Dataset Information

A study based on proteomic analysis

ABSTRACT: To understand the differentially expressed proteins of HIV/HBV co-infected persons at different stages of disease.

ORGANISM(S): Homo Sapiens

SUBMITTER: Rongrong Yang

PROVIDER: PXD046369 | iProX | Wed Oct 25 00:00:00 BST 2023

REPOSITORIES: iProX

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Publications

Serum protein biomarkers for HCC risk prediction in HIV/HBV co-infected people: a clinical proteomic study using mass spectrometry.

Ke Hengning H Yuan Rui R Liu Huan H Luo Mingqi M Hu Hui H Zhang Ejuan E Zhuang Ke K Yang Yong Y Yang Rongrong R

Frontiers in immunology 20231110

<h4>Background</h4>HBV coinfection is frequent in people living with HIV (PLWH) and is the leading cause of hepatocellular carcinoma (HCC). While risk prediction methods for HCC in patients with HBV monoinfection have been proposed, suitable biomarkers for early diagnosis of HCC in PLWH remain uncommon.<h4>Methods</h4>Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine serum protein alterations in HCC and non-HCC patients with HIV and HBV co-infection. Gene Ontology (GO ...[more]

PMID: 38022651

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Project description:Background and aims: The intrahepatic processes associated with chronic hepatitis B (CHB), especially in the context of HDV and HIV co-infection, require a better understanding. Spatial transcriptomics can provide new insights into the complex intrahepatic biological processes, guiding new personalized treatments. Our aim is to evaluate this method to characterize the hepatic transcriptional landscape, cellular composition and biological pathways in liver biopsy samples from patients infected with HBV and HDV or HIV co-infection. Method: The GeoMx nanostring Digital Spatial Profiling (DSP) platform was employed to assess expression of HBsAg and CD45 in formalin fixed paraffin embedded (FFPE) biopsies from three treatment-naïve patients with chronic HBV and HDV or HIV co-infection. The GeoMx whole transcriptome human atlas assay quantified the expression of genes enriched in specific regions of interest (ROIs). Cell type proportions within ROIs were deconvoluted using a training matrix from the human liver cell atlas. A weighted gene correlation network analysis (WGCNA) evaluated transcriptomic signatures across sampled regions. Results: We identified spatially discrete transcriptomic signatures and distinct biological pathways that associate with HBV infection/disease status and immune responses. Shared features including cytotoxicity and B cell receptor signaling were consistent across patients, suggesting common elements alongside individual traits. HDV/HBV co-infection exhibited upregulated genes linked to apoptosis and immune cell recruitment, whereas HIV/HBV co-infection featured genes related to interferon response regulation. Varied cellular characteristics and immune cell populations, with an abundance of T cells in the HDV/HBV sample, were observed within analyzed regions. Transcriptional differences in hepatocyte function suggest disrupted metabolic processes in HDV/HBV co-infection potentially impacting disease progression. Conclusion: This proof-of-principle study shows the value of this platform in investigating the complex immune landscape highlighting relevant host pathways to disease pathogenesis.

Dataset Information

A study based on proteomic analysis

Publications

Serum protein biomarkers for HCC risk prediction in HIV/HBV co-infected people: a clinical proteomic study using mass spectrometry.

Similar Datasets

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