ReviewJournal of the Chinese Medical Association : JCMA2021
Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy.
Review in Journal of the Chinese Medical Association : JCMA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Single Cell RNA Sequencing in Colorectal Cancer Immunology: Recent Updates, Application, and Emerging Challenges.Current molecular medicine · 2026Review
- Applications of single-cell analysis in immunotherapy for lung cancer: Current progress, new challenges and expectations.Journal of advanced research · 2025Review
- Tumor heterogeneity assessment using single-cell RNA sequencing (scRNA-seq): applications in lung cancer for diagnosis and treatment.Frontiers in immunology · 2025Review
- Single-cell spatial transcriptomics in cardiovascular development, disease, and medicine.Genes & diseases · 2024Review
- Targeting CDCP1 boost CD8+ T cells-mediated cytotoxicity in cervical cancer via the JAK/STAT signaling pathway.Journal for immunotherapy of cancer · 2024Article
- Article
- Advances in single-cell RNA sequencing and its applications in cancer research.Journal of hematology & oncology · 2023Review
- How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy.Frontiers in immunology · 2023Review
- Dissecting the Single-Cell Transcriptome Network of Immune Environment Underlying Cervical Premalignant Lesion, Cervical Cancer and Metastatic Lymph Nodes.Frontiers in immunology · 2022Article
- Decoding Lung Cancer at Single-Cell Level.Frontiers in immunology · 2022Review
- The Single-Cell Sequencing: A Dazzling Light Shining on the Dark Corner of Cancer.Frontiers in oncology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.