Evidence map›Paper›PMID 34459070›Full record

ArticleCancer science2021

Inhibition of acid ceramidase elicits mitochondrial dysfunction and oxidative stress in pancreatic cancer cells.

Tomohiko Taniai, Yoshihiro Shirai, Yohta Shimada, Ryoga Hamura, Mitsuru Yanagaki, Naoki Takada, Takashi Horiuchi, Koichiro Haruki, Kenei Furukawa, Tadashi Uwagawa and 6 more

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

17 citing papers in PubMed, 15 citations in OpenAlex.

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  2. FASEB bioAdvances · 2026
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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

16 authors at 3 institutions in 1 country.

Tomohiko TaniaiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0001-8911-5530
Yoshihiro ShiraiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-4907-0101
Yohta ShimadaDivision of Gene Therapy, Research Center for Medical Science, The Jikei University School of Medicine, Tokyo, Japan.
Ryoga HamuraDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0003-1670-4435
Mitsuru YanagakiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0003-0664-5830
Naoki TakadaDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0003-3192-7979
Takashi HoriuchiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.
Koichiro HarukiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-1686-3228
Kenei FurukawaDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5081-6417
Tadashi UwagawaDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.
Kazuhito TsuboiDepartment of Pharmacology, Kawasaki Medical School, Kurashiki, Japan.
Yasuo OkamotoDepartment of Pharmacology, Kawasaki Medical School, Kurashiki, Japan.
Shu ShimadaDepartment of Molecular Oncology Graduate School of Medicine, Tokyo Medical and Dental University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-4962-0636
Shinji TanakaDepartment of Molecular Oncology Graduate School of Medicine, Tokyo Medical and Dental University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-7718-3453
Toya OhashiDivision of Gene Therapy, Research Center for Medical Science, The Jikei University School of Medicine, Tokyo, Japan.
Toru IkegamiDepartment of Surgery, The Jikei University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0001-5792-5045
Jikei University School of Medicine · JPKawasaki Medical School · JPTokyo Medical and Dental University · JP

Funding

Japan Society for the Promotion of Science 17K16584Japan Society for the Promotion of Science 20K17665The Jikei University Research Fund for Graduate StudentsUehara Memorial Foundation
6 · The paper itself

Abstract

Although the inhibition of acid ceramidase (AC) is known to induce antitumor effects in various cancers, there are few reports in pancreatic cancer, and the underlying mechanisms remain unclear. Moreover, there is currently no safe administration method of AC inhibitor. Here the effects of gene therapy using siRNA and shRNA for AC inhibition with its mechanisms for pancreatic cancer were investigated. The inhibition of AC by siRNA and shRNA using an adeno-associated virus 8 (AAV8) vector had antiproliferative effects by inducing apoptosis in pancreatic cancer cells and xenograft mouse model. Acid ceramidase inhibition elicits mitochondrial dysfunction, reactive oxygen species accumulation, and manganese superoxide dismutase suppression, resulting in apoptosis of pancreatic cancer cells accompanied by ceramide accumulation. These results elucidated the mechanisms underlying the antitumor effect of AC inhibition in pancreatic cancer cells and suggest the potential of the AAV8 vector to inhibit AC as a therapeutic strategy.

Indexed as

Oxidative StressAcid CeramidaseAnimalsApoptosisCell Line, TumorCeramidesDependovirusGenetic TherapyGenetic VectorsHumansMaleMiceMice, Inbred BALB CMice, NudeMitochondrial DiseasesPancreatic NeoplasmsAcid CeramidaseASAH1 protein, humanCeramidesReactive Oxygen SpeciesRNA, Small InterferingSuperoxide Dismutaseacid ceramidaseadeno-associated virusmitochondrial dysfunctionoxidative stresspancreatic ductal adenocarcinoma

Identifiers

PMID34459070
PMCPMC8586682
OpenAlexW3198518645

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.