Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer

Peeney, David; Fan, Yu; Nguyen, Trinh; Meerzaman, Daoud; Stetler-Stevenson, William G.

doi:10.1038/s41598-019-56632-3

Cited by 26 publications

(20 citation statements)

References 67 publications

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“…Although these genes are differentially expressed in immune cells or stromal cells, the expression of these genes in normal germinal center B cells and in a subset of DLBCL is uncertain, and our sequencing data comes from tumor tissues, so we cannot distinguish whether the expression level is caused by stromal or tumor components. High expression of TIMP2 has been reported to inhibit matrix metalloproteinases to produce anti-tumor activity ( 20 ). TIMP2 was also demonstrated to interact with multiple integrin pathways and is involved in angiogenesis in gastric cancer ( 21 ).…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Chen

Pei

et al. 2021

Front. Oncol.

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Diffuse large B-cell lymphoma (DLBCL) is an extremely heterogeneous tumor entity, which makes prognostic prediction challenging. The tumor microenvironment (TME) has a crucial role in fostering and restraining tumor development. Consequently, we performed a systematic investigation of the TME and genetic factors associated with DLBCL to identify prognostic biomarkers for DLBCL. Data for a total of 1,084 DLBCL patients from the Gene Expression Omnibus database were included in this study, and patients were divided into a training group, an internal validation group, and two external validation groups. We calculated the abundance of immune–stromal components of DLBCL and found that they were related to tumor prognosis and progression. Then, differentially expressed genes were obtained based on immune and stromal scores, and prognostic TME‐related genes were further identified using a protein–protein interaction network and univariate Cox regression analysis. These genes were analyzed by the least absolute shrinkage and selection operator Cox regression model to establish a seven-gene signature, comprising TIMP2, QKI, LCP2, LAMP2, ITGAM, CSF3R, and AAK1. The signature was shown to have critical prognostic value in the training and validation sets and was also confirmed to be an independent prognostic factor. Subgroup analysis also indicated the robust prognostic ability of the signature. A nomogram integrating the seven-gene signature and components of the International Prognostic Index was shown to have value for prognostic prediction. Gene set enrichment analysis between risk groups demonstrated that immune-related pathways were enriched in the low-risk group. In conclusion, a novel and reliable TME relevant gene signature was proposed and shown to be capable of predicting the survival of DLBCL patients at high risk of poor survival.

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Section: Discussionmentioning

confidence: 99%

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Chen

Pei

et al. 2021

Front. Oncol.

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“…TIMPs inhibit the degradation of extracellular matrix, suppress angiogenesis, and play an important role in the occurrence, invasion and metastasis of tumor cells [25]. TIMP2 is reported dysregulated in more than 30 clinical studies about breast cancer[26], lung cancer [27], prostate cancer [28]. EZH2 can methylate the promoter of TIMP2, thereby inhibiting TIMP2 expression and promoting the metastasis of ovarian cancer [29].…”

Section: Discussionmentioning

confidence: 99%

TDG interacts with DNMT3A to inhibit the migration and invasion of human colon cancer cells

Miao

Zhao

Tang

et al. 2021

Preprint

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Background Colorectal cancer (CRC) is one of the most common malignant tumors with high recurrence and mortality. Thymine DNA glycosylase (TDG) is one of the key molecules involved in base excision repair pathway. Recently, more and more attentions have been paid to the role of TDG on tumor development. However, the specific functions of TDG in CRC remain unclear. Methods The biological functions of TDG and DNA methyltransferase 3 alpha (DNMT3A) in CRC were evaluated using migration and invasion assay. Tumor metastasis assay was performed in nude mice to detect the role of TDG in vivo. The interaction of TDG with DNMT3A was determined by co-immunoprecipitation (Co-IP). Chromatin immunoprecipitation analysis (CHIP) was applied to predict the DNA binding site of DNMT3A. We also performed methylation-specific PCR (MSP) to detect the changes in TIMP2 methylation levels. Results We found that TDG could inhibit the migration and invasion of human colon cancer cells in vitro and in vivo. TDG promoted the ubiquitination and degradation of DNMT3A by binding with it. Interference with siDNMT3A also inhibited the migration and invasion of human colon cancer cells. Further ChIP, MSP, and rescue experiments data confirmed that TDG accelerated the degradation of DNMT3A, and then significantly regulated the transcription and expression of TIMP2, thereby affecting the migration and invasion of human colon cancer cells. Conclusion Our findings reveal that TDG inhibit the migration and invasion of human colon cancer cells through DNMT3A-TIMP2 axis which may be potential therapeutic strategies in the development and treatment of CRC.

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“…With the growing interest in understanding the role that the matrisome plays in cancer chemoresistance and sensitivity [13,16,52,53] and the concurrent paucity of drugs targeting it [13], we believe that fine mapping of the gene regulatory networks governing the tumor matrisome will open novel therapeutic possibilities in the future and provide new tools to understand tumorigenic mechanisms and, finally, beat cancer.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

Kääriäinen

Pesola

Dittmann

et al. 2020

IJMS

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The expression and regulation of matrisome genes—the ensemble of extracellular matrix, ECM, ECM-associated proteins and regulators as well as cytokines, chemokines and growth factors—is of paramount importance for many biological processes and signals within the tumor microenvironment. The availability of large and diverse multi-omics data enables mapping and understanding of the regulatory circuitry governing the tumor matrisome to an unprecedented level, though such a volume of information requires robust approaches to data analysis and integration. In this study, we show that combining Pan-Cancer expression data from The Cancer Genome Atlas (TCGA) with genomics, epigenomics and microenvironmental features from TCGA and other sources enables the identification of “landmark” matrisome genes and machine learning-based reconstruction of their regulatory networks in 74 clinical and molecular subtypes of human cancers and approx. 6700 patients. These results, enriched for prognostic genes and cross-validated markers at the protein level, unravel the role of genetic and epigenetic programs in governing the tumor matrisome and allow the prioritization of tumor-specific matrisome genes (and their regulators) for the development of novel therapeutic approaches.

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Matrisome-Associated Gene Expression Patterns Correlating with TIMP2 in Cancer

Cited by 26 publications

References 67 publications

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

TDG interacts with DNMT3A to inhibit the migration and invasion of human colon cancer cells

Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

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