Evidence map›Paper›PMID 29558908›Full record

ReviewBMC cancer2018

Impact of RUNX2 on drug-resistant human pancreatic cancer cells with p53 mutations.

Toshinori Ozaki, Meng Yu, Danjing Yin, Dan Sun, Yuyan Zhu, Youquan Bu, Meixiang Sang

Open access · goldAbstract readReview
In one paragraph

Review in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.5field-weighted citation impact, top 8% 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

33 citing papers in PubMed, 66 citations in OpenAlex.

  1. Article
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  3. Non-syndromic supernumerary teeth and association with a self-reported family history of cancer.Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie · 2025
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  12. Runt-related transcription factors in human carcinogenesis: a friend or foe?Journal of cancer research and clinical oncology · 2023
    Review
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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

7 authors at 5 institutions in 2 countries.

Toshinori OzakiLaboratory of DNA Damage Signaling, Chiba Cancer Center Research Institute, Chiba, 260-8717, Japan. tozaki@chiba-cc.jp.
Meng YuDepartment of Laboratory Animal of China Medical University, Shenyang, 110001, People's Republic of China.
Danjing YinResearch Center, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050017, People's Republic of China.
Dan SunDepartment of Urology, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Yuyan ZhuDepartment of Urology, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Youquan BuDepartment of Biochemistry and Molecular Biology, Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Meixiang SangResearch Center, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050017, People's Republic of China.
First Hospital of China Medical University · CNHebei Medical University · CNChiba Cancer Center · JPChina Medical University · CNChongqing Medical University · CN

Funding

Japan Society for the Promotion of Science (JSPS) 23501278
6 · The paper itself

Abstract

backgroundDespite the remarkable advances in the early diagnosis and treatment, overall 5-year survival rate of patients with pancreatic cancer is less than 10%. Gemcitabine (GEM), a cytidine nucleoside analogue and ribonucleotide reductase inhibitor, is a primary option for patients with advanced pancreatic cancer; however, its clinical efficacy is extremely limited. This unfavorable clinical outcome of pancreatic cancer patients is at least in part attributable to their poor response to anti-cancer drugs such as GEM. Thus, it is urgent to understand the precise molecular basis behind the drug-resistant property of pancreatic cancer and also to develop a novel strategy to overcome this deadly disease. REVIEW: Accumulating evidence strongly suggests that p53 mutations contribute to the acquisition and/or maintenance of drug-resistant property of pancreatic cancer. Indeed, certain p53 mutants render pancreatic cancer cells much more resistant to GEM, implying that p53 mutation is one of the critical determinants of GEM sensitivity. Intriguingly, runt-related transcription factor 2 (RUNX2) is expressed at higher level in numerous human cancers such as pancreatic cancer and osteosarcoma, indicating that, in addition to its pro-osteogenic role, RUNX2 has a pro-oncogenic potential. Moreover, a growing body of evidence implies that a variety of miRNAs suppress malignant phenotypes of pancreatic cancer cells including drug resistance through the down-regulation of RUNX2. Recently, we have found for the first time that forced depletion of RUNX2 significantly increases GEM sensitivity of p53-null as well as p53-mutated pancreatic cancer cells through the stimulation of p53 family TAp63/TAp73-dependent cell death pathway.

conclusionsTogether, it is likely that RUNX2 is one of the promising molecular targets for the treatment of the patients with pancreatic cancer regardless of their p53 status. In this review article, we will discuss how to overcome the serious drug-resistant phenotype of pancreatic cancer.

Indexed as

Drug Resistance, NeoplasmMutationAntimetabolites, AntineoplasticCore Binding Factor Alpha 1 SubunitDeoxycytidineGemcitabineHumansPancreatic NeoplasmsPrognosisTumor Suppressor Protein p53Antimetabolites, AntineoplasticCore Binding Factor Alpha 1 SubunitDeoxycytidineGemcitabineRUNX2 protein, humanTP53 protein, humanTumor Suppressor Protein p53GemcitabineMutant p53p53 familyRUNX2

Identifiers

PMID29558908
PMCPMC5861661
OpenAlexW2804828062

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.