Evidence map›Paper›PMID 37059592›Full record

ArticleAging2023

Cellular senescence-related gene signature as a valuable predictor of prognosis in hepatocellular carcinoma.

Shuqiao Zhang, Yilu Zheng, Xinyu Li, Shijun Zhang, Hao Hu, Weihong Kuang

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 11 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

6 authors at 5 institutions in 1 country.

Shuqiao ZhangFirst Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Yilu ZhengDepartment of Hematology, The Seventh Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Xinyu LiMedical College of Acupuncture-Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Shijun ZhangDepartment of Traditional Chinese Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Hao HuFirst Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Weihong KuangGuangdong Key Laboratory for Research and Development of Natural Drugs, School of Pharmacy, The First Dongguan Affiliated Hospital of Guangdong Medical University, Guangdong Medical University, Dongguan, Guangdong, China.
First Affiliated Hospital of Guangzhou University of Chinese Medicine · CNGuangdong Medical College · CNGuangzhou University of Chinese Medicine · CNThe First Affiliated Hospital, Sun Yat-sen University · CNThe Seventh Affiliated Hospital of Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a lethal tumor. Its prognosis prediction remains a challenge. Meanwhile, cellular senescence, one of the hallmarks of cancer, and its related prognostic genes signature can provide critical information for clinical decision-making.

methodUsing bulk RNA sequencing and microarray data of HCC samples, we established a senescence score model via multi-machine learning algorithms to predict the prognosis of HCC. Single-cell and pseudo-time trajectory analyses were used to explore the hub genes of the senescence score model in HCC sample differentiation.

resultA machine learning model based on cellular senescence gene expression profiles was identified in predicting HCC prognosis. The feasibility and accuracy of the senescence score model were confirmed in external validation and comparison with other models. Moreover, we analyzed the immune response, immune checkpoints, and sensitivity to immunotherapy drugs of HCC patients in different prognostic risk groups. Pseudo-time analyses identified four hub genes in HCC progression, including CDCA8, CENPA, SPC25, and TTK, and indicated related cellular senescence.

conclusionsThis study identified a prognostic model of HCC by cellular senescence-related gene expression and insight into novel potential targeted therapies.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsCellular SenescenceGenes, cdcHumansPrognosiscellular senescencehepatocellular carcinomaimmunemachine learningprognosis

Identifiers

PMID37059592
PMCPMC10188344
OpenAlexW4365450147

What OpenQuestion holds

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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.