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Full-Text Articles in Life Sciences
Leveraging Global Gene Expression Patterns To Predict Expression Of Unmeasured Genes, James Rudd, René A. Zelaya, Eugene Demidenko, Ellen L. Goode, Casey S. Greene S. Greene, Jennifer A. Doherty
Leveraging Global Gene Expression Patterns To Predict Expression Of Unmeasured Genes, James Rudd, René A. Zelaya, Eugene Demidenko, Ellen L. Goode, Casey S. Greene S. Greene, Jennifer A. Doherty
Dartmouth Scholarship
BackgroundLarge collections of paraffin-embedded tissue represent a rich resource to test hypotheses based on gene expression patterns; however, measurement of genome-wide expression is cost-prohibitive on a large scale. Using the known expression correlation structure within a given disease type (in this case, high grade serous ovarian cancer; HGSC), we sought to identify reduced sets of directly measured (DM) genes which could accurately predict the expression of a maximized number of unmeasured genes.
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
Dartmouth Scholarship
Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data–derived predictor of known cancer associated genes. We found that the traditional approach of identifying cancer genes—identifying differentially expressed genes—is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results …
Interleukin-1Β Mediates Metalloproteinase-Dependent Renal Cell Carcinoma Tumor Cell Invasion Through The Activation Of Ccaat Enhancer Binding Protein Β, Brenda L. Petrella, Matthew P. P. Vincenti
Interleukin-1Β Mediates Metalloproteinase-Dependent Renal Cell Carcinoma Tumor Cell Invasion Through The Activation Of Ccaat Enhancer Binding Protein Β, Brenda L. Petrella, Matthew P. P. Vincenti
Dartmouth Scholarship
Effective treatment of metastatic renal cell carcinoma (RCC) remains a major medical concern, as these tumors are refractory to standard therapies and prognosis is poor. Although molecularly targeted therapies have shown some promise in the treatment of this disease, advanced RCC tumors often develop resistance to these drugs. Dissecting the molecular mechanisms underlying the progression to advanced disease is necessary to design alternative and improved treatment strategies. Tumor-associated macrophages (TAMs) found in aggressive RCC tumors produce a variety of inflammatory cytokines, including interleukin-1 b (IL-1b). Moreover, the presence of TAMs and high serum levels of IL-1b in RCC patients correlate …
Variations In Mre11/Rad50/Nbs1 Status And Dna Damage-Induced S-Phase Arrest In The Cell Lines Of The Nci60 Panel, Kristen M. K. Garner, Alan Eastman
Variations In Mre11/Rad50/Nbs1 Status And Dna Damage-Induced S-Phase Arrest In The Cell Lines Of The Nci60 Panel, Kristen M. K. Garner, Alan Eastman
Dartmouth Scholarship
The Mre11/Rad50/Nbs1 (MRN) complex is a regulator of cell cycle checkpoints and DNA repair. Defects in MRN can lead to defective S-phase arrest when cells are damaged. Such defects may elicit sensitivity to selected drugs providing a chemical synthetic lethal interaction that could be used to target therapy to tumors with these defects. The goal of this study was to identify these defects in the NCI60 panel of cell lines and identify compounds that might elicit selective cytotoxicity.