Evidence map›Paper›PMID 42032150›Full record

ReviewDiscover oncology2026

Bibliometric analysis of single-cell RNA sequencing in tumor microenvironment.

Jing Ma, Tingting Chen, Kefei Shen, Mengru Fang, Yanyan Zhang, Lu Yang, Longfei Guo

Abstract readReview
In one paragraph

Review in Discover oncology, 2026. 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. Review
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.

Jing Ma *Department of Endocrinology and Metabolism, Gansu Provincial Hospital, Gansu Branch of National Clinical Research Center for Metabolic Diseases, Lanzhou, China.
Tingting Chen *The Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, China.
Kefei ShenBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Mengru FangThe Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, China.
Yanyan ZhangDepartment of Endocrinology and Metabolism, Gansu Provincial Hospital, Gansu Branch of National Clinical Research Center for Metabolic Diseases, Lanzhou, China.
Lu YangThe Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, China.
Longfei GuoDepartment of Critical Care Medicine, Gansu Provincial Hospital, No. 204 Donggang West Road, Lanzhou, 730000, Gansu, China. guolongfei0920@126.com.

Funding

Gansu Provincial Hospital 21GSSYC-6Natural Science Foundation of Gansu Province 25JRRA872
6 · The paper itself

Abstract

The tumor microenvironment (TME) has emerged as a pivotal determinant of tumor progression, immune evasion, and therapeutic response, making it a central focus in modern oncology. Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to dissect the cellular heterogeneity and dynamic interactions within the TME at unprecedented resolution, enabling precise identification of cell types, functional states, and intercellular communication networks. In this study, we conducted a comprehensive bibliometric analysis of 187 publications of scRNA-seq in TME, indexed in the Web of Science Core Collection from January 1999 to July 2024. Our analysis reveals that China and the United States are the dominant contributors in terms of publication volume and citation impact, with Peking University and Harvard University leading institutional output. Keyword analysis revealed that the most frequent terms were “tumor microenvironment,” “single-cell RNA sequencing,” “gene expression,” and “cancer”. Journals with highly cited articles mainly include Nature Genetics, Cancer Research, Annual Review of Immunology, Nature Communications, Science Translational Medicine, Genome Biology, Journal of Hepatology, and Nature Cell Biology. Current studies primarily focus on using scRNA-seq to identify cell types and subtypes within the TME, as well as to investigate cell-cell interactions and communication. These findings offer valuable insights into advancing our understanding of tumor genetics, immune evasion mechanisms, diagnostic and prognostic biomarkers, and treatment resistance. While the field demonstrates rapid growth, enhanced international collaboration remains an urgent unmet need. Future research will likely to center on roles of immune and stromal cells within the TME revealed by scRNA-seq, as well as the integration of scRNA-seq with spatial transcriptomics and machine learning. It represents a promising direction for developing novel tumor therapies.

Indexed as

Bibliometric analysisCancer immunityImmunotherapySingle-cell RNA sequencingTumor microenvironment

Identifiers

PMID42032150
PMCPMC13243147

What OpenQuestion holds

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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.