Evidence map›Paper›PMID 31607216›Full record

ArticleRNA biology2020

Advancing Pan-cancer Gene Expression Survial Analysis by Inclusion of Non-coding RNA.

Bo Ye, Jianxin Shi, Huining Kang, Olufunmilola Oyebamiji, Deirdre Hill, Hui Yu, Scott Ness, Fei Ye, Jie Ping, Jiapeng He and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RNA biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

13 authors.

Bo YeDepartment of Thoracic Surgery, Shanghai Chest Hospital, Jiaotong University , Shanghai, China.
Jianxin ShiDepartment of Thoracic Surgery, Shanghai Chest Hospital, Jiaotong University , Shanghai, China.
Huining KangComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.ORCID 0000-0002-4415-3573
Olufunmilola OyebamijiComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.
Deirdre HillComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.ORCID 0000-0002-8495-659X
Hui YuComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.ORCID 0000-0002-4491-8855
Scott NessComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.ORCID 0000-0001-6965-8909
Fei YeDepartment of Biostatistics, Vanderbilt University Medical Center , Nashville, TN, USA.ORCID 0000-0001-6472-5076
Jie PingDepartment of Biostatistics, Vanderbilt University Medical Center , Nashville, TN, USA.ORCID 0000-0001-9907-5819
Jiapeng HeComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.
Jeremy EdwardsComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.ORCID 0000-0003-3694-3716
Ying-Yong ZhaoKey Laboratory of Resource Biology and Biotechnology in Western China, School of Life Sciences, Northwest University , Xi'an, Shaanxi, China.ORCID 0000-0002-0239-7342
Yan GuoComprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.

Funding

WOMEN'S CANCERS RESEARCH PROGRAMP30CA118100 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Yolanda Sanchez · 2005 to 2026
$57.1M
Mutations and Target Genes in Adenoid Cystic CarcinomaR01DE023222 · NIDCR · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Viswanathan Palanisamy · 2012 to 2026
$5.6M
NCI NIH HHS P30 CA118100NIDCR NIH HHS R01 DE023222
6 · The paper itself

Abstract

Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA's biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx.

Indexed as

Biomarkers, TumorGene Expression Regulation, NeoplasticComputational BiologyDatabases, GeneticGene Expression ProfilingHumansNeoplasmsPrognosisRNA, Long NoncodingRNA, UntranslatedBiomarkers, TumorRNA, Long NoncodingRNA, UntranslatedCancer survival analysislincRNAnon-coding RNApseudogene

Identifiers

PMID31607216
PMCPMC7567505

What OpenQuestion holds

Textmetadata
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.