Literature DB >> 25459666

Evaluation of serum-based cancer biomarkers: a brief review from a clinical and computational viewpoint.

Sohiya Yotsukura1, Hiroshi Mamitsuka2.   

Abstract

Biomarkers are vital to detect diseases in various clinical stages. A variety of cancer serum biomarkers are already known, while for more accurate cancer-type detection, there required more rigorous evaluation manners, especially computational evaluation measures, for biomarkers. In this review, we first show three typical pitfalls in finding biomarkers and their examples, after briefly presenting standard five clinical biomarker screening phases by National Cancer Institute. We then introduce current computational biomarker evaluation measures, including current, standard methods with their intrinsic features. We further show an up-to-date list of existing cancer serum biomarkers, pointing out several issues, being caused by the limitations of current biomarker evaluation approaches. Finally we discuss the current attempts to develop new, statistically robust, computational serum-based biomarker measures in terms of specificity to each of various cancer types.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Computational evaluation; Diagnostic odds ratio; Likelihood ratios; Predictive values; Quantitative assessment; Receiver operating characteristic curve; Serum biomarkers

Mesh:

Substances:

Year:  2014        PMID: 25459666     DOI: 10.1016/j.critrevonc.2014.10.002

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  18 in total

1.  Integrated electrokinetically driven microfluidic devices with pH-mediated solid-phase extraction coupled to microchip electrophoresis for preterm birth biomarkers.

Authors:  Mukul Sonker; Radim Knob; Vishal Sahore; Adam T Woolley
Journal:  Electrophoresis       Date:  2017-04-25       Impact factor: 3.535

2.  Magnetic Bead-Immobilized Mammalian Cells Are Effective Targets to Enrich Ligand-Displaying Yeast.

Authors:  Patrick S Lown; Benjamin J Hackel
Journal:  ACS Comb Sci       Date:  2020-04-27       Impact factor: 3.784

3.  Geometry and expression enhance enrichment of functional yeast-displayed ligands via cell panning.

Authors:  Lawrence A Stern; Ian A Schrack; Sadie M Johnson; Aakash Deshpande; Nathaniel R Bennett; Lauren A Harasymiw; Melissa K Gardner; Benjamin J Hackel
Journal:  Biotechnol Bioeng       Date:  2016-06-30       Impact factor: 4.530

4.  Quantitative Profiling of Post-translational Modifications by Immunoaffinity Enrichment and LC-MS/MS in Cancer Serum without Immunodepletion.

Authors:  Hongbo Gu; Jian Min Ren; Xiaoying Jia; Tyler Levy; Klarisa Rikova; Vicky Yang; Kimberly A Lee; Matthew P Stokes; Jeffrey C Silva
Journal:  Mol Cell Proteomics       Date:  2015-12-03       Impact factor: 5.911

5.  Ligand Engineering via Yeast Surface Display and Adherent Cell Panning.

Authors:  Lawrence A Stern; Patrick S Lown; Benjamin J Hackel
Journal:  Methods Mol Biol       Date:  2020

Review 6.  Tumor-Associated CSF MicroRNAs for the Prediction and Evaluation of CNS Malignancies.

Authors:  Tarek Shalaby; Michael A Grotzer
Journal:  Int J Mol Sci       Date:  2015-12-07       Impact factor: 5.923

7.  Count of platelet and mean platelet volume score: serologic prognostic factor in patients with oral squamous cell carcinoma.

Authors:  Jae Woo Park; Chul-Hwan Kim; Yong Chan Ha; Moon Young Kim; Sung Min Park
Journal:  J Korean Assoc Oral Maxillofac Surg       Date:  2017-10-26

8.  Significantly higher serum tumor marker levels in patients with oral submucous fibrosis.

Authors:  Yu-Hsueh Wu; Ping-Yi Lin; Ju-Hsuan Yang; Ying-Shiung Kuo; Yang-Che Wu; Chun-Pin Chiang
Journal:  J Dent Sci       Date:  2021-03-11       Impact factor: 2.080

Review 9.  Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

Authors:  Alan Kirwan; Marta Utratna; Michael E O'Dwyer; Lokesh Joshi; Michelle Kilcoyne
Journal:  Biomed Res Int       Date:  2015-10-05       Impact factor: 3.411

10.  Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human.

Authors:  Caixia Li; Xing Fei Tan; Teck Kwang Lim; Qingsong Lin; Zhiyuan Gong
Journal:  Sci Rep       Date:  2016-04-13       Impact factor: 4.379

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