Evidence map›Paper›PMID 29758961›Full record

ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2018

Exploration of genetics commonness between bladder cancer and breast cancer based on a silcio analysis on disease subtypes.

Wenbin Xu, Hong Xia, Wei Liu, Weiying Zheng, Lin Hua

Open access · greenAbstract read
In one paragraph

Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2018. 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
0.5field-weighted citation impact, top 34% 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, 5 citations in OpenAlex.

  1. Article
  2. Pharmaceuticals (Basel, Switzerland) · 2024
    Article
  3. Article
  4. 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

5 authors at 2 institutions in 1 country.

Wenbin XuSchool of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Hong XiaSchool of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Wei LiuDepartment of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.
Weiying ZhengSchool of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Lin HuaSchool of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Capital Medical University · CNBeijing Tongren Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveMuscle-invasive bladder cancers (MIBCs) are heterogeneous cancers and can be grouped into basal-like and luminal subtypes that are highly reminiscent of those found in breast cancer. Like basal-like breast cancers, basal-like MIBCs are associated with advanced stage and metastatic disease. However, the biological and clinical significance of molecular subtypes of MIBCs remain unclear. Therefore, we implemented a serious of bioinformatics methods to explore genetic similarities between bladder and breast cancers. METHODS AND

resultsIn the current study, by the application of multiple levels data analysis including random forest analysis, PPI and transcription factor regulation network construction, Gene Ontology (GO) and KEGG pathway enrichment analysis, we explored the genetics commonness between MIBC and breast cancers from the molecular heterogeneity based on the disease subtypes.

conclusionsOur study identified some basal-related and luminal-related genes shared by two cancers. These studies can help shed light on the potential relationships between MIBC and breast cancer as a whole.

Indexed as

AlgorithmsBiomarkers, TumorBreast NeoplasmsGene Expression ProfilingHumansInformed ConsentUrinary Bladder NeoplasmsBiomarkers, TumorBladder cancerbreast cancergenetic commonnessregulation network

Identifiers

PMID29758961
PMCPMC6027900
OpenAlexW2801627030

What OpenQuestion holds

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LicenceCC BY-NC
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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.