A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas.

ABSTRACT:

Introduction

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with the classical and follicular variants representing most cases. Despite generally favorable prognoses, approximately 10% of patients experience recurrence post-surgery and radioactive iodine therapy. Attempts to stratify risk of recurrence have relied on gene expression-based prognostic and predictive signatures with a focus on mutations of well-known driver genes, while hallmarks of tumor morphology have been ignored.

Objectives

We introduce a new computational pathology approach to develop prognostic gene signatures for PTC that is informed by quantitative features of tumor and immune cell morphology.

Methods

We quantified nuclear and immune-related features of tumor mor

SUBMITTER: Monabbati S 

PROVIDER: S-EPMC11531387 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature