Evidence map›Paper›PMID 35002290›Full record

ArticlePharmacogenomics and personalized medicine2021

Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC).

Xiaojie Bai, Yuanfei Cao, Xin Yan, Kurerban Tuoheti, Guowei Du, Zhao Chen, Huahui Wu, Linfa Guo, Tongzu Liu

Open access · goldAbstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
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  10. ESPL1 is Elevated in Hepatocellular Carcinoma and Predicts Prognosis.International journal of general medicine · 2022
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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.

Xiaojie BaiDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Yuanfei CaoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Xin YanDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Kurerban TuohetiDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Guowei DuDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Zhao ChenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Huahui WuDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Linfa GuoDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Tongzu LiuDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
Zhongnan Hospital of Wuhan University · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to carry out a pan-cancer analysis of kinesin family member 23 (KIF23) and construct a predictive model for the prognosis of clear cell renal cell carcinoma (ccRCC) patients.

methodsWe evaluated the differential expression of KIF23 in pan-cancer by The Cancer Genome Atlas (TCGA) and Oncomine database. Then, the correlation between KIF23 with prognosis, clinical grade, stage, immune subtype, tumor mutation burden (TMB), microsatellite instability (MSI) and immune microenvironment was explored by TCGA, an integrated repository portal for tumor-immune system interactions (TISIDB) and cBioPortal. Subsequently, we screened out ferroptosis-related genes (FRGs) related to KIF23 and constructed a risk score model. Univariate Cox analysis was used to determine independent prognostic factors for ccRCC overall survival (OS), and a nomogram was established. Furthermore, gene set enrichment analysis (GSEA) was applied to study the biological functions and pathways of KIF23. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to evaluate the expression of KIF23.

resultsKIF23 was highly expressed in most tumors. Further, KIF23 was strongly correlated with prognosis, clinical grade, stage, immune subtype, TMB, MSI and immune microenvironment in different tumors. We found that KIF23 was significantly associated with all aspects of ccRCC. Then, 8 FRGs were identified to construct a risk score model together with KIF23. And a prognostic nomogram prediction model of OS was established. After GSEA analysis, cell cycle, condensed chromosome and other physiological processes were screened out. Finally, qRT-PCR verified the high expression of KIF23 in ccRCC cell lines than normal kidney cell line.

conclusionKIF23 may act as a pivotal part in occurrence and progression of different tumors. In ccRCC, KIF23 can be a great prognostic biomarker, and the nomogram based on KIF23 may contribute to better treatment plans for ccRCC patients.

Indexed as

clear cell renal cell carcinomaferroptosisnomogram

Identifiers

PMID35002290
PMCPMC8725058
OpenAlexW4200334491

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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 OpenQuestion graph.