Investigation of Interferon Gamma Activity Using Bioinformatics Methods.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Breast cancer is a significant global health issue, often linked to genetic mutations.
• Bioinformatics offers powerful tools for analyzing gene sequences and protein structures.

Purpose of the Study:

• To investigate the structural and functional impact of Interferon Gamma (IFNγ) in breast cancer patients versus healthy controls using bioinformatics.
• To identify potential genetic markers for breast cancer.

Main Methods:

• Bioinformatics analysis of blood samples from 75 breast cancer patients and 25 healthy controls.
• Utilized BLAST, BioEdit, ProtParam, PSIpred, PHYRE2, RasMol, and STRING for mutation, structure, and interaction analysis.

Main Results:

• Identified higher rates of transversion (70%) and missense (84%) mutations in breast cancer patients' IFNγ.
• Observed alterations in IFNγ secondary structure (alpha-helix, beta-sheet, coil) and physicochemical properties due to mutations.
• Confirmed protein interactions and tertiary structure of IFNγ in breast cancer.

Conclusions:

• Mutations in Interferon Gamma (IFNγ) significantly affect its structure and function in breast cancer patients.
• IFNγ exhibits potential as a diagnostic marker for breast cancer.