Aakash Desai: Can Computational Pathology Improve TROP2 Biomarker Selection in NSCLC?
Aakash Desai/LinkedIn

Aakash Desai: Can Computational Pathology Improve TROP2 Biomarker Selection in NSCLC?

Aakash Desai, Associate Professor at UAB O’Neal Cancer Center, shared on LinkedIn:

“A digital TROP2 score separated who benefited from Dato-DXd in nonsquamous NSCLC, in a new Nature Portfolio Nature Medicine paper from TROPION-Lung01.

  • Normalized membrane ratio (NMR) = membrane / (membrane + cytoplasmic) TROP2, measured by computational pathology on IHC slides
  • Dato-DXd: mPFS 7.2 vs 4.0 mo for NMR+ vs NMR-, HR 0.40
  • Docetaxel: 4.1 vs 4.4 mo, HR 0.94 (interaction P=0.0098)

Visual TROP2 IHC scoring did not predict response.

  • Is a digital score the way TROP2 ADCs finally get a biomarker?
  • If so, how do we operationalize this to ensure widespread availability of this?
  • Perhaps an interesting take would be to use frontier LLMs to see if these could be applied and still preserve accuracy?”

Aakash Desai: Can Computational Pathology Improve TROP2 Biomarker Selection in NSCLC?

Read The Full Article.

Title: Normalized membrane ratio of TROP2 as a predictor of clinical outcomes with datopotamab deruxtecan in non-small-cell lung cancer

Authors: Marina C. Garassino, Myung-Ju Ahn, Markus Schick, Ansh Kapil, Luis Paz-Ares, Aaron Lisberg, Melissa L. Johnson, Maurice Pérol, Toshio Shimizu, Rebecca Heist, Alexander Spira, Isamu Okamoto, Nicolas Girard, Robin Cornelissen, Elvire Pons-Tostivint, Min Hee Hong, Ricardo Zwirtes, Rachel Chiaverelli, Marlon Rebelatto, Matthew Sung, Chuyu Deng, James Harper, Danielle Carroll, Hadassah Sade, Jacob Sands.

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