Evidence map›Paper›PMID 35588138›Full record

ArticleJournal of clinical laboratory analysis2022

A novel four-gene signature predicts immunotherapy response of patients with different cancers.

Yuanli Liu, Mingyue Ni, Lamei Li, Junyan Wang, Zhenzhen Tu, Haisheng Zhou, Siping Zhang

Abstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2022. 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

7 authors.

Yuanli LiuDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Mingyue NiDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Lamei LiDepartment of Dermatology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.
Junyan WangDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Zhenzhen TuDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Haisheng ZhouDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China.ORCID https://orcid.org/0000-0002-4218-8641
Siping ZhangDepartment of Dermatology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.

Funding

Anhui Natural Science Foundation 1808085MH259National Nature Science Foundation of China 81772909
6 · The paper itself

Abstract

backgroundImmune checkpoint blockade (ICB) therapy has demonstrated favorable clinical efficacy, particularly for advanced or difficult-to-treat cancer types. However, this therapy is ineffective for many patients displaying lack of immune response or resistance to ICB. This study aimed to establish a novel four-gene signature (CD8A, CD8B, TCF7, and LEF1) to provide a prognostic immunotherapy biomarker for different cancers.

methodsTranscriptome profiles and clinical data were obtained from The Cancer Genome Atlas database. Multivariate Cox regression analysis was used to establish a four-gene signature. The R package estimate was used to obtain the immune score for every patient.

resultsRisk scores of the novel four-gene signature could effectively divided all patients into high- and low-risk groups, with distinct outcomes. The immune score calculated via the estimate package demonstrated that the four-gene signature was significantly associated with the immune infiltration level. Furthermore, the four-gene signature could predict the response to atezolizumab immunotherapy in patients with metastatic urothelial cancer.

conclusionsThe novel four-gene signature developed in this study is a good prognostic biomarker, as it could identify many kinds of patients with cancer who are likely to respond to and benefit from immunotherapy.

Indexed as

Biomarkers, TumorNeoplasmsHumansImmunologic FactorsImmunotherapyPrognosisTranscriptomeBiomarkers, TumorImmunologic FactorscancerCD8immune checkpoint-blockadeLEF1TCF7

Identifiers

PMID35588138
PMCPMC9279975

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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.