Evidence map›Paper›PMID 30886153›Full record

ArticleNature communications2019

Clonal architectures predict clinical outcome in clear cell renal cell carcinoma.

Yi Huang, Jiayin Wang, Peilin Jia, Xiangchun Li, Guangsheng Pei, Changxi Wang, Xiaodong Fang, Zhongming Zhao, Zhiming Cai, Xin Yi and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
9.1field-weighted citation impact, top 2% 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

38 citing papers in PubMed, 66 citations in OpenAlex.

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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

12 authors at 6 institutions in 2 countries.

Yi HuangDepartment of Computer Science and Technology, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.
Jiayin WangDepartment of Computer Science and Technology, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China.
Peilin JiaCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Xiangchun LiDepartment of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China.
Guangsheng PeiCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Changxi WangGeneplus-Beijing, Beijing, 102206, China.
Xiaodong FangThe Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong, China.ORCID http://orcid.org/0000-0001-7061-3337
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.ORCID http://orcid.org/0000-0002-3477-0914
Zhiming CaiThe Third Affiliated Hospital of Shenzhen University, Shenzhen, 518001, Guangdong, China.
Xin YiGeneplus-Beijing, Beijing, 102206, China.
Song WuThe Third Affiliated Hospital of Shenzhen University, Shenzhen, 518001, Guangdong, China.
Baifeng ZhangGeneplus-Beijing, Beijing, 102206, China. zhangbaifeng1@gmail.com.
The University of Texas Health Science Center at Houston · USShenzhen University · CNXi'an Jiaotong University · CNAlibaba Group (China) · CNGuangzhou University of Chinese Medicine · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
NIH HHS R01LM012806NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

The genetic landscape of clear cell renal cell carcinoma (ccRCC) had been investigated extensively but its evolution patterns remained unclear. Here we analyze the clonal architectures of 473 patients from three different populations. We find that the mutational signatures vary substantially across different populations and evolution stages. The evolution patterns of ccRCC have great inter-patient heterogeneities, with del(3p) being regarded as the common earliest event followed by three early departure points: VHL and PBRM1 mutations, del(14q) and other somatic copy number alterations (SCNAs) including amp(7), del(1p) and del(6q). We identify three prognostic subtypes of ccRCC with distinct clonal architectures and immune infiltrates: long-lived patients, enriched with VHL but depleted of BAP1 mutations, have high levels of Th17 and CD8

Indexed as

Evolution, MolecularCarcinoma, Renal CellCD8-Positive T-LymphocytesClone CellsCohort StudiesDNA-Binding ProteinsDNA Copy Number VariationsGene Expression Regulation, NeoplasticGenetic HeterogeneityHumansKidneyKidney NeoplasmsMutationNuclear ProteinsPrognosisSurvival AnalysisDNA-Binding ProteinsNuclear ProteinsPBRM1 protein, humanTranscription FactorsVHL protein, humanVon Hippel-Lindau Tumor Suppressor Protein

Identifiers

PMID30886153
PMCPMC6423009
OpenAlexW2921992945

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.