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Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas using NGS and machine learning

Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas using NGS and machine learning
Correlation matrix with numerous significant positive correlations. Credit: Oncotarget (2024). DOI: 10.18632/oncotarget.28512

A new research paper titled "Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis" has been published in Oncotarget.

About 7% of all cancer deaths are caused by (PCa). PCa is known for its lowest survival rates among all oncological diseases and heterogenic molecular profile. Enormous amount of genetic changes, including , exceeds the limits of routine clinical genetic laboratory tests and further stagnates the development of personalized treatments.

In this new study, researchers aimed to build a mutational landscape of PCa in the Russian population based on full exome (NGS) of the limited group of patients.

"Applying a machine learning model on full exome individual data, we received personalized recommendations for targeted treatment options for each clinical case and summarized them in the unique therapeutic landscape," the researchers explain.

More information: P.A. Shatalov et al, Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis, Oncotarget (2024). DOI: 10.18632/oncotarget.28512

Journal information: Oncotarget
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Citation: Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas using NGS and machine learning (2024, February 14) retrieved 15 April 2024 from https://medicalxpress.com/news/2024-02-genetic-therapeutic-landscapes-cohort-pancreatic.html
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