&lt;p&gt;C14orf159 suppresses gastric cancer cells&amp;rsquo; invasion and proliferation by inactivating ERK signaling&lt;/p&gt;

Zhu, Yanmei; Li, Qiang; Gao, Xiaozhuo; Meng, Xiao Wen; Sun, Lili; Yu, Shichong; Lu, En-Tian; Zhang, Yong

doi:10.2147/cmar.s176771

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…The protein is d -glutamate cyclase that converts d -glutamate to 5-oxo- d -proline [36] . There is also evidence that loss of C14orf159 is associated with the progression of gastric cancer [37] . The product of AKNA may act as a transcription factor that specifically activates the expression of the CD40 receptor and its ligand CD40L/CD154, two cell surface molecules on lymphocytes that are critical for antigen-dependent-B-cell development [38] .…”

Section: Resultsmentioning

confidence: 99%

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values

Zhang

Pan

et al. 2020

eBioMedicine

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Background Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profiling has been utilized for identifying subclasses of sepsis, but the clinical utility of these subclasses was limited because of the classification instability, and the lack of a robust class prediction model with extensive external validation. The study aimed to develop a parsimonious class model for the prediction of class membership and validate the model for its prognostic and predictive capability in external datasets. Methods The Gene Expression Omnibus (GEO) and ArrayExpress databases were searched from inception to April 2020. Datasets containing whole blood gene expression profiling in adult sepsis patients were included. Autoencoder was used to extract representative features for k-means clustering. Genetic algorithms (GA) were employed to derive a parsimonious 5-gene class prediction model. The class model was then applied to external datasets ( n = 780) to evaluate its prognostic and predictive performance. Findings A total of 12 datasets involving 1613 patients were included. Two classes were identified in the discovery cohort ( n = 685). Class 1 was characterized by immunosuppression with higher mortality than class 2 (21.8% [70/321] vs. 12.1% [44/364]; p < 0.01 for Chi-square test). A 5-gene class model (C14orf159, AKNA, PILRA, STOM and USP4) was developed with GA. In external validation cohorts, the 5-gene class model (AUC: 0.707; 95% CI: 0.664 – 0.750) performed better in predicting mortality than sepsis response signature (SRS) endotypes (AUC: 0.610; 95% CI: 0.521 – 0.700), and performed equivalently to the APACHE II score (AUC: 0.681; 95% CI: 0.595 – 0.767). In the dataset E-MTAB-7581, the use of hydrocortisone was associated with increased risk of mortality (OR: 3.15 [1.13, 8.82]; p = 0.029) in class 2. The effect was not statistically significant in class 1 (OR: 1.88 [0.70, 5.09]; p = 0.211). Interpretation Our study identified two classes of sepsis that showed different mortality rates and responses to hydrocortisone therapy. Class 1 was characterized by immunosuppression with higher mortality rate than class 2. We further developed a 5-gene class model to predict class membership. Funding The study was funded by the National Natural Science Foundation of China (Grant No. 81,901,929).

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Section: Resultsmentioning

confidence: 99%

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values

Zhang

Pan

et al. 2020

eBioMedicine

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“…Likewise, it was reflected in the results of colony formation and transwell experiments that ANO6 overexpression will substantially promote cell proliferation and invasion and ANO6 knockdown or overexpression works well on the regulation of the proliferation and invasion of glioma cells. Since ERK, being an important extracellular signal-regulated kinase, is considered as a tumor-promoting gene and is closely associated with cell proliferation, apoptosis and differentiation,24 ERK is over-activated in various cancers such as lung cancer,25 stomach cancer,26 liver cancer,27 glioma28 and breast cancer29 to promote the development of cancer. Just as shown in some studies, ERK inhibitors can effectively inhibit the translocation of ERK by reducing phosphorylation of ERK so as to effectively treat Melanocytoma 30,31.…”

Section: Discussionmentioning

confidence: 99%

<p>ANO6 promotes cell proliferation and invasion in glioma through regulating the ERK signaling pathway</p>

Xuan¹,

Wang²,

Xie³

2019

OTT

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Anoctamin6 (ANO6) plays a crucial role in several cancers, whereas the specific role of ANO6 in glioblastoma is unclear. Methods: Kaplan-Meier survival analysis was used to analysis the correlation between ANO6 and survival rate of patients with glioblastoma. Univariate Cox regression analysis was used to analysis the correlation among ANO6 expression level,and age, gender, WHO and overall survival rate. Immunohistocemical technique, RT-PCR and western blot were used to dected the ANO6 expression. CCK8, colony formation and transwell were used to detected cell viability, cell proliferation and cell invasion in glioblastoma cells transfected with sh-ANO6 and ANO6 overexpression. In addition, after SHG-44 cells trasfected with ANO6 overexpression were ERK inhibitor (PD98059), CCK8, colony formation and transwell were used to detected cell viability, cell proliferation and cell invasion. Western blot was used to detected ERK protein level and the phosphorylation level of ERK in T89G and U87MG cells tranfected wih sh-ANO6. Results: The results indicated that the ANO6 expression level was significantly associated with patients' age and tumor stage. Univariate Cox regression analysis showed that the ANO6 expression level, age, gender and tumor stage were not related to the overall survival rate. ANO6 inhibition significantly suppressed the viability, invasion and the ability of colony formation in glioma cells, while ANO6 overexpression led to the opposite results in SHG-44 cells. ANO6 knockdown strongly inhibits the phosphorylation level and nuclear translocation of extracellular signal-regulated kinase (ERK) protein to inhibit ERK signaling. ERK inhibitor significantly decreased the cell proliferation and invasion in SHG-44 cells transfected with sh-ANO6. Conclusion: This study revealed that ANO6 activited ERK signaling pathway through promoting the nuclear translocation of ERK to increase the proliferation and invasion of glioblastoma cells.

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“…It can work as a switch in regulating multiple signaling pathways, including extracellular-signal-regulated kinase (ERK; Agudo-Ibanez, Crespo, & Casar, 2017), JNK (Ye et al, 2019), phosphoinositide 3-kinase/AKT (Li, Sun, Sun, & Yin, 2019), mTOR (Zhong et al, 2019), and so forth. It is noteworthy that, ERK activation plays a determining role in the invasive and growth of gastric cancer (Yoo et al, 2002;Zhu et al, 2019). Abnormal alteration of Ras-ERK signaling leads to the initiation and progression of gastric cancer (Gonzalez-Hormazabal & Musleh, 2018).…”

Section: R E T R a C T E Dmentioning

confidence: 99%

Retraction

Tian

Chen

et al. 2020

Journal Cellular Physiology

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HRas mutation rate is high in gastric cancer while the deep mechanism of HRasʼs oncogenic effects is unclear. The current work designed to link HRas signaling with H1.4S27ph in gastric cancer to decode the unclear mechanism in epigenetics standpoint. Ras Q61R/T35S expressing plasmids were transfected into SNU-16 cells.Western blot was conducted to check H1.4S27ph and extracellular-signal-regulatedtetrazolium bromide, colony formation, and transwell assays were carried out to see the effects of H1.4S27ph on SNU-16 cells phenotype. Chromatin immunoprecipitation was utilized to detect the interaction between H1.4S27ph and Ras downstream genes. Further, the enzymes responsible for H1.4S27 phosphorylation were studied by a quantitative reverse transcription-polymerase chain reaction and western blot. Ras mutation repressed H1.4 phosphorylation at Ser27 accompanied by ERK1/2 activation. H1.4S27ph reduced SNU-16 cells viability, colony formation, and migration. Meanwhile, H1.4S27ph regulated the transcription of Ras downstream genes. Ras-ERK1/2 signaling inhibited H1.4S27ph via inhibiting the activity of Aurora B. Aurora B exhibited H1.4S27ph-like effects on inhibiting SNU-16 cells viability, migration, and S-phase arrest. Further, Ras-ERK1/2 signaling degenerated Aurora B via mediating MDM2. H1.4S27ph worked as an anti-gastric cancer factor. It can be inhibited by activation of Ras-ERK1/2 signaling. Ras-ERK1/2 signaling repressed H1.4S27ph via MDM2-dependent degradation of Aurora B.

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<p>C14orf159 suppresses gastric cancer cells’ invasion and proliferation by inactivating ERK signaling</p>

Cited by 9 publications

References 21 publications

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values

<p>ANO6 promotes cell proliferation and invasion in glioma through regulating the ERK signaling pathway</p>

Retraction

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