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NanoString Technology Modernizes Liposarcoma Diagnostics

By LabMedica International staff writers
Posted on 15 Feb 2021
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Image: Atypical lipomatous tumor/well-differentiated liposarcoma (left-hand); lipoma (right-hand) (Photo courtesy of Dr.Tony Ng, The University of British Columbia)
Image: Atypical lipomatous tumor/well-differentiated liposarcoma (left-hand); lipoma (right-hand) (Photo courtesy of Dr.Tony Ng, The University of British Columbia)
A recently published study showed that a newer NanoString-based method could allow for more rapid and cost-efficient diagnosis of liposarcomas than the commonly used fluorescence in situ hybridization (FISH) method.

Liposarcoma is a rare type of cancer that arises in fat cells in soft tissue, such as that inside the thigh. It is typically a large, bulky tumor, and tends to have multiple smaller satellites that extend beyond the main confines of the growth. Several types of liposarcoma exist. While some grow slowly with the cells remaining localized to one area of the body, other types grow very quickly and may metastasize.

In addition to FISH, which is a relatively expensive as well as labor- and equipment-intensive technology, immunohistochemistry (IHC) is often used to diagnose liposarcoma. However, IHC is felt to be inaccurate and hard to interpret.

To modernize the diagnosis of liposarcoma, investigators at the University of British Columbia (Vancouver, Canada) examined whether the newer NanoString-based technology (Seattle, WA, USA) could allow for more rapid and cost-efficient diagnosis of liposarcomas on standard formalin-fixed tissues through gene expression. For this study, they used large-scale transcriptome data from The Cancer Genome Atlas. The Cancer Genome Atlas is a project, begun in 2005, to catalog genetic mutations responsible for cancer, using genome sequencing and bioinformatics. The Cancer Genome Atlas applies high-throughput genome analysis techniques to improve diagnosis, treatment, and prevention of cancer through a better understanding of the genetic basis of this disease.

Data extracted from The Cancer Genome Atlas identified 20 genes, most from the 12q13-15 amplicon, that distinguished de-differentiated liposarcoma from other sarcomas and could be measured within a single NanoString assay. A machine learning model was subsequently developed to determine the probability that a given sample was positive for liposarcoma and was then applied to 45 retrospective cases to determine boundaries for positive and negative predictions. The effectiveness of the assay was validated on an independent set of 100 sarcoma samples (including 40 incident prospective cases), where histologic examination was considered insufficient for clinical diagnosis.

Results revealed that the NanoString assay had a 93% technical success rate, and an accuracy of 97.8% versus the FISH gold standard. Furthermore, results from the NanoString assay were available in 36 hours, whereas it required from one to two weeks to obtain FISH results.

"Liposarcomas are a type of malignant cancer that is difficult to diagnose because, even under a microscope, it is hard to differentiate liposarcomas from benign tumors or other types of cancer that need different treatments," said senior author Dr. Torsten Owen Nielsen, clinician-scientist in the department of pathology and laboratory medicine at the University of British Columbia. "Many liposarcomas look like their benign and relatively common counterparts, lipomas. Diagnostic delay and uncertainty cause severe stress for patients, and misdiagnosis can have many consequences including delayed or inadequate treatment or unnecessary surgical procedures and long-term postoperative follow up."

The liposarcoma-Nanostring study was published in the December 23, 2020 online edition of The Journal of Molecular Diagnosis.

Related Links:
University of British Columbia

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