Evidence map›Paper›PMID 36726166›Full record

ArticleBMC medicine2023

PMCA inhibition reverses drug resistance in clinically refractory cancer patient-derived models.

Ki Cheong Park, Jung Min Kim, Sang Yong Kim, Seok-Mo Kim, Jin Hong Lim, Min Ki Kim, Sungsoon Fang, Yonjung Kim, Gordon B Mills, Sung Hoon Noh and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.9field-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

8 citing papers in PubMed, 17 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

11 authors at 3 institutions in 2 countries.

Ki Cheong ParkDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0002-3435-3985
Jung Min KimDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.
Sang Yong KimDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.
Seok-Mo KimDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jin Hong LimDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.
Min Ki KimSeverance Biomedical Science Institute, BK21 PLUS project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
Sungsoon FangSeverance Biomedical Science Institute, BK21 PLUS project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
Yonjung KimEONE-DIAGNOMICS Genome Center, New drug R&D Center, 291 Harmony-ro, Yeonsu-gu, Incheon, 22014, Republic of Korea.
Gordon B MillsDepartment of Systems Biology, the University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sung Hoon NohDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jae-Ho CheongDepartment of Surgery, Systems Cancer Biology & Biomarker Research Lab, Yonsei University College of Medicine, Seoul, Republic of Korea. jhcheong@yuhs.ac.
Yonsei University · KRGenome and Company (South Korea) · KRThe University of Texas MD Anderson Cancer Center · US

Funding

Korea Health Industry Development Institute HI14C1324Korea Health Industry Development Institute HI18C1188the National Research Foundation of Korea 2017R1D1A1B03029716
6 · The paper itself

Abstract

backgroundCancer cells have developed molecular strategies to cope with evolutionary stressors in the dynamic tumor microenvironment. Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1α) is a metabolic rheostat that regulates diverse cellular adaptive behaviors, including growth and survival. However, the mechanistic role of PGC1α in regulating cancer cell viability under metabolic and genotoxic stress remains elusive.

methodsWe investigated the PGC1α-mediated survival mechanisms in metabolic stress (i.e., glucose deprivation-induced metabolic stress condition)-resistant cancer cells. We established glucose deprivation-induced metabolic stress-resistant cells (selected cells) from parental tumor cells and silenced or overexpressed PGC1α in selected and parental tumor cells.

resultsSeveral in vitro and in vivo mouse experiments were conducted to elucidate the contribution of PGC1α to cell viability in metabolic stress conditions. Interestingly, in the mouse xenograft model of patient-derived drug-resistant cancer cells, each group treated with an anti-cancer drug alone showed no drastic effects, whereas a group that was co-administered an anti-cancer drug and a specific PMCA inhibitor (caloxin or candidate 13) showed marked tumor shrinkage.

conclusionsOur results suggest that PGC1α is a key regulator of anti-apoptosis in metabolic and genotoxic stress-resistant cells, inducing PMCA expression and allowing survival in glucose-deprived conditions. We have discovered a novel therapeutic target candidate that could be employed for the treatment of patients with refractory cancers.

Indexed as

NeoplasmsAnimalsDrug ResistanceHumansMicePeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaStress, PhysiologicalTumor MicroenvironmentPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaCandidate 13Drug-resistant cancerGlucose deprivation-induced metabolic stress-resistant cancerPGC1αPMCA

Identifiers

PMID36726166
PMCPMC9893610
OpenAlexW4318768306

What Socratic 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 Socratic graph.