Precision Pathology Podcast (P³) features monthly interviews hosted by George J. Netto, MD, Chair of Pathology and Laboratory Medicine at the University of Pennsylvania's Perelman School of Medicine. In each episode, he engages with global thought leaders and authors who are at the forefront of cutting- edge research in pathology and biomedical science.
The discussions are easy to follow and highly informative, covering a wide range of groundbreaking technological advancements in precision diagnostics and therapeutics. Topics include digital and computational pathology, single-cell and spatial omics, as well as multiplex biomarker assessment, which are transforming diagnostics, targeted therapies, immunotherapy, and cellular therapeutics.
Publisher
Perelman School of Medicine, Pathology & Laboratory Medicine
Can Computational Single-Cell Profiling of H&E WholeSlide Images reveal prognostic and predictive clues in Lung Adenocarcinoma?
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Yuri Tolkach, MD, PhD, Professor of Pathology at Cologne University in Germany, discusses his group's recently published study on computational single-cell profiling of Lung Adenocarcinoma (Precision Pathology 2026; https://doi.org/10.1016/j.prpath.2026.100005 (https://doi.org/10.1016/j.prpath.2026.100005)).
The authors apply their open-source model to 2,791 whole-slide H&E images, including TCGA and PLCO public datasets. They found
that high lymphocyte densities in tumor and tumor stroma were consistently associated with favorable outcomes,
whereas increased stromal granulocyte, connective tissue cell, and plasma cell proportions were associated with
adverse prognosis. Tumor cells lacking nearby lymphocytes, particularly within short distances, showed strong
adverse prognostic value, highlighting the importance of spatial immune-tumor interactions.
Integrative k-means clustering identified biologically coherent risk groups, including lymphocyte-rich favorable and granulocyte-rich adverse phenotypes, with validation across cohorts. Cellular-neighborhood analysis revealed ten spatial metaclusters representing tumor core, stroma, and tumor–stroma interface patterns; several meta-clusters showed
independent prognostic value.
28 Aug 2026
Can Spatial Immune Profiling Improve Oncotype Dx Guidance of Chemotherapy in Breast Cancer?
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Predictions of late recurrence risk in ER+HER2- breast cancer patients remain suboptimal, particularly for patients with intermediate risk determined by the Oncotype Dx Recurrence Score (RS, 16-25). Using spatial proteomics (multiplex immunofluorescence) and spatial transcriptomics, our guest, Zak Kinsella PhD, from the Royal College of Surgeons in Ireland, with his team of co-authors, observed an association between higher stromal tumor-infiltrating CD8+ lymphocyte (sTIL CD8+) density and poor outcome (ΔLR-χ2: 6.79, p = 0.009). The study suggests sTIL CD8+ density as a candidate biomarker for treatment decisions. Nature Communications ( 2026);
Learn more about Nature Communications (https://www.nature.com/articles/s41467-026-73432-2)
#OncotypeDX
#BreastCancer
#ERPositive
#HER2Negative
#CD8TCells
#SpatialOmics
#TumorMicroenvironment
17 Jul 2026
How CAR T-Cell Therapy Enabled Kidney Transplants for Highly Sensitized Patients
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This episode explains how a novel CAR T-cell approach made kidney transplantation possible for patients previously considered unmatched, and why that could change outcomes for people waiting on dialysis. Dr. Vijay Bhoj, MD, PhD, assistant professor of pathology and cellular immunotherapy at the University of Pennsylvania, walks through the phase 1, multi-institutional trial that combined CD19 and BCMA CAR T-cells to achieve durable antibody reduction and successful transplants.
Listen to the Podcast and watch the full vodcast on our YouTube channel for details.
Keywords: CAR T-Cell therapy, kidney transplantation, BCMA, CD19, plasmapheresis.
16 Jun 2026
Leveraging the Million Veteran Program Dataset to Bring a Prostate Genomic Risk to the Clinic: the ProGRESS study
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In this episode, we discuss the recent publication in Nature Cancer by Jason L. Vassy et al. on building a personalized genomic risk model to enhance precision in prostate cancer screening.
Guest Kara Maxwell, MD, PhD, from the University of Pennsylvania, explains how the PCARE test combines a polygenic risk score with genetic ancestry and family history to guide PSA decisions in clinical care. You'll hear how the Million Veteran Program enabled model development, why monogenic mutations were added to the clinical assay, and what the randomized PROGRESS trial will test about PSA screening pathways.
27 May 2026
GLP-1 Receptor Agonists and Cancer Risk Reduction: What is the Verdict?
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Glucagon-like peptide 1 receptor agonists (GLP1RAs) are widely used to treat type 2 diabetes mellitus (T2DM) and obesity. Given that T2DM and obesity are associated with a higher risk of cancer, the potential of GLP1RAs use to reduce cancer risk is of great interest. Professor Edoardo Mannucci from the University of Florence, Italy, discusses his recent publication in Nature Reviews Clinical Oncology (March 2026) on the current evidence from preclinical and clinical studies on the heterogeneous effects of GLP1RAs on cancer risk. The incidence of hepatocellular, oesophageal, endometrial, ovarian, and prostate cancers might be reduced, whereas safety concerns remain with respect to thyroid (both medullary and non-medullary) carcinoma.
#GLP1
#Weight Loss
#Obesity
#Diabetes
#Cancer Risk
28 Apr 2026
Intercepting Pancreatic Cancer: KRAS Inhibitors in Action
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Ben Stanger, MD, Hannah Weiss Professor of Oncology at the University of Pennsylvania, discusses his team's groundbreaking study on the use of KRAS-targeted small molecules to eliminate pancreatic cancer precursor lesions (PanIN) in a preclinical mouse model. The tremendous clinical implications of intercepting cancer development using novel pharmacologic agents are highlighted.
View Dr. Stanger's manuscript here (https://www.science.org/doi/10.1126/science.aec7929)
#PancreaticCancer
#KRAS-Inhibitors
#CancerInterception
#PrecisionOncology
#PanIN
10 Feb 2026
Cutting Edge Technologies Unlocking Barrett's Esophagus Clonal Cell States
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In this episode, Dr. Sydney Shaffer shares her expertise on cutting-edge technologies, including single-cell and spatial transcriptomics, and their significance for understanding cancer biology. The guest discusses these tools in the context of her recent Nature Communications publication (https://doi.org/10.1038/s41467-025-66302-w (https://doi.org/10.1038/s41467-025-66302-w)), which provides a single-cell view of cell dynamics in Barrett’s esophagus and links cell states along the disease trajectory from its origin to cancer.
#Barrett's
#Esophagus
#SpatialTranscriptomics
#Dysplasia
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Join Dr. George Netto as he discusses with Professor Felix Sahm, an international expert from Heidelberg University, his team's innovative multi-center study on intraoperative molecular profiling of central nervous system tumors (CNS). Learn how rapid methylation profiling could change the landscape of diagnostics and management of brain neoplasms. Don't miss this enlightening discussion!
#Neuropathology
#CNS
#BrainTumors
#MolecularProfiling
#MethylationProfiling
#PrecisionMedicine
#ArtificialIntelligence
21 Nov 2025
A Second Look at the Impact of TERTp Mutation on Meningioma Grade
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Join Dr. George Netto and Dr. Matija Snuderl of Langone Health at NY University as they discuss the significance of TERT promoter mutations in meningiomas and their implications for patient prognosis. This conversation sheds light on the need for reevaluation of molecular biomarkers in the grading of Meningiomas.
#Meningioma
#MolecularDiagnostics
#TERTPromoter
#Pathology
#CancerResearch
#TumorGrade
20 Oct 2025
AI-Driven Biomarkers for Antibody-Drug Conjugates (ADC)
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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 (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
27 Aug 2025
Introduction to Precision Pathology Podcast
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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.
27 Aug 2025
Pathology Foundation Model for Lung Cancer Bio-Marker Detection
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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%.
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