Evidence map›Paper›PMID 33644773›Full record

ArticleSTAR protocols2021

Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis.

Li Wang, John A Wrobel, Ling Xie, Xian Chen

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in STAR protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 58% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Li WangDepartment of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
John A WrobelDepartment of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Ling XieDepartment of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Xian ChenDepartment of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
University of North Carolina at Chapel Hill · US

Funding

Cancer Proteome Center at Washington Univ, Univ of North Carolina & Boise StateU24CA160035 · NCI · WASHINGTON UNIVERSITY · PI CHEN, XIAN, ELLIS, MATTHEW J · 2011 to 2016
$11.8M
Molecular mechanisms of CIB1 signalingR01GM133107 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHEN, XIAN · 2019 to 2020
$617k
NCI NIH HHS U24 CA160035NIGMS NIH HHS R01 GM133107
6 · The paper itself

Abstract

Inter- or intra-patient tumor heterogeneity hinders the discovery of biomarkers for predicting individualized prognosis. Here, we present a protocol for an alternative splicing activity-based proteogenomic approach for identification of candidate prognostic markers in cancer cell lines and human breast cancer specimens. The pull-down of protein complexes with intronic splicing enhancer (ISE) probes is followed by tandem mass spectrometry (MS/MS) peptide sequencing. The proteogenomic analysis of data from these ISE-MS/MS assays identifies new prognostic markers that can be utilized to stratify patients with poor prognosis. For complete details on the use and execution of this protocol, please refer to Wang et al. (2018).

Indexed as

Alternative SplicingEnhancer Elements, GeneticIntronsProteogenomicsRNA, NeoplasmHumansMCF-7 CellsNeoplasmsPredictive Value of TestsPrognosisRNA, NeoplasmCancerGenomicsMass spectrometryMolecular/chemical probesProteomics

Identifiers

PMID33644773
PMCPMC7887646
OpenAlexW3126757318

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.