ArticleMolecular therapy. Nucleic acids2021
Single-cell RNA-seq dissects the intratumoral heterogeneity of triple-negative breast cancer based on gene regulatory networks.
Article in Molecular therapy. Nucleic acids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Spatial and temporal intratumoral heterogeneity in breast cancer: a systematic and conceptual review of single-cell and spatial omics studies.BMC cancer · 2026Pooled it
- Hormone, Targeted, and Combinational Therapies for Breast Cancers: From Humans to Dogs.International journal of molecular sciences · 2024Pooled it
- Olaparib monotherapy in advanced triple-negative breast cancer patients with homologous recombination deficiency and without germline mutations in BRCA1/2: The NOBROLA phase 2 study.Breast (Edinburgh, Scotland) · 2024Trial
- Tumor-Intrinsic DNA Damage Signaling Is Associated with MHC-I Expression and CD8 Cytotoxic T-Cell Engagement in Triple-Negative Breast Cancer.Current issues in molecular biology · 2026Article
- A Multi-Omics Framework Reveals Tumor Heterogeneity and Predicts Therapeutic Targets in Renal Cell Carcinoma.International journal of molecular sciences · 2026Article
- Regulation of mitochondrial ROS by C15ORF48 in a basal cell subpopulation contributes to chemotherapy resistance in TNBC.Science advances · 2026Article
- Nanobioconjugate Trispecific Antibody Augments Antitumor Immunity of Triple Negative Breast Cancer.International journal of nanomedicine · 2026Article
- A DSSM network for inferring and prioritizing cell-type-specific regulons using single-cell RNA-seq data.BMC bioinformatics · 2025Article
- Reprogramming the tumor microenvironment: synergistic mechanisms of antibody-drug conjugates and immune checkpoint inhibitors.Antibody therapeutics · 2025Review
- Multi-omics analyses of the heterogenous immune microenvironment in triple-negative breast cancer implicate UQCRFS1 potentiates tumor progression.Experimental hematology & oncology · 2025Article
- Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.eLife · 2025Article
- Single-cell ligand-receptor profiling reveals an immunotherapy-responsive subtype and prognostic signature in triple-negative breast cancer.Frontiers in immunology · 2025Article
- Analysis of single-cell and spatial transcriptomics in TNBC cell-cell interactions.Frontiers in immunology · 2025Review
- Single-cell transcriptomes of dissecting the intra-tumoral heterogeneity of breast cancer microenvironment.Journal of cancer research and clinical oncology · 2024Article
- Knowledge-based inductive bias and domain adaptation for cell type annotation.Communications biology · 2024Article
- Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.Nature cancer · 2024Article
- Serial single-cell RNA sequencing unveils drug resistance and metastatic traits in stage IV breast cancer.NPJ precision oncology · 2024Article
- Integrating single-cell and bulk expression data to identify and analyze cancer prognosis-related genes.Heliyon · 2024Article
- Article
- Targeting triple-negative breast cancer cells with a β1-integrin binding aptamer.Molecular therapy. Nucleic acids · 2023Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high intratumoral heterogeneity. Recent studies revealed that TNBC patients might comprise cells with distinct molecular subtypes. In addition, gene regulatory networks (GRNs) constructed based on single-cell RNA sequencing (scRNA-seq) data have demonstrated the significance for decoding the key regulators. We performed a comprehensive analysis of the GRNs for the intrinsic subtypes of TNBC patients using scRNA-seq. The copy number variations (CNVs) were inferred from scRNA-seq data and identified 545 malignant cells. The subtypes of the malignant cells were assigned based on the PAM50 model. The cell-cell communication analysis revealed that the macrophage plays a dominant role in the tumor microenvironment. Next, the GRN for each subtype was constructed through integrating gene co-expression and enrichment of transcription-binding motifs. Then, we identified the critical genes based on the centrality metrics of genes. Importantly, the critical gene
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