ReviewInternational journal of molecular sciences2024
Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.
Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Single-Cell Analysis Reveals STARD10 as a Fatty Acid Metabolism Regulator of Breast Cancer Progression via the PI3K/Akt Pathway.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
- Targeted Therapies for Each Subtype of Breast Cancer.MedComm · 2026Review
- Development of a Prognostic Stratification Model and Identification of BDH1 as an Oncoprotein in Breast Cancer Based on Subcluster-Specific Markers of B-Cell Subsets.Breast cancer (Dove Medical Press) · 2026Article
- Emerging Approaches in Breast Cancer: From Molecular Mechanisms to Diagnosis and Therapeutic Strategies.Oncology research · 2026Review
- Systematic screening of metabolic pathways to identify two breast cancer subtypes with divergent immune characteristics.Scientific reports · 2025Article
- Multidrug Resistance: Are We Still Afraid of the Big Bad Wolf.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.International journal of molecular sciences · 2025Article
- Identification of potential novel targets for treating inflammatory bowel disease using Mendelian randomization analysis.International journal of colorectal disease · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.
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.