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A tartalmat a Oncotarget Podcast biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Oncotarget Podcast vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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Genetic and Therapeutic Landscapes in Cohort of Pancreatic Cancer Using NGS and Machine Learning

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Manage episode 400968863 series 1754503
A tartalmat a Oncotarget Podcast biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Oncotarget Podcast vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
BUFFALO, NY- February 14, 2024 – A new #research paper was #published in Oncotarget's Volume 15 on February 5, 2024, entitled, “Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis.” About 7% of all cancer deaths are caused by pancreatic cancer (PCa). PCa is known for its lowest survival rates among all oncological diseases and heterogenic molecular profile. Enormous amount of genetic changes, including somatic mutations, exceeds the limits of routine clinical genetic laboratory tests and further stagnates the development of personalized treatments. In this new study, researchers P.A. Shatalov, N.A. Falaleeva, E.A. Bykova, D.O. Korostin, V.A. Belova, A.A. Zabolotneva, A.P. Shinkarkina, A. Yu Gorbachev, M.B. Potievskiy, V.S. Surkova, Zh V. Khailova, N.A. Kulemin, Denis Baranovskii, A.A. Kostin, A.D. Kaprin, and P.V. Shegai from the Ministry of Health of the Russian Federation, Pirogov Russian National Research Medical University, Federal Medical-Biological Agency, Moscow, and the Peoples Friendship University of Russia (RUDN University) aimed to build a mutational landscape of PCa in the Russian population based on full exome next-generation sequencing (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.” DOI - https://doi.org/10.18632/oncotarget.28512 Correspondence to - Denis Baranovskii - doc.baranovsky@gmail.com Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28512 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, pancreatic cancer, tumor mutation burden, somatic mutations, artificial intelligence, machine learning About Oncotarget Oncotarget (a primarily oncology-focused, peer-reviewed, open access journal) aims to maximize research impact through insightful peer-review; eliminate borders between specialties by linking different fields of oncology, cancer research and biomedical sciences; and foster application of basic and clinical science. To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh Media Contact MEDIA@IMPACTJOURNALS.COM 18009220957
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454 epizódok

Artwork
iconMegosztás
 
Manage episode 400968863 series 1754503
A tartalmat a Oncotarget Podcast biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Oncotarget Podcast vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
BUFFALO, NY- February 14, 2024 – A new #research paper was #published in Oncotarget's Volume 15 on February 5, 2024, entitled, “Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis.” About 7% of all cancer deaths are caused by pancreatic cancer (PCa). PCa is known for its lowest survival rates among all oncological diseases and heterogenic molecular profile. Enormous amount of genetic changes, including somatic mutations, exceeds the limits of routine clinical genetic laboratory tests and further stagnates the development of personalized treatments. In this new study, researchers P.A. Shatalov, N.A. Falaleeva, E.A. Bykova, D.O. Korostin, V.A. Belova, A.A. Zabolotneva, A.P. Shinkarkina, A. Yu Gorbachev, M.B. Potievskiy, V.S. Surkova, Zh V. Khailova, N.A. Kulemin, Denis Baranovskii, A.A. Kostin, A.D. Kaprin, and P.V. Shegai from the Ministry of Health of the Russian Federation, Pirogov Russian National Research Medical University, Federal Medical-Biological Agency, Moscow, and the Peoples Friendship University of Russia (RUDN University) aimed to build a mutational landscape of PCa in the Russian population based on full exome next-generation sequencing (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.” DOI - https://doi.org/10.18632/oncotarget.28512 Correspondence to - Denis Baranovskii - doc.baranovsky@gmail.com Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28512 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, pancreatic cancer, tumor mutation burden, somatic mutations, artificial intelligence, machine learning About Oncotarget Oncotarget (a primarily oncology-focused, peer-reviewed, open access journal) aims to maximize research impact through insightful peer-review; eliminate borders between specialties by linking different fields of oncology, cancer research and biomedical sciences; and foster application of basic and clinical science. To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh Media Contact MEDIA@IMPACTJOURNALS.COM 18009220957
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