Dataset Information

Identification and validation of expressed HLA-binding breast cancer neoepitopes for potential use in individualized cancer therapy.

ABSTRACT:

Background

Therapeutic regimens designed to augment the immunological response of a patient with breast cancer (BC) to tumor tissue are critically informed by tumor mutational burden and the antigenicity of expressed neoepitopes. Herein we describe a neoepitope and cognate neoepitope-reactive T-cell identification and validation program that supports the development of next-generation immunotherapies.

Methods

Using GPS Cancer, NantOmics research, and The Cancer Genome Atlas databases, we developed a novel bioinformatic-based approach which assesses mutational load, neoepitope expression, human leukocyte antigen (HLA)-binding prediction, and in vitro confirmation of T-cell recognition to preferentially identify targetable neoepitopes. This program was validated by application to a BC cell line and confirmed using tumor biopsies from two patients with BC enrolled in the Tumor-Infiltrating Lymphocytes and Genomics (TILGen) study.

Results

The antigenicity and HLA-A2 restriction of the BC cell line predicted neoepitopes were determined by reactivity of T cells from HLA-A2-expressing healthy donors. For the TILGen subjects, tumor-infiltrating lymphocytes (TILs) recognized the predicted neoepitopes both as peptides and on retroviral expression in HLA-matched Epstein-Barr virus-lymphoblastoid cell line and BC cell line MCF-7 cells; PCR clonotyping revealed the presence of T cells in the periphery with T-cell receptors for the predicted neoepitopes. These high-avidity immune responses were polyclonal, mutation-specific and restricted to either HLA class I or II. Interestingly, we observed the persistence and expansion of polyclonal T-cell responses following neoadjuvant chemotherapy.

Conclusions

We demonstrate our neoepitope prediction program allows for the successful identification of neoepitopes targeted by TILs in patients with BC, providing a means to identify tumor-specific immunogenic targets for individualized treatment, including vaccines or adoptively transferred cellular therapies.

SUBMITTER: Reimann H

PROVIDER: S-EPMC8237736 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Publications

Identification and validation of expressed HLA-binding breast cancer neoepitopes for potential use in individualized cancer therapy.

Reimann Hannah H Nguyen Andrew A Sanborn J Zachary JZ Vaske Charles J CJ Benz Stephen C SC Niazi Kayvan K Rabizadeh Shahrooz S Spilman Patricia P Mackensen Andreas A Ruebner Matthias M Hein Alexander A Beckmann Matthias W MW van der Meijden Edith D ED Bausenwein Judith J Kretschmann Sascha S Griffioen Marieke M Schlom Jeffrey J Gulley James L JL Lee Karin L KL Hamilton Duane H DH Soon-Shiong Patrick P Fasching Peter A PA Kremer Anita N AN

Journal for immunotherapy of cancer 20210601 6

<h4>Background</h4>Therapeutic regimens designed to augment the immunological response of a patient with breast cancer (BC) to tumor tissue are critically informed by tumor mutational burden and the antigenicity of expressed neoepitopes. Herein we describe a neoepitope and cognate neoepitope-reactive T-cell identification and validation program that supports the development of next-generation immunotherapies.<h4>Methods</h4>Using GPS Cancer, NantOmics research, and The Cancer Genome Atlas databa ...[more]

PMID: 34172517

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Project description:BackgroundBreast cancer (BRCA) is one of the most common cancers and the leading cause of cancer-related death in women. RNA-binding proteins (RBPs) play an important role in the emergence and pathogenesis of tumors. The target RNAs of RBPs are very diverse; in addition to binding to mRNA, RBPs also bind to noncoding RNA. Noncoding RNA can cause secondary structures that can bind to RBPs and regulate multiple processes such as splicing, RNA modification, protein localization, and chromosomes remodeling, which can lead to tumor initiation, progression, and invasion.Methods(1) BRCA data were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases and were used as training and testing datasets, respectively. (2) The prognostic RBPs-related genes were screened according to the overlapping differentially expressed genes (DEGs) from the TCGA database. (3) Univariate Cox proportional hazard regression was performed to identify the genes with significant prognostic value. (4) Further, we used the LASSO regression to construct a prognostic signature and validated the signature in the TCGA and ICGC cohort. (5) Besides, we also performed prognostic analysis, expression level verification, immune cell correlation analysis, and drug correlation analysis of the genes in the model.ResultsFour genes (MRPL13, IGF2BP1, BRCA1, and MAEL) were identified as prognostic gene signatures. The prognostic model has been validated in the TCGA and ICGC cohorts. The risk score calculated with four genes signatures could largely predict overall survival for 1, 3, and 5 years in patients with BRCA. The calibration plot demonstrated outstanding consistency between the prediction and actual observation. The findings of online database verification revealed that these four genes were significantly highly expressed in tumors. Also, we observed their significant correlations with some immune cells and also potential correlations with some drugs.ConclusionWe constructed a 4-RBPs-based prognostic signature to predict the prognosis of BRCA patients, and it has the potential for treating and diagnosing BRCA.

Dataset Information

Identification and validation of expressed HLA-binding breast cancer neoepitopes for potential use in individualized cancer therapy.

Background

Methods

Results

Conclusions

Publications

Identification and validation of expressed HLA-binding breast cancer neoepitopes for potential use in individualized cancer therapy.

Similar Datasets

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