TY - JOUR
T1 - Gene expression analysis of human prostate cell lines with and without tumor metastasis suppressor CD82
AU - Dodla, Pushpaja
AU - Bhoopalan, Vanitha
AU - Khoo, Sok Kean
AU - Miranti, Cindy
AU - Sridhar, Suganthi
N1 - Funding Information:
Funding for this study came from the Grand Valley State University Graduate School Presidential Research Grant awards for Pushpaja Dodla and Vanitha Bhoopalan, University Innovation Grant from West Michigan Science and Technology Initiative (WMSTI), Grand Valley State University Center for Scholarly and Creative Excellence Catalyst Grant, and University of South Florida Start-up Grant for Suganthi Sridhar.
Funding Information:
We would like to thank Dr. Beatrice Knundsen, University of Utah for her generous donation of the normal prostate epithelial cell lines (PrEC-31). We would also like to thank Dr. Kyle Furge and the Microarray core facility at VanAndel Research Institute, Grand Rapids, MI for their help with the?microarrays.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12
Y1 - 2020/12
N2 - Background: Tetraspanin CD82 is a tumor metastasis suppressor that is known to down regulate in various metastatic cancers. However, the exact mechanism by which CD82 prevents cancer metastasis is unclear. This study aims to identify genes that are regulated by CD82 in human prostate cell lines. Methods: We used whole human genome microarray to obtain gene expression profiles in a normal prostate epithelial cell line that expressed CD82 (PrEC-31) and a metastatic prostate cell line that does not express CD82 (PC3). Then, siRNA silencing was used to knock down CD82 expression in PrEC-31 while CD82 was re-expressed in PC3 to acquire differentially-expressed genes in the respective cell line. Results: Differentially-expressed genes with a P < 0.05 were identified in 3 data sets: PrEC-31 (+CD82) vs PrEC-31(−CD82), PC3–57 (+CD82) vs. PC3-5 V (−CD82), and PC3–29 (+CD82) vs. PC3-5 V (−CD82). Top 25 gene lists did not show overlap within the data sets, except (CALB1) the calcium binding protein calbindin 1 which was significantly up-regulated (2.8 log fold change) in PrEC-31 and PC3–29 cells that expressed CD82. Other most significantly up-regulated genes included serine peptidase inhibitor kazal type 1 (SPINK1) and polypeptide N-acetyl galactosaminyl transferase 14 (GALNT14) and most down-regulated genes included C-X-C motif chemokine ligand 14 (CXCL14), urotensin 2 (UTS2D), and fibroblast growth factor 13 (FGF13). Pathways related with cell proliferation and angiogenesis, migration and invasion, cell death, cell cycle, signal transduction, and metabolism were highly enriched in cells that lack CD82 expression. Expression of two mutually inclusive genes in top 100 gene lists of all data sets, runt-related transcription factor (RUNX3) and trefoil factor 3 (TFF3), could be validated with qRT-PCR. Conclusion: Identification of genes and pathways regulated by CD82 in this study may provide additional insights into the role that CD82 plays in prostate tumor progression and metastasis, as well as identify potential targets for therapeutic intervention.
AB - Background: Tetraspanin CD82 is a tumor metastasis suppressor that is known to down regulate in various metastatic cancers. However, the exact mechanism by which CD82 prevents cancer metastasis is unclear. This study aims to identify genes that are regulated by CD82 in human prostate cell lines. Methods: We used whole human genome microarray to obtain gene expression profiles in a normal prostate epithelial cell line that expressed CD82 (PrEC-31) and a metastatic prostate cell line that does not express CD82 (PC3). Then, siRNA silencing was used to knock down CD82 expression in PrEC-31 while CD82 was re-expressed in PC3 to acquire differentially-expressed genes in the respective cell line. Results: Differentially-expressed genes with a P < 0.05 were identified in 3 data sets: PrEC-31 (+CD82) vs PrEC-31(−CD82), PC3–57 (+CD82) vs. PC3-5 V (−CD82), and PC3–29 (+CD82) vs. PC3-5 V (−CD82). Top 25 gene lists did not show overlap within the data sets, except (CALB1) the calcium binding protein calbindin 1 which was significantly up-regulated (2.8 log fold change) in PrEC-31 and PC3–29 cells that expressed CD82. Other most significantly up-regulated genes included serine peptidase inhibitor kazal type 1 (SPINK1) and polypeptide N-acetyl galactosaminyl transferase 14 (GALNT14) and most down-regulated genes included C-X-C motif chemokine ligand 14 (CXCL14), urotensin 2 (UTS2D), and fibroblast growth factor 13 (FGF13). Pathways related with cell proliferation and angiogenesis, migration and invasion, cell death, cell cycle, signal transduction, and metabolism were highly enriched in cells that lack CD82 expression. Expression of two mutually inclusive genes in top 100 gene lists of all data sets, runt-related transcription factor (RUNX3) and trefoil factor 3 (TFF3), could be validated with qRT-PCR. Conclusion: Identification of genes and pathways regulated by CD82 in this study may provide additional insights into the role that CD82 plays in prostate tumor progression and metastasis, as well as identify potential targets for therapeutic intervention.
KW - CD82
KW - Gene expression
KW - KAI1
KW - Metastasis tumor suppressor
KW - Microarray
KW - Prostate cancer
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U2 - 10.1186/s12885-020-07675-7
DO - 10.1186/s12885-020-07675-7
M3 - Article
C2 - 33298014
AN - SCOPUS:85097314073
VL - 20
JO - BMC Cancer
JF - BMC Cancer
SN - 1471-2407
IS - 1
M1 - 1211
ER -