Evidence map›Paper›PMID 38254728›Full record

ArticleCancers2024

Metabolomics, Transcriptome and Single-Cell RNA Sequencing Analysis of the Metabolic Heterogeneity between Oral Cancer Stem Cells and Differentiated Cancer Cells.

Yuwen Miao, Pan Wang, Jinyan Huang, Xin Qi, Yingjiqiong Liang, Wenquan Zhao, Huiming Wang, Jiong Lyu, Huiyong Zhu

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

12 citing papers in PubMed, 9 citations in OpenAlex.

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  12. Cancer Stem Cells from Definition to Detection and Targeted Drugs.International journal of molecular sciences · 2024
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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

9 authors at 2 institutions in 1 country.

Yuwen MiaoStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou 310020, China.
Pan WangDepartment of Stomatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0003-9500-1451
Jinyan HuangBiomedical Big Data Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Xin QiDepartment of Stomatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Yingjiqiong LiangBiomedical Big Data Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Wenquan ZhaoDepartment of Stomatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Huiming WangStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou 310020, China.
Jiong LyuDepartment of Stomatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0000-0001-6280-8687
Huiyong ZhuDepartment of Stomatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
First Affiliated Hospital Zhejiang University · CNStomatology Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the distinct metabolic characteristics of cancer stem cells (CSC) may allow us to better cope with the clinical challenges associated with them. In this study, OSCC cell lines (CAL27 and HSC3) and multicellular tumor spheroid (MCTS) models were used to generate CSC-like cells. Quasi-targeted metabolomics and RNA sequencing were used to explore altered metabolites and metabolism-related genes. Pathview was used to display the metabolites and transcriptome data in a KEGG pathway. The single-cell RNA sequencing data of six patients with oral cancer were analyzed to characterize in vivo CSC metabolism. The results showed that 19 metabolites (phosphoethanolamine, carbamoylphosphate, etc.) were upregulated and 109 metabolites (2-aminooctanoic acid, 7-ketocholesterol, etc.) were downregulated in both MCTS cells. Integration pathway analysis revealed altered activity in energy production (glycolysis, citric cycle, fatty acid oxidation), macromolecular synthesis (purine/pyrimidine metabolism, glycerophospholipids metabolism) and redox control (glutathione metabolism). Single-cell RNA sequencing analysis confirmed altered glycolysis, glutathione and glycerophospholipid metabolism in in vivo CSC. We concluded that CSCs are metabolically inactive compared with differentiated cancer cells. Thus, oral CSCs may resist current metabolic-related drugs. Our result may be helpful in developing better therapeutic strategies against CSC.

Indexed as

cancer stem cellmetabolic heterogeneitymetabolomicsoral cancersingle-cell RNA sequencing

Identifiers

PMID38254728
PMCPMC10813553
OpenAlexW4390614430

What OpenQuestion holds

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LicenceCC BY
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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.