Evidence map›Paper›PMID 37700496›Full record

ArticleClinical and translational medicine2023

Challenges of clinical translation from single-cell sequencing to measures in clinical biochemistry of haematology: Definition of immune cell identities.

Xuanqi Liu, Diane C Wang, Charles A Powell, Xiangdong Wang

Abstract readEditorial
In one paragraph

Article in Clinical and translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

4 authors.

Xuanqi LiuDepartment of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Fudan University Shanghai Medical College, Shanghai Institute of Clinical Bioinformatics, Shanghai, China.ORCID https://orcid.org/0000-0003-4275-9712
Diane C WangDepartment of Emergency Medicine, Princess Alexandra Hospital, Brisbane, Australia.
Charles A PowellDivision of Pulmonary, Department of Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Xiangdong WangDepartment of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Fudan University Shanghai Medical College, Shanghai Institute of Clinical Bioinformatics, Shanghai, China.ORCID https://orcid.org/0000-0002-8406-7928

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral immune cells play important roles in the maintenance of systemic and microenvironmental hemostasis. Measurements of circulating blood cells by single-cell RNA sequencing (scRNA-seq) were proposed as one of the routine measures in clinical biochemistry of hematology. Out of translational challenges, defining precise identities of cell subsets and states is more difficult, due to the complexity of immune cell development, location, regulation, function, and metabolism. It is also a challenge to precisely interpret clinical significance and impact of each cell identity marker gene panel (ciMGPs). ciMGPs have potential to advance the understanding of systemic responses of the disease, identify disease-specific biomarkers, and to define cell heterogeneity. Recently, a large number of peripheral cell subsets and expending/activating states have been identified and validated for use in the fast developments in clinical single cell biomedicine. Defining specificity, measurability, and repeatability of cell subsets/states is important for translation of peripheral scRNA-seq in clinical hematology and biochemistry. The development of standard operating procedure and performance of clinical trials in large populations at various ages, diseases, and therapies will promote the clinical translation of ciMGPs to measures. Thus, defining cell subset/state identities will provide the multi-dimensional and comprehensive readouts of systemic immune cells, the precision monitoring of immune dynamics, and deeper-understanding of the disease and response to therapy.

Indexed as

Clinical RelevanceHematologyCell Differentiationcell identityclinicalmedicineRNA sequencingsingle-celltranslational

Identifiers

PMID37700496
PMCPMC10497804

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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.