KLHL39 suppresses colon cancer metastasis by blocking KLHL20-mediated PML and DAPK ubiquitination

Chen, H Y; Hu, Jian; Chen, T H; Lin, Yu‐Ching; Liu, X; Lin, Meng-Hsuan; Lang, Yaw-Dong; Yen, Yun; Chen, R H

doi:10.1038/onc.2014.435

Cited by 32 publications

(30 citation statements)

References 40 publications

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“…Here, we show that the silencing of LncKLHDC7B led to resistance to cell death. Similarly, it has been reported that silencing of members of the Kelch family leads to death resistance by anoikis and is associated with lower survival in colorectal cancer (Chen et al ., ).…”

Section: Discussionmentioning

confidence: 97%

Expression of long non‐coding RNA ENSG00000226738 (LncKLHDC7B) is enriched in the immunomodulatory triple‐negative breast cancer subtype and its alteration promotes cell migration, invasion, and resistance to cell death

et al. 2019

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Triple negative breast cancer ( TNBC ) represents an aggressive phenotype with poor prognosis compared with ER , PR, and HER 2‐positive tumors. TNBC is a heterogeneous disease, and gene expression analysis has identified seven molecular subtypes. Accumulating evidence demonstrates that long non‐coding RNA (lnc RNA ) are involved in regulation of gene expression and cancer biology, contributing to essential cancer cell functions. In this study, we analyzed the expression profile of lnc RNA in TNBC subtypes from 156 TNBC samples, and then characterized the functional role of Lnc KLHDC 7B ( ENSG 00000226738 ). A total of 710 lnc RNA were found to be differentially expressed between TNBC subtypes, and a subset of these altered lnc RNA were independently validated. We discovered that Lnc KLHDC 7B ( ENSG 00000226738 ) acts as a transcriptional modulator of its neighboring coding gene KLHDC 7B in the immunomodulatory subtype. Furthermore, Lnc KLHDC 7B knockdown enhanced migration and invasion, and promoted resistance to cellular death. Our findings confirmed the contribution of Lnc KLHDC 7B to induction of apoptosis and inhibition of cell migration and invasion, suggesting that TNBC tumors with enrichment of Lnc KLHDC 7B may exhibit distinct regulatory activity, or that this may be a generalized process in breast cancer. Additionally, in silico analysis confirmed for the first time that the low expression of KLHDC 7B and Lnc KLHDC 7B is associated with poor prognosis in patients with breast cancer.

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Section: Discussionmentioning

confidence: 97%

Expression of long non‐coding RNA ENSG00000226738 (LncKLHDC7B) is enriched in the immunomodulatory triple‐negative breast cancer subtype and its alteration promotes cell migration, invasion, and resistance to cell death

et al. 2019

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“…We assessed the protein expression of WDR4 and PML in a cohort of 120 lung cancer patients. Immunohistochemical analydegradation has been observed in a number of cancer types (14,(18)(19)(20)(21)(22), and the ubiquitin ligases cullin 3-kelch-like family member 20 (CUL3-KLHL20) and ubiquitin protein ligase E3A (E6AP) are responsible for PML destruction in certain cancer types (18,22). However, the ubiquitin ligase that mediates PML degradation in lung cancer remains elusive, and the molecular mechanism for PML degradation in tumors has not been completely understood.…”

Section: Wdr4mentioning

confidence: 99%

Ubiquitination of tumor suppressor PML regulates prometastatic and immunosuppressive tumor microenvironment

Wang

Chen

Chang

et al. 2017

Journal of Clinical Investigation

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“…With respect to CRC pattern 1, that is the only one showing up-regulation, we found reports of some novel genes included in this pattern that can be related to the progression of the disease, like for example squalene epoxidase (SQLE) that is up-regulated in breast cancer and indicates poor clinical outcome in early stages of this disease [29]. Another very interesting protein found in this CRC pattern is KLHL20, a BTB-kelch protein that is involved colon cancer metastasis since it is a substrate adaptor of CUL3 E3 ligase complex catalyzing the ubiquitination of DAPK (death-associated protein kinase) a well-known tumor suppressor [30]. …”

Section: Resultsmentioning

confidence: 99%

Identification of expression patterns in the progression of disease stages by integration of transcriptomic data

et al. 2016

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BackgroundIn the study of complex diseases using genome-wide expression data from clinical samples, a difficult case is the identification and mapping of the gene signatures associated to the stages that occur in the progression of a disease. The stages usually correspond to different subtypes or classes of the disease, and the difficulty to identify them often comes from patient heterogeneity and sample variability that can hide the biomedical relevant changes that characterize each stage, making standard differential analysis inadequate or inefficient.ResultsWe propose a methodology to study diseases or disease stages ordered in a sequential manner (e.g. from early stages with good prognosis to more acute or serious stages associated to poor prognosis). The methodology is applied to diseases that have been studied obtaining genome-wide expression profiling of cohorts of patients at different stages. The approach allows searching for consistent expression patterns along the progression of the disease through two major steps: (i) identifying genes with increasing or decreasing trends in the progression of the disease; (ii) clustering the increasing/decreasing gene expression patterns using an unsupervised approach to reveal whether there are consistent patterns and find genes altered at specific disease stages. The first step is carried out using Gamma rank correlation to identify genes whose expression correlates with a categorical variable that represents the stages of the disease. The second step is done using a Self Organizing Map (SOM) to cluster the genes according to their progressive profiles and identify specific patterns. Both steps are done after normalization of the genomic data to allow the integration of multiple independent datasets. In order to validate the results and evaluate their consistency and biological relevance, the methodology is applied to datasets of three different diseases: myelodysplastic syndrome, colorectal cancer and Alzheimer’s disease. A software script written in R, named genediseasePatterns, is provided to allow the use and application of the methodology.ConclusionThe method presented allows the analysis of the progression of complex and heterogeneous diseases that can be divided in pathological stages. It identifies gene groups whose expression patterns change along the advance of the disease, and it can be applied to different types of genomic data studying cohorts of patients in different states.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1290-4) contains supplementary material, which is available to authorized users.

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KLHL39 suppresses colon cancer metastasis by blocking KLHL20-mediated PML and DAPK ubiquitination

Cited by 32 publications

References 40 publications

Expression of long non‐coding RNA ENSG00000226738 (LncKLHDC7B) is enriched in the immunomodulatory triple‐negative breast cancer subtype and its alteration promotes cell migration, invasion, and resistance to cell death

Expression of long non‐coding RNA ENSG00000226738 (LncKLHDC7B) is enriched in the immunomodulatory triple‐negative breast cancer subtype and its alteration promotes cell migration, invasion, and resistance to cell death

Ubiquitination of tumor suppressor PML regulates prometastatic and immunosuppressive tumor microenvironment

Identification of expression patterns in the progression of disease stages by integration of transcriptomic data

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