Glycoproteogenomics: Setting the Course for Next-Generation Cancer Neoantigen Discovery for Cancer Vaccines

Abstract

Molecular-assisted precision oncology gained tremendous ground with high-throughput next-generation sequencing (NGS), supported by robust bioinformatics. The quest for genomics-based cancer medicine set the foundations for improved patient stratification, while unveiling a wide array of neoantigens for immunotherapy. Upfront pre-clinical and clinical studies have successfully used tumor-specific peptides in vaccines with minimal off-target effects. However, the low mutational burden presented by many lesions challenges the generalization of these solutions, requiring the diversification of neoantigen sources. Oncoproteogenomics utilizing customized databases for protein annotation by mass spectrometry (MS) is a powerful tool toward this end. Expanding the concept toward exploring proteoforms originated from post-translational modifications (PTMs) will be decisive to improve molecular subtyping and provide potentially targetable functional nodes with increased cancer specificity. Walking through the path of systems biology, we highlight that alterations in protein glycosylation at the cell surface not only have functional impact on cancer progression and dissemination but also originate unique molecular fingerprints for targeted therapeutics. Moreover, we discuss the outstanding challenges required to accommodate glycoproteomics in oncoproteogenomics platforms. We envisage that such rationale may flag a rather neglected research field, generating novel paradigms for precision oncology and immunotherapy.

Expression Patterns of Glycosylation Regulators Define Tumor Microenvironment and Immunotherapy in Gastric Cancer

“…Although cumulative mutations may be part of the cause of GC, glycosylation in GC-related genes is also associated with GC ( Fernandes et al, 2020 ; Aziz et al, 2021 ). More than half of the proteins in organisms have glycosylation modification, including transcription factors and metabolism-related enzymes ( Ferreira et al, 2021 ; Sun et al, 2021 ; Zheng et al, 2021 ). Glycosylation modification affects protein spatial conformation, activity, transportation, and positioning and is widely involved in intercellular recognition, regulation, and signal transduction ( Hombu et al, 2021 ).…”

Glycoproteogenomics characterizes the CD44 splicing code driving bladder cancer invasion

“…Additionally, we tackled the limitations of transcriptomics and proteomics for definitive CD44 characterization, bringing together these different omics and glycomics. We have demonstrated that CD44 characterization cannot be achieved by a single omics and highlighted the importance of adding glycosylation for definitive isoforms identification, materializing the concept of glycoproteogenomics (28).…”

A roadmap for translational cancer glycoimmunology at single cell resolution

“…This rationale has also served as basis for glycoproteomics studies, supported by dedicated and progressively more standardized mass spectrometry workflows [ 88 ], which have now started to unveil the nature of the proteins carrying many of the described post-translational modifications. Blueprints regarding the existence of cancer unique and context-dependent glycoproteomes have already been provided [ 13 , 27 , 89 ], paving the way towards precise cancer targeting and personalization. These advances will be of major importance for decoding the crosstalk between cancer cells and the immune system towards clinical intervention.…”

“…Integrated SUGAR-seq and glycoproteome analysis has led to the characterization of tumour-infiltrating T cells glycophenotypes, mirroring their epigenetic and functional state and holding potential for advances in cancer glycoimmunology. Very recently, we have also materialized the concept of glycoproteogenomics, which builds on comprehensive integration of RNAseq-data to customized databases used in protein annotation [ 89 , 292 ]. This has allowed deeper access to the glycoproteome, now requiring translation to single cell analysis.…”