Machine learning approaches to drug response prediction: challenges and recent progress

G Adam, L Rampášek, Z Safikhani, P Smirnov… - NPJ precision …, 2020 - nature.com
Cancer is a leading cause of death worldwide. Identifying the best treatment using
computational models to personalize drug response prediction holds great promise to …

Machine learning and feature selection for drug response prediction in precision oncology applications

M Ali, T Aittokallio - Biophysical reviews, 2019 - Springer
In-depth modeling of the complex interplay among multiple omics data measured from
cancer cell lines or patient tumors is providing new opportunities toward identification of …

Pan-cancer analyses reveal genomic features of FOXM1 overexpression in cancer

CJ Barger, C Branick, L Chee, AR Karpf - Cancers, 2019 - mdpi.com
FOXM1 is frequently overexpressed in cancer, but this has not been studied in a
comprehensive manner. We utilized genotype-tissue expression (GTEx) normal and The …

[HTML][HTML] Machine learning in the prediction of cancer therapy

R Rafique, SMR Islam, JU Kazi - Computational and Structural …, 2021 - Elsevier
Resistance to therapy remains a major cause of cancer treatment failures, resulting in many
cancer-related deaths. Resistance can occur at any time during the treatment, even at the …

Dr. VAE: improving drug response prediction via modeling of drug perturbation effects

L Rampášek, D Hidru, P Smirnov, B Haibe-Kains… - …, 2019 - academic.oup.com
Motivation Individualized drug response prediction is a fundamental part of personalized
medicine for cancer. Great effort has been made to discover biomarkers or to develop …

Revisiting inconsistency in large pharmacogenomic studies

Z Safikhani, P Smirnov, M Freeman… - …, 2017 - pmc.ncbi.nlm.nih.gov
In 2013, we published a comparative analysis of mutation and gene expression profiles and
drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines …

CircCD44 plays oncogenic roles in triple-negative breast cancer by modulating the miR-502–5p/KRAS and IGF2BP2/Myc axes

J Li, X Gao, Z Zhang, Y Lai, X Lin, B Lin, M Ma, X Liang… - Molecular cancer, 2021 - Springer
Background Emerging studies have revealed the potent functions of circRNAs in breast
cancer tumorigenesis. However, the biogenesis, biofunction and mechanism of circRNAs in …

Alternative splicing, RNA-seq and drug discovery

S Zhao - Drug discovery today, 2019 - Elsevier
Highlights•RNA-seq is emerging as a powerful technology to study alternative splicing.•RNA
mis-splicing can cause cancers and a variety of other human diseases.•To target alternative …

RNA Sequencing of the NCI-60: Integration into CellMiner and CellMiner CDB

WC Reinhold, S Varma, M Sunshine, F Elloumi… - Cancer research, 2019 - AACR
Abstract CellMiner (http://discover. nci. nih. gov/cellminer) and CellMinerCDB
(https://discover. nci. nih. gov/cellminercdb/) are web-based applications for mining publicly …

Disruption of the anaphase-promoting complex confers resistance to TTK inhibitors in triple-negative breast cancer

KL Thu, J Silvester, MJ Elliott… - Proceedings of the …, 2018 - National Acad Sciences
TTK protein kinase (TTK), also known as Monopolar spindle 1 (MPS1), is a key regulator of
the spindle assembly checkpoint (SAC), which functions to maintain genomic integrity. TTK …