M. Robertson-Tessi

This study develops an adaptive therapy protocol for PARP inhibitors by combining mathematical modeling and experiments to optimize treatment scheduling and mitigate resistance.

The paper analyzes multiplexed histological images from NSCLC patients to identify spatial immune ecologies that predict disease progression and serve as potential biomarkers for therapy response.

This paper presents a multiscale mathematical model of tumor-immune interactions that identifies metaphenotypes driving immune escape and metabolic transformation in cancer.

VALIS automates registration of immunohistochemistry and immunofluorescence images, enabling spatial analysis of whole slide images with low error and minimal computational time.

Mistic provides an open-source tool to visualize multiplexed images using t-SNE or UMAP layouts for exploratory analysis of tumor tissue ecology.

This paper develops a mathematical model of stochastic phenotype switching in cancer cells to show how non-genetic inheritance contributes to treatment resistance and proposes a therapeutic strategy to enhance treatment efficacy.

This study shows how spatial structure affects adaptive therapy by influencing intra-tumoral competition between drug-sensitive and resistant cells.

This paper introduces a mathematical framework to quantify cancer cell line fragility or antifragility to treatment variability and applies it to treatment resistance and collateral sensitivity.

This study develops a mathematical model of neoantigen evolution in tumors and validates it with colorectal cancer data, showing how negative selection shapes tumor immunogenotype and clonality.

The paper investigates how harsh microenvironments in early breast cancer select for a Warburg phenotype through metabolic and transcriptomic changes.

This study investigates whether a cost of resistance is necessary for adaptive therapy to delay cancer progression, finding that cell turnover modulates this requirement depending on tumor growth conditions.

This study shows that tissue structure influences tumor evolution by accelerating neutral expansion through spatial constraints and dispersal events.

The paper models tumor-immune dynamics in colorectal cancer progression, showing immune evasion enables transition from immune-hot adenomas to immune-cold carcinomas.

This study uses immunohistochemistry data to model how macrophages influence tumor evolution through spatial dynamics and immune escape strategies in ductal carcinomas.

This study shows that tumor acidity promotes prostate cancer by altering macrophage phenotype, both in vitro and in vivo, and is supported by in silico modeling.

The paper develops a mathematical model to optimize neoadjuvant combination therapy for ER+ breast cancer by balancing tumor burden and metastatic potential using game theory.