Lung Adenocarcinoma Cancer Cell Lines Research Articles

Antioxidant and Anticancer Activities of Wampee (Clausena lansium (Lour.) Skeels) Peel

Antioxidant activities of wampee peel extracts using five different solvents (ethanol, hexane, ethyl acetate, butanol and water) were determined by using in-vitro antioxidant models including total antioxidant capability, 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, reducing power, and superoxide scavenging activity. Ethyl acetate fraction (EAF) exhibited the highest antioxidant activity compared to other fractions, even higher than synthetic antioxidant butylated hydroxyl toluene (BHT). In addition, the EAF exhibited strong anticancer activities against human gastric carcinoma (SGC-7901), human hepatocellular liver carcinoma (HepG-2) and human lung adenocarcinoma (A-549) cancer cell lines, higher than cisplatin, a conventional anticancer drug. The total phenolic content of wampee fraction was positively correlated with the antioxidant activity. This is the first report on the antioxidant and anticancer activities of the wampee peel extract. Thus, wampee peel can be used potentially as a readily accessible source of natural antioxidants and a possible pharmaceutical supplement.

Effects of matrine on the growth inhibition, c-myc and hTERT protein expression in human adenocarcinoma lung cancer cell line A549.

It was reported that telomerase was associated with the oncogenesis and progression of cancer, and to be the common targets of cancer therapy. The mechanism of matrine on lung cancer in vitro is not clear. We studied the effect of matrine on growth of human lung adenocarcinoma A549 cells and the mechanism related with telomerase. MTT was used for measuring A549 cells viability, Hoechst 33342-propidium iodide fluorescent staining for observing apoptotic cells, flow cytometry (FCM) for analyzing cell cycle and apoptosis, and immunocytochemistry for measuring the protein expressions of c-myc and hTERT in A549 cells. Matrine inhibited the proliferation of A549 cells with a time-dose-dependent manner (P <0.05). Hoechst 33342-propidium iodide staining showed apoptotic cells with chromatin condensation and fragmentation of nuclei. FCM analysis indicated elevating rate of cells in G0/G1 phase, lowering rate of that in S phase and the highering apoptotic rate. The levels of c-myc and hTERT protein expression in the matrine group was lower than that in the control group (P <0.05), and AOD of c-myc showed positive correlation with AOD of hTERT (r =0.633, P <0.01). The inhibitory effect of matrine on A549 cells may be related to the lower expression of c-myc and hTERT.

Effect of quercetin on the expression and growth of caspase-3 in lung adenocarcinoma cancer cell line A549.

To study the influence of Quercetin in the expression of caspase-3 in Lung Adenocarcinoma Cancer cell line A549. The mRNA expression of caspase-3 in A549 Cells was detected by RT-PCR , and the protein expression was detected by Western blot. The mRNA and protein expressions of caspase-3 was enhanced by Quercetin in dose- and time-dependent manners. The enhancement effects of Quercetin on caspase-3 in A549 cells may provide promising therapy of tumor.

Phorbol Ester-induced G1 Phase Arrest Selectively Mediated by Protein Kinase Cδ-dependent Induction of p21

Although protein kinase C (PKC) has been widely implicated in the positive and negative control of proliferation, the underlying cell cycle mechanisms regulated by individual PKC isozymes are only partially understood. In this report, we show that PKCdelta mediates phorbol ester-induced G1 arrest in lung adenocarcinoma cells and establish an essential role for this novel PKC in controlling the expression of the cell cycle inhibitor p21. Activation of PKC with phorbol 12-myristate 13-acetate (PMA) in early G1 phase impaired progression of lung adenocarcinoma cells into S phase, an effect that was completely abolished by specific depletion of PKCdelta, but not PKCalpha. Although the PKC effect was unrelated to the inhibition of cyclin D1 expression, PKC activation significantly up-regulated p21 and down-regulated Rb hyperphosphorylation and cyclin A expression. Elevations in p21 mRNA and protein by PMA were mediated by PKCdelta but not PKCalpha. Studies using luciferase reporters also revealed an essential role for PKCdelta in the PMA-induced inhibition of Rb-dependent cyclin A promoter activity. Finally, we showed that the cell cycle inhibitory effect of PKCdelta is greatly attenuated by RNA interference-mediated knock-down of p21. Our results identify a novel link between PKCdelta and G1 arrest via p21 up-regulation and highlight the complexities in the downstream effectors of PKC isozymes in the context of cell cycle progression and proliferation.

Using Nuclear Morphometry to Discriminate the Tumorigenic Potential of Cells: A Comparison of Statistical Methods

Abstract Despite interest in the use of nuclear morphometry for cancer diagnosis and prognosis as well as to monitor changes in cancer risk, no generally accepted statistical method has emerged for the analysis of these data. To evaluate different statistical approaches, Feulgen-stained nuclei from a human lung epithelial cell line, BEAS-2B, and a human lung adenocarcinoma (non-small cell) cancer cell line, NCI-H522, were subjected to morphometric analysis using a CAS-200 imaging system. The morphometric characteristics of these two cell lines differed significantly. Therefore, we proceeded to address the question of which statistical approach was most effective in classifying individual cells into the cell lines from which they were derived. The statistical techniques evaluated ranged from simple, traditional, parametric approaches to newer machine learning techniques. The multivariate techniques were compared based on a systematic cross-validation approach using 10 fixed partitions of the data to compute the misclassification rate for each method. For comparisons across cell lines at the level of each morphometric feature, we found little to distinguish nonparametric from parametric approaches. Among the linear models applied, logistic regression had the highest percentage of correct classifications; among the nonlinear and nonparametric methods applied, the Classification and Regression Trees model provided the highest percentage of correct classifications. Classification and Regression Trees has appealing characteristics: there are no assumptions about the distribution of the variables to be used, there is no need to specify which interactions to test, and there is no difficulty in handling complex, high-dimensional data sets containing mixed data types.