Transcriptomics

Dataset Information

0

Gene expression profiling of canine osteosarcoma reveals genes associated with short and long survival times


ABSTRACT: Osteosarcoma (OS) accounts for approximately 80% of all malignant bone tumors in the dog. Tumors are highly metastatic and long-term survival is poor. This study aims to investigate the prognosis associated gene expression profile in primary canine OS. Canine specific cDNA microarray representing 20,313 genes was used to analyze expression profiles in a panel of thirty-two primary osteosarcoma to identify genes associated with survival. The 32 tumours were classified into two groups of prognosis based on survival time (ST). They were defined as short survivors (dogs with poor prognosis that survived less than 6 months) and long survivors (dogs with better prognosis that survived longer than 6 months). Fifty-one genes were found to be differentially expressed, with common up regulation of these genes in the short survivors. The overexpression of these genes in short survivors suggests a possible role for increased proliferation, drug resistance or metastasis. Several deregulated pathways were identified in the present study includes Wnt signaling, Integrin signaling and Chemokine / cytokine signaling which were comparable to the pathway analysis conducted on human OS, adding more value for the dog as an excellent model to study human OS. Our results suggest that a molecular-based method for discrimination of outcome for short survivors and long survivors of canine OS may be useful for future prognostic stratification of dogs at initial diagnosis, where genes and pathways associated with cell cycle/ proliferation, drug resistance and metastasis could be potential targets for therapy that may not just be beneficial for dogs but also for humans.

ORGANISM(S): Canis lupus familiaris

PROVIDER: GSE14033 | GEO | 2009/09/14

SECONDARY ACCESSION(S): PRJNA112459

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2013-11-12 | GSE51976 | GEO
2013-11-12 | GSE51973 | GEO
2013-11-12 | GSE51734 | GEO
2013-11-12 | E-GEOD-51734 | biostudies-arrayexpress
2013-11-12 | E-GEOD-51973 | biostudies-arrayexpress
2013-11-12 | E-GEOD-51976 | biostudies-arrayexpress
2024-04-03 | GSE247355 | GEO
2020-10-22 | GSE155646 | GEO
2010-05-08 | E-GEOD-16087 | biostudies-arrayexpress
2021-09-03 | GSE183189 | GEO