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A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.


ABSTRACT: To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

SUBMITTER: Sugii Y 

PROVIDER: S-EPMC4778852 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

Sugii Yuh Y   Kasai Tomonari T   Ikeda Masashi M   Vaidyanath Arun A   Kumon Kazuki K   Mizutani Akifumi A   Seno Akimasa A   Tokutaka Heizo H   Kudoh Takayuki T   Seno Masaharu M  

Biomarkers in cancer 20160303


To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene ex  ...[more]