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Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

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Related Experiment Video

Updated: May 15, 2025

Tumor Transplantation for Assessing the Dynamics of Tumor-Infiltrating CD8+ T Cells in Mice

Tumor Transplantation for Assessing the Dynamics of Tumor-Infiltrating CD8+ T Cells in Mice

Published on: June 12, 2021

CD8+ T Cell Subsets as Biomarkers for Predicting Checkpoint Therapy Outcomes in Cancer Immunotherapy.

Rosaely Casalegno Garduño¹, Alf Spitschak¹, Tim Pannek¹

¹Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany.

|April 29, 2025

Summary

Immune checkpoint blockade (ICB) shows promise in cancer immunotherapy but has limited efficacy. New biomarkers, particularly circulating CD8+ T cells, can predict patient response to ICB, improving treatment decisions.

Keywords:

CD8+ T cell subsets ICB NSCLC TILs biomarker cancer immunotherapy melanoma

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Last Updated: May 15, 2025

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Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Area of Science:

Oncology
Immunology
Cancer Research

Background:

Immune checkpoint blockade (ICB) has revolutionized cancer immunotherapy, offering improved survival for some patients.
However, limited efficacy and immune-related adverse effects necessitate better predictive biomarkers.
Cancer heterogeneity and oncogenic drivers like E2F1 and MYC impede immunotherapy effectiveness.

Purpose of the Study:

To review the interplay between cancer drivers and immune response in ICB therapy.
To highlight the potential of T cells, especially CD8+ T cells, as predictive biomarkers for ICB efficacy.
To discuss the limitations of current biomarkers and the advantages of novel approaches.

Main Methods:

Literature review focusing on cancer drivers, immune evasion mechanisms, and biomarker development in ICB therapy.
Analysis of existing FDA-approved biomarkers (TMB, PD-L1) and their limitations.
Exploration of T cell subsets (tumor-infiltrating and circulating) as potential predictive biomarkers.

Main Results:

Tumor-infiltrating CD8+ T cells correlate with positive outcomes but are difficult to access.
Circulating T cell subsets, including memory and progenitor exhausted T cells, show promise as accessible biomarkers.
Terminally exhausted T cells are associated with poor ICB response.

Conclusions:

Combining existing biomarkers (TMB/PD-L1) with CD8+ T cell frequency can enhance predictive accuracy.
Circulating T cells offer a more practical approach for monitoring ICB efficacy.
Future research should focus on computational models integrating cancer and immune signatures for personalized immunotherapy stratification.