Evidence map›Paper›PMID 37676078›Full record

ArticleCancer medicine2023

Integrating bioinformatic analysis and detailed experiments reveal an EMT-related biomarker for clear cell renal cell carcinoma.

Yue Ge, Sheng Ma, Junbiao Zhang, Zezhong Xiong, Beining Li, Siquan Ma, Bo Liu, Xiangyang Yao, Zhihua Wang

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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.

Yue GeDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Sheng MaDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Junbiao ZhangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zezhong XiongDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Beining LiDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Siquan MaDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Bo LiuDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-5118-1890
Xiangyang YaoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zhihua WangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-5155-1457
Tongji Hospital · CNWuhan University · CN

Funding

National Natural Science Foundation of China 81974400National Natural Science Foundation of China 82173068
6 · The paper itself

Abstract

backgroundEpithelial-mesenchymal transition (EMT) is associated with early recurrence and a poor prognosis in clear cell renal cell carcinoma (ccRCC). Studies have shown that EMT-related genes play an important regulatory role in tumor invasion, metastasis, and drug resistance, but the biological functions of EMT-related genes in ccRCC have not been specifically described.

methodsThe mRNA and clinicopathological data of 532 ccRCC and 72 normal samples were downloaded from The Cancer Genome Atlas as a training set. The gene expression matrix and survival data of 91 and 101 ccRCC samples were obtained from the International Cancer Genome Consortium and the ArrayExpress databases as validation sets, respectively. Univariate Cox analysis was used to identify and cluster prognostic genes, and multivariate Cox was performed to construct a prognostic signature. Moreover, CIBERSORT and CellMiner were used to assess immune cell infiltration and prognostic gene-drug sensitivity of the signature, respectively. Most importantly, we performed detailed experiments to verify the oncogenic function of a significant gene, OLFML2B, in vitro and in vivo.

resultsWe constructed a prognostic signature including seven genes and divided patients into high-risk and low-risk groups. The prognosis of the high-risk group was significantly worse than that of the low-risk group through Kaplan-Meier survival analysis. Interestingly, significant differences were observed in clinical characteristics and immune cell infiltration between the two groups. In addition, a significant correlation was found between the expression of prognostic genes and the sensitivity of tumor cells to chemotherapeutics. Most importantly, OLFML2B was proved to contribute to the proliferation and metastasis of ccRCC through detailed functional experiments in vitro and in vivo, and its prognostic efficacy for ccRCC patients was affirmed.

conclusionWe identified the prognostic signature of seven genes based on EMT-related genes as prognostic biomarkers for ccRCC. Besides, OLFML2B was validated as a potential diagnostic and therapeutic target for ccRCC by our detailed experiments.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellComputational BiologyEpithelial-Mesenchymal TransitionKidney NeoplasmsAnimalsCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiceMiddle AgedPrognosisBiomarkers, Tumorbiomarkerclear cell renal cell carcinomaepithelial-mesenchymal transitionOLFML2B

Identifiers

PMID37676078
PMCPMC10557903
OpenAlexW4386501639

What Socratic holds

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LicenceCC BY
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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.