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Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer

Medicine and Health

Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer

Y. Iwatate, I. Hoshino, et al.

This groundbreaking study delves into the realm of radiogenomics, spotlighting its potential to predict p53 mutations and PD-L1 expression in pancreatic ductal adenocarcinoma (PDAC). With significant findings linking p53 mutations to poor prognosis, this research led by Yosuke Iwatate and collaborators opens new doors for precision medicine in PDAC treatment.

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Playback language: English
Abstract
This study investigated the use of radiogenomics to predict p53 mutations and PD-L1 expression in pancreatic ductal adenocarcinoma (PDAC) patients. 107 PDAC patients were retrospectively analyzed. Immunohistochemistry was used to assess p53 and PD-L1 status. Imaging features (IFs) were extracted from CT scans to create predictive models. The area under the curve (AUC) for p53 and PD-L1 prediction models was 0.795 and 0.683, respectively. Radiogenomics-predicted p53 mutations were significantly associated with poor prognosis (P=0.015). This suggests that radiogenomics may aid in the development of precision medicine for PDAC.
Publisher
British Journal of Cancer
Published On
Jul 21, 2020
Authors
Yosuke Iwatate, Isamu Hoshino, Hajime Yokota, Fumitaka Ishige, Makiko Itami, Yasukuni Mori, Satoshi Chiba, Hidehito Arimitsu, Hiroo Yanagibashi, Hiroki Nagase, Wataru Takayama
Tags
radiogenomics
p53 mutations
PD-L1 expression
pancreatic ductal adenocarcinoma
prognosis
CT scans
predictive models

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