Evidence map›Paper›PMID 35859897›Full record

ReviewFrontiers in cell and developmental biology2022

Why is Mortalin a Potential Therapeutic Target for Cancer?

A-Rum Yoon, Renu Wadhwa, Sunil C Kaul, Chae-Ok Yun

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 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 2 countries.

A-Rum YoonDepartment of Bioengineering, College of Engineering, Hanyang University, Seoul, South Korea.
Renu WadhwaAIST-INDIA DAILAB, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Sunil C KaulAIST-INDIA DAILAB, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Chae-Ok YunDepartment of Bioengineering, College of Engineering, Hanyang University, Seoul, South Korea.
Hanyang University · KRNational Institute of Advanced Industrial Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is one of the leading causes of death worldwide, accounting for nearly 10 million deaths in 2020. Therefore, cancer therapy is a priority research field to explore the biology of the disease and identify novel targets for the development of better treatment strategies. Mortalin is a member of the heat shock 70 kDa protein family. It is enriched in several types of cancer and contributes to carcinogenesis in various ways, including inactivation of the tumor suppressor p53, deregulation of apoptosis, induction of epithelial-mesenchymal transition, and enhancement of cancer stemness. It has been studied extensively as a therapeutic target for cancer treatment, and several types of anti-mortalin molecules have been discovered that effectively suppress the tumor cell growth. In this review, we 1) provide a comprehensive sketch of the role of mortalin in tumor biology; 2) discuss various anti-mortalin molecules, including natural compounds, synthetic small molecules, peptides, antibodies, and nucleic acids, that have shown potential for cancer treatment in laboratory studies; and 3) provide future perspectives in cancer treatment.

Indexed as

canceri-mot abMKT-077mortalinmortaparibmot-Adonwithaferin Awithanone

Identifiers

PMID35859897
PMCPMC9290191
OpenAlexW4283698144

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.