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Dynamic human liver proteome atlas reveals functional insights into disease pathways

ABSTRACT: Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell-type resolution. Here, we quantify more than 10,000 proteins and 150,000 sequence-unique peptides across total liver, the major liver cell types, time-course of primary cell cultures and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serves as spectral library to characterize a human cohort of non-alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver biopsies include signatures of stellate cell activation resembling liver cirrhosis, providing functional insights.

INSTRUMENT(S): Q Exactive HF-X, Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Kupffer Cell, Endothelial Cell Of Sinusoid, Primary Cell, Hepatocyte, Hepatic Stellate Cell, Liver, Cell Culture

DISEASE(S): Non-alcoholic Steatohepatitis,Liver Cirrhosis

SUBMITTER: Lili Niu

LAB HEAD: Matthias Mann

PROVIDER: PXD027722 | Pride | 2022-05-08

REPOSITORIES: Pride

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			Action	DRS
	20171224_QE10_nLC13_LiNi_SA_000001_HliverAtlas_Plate1_10_F1.raw	Raw
	20171224_QE10_nLC13_LiNi_SA_000001_HliverAtlas_Plate1_10_F2.raw	Raw
	20171224_QE10_nLC13_LiNi_SA_000001_HliverAtlas_Plate1_10_F3.raw	Raw
	20171224_QE10_nLC13_LiNi_SA_000001_HliverAtlas_Plate1_10_F4.raw	Raw
	20171224_QE10_nLC13_LiNi_SA_000001_HliverAtlas_Plate1_10_F5.raw	Raw

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Project description:Gene-expression profiles of hepatitis C-related, early-stage liver cirrhosis Background & Aims: Liver cirrhosis affects 1%M-bM-^HM-^R2% of population and is the major risk factor of hepatocellular carcinoma (HCC). Hepatitis C cirrhosis-related HCC is the most rapidly increasing cause of cancer death in the US. Non-invasive methods have been developed to identify patients with asymptomatic, early-stage cirrhosis, increasing the burden of HCC surveillance, but biomarkers are needed to identify patients with cirrhosis who are most in need of surveillance. We investigated whether a liver-derived 186-gene signature previously associated with outcomes of patients with HCC is prognostic for patients newly diagnosed with cirrhosis but without HCC. Methods: We performed gene expression profile analysis of formalin-fixed needle biopsies from the livers of 216 patients with hepatitis C-related early-stage (Child-Pugh class A) cirrhosis who were prospectively followed for a median of 10 years at an Italian center. We evaluated whether the 186-gene signature was associated with death, progression of cirrhosis, and development of HCC. Results: Fifty-five (25%), 101 (47%), and 60 (28%) patients were classified as having poor-, intermediate-, and good-prognosis signatures, respectively. In multivariable Cox regression modeling, the poor-prognosis signature was significantly associated with death (P=.004), progression to advanced cirrhosis (P<.001), and development of HCC (P=.009). The 10-year rates of survival were 63%, 74%, and 85% and the annual incidences of HCC were 5.8%, 2.2%, and 1.5% for patients with poor-, intermediate-, and good-prognosis signatures, respectively. Conclusions: A 186-gene signature used to predict outcomes of patients with HCC is also associated with outcomes of patients with hepatitis C-related early-stage cirrhosis. This signature might be used to identify patients with cirrhosis in most need of surveillance and strategies to prevent their development of HCC. 216 liver biopsy specimens

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Dynamic human liver proteome atlas reveals functional insights into disease pathways

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