Dataset Information

Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

ABSTRACT: Drug sensitivity and resistance are conventionally quantified by IC50 or Emax values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC50 and Emax on division rate creates artefactual correlations between genotype and drug sensitivity, while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative small molecule drug-response metrics that are insensitive to division number. These are based on estimation of the magnitude of drug-induced growth rate inhibition (GR) using endpoint or time-course assays. We show that GR50 and GRmax are superior to conventional metrics for assessing the effects of small molecule drugs in dividing cells. Moreover, adopting GR metrics requires only modest changes in experimental protocols. We expect GR metrics to improve the study of cell signaling and growth using small molecules and biologics and to facilitate the discovery of drug-response biomarkers and the identification of drugs effective against specific patient-derived tumor cells.

SUBMITTER: Hafner M

PROVIDER: S-EPMC4887336 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

Hafner Marc M Niepel Mario M Chung Mirra M Sorger Peter K PK

Nature methods 20160502 6

Drug sensitivity and resistance are conventionally quantified by IC50 or Emax values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC50 and Emax on division rate creates artefactual correlations between genotype and drug sensitivity, while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative small molecule drug-response metrics that are insensitive to divisio ...[more]

PMID: 27135972

Similar Datasets

Project description:Dysregulation of the anti-apoptotic protein, cellular FLICE-like inhibitory protein (c-FLIP), has been associated with tumorigenesis and chemoresistance in various human cancers. Therefore, c-FLIP is an excellent target for therapeutic intervention. MicroRNAs (miRNAs) are small non-coding RNAs that are involved in tumorigenesis, tumor suppression, and resistance or sensitivity to anti-cancer drugs. However, whether miRNAs can suppress c-FLIPL expression in cancer cells is unclear. The aim of this study was to identify miRNAs that could inhibit the growth of renal cancer cells and induce cell death by inhibiting c-FLIPL expression. We found that MiRNA-708 and c-FLIPL expression were inversely correlated. While c-FLIPL expression was upregulated, miRNA-708 was rarely expressed in renal cancer cells. Luciferase reporter assays demonstrated that miRNA-708 negatively regulated c-FLIPL expression by binding to the miRNA-708 binding site in the 3' untranslated region (3'UTR) of c-FLIPL. Ectopic expression of miRNA-708 increased the accumulation of sub-G1 populations and cleavage of procaspase-3 and PARP, which could be prevented by pretreatment with the pan-caspase inhibitor, Z-VAD. Ectopic expression of miRNA-708 also increased the sensitivity to various apoptotic stimuli such as tumor necrosis factor-related apoptosis-inducing ligand, doxorubicin (Dox), and thapsigargin in Caki cells. Interestingly, miRNA-708 specifically repressed c-FLIPL without any change in c-FLIPs expression. In contrast, inhibition of endogenous miRNA-708 using antago-miRNAs resulted in an increase in c-FLIPL protein expression. The expression of c-FLIPL was upregulated in renal cell carcinoma (RCC) tissues compared to normal tissues. In contrast, miRNA-708 expression was reduced in RCC tissues. Finally, miRNA-708 enhanced the tumor-suppressive effect of Dox in a xenograft model of human RCC. In conclusion, miRNA-708 acts as a tumor suppressor because it negatively regulates the anti-apoptotic protein c-FLIPL and regulates the sensitivity of renal cancer cells to various apoptotic stimuli.

Project description:PurposeMeaningful changes in picture naming responses may be obscured when measuring accuracy instead of quality. A statistic that incorporates information about the severity and nature of impairments may be more sensitive to the effects of treatment.MethodWe analyzed data from repeated administrations of a naming test to 72 participants with stroke aphasia in a clinical trial for anomia therapy. Participants were divided into two groups for analysis to demonstrate replicability. We assessed reliability among response type scores from five raters. We then derived four summary statistics of naming ability and their changes over time for each participant: (a) the standard accuracy measure, (b) an accuracy measure adjusted for item difficulty, (c) an accuracy measure adjusted for item difficulty for specific response types, and (d) a distance measure adjusted for item difficulty for specific response types. While accuracy measures address the likelihood of a correct response, the distance measure reflects that different response types range in their similarity to the target. Model fit was assessed. The frequency of significant improvements and the average magnitude of improvements for each summary statistic were compared between treatment groups and a control group. Effect sizes for each model-based statistic were compared with the effect size for the standard accuracy measure.ResultsInterrater and intrarater reliability were near perfect, on average, though compromised somewhat by phonological-level errors. The effects of treatment were more evident, in terms of both frequency and magnitude, when using the distance measure versus the other accuracy statistics.ConclusionsConsideration of item difficulty and response types revealed additional effects of treatment on naming scores beyond those observed for the standard accuracy measure. The results support theories that assume naming ability is decomposable into subabilities rather than being monolithic, suggesting new opportunities for measuring treatment outcomes.Supplemental materialhttps://doi.org/10.23641/asha.17019515.

Dataset Information

Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

Publications

Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets