Different strategies based on peptides are available for cancer treatment, in particular to
counter-act the progression of tumor growth and disease relapse. In the last decade, in the …

Abstract Machine learning and in particular deep learning (DL) are increasingly important in
mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention …

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer
immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a …

Most human proteins lack chemical probes, and several large-scale and generalizable small-
molecule binding assays have been introduced to address this problem. How compounds …

Therapy-resistant leukemia stem and progenitor cells (LSC) are a main cause of acute
myeloid leukemia (AML) relapse. LSC-targeting therapies may thus improve outcome of …

MS is the most effective method to directly identify peptides presented on human leukocyte
antigen (HLA) molecules. However, current standard approaches often use 500 million or …

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class
I, class II, and non-classical molecules. The peptides are produced by the degradation of …

Understanding the properties of human leukocyte antigen (HLA) peptides (immunopeptides)
is essential for precision cancer medicine, while the direct identification of immunopeptides …

In autoimmune diseases, recognition of self-antigens presented by major histocompatibility
complex (MHC) molecules elicits unexpected attack of tissue by autoantibodies and/or …

Introduction Mass spectrometry-based immunopeptidomics is the only unbiased method to
identify naturally presented HLA ligands, which is an indispensable prerequisite for …