Gene panel test empowers exceptionally exact diagnosis of liposarcomas

Gene panel test empowers exceptionally exact diagnosis of liposarcomas


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  • Source: Elsevier

  • Date: 05 Feb,2021

Scientists have leveraged the latest advances in RNA technology and machine learning methods to develop a gene panel evaluation which allows for highly accurate diagnosis of the most frequent kinds of liposarcoma. The new assay is described in The Journal of Molecular Diagnosis, published by Elsevier.

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. 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.”

Torsten Owen Nielsen, MD, PhD, Lead Author, Genetic Pathology Evaluation Centre, Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada

Among the present recommended diagnostic tests for liposarcomas, immunohistochemistry (IHC) is wrong and difficult to interpret, and fluorescence in situ hybridization (FISH) is relatively expensive, in addition to labour – and equipment-intensive. In this study, researchers explored whether NanoString technology, perfect for assessing even poor-quality RNA, could allow for more rapid and cost effective diagnosis of liposarcomas through gene expression.

Probes for these genes were designed by NanoString bioinformatics and operate on a set of”training samples” that comprised lipomas and liposarcomas.

A machine learning model was developed to determine the probability that a given sample was positive for liposarcoma and was subsequently implemented to 45 retrospective cases to determine bounds for positive and negative forecasts. The test was subsequently applied in a real-world clinical setting. A molecular technologist with no understanding of the clinical, histologic, IHC, or FISH information about the cases was asked to identify each sample as liposarcoma or not liposarcoma in the NanoString evaluation results. The very same samples were analyzed by specialist pathologists using standard testing.

The retrospective and prospective cases probed from the NanoString assay had a 93 percent success rate and agreed with regular tests 97.8 percent of the time. NanoString costs amounted to US$270 per instance, factoring in reagents, labour, and equipment maintenance.

Advances in biotechnology have shown great promise in other cancers like breast cancer. “We applied these new technologies to improve patient care in areas where existing diagnostic methods were inaccurate, slow, or expensive and saw substantial improvements. There is absolutely no patent on this test; anybody can use the method we describe, and we are pleased to help others get set up to run it in their own institution,” says Dr. Nielsen.

First writer Xiu Qing (Jenny) Wang, a fourth year medical student at the University of British Columbia, adds that accurate and fast diagnosis can be critical for patients that are dealing with what are often difficult and quite large tumors. “I am proud to be a part of a team that has made significant progress in bringing this test closer to clinical reality.”

This group previously published a NanoString-based assay for sarcomas bearing diagnostic fusion oncogenes, which is now in clinical use. However, the most frequent type of liposarcoma carries a different type of mutation (gene amplifications) and so was not covered. Therefore, the present study not only expands the kinds of sarcoma that can be diagnosed accurately with NanoString-based diagnostics, but also shows how a different category of mutation could be detected. This strategy can help develop diagnostics for different types of cancer.

Journal reference:

Wang, X.Q., et al. (2020) A Rapid and Cost-Effective Gene Expression Assay for the Diagnosis of Well-Differentiated and Dedifferentiated Liposarcomas. Journal of Molecular Diagnostics.

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