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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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Updated: Jun 4, 2025

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
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Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and

Huimin Li1, Yuheng Jiao2, Yi Zhang3

  • 1Department of Internal Medicine Residency Training Base, Gongli Hospital of Shanghai Pudong New Area, Shanghai, 200135, China.

Cellular Oncology (Dordrecht, Netherlands)
|December 19, 2024
PubMed
Summary
This summary is machine-generated.

Programmed cell death (PCD) pathways are linked to apoptosis and metastasis in non-small cell lung cancer (NSCLC). The gene SLC7A5 is identified as a prognostic indicator and potential therapeutic target for enhancing apoptosis in NSCLC.

Keywords:
BiomarkerCell apoptosisSLC7A5Single-cell RNA sequencingSpatial transcriptomics

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Non-small cell lung cancer (NSCLC) is the most common lung malignancy.
  • Programmed cell death (PCD) is crucial for cell survival and homeostasis, with growing relevance in cancer research.
  • Investigating PCD in NSCLC may reveal novel therapeutic strategies.

Purpose of the Study:

  • To explore the role and mechanisms of programmed cell death (PCD) in non-small cell lung cancer (NSCLC).
  • To identify genes causally related to PCD in NSCLC and their prognostic significance.
  • To evaluate SLC7A5 as a potential therapeutic target for NSCLC.

Main Methods:

  • Utilized GEO and TCGA databases for NSCLC gene expression analysis.
  • Employed single-cell sequencing and spatial transcriptomics to study PCD mechanisms and tumor microenvironment interactions.
  • Applied Mendelian randomization, machine learning for prognostic modeling, and in vitro experiments.

Main Results:

  • High PCD activity in NSCLC cells correlates with apoptosis, cell migration, and hypoxia pathways.
  • A prognostic model (NSCLCPCD) based on PCD genes shows strong predictive power.
  • SLC7A5 promotes NSCLC proliferation, and its knockout enhances tumor cell apoptosis.

Conclusions:

  • Programmed cell death in NSCLC is associated with apoptosis, metastasis, and hypoxia.
  • SLC7A5 is a significant prognostic indicator for NSCLC.
  • SLC7A5 represents a potential therapeutic target for increasing apoptosis in NSCLC.