ArticleBreast cancer research : BCR2021
Transcriptome analysis of heterogeneity in mouse model of metastatic breast cancer.
Article in Breast cancer research : BCR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 36 citations in OpenAlex.
- Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.Quantitative biology (Beijing, China) · 2026Article
- Spatiotemporal transcriptomic insights into ferroptosis and TFRC-linked immune interactions in ischemia-reperfusion acute kidney injury.Genes and immunity · 2026Article
- Role of intratumoral heterogeneity in metastatic progression and drug resistance.Discover oncology · 2025Review
- Coagulation proteases modulate nucleic acid uptake and cGAS-STING-IFN induction in the tumor microenvironment.JCI insight · 2025Article
- Transcriptomic Profiling of Paired Primary Tumors and CNS Metastases in Breast Cancer Reveals Immune Modulation Signatures.International journal of molecular sciences · 2025Article
- Bridging the Gap in Breast Cancer Dormancy: Models, Mechanisms, and Translational Challenges.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Characteristics of the Dynamic Evolutionary Pathway of ADSCs Induced Differentiation into Astrocytes Based on scRNA-Seq Analysis.Molecular neurobiology · 2025Article
- Heterogeneity analysis and prognostic model construction of HPV negative oral squamous cell carcinoma T cells using ScRNA-seq and bulk-RNA analysis.Functional & integrative genomics · 2025Article
- MDA-MB-231 breast cancer cells adapted to anchorage-independent growth reveal senescent-like phenotype and persistent downregulation of PD-L1 expression.Frontiers in oncology · 2025Article
- Mitophagy-associated biomarkers and macrophage involvement in pulmonary arterial hypertension: identification and functional implications.Frontiers in physiology · 2025Article
- The Role of Immunocyte Infiltration Regulatory Network Based on hdWGCNA and Single-Cell Bioinformatics Analysis in Intervertebral Disc Degeneration.Inflammation · 2024Article
- Article
- FOXF1 inhibits invasion and metastasis of lung adenocarcinoma cells and enhances anti-tumor immunity via MFAP4/FAK signal axis.Scientific reports · 2024Article
- Single-cell transcriptional profiling in osteosarcoma and the effect of neoadjuvant chemotherapy on the tumor microenvironment.Journal of bone oncology · 2024Article
- Exploring the resistance mechanism of triple-negative breast cancer to paclitaxel through the scRNA-seq analysis.PloS one · 2024Article
- Identification of antigen-presentation related B cells as a key player in Crohn's disease using single-cell dissecting, hdWGCNA, and deep learning.Clinical and experimental medicine · 2023Article
- scRNA-seq and proteomics reveal the distinction of M2-like macrophages between primary and recurrent malignant glioma and its critical role in the recurrence.CNS neuroscience & therapeutics · 2023Article
- Single-cell transcriptomics provide insight into metastasis-related subsets of breast cancer.Breast cancer research : BCR · 2023Review
- Taxane chemotherapy induces stromal injury that leads to breast cancer dormancy escape.PLoS biology · 2023Article
- Role of Up-Regulated Transmembrane Channel-Like Protein 5 in Pancreatic Adenocarcinoma.Digestive diseases and sciences · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCancer metastasis is a complex process involving the spread of malignant cells from a primary tumor to distal organs. Understanding this cascade at a mechanistic level could provide critical new insights into the disease and potentially reveal new avenues for treatment. Transcriptome profiling of spontaneous cancer models is an attractive method to examine the dynamic changes accompanying tumor cell spread. However, such studies are complicated by the underlying heterogeneity of the cell types involved. The purpose of this study was to examine the transcriptomes of metastatic breast cancer cells using the well-established MMTV-PyMT mouse model.
methodsOrgan-derived metastatic cell lines were harvested from 10 female MMTV-PyMT mice. Cancer cells were isolated and sorted based on the expression of CD44
resultsComparison of RNA sequencing data across all cell populations produced distinct gene clusters. Differential gene expression patterns related to CD44 expression, organ tropism, and immunomodulatory signatures were observed. scRNA-seq identified expression profiles based on tissue-dependent niches and clonal heterogeneity. These cohorts of data were narrowed down to identify subsets of genes with high expression and known metastatic propensity. Dot plot analyses further revealed clusters expressing cancer stem cell and cancer dormancy markers. Changes in relevant genes were investigated across pseudo-time and tissue origin using Monocle2. These data revealed transcriptomes that may contribute to sub-clonal evolution and treatment evasion during cancer progression.
conclusionsWe performed a comprehensive transcriptome analysis of tumor heterogeneity and organ tropism during breast cancer metastasis. These data add to our understanding of metastatic progression and highlight targets for breast cancer treatment. These markers could also be used to image the impact of tumor heterogeneity on metastases.
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