Evidence map›Paper›PMID 23255104›Full record

ArticleCell cycle (Georgetown, Tex.)2013

mTORC1 and p53: clash of the gods?

Paul Hasty, Zelton Dave Sharp, Tyler J Curiel, Judith Campisi

Open access · bronzeAbstract read
In one paragraph

Article in Cell cycle (Georgetown, Tex.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

57 citing papers in PubMed, 97 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Paul HastyDepartment of Molecular Medicine and Institute of Biotechnology, University of Texas Health Science Center, San Antonio, TX, USA. hastye@uthscsa.edu
Zelton Dave Sharp
Tyler J Curiel
Judith Campisi
The University of Texas Health Science Center at San Antonio · USLawrence Berkeley National Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A balance must be struck between cell growth and stress responses to ensure that cells proliferate without accumulating damaged DNA. This balance means that optimal cell proliferation requires the integration of pro-growth and stress-response pathways. mTOR (mechanistic target of rapamycin) is a pleiotropic kinase found in complex 1 (mTORC1).The mTORC1 pathway governs a response to mitogenic signals with high energy levels to promote protein synthesis and cell growth. In contrast, the p53DNA damage response pathway is the arbiter of cell proliferation, restraining mTORC1 under conditions of genotoxic stress. Recent studies suggest a complicated integration of these pathways to ensure successful cell growth and proliferation without compromising genome maintenance. Deciphering this integration could be key to understanding the potential clinical usefulness of mTORC1 inhibitors like rapamycin. Here we discuss how these p53-mTORC1 interactions might play a role in the suppression of cancer and perhaps the development of cellular senescence and organismal aging.

Indexed as

AgingDNA RepairHumansMechanistic Target of Rapamycin Complex 1Mitogen-Activated Protein Kinase 14Multiprotein ComplexesNeoplasmsProto-Oncogene Proteins c-aktRibosomal Protein S6 Kinases, 70-kDaTOR Serine-Threonine KinasesTumor Suppressor Protein p53Mechanistic Target of Rapamycin Complex 1Mitogen-Activated Protein Kinase 14Multiprotein ComplexesProto-Oncogene Proteins c-aktribosomal protein S6 kinase, 70kD, polypeptide 1Ribosomal Protein S6 Kinases, 70-kDaTOR Serine-Threonine KinasesTumor Suppressor Protein p53

Identifiers

PMID23255104
PMCPMC3570511
OpenAlexW2048512670

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.