&lt;p&gt;Histone Demethylase &lt;em&gt;KDM3A&lt;/em&gt; Promotes Cervical Cancer Malignancy Through the &lt;em&gt;ETS1&lt;/em&gt;/KIF14/Hedgehog Axis&lt;/p&gt;

Liu, Jinyu; Li, Dongqing; Zhang, Xin; Li, Yanyan; Jiang, Ou

doi:10.2147/ott.s276559

Cited by 20 publications

(15 citation statements)

References 42 publications

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“…The transcriptional activity of ets1 has been reported to be regulated by epigenetic modifications (Liu et al 2020;Sobral et al 2020). The present study represented an association between KMT5A and ets1 (Fig.…”

Section: Discussionsupporting

confidence: 72%

ets1 associates with KMT5A to participate in high glucose-mediated EndMT via upregulation of PFN2 expression in diabetic nephropathy

Zhong

et al. 2021

Mol Med

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Background Diabetic nephropathy (DN) is currently the leading cause of end-stage renal disease globally. The endothelial-to-mesenchymal transition (EndMT) of glomerular endothelial cells has been reported to play a crucial role in DN. As a specific form of epithelial-to-mesenchymal transition, EndMT and epithelial-to-mesenchymal transition may exhibit mutual modulators. Profilin 2 (PFN2) has been reported to participate in epithelial-to-mesenchymal transition. Moreover, ETS proto-oncogene 1 (ets1) and lysine methyltransferase 5A (KMT5A) have been reported to contribute to high glucose-mediated endothelial injury and epithelial-to-mesenchymal transition. In this study, we hypothesize ets1 associates with KMT5A to modulate PFN2 transcription, thus participating in high glucose-mediated EndMT in glomerular endothelial cells. Methods Immunohistochemistry (IHC) was performed to detect protein levels in the kidney tissues and/or aorta tissues of human subjects and rats. Western blot, qPCR and immunofluorescence were performed using human umbilical vein endothelial cells (HUVECs). Chromatin immunoprecipitation (ChIP) assays and dual luciferase assays were performed to assess transcriptional activity. The difference between the groups was compared by two-tailed unpaired t-tests or one-way ANOVAs. Results Our data indicated that vimentin, αSMA, S100A4 and PFN2 levels were increased, and CD31 levels were reduced in glomerular endothelial cells of DN patients and rats. Our cell experiments showed that high glucose induced EndMT by augmenting PFN2 expression in HUVECs. Moreover, high glucose increased ets1 expression. si-ets1 suppressed high glucose-induced PFN2 levels and EndMT. ets1 overexpression-mediated EndMT was reversed by si-PFN2. Furthermore, ets1 was determined to associate with KMT5A. High glucose attenuated KMT5A levels and histone H4 lysine 20 methylation (H4K20me1), one of the downstream targets of KMT5A. KMT5A upregulation suppressed high glucose-induced PFN2 levels and EndMT. sh-KMT5A-mediated EndMT was counteracted by si-PFN2. Furthermore, H4K20me1 and ets1 occupied the PFN2 promoter region. sh-KMT5A cooperated with ets1 overexpression to activate PFN2 promoter activity. Our in vivo study demonstrated that KMT5A was reduced, while ets1 was augmented, in glomerular endothelial cells of DN patients and rats. Conclusions The present study indicated that ets1 cooperated with KMT5A to transcribe PFN2, thus contributing to hyperglycemia-induced EndMT in the glomerular endothelial cells of DN patients and rats. Trial registration ChiCTR, ChiCTR2000029425. 2020/1/31, http://www.chictr.org.cn/showproj.aspx?proj=48548

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Section: Discussionsupporting

confidence: 72%

ets1 associates with KMT5A to participate in high glucose-mediated EndMT via upregulation of PFN2 expression in diabetic nephropathy

Zhong

et al. 2021

Mol Med

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“…For example, in a tissue-based study, CAPN6 was not detected in normal cervical squamous epithelium, but its expression was observed in low-grade and increased further in high-grade squamous cervical intraepithelial lesions [ 24 ]. KDM3A is an epigenetic regulator that has been found to be highly expressed in cervical cancer tissues and involved in cervical cancer progression [ 25 ]. P4HA1 was included in a five-gene signature to predict cervical cancer prognosis [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R

Archer

Seffernick

Sun

et al. 2022

Stats

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The stage of cancer is a discrete ordinal response that indicates the aggressiveness of disease and is often used by physicians to determine the type and intensity of treatment to be administered. For example, the FIGO stage in cervical cancer is based on the size and depth of the tumor as well as the level of spread. It may be of clinical relevance to identify molecular features from high-throughput genomic assays that are associated with the stage of cervical cancer to elucidate pathways related to tumor aggressiveness, identify improved molecular features that may be useful for staging, and identify therapeutic targets. High-throughput RNA-Seq data and corresponding clinical data (including stage) for cervical cancer patients have been made available through The Cancer Genome Atlas Project (TCGA). We recently described penalized Bayesian ordinal response models that can be used for variable selection for over-parameterized datasets, such as the TCGA-CESC dataset. Herein, we describe our ordinalbayes R package, available from the Comprehensive R Archive Network (CRAN), which enhances the runjags R package by enabling users to easily fit cumulative logit models when the outcome is ordinal and the number of predictors exceeds the sample size, P>N, such as for TCGA and other high-throughput genomic data. We demonstrate the use of this package by applying it to the TCGA cervical cancer dataset. Our ordinalbayes package can be used to fit models to high-dimensional datasets, and it effectively performs variable selection.

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“…For example, in a tissue-based study, CAPN6 was not detected in normal cervical squamous epithelium but its expression was observed in low-grade and increased further in high-grade squamous cervical intraepithelial lesions [23]. KDM3A is an epigenetic regulator that has been found to be highly expressed in cervical cancer tissues and involved in cervical cancer progression [24]. P4HA1 was included in a five-gene signature to predict cervical cancer prognosis [25].…”

Section: Resultsmentioning

confidence: 99%

Ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R

Archer¹,

Seffernick²,

Sun³

et al. 2022

Preprint

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Stage of cancer is a discrete ordinal response that indicates aggressiveness of disease and is often used by physicians to determine the type and intensity of treatment to be administered. For example, the FIGO stage in cervical cancer is based on the size and depth of the tumor as well as the level of spread. It may be of clinical relevance to identify molecular features from high-throughput genomic assays that are associated with stage of cervical cancer, to elucidate pathways related to tumor aggressiveness, identify improved molecular features that may be useful for staging, and identify therapeutic targets. High-throughput RNA-Seq data and corresponding clinical data (including stage) for cervical cancer patients has been made available through The Cancer Genome Atlas Project (TCGA). We recently described penalized Bayesian ordinal response models that can be used for variable selection for over-parameterized datasets such as the TCGA-CESC dataset. Herein, we describe our ordinalbayes R package, available from the Comprehensive R Archive Network (CRAN), which is capable of fitting cumulative logit models when the outcome is ordinal and the number of predictors exceeds the sample size, P>N, such as for TCGA data. We demonstrate use of this package through application to TCGA cervical cancer dataset. Our ordinalbayes package can be used to fit models to high-dimensional dataset and effectively performs variable selection.

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<p>Histone Demethylase <em>KDM3A</em> Promotes Cervical Cancer Malignancy Through the <em>ETS1</em>/KIF14/Hedgehog Axis</p>

Cited by 20 publications

References 42 publications

ets1 associates with KMT5A to participate in high glucose-mediated EndMT via upregulation of PFN2 expression in diabetic nephropathy

ets1 associates with KMT5A to participate in high glucose-mediated EndMT via upregulation of PFN2 expression in diabetic nephropathy

ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R

Ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R

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