LINCS MCF 10A Common Project: Fixed-time-point sensitivity measures of the MCF 10A breast cell line to 8 small molecule perturbagens. Repeat performed by Scientist C in 2019 to assess reproducibility. Dataset 2 of 2: Calculated dose response metrics. - Dataset (ID:20363)
|HMS Dataset ID:||20363|
|Dataset Title:||LINCS MCF 10A Common Project: Fixed-time-point sensitivity measures of the MCF 10A breast cell line to 8 small molecule perturbagens. Repeat performed by Scientist C in 2019 to assess reproducibility. Dataset 2 of 2: Calculated dose response metrics.|
|Screening Lab Investigator:||Caitlin E. Mills|
|Screening Principal Investigator:||Peter K. Sorger|
|Assay Description:||As part of the multi-center study on factors influencing the reproducibility of in vitro drug-response studies, we measured the sensitivities of the MCF 10A cell line to 8 small molecule perturbagens. A microscopy-based dose response assay was used to measure drug potency, and to quantify drug efficacy in terms of growth inhibition (GR metrics) and cell death. We treated cells with single drugs over a 9-point ½ log dilution series from a maximum dose not exceeding 10 µM and then measured cell number and viability after three days of drug exposure. Replicate experiments were performed at other centers, and by other HMS scientists in 2017 (datasets #20278-20286 ) and 2019 (datasets #20358-20363). These datasets as well as replicate datasets from other LINCS centers can also be accessed at https://www.synapse.org/#!Synapse:syn18456348/wiki/.|
1. Cells in mid-log phase of the growth cycle from three independent batches and one derivative of the MCF 10A cell line were cultured in DMEM/F12 base media (Invitrogen #11330-032) supplemented with 5% horse serum (Sigma-Aldrich #H1138), 0.5 μg/mL hydrocortisone (Sigma # H-4001), 20 ng/mL rhEGF (R&D Systems #236-EG), 10 μg/mL insulin (Sigma #I9278), 100 ng/mL cholera toxin (Sigma-Aldrich #C8052), and 100 units/mL penicillin and 100 μg/mL streptomycin (Invitrogen #15140148 or #15140122 or other sources). Cells were plated at a density of 750 cells per well in 60 μL of media in 384-well plates.|
2. The plated cells were grown for 24 hours at 37°C in the presence of 5% CO2 and were then treated with the indicated small molecules using a D300 Digital Dispenser (Hewlett-Packard, Palo Alto, CA).
3. Cells were stained and fixed for analysis at the time of drug delivery (one plate) and after 72 hours of incubation (four plates) by adding 15 µL of staining solution (1:1000 LIVE/DEAD Far Red Dead Cell Stain (Thermo Fisher Scientific, catalog #L-34974), 2 µg/ml Hoechst 33342 (Thermo Fisher Scientific, catalog #62249), 10% OptiPrep (Sigma-Aldrich, catalog #D1556-250ML) in PBS) for 30 min at room temperature followed by fixing solution (4% formaldehyde (v/v) (Sigma-Aldrich, catalogue #F1635-500ML), 20% OptiPrep in PBS) for 20 min at room temperature. After fixation, 80 µL of supernatant per well was removed and replaced with 80 µL of PBS with an EL406 Washer Dispenser (BioTek, Winooski, VT).
4. The plates were scanned with a PE Operetta high-throughput plate scanner. Six fields of view covering the full well were acquired with a 10x high NA objective for all wells. The excitation and emission filters used for image acquisition were 360-400 nm and 410-480 nm for Hoechst, and 620-640 nm and 650-700 nm for LDR.
5. Live and dead cell counts were obtained using Columbus software (Nuclear segmentation: module: ‘Find Nuclei’; method: C; default parameters except ‘Individual Threshold’ which was set to 0.25; Channel: Hoechst. Corpse segmentation: module: ‘Find Nuclei’; method: B; default parameters except ‘Area’ which was set to >50; Channel: LDR; filter: Hoechst intensity < 300; output: ‘Corpse- Number of objects’. Segmented nuclei were classified as dead based on LDR texture: module: ‘Calculate Texture Properties’; method: SER Features; scale: 8px; normalized by: Region Intensity SER Spot; channel: LDR; filter: >0.001; output: ‘DeadLDR- Number of objects’, or based on size: module: ‘Calculate Morphology Properties’; method: Standard Area; population: Nuclei segmented; filter: <60-120 depending on the cell line; output: ‘DeadSize- Number of objects’. Live cells were counted as the number of nuclei segmented that did not meet the size or texture criteria for dead cells; output: ‘Live-Number of objects’.) The fraction of dead cells was calculated by taking the sum of (‘Corpse’, ‘DeadLDR’, ‘DeadSize’ counts) divided by the sum of (‘Corpse’, ‘DeadLDR’, ‘DeadSize’, ‘Live’ counts).
6. Consistent with the methods reported in Hafner et al. (2016) (PMID: 27135972), the Mean Normalized Growth Rate Inhibition (GR) Values were calculated according to the following formula: 2^[log2(x(c)/x0)/log2(xctrl/x0)]-1 where x(c) is the mean of the measured ‘Live’ cell counts after a given treatment, x0 is the mean of the ‘Live’ cell counts from the day 0 untreated plate grown in parallel until the time of treatment, and xctrl is the mean of the ‘Live’ cell counts of the DMSO-treated control wells for all technical replicates. See HMS-LINCS dataset #20360 for these results.
7. The Increased Fraction Dead was calculated by subtracting the mean fraction of dead cells in the DMSO-treated control wells from the mean fraction of dead cells in the wells from a given treatment across all technical replicates. See HMS-LINCS dataset #20360 for these results.
8. The mean normalized growth rate inhibition (GR) values for a given cell line / small molecule combination across all tested concentrations were fitted to a sigmoidal curve according to: GRinf+(1-GRinf)/(1+(c/GEC50)hGR) where GRinf is the effect of the drug at infinite concentration, hGR is the GR Hill Coefficient of the fitted curve, and GEC50 is the concentration at half maximal effect. GR r2 is a measure of the goodness of the fit. The GR50 value is the concentration at which the GR value is 0.5, GRmax is the maximum effect of the treatment at the highest concentration tested, and GR_AOC is the area over the fitted curve. See Hafner et al. (2016) (PMID: 27135972) for further details.
|Assay Protocol Reference:||Hafner M, Niepel M, Subramanian K, and Sorger PK. Designing drug response experiments and quantifying their results. Curr Protoc Chem Biol 2017 Jun 19;9(2):96-116. doi: 10.1002/cpch.19 PubMed PMID: 28628201.|
|HMS Dataset Type:||Analysis|
|Date Publicly Available:||2019-06-27|
|Most Recent Update:||2019-06-27|