Diagnostic and prognostic gene expression signatures in 177 soft tissue sarcomas: hypoxia-induced transcription profile signifies metastatic potential.
BACKGROUND
Soft tissue sarcoma (STS) diagnosis is challenging because of a multitude of histopathological subtypes, different genetic characteristics, and frequent intratumoral pleomorphism. One-third of STS metastasize and current risk-stratification is suboptimal, therefore, novel diagnostic and prognostic markers would be clinically valuable. We assessed the diagnostic and prognostic value of array-based gene expression profiles using 27 k cDNA microarrays in 177, mainly high-grade, STS of 13 histopathological subtypes.


RESULTS
Unsupervised analysis resulted in two major clusters--one mainly containing STS characterized by type-specific genetic alterations and the other with a predominance of genetically complex and pleomorphic STS. Synovial sarcomas, myxoid/round-cell liposarcomas, and gastrointestinal stromal tumors clustered tightly within the former cluster and discriminatory signatures for these were characterized by developmental genes from the EGFR, FGFR, Wnt, Notch, Hedgehog, RAR and KIT signaling pathways. The more pleomorphic STS subtypes, e.g. leiomyosarcoma, malignant fibrous histiocytoma/undifferentiated pleomorphic sarcoma and dedifferentiated/pleomorphic liposarcoma, were part of the latter cluster and were characterized by relatively heterogeneous profiles, although subclusters herein were identified. A prognostic signature partly characterized by hypoxia-related genes was identified among 89 genetically complex pleomorphic primary STS and could, in a multivariate analysis including established prognostic markers, independently predict the risk of metastasis with a hazard ratio of 2.2 (P = 0.04).


CONCLUSIONS
Diagnostic gene expression profiles linking signaling pathways to the different STS subtypes were demonstrated and a hypoxia-induced metastatic profile was identified in the pleomorphic, high-grade STS. These findings verify diagnostic utility and application of expression data for improved selection of high-risk STS patients.
Francis
Princy
P
Department of Oncology, Institute of Clinical Sciences, Lund University, Lund, Sweden. princy.francis@med.lu.se
Namløs
Heidi Maria
HM
Müller
Christoph
C
Edén
Patrik
P
Fernebro
Josefin
J
Berner
Jeanne-Marie
JM
Bjerkehagen
Bodil
B
Akerman
Måns
M
Bendahl
Pär-Ola
PO
Isinger
Anna
A
Rydholm
Anders
A
Myklebost
Ola
O
Nilbert
Mef
M
D015687:Cell Hypoxia / Q000235:genetics*; D016000:Cluster Analysis; D018572:Disease-Free Survival; D046152:Gastrointestinal Stromal Tumors / Q000235:genetics / Q000473:pathology; D020869:Gene Expression Profiling; D051677:Histiocytoma, Malignant Fibrous / Q000235:genetics / Q000473:pathology; D006801:Humans; D007890:Leiomyosarcoma / Q000235:genetics / Q000473:pathology; D018208:Liposarcoma, Myxoid / Q000235:genetics / Q000473:pathology; D025202:Molecular Diagnostic Techniques; D009362:Neoplasm Metastasis / Q000175:diagnosis*; D018317:Nerve Sheath Neoplasms / Q000235:genetics / Q000473:pathology; D011379:Prognosis; D012509:Sarcoma / Q000175:diagnosis* / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D013584:Sarcoma, Synovial / Q000235:genetics / Q000473:pathology; D046888:Tissue Array Analysis / Q000379:methods*