Evidence map›Paper›PMID 38357945›Full record

ArticleCombinatorial chemistry & high throughput screening2025

A Novel KIF4A-related Model for Predicting Immunotherapy Response and Prognosis in Kidney Renal Clear Cell Carcinoma.

Guang Hua Yang, Xu Dong Ma, Xi Feng Wei, Ran Lu Liu, Chao Wang

Abstract readDataset
PubMed Publisher
In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Guang Hua YangDepartment of Urology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.ORCID 0000-0002-9315-4927
Xu Dong MaDepartment of Urology, Baotou Central Hospital, Inner Mongolia Medical University, Baotou, China.
Xi Feng WeiDepartment of Urology, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China.
Ran Lu LiuDepartment of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Chao WangDepartment of Urology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.

Funding

Fundamental Research Program of Shanxi Province 20210302123490
6 · The paper itself

Abstract

backgroundThe efficacy of chemotherapy in treating Kidney Renal Clear Cell Carcinoma (KIRC) is limited, whereas immunotherapy has shown some promising clinical outcomes. In this context, KIF4A is considered a potential therapeutic target for various cancers. Therefore, identifying the mechanism of KIF4A that can predict the prognosis and immunotherapy response of KIRC would be of significant importance.

methodsBased on the TCGA Pan-Cancer dataset, the prognostic significance of the KIF4A expression across 33 cancer types was analyzed by univariate Cox algorithm. Furthermore, overlapping differentially expressed genes (DEGs1) between the KIF4A high- and lowexpression groups and DEGs2 between the KIRC and normal groups were also analyzed. Machine learning and Cox regression algorithms were performed to obtain biomarkers and construct a prognostic model. Finally, the role of KIF4A in KIRC was analyzed using quantitative real-time PCR, transwell assay, and EdU experiment.

resultsOur analysis revealed that KIF4A was significant for the prognosis of 13 cancer types. The highest correlation with KIF4A was found for KICH among the tumour mutation burden (TMB) indicators. Subsequently, a prognostic model developed with UBE2C, OTX1, PPP2R2C, and RFLNA was obtained and verified with the Renal Cell Cancer-EU/FR dataset. There was a positive correlation between risk score and immunotherapy. Furthermore, the experiment results indicated that KIF4A expression was considerably increased in the KIRC group. Besides, the proliferation, migration, and invasion abilities of KIRC tumor cells were significantly weakened after KIF4A was knocked out.

conclusionWe identified four KIF4A-related biomarkers that hold potential for prognostic assessment in KIRC. Specifically, early implementation of immunotherapy targeting these biomarkers may yield improved outcomes for patients with KIRC.

Indexed as

Carcinoma, Renal CellImmunotherapyKidney NeoplasmsKinesinsBiomarkers, TumorCell LineGene Expression Regulation, NeoplasticHumansMachine LearningModels, BiologicalMutationPrognosisBiomarkers, TumorKIF4A protein, humanKinesinsKidney renal clear cell carcinomaKIF4APan-Cancerprognosisrisk scoretumour mutation burden.

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.