This study aimed to evaluate the biological role of geranylgeranyl diphosphate synthase (GGPPS) in the progression of lung adenocarcinoma. GGPPS expression was detected in lung adenocarcinoma tissues by qRT‐PCR, tissue microarray (TMA) and western blotting. The relationships between GGPPS expression and the clinicopathological characteristics and prognosis of lung adenocarcinoma patients were assessed. GGPPS was down‐regulated in SPCA‐1, PC9 and A549 cells using siRNA and up‐regulated in A549 cells using an adenoviral vector. The biological roles of GGPPS in cell proliferation, apoptosis, migration and invasion were determined by MTT and colony formation assays, flow cytometry, and transwell and wound‐healing assays, respectively. In addition, the regulatory roles of GGPPS on the expression of several epithelial‐mesenchymal transition (EMT) markers were determined. Furthermore, the Rac1/Cdc42 prenylation was detected after knockdown of GGPPS in SPCA‐1 and PC9 cells. GGPPS expression was significantly increased in lung adenocarcinoma tissues compared to that in adjacent normal tissues. Overexpression of GGPPS was correlated with large tumours, high TNM stage, lymph node metastasis and poor prognosis in patients. Knockdown of GGPPS inhibited the migration and invasion of lung adenocarcinoma cells, but did not affect cell proliferation and apoptosis. Meanwhile, GGPPS inhibition significantly increased the expression of E‐cadherin and reduced the expression of N‐cadherin and vimentin in lung adenocarcinoma cells. In addition, the Rac1/Cdc42 geranylgeranylation was reduced by GGPPS knockdown. Overexpression of GGPPS correlates with poor prognosis of lung adenocarcinoma and contributes to metastasis through regulating EMT.
Background Protein regulator of cytokinesis 1 (PRC1) has been reported to play important role in the pathogenesis of various cancers. However, its role in colon cancer has not been studied. Here, we aimed to investigate the biological functions and potential mechanism of PRC1 in colon cancer. Methods The expression level of PRC1 in colon cancer tissues and cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting, and immunohistochemical (IHC) staining of a tissue microarray (TMA). Furthermore, colon cancer cell lines HCT116 and SW480 were treated with short hairpin RNAs against PRC1. The biological function of PRC1 was determined by MTT proliferation, colony formation assay, cell cycle, and apoptosis assays. Then, an in vivo tumor formation assay was conducted to explore the effects of PRC1 on tumor growth. Results The mRNA and protein expression levels of PRC1 were highly expressed in colon cancer tissues and cell lines. PRC1 expression was associated with clinicopathological characteristics and overall survival of patients with colon cancer. Knockdown of PRC1 could decrease proliferation and colony forming ability of colon cancer cells, as well as arrested more cells at G2/M phase and promoted cell apoptosis. In cancer cells, the expression pattern of protein regulators included in cell cycle and apoptosis progress were reverted by PRC1 down-regulation. Additionally, PRC1 down-regulation could suppress colon tumor growth and differentiation. Conclusions We confirmed that PRC1 was overexpressed in colon cancer and was associated with poor prognosis of colon cancer patients. PRC1 down-regulation could arrest cell cycle at G2/M stage, inhibit proliferation, and elicit apoptosis. These findings showed the potential of PRC1 to be used for therapeutic approaches in colon cancer.
The neutrophil-to-lymphocyte ratio is used to reflect body's inflammatory status with prognostic value in different cancers. We aimed to investigate the influence of preoperative NLR in the prognosis of CRLM patients receiving surgery using meta-analysis. Data in Cochrane Library, PubMed, Embase, and Web of Science databases created before October 2022 were recruited. Meta-analysis was carried out with RevMan 5.3 and Stata16 software, and the primary outcome indicators included overall survival (OS), and secondary outcome indicators included disease-free survival (DFS) and relapse-free survival (RFS). The pooled risk ratio (HR) and 95% confidence interval (CI) for each outcome indicator were determined using random-effects models or fixed-effects models. The pooled odds ratio (OR) and corresponding 95% confidence intervals (CI) for NLR and clinicopathological characteristics were determined with a fixed-effects model. 18 papers published between 2008 and 2022 (3184 patients in total) were included. The pooled analysis found that high preoperative NLR was correlated with poor OS (multivariate HR = 1.83, 95% CI = 1.61–2.08, p < 0.01), DFS (multivariate HR = 1.78, 95% CI = 1.16–2.71, p < 0.01) and RFS (multivariate HR = 1.46, 95% CI = 1.15–1.85, p < 0.01), but NLR was not related to clinicopathological features of CRLM patients correlation. In conclusion, NLR is an independent risk factor for poor prognosis in patients with CRLM. More large-scale clinical researches are required in the future to demonstrate the inclusion of preoperative NLR as a prognostic indicator for CRLM patients to guide postoperative adjuvant chemotherapy.
We summarize some results from an extensive performance comparison of the procedures MSER-5 and N-Skart for handling the simulation start-up problem. We assume a fixed-length simulation-generated time series from which point and confidence-interval (CI) estimators of the steady-state mean are sought. MSER-5 uses the data-truncation point that minimizes the half-length of the usual batch-means CI computed from the truncated data set. N-Skart uses a randomness test to determine the data-truncation point beyond which spaced batch means are approximately independent of each other and the simulation's initial condition; then using truncated nonspaced batch means, N-Skart exploits separate adjustments to the CI half-length that account for the effects on the distribution of the underlying Student's t-statistic arising from skewness and autocorrelation of the batch means. In most of the test problems, N-Skart's point estimator had smaller bias than that of MSER-5; moreover in all cases, N-Skart's CI estimator outperformed that of MSER-5.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.