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The Spatial Extracellular Proteomic Tumor Microenvironment Distinguishes Molecular Subtypes of Hepatocellular Carcinoma.
- Source :
-
Journal of proteome research [J Proteome Res] 2024 Sep 06; Vol. 23 (9), pp. 3791-3805. Date of Electronic Publication: 2024 Jul 09. - Publication Year :
- 2024
-
Abstract
- Hepatocellular carcinoma (HCC) mortality rates continue to increase faster than those of other cancer types due to high heterogeneity, which limits diagnosis and treatment. Pathological and molecular subtyping have identified that HCC tumors with poor outcomes are characterized by intratumoral collagenous accumulation. However, the translational and post-translational regulation of tumor collagen, which is critical to the outcome, remains largely unknown. Here, we investigate the spatial extracellular proteome to understand the differences associated with HCC tumors defined by Hoshida transcriptomic subtypes of poor outcome (Subtype 1; S1; n = 12) and better outcome (Subtype 3; S3; n = 24) that show differential stroma-regulated pathways. Collagen-targeted mass spectrometry imaging (MSI) with the same-tissue reference libraries, built from untargeted and targeted LC-MS/MS was used to spatially define the extracellular microenvironment from clinically-characterized, formalin-fixed, paraffin-embedded tissue sections. Collagen α-1(I) chain domains for discoidin-domain receptor and integrin binding showed distinctive spatial distribution within the tumor microenvironment. Hydroxylated proline (HYP)-containing peptides from the triple helical regions of fibrillar collagens distinguished S1 from S3 tumors. Exploratory machine learning on multiple peptides extracted from the tumor regions could distinguish S1 and S3 tumors (with an area under the receiver operating curve of ≥0.98; 95% confidence intervals between 0.976 and 1.00; and accuracies above 94%). An overall finding was that the extracellular microenvironment has a high potential to predict clinically relevant outcomes in HCC.
- Subjects :
- Humans
Tandem Mass Spectrometry
Proteome analysis
Proteome genetics
Chromatography, Liquid
Machine Learning
Collagen Type I metabolism
Collagen Type I genetics
Carcinoma, Hepatocellular genetics
Carcinoma, Hepatocellular metabolism
Carcinoma, Hepatocellular pathology
Carcinoma, Hepatocellular classification
Liver Neoplasms genetics
Liver Neoplasms metabolism
Liver Neoplasms pathology
Liver Neoplasms classification
Tumor Microenvironment
Proteomics methods
Subjects
Details
- Language :
- English
- ISSN :
- 1535-3907
- Volume :
- 23
- Issue :
- 9
- Database :
- MEDLINE
- Journal :
- Journal of proteome research
- Publication Type :
- Academic Journal
- Accession number :
- 38980715
- Full Text :
- https://doi.org/10.1021/acs.jproteome.4c00099