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Possibility of the use of public microarray database for identifying significant genes associated with oral squamous cell carcinoma.

Kim KY, Cha IH - Genomics Inform (2012)

Bottom Line: From these selected genes, significant genetic pathways associated with expression changes were identified.By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information.Several unknown genes can be biologically evaluated in further studies.

View Article: PubMed Central - PubMed

Affiliation: Oral Cancer Research Institute, College of Dentistry, Yonsei University, Seoul 120-752, Korea.

ABSTRACT
There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

No MeSH data available.


Related in: MedlinePlus

Network with the highest score (Network 1). Functional relationships between genes based on known interactions in Ingenuity Pathway Analysis (IPA) knowledge are described.
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Related In: Results  -  Collection

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Figure 3: Network with the highest score (Network 1). Functional relationships between genes based on known interactions in Ingenuity Pathway Analysis (IPA) knowledge are described.

Mentions: To generate networks in this work, the knowledge base was queried for interactions between the identified genes and all other genes stored in the database. Four networks were found to be significant in OSCC. The network with the highest score (Network 1, score = 36) was generated, with 17 identified genes (Table 7, Fig. 3).


Possibility of the use of public microarray database for identifying significant genes associated with oral squamous cell carcinoma.

Kim KY, Cha IH - Genomics Inform (2012)

Network with the highest score (Network 1). Functional relationships between genes based on known interactions in Ingenuity Pathway Analysis (IPA) knowledge are described.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3475481&req=5

Figure 3: Network with the highest score (Network 1). Functional relationships between genes based on known interactions in Ingenuity Pathway Analysis (IPA) knowledge are described.
Mentions: To generate networks in this work, the knowledge base was queried for interactions between the identified genes and all other genes stored in the database. Four networks were found to be significant in OSCC. The network with the highest score (Network 1, score = 36) was generated, with 17 identified genes (Table 7, Fig. 3).

Bottom Line: From these selected genes, significant genetic pathways associated with expression changes were identified.By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information.Several unknown genes can be biologically evaluated in further studies.

View Article: PubMed Central - PubMed

Affiliation: Oral Cancer Research Institute, College of Dentistry, Yonsei University, Seoul 120-752, Korea.

ABSTRACT
There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

No MeSH data available.


Related in: MedlinePlus