Evidence map›Paper›PMID 29340065›Full record

ArticleOncotarget2017

Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses.

Chunlong Zhang, Yanjun Xu, Haixiu Yang, Yingqi Xu, Qun Dong, Siyao Liu, Tan Wu, Yunpeng Zhang

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

8 authors.

Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanjun XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Haixiu YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yingqi XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Qun DongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Siyao LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Tan WuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

LncRNAs acting as miRNA sponges to indirectly regulate mRNAs is a novel layer of gene regulation, therefore, it is necessary to integrate lncRNA and gene levels for interpreting tumor biological mechanism. In this study, we developed a lncRNA-gene integrated strategy to infer functional activities for tumor analyses at the subpathway level. In this strategy, we reconstructed subpathway graphs by embedding lncRNA components and considered the expression levels of both genes and lncRNAs to infer subpathway activities for each tumor sample. And the activities were applied to three aspects of tumor analyses; First, the subpathway activities across tumor samples of five tumor types were analyzed, and it was observed that the samples with consistent subpathway activities were derived from the same or similar tumor types. Also, the subpathway activities could stratify samples into several subtypes which has different clinical characterization, e.g. survival status. Second, the subpathway activities between tumor and normal samples were analyzed, and the comparative results showed that subpathway activities displayed more specificities than entire pathway activities. Finally, based on the subpathway activities, we identified prognostic subpathways for lung cancer. Our subpathway-based signatures shared significant overlap with enrichment analysis results and displayed predictive power in the independent testing sets. In conclusion, our integrated strategy provided a framework to infer subpathway activities for tumor analyses and identify subpathway signatures for clinical use.

Indexed as

lncRNAsubpathway

Identifiers

PMID29340065
PMCPMC5762333

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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.