Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 898

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action

Open access
Rees, Matthew G, Seashore-Ludlow, Brinton, Cheah, Jaime H, Adams, Drew J, Price, Edmund V, Gill, Shubhroz, Javaid, Sarah, Coletti, Matthew E, Jones, Victor L, Bodycombe, Nicole E, Soule, Christian K, Alexander, Benjamin, Li, Ava, Montgomery, Philip, Kotz, Joanne D, Hon, C Suk-Yee, Munoz, Benito, Liefeld, Ted, Dančík, Vlado, Haber, Daniel A, Clish, Clary B, Bittker, Joshua A, Palmer, Michelle, Wagner, Bridget K, Clemons, Paul A, Shamji, Alykhan F, Schreiber, Stuart L·2016·Nature Chemical Biology
DOI 10.1038/nchembio.1986
Open this paper in CoChat — free account

Abstract

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ~19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters, and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nchembio.1986

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 14 references

Research works printed but not linked: 34

  1. Schenone, M., Dančík, V., Wagner, B.K. & Clemons, P.A. Target identification and mechanism of action in chemical biology and drug discovery. Nat. Chem. Biol. 9, 232–240 (2013). · DOI · Paper page
  2. Hughes, T.R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000). · DOI · Paper page
  3. Lamb, J. et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929–1935 (2006). · DOI · Paper page
  4. Basu, A. et al. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules. Cell 154, 1151–1161 (2013). · DOI · Paper page
  5. Guo, W. et al. Formation of 17-allylamino-demethoxygeldanamycin (17-AAG) hydroquinone by NAD(P)H:quinone oxidoreductase 1: role of 17-AAG hydroquinone in heat shock protein 90 inhibition. Cancer Res. 65, 10006–10015 (2005). · DOI · Paper page
  6. Papillon-Cavanagh, S. et al. Comparison and validation of genomic predictors for anticancer drug sensitivity. J. Am. Med. Inform. Assoc. 20, 597–602 (2013). · DOI
  7. Shoemaker, R.H. The NCI60 human tumour cell line anticancer drug screen. Nat. Rev. Cancer 6, 813–823 (2006). · DOI · Paper page
  8. Dančík, V. et al. Connecting small molecules with similar assay performance profiles leads to new biological hypotheses. J. Biomol. Screen. 19, 771–781 (2014). · DOI
  9. Adams, D.J. et al. NAMPT is the cellular target of STF-31-like small-molecule probes. ACS Chem. Biol. 9, 2247–2254 (2014). · DOI
  10. Zhai, D., Jin, C., Satterthwait, A.C. & Reed, J.C. Comparison of chemical inhibitors of antiapoptotic Bcl-2-family proteins. Cell Death Differ. 13, 1419–1421 (2006). · DOI · Paper page
  11. Franceschini, A. et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 41, D808–D815 (2013). · DOI · Paper page
  12. Benetatos, C.A. et al. Birinapant (TL32711), a bivalent SMAC mimetic, targets TRAF2-associated cIAPs, abrogates TNF-induced NF-κB activation, and is active in patient-derived xenograft models. Mol. Cancer Ther. 13, 867–879 (2014). · DOI · Paper page
  13. Zoppoli, G. et al. Putative DNA/RNA helicase Schlafen-11 (SLFN11) sensitizes cancer cells to DNA-damaging agents. Proc. Natl. Acad. Sci. USA 109, 15030–15035 (2012). · DOI · Paper page
  14. Marks, K.M. et al. The selectivity of austocystin D arises from cell-line-specific drug activation by cytochrome P450 enzymes. J. Nat. Prod. 74, 567–573 (2011). · DOI
  15. Lafite, P., Dijols, S., Zeldin, D.C., Dansette, P.M. & Mansuy, D. Selective, competitive and mechanism-based inhibitors of human cytochrome P450 2J2. Arch. Biochem. Biophys. 464, 155–168 (2007). · DOI
  16. Javaid, S. et al. Dynamic chromatin modification sustains epithelial-mesenchymal transition following inducible expression of Snail-1. Cell Rep. 5, 1679–1689 (2013). · DOI
  17. Rivera, M.I. et al. Selective toxicity of the tricyclic thiophene NSC 652287 in renal carcinoma cell lines: differential accumulation and metabolism. Biochem. Pharmacol. 57, 1283–1295 (1999). · DOI
  18. Glaros, T.G. et al. The “survivin suppressants” NSC 80467 and YM155 induce a DNA damage response. Cancer Chemother. Pharmacol. 70, 207–212 (2012). · DOI
  19. Nakahara, T. et al. YM155, a novel small-molecule survivin suppressant, induces regression of established human hormone-refractory prostate tumor xenografts. Cancer Res. 67, 8014–8021 (2007). · DOI · Paper page
  20. Kamath, A.V., Chong, S., Chang, M. & Marathe, P.H. P-glycoprotein plays a role in the oral absorption of BMS-387032, a potent cyclin-dependent kinase 2 inhibitor, in rats. Cancer Chemother. Pharmacol. 55, 110–116 (2005). · doi:10.1007/s00280-004-0873-3
  21. Young, L.C. et al. Expression of multidrug resistance protein-related genes in lung cancer: correlation with drug response. Clin. Cancer Res. 5, 673–680 (1999).
  22. Adams, D.J. et al. Discovery of small-molecule enhancers of reactive oxygen species that are nontoxic or cause genotype-selective cell death. ACS Chem. Biol. 8, 923–929 (2013). · DOI
  23. Long, J.Z. et al. Selective blockade of 2-arachidonoylglycerol hydrolysis produces cannabinoid behavioral effects. Nat. Chem. Biol. 5, 37–44 (2009). · DOI · Paper page
  24. Germain, A.R. et al. Identification of a selective small molecule inhibitor of breast cancer stem cells. Bioorg. Med. Chem. Lett. 22, 3571–3574 (2012). · DOI
  25. Taube, J.H. et al. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc. Natl. Acad. Sci. USA 107, 15449–15454 (2010). · DOI · Paper page
  26. Sprecher, H. Metabolism of highly unsaturated n-3 and n-6 fatty acids. Biochim. Biophys. Acta 1486, 219–231 (2000). · DOI · Paper page
  27. Obukowicz, M.G. et al. Identification and characterization of a novel delta6/delta5 fatty acid desaturase inhibitor as a potential anti-inflammatory agent. Biochem. Pharmacol. 55, 1045–1058 (1998). · DOI
  28. Snyder, F., Lee, T. & Wykle, R.L. Ether-linked lipids and their bioactive species. in Biochemistry of Lipids, Lipoproteins, and Membranes edn. 4 (eds. Vance, D.E. & Vance, J.E.) 233–262 (Elsevier, 2002). · doi:10.1016/s0167-7306(02)36011-3
  29. Park, W.J., Kothapalli, K.S., Lawrence, P. & Brenna, J.T. FADS2 function loss at the cancer hotspot 11q13 locus diverts lipid signaling precursor synthesis to unusual eicosanoid fatty acids. PLoS One 6, e28186 (2011). · doi:10.1371/journal.pone.0028186
  30. Byers, L.A. et al. An epithelial-mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance. Clin. Cancer Res. 19, 279–290 (2013). · DOI · Paper page
  31. Fischer, E.S. et al. Structure of the DDB1-CRBN E3 ubiquitin ligase in complex with thalidomide. Nature 512, 49–53 (2014). · DOI · Paper page
  32. Palmer, A.C. & Kishony, R. Opposing effects of target overexpression reveal drug mechanisms. Nat. Commun. 5, 4296 (2014). · DOI
  33. Cowley, G.S. et al. Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies. Sci. Data 1, 140035 (2014). · DOI · Paper page
  34. Chen, C. et al. Selective inhibitors of CYP2J2 related to terfenadine exhibit strong activity against human cancers in vitro and in vivo. J. Pharmacol. Exp. Ther. 329, 908–918 (2009). · DOI

Cited by

See all 898

Metadata

Authors
Rees, M. G., Seashore-Ludlow, B., Cheah, J. H., Adams, D. J., Price, E. V., Gill, S., Javaid, S., Coletti, M. E., Jones, V. L., Bodycombe, N. E., Soule, C. K., Alexander, B., Li, A., Montgomery, P., Kotz, J. D., Hon, C. S.-Y., Munoz, B., Liefeld, T., Dančík, V., Haber, D. A., Clish, C. B., Bittker, J. A., Palmer, M., Wagner, B. K., Clemons, P. A., Shamji, A. F., & Schreiber, S. L.
Venue
Nature Chemical Biology
Publisher
Springer Science and Business Media LLC
Published
2015-12-14
Volume
12
Issue
2
Pages
109-116
ISSN
  • 1552-4450 (ISSN-L)
  • 1552-4469
DOI
10.1038/nchembio.1986
OpenAlex
W2220553089
Cited by
898
References
14
FWCI
36.93
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Correlating chemical sensitivity and basal gene expression reveals mechanism of action. https://app.cochat.ai/papers/10.1038/nchembio.1986
The paper
Rees, M. G., Seashore-Ludlow, B., Cheah, J. H., Adams, D. J., Price, E. V., Gill, S., Javaid, S., Coletti, M. E., Jones, V. L., Bodycombe, N. E., Soule, C. K., Alexander, B., Li, A., Montgomery, P., Kotz, J. D., Hon, C. S.-Y., Munoz, B., Liefeld, T., Dančík, V., . . . Schreiber, S. L. (2016). Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nature Chemical Biology. https://doi.org/10.1038/nchembio.1986

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.