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Circulating tumor cells mirror bone metastatic phenotype in prostate cancer
A. Josefsson, K. Larsson, M. Månsson, J. Björkman, E. Rohlova, D. Åhs, H. Brisby, JE. Damber, K. Welén,
Language English Country United States
Document type Journal Article
NLK
Free Medical Journals
from 2010
Freely Accessible Journals
from 2010
PubMed Central
from 2010
Europe PubMed Central
from 2010
Open Access Digital Library
from 2010-01-01
- Publication type
- Journal Article MeSH
Circulating tumor cells (CTCs) are promising biomarkers in prostate cancer (PC) because they derive from primary tumor and metastatic tissues. In this study, we used quantitative real-time PCR (qPCR) to compare the expression profiles of 41 PC-related genes between paired CTC and spinal column metastasis samples from 22 PC patients that underwent surgery for spinal cord compression. We observed good concordance between the gene expression profiles in the CTC and metastasis samples in most of the PC patients. Expression of nine genes (AGR2, AKR1C3, AR, CDH1, FOLH1, HER2, KRT19, MDK, and SPINK1) showed a significant correlation between the CTC and metastasis samples. Hierarchical clustering analysis showed a similar grouping of PC patients based on the expression of these nine genes in both CTC and metastasis samples. Our findings demonstrate that CTCs mirror gene expression patterns in tissue metastasis samples from PC patients. Although low detection frequency of certain genes is a limitation in CTCs, our results indicate the potential for CTC phenotyping as a tool to improve individualized therapy in metastatic prostate cancer.
References provided by Crossref.org
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- $a Circulating tumor cells (CTCs) are promising biomarkers in prostate cancer (PC) because they derive from primary tumor and metastatic tissues. In this study, we used quantitative real-time PCR (qPCR) to compare the expression profiles of 41 PC-related genes between paired CTC and spinal column metastasis samples from 22 PC patients that underwent surgery for spinal cord compression. We observed good concordance between the gene expression profiles in the CTC and metastasis samples in most of the PC patients. Expression of nine genes (AGR2, AKR1C3, AR, CDH1, FOLH1, HER2, KRT19, MDK, and SPINK1) showed a significant correlation between the CTC and metastasis samples. Hierarchical clustering analysis showed a similar grouping of PC patients based on the expression of these nine genes in both CTC and metastasis samples. Our findings demonstrate that CTCs mirror gene expression patterns in tissue metastasis samples from PC patients. Although low detection frequency of certain genes is a limitation in CTCs, our results indicate the potential for CTC phenotyping as a tool to improve individualized therapy in metastatic prostate cancer.
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