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Related Concept Videos

The Tumor Microenvironment02:17

The Tumor Microenvironment

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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
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Mapping Breast Cancer Microenvironment Through Single-Cell Omics.

Zhenya Tan1, Chen Kan1, Minqiong Sun1

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This summary is machine-generated.

Breast cancer progression involves a complex tumor microenvironment. Single-cell RNA sequencing (scRNA-seq) helps dissect this heterogeneity, aiding diagnosis and treatment strategies for breast cancer.

Keywords:
breast cancerheterogeneitymicroenvironmentsingle-cell RNA sequencingsingle-cell omics

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Area of Science:

  • Oncology
  • Immunology
  • Genomics

Background:

  • Breast cancer progression is influenced by tumor microenvironment (TME) heterogeneity.
  • Key TME components include lymphocytes, myeloid cells, macrophages, and fibroblasts.
  • The role of TME cell patterns in breast cancer pathogenesis is understudied.

Purpose of the Study:

  • To review recent literature on breast cancer TME using single-cell RNA sequencing (scRNA-seq).
  • To analyze cell heterogeneity and spatial distribution within the breast cancer TME.
  • To enhance understanding for clinical classification, diagnosis, and treatment.

Main Methods:

  • Literature review focusing on scRNA-seq studies of breast cancer TME.
  • Analysis of cell types including T cells, B cells, macrophages, monocytes, neutrophils, and stromal cells.
  • Discussion of advanced single-cell omics technologies and deep learning.

Main Results:

  • scRNA-seq provides high-resolution single-cell expression data.
  • Detailed dissection of molecular characteristics within the TME is achievable.
  • Heterogeneity and spatial location of various immune and stromal cells are being elucidated.

Conclusions:

  • A comprehensive understanding of the breast cancer TME is emerging.
  • scRNA-seq is crucial for characterizing TME complexity.
  • Novel omics technologies and AI will advance breast cancer research.