Project description:Twenty three small-cell lung carcinoma (SCLC) cell lines from ATCC profiled on 100K genotyping arrays Experiment Overall Design: The cell lines were run on 100K SNP genotyping arrays to obtain copy number information
Project description:Copy number profiling of 92 human lung tumors on Affymetrix 100K SNP arrays was conducted in order to assess the interaction of common genomic alterations with response to targeted anti-cancer therapeutics. Class 1 phosphatidylinositol 3' kinase (PI3K) plays a major role in cell proliferation and survival in a wide variety of human cancers. Here we investigate biomarker strategies for PI3K pathway inhibitors in non-small-cell lung cancer (NSCLC). Molecular profiling of NSCLC tumor samples showed that copy number gains in PIK3CA and total loss of PTEN protein were common in squamous cell carcinoma samples, whereas LKB1 loss and mutations in KRAS and EGFR were common in adenocarcinomas. A panel of NSCLC cell lines characterized for alterations in the PI3K pathway was screened with PI3K and dual PI3K/mTOR inhibitors to assess the preclinical predictive value of candidate biomarkers. Cell lines harboring pathway alterations (RTK activation, PI3K mutation or amplification, PTEN loss) were exquisitely sensitive to the PI3K inhibitor GDC-0941. A dual PI3K/mTOR inhibitor had broader activity across the cell line panel and in tumor xenografts. The combination of GDC-0941 with paclitaxel, erlotinib, or a MEK inhibitor had greater effects on cell viability than PI3K inhibition alone. CONCLUSIONS: Candidate biomarkers for PI3K inhibitors have predictive value in preclinical models and show histology-specific alterations in primary tumors, suggesting that distinct biomarker strategies may be required in squamous compared with non-squamous NSCLC patient populations. Lung tumors were profiled on Affymetrix GeneChip Mapping 100K Set Arrays Tumor samples were profiled for copy number without any treatment of the tumor.
Project description:Breast cancer cell lines grown in full serum under standard conditions were profiled on Affymetrix GeneChip Mapping 100K Set Arrays Experiment Overall Design: Profiling of cell lines grown under standard conditions
Project description:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array. Affymetrix 100K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1). Affymetrix 500K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Forty-eight normal samples were downloaded from the Affymetrix website (http://www.affymetrix.com/support/technical/byproduct.affx?product=500k) and analyzed at the same time. One CEL file for each set (Sty and Nsp) with the median signal intensity across the set was selected as the reference array. The dChip-normalized signal intensities were converted to log2 ratios and segmented as follows. For each autosomal probe set, the log2 tumor/normal ratio of each tumor sample was calculated using the average intensity for each probe set in the normal set. For Chromosome X, the average of the 20 normal female samples was used. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1).