Combination therapy for colorectal cancer with anti-PD-L1 and cancer vaccine: A multiscale mathematical model of tumor-immune interactions

TL;DR

This study presents a multiscale mathematical model to analyze the effectiveness of combination therapy with anti-PD-L1 and cancer vaccines in colorectal cancer, highlighting optimal dosing strategies and predictive biomarkers for personalized treatment.

Contribution

It introduces a novel computational framework integrating tumor-immune interactions and heterogeneity, providing insights into optimal therapy regimens and biomarkers for colorectal cancer.

Findings

Multiple low-dose anti-PD-L1 regimens reduce tumor burden.

Maximum dose cancer vaccine therapy controls tumor growth effectively.

Cytotoxic T cells-to-regulatory T cells ratio predicts treatment response.

Abstract

The tumor-immune system plays a critical role in colorectal cancer progression. Recent preclinical and clinical studies showed that combination therapy with anti-PD-L1 and cancer vaccines improved treatment response. In this study, we developed a multiscale mathematical model of interactions among tumors, immune cells, and cytokines to investigate tumor evolutionary dynamics under different therapeutic strategies. Additionally, we established a computational framework based on approximate Bayesian computation to generate virtual tumor samples and capture inter-individual heterogeneity in treatment response. The results demonstrated that a multiple low-dose regimen significantly reduced advanced tumor burden compared to baseline treatment in anti-PD-L1 therapy. In contrast, the maximum dose therapy yielded superior tumor growth control in cancer vaccine therapy. Furthermore, cytotoxic T cells were identified as a consistent predictive biomarker both before and after treatment initiation. Notably, the cytotoxic T cells-to-regulatory T cells ratio specifically served as a robust pre-treatment predictive biomarker, offering potential clinical utility for patient stratification and therapy personalization.