Weakly-supervised tumor purity prediction from frozen H&E stained slides.

ABSTRACT:

Background

Estimating tumor purity is especially important in the age of precision medicine. Purity estimates have been shown to be critical for correction of tumor sequencing results, and higher purity samples allow for more accurate interpretations from next-generation sequencing results. Molecular-based purity estimates using computational approaches require sequencing of tumors, which is both time-consuming and expensive.

Methods

Here we propose an approach, weakly-supervised purity (wsPurity), which can accurately quantify tumor purity within a digitally captured hematoxylin and eosin (H&E) stained histological slide, using several types of cancer from The Cancer Genome Atlas (TCGA) as a proof-of-concept.

Findings

Our model predicts cancer type with high accuracy

SUBMITTER: Brendel M 

PROVIDER: S-EPMC9157012 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature