Evidence map›Paper›PMID 23050960›Full record

ReviewAnnals of the New York Academy of Sciences2012

Unfolded protein response to autophagy as a promising druggable target for anticancer therapy.

Dong Hoon Suh, Mi-Kyung Kim, Hee Seung Kim, Hyun Hoon Chung, Yong Sang Song

Open access · bronzeAbstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed
8.0field-weighted citation impact, top 2% 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

75 citing papers in PubMed, 130 citations in OpenAlex.

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  9. Endoplasmic reticulum stress: a vital process and potential therapeutic target in chronic obstructive pulmonary disease.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2023
    Review
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15 more citing papers are in PubMed but not listed here.

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

5 authors at 1 institution in 1 country.

Dong Hoon SuhDepartment of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Mi-Kyung Kim
Hee Seung Kim
Hyun Hoon Chung
Yong Sang Song
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The endoplasmic reticulum (ER) is responsible for protein processing. In rapidly proliferating tumor cells, the ER tends to be overloaded with unfolded and misfolded proteins due to high metabolic demand. With the limited protein-folding capacity of the ER, tumor cells often suffer from more ER stress than do normal cells. Thus, cellular stress responses to cope with ER stress, such as the unfolded protein response (UPR) and autophagy, might be more activated in cancer cells than in normal cells. The complex signaling pathways from the UPR to autophagy provide promising druggable targets; a number of UPR/autophagy-targeted anticancer agents are currently in development in preclinical and clinical studies. In this short review we will discuss the potential anticancer efficacy of modulators of cellular stress responses, especially UPR and autophagy, on the basis of their signaling pathways. In addition, the current developmental status of the UPR/autophagy-targeted agents will be discussed.

Indexed as

Molecular Targeted TherapyAnimalsAnticarcinogenic AgentsAntineoplastic AgentsApoptosisAutophagyEndoplasmic Reticulum StressHumansNeoplasm ProteinsNeoplasmsSignal TransductionUnfolded Protein ResponseAnticarcinogenic AgentsAntineoplastic AgentsNeoplasm Proteins

Identifiers

PMID23050960
PMCPMC3499662
OpenAlexW1527321800

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.