Proteomics

Dataset Information

0

Plasma glycoproteomic biomarkers identify metastatic melanoma patients with reduced clinical benefit from immune checkpoint inhibitor therapy


ABSTRACT: The clinical success of immune-checkpoint inhibitors (ICI) in both resected and metastatic melanoma has confirmed the validity of therapeutic strategies that boost the immune system to counteract cancer. However, half of patients with metastatic disease treated with even the most aggressive regimen do not derive durable clinical benefit. Thus, there is a critical need for predictive biomarkers that can identify individuals who are unlikely to benefit with high accuracy, so that these patients may be spared the toxicity of treatment without the likely benefit of response. Ideally, such an assay would have a fast turnaround time and minimal invasiveness. Here, we utilize a novel platform that combines mass spectrometry with an artificial intelligence-based data processing engine to interrogate the blood glycoproteome in melanoma patients before receiving ICI therapy. We identify 143 biomarkers that demonstrate a difference in expression between the patients who died within six months of starting ICI treatment and those who remained progression-free for three years. We then develop a glycoproteomic classifier that predicts benefit of immunotherapy (HR=2.7; p=0.026) and achieves a significant separation of patients in an independent cohort (HR=5.6; p=0.027). To understand how circulating glycoproteins may affect efficacy of treatment, we analyze the differences in glycosylation structure and discover a fucosylation signature in patients with shorter overall survival (OS). We then develop a fucosylation-based model that effectively stratifies patients (HR=3.5; p=0.0066). Together, our data demonstrate the utility of plasma glycoproteomics for biomarker discovery and prediction of ICI benefit in patients with metastatic melanoma and suggest that protein fucosylation may be a determinant of anti-tumor immunity.

INSTRUMENT(S): 6495C Triple Quadrupole LC/MS

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Gege Xu  

PROVIDER: MSV000092069 | MassIVE | Wed May 31 16:41:00 BST 2023

REPOSITORIES: MassIVE

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2017-12-04 | GSE100797 | GEO
2020-06-01 | GSE144946 | GEO
2022-12-16 | PXD038068 | Pride
2022-12-16 | PXD038303 | Pride
2022-12-16 | PXD038636 | Pride
2022-12-16 | PXD038065 | Pride
2023-11-17 | MODEL2310150001 | BioModels
2015-12-31 | E-GEOD-67496 | biostudies-arrayexpress
2016-10-23 | MSV000080280 | MassIVE
2016-10-23 | MSV000080282 | MassIVE