AIMC Topic: Gene Expression Regulation, Neoplastic
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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...
The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome.
Nature cancer
Nov 2, 2020
We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in ...
Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.
Nature communications
Oct 30, 2020
Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational...
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...
Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma.
International immunopharmacology
Oct 19, 2020
BACKGROUND: Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.
Leveraging TCGA gene expression data to build predictive models for cancer drug response.
BMC bioinformatics
Sep 30, 2020
BACKGROUND: Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression da...
An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.
Journal of cancer research and clinical oncology
Sep 23, 2020
PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient ...
Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice.
BMC medical genomics
Sep 21, 2020
BACKGROUND: Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. Molecular level characters, such as gene expression levels and mutations, may provide profound information for precision treatment apart from path...
Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.
Journal of bioinformatics and computational biology
Aug 21, 2020
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...
Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.
Biomolecules
Aug 20, 2020
An effective feature extraction method is key to improving the accuracy of a prediction model. From the Gene Expression Omnibus (GEO) database, which includes 13,487 genes, we obtained microarray gene expression data for 238 samples from colorectal c...
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