Neoantigen prediction in human breast cancer using RNA sequencing data

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.

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.

Neoantigens and cancer-testis antigens as promising vaccine candidates for triple-negative breast cancer: Delivery strategies and clinical trials

Immunotherapy is gaining prominence as a promising strategy for treating triple-negative breast cancer (TNBC). Neoantigens (neoAgs) and cancer-testis antigens (CTAs) are tumor-specific targets originating from somatic mutations and epigenetic changes in cancer cells. These antigens hold great promise for personalized cancer vaccines, as supported by preclinical and early clinical evidence in TNBC. This review delves into the potential of neoAgs and CTAs as vaccine candidates, emphasizing diverse strategies and delivery approaches. It also highlights the current status of vaccination modalities undergoing clinical trials in TNBC therapy. A comprehensive understanding of neoAgs, CTAs, vaccination strategies, and innovative delivery methods is crucial for optimizing neoAg-based immunotherapies in clinical practice.

Advances in Therapeutic Cancer Vaccines, Their Obstacles, and Prospects Toward Tumor Immunotherapy

Over the past few decades, cancer immunotherapy has experienced a significant revolution due to the advancements in immune checkpoint inhibitors (ICIs) and adoptive cell therapies (ACTs), along with their regulatory approvals. In recent times, there has been hope in the effectiveness of cancer vaccines for therapy as they have been able to stimulate de novo T-cell reactions against tumor antigens. These tumor antigens include both tumor-associated antigen (TAA) and tumor-specific antigen (TSA). Nevertheless, the constant quest to fully achieve these abilities persists. Therefore, this review offers a broad perspective on the existing status of cancer immunizations. Cancer vaccine design has been revolutionized due to the advancements made in antigen selection, the development of antigen delivery systems, and a deeper understanding of the strategic intricacies involved in effective antigen presentation. In addition, this review addresses the present condition of clinical tests and deliberates on their approaches, with a particular emphasis on the immunogenicity specific to tumors and the evaluation of effectiveness against tumors. Nevertheless, the ongoing clinical endeavors to create cancer vaccines have failed to produce remarkable clinical results as a result of substantial obstacles, such as the suppression of the tumor immune microenvironment, the identification of suitable candidates, the assessment of immune responses, and the acceleration of vaccine production. Hence, there are possibilities for the industry to overcome challenges and enhance patient results in the coming years. This can be achieved by recognizing the intricate nature of clinical issues and continuously working toward surpassing existing limitations.

Tumor neoantigens and tumor immunotherapies

As a high-risk group of patients with cancer, the elderly exhibit limited efficacy with traditional treatments. Immunotherapy emerges as a promising adjunctive therapeutic approach that holds potential in addressing the needs of geriatric patients with cancer. Neoantigens, a unique class of tumor-specific antigens generated by non-synonymous mutations, are garnering increasing attention as targets for immunotherapy in clinical applications. Newly developed technologies, such as second-generation gene sequencing and mass spectrometry, have provided powerful technical support for the identification and prediction of neoantigens. At present, neoantigen-based immunotherapy has been extensively applied in clinical trials and has demonstrated both safety and efficacy, marking the beginning of a new era for cancer immunotherapy. This article reviews the conception, classification, inducers, and screening process of tumor neoantigens, as well as the application prospects and combination therapy strategies of neoantigen-based cancer immunotherapy.

Full-length isoform concatenation sequencing to resolve cancer transcriptome complexity

BACKGROUND

Cancers exhibit complex transcriptomes with aberrant splicing that induces isoform-level differential expression compared to non-diseased tissues. Transcriptomic profiling using short-read sequencing has utility in providing a cost-effective approach for evaluating isoform expression, although short-read assembly displays limitations in the accurate inference of full-length transcripts. Long-read RNA sequencing (Iso-Seq), using the Pacific Biosciences (PacBio) platform, can overcome such limitations by providing full-length isoform sequence resolution which requires no read assembly and represents native expressed transcripts. A constraint of the Iso-Seq protocol is due to fewer reads output per instrument run, which, as an example, can consequently affect the detection of lowly expressed transcripts. To address these deficiencies, we developed a concatenation workflow, PacBio Full-Length Isoform Concatemer Sequencing (PB_FLIC-Seq), designed to increase the number of unique, sequenced PacBio long-reads thereby improving overall detection of unique isoforms. In addition, we anticipate that the increase in read depth will help improve the detection of moderate to low-level expressed isoforms.

RESULTS

In sequencing a commercial reference (Spike-In RNA Variants; SIRV) with known isoform complexity we demonstrated a 3.4-fold increase in read output per run and improved SIRV recall when using the PB_FLIC-Seq method compared to the same samples processed with the Iso-Seq protocol. We applied this protocol to a translational cancer case, also demonstrating the utility of the PB_FLIC-Seq method for identifying differential full-length isoform expression in a pediatric diffuse midline glioma compared to its adjacent non-malignant tissue. Our data analysis revealed increased expression of extracellular matrix (ECM) genes within the tumor sample, including an isoform of the Secreted Protein Acidic and Cysteine Rich (SPARC) gene that was expressed 11,676-fold higher than in the adjacent non-malignant tissue. Finally, by using the PB_FLIC-Seq method, we detected several cancer-specific novel isoforms.

CONCLUSION

This work describes a concatenation-based methodology for increasing the number of sequenced full-length isoform reads on the PacBio platform, yielding improved discovery of expressed isoforms. We applied this workflow to profile the transcriptome of a pediatric diffuse midline glioma and adjacent non-malignant tissue. Our findings of cancer-specific novel isoform expression further highlight the importance of long-read sequencing for characterization of complex tumor transcriptomes.

MALAT1 promotes FOXA1 degradation by competitively binding to miR-216a-5p and enhancing neuroendocrine differentiation in prostate cancer

OBJECTIVES

Prostate cancer (PC) is a leading cause of cancer-related death in males worldwide. Neuroendocrine differentiation (NED) is a feature of PC that often goes undetected and is associated with poor patient outcomes. Long non-coding RNAs (lncRNAs), microRNAs (miRNAs/miRs), and messenger RNAs (mRNAs) play important roles in the development and progression of PC.

METHODS

In this study, we used transcriptome sequencing and bioinformatics analysis to identify key regulators of NED in PC. Specifically, we examined the expression of PC-related lncRNAs, miRNAs, and mRNAs in PC cells and correlated these findings with NED phenotypes.

RESULTS

Our data revealed that metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and zinc finger protein 91 (ZFP91) were upregulated in PC, while miR-216a-5p was down-regulated. Ectopic expression of MALAT1 induced NED and promoted malignant phenotypes of PC cells. Furthermore, we found that MALAT1 competitively bound to miR-216a-5p, upregulated ZFP91, and promoted the degradation of forkhead box A1 (FOXA1), a key gene involved in NED of PC.

CONCLUSION

Taken together, these results suggest that MALAT1 plays an oncogenic role in NED and metastasis of PC via the miR-216a-5p/ZFP91/FOXA1 pathway. Our study highlights the potential of targeting this pathway as a novel therapeutic strategy for PC.

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling

Introduction

Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.

Methods

In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).

Results

We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.

Discussion

This integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

The current advances of lncRNAs in breast cancer immunobiology research

Breast cancer is the most frequently diagnosed malignancy and the leading cause of cancer-related death in women worldwide. Breast cancer development and progression are mainly associated with tumor-intrinsic alterations in diverse genes and signaling pathways and with tumor-extrinsic dysregulations linked to the tumor immune microenvironment. Significantly, abnormal expression of lncRNAs affects the tumor immune microenvironment characteristics and modulates the behavior of different cancer types, including breast cancer. In this review, we provide the current advances about the role of lncRNAs as tumor-intrinsic and tumor-extrinsic modulators of the antitumoral immune response and the immune microenvironment in breast cancer, as well as lncRNAs which are potential biomarkers of tumor immune microenvironment and clinicopathological characteristics in patients, suggesting that lncRNAs are potential targets for immunotherapy in breast cancer.

Update Breast Cancer 2022 Part 5 - Early Stage Breast Cancer

The treatment of patients with early stage breast cancer has changed in recent years due to the introduction of pembrolizumab, olaparib, and abemaciclib. These and other drugs with the same class of active ingredient are currently in trial for various indications. This review article summarizes the latest results that have either been presented at major conferences such as the ESMO 2022 or published recently in international journals. This includes reports on newly discovered breast cancer genes, atezolizumab in neoadjuvant therapy in HER2-positive patients, long-term data from the APHINITY study, and on how preoperative peritumoral application of local anesthetics can influence the prognosis. We also present solid data on dynamic Ki-67 from the ADAPT studies.

Engineering neoantigen vaccines to improve cancer personalized immunotherapy

Immunotherapy treatments harnessing the immune system herald a new era of personalized medicine, offering considerable benefits for cancer patients. Over the past years, tumor neoantigens emerged as a rising star in immunotherapy. Neoantigens are tumor-specific antigens arising from somatic mutations, which are proceeded and presented by the major histocompatibility complex on the cell surface. With the advancement of sequencing technology and bioinformatics engineering, the recognition of neoantigens has accelerated and is expected to be incorporated into the clinical routine. Currently, tumor vaccines against neoantigens mainly encompass peptides, DNA, RNA, and dendritic cells, which are extremely specific to individual patients. Due to the high immunogenicity of neoantigens, tumor vaccines could activate and expand antigen-specific CD4+ and CD8+ T cells to intensify anti-tumor immunity. Herein, we introduce the origin and prediction of neoantigens and compare the advantages and disadvantages of multiple types of neoantigen vaccines. Besides, we review the immunizations and the current clinical research status in neoantigen vaccines, and outline strategies for enhancing the efficacy of neoantigen vaccines. Finally, we present the challenges facing the application of neoantigens.

Update Breast Cancer 2022 Part 1 - Early Stage Breast Cancer

Evidence relating to the treatment of breast cancer patients with early-stage disease has increased significantly in the past year. Abemaciclib, olaparib, and pembrolizumab are new drugs with good efficacy in the relevant patient groups. However, some questions remain unanswered. In particular, it remains unclear which premenopausal patients with hormone receptor-positive breast cancer should be spared unnecessary treatment. The question of the degree to which chemotherapy exerts a direct cytotoxic effect on the tumor or reduces ovarian function through chemotherapy could be of key importance. This group of patients could potentially be spared chemotherapy. New, previously experimental biomarker analysis methods, such as spatial analysis of gene expression (spatial transcriptomics) are gradually finding their way into large randomized phase III trials, such as the NeoTRIP trial. This in turn leads to a better understanding of the predictive factors of new therapies, for example immunotherapy. This review summarizes the scientific innovations from recent congresses such as the San Antonio Breast Cancer Symposium 2021 but also from recent publications.

Development of antigen-prediction algorithm for personalized neoantigen vaccine using human leukocyte antigen transgenic mouse

Immunotherapy is currently recognized as the fourth modality in cancer therapy. CTLs can detect cancer cells via complexes involving human leukocyte antigen (HLA) class I molecules and peptides derived from tumor antigens, resulting in antigen-specific cancer rejection. The peptides may be predicted in silico using machine learning-based algorithms. Neopeptides, derived from neoantigens encoded by somatic mutations in cancer cells, are putative immunotherapy targets, as they have high tumor specificity and immunogenicity. Here, we used our pipeline to select 278 neoepitopes with high predictive "SCORE" from the tumor tissues of 46 patients with hepatocellular carcinoma or metastasis of colorectal carcinoma. We validated peptide immunogenicity and specificity by in vivo vaccination with HLA-A2, A24, B35, and B07 transgenic mice using ELISpot assay, in vitro and in vivo killing assays. We statistically evaluated the power of our prediction algorithm and demonstrated the capacity of our pipeline to predict neopeptides (area under the curve = 0.687, p < 0.0001). We also analyzed the potential of long peptides containing the predicted neoepitopes to induce CTLs. Our study indicated that the short peptides predicted using our algorithm may be intrinsically present in tumor cells as cleavage products of long peptides. Thus, we empirically demonstrated that the accuracy and specificity of our prediction tools may be potentially improved in vivo using the HLA transgenic mouse model. Our data will help to feedback algorithms to improve in silico prediction, potentially allowing researchers to predict peptides for personalized immunotherapy.

Towards customized cancer vaccines: a promising filed in personalized cancer medicine

INTRODUCTION

Cancer remains a major source of disease burden worldwide. Although cancer vaccines have been developed, most currently available cancer vaccines have limited therapeutic efficacy. Recent research using novel sequencing and bioinformatic tools has led scientists to realize that each tumor harbors a unique set of genetic mutations that can manifest as tumor-specific neoantigens. Therefore, it would be useful to develop personalized cancer vaccines that target neoantigens, which might improve the efficacy of these cancer treatments.

AREAS COVERED

This review covers cancer vaccine development and the emerging field of personalized cancer vaccines, with a discussion of future clinical trials for this promising treatment strategy.

EXPERT OPINION

Developing vaccines to treat tumors is one of the most promising and exciting fields in cancer research. However, cancer vaccines have shown limited efficacy in clinical trials for several decades, which may be related to the unique and complex processes underlying tumor development and progression. Recent studies have indicated that tumors express highly specific neoantigens, which are distinct from self-antigens. Thus, developing cancer vaccines that target these tumor-specific neoantigens is a promising strategy for developing personalized cancer vaccines.

A Local and Low-Dose Chemotherapy/Autophagy-Enhancing Regimen Treatment Markedly Inhibited the Growth of Established Solid Tumors Through a Systemic Antitumor Immune Response

Chemotherapy is one of the main options for the treatment of a variety of malignant tumors. However, the severe side effects resulting from the killing of normal proliferating cells limit the application of cancer-targeting chemotherapeutic drugs. To improve the efficacy of classic systemic chemotherapy, the local delivery of high-dose chemotherapeutic drugs was developed as a method to enhance local drug concentrations and minimize systemic toxicity. Studies have demonstrated that chemotherapy is often accompanied by cancer-associated immunogenic cell death (ICD) and that autophagy is involved in the induction of ICD. To improve the efficacy of local cancer chemotherapy, we hypothesized that the local delivery of chemotherapeutic plus autophagy-enhancing agents would enhance the promotive effects of ICD on the antitumor immune response. Here, we report that a low-dose chemotherapy/autophagy enhancing regimen (CAER) not only resulted in the increased death of B16F10 and 4T1 tumor cells, but also induced higher levels of autophagy in vitro. Importantly, the local delivery of the CARE drugs significantly inhibited tumor growth in B16F10 and 4T1 tumor-bearing mice. Systemic antitumor T-cell immunity was observed in vivo, including neoantigen-specific T-cell responses. Furthermore, bioinformatic analysis of human breast cancer and melanoma tissues showed that autophagy-associated gene expression was upregulated in tumor samples. Increased autophagy and immune cell infiltration in tumor tissues were positively correlated with good prognosis of tumor patients. This work highlights a new approach to improve the effects of local chemotherapy and enhance systemic antitumor immunity.