TY - JOUR
T1 - Gene expression profiling identifies potential molecular markers of papillary thyroid carcinoma
AU - Reyes, Ismael
AU - Reyes, Niradiz
AU - Suriano, Robert
AU - Iacob, Codrin
AU - Suslina, Nina
AU - Policastro, Anthony
AU - Moscatello, Augustine
AU - Schantz, Stimson
AU - Tiwari, Raj K.
AU - Geliebter, Jan
N1 - Publisher Copyright:
© 2019-IOS Press and the authors. All rights reserved.
PY - 2019
Y1 - 2019
N2 - BACKGROUND: Thyroid cancer is the most common endocrine malignancy worldwide, with the predominant form papillary thyroid carcinoma (PTC) representing approximately 80% of cases. OBJECTIVE: This study was addressed to identify potential genes and pathways involved in the pathogenesis of PTC and potential novel biomarkers for this disease. METHODS: Gene expression profiling was carried out by DNA microarray technology. Validation of microarray data by qRT-PCR, western blot, and enzyme linked immunosorbent assay was also performed in a selected set of genes and gene products, with the potential to be used as diagnostic or prognostic biomarkers, such as those associated with cell adhesion, extracellular matrix (ECM) remodeling and immune/inflammatory response. RESULTS: In this study we found that upregulation of extracellular activities, such as proteoglycans, ECM-receptor interaction, and cell adhesion molecules, were the most prominent feature of PTC. Significantly over-expressed genes included SDC1 (syndecan 1), SDC4 (syndecan 4), KLK7 (kallikrein-related peptidase 7), KLK10 (kallikrein-related peptidase 10), SLPI (secretory leukocyte peptidase inhibitor), GDF15 (growth/differentiation factor-15), ALOX5 (arachidonate 5-lipoxygenase), SFRP2 (secreted Frizzled-related protein 2), among others. Further, elevated KLK10 levels were detected in patients with PTC. Many of these genes belong to KEGG pathway "Proteoglycans in cancer". CONCLUSIONS: Using DNA microarray analysis allowed the identification of genes and pathways with known important roles in malignant transformation, and also the discovery of novel genes that may be potential biomarkers for PTC.
AB - BACKGROUND: Thyroid cancer is the most common endocrine malignancy worldwide, with the predominant form papillary thyroid carcinoma (PTC) representing approximately 80% of cases. OBJECTIVE: This study was addressed to identify potential genes and pathways involved in the pathogenesis of PTC and potential novel biomarkers for this disease. METHODS: Gene expression profiling was carried out by DNA microarray technology. Validation of microarray data by qRT-PCR, western blot, and enzyme linked immunosorbent assay was also performed in a selected set of genes and gene products, with the potential to be used as diagnostic or prognostic biomarkers, such as those associated with cell adhesion, extracellular matrix (ECM) remodeling and immune/inflammatory response. RESULTS: In this study we found that upregulation of extracellular activities, such as proteoglycans, ECM-receptor interaction, and cell adhesion molecules, were the most prominent feature of PTC. Significantly over-expressed genes included SDC1 (syndecan 1), SDC4 (syndecan 4), KLK7 (kallikrein-related peptidase 7), KLK10 (kallikrein-related peptidase 10), SLPI (secretory leukocyte peptidase inhibitor), GDF15 (growth/differentiation factor-15), ALOX5 (arachidonate 5-lipoxygenase), SFRP2 (secreted Frizzled-related protein 2), among others. Further, elevated KLK10 levels were detected in patients with PTC. Many of these genes belong to KEGG pathway "Proteoglycans in cancer". CONCLUSIONS: Using DNA microarray analysis allowed the identification of genes and pathways with known important roles in malignant transformation, and also the discovery of novel genes that may be potential biomarkers for PTC.
KW - Biological Markers
KW - gene expression
KW - kallikrein-related peptidase
KW - thyroid carcinoma
UR - http://www.scopus.com/inward/record.url?scp=85062181110&partnerID=8YFLogxK
U2 - 10.3233/CBM-181758
DO - 10.3233/CBM-181758
M3 - Article
C2 - 30614796
AN - SCOPUS:85062181110
SN - 1574-0153
VL - 24
SP - 71
EP - 83
JO - Cancer Biomarkers
JF - Cancer Biomarkers
IS - 1
ER -