Analysis of Response to Immunotherapies – Transcriptomic Biomarkers

Immunotherapies are a groundbreaking approach in cancer treatment, stimulating the immune system to recognize and attack tumor cells. Gene expression analysis helps better understand immunotherapy response, predict treatment efficacy, and monitor immune response evolution.

Genes Analyzed in Immunotherapy Response

Our panel targets key biomarkers linked to immune response, inflammation, and immunotherapy effectiveness, including:

• PD-1 (Programmed Death-1) & PD-L1 (Programmed Death-Ligand 1) – Checkpoint inhibitors targeted by therapies like pembrolizumab and nivolumab

• CTLA-4 (Cytotoxic T-Lymphocyte-Associated Protein 4) – Inhibitory receptor targeted by ipilimumab to enhance anti-tumor immunity

• IFN-γ (Interferon gamma) – Key cytokine in anti-tumor immune response, used as a biomarker for predicting immunotherapy response

• CD8+ T lymphocytes – Cytotoxic T cells essential for tumor elimination; their levels and activation indicate treatment response

• IL-2 (Interleukin-2) – Cytokine activating T cells and NK cells, enhancing immune response in immunotherapies

• TGF-β (Transforming Growth Factor Beta) – Immunosuppressive cytokine; high levels in the tumor microenvironment indicate potential treatment resistance

• MHC (Major Histocompatibility Complex) – Crucial for tumor antigen presentation to T cells, influencing tumor recognition

• Indoleamine 2,3-Dioxygenase (IDO) – Enzyme suppressing immune response, often linked to immunotherapy resistance

• TILs (Tumor-Infiltrating Lymphocytes) – Immune cells within tumors; their quantity and activity indicate treatment response

• MMP-9 (Matrix Metalloproteinase-9) – Enzyme linked to extracellular matrix remodeling, altered in tumors treated with immunotherapy

Applications & Benefits

• Predicting Immunotherapy Response – Determining a patient’s likelihood of responding to immune checkpoint inhibitors (anti-PD-1/PD-L1, anti-CTLA-4)

• Monitoring Treatment Efficacy – Tracking tumor response by measuring biomarker expression

• Identifying Resistant Patients – Detecting resistance-associated biomarkers like PD-L1, IDO, and TGF-β to adjust treatment strategies

• Personalizing Therapies – Tailoring immunotherapy protocols based on patient-specific gene expression profiles

• Evaluating T-Cell Activation & Inflammatory Responses – CD8+ T cell activation and IFN-γ production as indicators of an active immune response

• Optimizing Combination Therapies – Guiding the selection of immunotherapy combinations with conventional or targeted treatments to enhance overall efficacy

Technologies Used

• RT-qPCR & RNA-seq (NGS) – Quantifying immune-related and anti-tumor gene expression

• Nanostring & Transcriptomic Microarrays – Multiplex biomarker analysis for immunotherapy response prediction

• Flow Cytometry (FACS) – Assessing T cell activation and tumor-targeting ability

• Immunohistochemistry – Measuring protein expression of PD-L1, CTLA-4, and other biomarkers in tumor tissues

Contact us at contact@genxmap.com for an in-depth and personalized analysis of immunotherapy response to optimize your treatment strategies!