ReviewJournal of hematology & oncology2021
Applications of single-cell sequencing in cancer research: progress and perspectives.
Review in Journal of hematology & oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 398 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
398 citing papers in PubMed, 570 citations in OpenAlex.
- DHCR24Oncogene · 2026Article
- Machine learning and multi-omics clustering to map cellular rewiring and immune evasion in ccRCC.Human genomics · 2026Article
- Democratized single-cell proteomics resolves cell state heterogeneity in skin tumors.Life science alliance · 2026Article
- TLS as Predictors and Targets in Neoadjuvant Chemoimmunotherapy for NSCLC.Thoracic cancer · 2026Review
- An early invasive signature from the adenocarcinoma in situ-to-invasive adenocarcinoma single-cell trajectory stratifies stage I lung adenocarcinoma overall survival.Journal of thoracic disease · 2026Article
- GNAS drives gastric cancer progression via pyrimidine metabolic reprogramming and immune-microenvironment remodeling.Apoptosis : an international journal on programmed cell death · 2026Article
- Machine learning-based prognostic model and single-cell transcriptomic integration for identifying brain metastasis-associated malignant subpopulations and potential therapeutic targets in lung adenocarcinoma.Cancer cell international · 2026Article
- Tumor heterogeneity: development, mechanisms, and therapeutic implications.Signal transduction and targeted therapy · 2026Review
- Understanding nerve-tumor interactions: From basic biology to therapeutic innovation.Genes & diseases · 2026Review
- Integrated bioinformatics, machine learning, and experimental validation identify a four-gene diagnostic signature for cervical cancer associated with PI3K/AKT signaling.Scientific reports · 2026Article
- Single-cell transcriptomics unveils pyroptosis-related immune microenvironment dynamics and prognostic modeling in esophageal squamous cell carcinoma.Journal of cardiothoracic surgery · 2026Article
- Integrating MRI radiomics and transcriptomics to predict IDH mutation status and prognosis in glioma.Cancer cell international · 2026Article
- Phylogenetic tree inference from single-cell RNA sequencing data with SCITE-RNA.Genome biology · 2026Article
- Hierarchies of resistance to DNA damage response inhibitors: from pathway restoration to replication stress tolerance.Experimental hematology & oncology · 2026Review
- Multi-omics profiling reveals tumor microenvironment characteristics linked to immunotherapy response and prognosis in non-small cell lung cancer.NPJ precision oncology · 2026Article
- Article
- Single-cell genomic analysis of cancer cells from one treatment-naïve patient with metastatic prostate cancer.BMC genomic data · 2026Article
- Inferring tumor absolute copy number and clonal substructure from single-cell chromatin accessibility.Briefings in bioinformatics · 2026Article
- Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Analyses of single-cell and bulk RNA-sequencing datasets identify biomarker-based molecular subtypes and a prognostic signature in lung adenocarcinoma.Translational cancer research · 2026Article
338 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.
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What Socratic 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 Socratic graph.