optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM.

T-Cell-Based Platform for Functional Screening of T-Cell Receptors Identified in Single-Cell RNA Sequencing Data Sets of Tumor-Infiltrating T-Cells.

The advent of single-cell RNA sequencing (scRNAseq) has enabled in-depth gene expression analysis of several thousand cells isolated from tissues. We recently reported the application of scRNAseq toward the dissection of the tumor-infiltrating T-cell repertoire in human pancreatic cancer samples. In this study, we demonstrated that combined whole transcriptome and T-cell receptor (TCR) sequencing provides an effective way to identify tumor-reactive TCR clonotypes on the basis of gene expression signatures.

Low tumor interleukin-1β expression predicts a limited effect of adjuvant platinum-based chemotherapy for patients with completely resected lung adenocarcinoma: An identification and validation study.

Introduction And Objectives: Adjuvant platinum-based chemotherapy for completely resected non-small cell lung cancer is associated with modest improvement in survival; nevertheless, no validated biomarker exists for predicting the benefit or harm of adjuvant platinum-based chemotherapy.

Materials And Methods: We simultaneously measured 27 cytokines in operative tumor specimens from a discovery cohort (n = 97) by multiplex immunoassay; half of the patients received adjuvant platinum-based chemotherapy, and the other half were observed. We tested possible prognostic and predictive factors in multivariate Cox models for overall survival (OS) and relapse-free survival (RFS), and a tree-based method was applied to detect predictive factors with respect to RFS.

Prediction of tumor-reactive T cell receptors from scRNA-seq data for personalized T cell therapy.

The identification of patient-derived, tumor-reactive T cell receptors (TCRs) as a basis for personalized transgenic T cell therapies remains a time- and cost-intensive endeavor. Current approaches to identify tumor-reactive TCRs analyze tumor mutations to predict T cell activating (neo)antigens and use these to either enrich tumor infiltrating lymphocyte (TIL) cultures or validate individual TCRs for transgenic autologous therapies. Here we combined high-throughput TCR cloning and reactivity validation to train predicTCR, a machine learning classifier that identifies individual tumor-reactive TILs in an antigen-agnostic manner based on single-TIL RNA sequencing.

H3K27M neoepitope vaccination in diffuse midline glioma induces B and T cell responses across diverse HLA loci of a recovered patient.

H3K27M, a driver mutation with T and B cell neoepitope characteristics, defines an aggressive subtype of diffuse glioma with poor survival. We functionally dissect the immune response of one patient treated with an H3K27M peptide vaccine who subsequently entered complete remission. The vaccine robustly expanded class II human leukocyte antigen (HLA)-restricted peripheral H3K27M-specific T cells.