Evidence map›Paper›PMID 38244584›Full record

ArticleAging2024

Malignant cell receptor-ligand subtypes guide the prediction of prognosis and personalized immunotherapy of liver cancer.

Junzheng Wu, Chuncheng Wu, Xianhui Cai, Peipei Li, Jianjun Lin, Fuqiang Wang

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Junzheng WuXiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.
Chuncheng WuXiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.
Xianhui CaiXiamen Xianyue Hospital, Xiamen, Fujian, China.
Peipei LiXiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.
Jianjun LinXiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.
Fuqiang WangXiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.
Beijing University of Chinese Medicine · CNTianjin haihe hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveLiver cancer is a prevalent disease with a dismal prognosis. The aim of the research is to identify subgroups based on malignant cell receptor ligand gene from single-cell RNA, which might lead to customized immunotherapy for patients with liver cancer.

methodsBased on scRNA-seq data, we identified the receptor-ligand genes associated with prognosis and classify patients into molecular subtypes by univariate Cox regression and consensus clustering. LASSO regression was performed to construct a prognostic model, which was validated in TCGA and ICGC datasets. Immune infiltration and prediction of immunotherapy response were analyzed using ssGSEA, ESTIMATE, TIDE, and TRS score calculation. Finally, qPCR and Western blot validation of key genes and protein levels in cell lines.

resultsA risk model using 16-gene expression levels predicted liver cancer patients' prognosis. The RiskScore associated significantly with tumor clinical characteristics and immunity, integrated with clinicopathological features for survival prediction. Differential expression of SRXN1 was verified in hepatocellular carcinoma and normal liver cells.

conclusionOur study utilizes single-cell analysis to investigate the communication between malignant cells and other cell types, identifying molecular subtypes based on malignant cell receptor ligand genes, offering new insights for the development of personalized immunotherapy and prognostic prediction models.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsHumansImmunotherapyLigandsPrognosisTumor MicroenvironmentLigandshepatocellular carcinomaimmunotherapyrisk-scorescRNA-seq

Identifiers

PMID38244584
PMCPMC10866410
OpenAlexW4390975273

What OpenQuestion holds

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LicenceCC BY
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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.