Evidence map›Paper›PMID 34177965›Full record

ReviewFrontiers in immunology2021

Applications of Single-Cell Omics in Tumor Immunology.

Junwei Liu, Saisi Qu, Tongtong Zhang, Yufei Gao, Hongyu Shi, Kaichen Song, Wei Chen, Weiwei Yin

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

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  16. [Advances in methods and applications of single-cell Hi-C data analysis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
    Article
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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

8 authors at 3 institutions in 1 country.

Junwei LiuDepartment of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Saisi QuDepartment of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Tongtong ZhangDepartment of Hepatobiliary and Pancreatic Surgery, The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yufei GaoSchool of Mechanical Engineering, Zhejiang University, Hangzhou, China.
Hongyu ShiDepartment of Biological Testing, Zhejiang Puluoting Health Technology Co., Ltd., Hangzhou, China.
Kaichen SongDepartment of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Wei ChenDepartment of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Weiwei YinDepartment of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Second Affiliated Hospital of Zhejiang University · CNHangzhou First People's Hospital · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem's complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques.

Indexed as

Biomarkers, TumorComputational BiologyDrug Resistance, NeoplasmEpigenomicsFlow CytometryGene Expression ProfilingGenomicsHumansImmunotherapyNeoplasmsPrognosisProteomicsReceptors, Antigen, T-CellRNA-SeqSingle-Cell AnalysisT-LymphocytesBiomarkers, TumorReceptors, Antigen, T-Cellbiomarkerscancerimmunotherapysingle-cell omicsTCR (T cell receptor)

Identifiers

PMID34177965
PMCPMC8221107
OpenAlexW3166831499

What OpenQuestion holds

Textmetadata
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.