Valid-NEO: A Multi-Omics Platform for Neoantigen Detection and Quantification from Limited Clinical Samples

Preclinical studies show that Co-STARs combine the advantages of chimeric antigen and T cell receptors for the treatment of tumors with low antigen densities

Two types of engineered T cells have been successfully used to treat patients with cancer, one with an antigen recognition domain derived from antibodies [chimeric antigen receptors (CARs)] and the other derived from T cell receptors (TCRs). CARs use high-affinity antigen-binding domains and costimulatory domains to induce T cell activation but can only react against target cells with relatively high amounts of antigen. TCRs have a much lower affinity for their antigens but can react against target cells displaying only a few antigen molecules. Here, we describe a new type of receptor, called a Co-STAR (for costimulatory synthetic TCR and antigen receptor), that combines aspects of both CARs and TCRs. In Co-STARs, the antigen-recognizing components of TCRs are replaced by high-affinity antibody fragments, and costimulation is provided by two modules that drive NF-κB signaling (MyD88 and CD40). Using a TCR-mimic antibody fragment that targets a recurrent p53 neoantigen presented in a common human leukocyte antigen (HLA) allele, we demonstrate that T cells equipped with Co-STARs can kill cancer cells bearing low densities of antigen better than T cells engineered with conventional CARs and patient-derived TCRs in vitro. In mouse models, we show that Co-STARs mediate more robust T cell expansion and more durable tumor regressions than TCRs similarly modified with MyD88 and CD40 costimulation. Our data suggest that Co-STARs may have utility for other peptide-HLA antigens in cancer and other targets where antigen density may limit the efficacy of engineered T cells.

A new high-throughput screening methodology for the discovery of cancer-testis antigen using multi-omics data

BACKGROUND

Cancer/testis antigens (CTAs), also known as tumor-specific antigens (TSAs) are specifically expressed in cancer cells and exhibit high immunogenicity, making them promising targets for immunotherapy and cancer vaccines.

METHODS

A new integrated high-throughput screening methodology for CTAs was proposed in this study through combining DNA methylation and RNA sequencing data. Briefly, the genes with increased transcript level and decreased DNA methylation were identified by multi-omics analysis. RNA sequencing studies in cell lines exposed to DNA methyltransferase (DNMT) inhibitors were performed to validate the inherent causal relationship between DNA hypomethylation and gene expression upregulation.

RESULTS

We proposed a new integrated high-throughput screening methodology for identification of CTAs using multi-omics analysis. In addition, we tested the feasibility of this method using gastric cancer (GC) as an example. In GC, we identified over 2000 primary candidate CTAs and ultimately identified 20 CTAs with significant tissue-specificity, including a testis-specific serine protease TESSP1/PRSS41. Integrated analysis confirmed that PRSS41 expression was reactivated in gastrointestinal cancers by promoter DNA hypomethylation at the CpG site (cg08104780). Additionally, DNA hypomethylation of PRSS41 predicted a poor prognosis in GC.

CONCLUSION

We propose a new high-throughput screening method for the identification of CTAs in cancer and validate its effectiveness. Our work emphasizes that serine protease PRSS41 is a novel TSA that is reactivated in GC due to promoter DNA hypomethylation.

Shared graft-versus-leukemia minor histocompatibility antigens in DISCOVeRY-BMT

T-cell responses to minor histocompatibility antigens (mHAs) mediate graft-versus-leukemia (GVL) effects and graft-versus-host disease (GVHD) in allogeneic hematopoietic cell transplantation. Therapies that boost T-cell responses improve allogeneic hematopoietic cell transplant (alloHCT) efficacy but are limited by concurrent increases in the incidence and severity of GVHD. mHAs with expression restricted to hematopoietic tissue (GVL mHAs) are attractive targets for driving GVL without causing GVHD. Prior work to identify mHAs has focused on a small set of mHAs or population-level single-nucleotide polymorphism-association studies. We report the discovery of a large set of novel GVL mHAs based on predicted immunogenicity, tissue expression, and degree of sharing among donor-recipient pairs (DRPs) in the DISCOVeRY-BMT data set of 3231 alloHCT DRPs. The total number of predicted mHAs varied by HLA allele, and the total number and number of each class of mHA significantly differed by recipient genomic ancestry group. From the pool of predicted mHAs, we identified the smallest sets of GVL mHAs needed to cover 100% of DRPs with a given HLA allele. We used mass spectrometry to search for high-population frequency mHAs for 3 common HLA alleles. We validated 24 predicted novel GVL mHAs that are found cumulatively within 98.8%, 60.7%, and 78.9% of DRPs within DISCOVeRY-BMT that express HLA-A∗02:01, HLA-B∗35:01, and HLA-C∗07:02, respectively. We confirmed the immunogenicity of an example novel mHA via T-cell coculture with peptide-pulsed dendritic cells. This work demonstrates that the identification of shared mHAs is a feasible and promising technique for expanding mHA-targeting immunotherapeutics.

de la Fuente I. A Universal Antigen-Ranking Method to Design Personalized Vaccines Targeting Neoantigens against Melanoma

Background: The main purpose of this article is to introduce a universal mathematics-aided vaccine design method against malignant melanoma based on neoantigens. The universal method can be adapted to the mutanome of each patient so that a specific candidate vaccine can be tailored for the corresponding patient. Methods: We extracted the 1134 most frequent mutations in melanoma, and we associated each of them to a vector with 10 components estimated with different bioinformatics tools, for which we found an aggregated value according to a set of weights, and then we ordered them in decreasing order of the scores. Results: We prepared a universal table of the most frequent mutations in melanoma ordered in decreasing order of viability to be used as candidate vaccines, so that the selection of a set of appropriate peptides for each particular patient can be easily and quickly implemented according to their specific mutanome and transcription profile. Conclusions: We have shown that the techniques that are commonly used for the design of personalized anti-tumor vaccines against malignant melanoma can be adapted for the design of universal rankings of neoantigens that originate personalized vaccines when the mutanome and transcription profile of specific patients is considered, with the consequent savings in time and money, shortening the design and production time.