Evidence map›Paper›PMID 26912667›Full record

ArticleMolecular & cellular proteomics : MCP2016

Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

Jennifer G Abelin, Jinal Patel, Xiaodong Lu, Caitlin M Feeney, Lola Fagbami, Amanda L Creech, Roger Hu, Daniel Lam, Desiree Davison, Lindsay Pino and 10 more

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
11.8field-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

56 citing papers in PubMed, 102 citations in OpenAlex.

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  7. A framework for quality control in quantitative proteomics.bioRxiv : the preprint server for biology · 2024
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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

20 authors at 3 institutions in 1 country.

Jennifer G AbelinFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Jinal PatelFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Xiaodong LuFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Caitlin M FeeneyFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Lola FagbamiFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Amanda L CreechFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Roger HuFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Daniel LamFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Desiree DavisonFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Lindsay PinoFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Jana W QiaoFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Eric KuhnFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Adam OfficerFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Jianxue Li§Beth-Israel Deaconess Medical Center, Boston, Massachusetts, 02215;
Susan AbbatielloFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Aravind SubramanianFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Richard Sidman§Beth-Israel Deaconess Medical Center, Boston, Massachusetts, 02215;
Evan Snyder¶Sanford-Burhnam Research Institute, La Jolla, California 92037.
Steven A CarrFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
Jacob D JaffeFrom the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142; jjaffe@broadinstitute.org.
Broad Institute · USBeth Israel Deaconess Medical Center · USSanford Burnham Prebys Medical Discovery Institute · US

Funding

Proteo-genomic Discovery, Prioritization and Verification of Cancer BiomarkersU24CA160034 · NCI · BROAD INSTITUTE, INC. · PI CARR, STEVEN A, PAULOVICH, AMANDA G · 2011 to 2016
$16.2M
There and Back Again: Epigenetic Reinforcement of Cellular Signaling States - OverallU54HG008097 · NHGRI · BROAD INSTITUTE, INC. · PI JAFFE, JACOB DAVID · 2014 to 2019
$9.3M
Accelerated Protein Signaling SignaturesU01CA164186 · NCI · BROAD INSTITUTE, INC. · PI JAFFE, JACOB DAVID, MACCOSS, MICHAEL · 2011 to 2013
$2.2M
NCI NIH HHS U01 CA164186NCI NIH HHS U24 CA160034NHGRI NIH HHS U54 HG008097
6 · The paper itself

Abstract

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.

Indexed as

AnimalsCells, CulturedEmbryonic Stem CellsHigh-Throughput Screening AssaysHumansMCF-7 CellsMicePhosphoproteinsProteomicsSignal TransductionSmall Molecule LibrariesPhosphoproteinsSmall Molecule Libraries

Identifiers

PMID26912667
PMCPMC4858944
OpenAlexW2285216336

What OpenQuestion holds

Textmetadata
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.