Oncotarget cover image

Oncotarget

Unlocking the Potential of Molecular-Driven Stratification of Osteosarcoma

Mar 20, 2023
Discover the complexity of genetic landscape and microenvironment in Osteosarcoma tumors through unsupervised machine learning algorithms. Explore stratification based on gene expression modules enriched for immune microenvironment and tumor phenotypic traits for improved treatment strategies.
02:38

Podcast summary created with Snipd AI

Quick takeaways

  • Challenges in stratifying osteosarcoma patients stem from genetic complexity, microenvironment heterogeneity, and tumor plasticity.
  • Advancements in using machine learning algorithms for gene expression profiling offer new insights for osteosarcoma classification.

Deep dives

Challenges in Osteosarcoma Treatment

The podcast highlights the challenges in stratifying osteosarcoma patients for treatment due to the complex genetic landscape, microenvironment heterogeneity, and tumor self-plasticity. This complexity has hindered the development of efficient treatments and patient stratification based on molecular evidence, impacting the interpretation of treatment outcomes, especially with targeted agents like multi-kinase inhibitors. Fortunately, recent research efforts using unsupervised machine learning algorithms have led to new discoveries in classifying osteosarcoma at diagnosis, focusing on gene expression modules enriched for immune microenvironment and tumor phenotypic traits.

Remember Everything You Learn from Podcasts

Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
App store bannerPlay store banner