Dataset Information

Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer.

ABSTRACT: Remodeling of the extracellular matrix (ECM) to facilitate invasion and metastasis is a universal hallmark of cancer progression. However, a definitive therapeutic target remains to be identified in this tissue compartment. As major modulators of ECM structure and function, matrix metalloproteinases (MMPs) are highly expressed in cancer and have been shown to support tumor progression. MMP enzymatic activity is inhibited by the tissue inhibitor of metalloproteinase (TIMP1-4) family of proteins, suggesting that TIMPs may possess anti-tumor activity. TIMP2 is a promiscuous MMP inhibitor that is ubiquitously expressed in normal tissues. In this study, we address inconsistencies in the literature regarding the role of TIMP2 in tumor progression by analyzing co-expressed genes in tumor vs. normal tissue. Utilizing data from The Cancer Genome Atlas and Genotype-Tissue expression studies, focusing on breast and lung carcinomas, we analyzed the correlation between TIMP2 expression and the transcriptome to identify a list of genes whose expression is highly correlated with TIMP2 in tumor tissues. Bioinformatic analysis of the identified gene list highlights a core of matrix and matrix-associated genes that are of interest as potential modulators of TIMP2 function, thus ECM structure, identifying potential tumor microenvironment biomarkers and/or therapeutic targets for further study.

SUBMITTER: Peeney D

PROVIDER: S-EPMC6934702 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer.

Peeney David D Fan Yu Y Nguyen Trinh T Meerzaman Daoud D Stetler-Stevenson William G WG

Scientific reports 20191227 1

Remodeling of the extracellular matrix (ECM) to facilitate invasion and metastasis is a universal hallmark of cancer progression. However, a definitive therapeutic target remains to be identified in this tissue compartment. As major modulators of ECM structure and function, matrix metalloproteinases (MMPs) are highly expressed in cancer and have been shown to support tumor progression. MMP enzymatic activity is inhibited by the tissue inhibitor of metalloproteinase (TIMP1-4) family of proteins, ...[more]

PMID: 31882975

Similar Datasets

Project description:Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function).The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors.Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data.In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

Project description:Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein Tissue inhibitors of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.

Dataset Information

Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer.

Publications

Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure