In this episode, I discuss with Dr. Salgado, Co-Chair of the International Immuno-Oncology Biomarkers Working Group, his editorial (https://doi.org/10.1016/j.ccell.2025.03.020) on the recent Cancer Cell study by Ding Ma et al, presenting a predictive AI model for HER2-targeting ADC efficacy, incorporating immune system components, hormone receptor status, clinical staging, and HER2+ cell proportion. 

#ImmunoOncology
#HER2Biomarker
#AntibodyDrugConjugates

Introducing P³ Podcast

Welcome to P³, our new podcast series on Precision Pathology, created and hosted by Dr. George J. Netto, the Simon Flexner Professor and  Chair of Pathology and Laboratory Medicine at the University of Pennsylvania in Philadelphia, PA.

In each episode, Dr. Netto will share his perspective on the latest discoveries in precision medicine through informal conversations with accomplished authors and thought leaders from around the world. These dynamic discussions are designed to keep you informed about the most critical publications from high-impact journals.
Topics will cover a wide range of disruptive technological advances in diagnostics, prognostics, and predictors of therapeutic response—from digital and computational pathology to spatial and single-cell omics, cell-free nucleic acid assays, and the latest in cellular therapeutics.

We hope you’ll enjoy listening and watching and find the conversations both informative and stimulating. We welcome your thoughts and feedback. Please feel free to connect by email (george.netto@pennmedicine.upenn.edu) or at Dr. Netto’s LinkedIn or Substack.

Rapid and accurate assessment of EGFR mutations in lung adenocarcinoma is critical for the management of NSCLC patients.
PCR-based assays provide rapid results but with reduced accuracy compared with next-generation sequencing and can exhaust the increasingly valuable small amount of biopsy tissue available for predictive biomarkers. Computational biomarkers
Leveraging modern foundation models may offer alternative solutions. 

In this episode of Precision Pathology Podcast (P3), the host discusses with Dr. Chad Vanderbilt from the Department of Pathology and Laboratory Medicine at MSKCC in NY, his team’s recent study, published in Nature Medicine, using a large international clinical dataset of digital lung adenocarcinoma slides to develop a computational EGFR biomarker. The artificial-intelligence-assisted workflow has the potential to reduce the number of rapid molecular tests needed by up to 43%.