Researchers develop new computational tool to interpret clinical significance of cancer mutations

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Researchers at the Philadelphia Children’s Hospital (CHOP) have developed a new tool to help researchers interpret the clinical significance of mutations in cancer. Tool, known as CancerVar, includes a machine learning process to go beyond just detecting cancer mutations and interpreting the potential meaning of those mutations in relation to cancer detection, prognosis, and purpose. A paper describing CancerVar was published today Scientific Progress.

“CancerVar will not replace human translation into another hospital settingbut it will reduce the workload of laboratory technicians in disseminating the differences identified by designing and compiling clinical reports in clinical practice, ”said Kai Wang, Ph.D., Professor of Pathology and Laboratory Medicine at CHOP and senior author. Of paper. “CancerVar documents also suitable for a variety of types hospital evidence including drug information, literature, and methods for somatic replacement in detail. By providing accurate, reproducible, and efficient output to translate somatic differences, CancerVar can help researchers and clinicians prioritize stress replacement. “

Maryn M. Live, Professor of Dermatology and Dermatology and historian. “CancerVar provides strength tool which controls these two important steps. The clinical implementation of this tool will improve test delivery time and performance accuracy, making the tests more effective and affordable for all pediatric cancer patients. ”

Improving the next generation of neurons (NGS) with the right treatment has led to the identification of millions of variants of somatic cancer. To further understand whether these mutations are related to or impact the clinical process, researchers have established numerous data that compute these differences. However, these data do not provide accurate interpretations of somatic differences, so in 2017, the Association of Molecular Pathology (AMP), the American Society of Clinical Oncology (ASCO), and the College of American Pathologists (CAP) collaborated. and recommending translations and translation guidelines. , reporting, and quantifying somatic differences.

However even with these guidelines, the AMP / ASCO / CAP distribution system does not specify how these standards are implemented, so different knowledge sources offer different results. To address this problem, CHOP researchers, including CHOP data scientist and lead author Yunyun Zhou, Ph.D., have developed CancerVar, an advanced somatic. diversity translation tool using command line software called Python with accompanying web server. With a reliable web server, CancerVar includes clinical evidence for 13 million somatic cancer variants out of 1,911 cancer the genes of the census were extracted by existing studies and data sets.

In addition to including millions replacementwhether important knowledge or not, tools are used deepen learning to improve the clinical interpretation of those mutations. Users can ask clinical interpretations for variables using data such as chromosome position or protein mutation and adjust the accuracy of measuring different types of features, based on consideration. before education or more specific user specifications. The CancerVar web server generates automated translations, such as whether the replacement is appropriate for diagnosis or prognosis or to ongoing clinical trials.

“This tool demonstrates how we can use computational tools to manage human-generated values, and how machine learning can guide decisions,” Wang said. “Future research should investigate the application of this system to other infectious disease sites as well.”

AMP provides a collaborative guide to standardize interpretation and report variability in cancer

Learn more:
Quan Li et al, CancerVar: An artificial intelligence-based platform for the clinical interpretation of mutations in cancer, Scientific Progress (2022). DOI: 10.1126 / sciadv.abj1624.

hint: Researchers have developed a new mathematical tool to interpret the clinical significance of mutations (2022, May 6) restored May 6, 2022 from -cancer-mutations.html

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