Linked Life Data

16941571

Source:http://linkedlifedata.com/resource/pubmed/id/16941571

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
19
pubmed:dateCreated
2006-10-10
pubmed:abstractText
To find new biomarkers and establish serum protein fingerprint models for early diagnosis and preoperative staging of papillary thyroid carcinoma, we employed SELDI-TOF-MS and bioinformatics tools. A total of 116 samples were analyzed in this study. The first 80 samples were analyzed by SELDI-TOF-MS and two biomarker patterns were identified. Pattern 1 distinguishes patients with papillary thyroid carcinoma from healthy individuals. Pattern 2 distinguishes papillary thyroid carcinoma from benign thyroid nodes. The remaining 29 samples were analyzed on the second day and served as an independent test set. The analysis of this independent test set yielded a specificity of 80.0% and a sensitivity of 88.9% for pattern 1 and a specificity of 80.0% and a sensitivity of 80.0% for pattern 2. Two additional biomarker patterns were identified to distinguish different stages of the papillary thyroid carcinoma (pattern 3) with an accuracy of 77.1% and different pathological types of thyroid carcinoma (pattern 4) with an accuracy of 88.1%. Taken together, the SELDI-TOF-MS technique combined with bioinformatics approaches can not only facilitate the discovery of better biomarkers for papillary thyroid carcinoma but also provide a useful tool for molecular diagnosis in the future.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1615-9853
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5344-9
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Application of serum protein fingerprint in diagnosis of papillary thyroid carcinoma.
pubmed:affiliation
Department of Surgery, the First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henang Province, P R China.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Validation Studies