Related Experiment Video

Updated: Jul 17, 2025

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens
09:53

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Published on: February 6, 2017

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Molecular characteristics and therapeutic implications of Toll-like receptor signaling pathway in melanoma

Hewen Guan1, Xu Chen2, Jifeng Liu2

  • 1Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Scientific Reports
|September 4, 2023
PubMed

Insights

This study reveals Toll-like receptor (TLR) genes are crucial for melanoma. A new prognostic model using six TLR genes accurately predicts melanoma patient survival and immune traits.

Area of Science:

  • Oncology
  • Immunology
  • Genetics

Background:

  • Melanoma, a cancer of melanocytes, is often immunogenic, but the role of Toll-like receptors (TLRs) remains unclear.
  • TLR gene expression varies across cancers, influenced by the tumor immune microenvironment.

Purpose of the Study:

  • To investigate the role of TLR-related genes in melanoma.
  • To develop a prognostic model for melanoma based on TLR gene expression.
  • To explore correlations between TLR pathways, prognosis, immune infiltration, and metabolic reprogramming in melanoma.

Main Methods:

  • Pan-cancer analysis of TLR gene alterations (CNV, SNV, mRNA) using TCGA and GEO data.
  • Clustering of melanoma patients based on TLR pathway expression.
  • Construction and validation of a six-gene prognostic model using Cox regression and LASSO analysis.

Main Results:

  • Melanoma patients were classified into three subgroups based on TLR pathway expression.
  • The study identified significant correlations between TLR pathways and melanoma prognosis, immune infiltration, metabolic reprogramming, and oncogene expression.
  • A validated prognostic model comprising six TLR-related genes was developed.

Conclusions:

  • A novel prognostic survival model based on TLR-related genes accurately assesses melanoma patient prognosis and immune traits.
  • This model holds critical potential for improving patient survival outcomes.
  • Understanding TLRs' role is vital for melanoma treatment strategies.

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