AIMC Topic: Drug Resistance, Neoplasm

Clear Filters Showing 41 to 50 of 94 articles

Biologically informed deep neural network for prostate cancer discovery.

Nature Sep 22, 2021
The determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer remains a major biological and clinical challenge. Recent advances in interpretability of machine learning models as applied to biomedical proble...
Humans Reproducibility of Results Male Receptors, Androgen Cell Cycle Proteins Proto-Oncogene Proteins Receptor, Fibroblast Growth Factor, Type 1 Deep Learning Prostatic Neoplasms Drug Resistance, Neoplasm Tumor Suppressor Protein p53
View on PubMed DOI

Predicting drug sensitivity of cancer cells based on DNA methylation levels.

PloS one Sep 10, 2021
Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug responses for a given cell line based on molecular featur...
Humans Machine Learning Algorithms Neoplasms Antineoplastic Agents Cell Line, Tumor DNA Methylation Drug Resistance, Neoplasm
View on PubMed DOI

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Scientific reports Aug 19, 2021
Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplat...
Drug Resistance, Neoplasm Gene Expression Regulation, Neoplastic Ovarian Neoplasms Cisplatin Inhibitory Concentration 50 Humans Machine Learning Female Biomarkers, Tumor Gene Expression Profiling Cell Line, Tumor
View on PubMed DOI

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.

PloS one Apr 29, 2021
Determining sensitive drugs for a patient is one of the most critical problems in precision medicine. Using genomic profiles of the tumor and drug information can help in tailoring the most efficient treatment for a patient. In this paper, we propose...
Humans Machine Learning Neoplasms Antineoplastic Agents Cell Line, Tumor Computational Biology Drug Resistance, Neoplasm
View on PubMed DOI

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines.

IEEE/ACM transactions on computational biology and bioinformatics Apr 6, 2021
High-throughput screening technologies have provided a large amount of drug sensitivity data for a panel of cancer cell lines and hundreds of compounds. Computational approaches to analyzing these data can benefit anticancer therapeutics by identifyi...
Antineoplastic Agents High-Throughput Screening Assays Deep Learning Drug Resistance, Neoplasm Cell Line, Tumor Humans Models, Statistical
View on PubMed DOI

Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 18, 2020
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...
Progression-Free Survival Drug Resistance, Neoplasm Image Processing, Computer-Assisted Follow-Up Studies Prognosis Neoplasm Staging Female Risk Assessment Skin Melanoma Disease Progression Humans Skin Neoplasms ROC Curve Aged Machine Learning Immune Checkpoint Inhibitors Prospective Studies Adult Male Middle Aged
View on PubMed DOI

Prediction of cancer dependencies from expression data using deep learning.

Molecular omics Nov 2, 2020
Detecting cancer dependencies is key to disease treatment. Recent efforts have mapped gene dependencies and drug sensitivities in hundreds of cancer cell lines. These data allow us to learn for the first time models of tumor vulnerabilities and apply...
Computational Biology Gene Expression Regulation, Neoplastic Drug Resistance, Neoplasm Linear Models Humans Neural Networks, Computer Neoplasms Gene Expression Profiling Transcriptome Deep Learning
View on PubMed DOI

Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 27, 2020
PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer has potential to reshape the colorectal cancer landscape. We developed and validated an assay that is applicable on formalin-fixed, paraffin-embedded (FFPE) samples of colorectal cance...
Female Reproducibility of Results Colorectal Neoplasms Biomarkers, Tumor Male Middle Aged Risk Assessment Antineoplastic Agents Humans Prognosis Gene Expression Profiling Drug Resistance, Neoplasm Transcriptome Gene Expression Regulation, Neoplastic Support Vector Machine
View on PubMed DOI

Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks.

Nature communications Sep 1, 2020
Deep learning with Convolutional Neural Networks has shown great promise in image-based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation ap...
Drug Resistance, Neoplasm Oligonucleotide Array Sequence Analysis Drug Screening Assays, Antitumor Bayes Theorem High-Throughput Nucleotide Sequencing Datasets as Topic Humans Deep Learning Biomarkers, Tumor Cell Line, Tumor Neoplasms Image Processing, Computer-Assisted Cell Proliferation Antineoplastic Agents Gene Expression Profiling
View on PubMed DOI

Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

Frontiers in immunology Aug 25, 2020
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
Carcinoma Male Drug Resistance, Neoplasm Risk Assessment Humans Clinical Decision-Making Urothelium Gene Expression Profiling Time Factors Machine Learning Transcriptome Treatment Outcome Female Decision Support Techniques Immune Checkpoint Inhibitors Antibodies, Monoclonal, Humanized Risk Factors B7-H1 Antigen Urinary Bladder Neoplasms Biomarkers, Tumor Nomograms Predictive Value of Tests
View on PubMed DOI
Popular Topics
Recent Journals