database (GD) with 6344 papers. A bibliometric analysis was performed to provide insights into the research landscape, to identify emerging trends and highly cited papers and journals in the field of IRT. The CD contained 864 papers that were collectively cited 31,818 times. Prominent journals in this area included the New England Journal of Medicine, Lancet Oncology, and the Journal of Clinical Oncology. Corresponding authors from the USA contributed the most publications. In recent years, lung cancer, melanoma, stereotactic radiotherapy, immune checkpoint inhibitors, and the tumor microenvironment emerged as hot research areas. This bibliometric analysis presented quantitative insights into research concerning IRT and proposed potential avenues for further exploration. Moreover, researchers can use our findings to select appropriate journals for publication or identify prospective collaborators. In summary, this bibliometric analysis provides a comprehensive overview of the historical progression and recent advancements in IRT research that may serve as inspiration for future investigations.

Possible impact of HLA class I and class II on malignancies driven by a single germ-line BRCA1 mutation

This study provides the first immunogenetic preliminary evidence that specific human leucocyte antigen (HLA) class I and class II alleles and haplotypes may be relevant for BRCA1 c.5263_5264insC driven oncogenesis. Observed HLA associations might have practical implications for establishment of predictive markers for the response to immunotherapies in malignancies driven by this germ-line mutation.

Prognostic and Clinical Significance of Human Leukocyte Antigen Class I Expression in Breast Cancer: A Meta-Analysis

BACKGROUND

The value of human leukocyte antigen (HLA; also known as major histocompatibility complex) class I expression for the prediction of breast cancer survival outcomes remains unclear. We conducted a meta-analysis to explore the prognostic significance of this expression.

MATERIALS AND METHODS

We searched electronic databases to identify reports on associations of HLA class I protein or mRNA expression with survival outcomes and clinicopathological factors in the breast cancer context. Pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were used to conduct a quantitative meta-analysis.

RESULTS

The sample comprised eight studies involving 3590 patients. Only the classical HLA class Ia (HLA-ABC) molecules studies were included in this meta-analysis. Elevated HLA class I protein expression was found to be significantly related to better disease-free survival (DFS) (HR 0.58, 95% CI 0.35-0.95, P = 0.03), particularly among patients with triple-negative breast cancer (TNBC) (HR 0.31, 95% CI 0.18-0.52, P < 0.001), but not to overall survival. It was also associated with estrogen receptor (ER) negativity (OR 1.71, 95% CI 1.24-2.35, P = 0.001), progesterone receptor (PR) negativity (OR 1.49, 95% CI 1.22-1.81, P < 0.001), human epidermal growth factor receptor 2 (HER2) positivity (OR 1.51, 95% CI 1.18-1.94, P = 0.001), TNBC (OR 1.68, 95% CI 1.15-2.45, P < 0.01), high Ki-67 indices (OR 2.06, 95% CI 1.62-2.61, P < 0.001), and high nuclear grades (OR 2.67, 95% CI 2.17-3.29, P < 0.001).

CONCLUSION

This meta-analysis demonstrated that enhanced HLA class I protein expression is significantly associated with the better DFS of patients with breast cancer, especially TNBC, as well as with ER and PR negativity, HER2 positivity, TNBC, and high Ki-67 indices and nuclear grades. The immune target HLA class I may serve as a prognostic indicator for breast cancer.

In silico designed mRNA vaccines targeting CA-125 neoantigen in breast and ovarian cancer

Somatic mutation-derived neoantigens are associated with patient survival in breast and ovarian cancer. These neoantigens are targets for cancer, as shown by the implementation of neoepitope peptides as cancer vaccines. The success of cost-effective multi-epitope mRNA vaccines against SARS-Cov-2 in the pandemic established a model for reverse vaccinology. In this study, we aimed to develop an in silico pipeline designing an mRNA vaccine of the CA-125 neoantigen against breast and ovarian cancer, respectively. Using immuno-bioinformatics tools, we predicted cytotoxic CD8+ T cell epitopes based on somatic mutation-driven neoantigens of CA-125 in breast or ovarian cancer, constructed a self-adjuvant mRNA vaccine with CD40L and MHC-I -targeting domain to enhance cross-presentation of neoepitopes by dendritic cells. With an in silico ImmSim algorithm, we estimated the immune responses post-immunization, showing IFN-γ and CD8+ T cell response. The strategy described in this study may be scaled up and implemented to design precision multi-epitope mRNA vaccines by targeting multiple neoantigens.

Immunogenetic Profiles and Associations of Breast, Cervical, Ovarian, and Uterine Cancers

It is increasingly recognized that the human immune response influences cancer risk, progression, and survival; consequently, there is growing interest in the role of human leukocyte antigen (HLA), genes that play a critical role in initiating the immune response, on cancer. Recent evidence documented clustering of cancers based on immunogenetic profiles such that breast and ovarian cancers clustered together as did uterine and cervical cancers. Here we extend that line of research to evaluate the HLA profile of those 4 cancers and their associations. Specifically, we evaluated the associations between the frequencies of 127 HLA alleles and the population prevalences of breast, ovarian, cervical, and uterine cancer in 14 countries in Continental Western Europe. Factor analysis and hierarchical clustering were used to evaluate groupings of cancers based on their immunogenetic profiles. The results documented highly similar immunogenetic profiles for breast and ovarian cancers that were characterized predominantly by protective HLA effects. In addition, highly similar immunogenetic profiles for cervical and uterine cancers were observed that were, conversely, characterized by susceptibility effects. In light of the role of HLA in host immune system protection against non-self antigens, these findings suggest that certain cancers may be associated with similar contributory factors such as viral oncoproteins or neoantigens.

Immune cells are increased in normal breast tissues of BRCA1/2 mutation carriers

PURPOSE

Breast cancer risk is elevated in pathogenic germline BRCA 1/2 mutation carriers due to compromised DNA quality control. We hypothesized that if immunosurveillance promotes tumor suppression, then normal/benign breast lobules from BRCA carriers may demonstrate higher immune cell densities.

METHODS

We assessed immune cell composition in normal/benign breast lobules from age-matched women with progressively increased breast cancer risk, including (1) low risk: 19 women who donated normal breast tissue to the Komen Tissue Bank (KTB) at Indiana University Simon Cancer Center, (2) intermediate risk: 15 women with biopsy-identified benign breast disease (BBD), and (3) high risk: 19 prophylactic mastectomies from women with germline mutations in BRCA1/2 genes. We performed immunohistochemical stains and analysis to quantitate immune cell densities from digital images in up to 10 representative lobules per sample. Median cell counts per mm2 were compared between groups using Wilcoxon rank-sum tests.

RESULTS

Normal/benign breast lobules from BRCA carriers had significantly higher densities of immune cells/mm2 compared to KTB normal donors (all p < 0.001): CD8 + 354.4 vs 150.9; CD4 + 116.3 vs 17.7; CD68 + 237.5 vs 57.8; and CD11c + (3.5% vs 0.4% pixels positive). BBD tissues differed from BRCA carriers only in CD8 + cells but had higher densities of CD4 + , CD11c + , and CD68 + immune cells compared to KTB donors.

CONCLUSIONS

These preliminary analyses show that normal/benign breast lobules of BRCA mutation carriers contain increased immune cells compared with normal donor breast tissues, and BBD tissues appear overall more similar to BRCA carriers.

Characterization of genomic alterations and neoantigens and analysis of immune infiltration identified therapeutic and prognostic biomarkers in adenocarcinoma at the gastroesophageal junction

Objectives

Adenocarcinoma at the gastroesophageal junction (ACGEJ) refers to a malignant tumor that occurs at the esophagogastric junction. Despite some progress in targeted therapies for HER2, FGFR2, EGFR, MET, Claudin 18.2 and immune checkpoints in ACGEJ tumors, the 5-year survival rate of patients remains poor. Thus, it is urgent to explore genomic alterations and neoantigen characteristics of tumors and identify CD8+ T-cell infiltration-associated genes to find potential therapeutic targets and develop a risk model to predict ACGEJ patients’ overall survival (OS).

Methods

Whole-exome sequencing (WES) was performed on 55 paired samples from Chinese ACGEJ patients. Somatic mutations and copy number variations were detected by Strelka2 and FACETS, respectively. SigProfiler and SciClone were employed to decipher the mutation signature and clonal structure of each sample, respectively. Neoantigens were predicted using the MuPeXI pipeline. RNA sequencing (RNA-seq) data of ACGEJ samples from our previous studies and The Cancer Genome Atlas (TCGA) were used to identify genes significantly associated with CD8+ T-cell infiltration by weighted gene coexpression network analysis (WGCNA). To construct a risk model, we conducted LASSO and univariate and multivariate Cox regression analyses.

Results

Recurrent MAP2K7, RNF43 and RHOA mutations were found in ACGEJ tumors. The COSMIC signature SBS17 was associated with ACGEJ progression. CCNE1 and VEGFA were identified as putative CNV driver genes. PI3KCA and TP53 mutations conferred selective advantages to cancer cells. The Chinese ACGEJ patient neoantigen landscape was revealed for the first time, and 58 potential neoantigens common to TSNAdb and IEDB were identified. Compared with Siewert type II samples, Siewert type III samples had significant enrichment of the SBS17 signature, a lower TNFRSF14 copy number, a higher proportion of samples with complex clonal architecture and a higher neoantigen load. We identified 10 important CD8+ T-cell infiltration-related Hub genes (CCL5, CD2, CST7, GVINP1, GZMK, IL2RB, IKZF3, PLA2G2D, P2RY10 and ZAP70) as potential therapeutic targets from the RNA-seq data. Seven CD8+ T-cell infiltration-related genes (ADAM28, ASPH, CAMK2N1, F2R, STAP1, TP53INP2, ZC3H3) were selected to construct a prognostic model. Patients classified as high risk based on this model had significantly worse OS than low-risk patients, which was replicated in the TCGA-ACGEJ cohort.

Conclusions

This study provides new neoantigen-based immunotherapeutic targets for ACGEJ treatment and effective disease prognosis biomarkers.

Harnessing gene fusion-derived neoantigens for 'cold' breast and prostate tumor immunotherapy

Breast and prostate cancers are generally considered immunologically 'cold' tumors due to multiple mechanisms rendering them unresponsive to immune checkpoint blockade therapies. With little success in garnering positive outcomes in modern immunotherapeutic clinical trials, it is prudent to re-examine the role of immunogenic neoantigens in these cold tumors. Gene fusions are driver mutations in hormone-driven cancers that can result in alternative mutation-specific neoantigens to promote immunotherapy sensitivity. This review focuses on 1) gene fusion formation mechanisms in neoantigen generation; 2) gene fusion neoantigens in cancer immunotherapeutic strategies and associated clinical trials; and 3) challenges and opportunities in computational and liquid biopsy technologies. This review is anticipated to initiate further research into gene fusion neoantigens of cold tumors for further experimental validation.

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.

Prognostic Value of Neoantigen Load in Immune Checkpoint Inhibitor Therapy for Cancer

Immune checkpoint inhibitors (ICIs) have made great progress in the field of tumors and have become a promising direction of tumor treatment. With advancements in genomics and bioinformatics technology, it is possible to individually analyze the neoantigens produced by somatic mutations of each patient. Neoantigen load (NAL), a promising biomarker for predicting the efficacy of ICIs, has been extensively studied. This article reviews the research progress on NAL as a biomarker for predicting the anti-tumor effects of ICI. First, we provide a definition of NAL, and summarize the detection methods, and their relationship with tumor mutation burden. In addition, we describe the common genomic sources of NAL. Finally, we review the predictive value of NAL as a tumor prediction marker based on various clinical studies. This review focuses on the predictive ability of NAL’s ICI efficacy against tumors. In melanoma, lung cancer, and gynecological tumors, NAL can be considered a predictor of treatment efficacy. In contrast, the use of NAL for urinary system and liver tumors requires further research. When NAL alone is insufficient to predict efficacy, its combination with other indicators can improve prediction efficiency. Evaluating the response of predictive biomarkers before the treatment initiation is essential for guiding the clinical treatment of cancer. The predictive power of NAL has great potential; however, it needs to be based on more accurate sequencing platforms and technologies.

Neoantigens and their potential applications in tumor immunotherapy

The incidence of malignant tumors is increasing, the majority of which are associated with high morbidity and mortality rates worldwide. The traditional treatment method for malignant tumors is surgery, coupled with radiotherapy or chemotherapy. However, these therapeutic strategies are frequently accompanied with adverse side effects. Over recent decades, tumor immunotherapy shown promise in demonstrating notable efficacy for the treatment of cancer. With the development of sequencing technology and bioinformatics algorithms, neoantigens have become compelling targets for cancer immunotherapy due to high levels of immunogenicity. In addition, neoantigen-based vaccines have demonstrated potential for cancer therapy, primarily by augmenting T-cell responses. Neoantigens have also been shown to be effective in immune checkpoint blockade therapy. Therefore, neoantigens may serve to be predictive biomarkers and synergistic treatment targets in cancer immunotherapy. The aim of the present review was to provide an overview of the recent progress in the classification, screening and clinical application of neoantigens for cancer therapy.

Breast cancer vaccines for treatment and prevention

Breast cancer is immunogenic and a variety of vaccines have been designed to boost immunity directed against the disease. The components of a breast cancer vaccine, the antigen, the delivery system, and the adjuvant, can have a significant impact on vaccine immunogenicity. There have been numerous immunogenic proteins identified in all subtypes of breast cancer. The majority of these antigens are weakly immunogenic nonmutated tumor-associated proteins. Mutated proteins and neoantigen epitopes are found only in a small minority of patients and are enriched in the triple negative subtype. Several vaccines have advanced to large randomized Phase II or Phase III clinical trials. None of these trials met their primary endpoint of either progression-free or overall survival. Despite these set-backs investigators have learned important lessons regarding the clinical application of breast cancer vaccines from the type of immune response needed for tumor eradication, Type I T-cell immunity, to the patient populations most likely to benefit from vaccination. Many therapeutic breast cancer vaccines are now being tested in combination with other forms of immune therapy or chemotherapy and radiation. Breast cancer vaccines as single agents are now studied in the context of the prevention of relapse or development of disease. Newer approaches are designing vaccines to prevent breast cancer by intercepting high-risk lesions such as ductal carcinoma in situ to limit the progression of these tumors to invasive cancer. There are also several efforts to develop vaccines for the primary prevention of breast cancer by targeting antigens expressed during breast cancer initiation.

Impact of Neoantigen Expression and T-Cell Activation on Breast Cancer Survival

Simple Summary

Neoantigens are novel proteins presented on the cell surface and derived from the accumulation of somatic mutations in tumor cells. They can be recognized by the immune system and may play a crucial role in boosting immune responses against tumor cells. The impact of neoantigen expression and T-cell activation status on overall survival was investigated in a breast cancer cohort. We found that high neoantigen expression and T-cell activation status was correlated with improved patient survival in the study population. This result supports that neoantigens are promising to serve as immunogenic agents for immunotherapy in breast cancer.

Abstract

Neoantigens are derived from tumor-specific somatic mutations. Neoantigen-based synthesized peptides have been under clinical investigation to boost cancer immunotherapy efficacy. The promising results prompt us to further elucidate the effect of neoantigen expression on patient survival in breast cancer. We applied Kaplan–Meier survival and multivariable Cox regression models to evaluate the effect of neoantigen expression and its interaction with T-cell activation on overall survival in a cohort of 729 breast cancer patients. Pearson’s chi-squared tests were used to assess the relationships between neoantigen expression and clinical pathological variables. Spearman correlation analysis was conducted to identify correlations between neoantigen expression, mutation load, and DNA repair gene expression. ERCC1, XPA, and XPC were negatively associated with neoantigen expression, while BLM, BRCA2, MSH2, XRCC2, RAD51, CHEK1, and CHEK2 were positively associated with neoantigen expression. Based on the multivariable Cox proportional hazard model, patients with a high level of neoantigen expression and activated T-cell status showed improved overall survival. Similarly, in the T-cell exhaustion and progesterone receptor (PR) positive subgroups, patients with a high level of neoantigen expression showed prolonged survival. In contrast, there was no significant difference in the T-cell activation and PR negative subgroups. In conclusion, neoantigens may serve as immunogenic agents for immunotherapy in breast cancer.

The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

Analysis of multi-omics differences in left-side and right-side colon cancer

Background

Colon cancer is one of the most common tumors in the digestive tract. Studies of left-side colon cancer (LCC) and right-side colon cancer (RCC) show that these two subtypes have different prognoses, outcomes, and clinical responses to chemotherapy. Therefore, a better understanding of the importance of the clinical classifications of the anatomic subtypes of colon cancer is needed.

Methods

We collected colon cancer patients’ transcriptome data, clinical information, and somatic mutation data from the Cancer Genome Atlas (TCGA) database portal. The transcriptome data were taken from 390 colon cancer patients (172 LCC samples and 218 RCC samples); the somatic mutation data included 142 LCC samples and 187 RCC samples. We compared the expression and prognostic differences of LCC and RCC by conducting a multi-omics analysis of each using the clinical characteristics, immune microenvironment, transcriptomic differences, and mutation differences. The prognostic signatures was validated using the internal testing set, complete set, and external testing set (GSE39582). We also verified the independent prognostic value of the signature.

Results

The results of our clinical characteristic analysis showed that RCC had a significantly worse prognosis than LCC. The analysis of the immune microenvironment showed that immune infiltration was more common in RCC than LCC. The results of differential gene analysis showed that there were 360 differentially expressed genes, with 142 upregulated genes in LCC and 218 upregulated genes in RCC. The mutation frequency of RCC was generally higher than that of LCC. BRAF and KRAS gene mutations were the dominant genes mutations in RCC, and they had a strong mutual exclusion with APC, while APC gene mutation was the dominant gene mutation in LCC. This suggests that the molecular mechanisms of RCC and LCC differed. The 4-mRNA and 6-mRNA in the prognostic signatures of LCC and RCC, respectively, were highly predictive and may be used as independent prognostic factors.

Conclusion

The clinical classification of the anatomic subtypes of colon cancer is of great significance for early diagnosis and prognostic risk assessment. Our study provides directions for individualized treatment of left and right colon cancer.

Beyond Tumor Mutation Burden: Tumor Neoantigen Burden as a Biomarker for Immunotherapy and Other Types of Therapy

Immunotherapy has significantly improved the clinical outcome of patients with cancer. However, the immune response rate varies greatly, possibly due to lack of effective biomarkers that can be used to distinguish responders from non-responders. Recently, clinical studies have associated high tumor neoantigen burden (TNB) with improved outcomes in patients treated with immunotherapy. Therefore, TNB has emerged as a biomarker for immunotherapy and other types of therapy. In the present review, the potential application of TNB as a biomarker was evaluated. The methods of neoantigen prediction were summarized and the mechanisms involved in TNB were investigated. The impact of high TNB and increased number of infiltrating immune cells on the efficacy of immunotherapy was also addressed. Finally, the future challenges of TNB were discussed.

Neoantigen landscape in metastatic nasopharyngeal carcinoma

Background: Reportedly, nasopharyngeal carcinoma (NPC) patients with MHC I Class aberration are prone to poor survival outcomes, which indicates that the deficiency of tumor neoantigens might represent a mechanism of immune surveillance escape in NPC.

Methods: To clearly delineate the landscape of neoantigens in NPC, we performed DNA and RNA sequencing on paired primary tumor, regional lymph node metastasis and distant metastasis samples from 26 patients. Neoantigens were predicted using pVACseq pipeline. Subtype prediction model was built using random forest algorithm.

Results: Portraying the landscape of neoantigens in NPC for the first time, we found that the neoantigen load of NPC was above average compared to that of other cancers in The Cancer Genome Atlas program. While the quantity and quality of neoantigens were similar among primary tumor, regional lymph node metastasis and distant metastasis samples, neoantigen depletion was more severe in metastatic sites than in primary tumors. Upon tracking the clonality change of neoantigens, we found that neoantigen reduction occurred during metastasis. Building a subtype prediction model based on reported data, we observed that subtype I lacked T cells and suffered from severe neoantigen depletion, subtype II highly expressed immune checkpoint molecules and suffered from the least neoantigen depletion, and subtype III was heterogenous.

Conclusions: These results indicate that neoantigens are conducive to the guidance of clinical treatment, and personalized therapeutic vaccines for NPC deserve deeper basic and clinical investigations to make them feasible in the future.

Intron retention-induced neoantigen load correlates with unfavorable prognosis in multiple myeloma

Neoantigen peptides arising from genetic alterations may serve as targets for personalized cancer vaccines and as positive predictors of response to immune checkpoint therapy. Mutations in genes regulating RNA splicing are common in hematological malignancies leading to dysregulated splicing and intron retention (IR). In this study, we investigated IR as a potential source of tumor neoantigens in multiple myeloma (MM) patients and the relationship of IR-induced neoantigens (IR-neoAg) with clinical outcomes. MM-specific IR events were identified in RNA-sequencing data from the Multiple Myeloma Research Foundation CoMMpass study after removing IR events that also occurred in normal plasma cells. We quantified the IR-neoAg load by assessing IR-induced novel peptides that were predicted to bind to major histocompatibility complex (MHC) molecules. We found that high IR-neoAg load was associated with poor overall survival in both newly diagnosed and relapsed MM patients. Further analyses revealed that poor outcome in MM patients with high IR-neoAg load was associated with high expression levels of T-cell co-inhibitory molecules and elevated interferon signaling activity. We also found that MM cells exhibiting high IR levels had lower MHC-II protein abundance and treatment of MM cells with a spliceosome inhibitor resulted in increased MHC-I protein abundance. Our findings suggest that IR-neoAg may represent a novel biomarker of MM patient clinical outcome and further that targeting RNA splicing may serve as a potential therapeutic strategy to prevent MM immune escape and promote response to checkpoint blockade.

Detection of immunogenic cell death and its relevance for cancer therapy

Chemotherapy, radiation therapy, as well as targeted anticancer agents can induce clinically relevant tumor-targeting immune responses, which critically rely on the antigenicity of malignant cells and their capacity to generate adjuvant signals. In particular, immunogenic cell death (ICD) is accompanied by the exposure and release of numerous damage-associated molecular patterns (DAMPs), which altogether confer a robust adjuvanticity to dying cancer cells, as they favor the recruitment and activation of antigen-presenting cells. ICD-associated DAMPs include surface-exposed calreticulin (CALR) as well as secreted ATP, annexin A1 (ANXA1), type I interferon, and high-mobility group box 1 (HMGB1). Additional hallmarks of ICD encompass the phosphorylation of eukaryotic translation initiation factor 2 subunit-α (EIF2S1, better known as eIF2α), the activation of autophagy, and a global arrest in transcription and translation. Here, we outline methodological approaches for measuring ICD markers in vitro and ex vivo for the discovery of next-generation antineoplastic agents, the development of personalized anticancer regimens, and the identification of optimal therapeutic combinations for the clinical management of cancer.

MPA/DMBA-driven mammary carcinomas

The polycyclic aromatic hydrocarbon 7,12-dimethylbenz[a]anthracene (DMBA, D) administered per os to wild-type female mice bearing slow-release medroxyprogesterone (MPA, M) pellets s.c. drives the formation of mammary carcinomas that recapitulate numerous immunobiological features of human luminal B breast cancer. In particular, M/D-driven mammary carcinomas established in immunocompetent C57BL/6 female mice (1) express hormone receptors, (2) emerge by evading natural immunosurveillance and hence display a scarce immune infiltrate largely polarized toward immunosuppression, (3) exhibit exquisite sensitivity to CDK4/CDK6 inhibitors, and (4) are largely resistant to immunotherapy with immune checkpoint blockers targeting PD-1. Thus, M/D-driven mammary carcinomas evolving in immunocompetent female mice stand out as a privileged preclinical platform for the study of luminal B breast cancer. Here, we provide a detailed protocol for the establishment of M/D-driven mammary carcinomas in wild-type C57BL/6 female mice. This protocol can be easily adapted to generate M/D-driven mammary carcinomas in female mice with most genetic backgrounds (including genetically-engineered mice).

The Role of the Tumor Microenvironment in Developing Successful Therapeutic and Secondary Prophylactic Breast Cancer Vaccines

Breast cancer affects roughly one in eight women over their lifetime and is a leading cause of cancer-related death in women. While outcomes have improved in recent years, prognosis remains poor for patients who present with either disseminated disease or aggressive molecular subtypes. Cancer immunotherapy has revolutionized the treatment of several cancers, with therapeutic vaccines aiming to direct the cytotoxic immune program against tumor cells showing particular promise. However, these results have yet to translate to breast cancer, which remains largely refractory from such approaches. Recent evidence suggests that the breast tumor microenvironment (TME) is an important and long understudied barrier to the efficacy of therapeutic vaccines. Through an improved understanding of the complex and biologically diverse breast TME, it may be possible to advance new combination strategies to render breast carcinomas sensitive to the effects of therapeutic vaccines. Here, we discuss past and present efforts to advance therapeutic vaccines in the treatment of breast cancer, the molecular mechanisms through which the TME contributes to the failure of such approaches, as well as the potential means through which these can be overcome.

Immune Responses and Risk of Triple-negative Breast Cancer: Implications for Higher Rates among African American Women

The etiology of triple-negative breast cancers (TNBC) is poorly understood. As many TNBCs develop prior to the initiation of breast cancer screening or at younger ages when the sensitivity of mammography is comparatively low, understanding the etiology of TNBCs is critical for discovering novel prevention approaches for these tumors. Furthermore, the higher incidence rate of estrogen receptor-negative breast cancers, and specifically, of TNBCs, among young African American women (AAW) versus white women is a source of racial disparities in breast cancer mortality. Whereas immune responses to TNBCs have received considerable attention in relation to prognosis and treatment, the concept that dysregulated immune responses may predispose to the development of TNBCs has received limited attention. We present evidence that dysregulated immune responses are critical in the pathogenesis of TNBCs, based on the molecular biology of the cancers and the mechanisms proposed to mediate TNBC risk factors. Furthermore, proposed risk factors for TNBC, especially childbearing without breastfeeding, high parity, and obesity, are more prevalent among AAW than white women. Limited data suggest genetic differences in immune responses by race, which favor a stronger Thr type 2 (Th2) immune response among AAW than white women. Th2 responses contribute to wound-healing processes, which are implicated in the pathogenesis of TNBCs. Accordingly, we review data on the link between immune responses and TNBC risk and consider whether the prevalence of risk factors that result in dysregulated immunity is higher among AAW than white women.