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Molecular characterization and cell type composition deconvolution of fibrosis in NAFLD.

ABSTRACT: Non-alcoholic fatty liver disease (NAFLD) is the most common cause of liver disease worldwide. In adults with NAFLD, fibrosis can develop and progress to liver cirrhosis and liver failure. However, the underlying molecular mechanisms of fibrosis progression are not fully understood. Using total RNA-Seq, we investigated the molecular mechanisms of NAFLD and fibrosis. We sequenced liver tissue from 143 adults across the full spectrum of fibrosis stage including those with stage 4 fibrosis (cirrhosis). We identified gene expression clusters that strongly correlate with fibrosis stage including four genes that have been found consistently across previously published transcriptomic studies on NASH i.e. COL1A2, EFEMP2, FBLN5 and THBS2. Using cell type deconvolution, we estimated the loss of hepatocytes versus gain of hepatic stellate cells, macrophages and cholangiocytes with advancing fibrosis stage. Hepatocyte-specific functional analysis indicated increase of pro-apoptotic pathways and markers of bipotent hepatocyte/cholangiocyte precursors. Regression modelling was used to derive predictors of fibrosis stage. This study elucidated molecular and cell composition changes associated with increasing fibrosis stage in NAFLD and defined informative gene signatures for the disease.

SUBMITTER: Pantano L

PROVIDER: S-EPMC8433177 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Acute myeloid leukemia (AML) is one of the malignant hematologic cancers with rapid progress and poor prognosis. Most AML prognostic stratifications focused on genetic abnormalities. However, none of them was established based on the cell type compositions (CTCs) of peripheral blood or bone marrow aspirates from patients at diagnosis. Here we sought to develop a novel prognostic model for AML in adults based on the CTCs. First, we applied the CIBERSORT algorithm to estimate the CTCs for patients from two public datasets (GSE6891 and TCGA-LAML) using a custom gene expression signature reference constructed by an AML single-cell RNA sequencing dataset (GSE116256). Then, a CTC-based prognostic model was established using least absolute shrinkage and selection operator Cox regression, termed CTC score. The constructed prognostic model CTC score comprised 3 cell types, GMP-like, HSC-like, and T. Compared with the low-CTC-score group, the high-CTC-score group showed a 1.57-fold [95% confidence interval (CI), 1.23 to 2.00; p = 0.0002] and a 2.32-fold (95% CI, 1.53 to 3.51; p < 0.0001) higher overall mortality risk in the training set (GSE6891) and validation set (TCGA-LAML), respectively. When adjusting for age at diagnosis, cytogenetic risk, and karyotype, the CTC score remained statistically significant in both the training set [hazard ratio (HR) = 2.25; 95% CI, 1.20 to 4.24; p = 0.0119] and the validation set (HR = 7.97; 95% CI, 2.95 to 21.56; p < 0.0001]. We further compared the performance of the CTC score with two gene expression-based prognostic scores: the 17-gene leukemic stem cell score (LSC17 score) and the AML prognostic score (APS). It turned out that the CTC score achieved comparable performance at 1-, 2-, 3-, and 5-years timepoints and provided independent and additional prognostic information different from the LSC17 score and APS. In conclusion, the CTC score could serve as a powerful prognostic marker for AML and has great potential to assist clinicians to formulate individualized treatment plans.

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Molecular characterization and cell type composition deconvolution of fibrosis in NAFLD.

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