Evidence map›Paper›PMID 35579380›Full record

ArticleJournal of cellular and molecular medicine2022

Combination of FOXD1 and Plk2: A novel biomarker for predicting unfavourable prognosis of colorectal cancer.

Yaping Zong, Yiming Miao, Wenchang Li, Minhua Zheng, Zhuoqing Xu, Han Gao, Wenqing Feng, Zifeng Xu, Jingkun Zhao, Lifei Shen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

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  8. LMNB1 targets FOXD1 to promote progression of prostate cancer.Experimental and therapeutic medicine · 2023
    Article
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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

11 authors at 1 institution in 1 country.

Yaping ZongDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Yiming MiaoDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Wenchang LiDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Minhua ZhengDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Zhuoqing XuDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Han GaoDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Wenqing FengDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Zifeng XuDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Jingkun ZhaoDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Lifei ShenDepartment of Obstetrics and Gynecology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.
Aiguo LuDepartment of General Surgery, Ruijin hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China.ORCID 0000-0003-4028-0644
Ruijin Hospital · CN

Funding

Foundation of Shanghai Municipal Health Committee 202040144National Nature Science Foundation for Youth 81802326National Nature Science Foundation of China 81871933
6 · The paper itself

Abstract

Colorectal cancer (CRC) is a worldwide disease with worse survival. Our objective is to identify previously unrecognized prognostic factors to better evaluate disease progression. Seven GEO datasets were collected and analysed using R software, followed by KEGG enrichment analysis and TFs network construction. LASSO-COX analysis was performed to select the most useful prognostic features. COX model was used to analyse prognostic factors associated with OS. The survival curve was constructed using Kaplan-Meier analysis. A Nomogram model was also constructed to predict prognosis. A total of 3559 differentially expressed genes (DEGs) and 66 differentially expressed transcription factors were identified. FOXD1 was identified as the most differentially expressed factor of TFs covering the most downstream DEGs and independent risk prognostic factor. Next, FOXD1 expression was detected using immunohistochemical staining in 131 CRC patients' tissue and the association between FOXD1 expression and clinicopathologic features was analysed. High expression of FOXD1 was correlated with TNM stage and pathological differentiation. Multivariate COX regression analyses confirmed that FOXD1 high-expression, TNM stage and tumour differentiation were independent prognostic risk factor of OS and DFS. Patients with high expression of FOXD1 were more likely to have poor overall survival and disease-free survival. The combination of FOXD1 and Plk2 which we have previously reported allowed us to predict the survival of post-surgical CRC patients more accurately, adding to the former prognostic model based on the TNM Stage. The results showed that patients with high expression of both FOXD1 and Plk2 have the worst survival. A combination of FOXD1 and Plk2 can better evaluate patients' survival.

Indexed as

Colorectal NeoplasmsForkhead Transcription FactorsProtein Serine-Threonine KinasesBiomarkers, TumorDisease-Free SurvivalHumansKaplan-Meier EstimatePredictive Value of TestsPrognosisProportional Hazards ModelsBiomarkers, TumorForkhead Transcription FactorsFOXD1 protein, humanPLK2 protein, humanProtein Serine-Threonine Kinasesbiomarkercolorectal cancerFOXD1nomogramPlk2

Identifiers

PMID35579380
PMCPMC9189346
OpenAlexW4280534092

What OpenQuestion holds

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LicenceCC BY
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.