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Chinese Journal of Breast Disease(Electronic Edition) ›› 2007, Vol. 01 ›› Issue (03): 40-43. doi: 10.3877/cma.j.issn.1674-0807.2007.03.013

• Clinical Research • Previous Articles     Next Articles

Proteome analysis for the identification of tumor-associated biomarkers to predict breast cancer prognosis

Xi WANG1, Ming-tian YANG,1(), Ze-ming XIE1, Jun TANG1, Zhong-mei ZHOU1, Yi-xin ZENG1, Zhen-yu ZHU1   

  1. 1.State Key Laboratory of Oncology in South China,Guangzhou 510060,China
  • Received:2007-02-15 Online:2007-06-01 Published:2024-12-12
  • Contact: Ming-tian YANG

Abstract:

Objective

To find new biomarkers that can estimate the prognosis of breast cancer patients,for the patients who have the similar staging and accept same treatment get different treatment results.

Methods

Protein expression differences of serum samples of 64 breast cancer patients were analyzed with IMAC-3 and WCX-2 Ciphergen Protein Chip Arrays.Five-year follow-up of all the 64 breast cancer patients showed 13 patients died.The protein atlas of the 13 dead patients was compared with that of the other patients.

Results

On WCX-2 chip,a panel of two proteins(Mr9405 and Mr6424)was selected based on their collective contribution to the optimal separation between the dead patients and alive patients after 5-year follow-up.On Mr9405 site survived breast cancer patients had low expression,on Mr6424 site survived breast cancer patients had high expression,with sensitivity of 76.9%-84.6%and specificity of 76.4%-80.3%.On IMAC-3 chip,another two proteins(Mr4643 and Mr5910)had the ability to distinguish between the dead patients and alive patients after 5-year follow-up.Survived breast cancer patients had high expression,with sensitivity of 61.5%~76.9%and specificity of 68.6%~74.5%.

Conclusion

Protein expression in dead patients after 5-year follow-up is different from that of alive patients after 5-year follow-up,and those proteins with different expressions can be used as new biomarkers to predict breast cancer prognosis.

Key words: Breast neoplasms, Proteome analysis

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