Protocol to analyze dysregulation of the eIF4F complex in human cancers using R software and large public datasets.

Su Wu, Gerhard Wagner

Open access · goldAbstract read

In one paragraph

Article in STAR protocols, 2022. 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

0.2field-weighted citation impact, top 51% 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, 2 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

2 authors at 1 institution in 1 country.

Su WuDepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address: su_wu@hms.harvard.edu.

Gerhard WagnerDepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address: gerhard_wagner@hms.harvard.edu.

Harvard University · US

Funding

Protein Production CoreP01AI143565 · NIAID · DANA-FARBER CANCER INST · PI Matthew J. Lang, ELLIS L REINHERZ · 2020 to 2026

$19.9M

Roles of Eukaryotic Translation Initiation Factors in Gene ExpressionR01CA200913 · NCI · HARVARD MEDICAL SCHOOL · PI WAGNER, GERHARD · 2016 to 2020

$2.3M

NCI NIH HHS R01 CA200913NIAID NIH HHS P01 AI143565

6 · The paper itself

Abstract

Understanding dysregulation of the eukaryotic initiation factor 4F (eIF4F) complex across tumor types is critical to cancer treatment development. We present a protocol and accompanying R package "eIF4F.analysis". We describe analysis of copy number status, gene abundance and stoichiometry, survival probability, expression covariation, correlating genes, mRNA/protein correlation, and protein co-expression. Using publicly available large multi-omics data, eIF4F.analysis permits computationally derived and statistically powerful inferences regarding initiation factor regulation in human cancers and clinical relevance of protein interactions within the eIF4F complex. For complete details on the use and execution of this protocol, please refer to Wu and Wagner (2021).

Indexed as

Eukaryotic Initiation Factor-4FNeoplasmsHumansProtein Processing, Post-TranslationalRNA, MessengerEukaryotic Initiation Factor-4FRNA, MessengerBioinformaticsCancerProteomicsRNAseq

Identifiers

PMID36595939

DOI10.1016/j.xpro.2022.101880

PMCPMC9768376

OpenAlexW4311840373

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.