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Gene Expression Changes Associated with Dedifferentiation in Liposarcoma Predict Overall Survival

SIMPLE SUMMARY: Previous studies have performed integrative analyses of genomic aberrations in soft tissue sarcomas. Utilising clinical information, groups have proposed nomograms for prediction of survival and recurrence in retroperitoneal sarcomas. Expanding on clinical nomogram prediction models...

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Detalles Bibliográficos
Autores principales: Shannon, Nicholas Brian, Tan, Qiu Xuan, Tan, Joey Wee-Shan, Hendrikson, Josephine, Ng, Wai Har, Ng, Gillian, Liu, Ying, Tan, Grace Hwei Ching, Wong, Jolene Si Min, Soo, Khee Chee, Teo, Melissa Ching Ching, Chia, Claramae Shulyn, Ong, Chin-Ann Johnny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235385/
https://www.ncbi.nlm.nih.gov/pubmed/34207401
http://dx.doi.org/10.3390/cancers13123049
Descripción
Sumario:SIMPLE SUMMARY: Previous studies have performed integrative analyses of genomic aberrations in soft tissue sarcomas. Utilising clinical information, groups have proposed nomograms for prediction of survival and recurrence in retroperitoneal sarcomas. Expanding on clinical nomogram prediction models with molecular classification of tumours may allow us to further identify clinical phenotypes within this heterogeneous group. We showed that a five-gene molecular prognostic panel can provide additional prognostic information in patients with retroperitoneal DDLS, independent of clinical features. A combined clinical and molecular prediction model may offer the best way to prognosticate patients for patient counselling and therapeutic decision making. ABSTRACT: Up to 10% of well-differentiated liposarcoma (WDLS) progress to dedifferentiated liposarcoma (DDLS). We aimed to identify gene expression changes associated with dedifferentiation and whether these were informative of tumour biology of DDLS. We analysed datasets from the Gene Expression Omnibus (GEO, ID = GSE30929) database to identify differentially expressed genes between WDLS (n = 52) and DDLS (n = 39). We validated the signature on whole and laser-capture microdissected samples from patients with tumours consisting of mixed WDLS and DDLS components. A subset of this signature was applied to an independent dataset from The Cancer Genome Atlas (TCGA, n = 58 DDLS) database to segregate samples based on gene expression and compared for recurrence and overall survival (OS). A 15-gene signature consisting of genes with increased expression in DDLS compared to WDLS was generated. This signature segregated WDLS and DDLS samples from patients with mixed component tumours and across multiple recurrences. A further subset of this signature, consisting of five genes (AQP7, ACACB, FZD4, GPD1, LEP), segregated DDLS in a TCGA cohort with a significant difference in OS (p = 0.019) and recurrence-free survival (RFS) (p = 0.061). The five-gene model stratified DDLS into prognostic groups and outperformed clinical factors in existing models in retroperitoneal DDLS.