Evidence map›Paper›PMID 36388031›Full record

ArticleTranslational cancer research2022

Development and validation of a novel ubiquitination-related gene prognostic signature based on tumor microenvironment for colon cancer.

Baoyi Huang, Weiping Deng, Pengfei Chen, Qiuxian Mao, Hao Chen, Zewei Zhuo, Zena Huang, Kequan Chen, Jiayu Huang, Yujun Luo

Open access · diamondAbstract read
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Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 4 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

10 authors at 6 institutions in 1 country.

Baoyi Huang *Department of Clinical Medicine, The Second Clinical College of Guangzhou Medical University, Guangzhou, China.
Weiping Deng *Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Pengfei Chen *Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Qiuxian Mao *Prenatal Diagnostic Department, Guangdong Second Provincial General Hospital, Guangzhou, China.
Hao ChenDepartment of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zewei ZhuoDepartment of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zena HuangDepartment of General Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Kequan ChenDepartment of Gastroenterology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jiayu HuangDepartment of Otorhinolaryngology-Head and Neck Surgery, Huizhou Municipal Central People's Hospital, Huizhou, China.
Yujun LuoDepartment of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guangdong Provincial People's Hospital · CNFirst Affiliated Hospital of Guangzhou Medical University · CNGuangdong Academy of Medical Sciences · CNHuizhou Central People's Hospital · CNSecond Affiliated Hospital of Guangzhou Medical University · CNSun Yat-sen University Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colon cancer (CC) is one of the most common cancers with high morbidity globally. Ubiquitination is involved in the characterization of multiple biological processes, and some ubiquitinated enzymes are associated with the prognosis of CC. However, the prognostic model associated with ubiquitination-related genes (URGs) for CC is unavailable. Methods: Gene expression data, somatic mutations, transcriptome profiles, microsatellite instability status (MSI) status, and clinical information for CC were obtained from The Cancer Genome Atlas (TCGA) dataset. Seven URGs were used for establishing a prognostic prediction model, which was constructed and validated in GSE17538. Besides, genomic variance analysis (GSVA) was used to explore further the differences in biological pathway activation status between the high-risk and low-risk groups. Finally, the single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithm analysis were used to characterize the cellular infiltration in the microenvironment. Results: A seven-URG prognostic signature was established, based on which patients in the training and test groups could be divided into high-risk and low-risk groups. The results demonstrated that the model has a solid ability to predict the prognosis of CC patients. Conclusions: We established a prognostic prediction model for CC based on ubiquitination. Then we analyzed the genetic characteristics associated with ubiquitination and the tumor microenvironment (TME) cell infiltration in CC. These results are worthy of exploring new clinical treatment strategies for CC.

Indexed as

Colon cancer (CC)prognostictumor microenvironment (TME)ubiquitination

Identifiers

PMID36388031
PMCPMC9641125
OpenAlexW4293412887

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LicenceCC BY-NC-ND
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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.