Mechanisms underlying the transformation between low-grade well-differentiated liposarcoma (WDLPS) and malignant dedifferentiated liposarcoma (DDLPS) Well-differentiated liposarcoma (WDLPS) is a low grade, locally aggressive tumour, but can transform into dedifferentiated liposarcoma (DDLPS), a more aggressive one. WDLPS in the retroperitoneum and abdomen has a significantly higher risk of dedifferentiation than those that arise in the limbs. However, the mechanism of dedifferentiation and the reason for anatomical predilection remain unclear. By alignment and bioinformatic analysis of whole-exon sequencing (WES) and RNA sequencing (RNA-seq) from whole blood/normal fat tissue, and tumour samples from the same patient, we intend to identify the genes that are responsible for dedifferentiation, their relative expressions and their roles in the function and survival of liposarcoma cells, and consequently, we hope to identify potential therapeutic targets for liposarcoma treatment. We plan to sequence DNA and RNA samples from up to 50 patients. Currently, we have sequenced DNA of 12 tumour samples and 8 blood samples. Bioinformatics analysis is being performed for the sequencing data.

Principal investigator

Jun Lu jun.lu@research.uwa.edu.au
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Area of science

Health, Oncology

Systems used


Applications used

Nimbus Application
Partner Institution: The University of Western Australia| Project Code: c2111e08797544ec9cdd4f0a72602462

The Challenge

We are aiming at identifying copy number variants (CNVs) and single-nucleotide variants (SNVs) that are responsible for the dedifferentiation of WDLPS via bioinformatics analysis.

The Solution

We are using GATK, GISTIC2.0 and R packages to analyse our sequencing data and DDLPS data from TCGA database.

The Outcome

We have finished CNV calling for our sequencing data by running analysis on Nimbus.