Targeting the tumor mutanome for personalized vaccination in lung cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA745456 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15097633_1.fastq.gz | Fastqsanger.gz | |||
| SRR15097633_2.fastq.gz | Fastqsanger.gz | |||
| SRR15097634_1.fastq.gz | Fastqsanger.gz | |||
| SRR15097634_2.fastq.gz | Fastqsanger.gz | |||
| SRR15097635_1.fastq.gz | Fastqsanger.gz |
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Project description:Cancer is characterized by an accumulation of somatic mutations, of which a significant subset can generate cancer-specific neoepitopes that are recognized by autologous T cells. Neoepitopes are emerging as important targets for cancer immunotherapy, including personalized cancer vaccination strategies. We used whole-exome and RNA sequencing analysis to identify potential neoantigens for a patient with non-small cell lung cancer. Sequencing revealed a low tumor mutational burden: 2,219 sequence variants were identified from the primary tumor, of which 23 were expressed in the transcriptome, involving 18 gene products. We assessed autologous T-cell reactivity to the candidate neoantigens using a long peptide approach and could demonstrate spontaneous T-cell responses to 5/18 (28%) mutated gene variants. Further, analysis of the TCR repertoire of neoantigen-specific CD4+ and CD8+ T cells revealed TCR clonotypes that were expanded in both blood and tumor tissue. In parallel, the 18 gene variants were incorporated into a Modified Vaccinia Ankara-based vaccine, which was evaluated in the transgenic HLA-A*02-restricted HHD mouse model. Following vaccination, de novo T-cell responses were generated to 4/18 (22%) mutated gene variants, of which 2 were also observed in the autologous setting; we determined the MHC restriction of the T-cell responses and used in silico prediction tools to determine the likely neoepitopes. Our study demonstrates the feasibility of efficiently identifying tumor-specific neoantigens that can be targeted by vaccination in tumors with a low mutational burden, and promises successful clinical application, with trials currently underway.
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Project description:Oropharyngeal squamous cell carcinoma (OPSCC) is diagnosed in 93,000 patients worldwide per year and 51,000 annual deaths can be attributed to this disease. OPSCCs are either human papillomavirus associated (HPV-positive) cancers or non-virally induced, primarily tobacco and alcohol associated (HPV-negative) cancers. MS analysis enabled the identification of naturally HLA-presented peptides in OPSCC tumor tissue. By comparative profiling against benign HLA ligandomic datasets, we demonstrated that tumor-associated peptides are HLA-presented on the cell surfaces of OPSCCs. The established warehouse of OPSCC-associated peptides can be used for downstream immunogenicity testing and peptide-based immunotherapy in (semi-) personalized strategies.
2023-02-27 | PXD033383 | Pride
Project description:The lung cancer tumor K-rasLA1/ p53 R172HDeltag mouse model was used to identify genes associated to the tumor mass increase in lungs. Those genes were then ranked on the basis of their oncogenic potential using a metadataset encompassing 695 human lung adenocarcinomas and ranking them on the basis of their expression in normal tissues. The genes characterized by the higher oncogenic potential combined to a low expression in normal tissues were selected as putative targets for preclinical studies on lung cancer vaccination.
2013-12-30 | GSE30878 | GEO
Project description:The lung cancer tumor K-rasLA1/ p53 R172HDeltag mouse model was used to identify genes associated to the tumor mass increase in lungs. Those genes were then ranked on the basis of their oncogenic potential using a metadataset encompassing 695 human lung adenocarcinomas and ranking them on the basis of their expression in normal tissues. The genes characterized by the higher oncogenic potential combined to a low expression in normal tissues were selected as putative targets for preclinical studies on lung cancer vaccination. Two prototypic situations (WT, and MUT) were examined using Exon arrays over a three-points time course (10, 20, and 30 weeks old animals), for each time point two/three male and female animals were used. A total of 30 mouse Exon 1.0 arrays were hybridized.
2013-12-30 | E-GEOD-30878 | biostudies-arrayexpress
Project description:We performed single cell RNA-seq gene expression analysis on bone marrow of 9 lymphoplasmacytic lymphoma patients before and after vaccination with personalized idiotype DNA vaccine to study changes in tumor microenvironment
2023-09-20 | GSE243545 | GEO
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Project description:Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models
Natalie Kronik1¤, Yuri Kogan1, Moran Elishmereni1, Karin Halevi-Tobias1, Stanimir Vuk-Pavlovic ́2.,Zvia Agur1*.1Institute for Medical BioMathematics, Bene Ataroth, Israel,2College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
Abstract
Background:Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients.We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simplemathematical models.Methodology/Principal Findings:We developed a general mathematical model encompassing the basic interactions of avaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cellvaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes inprostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were dividedinto each patient’s training set and his validation set. The training set, used for model personalization, contained thepatient’s initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized modelswere simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set.The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients(the coefficient of determination between the predicted and observed PSA values wasR2= 0.972). The model could notaccount for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validatedpersonalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccinationregimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Conclusions/Significance:Using a few initial measurements, we constructed robust patient-specific models of PCaimmunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value andfeasibility of individualized model-suggested immunotherapy protocols.
2020-01-13 | MODEL2001130003 | BioModels
Project description:<p>Neoantigens, which are derived from tumour-specific protein-coding mutations, are exempt from central tolerance, can generate robust immune responses and can function as bona fide antigens that facilitate tumour rejection. We demonstrated that a strategy that uses multi-epitope, personalized neoantigen vaccination, which has previously been tested in patients with high-risk melanoma, is feasible for tumours such as glioblastoma, which typically have a relatively low mutation load and an immunologically ‘cold’ tumour microenvironment. Here we conducted whole-exome sequencing of tumor and normal cells from individual patients with glioblastoma to identify tumor-specific mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor. We used personalized neoantigen-targeting vaccines to immunize patients newly diagnosed with glioblastoma following surgical resection and conventional radiotherapy in a phase I/Ib study. Patients who did not receive dexamethasone-a highly potent corticosteroid that is frequently prescribed to treat cerebral oedema in patients with glioblastoma-generated circulating polyfunctional neoantigen-specific CD4+ and CD8+ T cell responses that were enriched in a memory phenotype and showed an increase in the number of tumour-infiltrating T cells. Using single-cell T cell receptor analysis, we provide evidence that neoantigen-specific T cells from the peripheral blood can migrate into an intracranial glioblastoma tumour. Neoantigen-targeting vaccines thus have the potential to favourably alter the immune milieu of glioblastoma.</p>
| phs001519 | dbGaP
Project description:BackgroundCancer is characterized by an accumulation of somatic mutations, of which a significant subset can generate cancer-specific neoepitopes that are recognized by autologous T cells. Such neoepitopes are emerging as important targets for cancer immunotherapy, including personalized cancer vaccination strategies.MethodsWe used whole-exome and RNA sequencing analysis to identify potential neoantigens for a patient with non-small cell lung cancer. Thereafter, we assessed the autologous T-cell reactivity to the candidate neoantigens using a long peptide approach in a cultured interferon gamma ELISpot and tracked the neoantigen-specific T-cells in the tumor by T-cell receptor (TCR) sequencing. In parallel, identified gene variants were incorporated into a Modified Vaccinia Ankara-based vaccine, which was evaluated in the human leucocyte antigen A*0201 transgenic mouse model (HHD).ResultsSequencing revealed a tumor with a low mutational burden: 2219 sequence variants were identified from the primary tumor, of which 23 were expressed in the transcriptome, involving 18 gene products. We could demonstrate spontaneous T-cell responses to 5/18 (28%) mutated gene variants, and further analysis of the TCR repertoire of neoantigen-specific CD4+ and CD8+ T cells revealed TCR clonotypes that were expanded in both blood and tumor tissue. Following vaccination of HHD mice, de novo T-cell responses were generated to 4/18 (22%) mutated gene variants; T cells reactive against two variants were also evident in the autologous setting. Subsequently, we determined the major histocompatibility complex restriction of the T-cell responses and used in silico prediction tools to determine the likely neoepitopes.ConclusionsOur study demonstrates the feasibility of efficiently identifying tumor-specific neoantigens that can be targeted by vaccination in tumors with a low mutational burden, promising successful clinical exploitation, with trials currently underway.
| S-EPMC8971766 | biostudies-literature
Project description:Personalized cancer vaccines aim to activate and expand cytotoxic anti-tumor CD8+ T cells to recognize and kill tumor cells. However, the role of CD4+ T cell activation in the clinical benefit of these vaccines is not well defined. We previously established a personalized neoantigen vaccine (PancVAX) for the pancreatic cancer cell line Panc02, which activates tumor-specific CD8+ T cells but required combinatorial checkpoint modulators to achieve therapeutic efficacy. To determine the effects of neoantigen-specific CD4+ T cell activation, we generated a new vaccine (PancVAX2) targeting both MHCI- and MHCII-specific neoantigens. Tumor-bearing mice vaccinated with PancVAX2 had significantly improved control of tumor growth and long-term survival benefit without concurrent administration of checkpoint inhibitors. PancVAX2 significantly enhanced priming and recruitment of neoantigen-specific CD8+ T into the tumor with lower PD1 expression after reactivation compared to the CD8+ vaccine alone. Vaccine-induced neoantigen- specific Th1 CD4+ T cells in the tumor were associated with decreased T regulatory cells (Tregs). Consistent with this, PancVAX2 was associated with more pro-immune myeloid-derived suppressor cells and M1-like macrophages in the tumor demonstrating a less immunosuppressive tumor microenvironment. This study demonstrates the biological importance of prioritizing and including CD4 T cell-specific neoantigens for personalized cancer vaccine modalities.
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