Evidence map›Paper›PMID 31933519›Full record

ArticleCancer informatics2020

Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma.

Po-Ming Chen, Jian-Rong Li, Chun-Chi Liu, Feng-Yao Tang, En-Pei Isabel Chiang

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 42% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Downregulation of Methionine Cycle GenesInternational journal of molecular sciences · 2022
    Article
  4. Article
  5. 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

5 authors at 2 institutions in 1 country.

Po-Ming ChenDepartment of Food Science and Biotechnology, National Chung Hsing University, Taichung.
Jian-Rong LiInstitute of Genomics and Bioinformatics, National Chung Hsing University, Taichung.
Chun-Chi LiuInstitute of Genomics and Bioinformatics, National Chung Hsing University, Taichung.
Feng-Yao TangDepartment of Nutrition, China Medical University, Taichung.
En-Pei Isabel ChiangDepartment of Food Science and Biotechnology, National Chung Hsing University, Taichung.ORCID https://orcid.org/0000-0002-0158-0962
National Chung Hsing University · TWChina Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal

Indexed as

ENO1HCCHK2metabolismp53RNA-Seq

Identifiers

PMID31933519
PMCPMC6947881
OpenAlexW3000663361

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.