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Related Experiment Video

Updated: Jun 28, 2025

Author Spotlight: Replicating Human Osteosarcoma Progression in Immunodeficient Mice for Cancer Study
02:35

Author Spotlight: Replicating Human Osteosarcoma Progression in Immunodeficient Mice for Cancer Study

Published on: March 22, 2024

794

Deciphering programmed cell death mechanisms in osteosarcoma for prognostic modeling.

Jingyang Chen1, Tengdi Fan1, Lingxiao Pan1

  • 1Department of Orthopedics, Ningbo Medical Center Lihuili Hospital, Ningbo, Zhejiang, China.

Environmental Toxicology
|April 16, 2024
PubMed
Summary
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Substance P-expressing neurons in the hypothalamic paraventricular nucleus mediate chronic cough hypersensitivity via the hypothalamus-airway neural pathway.

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This study reveals key programmed cell death (PCD) genes in osteosarcoma (OS) and develops a bioinformatics model to predict patient outcomes, aiding in the development of targeted therapies for this challenging cancer.

Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Osteosarcoma (OS) is characterized by high rates of recurrence and metastasis, presenting a significant clinical challenge.
  • Understanding the molecular mechanisms, including programmed cell death (PCD), is crucial for improving OS treatment outcomes.

Purpose of the Study:

  • To investigate the role of PCD genes in osteosarcoma.
  • To develop and validate a prognostic model for OS based on PCD-related genes using bioinformatics approaches.

Main Methods:

  • Analysis of single-cell and bulk sequencing data from public databases (GEO, TARGET).
  • Application of consistency clustering, Kaplan-Meier survival analysis, and ssGSEA for PCD score calculation.
  • Identification of differentially expressed genes, GO/KEGG enrichment analysis, and immune cell infiltration analysis.
Keywords:
GEOTARGETmachine learningosteosarcomaprogrammed cell death

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  • Development and validation of a prognostic model using LASSO regression.
  • Main Results:

    • Identification of distinct cell subpopulations and PCD gene distribution in OS.
    • Development of a robust prognostic model based on five genes (BAMBI, TMCC2, NOX4, DKK1, CBS) with significant predictive accuracy.
    • Insights into PCD pathways, drug sensitivity, and immune microenvironment in OS.

    Conclusions:

    • The developed prognostic model enhances the understanding of PCD's role in OS progression.
    • This research provides a foundation for developing novel therapeutic strategies targeting PCD pathways in osteosarcoma.