Genomics of Drug Sensitivity in Cancer

Downloads

This page allows access to all of our drug sensitivity data and the genomic datasets used in our analyses.

The same data but for individual drugs or genes is also available from the relevant pages.

Data sharing policy -- Our commitment

The Wellcome Trust is committed to data sharing wherever possible. This maximises the value and scientific impact of the data, and ensures transparency and equity in exploitation of the opportunities created. The Institute recognises the need for researchers to be appropriately credited for their scientific contribution and investment in data generation. It is therefore expected that all researchers both honour agreements in line with Fort Lauderdale's data sharing principles and appropriately acknowledge the contributions of others.

For more information about the Institute's data policies, please refer to our legal http://www.sanger.ac.uk/legal/index.html page, which has sections on data sharing and use.

Alternatively you can download the PDF version of the Data Sharing Policy.

Resources

• Cell line drug sensitivity, mutations and tissue type

  A table of cell line drug sensitivity data, mutations in cancer genes and tissue type. The genomic data in this file was used for the MANOVA. Download here as a CSV or Excel file.

  HideShow table desctiption

  Cell Line

  Cell line name

  Cosmic_ID

  Unique cell line identifier

  Tissue

  Tissue type of cell line

  Cancer-type

  Cancer sub-type of cell line based on tissue and histology

  Genetic information

  Genetic mutation data for cancer genes. Includes MSI status (1 = unstable and 0 = stable) and gene-fusions. A binary code 'x::y' description is used for each gene where 'x' identifies a coding variant and 'y' indicates copy number information from SNP6.0 data. For gene fusions, cell lines are identified as fusion not-detected (0) or the identified fusion is given. The following abbreviations are used: not analysed (na), not detected or wild-type (wt), no copy number information (nci).

  IC50 values for each drug

  Half maximal inhibitory (IC50) drug concentrations (natural log microMolar)

  Drug response curve features for each drug

  ALPHA - sharp parameter from curve-fitting

  BETA - slope parameter from curve-fitting

  B - variance parameter from curve-fitting

  IC_25 - 25% inhibitory drug concentration (natural log microMolar)

  IC_50 - Half maximal inhibitory (50%) drug concentrations (natural log microMolar)

  IC_75 - 75% inhibitory drug concentration (natural log microMolar)

  IC_90 - 90% inhibitory drug concentration (natural log microMolar)

  AUC - area under curve

  D - residuals from curve fitting of data

  IC_RESULTS_ID - unique result identifier

  IC50 value including confidence intervals for each drug

  IC_50_LOW - IC50 low confidence interval (natural log microMolar)

  IC_50 - Half maximal inhibitory (50%) drug concentrations (natural log microMolar)

  IC_50_HIGH - IC50 high confidence interval (natural log microMolar)

• Multivariate ANOVA for all compounds

  A table of results from multivariate ANOVA of cancer genes as modifiers of drug response. Download here as a CSV or Excel file.

  Drug response was analysed incorporating both IC50 values and the slope of drug response curves.

  HideShow table desctiption

  drug

  drug name

  gene

  Name of gene used for genetic correlation

  no_mut

  Total number of mutant cell lines used for correlation

  mut

  Number of cell lines with a coding sequence variant in the indicated gene

  amp

  Number of cell lines with a amplifcation in the indicated gene

  del

  Number of cell lines with a homozygous deletion in the indicated gene

  pvalue

  significance value from MANOVA

  anova_effect

  Effect of mutation on IC50s. Proportional to the difference in mean IC50 between wild-type and mutant cell lines. Negative numbers indicate drug sensitivity and positive numbers drug resistance.

  Mean_WT

  Mean IC50 of wild-type cell lines (natural log microMolar)

  Mean_MT

  Mean IC50 of mutated cell lines (natural log microMolar)

  qvalue

  adjusted p-value incorporating 0.2 FDR

  cut_off

  p-value threshold for 0.2 FDR

  tt_pvalue

  t-test p-value (comparison of WT and MT)

  tt_qvalue

  t-test adjusted p-value incorporating 0.2 FDR

  tt_effect

  t-test effect size

  cell_lines

  Total number of cell lines screened against the drug

  Mut

  Total number of cell lines screend against the drug with a mutation in specified gene

  Mode_MT

  Mode_MT (natural log microMolar)

  Median_MT

  Median_MT (natural log microMolar)

  Range_MT

  Range_MT (natural log microMolar)

  Minimum_MT

  Minimum_MT (natural log microMolar)

  Maximum_MT

  Maximum_MT (natural log microMolar)

  Variance_MT

  Variance_MT (natural log microMolar)

  Std_Dev_MT

  Std_Dev_MT (natural log microMolar)

  Skewness_MT

  Skewness_MT

  Kurtosis_MT

  Kurtosis_MT

  Semi-Interquartile Range_MT

  Semi-Interquartile Range_MT (natural log microMolar)

  Average Deviation_MT

  Average Deviation_MT

  Sum Of Squares_MT

  Sum Of Squares_MT

  Variation Ratio_MT

  Variation Ratio_MT

  WT

  Total number of wild type cell lines screened against drug.

  Mode_WT

  Mode_WT (natural log microMolar)

  Median_WT

  Median_WT (natural log microMolar)

  Range_WT

  Range_WT (natural log microMolar)

  Minimum_WT

  Minimum_WT (natural log microMolar)

  Maximum_WT

  Maximum_WT (natural log microMolar)

  Variance_WT

  Variance_WT (natural log microMolar)

  Std_Dev_WT

  Std_Dev_WT (natural log microMolar)

  Skewness_WT

  Skewness_WT

  Kurtosis_WT

  Kurtosis_WT

  Semi-Interquartile Range_WT

  Semi-Interquartile Range_WT (natural log microMolar)

  Average Deviation_WT

  Average Deviation_WT

  Sum Of Squares_WT

  Sum Of Squares_WT

  Variation Ratio_WT

  Variation Ratio_WT

  drug_effect

  anova effect divided by LN (10).

  Volcano plot value

  This value is 10^(2 * drug_effect). It is used to represent the data on volcano plots.

  drug_id

  A unique ID for each screening drug

  slope effect

  Effect of mutation on slope (BETA). Proportional to the difference in the mean slope of the drug response curve between wild-type and mutant cell lines.

• ANOVA of tissue effect on drug response

  A table of results from ANOVA of drug sensitivity in 48 different cancer subtypes as determined by measuring cell lines IC50s. Download here as a CSV or Excel file.

  HideShow table desctiption

  drug name

  Name of drug used for analysis

  cancer type

  Cancer subtype analysed based on tissue and histology

  ttest p value

  t-test p-value (comparison of mean IC50 for given cancer type versus all other tissues)

  ttest effect size

  t-test effect size (comparison of mean IC50 for given cancer type versus all other tissues)

  group mean

  Mean IC50 of cell lines for indicated cancer subtype (natural log microMolar)

  mutant cell lines

  Total number of cell lines of a given subtype screened against the drug

  ttest q value

  corrected t-test p-value incorporating 0.2 FDR

  sign diff subgroups

  ANOVA summary for specified cancer subtype. The number of significantly different cancer subtypes

  Tissue for comparison (e.g. Myeloma)

  Mean IC50 of cell lines for indicated cancer subtype (natural log microMolar) used for comparison.

  sign_X

  ANOVA result for each cancer subtype. 1 = significantly different, 0 = not significantly different, and NaN = not a number (i.e not determined)

• Elastic net results for all compounds

  A table of results from the elastic net analysis of drug sensitivity. All of our available genomic data including mutations and copy number changes in cancer genes, transcriptional profiles and tissue type are used as input variables. Download here as a CSV or Excel file.

  HideShow table desctiption

  Feature

  The name of the gene present in an EN model. CN indicates that the feature is a copy number change. Mut indicates that the feature is a mutational event. No indication indicates the feature is an expression level change. In some cases two genes are assigned to a single microarray probe and both gene are listed (gene 1 /// gene 2).

  Drug ID

  a unique drug identifier

  Drug name

  The common name of the drug

  Target

  The therapeutically relevant drug target.

  Freq

  100 modeling iterations were performed and the frequency at which each feature is present in the resulting model is reported (e.g. a frequency of 1 indicates that the feature was present in all 100 models).

  Effect

  Strength of the association between gene and drug response. Effect < 0: Sensitizing feature. For expression change: Higher expression in cell lines with lower IC50. For Copy Number (CN), amplified in cell lines with lower IC50 or deleted in cell lines with higher IC50. For Mutation (Mut), mutated in cell lines with lower IC50.

• Cell line genetic (mutation and copy number) and gene expression data used for EN analysis.

  A table of the transcriptional, mutation, copy number and tissue features used as input variables for the elastic net analysis. Download from here.

  HideShow table desctiption

  First row

  Cell lines names

  First column

  The name of the genetic or transcriptomic features used in the EN analysis. The gene expression data are listed first, followed by the copy number (CN) and mutation status (MUT) data for individual cancer genes, and lastly the tissue sub-type for each cell line. For gene expression analysis, RNA was hybridized to the HT-HGU133A Affymetrix whole genome array and normalised gene expression intensities were generated using the MAS5 algorithm.

  A table of normalised gene expression data used in EN analysis. Download from here. The raw data is deposited in ArrayExpress (accession number is E-MTAB-783).

• Cell line collection

  A table of the cell lines within our collection for screening. Download here as a CSV or Excel file.

• Screening Concentration

  A table of the compounds with minimum and maximum concentration used in the screening. Download here as a CSV or Excel file

• Archive

  Click here to download all releases.