Evidence mapPaperPMID 38183115Full record

ArticleJournal of translational medicine2024

Transcriptomic insights into UTUC: role of inflammatory fibrosis and potential for personalized treatment.

Keqiang Li, Zhenlin Huang, Guoqing Xie, Budeng Huang, Liang Song, Yu Zhang, Jinjian Yang

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2024. 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
5.2field-weighted citation impact, top 5% 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, 9 citations in OpenAlex.

  1. Article
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  6. Review
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  8. Unleashing Wnts: Wnt Ligands Fuel Cancer Spread.Journal of cancer biology · 2025
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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 at 2 institutions in 1 country.

Keqiang Li *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-9482-147X
Zhenlin Huang *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Guoqing Xie *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Budeng Huang *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Liang SongDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Yu ZhangDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China. william19940918@outlook.com.
Jinjian YangDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China. hzlinok@126.com.
Zhengzhou University · CNFirst Affiliated Hospital of Zhengzhou University · CN

Funding

National Natural Science Foundation of China 82172564National Natural Science Foundation of China 82303032
6 · The paper itself

Abstract

backgroundUpper tract urothelial carcinoma (UTUC) is a rare disease, belonging to the same category of urothelial cancers as bladder cancer (BC). Despite sharing similar non-surgical treatment modalities, UTUC demonstrates a higher metastasis propensity than BC. Furthermore, although both cancers exhibit similar molecular disease emergence mechanisms, sequencing data reveals some differences. Our study investigates the transcriptomic distinctions between UTUC and BC, explores the causes behind UTUC's heightened metastatic tendency, constructs a model for UTUC metastasis and prognosis, and propose personalized treatment strategies for UTUC.

methodsIn our research, we utilized differential gene expression analysis, interaction networks, and Cox regression to explore the enhanced metastatic propensity of UTUC. We formulated and validated a prognostic risk model using diverse techniques, including cell co-culture, reverse transcription quantitative polymerase chain reaction (rt-qPCR), western blotting, and transwell experiments. Our methodological approach also involved survival analysis, risk model construction, and drug screening leveraging the databases of CTRPv2, PRISM and CMap. We used the Masson staining technique for histological assessments. All statistical evaluations were conducted using R software and GraphPad Prism 9, reinforcing the rigorous and comprehensive nature of our research approach.

resultsScreening through inflammatory fibrosis revealed a reduction of extracellular matrix and cell adhesion molecules regulated by proteoglycans in UTUC compared with BC, making UTUC more metastasis-prone. We demonstrated that SDC1, LUM, VEGFA, WNT7B, and TIMP3, are critical in promoting UTUC metastasis. A risk model based on these five molecules can effectively predict the risk of UTUC metastasis and disease-free survival time. Given UTUC's unique molecular mechanisms distinct from BC, we discovered that UTUC patients could better mitigate the issue of poor prognosis associated with UTUC's easy metastasis through tyrosine kinase inhibitors (TKIs) alongside the conventional gemcitabine and cisplatin chemotherapy regimen.

conclusionsThe poor prognosis of UTUC because of its high metastatic propensity is intimately tied to inflammatory fibrosis induced by the accumulation of reactive oxygen species. The biological model constructed using the five molecules SDC1, LUM, VEGFA, WNT7B, and TIMP3 can effectively predict patient prognosis. UTUC patients require specialized treatments in addition to conventional regimens, with TKIs exhibiting significant potential.

Indexed as

Carcinoma, Transitional CellUrinary Bladder NeoplasmsGene Expression ProfilingHumansPrecision MedicineTranscriptomeAristolochic acidBladder CancerFibrosisTKIsUTUC

Identifiers

PMID38183115
PMCPMC10768331
OpenAlexW4390619446

What Socratic 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 Socratic graph.