Evidence map›Paper›PMID 35401750›Full record

ArticleJournal of oncology2022

Analysis of the Heterogeneity of the Tumor Microenvironment and the Prognosis and Immunotherapy Response of Different Immune Subtypes in Hepatocellular Carcinoma.

Jian Hu, Feifei Mao, Lifang Li, Xiaoqian Wang, Depei Cai, Longmei He, Qian Wu, Cong Wang, Ning Zhang, Yanfen Ma and 3 more

Abstract read
In one paragraph

Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Jian HuDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0002-2523-9275
Feifei MaoTongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.ORCID https://orcid.org/0000-0002-4551-7084
Lifang LiEmergency Department, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0002-0300-6286
Xiaoqian WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0001-5646-1672
Depei CaiDepartment of Clinical Laboratory, Xi'an Aerospace General Hospital, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0001-7661-6002
Longmei HeDepartment of Clinical Laboratory, Shaanxi Provincial Hospital of Chinese Medicine, Xi'an, 710082 Shaanxi Province, China.ORCID https://orcid.org/0000-0002-8071-2117
Qian WuDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0001-7480-1028
Cong WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0003-3007-4556
Ning ZhangDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0003-0773-8916
Yanfen MaDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0003-3001-0501
Xia WuDepartment of Clinical Laboratory, Xi'an Chest Hospital, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0003-2537-7130
Kai QuDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0002-1138-3727
Xiaoqin WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi Province, China.ORCID https://orcid.org/0000-0002-3348-1790

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The current clinical classification of hepatocellular carcinoma (HCC) cannot well predict the patient's possible response to the treatment plan, nor can it predict the patient's prognosis. We use the gene expression patterns of patients with hepatocellular carcinoma to reveal the heterogeneity of hepatocellular carcinoma and analyze the differences in prognosis and immunotherapy response of different immune subtypes. Methods: Firstly, using the hepatocellular carcinoma expression profile data of TCGA, combined with the single sample gene set enrichment analysis (ssGSEA) algorithm, the immune enrichment of the patient's tumor microenvironment was analyzed. Subsequently, the spectral clustering algorithm was used to extract different classifications, and the cohort of hepatocellular carcinoma was divided into 3 subtypes, and the correlation between immune subtypes and clinical characteristics and survival prognosis was established. The patient's risk index is obtained through the prognostic prediction model, suggesting the correlation between the risk index and various types of immune cells. Results: We can divide the liver cancer cohort into three subtypes: stromal cell activated immune-enriched type (A-IS), general immune-enriched type (N-IS), and non-immune-enriched type (non-IS). The 3-year survival rate of TCGA's A-IS is higher than that of N-IS and non-IS, and the three components are significantly different ( Conclusion: The tumor gene expression characteristics of patients with hepatocellular carcinoma can be used as a basis for clinical patient classification. Different immune subtypes are closely related to survival prognosis. Different immune cell states of patients may lead to different disease risk levels. All these provide important references for the clinical identification and prognosis prediction of hepatocellular carcinoma.

Identifiers

PMID35401750
PMCPMC8984740

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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.