Evidence mapPaperPMID 38835670Full record

ArticleFrontiers in pharmacology2024

Protein and metabolic profiles of tyrosine kinase inhibitors co-resistant liver cancer cells.

Zengbin Wang, Linqing Wu, Yu Zhou, Zhong Chen, Tao Zhang, Hong Wei, Zhihong Wang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
field-weighted citation impact
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

4 citing papers in PubMed.

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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.

Zengbin Wang *Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Linqing Wu *Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Yu Zhou *Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fujian Medical University, Fuzhou, China.
Zhong Chen *Department of Hepatobiliary Surgery, Fujian Provincial Hospital, Fuzhou, China.
Tao ZhangDepartment of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Hong WeiShengli Clinical Medical College of Fujian Medical University, Fuzhou, China.
Zhihong WangShengli Clinical Medical College of Fujian Medical University, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular Carcinoma (HCC) patients often develop resistance to tyrosine kinase inhibitors (TKIs) like sorafenib (SR) and lenvatinib (RR). We established HCC cell lines resistant to these drugs and analyzed the correlation between protein and metabolite profiles using bioinformatics. Our analysis revealed overexpression of MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1, and downregulation of IFITM3, CA4, AGR2, and SLC51B in drug-resistant cells. Differential signals are mainly enriched in steroid hormone biosynthesis, cell adhesion, and immune synapses, with metabolic pathways including cytochrome P450 drug metabolism, amino acid metabolism, and glycolysis. Proteomics and metabolomics analysis showed co-enrichment signals in drug metabolism, amino acids, glucose metabolism, ferroptosis, and other biological processes. Knocking down MISP, CHMP2B, IL-18, TMSB4X, and EFEMP1 significantly reduced drug resistance, indicating their potential as therapeutic response biomarkers. This study characterizes protein and metabolic profiles of drug-resistant HCC cells, exploring metabolite-protein relationships to enhance understanding of drug resistance mechanisms and clinical treatment.

Indexed as

drug resistancehepatocellular carcinomalenvatinibmetabolomicsproteomicssorafenib

Identifiers

PMID38835670
PMCPMC11149701

What Socratic holds

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Registered trials

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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.