Evidence map›Paper›PMID 38867700›Full record

ArticleGenomics, proteomics & bioinformatics2024

CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization.

Xiaoping Liu, Zisong Wang, Hongjie Shi, Sheng Li, Xinghuan Wang

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

5 authors.

Xiaoping LiuDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.ORCID 0000-0001-6179-0964
Zisong WangDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.ORCID 0009-0005-0357-4311
Hongjie ShiCancer Precision Diagnosis and Treatment and Translational Medicine Hubei Engineering Research Center, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.ORCID 0009-0008-7917-3241
Sheng LiDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.ORCID 0000-0003-4070-7345
Xinghuan WangDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.ORCID 0000-0003-3497-0024

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a leading cause of death worldwide, and the identification of biomarkers and subtypes that can predict the long-term survival of cancer patients is essential for their risk stratification, treatment, and prognosis. However, there are currently no standardized tools for exploring cancer biomarkers or subtypes. In this study, we introduced Cancer Biomarker and subtype Profiler (CBioProfiler), a web server and standalone application that includes two pipelines for analyzing cancer biomarkers and subtypes. The cancer biomarker pipeline consists of five modules for identifying and annotating cancer survival-related biomarkers using multiple survival-related machine learning algorithms. The cancer subtype pipeline includes three modules for data preprocessing, subtype identification using multiple unsupervised machine learning methods, and subtype evaluation and validation. CBioProfiler also includes CuratedCancerPrognosisData, a novel R package that integrates reviewed and curated gene expression and clinical data from 268 studies. These studies cover 43 common blood and solid tumors and draw upon 47,686 clinical samples. The web server is available at https://www.cbioprofiler.com/ and https://cbioprofiler.znhospital.cn/CBioProfiler/, and the standalone app and source code can be found at https://github.com/liuxiaoping2020/CBioProfiler.

Indexed as

Biomarkers, TumorInternetNeoplasmsSoftwareComputational BiologyHumansBiomarkers, TumorCancer biomarkerCancer subtypeCBioProfilerMachine learningWeb app

Identifiers

PMID38867700
PMCPMC11464420

What OpenQuestion holds

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Registered trials

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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.