DeepAI AI Chat
Log In Sign Up

Identifying Epigenetic Signature of Breast Cancer with Machine Learning

by   Maxim Vaysburd, et al.

The research reported in this paper identifies the epigenetic biomarker (methylation beta pattern) of breast cancer. Many cancers are triggered by abnormal gene expression levels caused by aberrant methylation of CpG sites in the DNA. In order to develop early diagnostics of cancer-causing methylations and to develop a treatment, it is necessary to identify a few dozen key cancer-related CpG methylation sites out of the millions of locations in the DNA. This research used public TCGA dataset to train a TensorFlow machine learning model to classify breast cancer versus non-breast-cancer tissue samples, based on over 300,000 methylation beta values in each sample. L1 regularization was applied to identify the CpG methylation sites most important for accurate classification. It was hypothesized that CpG sites with the highest learned model weights correspond to DNA locations most relevant to breast cancer. A reduced model trained on methylation betas of just the 25 CpG sites having the highest weights in the full model (trained on methylation betas at over 300,000 CpG sites) has achieved over 94 data, confirming that the identified 25 CpG sites are indeed a biomarker of breast cancer.


Breast cancer detection using artificial intelligence techniques: A systematic literature review

Cancer is one of the most dangerous diseases to humans, and yet no perma...

betaclust: a family of mixture models for beta valued DNA methylation data

The DNA methylation process has been extensively studied for its role in...

A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation

Epigenetic alterations have an important role in the development of seve...

Nonparametric Bayes Differential Analysis of Multigroup DNA Methylation Data

DNA methylation datasets in cancer studies are comprised of sample measu...

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

The evaluation of human epidermal growth factor receptor 2 (HER2) expres...

CBCT-to-CT synthesis with a single neural network for head-and-neck, lung and breast cancer adaptive radiotherapy

Purpose: CBCT-based adaptive radiotherapy requires daily images for accu...

Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review

For invasive breast cancer, immunohistochemical (IHC) techniques are oft...