Instruct: Identify the main category of Biorxiv papers based on the titles and abstracts
Query: A Non-Negative Tensor Factorization Approach to Deconvolute Epigenetic Microenvironment in Breast Cancer An in-depth understanding of epithelial breast cell response to growth-promoting ligands is required to elucidate how signals from the microenvironment affect cell-intrinsic regulatory networks and their resultant cellular phenotypes, such as cell growth, progression, and differentiation. Understanding the cellular response to these signals is particularly important in understanding the mechanisms of breast cancer initiation and progression. There is increasing evidence that aberrant epigenetic marks are present in cells of the breast tumor microenvironment and are known to affect primary cellular processes like proliferation, differentiation, and apoptosis. However, the current mechanisms by which epigenetic microenvironment signals influence these cellular phenotypes are not well established. We developed a high-order correlation method using proteomics data to reveal the regulatory dynamics among signaling proteins, histones, and growth-promoting ligands in the breast epithelial cells. In the proposed method, the protein-ligand and histone-ligand correlations at multiple time points are first encoded in two three-way tensors. Then, a non-negative tensor factorization (NTF) model is used to capture and quantify the protein-ligand and histone-ligand correlations spanning all time points, followed by a correlation analysis to reveal the pairwise correlations between histones and proteins. Our method revealed the onset of specific protein-histone signatures in response to growth ligands contributing to distinct cellular phenotypes that are indicative of breast cancer initiation and progression. Furthermore, the differential and enrichment analyses of transcriptomic data corroborated with the correlations found between ligands and signaling proteins by the NTF-based model.

Author summaryBreast cancer is the most common malignancy, which has become the dominant cause of cancer-relevant death in women worldwide. Breast cancer comprises not only tumor cells but also epigenetic alterations in the surrounding microenvironment (ME). Increasing evidence shows that aberrant epigenetic marks are present in cells of the ME, contributing to cancer initiation, growth, progression, invasion, and metastasis. As a result, epigenetic ME responses are key indicators of the therapeutic efficacy of various clinical treatments. Due to the importance of epigenetic ME responses in various cancer cellular activities, recent years have seen an increasing interest in developing therapies targeting specific epigenetic biomarkers in the tumor microenvironment (TME).

However, communications among different biomolecules such as growth-promoting ligands, signaling proteins, and epigenetic marks in TME are complex. How their interactions affect various cellular behaviors causing cancer initiation, growth and progression are not well understood. In this study, we focus on the interaction mechanisms among ligands, proteins, and histone modifications, aiming to identify likely biomarkers and the onset of tumorigenesis through computational modeling. The findings from our study will help identify potential biomarkers for developing epigenetic-directed breast cancer therapies in the future.
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The categories of this paper are: physiology
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The categories of this paper are: immunology
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The categories of this paper are: pathology
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The categories of this paper are: zoology
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The categories of this paper are: toxicology
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The categories of this paper are: bioengineering
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The categories of this paper are: genetics
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The categories of this paper are: molecular
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The categories of this paper are: communication
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The categories of this paper are: education
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The categories of this paper are: cognition
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The categories of this paper are: scientific
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The categories of this paper are: bioinformatics
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The categories of this paper are: and
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The categories of this paper are: animal
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The categories of this paper are: biophysics