Evidence map›Paper›PMID 34938069›Full record

ArticleDrug design, development and therapy2021

Establishment of Sunitinib-Resistant Xenograft Model of Renal Cell Carcinoma and the Identification of Drug-Resistant Hub Genes and Pathways.

Yingwei Xie, Wentai Shangguan, Zhiliang Chen, Zaosong Zheng, Yuqing Chen, Qiyu Zhong, Yishan Zhang, Jingying Yang, Dingjun Zhu, Wenlian Xie

Open access · goldAbstract read
In one paragraph

Article in Drug design, development and therapy, 2021. 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
1.2field-weighted citation impact, top 20% 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, 10 citations in OpenAlex.

  1. Biomedicines · 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

10 authors at 2 institutions in 1 country.

Yingwei Xie *Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Wentai Shangguan *Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Zhiliang Chen *Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Zaosong ZhengDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People's Republic of China.
Yuqing ChenDepartment of Pathology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Qiyu ZhongDepartment of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Yishan ZhangDepartment of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Jingying YangDepartment of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Dingjun ZhuDepartment of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.
Wenlian XieDepartment of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People's Republic of China.ORCID 0000-0001-5222-0767
Sun Yat-sen University · CNNanfang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSunitinib is the first-line targeted drug for the treatment of advanced renal cell carcinoma (RCC), but its therapeutic potential is limited by premature drug resistance. In an attempt to overcome this limitation, a sunitinib-resistant cell-derived xenograft (CDX) model of clear cell renal cell carcinoma (ccRCC) in vivo was constructed in this study. The molecular mechanism of drug resistance was analyzed using sequencing and bioinformatics tools.

methodsFirst, mice were injected subcutaneously with tumor cells 786-O to create tumors and were simultaneously treated with sunitinib. After three consecutive passages, a drug-resistant xenograft model was obtained. Then, key pathways and genes were identified via second-generation sequencing of the tissue and the examination of differentially expressed genes (DEGs) with bioinformatics tools.

resultsAnalysis of sequencing data revealed that 646 DEGs were upregulated and 465 were downregulated in the drug-resistant tissues when compared with the sensitive tissues. GO showed that the DEGs were significantly enriched in angiogenesis, cell hypoxia response, and apoptosis. KEGG analysis demonstrated that the main pathways were PI3K-Akt, HIF-1, NF-kappa B, and MAPK. Modular analysis of the PPI network indicated that the GO and KEGG analyses of module 1 with the highest ranking were mainly related to ubiquitinase activity. Similarly, the GO and KEGG analyses of the top 10 hub genes were also chiefly linked to ubiquitinase activity. Then, comprehensive expression analysis of the hub genes, and finally, the genes BTRC and TRIM32 were identified, which were consistent in all observations.

conclusionIn this study, through the construction of in vitro models and bioinformatics analysis, the important pathways and key genes related to ccRCC sunitinib resistance were discovered. Among them, ubiquitinase may play an important role in drug resistance and may be a potential therapeutic target and biomarker.

Indexed as

AnimalsBiomarkers, TumorCarcinoma, Renal CellComputational BiologyDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticGene Regulatory NetworksKidney NeoplasmsMiceSunitinibUbiquitinXenograft Model Antitumor AssaysBiomarkers, TumorSunitinibUbiquitinccRCCdrug resistancesunitinibubiquitinasexenograft model

Identifiers

PMID34938069
PMCPMC8687523
OpenAlexW4200270617

What OpenQuestion holds

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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.