Machine and deep learning methods for predicting 3D genome organization.

Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers, Transcription Factor Binding Site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, TAD boundaries) and analyze their pros and cons. We also point out obstacles of computational prediction of 3D interactions and suggest future research directions.

The Transformative Role of 3D Culture Models in Triple-Negative Breast Cancer Research.

Advancements in cell culturing techniques have allowed the development of three-dimensional (3D) cell culture models sourced directly from patients' tissues and tumors, faithfully replicating the native tissue environment. These models provide a more clinically relevant platform for studying disease progression and treatment responses compared to traditional two-dimensional (2D) models. Patient-derived organoids (PDOs) and patient-derived xenograft organoids (PDXOs) emerge as innovative 3D cancer models capable of accurately mimicking the tumor's unique features, enhancing our understanding of tumor complexities, and predicting clinical outcomes. Triple-negative breast cancer (TNBC) poses significant clinical challenges due to its aggressive nature, propensity for early metastasis, and limited treatment options. TNBC PDOs and PDXOs have significantly contributed to the comprehension of TNBC, providing novel insights into its underlying mechanism and identifying potential therapeutic targets. This review explores the transformative role of various 3D cancer models in elucidating TNBC pathogenesis and guiding novel therapeutic strategies. It also provides an overview of diverse 3D cell culture models, derived from cell lines and tumors, highlighting their advantages and culturing challenges. Finally, it delves into live-cell imaging techniques, endpoint assays, and alternative cell culture media and methodologies, such as scaffold-free and scaffold-based systems, essential for advancing 3D cancer model research and development.

The Human Intermediate Prolactin Receptor I-tail Contributes Breast Oncogenesis by Targeting Ras/MAPK Pathway.

Prolactin and its receptor (PRLr) in humans are significantly involved in breast cancer pathogenesis. The intermediate form of human PRLr (hPRLrI) is produced by alternative splicing and has a novel 13 amino acid tail ("I-tail") gain. hPRLrI induces significant proliferation and anchorage-independent growth of normal mammary epithelia in vitro when coexpressed with the long form hPRLr (hPRLrL). hPRLrL and hPRLrI coexpression is necessary to induce the transformation of mammary epithelia in vivo. The I-tail is associated with the ubiquitin-like protein neural precursor cell expressed developmentally downregulated protein 8. Treatment with the neural precursor cell expressed developmentally downregulated protein 8-activating enzyme inhibitor pevonedistat resulted in increased hPRLrL and the death of breast cancer cells. The goal of this study was to determine the function of the hPRLrI I-tail in hPRLrL/hPRLrI-mediated mammary transformation. hPRLrL/hPRLrI and hPRLrL/hPRLrIΔ13 (I-tail removal mutant) were delivered to MCF10AT cells. Cell proliferation was decreased when hPRLrI I-tail was removed. I-tail deletion decreased anchorage-independent growth and attenuated cell migration. The I-tail was involved in Ras/MAPK signaling but not PI3K/Akt signaling pathway as shown by western blot. I-tail removal resulted in decreased hPRLrI stability. RNA-sequencing data revealed that I-tail removal resulted in differential gene expression induced by prolactin. Ingenuity Pathway Analysis revealed that the activity of ERK was attenuated. Treatment of breast cancer cells with ERK1/2 inhibitor ulixertinib resulted in decreased colony-forming ability and less proliferation. These studies suggest that the hPRLrI I-tail contributed to breast oncogenesis and may be a promising target for the development of new breast cancer therapies.