Evidence map›Paper›PMID 31489573›Full record

ArticlePathology oncology research : POR2020

Bioinformatics Analysis Suggests the Combined Expression of AURKB and KIF18B Being an Important Event in the Development of Clear Cell Renal Cell Carcinoma.

Qianqian Liu, Xiling Zhang, Haichao Tang, Jinwei Liu, Chen Fu, Mingli Sun, Lin Zhao, Minjie Wei, Zhaojin Yu, Ping Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Pathology oncology research : POR, 2020. 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
1.7field-weighted citation impact, top 14% 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, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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.

Qianqian LiuDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Xiling ZhangDepartment of Urology, The Fourth Affiliated Hospital of China Medical University, Shenyang, 110000, Liaoning, China.
Haichao TangDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Jinwei LiuDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Chen FuDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Mingli SunDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Lin ZhaoDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Minjie WeiDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China.
Zhaojin YuDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, Liaoning, China. yuzhaojincmu@163.com.
Ping WangDepartment of Urology, The Fourth Affiliated Hospital of China Medical University, Shenyang, 110000, Liaoning, China. cmu4h_wangping@126.com.
China Medical University · CNFourth Affiliated Hospital of China Medical University · CN

Funding

National Key Clinical Specialty Discipline Construction Program of China (CN) No. U1608281the Construction of Translational Medicine Research Center and Collaborative Network in the Area of Bladder Diseases of Liaoning Province No. 2015225009the Double Hundred Program for Shenyang Scientific and Technological Innovation Projects 100040the National Natural Science Foundation of China No. 81601370
6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma with high metastatic rate and high mortality rate, needing to find potential therapeutic targets and develop new therapy methods. The bioinformatics analysis was used in this study to find the targets. Firstly, the expression profile of ccRCC obtained from The Cancer Genome Atlas (TCGA) database and GSE53757 dataset were used to identify the significant up-regulated genes. IL20RB, AURKB and KIF18B with the top efficiency of capable of diagnosis ccRCC from para cancer tissue, were over-expressed in ccRCC samples, and expressed increasedly with the development of ccRCC. There was the closest correlation between AURKB and KIF18B in these three over-expressed genes. AURKB (high) or KIF18B (high) were all significantly correlated with higher T, N, M stage, G grade and shorter overall survival (OS) of ccRCC patients. Furthermore, the ccRCC patients with AURKB (high) + KIF18B (high) showed worse clinical characteristics and prognosis. Multivariate COX regression analysis indicated AURKB (high) and KIF18B (high) were all the independent prognostic risk factor without considering the interaction of AURKB and KIF18B. Moreover, considering the combination of each other, only AURKB (high) + KIF18B (high) expression was an independent prognostic risk factor for ccRCC patients, but not other situations. Collectively, AURKB was closely associated with KIF18B, and the combined expression of AURKB and KIF18B may be of great significance in ccRCC.

Indexed as

AdultAgedAurora Kinase BBiomarkers, TumorCarcinoma, Renal CellComputational BiologyFemaleGene Expression ProfilingHumansKidney NeoplasmsKinesinsMaleMiddle AgedPrognosisTranscriptomeAURKB protein, humanAurora Kinase BBiomarkers, TumorKIF18B protein, humanKinesinsAURKBClear cell renal cell carcinomaCombined expressionDifferentially expressed genesKIF18B

Identifiers

PMID31489573
OpenAlexW2971867409

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.