Deciphering the Role of 3D Genome Organization in Breast Cancer Susceptibility

Examining the dynamics of three-dimensional genome organization with multitask matrix factorization

Three-dimensional (3D) genome organization, which determines how the DNA is packaged inside the nucleus, has emerged as a key component of the gene regulation machinery. High-throughput chromosome conformation data sets, such as Hi-C, have become available across multiple conditions and time points, offering a unique opportunity to examine changes in 3D genome organization and link them to phenotypic changes in normal and disease processes. However, systematic detection of higher-order structural changes across multiple Hi-C data sets remains a major challenge. Existing computational methods either do not model higher-order structural units or cannot model dynamics across more than two conditions of interest. We address these limitations with tree-guided integrated factorization (TGIF), a generalizable multitask nonnegative matrix factorization (NMF) approach that can be applied to time series or hierarchically related biological conditions. TGIF can identify large-scale changes at the compartment or subcompartment levels, as well as local changes at boundaries of topologically associated domains (TADs). Based on benchmarking in simulated and real Hi-C data, TGIF boundaries are more accurate and reproducible across differential levels of noise and sources of technical artifacts, and are more enriched in CTCF. Application to three multisample mammalian data sets shows that TGIF can detect differential regions at compartment, subcompartment, and boundary levels that are associated with significant changes in regulatory signals and gene expression enriched in tissue-specific processes. Finally, we leverage TGIF boundaries to prioritize sequence variants for multiple phenotypes from the NHGRI GWAS catalog. Taken together, TGIF is a flexible tool to examine 3D genome organization dynamics across disease and developmental processes.

Unveiling Alterations of Epigenetic Modifications and Chromatin Architecture Leading to Lipid Metabolic Reprogramming during the Evolutionary Trastuzumab Adaptation of HER2-Positive Breast Cancer

Secondary trastuzumab resistance represents an evolutionary adaptation of HER2-positive breast cancer during anti-HER2 treatment. Most current studies have tended to prioritize HER2 and its associated signaling pathways, often overlooking broader but seemingly less relevant cellular processes, along with their associated genetic and epigenetic mechanisms. Here, transcriptome data is not only characterized but also examined epigenomic and 3D genome architecture information in both trastuzumab-sensitive and secondary-resistant breast cancer cells. The findings reveal that the global metabolic reprogramming associated with trastuzumab resistance may stem from genome-wide alterations in both histone modifications and chromatin structure. Specifically, the transcriptional activities of key genes involved in lipid metabolism appear to be regulated by variant promoter H3K27me3 and H3K4me3 modifications, as well as promoter-enhancer interactions. These discoveries offer valuable insights into how cancer cells adapt to anti-tumor drugs and have the potential to impact future diagnostic and treatment strategies.

The 3D genome and its impacts on human health and disease

Eukaryotic genomes are highly compacted in the cell nucleus. Two loci separated by a long linear distance can be brought into proximity in space through DNA-binding proteins and RNAs, which contributes profoundly to the regulation of gene expression. Recent technology advances have enabled the development and application of the chromosome conformation capture (3C) technique and a host of 3C-based methods that enable genome-scale investigations into changes in chromatin high-order structures during diverse physiological processes and diseases. In this review, we introduce 3C-based technologies and discuss how they can be utilized to glean insights into the impacts of three-dimensional (3D) genome organization in normal physiological and disease processes.