For survival analysis, GEPIA also provides a gene normalization feature that allows the relative expression of two different genes as input. For example, when investigating gene FOXP3 in cancer survival analysis, users can also input another gene such as CD3G to normalize the expression of FOXP3. In such case, GEPIA will perform the survival analysis based on the FOXP3/CD3G relative expression levels. Furthermore, GEPIA can also present top genes that are most associated with cancer patient survival. The gene list is ranked by P-values of survival analysis based on any input cancer types.
Lung Cancer
It is one of the most common and deadly forms of cancer, with various histological subtypes and risk factors including smoking, occupational exposures, and genetic predisposition.
Effective diagnosis and treatment strategies are critical for improving patient outcomes, and ongoing research aims to advance our understanding of the molecular mechanisms driving lung cancer development and progression.
Most cited protocols related to «Lung Cancer»
For survival analysis, GEPIA also provides a gene normalization feature that allows the relative expression of two different genes as input. For example, when investigating gene FOXP3 in cancer survival analysis, users can also input another gene such as CD3G to normalize the expression of FOXP3. In such case, GEPIA will perform the survival analysis based on the FOXP3/CD3G relative expression levels. Furthermore, GEPIA can also present top genes that are most associated with cancer patient survival. The gene list is ranked by P-values of survival analysis based on any input cancer types.
The two large studies included a lung cancer set was provided with GSEA-R package [49 ] and a type 2 diabetes dataset comes from ChipperDB [51 ]. These datasets were chosen because they were originally used to validate and/or compare GSEA [3 (link),4 (link)] and PAGE [5 (link)]
The small dataset is a gene expression study from our group describing human MSC response to 8 hours of exposure to the signaling molecule BMP6. This dataset includes two experimental groups each with paired treatment and control samples, resulting in a total of 4 gene chips. We have deposited the dataset into Gene Expression Omnibus (GEO) repository (accession number GSE13604). For the use in this paper, the raw data were processed by using RMA implemented in the Bioconductor Affy package [52 (link)] with up-to-date probe set definition (.CDF file) based on Entrez Gene sequence, Hs133P_Hs_ENTREZG_8 [53 (link)]. Annotation data were retrieved from the GAIQ website [48 ]. The type 2 diabetes dataset was processed similarly from raw data files.
To visualize the performance of the various biomarkers in datasets including different number of patients, we have generated funnel plots depicting the hazard ratio (and confidence intervals) on the horizontal axis vs. the sample size on the vertical axis for each dataset. We also added an option to the online interface to simultaneously perform the analysis in each of the individual datasets. Finally, significance was set at p<0.01.
Most recents protocols related to «Lung Cancer»
Example 49
The functional activity of compounds was determined in a cell line where p70S6K is constitutively activated. Test article was dissolved in DMSO to make a 10 μM stock. PathScan® Phospho-S6 Ribosomal Protein (Ser235/236) Sandwich ELISA Kit was purchased from Cell Signaling Technology. A549 lung cancer cell line, was purchased from American Type Culture Collection. A549 cells were grown in F-12K Medium supplemented with 10% FBS. 100 μg/mL penicillin and 100 μg/mL streptomycin were added to the culture media. Cultures were maintained at 37° C. in a humidified atmosphere of 5% CO2 and 95% air. 2.0×105 cells were seeded in each well of 12-well tissue culture plates for overnight. Cells were treated with DMSO or test article (starting at 100 μM, 10-dose with 3 fold dilution) for 3 hours. The cells were washed once with ice cold PBS and lysed with 1× cell lysis buffer. Cell lysates were collected and samples were added to the appropriate wells of the ELISA plate. Plate was incubated for overnight at 4° C. 100 μL of reconstituted Phospho-S6 Ribosomal Protein (Ser235/236) Detection Antibody was added to each well and the plate was incubated at 37° C. for 1 hour. Wells were washed and 100 μl of reconstituted HRP-Linked secondary antibody was added to each well. The plate was incubated for 30 minutes at 37° C. Wash procedure was repeated and 100 μL of TMB Substrate was added to each well. The plate was incubated for 10 minutes at 37° C. 100 μL of STOP Solution was added to each well and the absorbance was read at 460 nm using Envision 2104 Multilabel Reader (PerkinElmer, Santa Clara, CA). IC50 curves were plotted and IC50 values were calculated using the GraphPad Prism 4 program based on a sigmoidal dose-response equation.
Unless otherwise noted, compounds that were tested had an IC50 of less than 50 μM in the S6K Binding assay. A=less than 0.05 μM; B=greater than 0.05 μM and less than 0.5 μM; C=greater than 0.5 μM and less than 10 μM;
Example 7
The MTT Cell Proliferation assay determines cell survival following apple stem cell extract treatment. The purpose was to evaluate the potential anti-tumor activity of apple stem cell extracts as well as to evaluate the dose-dependent cell cytotoxicity.
Principle: Treated cells are exposed to 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT). MTT enters living cells and passes into the mitochondria where it is reduced by mitochondrial succinate dehydrogenase to an insoluble, colored (dark purple) formazan product. The cells are then solubilized with DMSO and the released, solubilized formazan is measured spectrophotometrically. The MTT assay measures cell viability based on the generation of reducing equivalents. Reduction of MTT only occurs in metabolically active cells, so the level of activity is a measure of the viability of the cells. The percentage cell viability is calculated against untreated cells.
Method: A549 and NCI-H520 lung cancer cell lines and L132 lung epithelial cell line were used to determine the plant stem cell treatment tumor-specific cytotoxicity. The cell lines were maintained in Minimal Essential Media supplemented with 10% FBS, penicillin (100 U/ml) and streptomycin (100 μg/ml) in a 5% CO2 at 37 Celsius. Cells were seeded at 5×103 cells/well in 96-well plates and incubated for 48 hours. Triplicates of eight concentrations of the apple stem cell extract were added to the media and cells were incubated for 24 hours. This was followed by removal of media and subsequent washing with the phosphate saline solution. Cell proliferation was measured using the MTT Cell Proliferation Kit I (Boehringer Mannheim, Indianapolis, IN) New medium containing 50 μl of MTT solution (5 mg/ml) was added to each well and cultures were incubated a further 4 hours. Following this incubation, DMSO was added and the cell viability was determined by the absorbance at 570 nm by a microplate reader.
In order to determine the effectiveness of apple stem cell extracts as an anti-tumor biological agent, an MTT assay was carried out and IC50 values were calculated. IC50 is the half maximal inhibitory function concentration of a drug or compound required to inhibit a biological process. The measured process is cell death.
Results: ASC-Treated Human Lung Adenocarcinoma Cell Line A549.
Results: ASC-Treated Human Squamous Carcinoma Cell Line NCI-H520.
Results: ASC-treated Lung Epithelial Cell Line L132.
Summary Results: Cytotoxicity of Apple Stem Cell Extracts.
Apple stem cell extracts killed lung cancer cells lines A549 and NCI-H520 at relatively low doses: IC50s were 12.58 and 10.21 μg/ml respectively as compared to 127.46 μg/ml for the lung epithelial cell line L132. Near complete anti-tumor activity was seen at a dose of 250 μg/ml in both the lung cancer cell lines. This same dose spared more than one half of the L132 cells. See Tables 7-10. The data revealed that apple stem cell extract is cytotoxic to lung cancer cells while sparing lung epithelial cells.
Example 9
The experiment of Example 7 was repeated substituting other plant materials for ASC. Plant stem cell materials included Dandelion Root Extract (DRE), Aloe Vera Juice (AVJ), Apple Fiber Powder (AFP), Ginkgo Leaf Extract (GLE), Lingonberry Stem Cells (LSC), Orchid Stem Cells (OSC) as described in Examples 1 and 2. The concentrations of plant materials used were nominally 250, 100, 50, 25, 6.25, 3.125, 1.562, and 0.781 μg/mL. These materials were tested only for cells the human lung epithelial cell line L132 (as a proxy for normal epithelial cells) and for cells of the human lung adenocarcinoma cell line A549 (as a proxy for lung cancer cells).
A549 cells lung cancer cell line cytotoxicity results for each of the treatment materials.
DRE-Treated Lung Cancer Cell Line A549 Cells.
AVJ-Treated Lung Cancer Cell line A549 Cells.
AFP-Treated Lung Cancer Cell line A549 Cells.
GLE-treated Lung Cancer Cell line A549 Cells.
LSC-treated lung cancer cell lines A549 cells.
OSC-treated Lung Cancer Cell line A549 Cells.
L132 cells (“normal” lung epithelial cell line) cytotoxicity results for each of the treatment materials.
DRE-Treated Lung Epithelial Cell Line L132 cells.
AVJ-Treated Lung Epithelial Cell Line L132 cells.
AFP-Treated Lung Epithelial Cell Line L132 cells.
GLE-Treated Lung Epithelial Cell Line L132 cells.
LSC-Treated Lung Epithelial Cell Line L132 cells.
OSC-Treated Lung Epithelial Cell Line L132 cells.
Calculated values.
Example 3
Lung cancer cell line A549 and squamous cell carcinoma cell line H10 expressing inducible SEQ ID NO: 1-HA vector were established as described previously. SEQ ID NO: 1 expression was detected by qPCR (
To evaluate the effects of SEQ ID NO: 1 on proliferation, A549 and H10 cells transduced with SEQ ID NO: 1-HA vector or control vector were monitored for 14 days. Growth curves show that cells overexpressing micropeptide SEQ ID NO: 1 have a consistently lower growth rate compared to the control (
Example 4
Through use of a lung metastasis model of mouse breast cancer 4T1 cells, the lung metastasis-suppressing effects of anti-S100A8/A9 monoclonal antibodies were investigated.
In accordance with a protocol illustrated in
Example 9
The ORF encoding the micropeptide of SEQ ID NO: 3 was cloned in frame with the HA epitope tag in the pMSCV retroviral vector. Western blot and qPCR analysis demonstrated that the micropeptide of SEQ ID NO: 3 was successfully expressed after retroviral transduction, and that the protein product was stable (
Importantly, overexpression of the micropeptide of SEQ ID NO: 3 induces massive cell death in cancer cell lines (A549, human lung cancer and HCT116, human colorectal cancer) (
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More about "Lung Cancer"
It is one of the most prevalent and deadly forms of cancer, with various histological subtypes and risk factors including smoking, occupational exposures, and genetic predisposition.
Effective diagnosis and treatment strategies are critical for improving patient outcomes, and ongoing research aims to advance our understanding of the molecular mechanisms driving lung cancer development and progression.
Researchers often utilize cell lines like H1299 and MCF-7, as well as culture media like RPMI 1640 and DMEM, supplemented with additives like penicillin, streptomycin, and Lipofectamine 2000, to study lung cancer biology and test potential therapies.
Lung cancer can be categorized into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the latter of which includes subtypes like adenocarcinoma, squamous cell carcinoma, and large cell carcinoma.
Early detection through techniques like low-dose CT screening and minimally invasive biopsies, coupled with advancements in targeted therapies and immunotherapies, have shown promise in enhancing patient prognosis and quality of life.
By leveraging the latest research tools and technologies, scientists are poised to make significant strides in unraveling the complexities of lung cancer, ultimately leading to more effective and personalized treatment approaches for this deadly disease.