Evidence map›Paper›PMID 37539322›Full record

ArticleHeliyon2023

Gene expression networks involved in multiple cellular programs coexist in individual hepatocellular cancer cells.

Jin Zhao, Ran Lu, Chen Jin, Siying Li, Yulin Chen, Qiaorong Huang, Xue Li, Wentong Meng, Hong Wu, Tianfu Wen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 1 institution in 1 country.

Jin ZhaoDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Ran LuDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Chen JinDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Siying LiDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Yulin ChenDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Qiaorong HuangDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Xue LiDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Wentong MengDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Hong WuDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Tianfu WenDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Xianming MoDepartment of Liver Surgery, Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gene expression networks of a single cell can be used to reveal cell type- and condition-specific patterns that account for cell states, cell identity, and its responses to environmental changes. We applied single cell sequencing datasets to define mRNA patterns and visualized potential cellular capacities among hepatocellular cancer cells. The expressing numbers and levels of genes were highly heterogenous among the cancer cells. The cellular characteristics were dependent strongly on the expressing numbers and levels of genes, especially oncogenes and anti-oncogenes, in an individual cancer cell. The transcriptional activations of oncogenes and anti-oncogenes were strongly linked to inherent multiple cellular programs, some of which oppose and contend against other processes, in a cancer cell. The gene expression networks of multiple cellular programs proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, ATP production, and neurogenesis coexisted in an individual cancer cell. The findings give rise a hypothesis that a cancer cell expresses balanced combinations of genes and undergoes a given biological process by rapidly transmuting gene expressing networks.

Indexed as

Balanced combination of gene expressionsCellular programGene expression networksHepatocellular carcinomaIndividual cancer cellOncogene and anti-oncogene expression

Identifiers

PMID37539322
PMCPMC10393770
OpenAlexW4384565000

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.