Evidence map›Paper›PMID 31268164›Full record

ArticleInternational journal of oncology2019

Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data.

Hua-Yu Wu, Zhi-Gang Peng, Rong-Quan He, Bin Luo, Jie Ma, Xiao-Hua Hu, Yi-Wu Dang, Gang Chen, Shang-Ling Pan

Open access · hybridAbstract read
In one paragraph

Article in International journal of oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.3field-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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Alternative RNA Splicing in Fatty Liver Disease.Frontiers in endocrinology · 2021
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

9 authors at 2 institutions in 1 country.

Hua-Yu WuDepartment of Pathophysiology, School of Pre‑clinical Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Zhi-Gang PengDepartment of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Rong-Quan HeDepartment of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Bin LuoDepartment of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Jie MaDepartment of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Xiao-Hua HuDepartment of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Yi-Wu DangDepartment of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Gang ChenDepartment of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Shang-Ling PanDepartment of Pathophysiology, School of Pre‑clinical Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China.
Guangxi Medical University · CNFirst Affiliated Hospital of GuangXi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative splicing in tumor cells may be used as a molecular marker for the differential diagnosis of certain tumor types and assessment of prognosis. The aim of the present study was to investigate the associations among alternative splicing events, splicing factors, and the survival of patients with hepatocellular carcinoma (HCC). The alternative splicing event profiles of 371 patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq data, and the percent‑splice‑in value for each splicing event was calculated. The association between alternative splicing events and overall survival was evaluated. The most significant prognosis‑related splicing events were used to build up a prognostic index (PI). A total of 3,082 survival‑associated alternative splicing events were detected in HCC. The final PI based on all of the most significant candidate alternative splicing events exhibited better performance in distinguishing good or poor survival in patients compared to the PI based on a single type of splicing event. Receiver operating characteristic curves confirmed the high efficiency of the PI in predicting the survival of HCC patients, with an area under the curve of 0.914. The overexpression of 32 prognosis‑related splicing factor genes could also predict poor prognosis in patients with HCC. In conclusion, the constructed computational prognostic model based on HCC‑specific alternative splicing events may be used as a molecular marker for the prognosis of HCC.

Indexed as

Alternative SplicingGene Expression Regulation, NeoplasticBiomarkers, TumorCarcinoma, HepatocellularFemaleGene Expression ProfilingGene Regulatory NetworksHumansLiver NeoplasmsLymphatic MetastasisMaleMiddle AgedNeoplasm InvasivenessPrognosisRNA, MessengerROC CurveBiomarkers, TumorRNA, Messenger

Identifiers

PMID31268164
PMCPMC6615926
OpenAlexW2954495978

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.