CHAF1B promotes proliferation and reduces apoptosis in 95‑D lung cancer cells and predicts a poor prognosis in non‑small cell lung cancer

Duan, Yan; Liu, Tanzhen; Li, Shengwen; Huang, Mengyi; Li, Xiaoyü; Zhao, Hui; Li, Jianqiang

doi:10.3892/or.2019.6994

Cited by 9 publications

(12 citation statements)

References 29 publications

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“…The p150 subunit was highly expressed in HCC tissue and epithelial ovarian cancer where it was associated a poor prognosis (203,204). Similar data were obtained regarding the p60 subunit in prostate and lung cancers (205,206), however virtually no information is available on p48, as it has not yet been identified in humans. As informative as these data may be, they do not address the gaping hole of how and why these CAF1 subunits are involved.…”

Section: Remodeling Our Understanding Of Chromatin Machinery In Emtmentioning

confidence: 57%

Unresolved Complexity in the Gene Regulatory Network Underlying EMT

Lavin

Tiwari

2020

Front. Oncol.

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Epithelial to mesenchymal transition (EMT) is the process whereby a polarized epithelial cell ceases to maintain cell-cell contacts, loses expression of characteristic epithelial cell markers, and acquires mesenchymal cell markers and properties such as motility, contractile ability, and invasiveness. A complex process that occurs during development and many disease states, EMT involves a plethora of transcription factors (TFs) and signaling pathways. Whilst great advances have been made in both our understanding of the progressive cell-fate changes during EMT and the gene regulatory networks that drive this process, there are still gaps in our knowledge. Epigenetic modifications are dynamic, chromatin modifying enzymes are vast and varied, transcription factors are pleiotropic, and signaling pathways are multifaceted and rarely act alone. Therefore, it is of great importance that we decipher and understand each intricate step of the process and how these players at different levels crosstalk with each other to successfully orchestrate EMT. A delicate balance and fine-tuned cooperation of gene regulatory mechanisms is required for EMT to occur successfully, and until we resolve the unknowns in this network, we cannot hope to develop effective therapies against diseases that involve aberrant EMT such as cancer. In this review, we focus on data that challenge these unknown entities underlying EMT, starting with EMT stimuli followed by intracellular signaling through to epigenetic mechanisms and chromatin remodeling.

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Section: Remodeling Our Understanding Of Chromatin Machinery In Emtmentioning

confidence: 57%

Unresolved Complexity in the Gene Regulatory Network Underlying EMT

Lavin

Tiwari

2020

Front. Oncol.

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“…It has been confirmed that CHAF1B is overexpressed in laryngeal cancer, squamous cell carcinoma [26] ,high-grade gliomas,prostatic cancer and lung cancer, and its high expression leads to a shorter survival period for high-grade gliomas [27] ,prostatic cancer [28] and patients lung cancer. Cellular experiments confirmed that knockdown of CHAF1B inhibits the proliferation and invasion of cancer cells and inhibits the growth of xenografts in vitro [29][30][31]. Recent studies show that CHAF1B acts as a novel marker of tumor proliferation and prognosis.…”

Section: Discussionmentioning

confidence: 70%

Ubiquitin ligase CHAF1B induces cisplatin resistance in lung adenocarcinoma by promoting NCOR2 degradation

Gong

et al. 2020

Cancer Cell Int

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Background: Lung cancer is the most common malignant tumor in the world. The Whole-proteome microarray showed that ubiquitin ligase chromatin assembly factor 1 subunit B (CHAF1B) expression in A549/DDP cells is higher than in A549 cells. Our study explored the molecular mechanism of CHAF1B affecting cisplatin resistance in lung adenocarcinoma (LUAD). Methods: Proteome microarray quantify the differentially expressed proteins between LUAD cell line A549 and its cisplatin-resistant strain A549/DDP. Quantitative real-time quantitative polymerase chain reaction (qRT-PCR) and Western blot (WB) confirmed the CHAF1B expression. Public databases analyzed the prognosis of LUAD patients with varied LUAD expression followed by the substrates prediction of CHAF1B. Public databases showed that nuclear receptor corepressor 2 (NCOR2) may be substrates of CHAF1B. WB detected that CHAF1B expression affected the expression of NCOR2. Cell and animal experiments and clinical data detected function and integrating mechanism of CHAF1B compounds. Results: Proteome chips results indicated that CHAF1B, PPP1R13L, and CDC20 was higher than A549 in A549/DDP. Public databases showed that high expression of CHAF1B, PPP1R13L, and CDC20 was negatively correlated with prognosis in LUAD patients. PCR and WB results indicated higher CHAF1B expression in A549/DDP cells than that in A549 cells. NCOR2 and PPP5C were confirmed to be substrates of CHAF1B. CHAF1B knockdown significantly increased the sensitivity of cisplatin in A549/DDP cells and the upregulated NCOR2 expression. CHAF1B and NCOR2 are interacting proteins and the position of interaction between CHAF1B and NCOR2 was mainly in the nucleus. CHAF1B promotes ubiquitination degradation of NCOR2. Cells and animal experiments showed that under the action of cisplatin, after knockdown of CHAF1B and NCOR2 in A549/DDP group compared with CHAF1B knockdown alone, the cell proliferation and migratory ability increased and apoptotic rate decreased, and the growth rate and size of transplanted tumor increased significantly. Immunohistochemistry suggested that Ki-67 increased, while apoptosis-related indicators caspase-3 decreased significantly. Clinical data showed that patients with high expression of CHAF1B are more susceptible to cisplatin resistance.

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“…Seven mRNAs and two lncRNAs were finally selected and further used to establish survival predictive models (mRNAs: CDC25A, CDK6, CHAF1B, CKS2, CORO1C, WEE1, and KIF23; lncRNAs: SGMS1-AS1 and LINC00689). Besides, after reviews of these genes in the model, we found that all of the seven genes have been associated with multiple processes of tumor, where CDC25A, CDK6, and KIF23 have been reported to directly participate in the pathophysiological process of MPM (31)(32)(33). The expression of CDC25A has been reported to correlate with lymph-node spread of MPM (33).…”

Section: Discussionmentioning

confidence: 89%

“…Although the other four genes have not been directly linked to MPM, they are widely involved in the development of cancers. CHAF1B plays a considerable role in leukemia pathogenesis and proliferation of the lung cancer and the prognosis of some cancers (32,33). CKS2 and CORO1C participate in the growth, invasion, and prognosis of several types of cancers (35)(36)(37)(38).…”

Section: Discussionmentioning

confidence: 99%

Combined Analysis of RNA Sequence and Microarray Data Reveals a Competing Endogenous RNA Network as Novel Prognostic Markers in Malignant Pleural Mesothelioma

et al. 2021

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Malignant pleural mesothelioma (MPM) is a highly aggressive cancer with short survival time. Unbalanced competing endogenous RNAs (ceRNAs) have been shown to participate in the tumor pathogenesis and served as biomarkers for the clinical prognosis. However, the comprehensive analyses of the ceRNA network in the prognosis of MPM are still rarely reported. In this study, we obtained the transcriptome data of the MPM and the normal samples from TCGA, EGA, and GEO databases and identified the differentially expressed (DE) mRNAs, lncRNAs, and miRNAs. The functions of the prognostic genes and the overlapped DEmRNAs were further annotated by the multiple enrichment analyses. Then, the targeting relationships among lncRNA–miRNA and miRNA–mRNA were predicted and calculated, and a prognostic ceRNA regulatory network was established. We included the prognostic 73 mRNAs and 13 miRNAs and 26 lncRNAs into the ceRNA network. Moreover, 33 mRNAs, three miRNAs, and seven lncRNAs were finally associated with prognosis, and a model including seven mRNAs, two lincRNAs, and some clinical factors was finally established and validated by two independent cohorts, where CDK6 and SGMS1-AS1 were significant to be independent prognostic factors. In addition, the identified co-expressed modules associated with the prognosis were overrepresented in the ceRNA network. Multiple enrichment analyses showed the important roles of the extracellular matrix components and cell division dysfunction in the invasion of MPM potentially. In summary, the prognostic ceRNA network of MPM was established and analyzed for the first time and these findings shed light on the function of ceRNAs and revealed the potential prognostic and therapeutic biomarkers of MPM.

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CHAF1B promotes proliferation and reduces apoptosis in 95‑D lung cancer cells and predicts a poor prognosis in non‑small cell lung cancer

Cited by 9 publications

References 29 publications

Unresolved Complexity in the Gene Regulatory Network Underlying EMT

Unresolved Complexity in the Gene Regulatory Network Underlying EMT

Ubiquitin ligase CHAF1B induces cisplatin resistance in lung adenocarcinoma by promoting NCOR2 degradation

Combined Analysis of RNA Sequence and Microarray Data Reveals a Competing Endogenous RNA Network as Novel Prognostic Markers in Malignant Pleural Mesothelioma

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