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Updated: May 2, 2026
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Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Published on: February 21, 2014
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Epigenomic, transcriptomic, and proteomic characterization of breast cancer cell line reference samples
Chirag Nepal1, Wanqiu Chen1, Zhong Chen1
1Center for Genomics, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA; Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA.
Cell Reports Methods
|January 15, 2026
Summary
This study establishes comprehensive multi-omics reference materials for breast cancer and B cell lines. These integrated genomic, epigenomic, transcriptomic, and proteomic datasets serve as benchmarks for validating omics assays and bioinformatics methods.
Area of Science:
- Genomics and Bioinformatics
- Molecular Biology
- Cancer Research
Background:
- Next-generation sequencing (NGS) demands high accuracy, reproducibility, and standardized reference materials.
- Existing SEQC-2 studies provided extensive genomic data but lacked integrated epigenomic and proteomic references.
Purpose of the Study:
- To establish comprehensive multi-omics reference materials using Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), Methyl-seq, RNA sequencing (RNA-seq), and proteomic profiling.
- To provide well-defined benchmarks for validating omics assays and bioinformatics methods.
Main Methods:
- Performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic profiling on paired breast cancer and B cell lines.
- Integrated genomic, epigenomic, transcriptomic, and proteomic data.
Main Results:
- Identified over 7,700 protein groups, with 95% of genes encoding a single peptide isoform.
- Protein expression was higher from CpG island (CGI)-overlapping transcripts.
- Chromatin accessibility correlated with CG density, influencing gene and protein expression patterns.
Conclusions:
- Developed comprehensive multi-omics reference datasets for cancer and immune cell lines.
- These benchmarks are valuable for validating omics technologies and bioinformatics pipelines.
- The data supports a community resource for advancing omics research.
