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An integrative multi-platform analysis for discovering biomarkers of osteosarcoma.

Li G, Zhang W, Zeng H, Chen L, Wang W, Liu J, Zhang Z, Cai Z - BMC Cancer (2009)

Bottom Line: While expression of 310 genes was increased, expression of the other 343 genes was decreased.Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Orthopaedics, Tenth People's Hospital, Tongji University, Shanghai, PR China. litrue2004@yahoo.com.cn

ABSTRACT

Background: SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (m/z) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis.

Methods: After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma.

Results: Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.

Conclusion: Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.

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Related in: MedlinePlus

Flowchart in this study. Microarray and SELDI-TOF data were processed independently, and differentially expressed candidate markers were extracted from each type of analysis. Link tests were then applied to identify the significant common candidates from the association of microarray markers and mass spectrum markers. Finally, the candidate biomarkers were screened and expression of CYC-1 gene was validated by the experiments as an example.
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Figure 1: Flowchart in this study. Microarray and SELDI-TOF data were processed independently, and differentially expressed candidate markers were extracted from each type of analysis. Link tests were then applied to identify the significant common candidates from the association of microarray markers and mass spectrum markers. Finally, the candidate biomarkers were screened and expression of CYC-1 gene was validated by the experiments as an example.

Mentions: We reasoned that the non-random peaks from mass spectrum analysis were likely to be originated from altered gene expression. Therefore, differentially expressed transcripts from microarray analysis were compared to the SELDI-TOF-MS data by link-test to determine the statistically significant hits [1]. Briefly, genes identified by microarray analysis were translated into corresponding proteins or peptides, and the expected m/z values were obtained from SWISS-PROT [16-19]http://www.expasy.ch/sprot/. Then, each m/z value of the peaks detected by SELDI-TOF mass spectrometry was compared with all those expected m/z values repeatedly. The significance of the result was evaluated by link-test. The p value was assigned to 0.05 by binomial test using default parameters with δ = 0.01[1]. The candidate biomarkers supported by both advanced high-throughput platforms were chosen for further experimental validation (see Figure 1). The algorithm of link-test was re-implemented in C/C++ code. All parameters were set by default.


An integrative multi-platform analysis for discovering biomarkers of osteosarcoma.

Li G, Zhang W, Zeng H, Chen L, Wang W, Liu J, Zhang Z, Cai Z - BMC Cancer (2009)

Flowchart in this study. Microarray and SELDI-TOF data were processed independently, and differentially expressed candidate markers were extracted from each type of analysis. Link tests were then applied to identify the significant common candidates from the association of microarray markers and mass spectrum markers. Finally, the candidate biomarkers were screened and expression of CYC-1 gene was validated by the experiments as an example.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2691408&req=5

Figure 1: Flowchart in this study. Microarray and SELDI-TOF data were processed independently, and differentially expressed candidate markers were extracted from each type of analysis. Link tests were then applied to identify the significant common candidates from the association of microarray markers and mass spectrum markers. Finally, the candidate biomarkers were screened and expression of CYC-1 gene was validated by the experiments as an example.
Mentions: We reasoned that the non-random peaks from mass spectrum analysis were likely to be originated from altered gene expression. Therefore, differentially expressed transcripts from microarray analysis were compared to the SELDI-TOF-MS data by link-test to determine the statistically significant hits [1]. Briefly, genes identified by microarray analysis were translated into corresponding proteins or peptides, and the expected m/z values were obtained from SWISS-PROT [16-19]http://www.expasy.ch/sprot/. Then, each m/z value of the peaks detected by SELDI-TOF mass spectrometry was compared with all those expected m/z values repeatedly. The significance of the result was evaluated by link-test. The p value was assigned to 0.05 by binomial test using default parameters with δ = 0.01[1]. The candidate biomarkers supported by both advanced high-throughput platforms were chosen for further experimental validation (see Figure 1). The algorithm of link-test was re-implemented in C/C++ code. All parameters were set by default.

Bottom Line: While expression of 310 genes was increased, expression of the other 343 genes was decreased.Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Orthopaedics, Tenth People's Hospital, Tongji University, Shanghai, PR China. litrue2004@yahoo.com.cn

ABSTRACT

Background: SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (m/z) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis.

Methods: After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma.

Results: Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.

Conclusion: Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.

Show MeSH
Related in: MedlinePlus