Potential proteomic biomarkers in assessing liver fibrosis using SELDI-TOF MS

Karataylı, Senem Ceren; Alagöz, Sümeyye; Mızrak, Dılşa; Sayki, Müyesser; Özkan, Mehmet; Savaş, Berna; Erden, Esra; Çınar, Kubilay; İdilman, Ramazan; Yurdaydın, Cihan; Bozdayı, A. Mithat

doi:10.4318/tjg.2012.0415

Cited by 4 publications

(4 citation statements)

References 26 publications

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“…Technical problems include selecting the best proteomics method for serum biomarker discovery [ 5 ]. Potential proteomic biomarkers can be notably determined through SELDI-TOF-MS [ 39 , 40 ]. SELDI-TOF-MS is a widely used technique for diagnostic biomarker discovery in plasma, serum, and tissue and has the ability to carry out screening and identification.…”

Section: Discussionmentioning

confidence: 99%

Determination of Serum Lost Goodwill Target Proteome in Patients with Severe Traumatic Brain Injury

Zhang

et al. 2015

BioMed Research International

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Section: Discussionmentioning

confidence: 99%

Determination of Serum Lost Goodwill Target Proteome in Patients with Severe Traumatic Brain Injury

Zhang

et al. 2015

BioMed Research International

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“…They obtained a sensitivity of 80.0% for all LC patients and a specificity of 81.8% for all noncirrhotic cohorts. Bozdayi et al [15] provided similar results with a sensitivity of 83.3% and a specificity of 85.1%. However, establishment of serum peptide pattern for predicting HBV-induced LC from noncirrhotic cohorts remains challenging.…”

Section: Introductionmentioning

confidence: 66%

Two Classifiers Based on Serum Peptide Pattern for Prediction of HBV-Induced Liver Cirrhosis Using MALDI-TOF MS

Cao

Cheng

et al. 2013

BioMed Research International

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Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of liver cirrhosis (LC) in China. Although liver biopsy is the reference method for evaluation of cirrhosis, it is an invasive procedure with inherent risk. The aim of this study is to discover novel noninvasive specific serum biomarkers for the diagnosis of HBV-induced LC. We performed bead fractionation/MALDI-TOF MS analysis on sera from patients with LC. Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine-(SVM-) based strategy. Based on the previous results, five supervised machine learning methods were employed to construct classifiers that discriminated proteomic spectra of patients with HBV-induced LC from those of controls. Here, we describe two novel methods for prediction of HBV-induced LC, termed LC-NB and LC-MLP, respectively. We obtained a sensitivity of 90.9%, a specificity of 94.9%, and overall accuracy of 93.8% on an independent test set. Comparisons with the existing methods showed that LC-NB and LC-MLP held better accuracy. Our study suggests that potential serum biomarkers can be determined for discriminating LC and non-LC cohorts by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. These two classifiers could be used for clinical practice in HBV-induced LC assessment.

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“…In limited studies published to date, these have been demonstrated to be highly predictive (AUROC >0.85) of fibrosis in hepatitis C, hepatitis B and NAFLD. 28 Recent advances in genomics and the advent of new efficient tools for large-scale analysis of gene expression have provided new insights into the knowledge and understanding of gene networks and regulatory pathways in various disease processes. 29 These methods include microarrays which can be used to analyse the expression of thousands of genes at a time.…”

Section: Future Developmentsmentioning

confidence: 99%

Serum Marker Panels for Predicting Liver Fibrosis – An Update

Joseph

2020

CBR

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Fibrosis prediction is an essential part of the assessment and management of patients with chronic liver disease. Traditionally the gold standard for assessment of fibrosis is liver biopsy, but it suffers from various limitations including risk of patient injury and sampling error. As a result, noninvasive tests of hepatic fibrosis have been used in patients with chronic liver disease due to conditions such as hepatitis B and C, and alcoholic and non-alcoholic fatty liver disease. With the advent of new direct-acting antivirals, hepatic fibrosis staging is an important component of treatment decisions in the care of patients with chronic hepatitis C virus infection. Current limitations of the noninvasive biomarker models include a significant indeterminate range, and a predictive ability that is limited to only a few stages of fibrosis. However newer technologies and novel proteins identified by proteomics and genomics offer the possibility for further refinement and individualisation of biomarker fibrosis models in the future.

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Potential proteomic biomarkers in assessing liver fibrosis using SELDI-TOF MS

Cited by 4 publications

References 26 publications

Determination of Serum Lost Goodwill Target Proteome in Patients with Severe Traumatic Brain Injury

Determination of Serum Lost Goodwill Target Proteome in Patients with Severe Traumatic Brain Injury

Two Classifiers Based on Serum Peptide Pattern for Prediction of HBV-Induced Liver Cirrhosis Using MALDI-TOF MS

Serum Marker Panels for Predicting Liver Fibrosis – An Update

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