Literature DB >> 26504887

Deciphering hepatocellular responses to metabolic and oncogenic stress.

Kathrina L Marcelo1, Fumin Lin1, Kimal Rajapakshe1, Adam Dean1, Naomi Gonzales1, Cristian Coarfa1, Anthony R Means2, Lauren C Goldie3, Brian York2.   

Abstract

Each cell type responds uniquely to stress and fractionally contributes to global and tissue-specific stress responses. Hepatocytes, liver macrophages (MΦ), and sinusoidal endothelial cells (SEC) play functionally important and interdependent roles in adaptive processes such as obesity and tumor growth. Although these cell types demonstrate significant phenotypic and functional heterogeneity, their distinctions enabling disease-specific responses remain understudied. We developed a strategy for the simultaneous isolation and quantification of these liver cell types based on antigenic cell surface marker expression. To demonstrate the utility and applicability of this technique, we quantified liver cell-specific responses to high-fat diet (HFD) or diethylnitrosamine (DEN), a liver-specific carcinogen, and found that while there was only a marginal increase in hepatocyte number, MΦ and SEC populations were quantitatively increased. Global gene expression profiling of hepatocytes, MΦ and SEC identified characteristic gene signatures that define each cell type in their distinct physiological or pathological states. Integration of hepatic gene signatures with available human obesity and liver cancer microarray data provides further insight into the cell-specific responses to metabolic or oncogenic stress. Our data reveal unique gene expression patterns that serve as molecular "fingerprints" for the cell-centric responses to pathologic stimuli in the distinct microenvironment of the liver. The technical advance highlighted in this study provides an essential resource for assessing hepatic cell-specific contributions to metabolic and oncogenic stress, information that could unveil previously unappreciated molecular mechanisms for the cellular crosstalk that underlies the continuum from metabolic disruption to obesity and ultimately hepatic cancer.

Entities:  

Keywords:  endothelium; hepatocytes; liver cancer; macrophages; obesity

Year:  2015        PMID: 26504887      PMCID: PMC4617787          DOI: 10.14440/jbm.2015.77

Source DB:  PubMed          Journal:  J Biol Methods        ISSN: 2326-9901


  43 in total

1.  Functional and morphological characterization of cultures of Kupffer cells and liver endothelial cells prepared by means of density separation in Percoll, and selective substrate adherence.

Authors:  B Smedsrød; H Pertoft; G Eggertsen; C Sundström
Journal:  Cell Tissue Res       Date:  1985       Impact factor: 5.249

Review 2.  Obesity, inflammation, and liver cancer.

Authors:  Beicheng Sun; Michael Karin
Journal:  J Hepatol       Date:  2011-11-25       Impact factor: 25.083

3.  Kupffer cells express a unique combination of phenotypic and functional characteristics compared with splenic and peritoneal macrophages.

Authors:  Dowty Movita; Kim Kreefft; Paula Biesta; Adri van Oudenaren; Pieter J M Leenen; Harry L A Janssen; Andre Boonstra
Journal:  J Leukoc Biol       Date:  2012-06-08       Impact factor: 4.962

4.  Quantitative assessment of retroviral transfer of the human multidrug resistance 1 gene to human mobilized peripheral blood progenitor cells engrafted in nonobese diabetic/severe combined immunodeficient mice.

Authors:  B Schiedlmeier; K Kühlcke; H G Eckert; C Baum; W J Zeller; S Fruehauf
Journal:  Blood       Date:  2000-02-15       Impact factor: 22.113

5.  Cell expression patterns of CD147 in N-diethylnitrosamine/phenobarbital-induced mouse hepatocellular carcinoma.

Authors:  Meng Lu; Jiao Wu; Feng He; Xi-Long Wang; Can Li; Zhi-Nan Chen; Huijie Bian
Journal:  J Mol Histol       Date:  2014-12-02       Impact factor: 2.611

6.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

7.  A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.

Authors:  Stephanie Roessler; Hu-Liang Jia; Anuradha Budhu; Marshonna Forgues; Qing-Hai Ye; Ju-Seog Lee; Snorri S Thorgeirsson; Zhongtang Sun; Zhao-You Tang; Lun-Xiu Qin; Xin Wei Wang
Journal:  Cancer Res       Date:  2010-12-15       Impact factor: 12.701

8.  Mouse liver cell culture. I. Hepatocyte isolation.

Authors:  J E Klaunig; P J Goldblatt; D E Hinton; M M Lipsky; J Chacko; B F Trump
Journal:  In Vitro       Date:  1981-10

9.  Thyroid hormone-related regulation of gene expression in human fatty liver.

Authors:  Jussi Pihlajamäki; Tanner Boes; Eun-Young Kim; Farrell Dearie; Brian W Kim; Joshua Schroeder; Edward Mun; Imad Nasser; Peter J Park; Antonio C Bianco; Allison B Goldfine; Mary Elizabeth Patti
Journal:  J Clin Endocrinol Metab       Date:  2009-06-23       Impact factor: 5.958

Review 10.  New possibilities in hepatocellular carcinoma treatment.

Authors:  Mahmood Rasool; Sana Rashid; Mahwish Arooj; Shakeel Ahmed Ansari; Khalid Mahmud Khan; Arif Malik; Muhammad Imran Naseer; Sara Zahid; Abdul Manan; Muhammad Asif; Zarish Razzaq; Sadia Ashraf; Mahmood Husain Qazi; Zafar Iqbal; Siew Hua Gan; Mohammad Amjad Kamal; Ishfaq Ahmed Sheikh
Journal:  Anticancer Res       Date:  2014-04       Impact factor: 2.480

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  3 in total

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Authors:  Brittany A Stork; Adam Dean; Andrea R Ortiz; Pradip Saha; Nagireddy Putluri; Maricarmen D Planas-Silva; Iqbal Mahmud; Kimal Rajapakshe; Cristian Coarfa; Stefan Knapp; Philip L Lorenzi; Bruce E Kemp; Benjamin E Turk; John W Scott; Anthony R Means; Brian York
Journal:  Mol Metab       Date:  2022-05-11       Impact factor: 8.568

2.  Methodology for measuring oxidative capacity of isolated peroxisomes in the Seahorse assay.

Authors:  Brittany A Stork; Adam Dean; Brian York
Journal:  J Biol Methods       Date:  2022-06-08

3.  A genome-scale CRISPR Cas9 dropout screen identifies synthetically lethal targets in SRC-3 inhibited cancer cells.

Authors:  Yosi Gilad; Yossi Eliaz; Yang Yu; Adam M Dean; San Jung Han; Li Qin; Bert W O'Malley; David M Lonard
Journal:  Commun Biol       Date:  2021-03-25
  3 in total

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