Evidence map›Paper›PMID 19232462›Full record

ReviewCancer letters2009

Comparative analysis of the liver and plasma proteomes as a novel and powerful strategy for hepatocellular carcinoma biomarker discovery.

Laura Beretta

Abstract readComparative StudyReview
In one paragraph

Review in Cancer letters, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
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  5. Article
  6. Progress in mining the human proteome for disease applications.Omics : a journal of integrative biology · 2011
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Laura BerettaMolecular Diagnostics Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center (M5-A864), 1100 Fairview Avenue North Seattle, WA 98109, USA. lberetta@fhcrc.org
Fred Hutch Cancer Center · US

Funding

Novel markers for HCV-related HCCR01DK066840 · NIDDK · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BERETTA, LAURA · 2004 to 2010
$2.0M
Markers for HCV-related HCC: plasma profiling, targeted strategies and validationR01CA120719 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BERETTA, LAURA · 2009 to 2013
$1.7M
NCI NIH HHS R01 CA120719NIDDK NIH HHS R01 DK066840
6 · The paper itself

Abstract

The extraordinary developments made in the past decade in proteomic technologies, in particular in mass spectrometry, have enabled investigators to consider designing studies to search for diagnostic and therapeutic biomarkers by scanning complex proteome samples. We developed a method based on extensive fractionation of intact proteins, to comprehensively and quantitatively profile the liver and plasma proteomes in health and disease. We have applied this method to samples collected from patients with early hepatocellular carcinoma (HCC) and from patients with liver cirrhosis as well as to samples collected from three mouse models of HCC. This method allowed for the identification of proteins that differ in expression levels in liver tissue or in plasma with disease progression from liver fibrosis, cirrhosis or steatohepatitis to HCC. The comparative analysis of the liver and plasma proteomes generated from human and mouse specimens, constitutes a novel and powerful strategy for HCC biomarker discovery.

Indexed as

ProteomeAnimalsBiomarkers, TumorCarcinoma, HepatocellularHumansLiver NeoplasmsMiceNeoplasm ProteinsBiomarkers, TumorNeoplasm ProteinsProteome

Identifiers

PMID19232462
PMCPMC4601561
OpenAlexW2038160689

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.