Evidence map›Paper›PMID 27135972›Full record

ArticleNature methods2016

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

Marc Hafner, Mario Niepel, Mirra Chung, Peter K Sorger

Open access · greenAbstract read
In one paragraph

Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 441 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
441citing papers in PubMed, 1 pooled it
25.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

441 citing papers in PubMed, 1 synthesis or guideline pooled it, 713 citations in OpenAlex.

  1. Pooled it
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  3. TROP2 Expression in Salivary Gland Adenoid Cystic Carcinoma (ACC) According to Histologic Subtype: Therapeutic Implications.Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology · 2025
    Trial
  4. Phase I/II Study of the Aurora Kinase A Inhibitor Alisertib and Pembrolizumab in Refractory, Rb-Deficient Head and Neck Squamous Cell Carcinomas.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
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381 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Marc HafnerHMS LINCS Center Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-1337-7598
Mario NiepelHMS LINCS Center Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-1415-6295
Mirra ChungHMS LINCS Center Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
Peter K SorgerHMS LINCS Center Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
Harvard University · US

Funding

Pharmaco Response Signatures and Disease MechanismU54HL127365 · NHLBI · HARVARD MEDICAL SCHOOL · PI SORGER, PETER KARL · 2014 to 2019
$13.1M
TRANSLATIONAL PHARMACOLOGY COREP50GM107618 · NIGMS · HARVARD MEDICAL SCHOOL · PI MALISZEWSKI, LAURA ELIZABETH · 2014 to 2018
$10.8M
NHLBI NIH HHS U54 HL127365NIGMS NIH HHS P50 GM107618
6 · The paper itself

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.

Indexed as

Models, TheoreticalAntineoplastic AgentsBiological ProductsCell CountCell Culture TechniquesCell Line, TumorCell ProliferationComputer SimulationDose-Response Relationship, DrugDrug DiscoveryDrug Resistance, NeoplasmHigh-Throughput Screening AssaysHumansInhibitory Concentration 50Small Molecule LibrariesAntineoplastic AgentsBiological ProductsSmall Molecule Libraries

Identifiers

PMID27135972
PMCPMC4887336
OpenAlexW2344714812

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.