Liposarcoma

Liposarcoma is a type of cancer that occurs in fat cells in the body, most often in the muscles of the limbs or the abdomen. Liposarcoma is a rare type of cancer that begins in the fat cells. Liposarcoma is considered the most common type of soft tissue sarcoma. However, its molecular mechanism is poorly defined. Computational biology approaches can help to identify genes crucial to the pathogenesis of liposarcoma and to explore their functions, related pathways, and prognostic value.

Computational Material and Methods

• Screen differentially expressed genes (DEGs)
• Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis
• Protein-protein interaction (PPI) networks construction
• Module analysis to identify hub genes from the DEGs
• Distant recurrence-free survival (DRFS) assessment (Cox model analysis)

Liposarcoma Subtypes Profiling

Liposarcoma subtype is an important determinant of local recurrence and metastatic potential. Based on morphology it is often challenging to distinguish between the many different liposarcoma subtypes. We are exploring novel molecular classification approaches to liposarcoma based on genomic profiling. Attributing to our computational biology and bioinformatics backgrounds, we are interested in assisting in the development and implementation of novel bioinformatics approaches to analyze high-dimensional genomic data in a biologically relevant manner. Due to more precise molecular profiling and characterization, liposarcoma subtypes are being discovered. Novel therapeutic targets and prognostic/predictive biomarkers are also being revealed.

Our Technical Advancements

• Conduct microarray analysis to explore genes as potential biomarkers for diagnosis and prognosis.
• Construct gene networks to find hub genes and estimate the prognostic value of those genes.
• Construct gene signatures to search for more valuable prognostic indicators.

AI-Driven Liposarcoma Research

Machine learning on omics data could be a valuable new tool to understand differences between and within entities, to identify novel diagnostic and prognostic markers and therapeutic targets for liposarcoma.

In addition, CD ComputaBio has multiple resources including academic research and preclinical works in the identification of a suitable disease target and its corresponding hit. Contact us for more service details.