Evidence map›Paper›PMID 27977206›Full record

ArticleJournal of proteome research2017

CanProVar 2.0: An Updated Database of Human Cancer Proteome Variation.

Menghuan Zhang, Bo Wang, Jia Xu, Xiaojing Wang, Lu Xie, Bing Zhang, Yixue Li, Jing Li

Abstract read
In one paragraph

Article in Journal of proteome research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

21 citing papers in PubMed, 50 citations in OpenAlex.

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  8. Multi-omic stratification of the missense variant cysteinome.bioRxiv : the preprint server for biology · 2023
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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

8 authors at 3 institutions in 2 countries.

Menghuan ZhangDepartment of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.
Bo WangDepartment of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.
Jia XuDepartment of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.
Xiaojing Wang
Lu XieShanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology , Shanghai 201203, China.
Bing Zhang
Yixue LiDepartment of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.
Jing LiDepartment of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.ORCID 0000-0003-4602-3227
Shanghai Jiao Tong University · CNBaylor College of Medicine · USShanghai Academy of Science & Technology · CN

Funding

iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTACU24CA210954 · NCI · BAYLOR COLLEGE OF MEDICINE · PI ZHANG, BING · 2016 to 2020
$4.9M
NCI NIH HHS U24 CA210954
6 · The paper itself

Abstract

Identification and annotation of the mutations involved in oncogenesis and tumor progression are crucial for both cancer biology and clinical applications. Previously, we developed a public resource CanProVar, a human cancer proteome variation database for storing and querying single amino acid alterations in the human cancers. Since the publication of CanProVar, extensive cancer genomics efforts have revealed the enormous genomic complexity of various types of human cancers. Thus, there is an overwhelming need for comprehensive annotation of the genomic alterations at the protein level and making such knowledge easily accessible. Here, we describe CanProVar 2.0, a significantly expanded version of CanProVar, in which the amount of cancer-related variations and noncancer specific variations was increased by about 10-fold as compared to the previous version. To facilitate the interpretation of the variations, we added to the database functional data on potential impact of the cancer-related variations on 3D protein interaction and on the differential expression of the variant-bearing proteins between cancer and normal samples. The web interface allows for flexible queries based on gene or protein IDs, cancer types, chromosome locations, or pathways. An integrated protein sequence database containing variations that can be directly used for proteomics database searching can be downloaded.

Indexed as

Databases, ProteinGenetic VariationSoftwareAmino Acid SequenceChromosome MappingGene ExpressionHumansInternetNeoplasm ProteinsNeoplasmsProtein ConformationProtein Interaction MapsNeoplasm Proteinscancerdatabaseproteomevariation

Identifiers

PMID27977206
PMCPMC5515284
OpenAlexW2557260411

What OpenQuestion holds

Textmetadata
LicenceTDM
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.