Article

Unraveling tumor heterogeneity: Quantitative insights from scRNA-seq analysis in breast cancer subtypes

2024-09-01

Abstract excerpt

Tumors are complex systems characterized by genetic, transcriptomic, phenotypic, and microenvironmental variations. The complexity of this heterogeneity plays a crucial role in metastasis, tumor progression, and recurrence. In this work, we utilized publicly available single-cell transcriptomics data from human breast cancer samples (ER+, HER2+, and triple-negative) to evaluate key concepts pertinent to cancer bio...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1aab1500-ed01-5f93-9a9d-175fede563cd
DOI: 10.1101/2024.08.30.610531

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Unraveling tumor heterogeneity: Quantitative insights from scRNA-seq analysis in breast cancer subtypesDOI 10.1101/2024.08.30.610531Read

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seqSemantic proximity Read

Chromosomal copy number heterogeneity predicts survival rates across cancers.Semantic proximity Read

Novel insights into breast cancer copy number genetic heterogeneity revealed by single-cell genome sequencing.Semantic proximity Read

Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes.Semantic proximity Read

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-SeqSemantic proximity Read

Single-cell allelic transcriptomic analysis unravels intratumoral gene expression heterogeneity linked to TNBC pathogenesisSemantic proximity Read

A Retrospective View on Triple Negative Breast Cancer Microenvironment: Novel Markers, Interactions, and Mechanisms of Tumor-Associated Components using public Single-cell RNA Seq DatasetsSemantic proximity Read

Identification of malignant cells in single-cell transcriptomics dataSemantic proximity Read

An Integrative Model of Single Cell Transcriptomic States for Triple-Negative Breast CancerSemantic proximity Read

Tumor Functional Heterogeneity Unraveled by scRNA-seq TechnologiesSemantic proximity Read

Single-cell analyses reveal a simple multi-gene transcriptomic signature with predictive power in prognosis and therapy effectiveness in triple-negative breast cancerSemantic proximity Read

Intra-tumor heterogeneity defines treatment-resistant HER2+ breast tumorsSemantic proximity Read