Dataset Information

Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines.

ABSTRACT:

Background

Matrix metalloproteinases (MMPs) are involved in the degradation of protein components of the extracellular matrix and thus play an important role in tumor invasion and metastasis. Their expression is related to the progression of gynecological cancers (e.g. endometrial, cervical or ovarian carcinoma). In this study we investigated the expression pattern of the 23 MMPs, currently known in humans, in different gynecological cancer cell lines.

Methods

In total, cell lines from three endometrium carcinomas (Ishikawa, HEC-1-A, AN3 CA), three cervical carcinomas (HeLa, Caski, SiHa), three chorioncarcinomas (JEG, JAR, BeWo), two ovarian cancers (BG-1, OAW-42) and one teratocarcinoma (PA-1) were examined. The expression of MMPs was analyzed by RT-PCR, Western blot and gelatin zymography.

Results

We demonstrated that the cell lines examined can constitutively express a wide variety of MMPs on mRNA and protein level. While MMP-2, -11, -14 and -24 were widely expressed, no expression was seen for MMP-12, -16, -20, -25, -26, -27 in any of the cell lines. A broad range of 16 MMPs could be found in the PA1 cells and thus this cell line could be used as a positive control for general MMP experiments. While the three cervical cancer cell lines expressed 10-14 different MMPs, the median expression in endometrial and choriocarcinoma cells was 7 different enzymes. The two investigated ovarian cancer cell lines showed a distinctive difference in the number of expressed MMPs (2 vs. 10).

Conclusions

Ishikawa, Caski, OAW-42 and BeWo cell lines could be the best choice for all future experiments on MMP regulation and their role in endometrial, cervical, ovarian or choriocarcinoma development, whereas the teratocarcinoma cell line PA1 could be used as a positive control for general MMP experiments.

SUBMITTER: Schropfer A

PROVIDER: S-EPMC2964638 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Publications

Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines.

Schröpfer Andrea A Kammerer Ulrike U Kapp Michaela M Dietl Johannes J Feix Sonja S Anacker Jelena J

BMC cancer 20101013

<h4>Background</h4>Matrix metalloproteinases (MMPs) are involved in the degradation of protein components of the extracellular matrix and thus play an important role in tumor invasion and metastasis. Their expression is related to the progression of gynecological cancers (e.g. endometrial, cervical or ovarian carcinoma). In this study we investigated the expression pattern of the 23 MMPs, currently known in humans, in different gynecological cancer cell lines.<h4>Methods</h4>In total, cell lines ...[more]

PMID: 20942921

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Project description:Matrix metalloproteinases (MMPs) are zinc- and calcium- dependent endopeptidases that play pivotal roles in many biological processes. The expression of several MMPs in the central nervous system (CNS) have been shown to change in response to injury and various neurological/neurodegenerative disorders. While extracellular MMPs degrade the extracellular matrix (ECM) and regulate cell surface receptor signaling, the intracellular functions of MMPs or their roles in CNS disorders is unclear. Around 23 different MMPs are found in the human genome with overlapping function, making analysis of the intracellular role of human MMPs a daunting task. However, the fruit fly Drosophila melanogaster genome encodes only two MMPs: dMMP1 and dMMP2. To better understand the intracellular role of MMPs in the CNS, we expressed Green Fluorescent Protein (GFP)- tagged dMMPs in SH-SY5Y neuroblastoma cells and C6 glioblastoma cell lines. Lipofection of GFP-dMMPs in SH-SY5Y cells enhanced nuclear rupture and reduced cell viability (coupled with increased apoptosis) as compared to GFP alone. In non-liposomal transfection experiments, dMMP1 localizes to both the cytoplasm and the nucleus whereas dMMP2 had predominantly cytoplasmic localization in both neural and glial cell lines. Cytoplasmic localization demonstrated co-localization of dMMPs with cytoskeleton proteins which suggests a possible role of dMMPs in cell morphology. This was further supported by transient dMMP expression experiments that showed that dMMPs significantly increased neurite formation and length in neuronal cell lines. Inhibition of endogenous MMPs decreased neurite formation, length and βIII Tubulin protein levels in differentiated SH-SY5Y cells. Further, transient expression experiments showed similar changes in glial cell morphology, wherein dMMP expression increased glial process formation and process length. Interestingly, C6 cells expressing dMMPs had a glia-like appearance, suggesting MMPs may be involved in intracellular glial differentiation. Inhibition or suppression of endogenous MMPs in C6 cells increased process formation, increased process length, modulated GFAP protein expression, and induced distinct glial-like phenotypes. Taken together, our results strongly support the intracellular role that dMMPs can play in apoptosis, cytoskeleton remodeling, and cell differentiation. Our studies further reinforce the use of Drosophila MMPs to dissect out the precise mechanisms whereby they exert their intracellular roles in CNS disorders.

Project description:BackgroundAlthough metabolism is profoundly altered in human liver cancer, the extent to which experimental models, e.g. cell lines, mimic those alterations is unresolved. Here, we aimed to determine the resemblance of hepatocellular carcinoma (HCC) cell lines to human liver tumours, specifically in the expression of deregulated metabolic targets in clinical tissue samples.MethodsWe compared the overall gene expression profile of poorly-differentiated (HLE, HLF, SNU-449) to well-differentiated (HUH7, HEPG2, HEP3B) HCC cell lines in three publicly available microarray datasets. Three thousand and eighty-five differentially expressed genes in ?2 datasets (P?<?0.05) were used for pathway enrichment and gene ontology (GO) analyses. Further, we compared the topmost gene expression, pathways, and GO from poorly differentiated cell lines to the pattern from four human HCC datasets (623 tumour tissues). In well- versus poorly differentiated cell lines, and in representative models HLE and HUH7 cells, we specifically assessed the expression pattern of 634 consistently deregulated metabolic genes in human HCC. These data were complemented by quantitative PCR, proteomics, metabolomics and assessment of response to thirteen metabolism-targeting compounds in HLE versus HUH7 cells.ResultsWe found that poorly-differentiated HCC cells display upregulated MAPK/RAS/NFkB signaling, focal adhesion, and downregulated complement/coagulation cascade, PPAR-signaling, among pathway alterations seen in clinical tumour datasets. In HLE cells, 148 downregulated metabolic genes in liver tumours also showed low gene/protein expression - notably in fatty acid ?-oxidation (e.g. ACAA1/2, ACADSB, HADH), urea cycle (e.g. CPS1, ARG1, ASL), molecule transport (e.g. SLC2A2, SLC7A1, SLC25A15/20), and amino acid metabolism (e.g. PHGDH, PSAT1, GOT1, GLUD1). In contrast, HUH7 cells showed a higher expression of 98 metabolic targets upregulated in tumours (e.g. HK2, PKM, PSPH, GLUL, ASNS, and fatty acid synthesis enzymes ACLY, FASN). Metabolomics revealed that the genomic portrait of HLE cells co-exist with profound reliance on glutamine to fuel tricarboxylic acid cycle, whereas HUH7 cells use both glucose and glutamine. Targeting glutamine pathway selectively suppressed the proliferation of HLE cells.ConclusionsWe report a yet unappreciated distinct expression pattern of clinically-relevant metabolic genes in HCC cell lines, which could enable the identification and therapeutic targeting of metabolic vulnerabilities at various liver cancer stages.

Dataset Information

Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines.

Background

Methods

Results

Conclusions

Publications

Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines.

Similar Datasets

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