Metastatic potential is determined early in synovial sarcoma development and reflected by tumor molecular features [aCGH]

Synovial sarcoma (SynSa) is an aggressive mesenchymal tumor, comprising approximately 10% of all soft tissue sarcomas. Over half of SynSa patients develop metastasis or local recurrence, but the underlying molecular mechanisms of the aggressive clinical behavior remain poorly characterized. Sixty four frozen tumor specimens from 54 SynSa patients were subjected to array comparative genomic hybridization (aCGH) and gene expression profiling. The examined set of tumor specimens included 16 primary tumors from untreated patients who did not develop metastasis/local recurrence (SynSa1 group), 26 primary tumors from untreated patients who developed metastases or local recurrence during follow-up (SynSa2 group), and 22 metachronous metastatic/recurrent SynSa tumors (SynSa3 group). AURKA and KIF18A, which play important roles in various mitotic events, were the two most up-regulated genes in SynSa2 and SynSa3 groups compared to the SynSa1 group. Expression profiles of SynSa2 and SynSa3 tumors did not show any significant differences. Analysis of genomic index (GI) based on aCGH profiles demonstrated that the SynSa1 group consisted of tumors with significantly less complex genomes compared to SynSa2 and SynSa3 groups. There was no significant difference in genome complexity between SynSa2 and SynSa3 tumors. Primary SynSa tumors from patients who develop metastases or local recurrence share common molecular features with metastatic/recurrent tumors. Presented data suggest that the aggressive clinical SynSa behavior is determined early in tumorigenesis and might be related to impaired regulation of mitotic mechanisms. Introduction: Synovial sarcoma (SynSa) is an aggressive mesenchymal tumor, comprising approximately 10% of all soft tissue sarcomas. Over half of SynSa patients develop metastasis or local recurrence, but the underlying molecular mechanisms of the aggressive clinical behavior remain poorly characterized. Materials and methods: Sixty four frozen tumor specimens from 54 SynSa patients were subjected to array comparative genomic hybridization (aCGH) and gene expression profiling. The examined set of tumor specimens included 16 primary tumors from untreated patients who did not develop metastasis/local recurrence (SynSa1 group), 26 primary tumors from untreated patients who developed metastases or local recurrence during follow-up (SynSa2 group), and 22 metachronous metastatic/recurrent SynSa tumors (SynSa3 group). Results: AURKA and KIF18A, which play important roles in various mitotic events, were the two most up-regulated genes in SynSa2 and SynSa3 groups compared to the SynSa1 group. Expression profiles of SynSa2 and SynSa3 tumors did not show any significant differences. Analysis of genomic index (GI) based on aCGH profiles demonstrated that the SynSa1 group consisted of tumors with significantly less complex genomes compared to SynSa2 and SynSa3 groups. There was no significant difference in genome complexity between SynSa2 and SynSa3 tumors. Conclusions: Primary SynSa tumors from patients who develop metastases or local recurrence share common molecular features with metastatic/recurrent tumors. Presented data suggest that the aggressive clinical SynSa behavior is determined early in tumorigenesis and might be related to impaired regulation of mitotic mechanisms.

Dataset features

Information

Specifications

Application:	aCGH data analysis
Number of samples:	61
Release date:	Jul 31 2014
Last update date:	Jul 31 2014
Access:	Public
Diseases:	Brain Neoplasms, Neoplasms, Sarcoma, Sarcoma, Synovial
Dataset link	Metastatic potential is determined early in synovial sarcoma development and reflected by tumor molecular features [aCGH]

Experimental Protocol

Genomic DNA was extracted from the frozen tumor specimens using High Pure PCR Template Preparation Kit (Roche). DNA of sufficient quality was obtained from 61 tumor specimens. Agilent SurePrint G3 Human CGH 4x180K array

Repositories

GEO

GSE54183

ArrayExpress

E-GEOD-54183

BioProject

PRJNA235617

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Contact

Joanna Przybyl