Evidence map›Paper›PMID 38890649›Full record

ArticleBMC gastroenterology2024

Finding key genes (UBE2T, KIF4A, CDCA3, and CDCA5) co-expressed in hepatitis, cirrhosis and hepatocellular carcinoma based on multiple bioinformatics techniques.

Yingai Zhang, Weiling Yu, Shuai Zhou, Jingchuan Xiao, Xiaoyu Zhang, Haoliang Yang, Jianquan Zhang

Abstract read
In one paragraph

Article in BMC gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

7 authors.

Yingai ZhangCentral Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Weiling YuDepartment of Chemotherapy, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Shuai ZhouHepatobiliary surgery, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Jingchuan XiaoCentral Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Xiaoyu ZhangHepatobiliary surgery, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Haoliang YangCentral Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China.
Jianquan ZhangHepatobiliary surgery, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, No.43 Renmin Road, Haikou, Hainan, 570208, China. jianquanzhang@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Hepatitis B virus (HBV) is one of the major causes of liver cirrhosis (LC) and HCC. Therefore, the discovery of common markers for hepatitis B or LC and HCC is crucial for the prevention of HCC.

methodsExpressed genes for to chronic active hepaititis B (CAH-B), LC and HCC were obtained from the GEO and TCGA databases, and co-expressed genes were screened using Protein-protein interaction (PPI) networks, least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine - recursive feature elimination (SVM-RFE). The prognostic value of genes was assessed using Kaplan-Meier (KM) survival curves. Columnar line plots, calibration curves and receiver operating characteristic (ROC) curves of individual genes were used for evaluation. Validation was performed using GEO datasets. The association of these key genes with HCC clinical features was explored using the UALCAN database ( https://ualcan.path.uab.edu/index.html ).

resultsBased on WGCNA analysis and TCGA database, the co-expressed genes (565) were screened. Moreover, the five algorithms of MCODE (ClusteringCoefficient, MCC, Degree, MNC, and DMNC) was used to select one of the most important and most closely linked clusters (the top 50 genes ranked). Using, LASSO regression model, RF model and SVM-RFE model, four key genes (UBE2T, KIF4A, CDCA3, and CDCA5) were identified for subsequent research analysis. These 4 genes were highly expressed and associated with poor prognosis and clinical features in HCC patients.

conclusionThese four key genes (UBE2T, KIF4A, CDCA3, and CDCA5) may be common biomarkers for CAH-B and HCC or LC and HCC, promising to advance our understanding of the molecular basis of CAH-B/LC/HCC progression.

Indexed as

Carcinoma, HepatocellularCell Cycle ProteinsComputational BiologyKinesinsLiver CirrhosisLiver NeoplasmsBiomarkers, TumorHepatitis B, ChronicHumansKaplan-Meier EstimateMalePrognosisProtein Interaction MapsSupport Vector MachineBiomarkers, TumorCell Cycle ProteinsKIF4A protein, humanKinesinsBioinformaticsChronic active hepaititis BCo-expressed genesHepatocellular carcinomaLiver cirrhosis

Identifiers

PMID38890649
PMCPMC11184838

What OpenQuestion holds

Textmetadata
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.