Mitochondrial gene expression-based model for the prediction of thyroid cancer prognosis

Area of Science:

• Mitochondrial genomics
• Cancer biology
• Immunology

Background:

• Mitochondrial gene roles in thyroid cancer (TC) and its tumor microenvironment are unclear.
• Understanding these roles is crucial for developing novel prognostic tools and therapeutic strategies.

Purpose of the Study:

• To elucidate the role of mitochondrial genes in TC development and the tumor microenvironment.
• To construct a prognostic model for TC based on dysregulated mitochondrial genes.
• To investigate the function of semaphorin 7A (SEMA7A) in TC progression and immune infiltration.

Main Methods:

• Unsupervised consensus clustering of TC datasets from TCGA and gene expression databases.
• Machine learning for constructing a prognostic model using 64 dysregulated mitochondrial genes.
• Functional assays (cloning, migration, invasion) and immune cell infiltration analysis for SEMA7A.

Main Results:

• A 14-gene prognostic model (including SEMA7A) accurately predicted overall survival (OS) in TC across stages.
• SEMA7A was upregulated in TC tissues and cell lines, promoting proliferation, migration, and invasion.
• SEMA7A expression correlated with increased regulatory T cell (Treg) infiltration, suggesting an immunosuppressive tumor microenvironment.

Conclusions:

• The developed mitochondrial gene-based prognostic model shows clinical value for TC.
• Oncogenic SEMA7A drives TC progression and contributes to an immunosuppressive tumor microenvironment.
• Targeting mitochondrial dysregulation and SEMA7A may offer new therapeutic avenues for TC.