Gene Expression Changes Associated with Dedifferentiation in Liposarcoma Predict Overall Survival.

Nicholas Brian Shannon,Wai Har Ng,Jolene Si Min Wong,Joey Wee-Shan Tan,Gillian Ng,Ying Liu,Josephine Hendrikson,Melissa Ching Ching Teo,Qiu Xuan Tan,Khee Chee Soo,Chin-Ann Johnny Ong,Claramae Shulyn Chia,Grace Hwei Ching Tan

doi:10.3390/cancers13123049

Abstract

Simple SummaryPrevious 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.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.

Highlights

Soft tissue sarcomas (STSs) are a heterogeneous disease that comprise approximately1% of all malignancies [1]
The top 15 differentially expressed genes between well-differentiated liposarcoma (WDLS) and dedifferentiated liposarcoma (DDLS) were selected for further analysis of laser-capture microdissection (LCM)/whole tissue samples
Th top 15 differentially expressed genes between WDLS and DDLS were selected for furth analysis of LCM/whole tissue samples

Summary

Introduction

Soft tissue sarcomas (STSs) are a heterogeneous disease that comprise approximately1% of all malignancies [1]. Systemic treatment choices are increasingly made considering histology and molecular pathways associated with the disease, largely based on the response to different classes of agents. Compared to those of more common tumour types, the molecular data available for sarcomas are limited. In 2010, Barretina et al [2] performed integrative analysis of mutation, copy number, and expression data, but the reported results were largely limited to genomic aberrations in subtypes of STS, with a focus on liposarcoma. A more recent study from the Cancer Genome Atlas Research Network (CGARN) [3] reported a comprehensive integrative analysis of 206 adults with STSs representing six major types, including liposarcoma, for which they identified potential prognostic grouping defined by copy number and methylation changes

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