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PMID: 27573699 已发表 · ppublish 英语

Protein signatures as potential surrogate biomarkers for stratification and prediction of treatment response in chronic myeloid leukemia patients.

International journal of oncology ·第 49 卷 ·第 3 期 ·0000-00-00

Alaiya Ayodele A, Aljurf Mahmoud, Shinwari Zakia, Almohareb Fahad, Malhan Hafiz, Alzahrani Hazzaa, Owaidah Tarek, Fox Jonathan, Alsharif Fahad, Mohamed Said Y, Rasheed Walid, Aldawsari Ghuzayel, Hanbali Amr, Ahmed Syed Osman, Chaudhri Naeem

摘要

There is unmet need for prediction of treatment response for chronic myeloid leukemia (CML) patients. The present study aims to identify disease-specific/disease-associated protein biomarkers detectable in bone marrow and peripheral blood for objective prediction of individual's best treatment options and prognostic monitoring of CML patients. Bone marrow plasma (BMP) and peripheral blood plasma (PBP) samples from newly-diagnosed chronic-phase CML patients were subjected to expression-proteomics using quantitative two-dimensional gel electrophoresis (2-DE) and label-free liquid chromatography tandem mass spectrometry (LC-MS/MS). Analysis of 2-DE protein fingerprints preceding therapy commencement accurately predicts 13 individuals that achieved major molecular response (MMR) at 6 months from 12 subjects without MMR (No-MMR). Results were independently validated using LC-MS/MS analysis of BMP and PBP from patients that have more than 24 months followed-up. One hundred and sixty-four and 138 proteins with significant differential expression profiles were identified from PBP and BMP, respectively and only 54 proteins overlap between the two datasets. The protein panels also discriminates accurately patients that stay on imatinib treatment from patients ultimately needing alternative treatment. Among the identified proteins are TYRO3, a member of TAM family of receptor tyrosine kinases (RTKs), the S100A8, and MYC and all of which have been implicated in CML. Our findings indicate analyses of a panel of protein signatures is capable of objective prediction of molecular response and therapy choice for CML patients at diagnosis as 'personalized-medicine-model'.

文献信息
期刊
International journal of oncology
期刊简称
Int J Oncol
发表日期
0000-00-00
收录日期
2016-08-31
更新日期
2016-09-02
语言
英语
国家/地区
Greece
NLM ID
9306042
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