Project description:The intention was to detect genes that are determining trastuzumab efficiency in HER2-positive breast cancer cell lines with different resistance phenotypes. While BT474 should be sensitive to the drug treatment, HCC1954 is expected to be resistant due to a PI3K mutation. The cell line BTR50 has been derived from BT474 and was cultured to be resistant as well. Based on RNA-Seq data, we performed differential expression analyses on these breast cancer cell lines with and without trastuzumab treatment. In detail, five separate tests were performed, namely resistant cells vs. wild type, i.e. HCC1954 and BTR50 vs. BT474, respectively, and untreated vs. drug treated cells. The significant genes of the first two tests should contribute to resistance. The significant genes of the test BT474 vs. its drug treated version should contribute to the trastuzumab effect. To exclude false positives from the combined gene set (#64), we removed ten genes that were also significant in the test BTR50 vs. its drug treated version. This way we ended up with 54 genes that are very likely to determine trastuzumab efficiency in HER2-positive breast cancer cell lines. mRNA profiles of human breast cancer cell lines were generated by deep sequencing using Illumina HiSeq 2000. The cell lines BT474 and HCC1954 were analyzed with and without trastuzumab treatment. HCC1954 is known to be trastuzumab resistant. Additionally, the cell line BTR50 was generated as resistant version of BT474, and was analyzed with and without trastuzumab as well.
Project description:We sequenced untreated BT474 cells, BT474 cells treated for three days with trastuzumab or trastuzumab + pertuzumab, as well as two BT474-derived trastuzumab-resistant pools and two BT474-derived trastuzumab + pertuzumab resistant pools. Resistant pools were generated by culturing BT474 cells in gradually increasing doses of trastuzumab and trastuzumab + pertuzumab over the course of several months and continually maintained in drug.
Project description:The intention was to detect genes that are determining trastuzumab efficiency in HER2-positive breast cancer cell lines with different resistance phenotypes. While BT474 should be sensitive to the drug treatment, HCC1954 is expected to be resistant due to a PI3K mutation. The cell line BTR50 has been derived from BT474 and was cultured to be resistant as well. Based on RNA-Seq data, we performed differential expression analyses on these breast cancer cell lines with and without trastuzumab treatment. In detail, five separate tests were performed, namely resistant cells vs. wild type, i.e. HCC1954 and BTR50 vs. BT474, respectively, and untreated vs. drug treated cells. The significant genes of the first two tests should contribute to resistance. The significant genes of the test BT474 vs. its drug treated version should contribute to the trastuzumab effect. To exclude false positives from the combined gene set (#64), we removed ten genes that were also significant in the test BTR50 vs. its drug treated version. This way we ended up with 54 genes that are very likely to determine trastuzumab efficiency in HER2-positive breast cancer cell lines.
Project description:In order to benchmark the reproducibility of Affymetrix Genome-Wide Human SNP Array 6.0 for detecting copy-number alterations, we performed replicate hybridizations of 3 tumor cell lines and 2 paired normal cell lines obtained from the American Type Culture Collection (ATCC). We calculated copy numbers at each SNP probeset by a custom copy-number pipeline (PMID: 18772890). For each cell line, copy number data from replicate arrays are supplied in the accompanying matrix files. For each SNP probeset, we calculated the median copy number across replicate arrays. We compared the copy-number alterations detected by Circular Binary Segmentation segmentation of these arrays with statistical analyses of short sequence reads obtained from the Illumina/Solexa 1G GenomeAnalyzer. Shotgun sequencing results can be found in the NCBI Short Read Archive, accession number SRP000246 Keywords: disease state analysis
Project description:In order to benchmark the reproducibility of Affymetrix 238K Sty arrays for detecting copy-number alterations. We performed replicate hybridizations of 3 tumor cell lines and 2 paired normal cell lines obtained from the American Type Culture Collection (ATCC). We calculated copy numbers at each SNP probeset by array pre-processing with the GISTIC algorithm (PMID: 18077431). For each SNP probeset, we calculated the median copy number across replicate arrays. The median copy number profile for each tumor cell line was segmented with the GLAD algorithm (PMID: 15381628) to partition the genome into regions of constant copy number. We compared the copy-number alterations detected by GLAD segmentation of these arrays with statistical analyses of short sequence reads obtained from the Illumina/Solexa 1G GenomeAnalyzer. Shotgun sequencing results can be found in the NCBI Short Read Archive, accession number SRP000246. Keywords: disease state analysis
Project description:We analyzed copy numbers of 60 SCLC cell lines using 6.0 SNP-arrays. For a subgroup of 36 cell lines, previously published copy number data was utilized. CEL and SEG files are included for all cell lines, for which copy number data were not publicly available.
Project description:The genomic loci with copy number alterations are known to harbor cancer genes. We investigated a comprehensive panel of gastric cancer cell lines for their genome-wide copy number alterations. Eighteen gastric cancer cell lines were profiled using Affymetrix 500K SNP arrays. For copy number calculation, seven independent normal blood samples were profiled together. The copy numbers were calculated genome-wide, in these cell lines with high resolution and reveal the cell line specific amplification and copy number changes.
Project description:Copy number and LOH analysis was performed for 36 acute leukemia cell lines. All cases were genotyped with Affymetrix 250k Sty and Nsp arrays. Keywords: Acute leukemia, BCR-ABL1, cell lines, copy number analysis, loss-of-heterozygosity, genomics *** Due to privacy concerns, the primary SNP array data is no longer available with unrestricted access. Individuals wishing to obtain this data for research purposes may request access using the Web links below. ***
Project description:Genomic copy-number changes were measured using 250K StyI SNP arrays after selection of cells to enrich for resistance to BEZ235. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted using Qiagen DNeasy from engineered human cell-lines.