logo
ResearchBunny Logo
Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

Medicine and Health

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

J. Kong, H. Lee, et al.

Discover a groundbreaking machine-learning framework developed by JungHo Kong, Heetak Lee, Donghyo Kim, Seong Kyu Han, Doyeon Ha, Kunyoo Shin, and Sanguk Kim that identifies robust drug biomarkers through innovative network-based analyses of pharmacogenomic data. This research promises to enhance drug response predictions in colorectal and bladder cancer treatments, verified by extensive validation against external datasets.

00:00
00:00
Playback language: English
Abstract
This study presents a machine-learning framework for identifying robust drug biomarkers using network-based analyses of pharmacogenomic data from 3D organoid culture models. The identified biomarkers accurately predict drug responses in colorectal and bladder cancer patients treated with 5-fluorouracil and cisplatin, respectively. Validation using external datasets of isogenic cancer cell lines and concordance analysis with somatic mutation-based biomarkers further support the method's robustness.
Publisher
Nature Communications
Published On
Oct 30, 2020
Authors
JungHo Kong, Heetak Lee, Donghyo Kim, Seong Kyu Han, Doyeon Ha, Kunyoo Shin, Sanguk Kim
Tags
machine learning
drug biomarkers
pharmacogenomics
cancer treatment
bioinformatics
network analysis
3D organoid models

Related Publications

Explore these studies to deepen your understanding of the subject.

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs
Medicine and Health

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs

H. Gerdes, P. Casado, et al.

Therapeutic efficacy of a MMAE-based anti-DR5 drug conjugate Oba01 in preclinical models of pancreatic cancer
Medicine and Health

Therapeutic efficacy of a MMAE-based anti-DR5 drug conjugate Oba01 in preclinical models of pancreatic cancer

C. Zheng, D. Zhou, et al.

Efficacy of early PET-CT directed switch to carboplatin and paclitaxel based definitive chemoradiotherapy in patients with oesophageal cancer who have a poor early response to induction cisplatin and capecitabine in the UK: a multi-centre randomised controlled phase II trial
Medicine and Health

Efficacy of early PET-CT directed switch to carboplatin and paclitaxel based definitive chemoradiotherapy in patients with oesophageal cancer who have a poor early response to induction cisplatin and capecitabine in the UK: a multi-centre randomised controlled phase II trial

S. Mukherjee, C. N. Hurt, et al.

A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes
Medicine and Health

A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes

I. Piazza, N. Beaton, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny