phenotype: T-PLL tcl1a: POS mtcp1: NA os_diagnosis_to_last_fu: 265 os_treatment_to_last_fu: 139 os_scoring: DOD pfs: NA pfs_scoring: death; relapse or progression; primary treatment failure wbc_diagn: 77 wbc_sample: 77 description: NA cell type: T cells
Extracted molecule
genomic DNA
Extraction protocol
Human T-PLL cells. Sample preparation: DNAs were isolated from PBMCs of T-PLL patients (n=83, >95% purity of T-cells) that included 13 CD4/CD8-enriched/depleted tumor/germline (t/g) pairs (see chapter “Magnetic-bead based cell enrichment” for details on cell purification) using the QIAamp DNA Kit (Qiagen). SNP-array analyses were conducted using Affymetrix SNP 6.0 chips according to manufacturer’s instructions.
Label
biotin
Label protocol
As per manufacturer (Affymetrix)
Hybridization protocol
DNA was restriction digested, PCR amplified, fragmented, labeled and hybridized to each array according to the manufacturer's instructions.
Scan protocol
The Arrays were then washed using Affymetrix fluidics stations, and scanned using the Gene Chip Scanner 3000.
Data processing
Bioinformatics: To globally infer on sCNAs across the T-PLL genome, the T-PLL data sets were compared to the pooled controls (non-tumor hematopoietic cell DNA as ‘germline’ from T-PLL patients, n=13) obtained by the Affymetrix Power Tools, version 1.14.2 with duplicate SNP/CN markers (by identical position) removed. We segmented the called SNP / copy number (CN) markers by the Circular binary segmentation (CBS) algorithm (default options, p<0.01) within the DNAcopy R-package and converted the output files to .seg files to view them in the “Integrative Genome Viewer”. Since the CBS algorithm only reports significantly altered segments/regions and therefore disregards gene structure (perhaps splits them in two or more segments), we mapped regions on gene CDS (based on version 75 of the Ensembl annotation) within the GenomicRanges R package, version 1.16.4, and clustered CNs by gene names and 100kb regions with the gplots R package. Globally, we identified gains (CN>2.5) in 19,590 genes and losses (CN<1.5) in 27,193 genes (Supplementary Data7). The number of sCNA-affected genes (median 3354) varied inter-individually (e.g. 13,862 in TP038 vs. 42 in TP033).
