Javascript must be enabled to continue!
Abstract 176: Detecting neoepitopes from tumor RNA sequencing datasets
View through CrossRef
Abstract
Epitopes are peptides that present on the surface of the cell and can be recognized by immune cells to initiate the immune response. Identification of neoepitopes – tumor-specific, MHC-bound epitopes recognized specifically by T-cells – is valuable for predicting response to immunotherapies, including checkpoint blockade therapies. Tumors with more neoepitopes tend to be more responsive to immune checkpoint therapies compared to tumors with fewer neoepitopes. ProTECT is a previously published computational method that uses Illumina whole genome and transcriptome sequencing data from tumor and matched normal tissues to identify neoepitopes. Tumor and normal whole genome sequencing data are used to infer a patient's HLA haplotypes, as well as annotate variants as either somatic or germline. While whole genome sequencing is comprehensive, it is quite costly and not available for many samples. Here we adapt ProTECT to use only tumor RNA sequencing data and HLA haplotype information available to the clinician to identify neoepitopes in a tumor sample. Prior to running ProTECT, we use the computational tools Opossum and Platypus for variant calling instead of Radia (which is designed for variant calling using both RNA and DNA sequencing data as input). To determine which variants are somatic and therefore could represent tumor neoepitopes, variants found in RNA are compared to a panel of normals, for example the Genome Aggregation Database (gnomAD; containing variants from 125,748 exome sequences and 15,708 whole-genome sequences). With the resulting somatic variants and the HLA type, ProTECT proceeds as usual, with translation of variants into proteins, MHC:Peptide binding predictions and neoepitope ranking. We find that high quality neoepitopes are identifiable using an RNA-only approach, when genomic data is absent. Future work will validate the sensitivity of our method by benchmarking it against the original ProTECT predictions in the TCGA Prostate Adenocarcinoma cohort.
Citation Format: Drew Thompson, Olena M. Vaske, Arjun Rao, Holly C. Beale. Detecting neoepitopes from tumor RNA sequencing datasets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 176.
American Association for Cancer Research (AACR)
Title: Abstract 176: Detecting neoepitopes from tumor RNA sequencing datasets
Description:
Abstract
Epitopes are peptides that present on the surface of the cell and can be recognized by immune cells to initiate the immune response.
Identification of neoepitopes – tumor-specific, MHC-bound epitopes recognized specifically by T-cells – is valuable for predicting response to immunotherapies, including checkpoint blockade therapies.
Tumors with more neoepitopes tend to be more responsive to immune checkpoint therapies compared to tumors with fewer neoepitopes.
ProTECT is a previously published computational method that uses Illumina whole genome and transcriptome sequencing data from tumor and matched normal tissues to identify neoepitopes.
Tumor and normal whole genome sequencing data are used to infer a patient's HLA haplotypes, as well as annotate variants as either somatic or germline.
While whole genome sequencing is comprehensive, it is quite costly and not available for many samples.
Here we adapt ProTECT to use only tumor RNA sequencing data and HLA haplotype information available to the clinician to identify neoepitopes in a tumor sample.
Prior to running ProTECT, we use the computational tools Opossum and Platypus for variant calling instead of Radia (which is designed for variant calling using both RNA and DNA sequencing data as input).
To determine which variants are somatic and therefore could represent tumor neoepitopes, variants found in RNA are compared to a panel of normals, for example the Genome Aggregation Database (gnomAD; containing variants from 125,748 exome sequences and 15,708 whole-genome sequences).
With the resulting somatic variants and the HLA type, ProTECT proceeds as usual, with translation of variants into proteins, MHC:Peptide binding predictions and neoepitope ranking.
We find that high quality neoepitopes are identifiable using an RNA-only approach, when genomic data is absent.
Future work will validate the sensitivity of our method by benchmarking it against the original ProTECT predictions in the TCGA Prostate Adenocarcinoma cohort.
Citation Format: Drew Thompson, Olena M.
Vaske, Arjun Rao, Holly C.
Beale.
Detecting neoepitopes from tumor RNA sequencing datasets [abstract].
In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21.
Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 176.
Related Results
Complex Collision Tumors: A Systematic Review
Complex Collision Tumors: A Systematic Review
Abstract
Introduction: A collision tumor consists of two distinct neoplastic components located within the same organ, separated by stromal tissue, without histological intermixing...
Detecting RNA–RNA interactome
Detecting RNA–RNA interactome
AbstractThe last decade has seen a robust increase in various types of novel RNA molecules and their complexity in gene regulation. RNA molecules play a critical role in cellular e...
Abstract B054: Identification and functional characterization of CD8 T cells recognizing neoepitopes with low affinity (11,987 nM IC50) for MHCI (Kd)
Abstract B054: Identification and functional characterization of CD8 T cells recognizing neoepitopes with low affinity (11,987 nM IC50) for MHCI (Kd)
Abstract
Cancer neoepitopes are considered arguably central to cancer immunology. The neoepitopes which elicit CD8 T cell–dependent tumor control in murine models...
Cancers associés au VIH : immunogénomique, immunogénicité et immunothérapie
Cancers associés au VIH : immunogénomique, immunogénicité et immunothérapie
Les cancers, notamment les cancers bronchiques non à petites cellules (CBNPC), sont particulièrement fréquents chez les personnes vivant avec le VIH (PVVIH). Cependant, malgré cett...
Effect of RNA preservation methods on RNA quantity and quality of field collected avian whole blood
Effect of RNA preservation methods on RNA quantity and quality of field collected avian whole blood
ABSTRACT
A limitation of comparative transcriptomic studies of wild avian populations continues to be sample acquisition and preservation to achi...
Interannual Variability in Arctic Surface Energy Fluxes and their Drivers
Interannual Variability in Arctic Surface Energy Fluxes and their Drivers
<div>
<p>The Arctic is undergoing amplified climate warming, and temperature and precipitation are predicted to increase even more in the future. Increa...
B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
Abstract
Background
Efficient nucleic acid extraction and purification are crucial for cellular and molecular biology research, ...
Giant Sacrococcygeal Teratoma in Infant: Systematic Review
Giant Sacrococcygeal Teratoma in Infant: Systematic Review
Abstract
Introduction
Sacrococcygeal teratoma (SCT) is a rare embryonal tumor that occurs in the sacrococcygeal region, with an incidence of about 1 in 35,000 to 40,000 live births...

