Alexander R.A. Anderson

This study shows that durable CAR-T therapy in lymphoma requires cooperation with endogenous CD8 T cells, and tumors lacking MHC class I or CD58 resist treatment.

This paper curates a large corpus of mathematical oncology literature using AI, revealing its evolution from cancer biology to therapeutic modeling over 140 years.

This study shows that stromal niches protect lung cancers from ALK inhibitors through multiple mechanisms, and targeting these mechanisms together is more effective than targeting them individually.

The paper shows that targeted therapy resistance in cancer selects for cells with higher phenotypic plasticity, which enhances their ability to adapt to other stressors and promotes metastasis.

The paper develops a combination therapy for ER+ breast cancer that uses an evolutionary double-bind strategy to suppress drug resistance.

The paper identifies collagen remodeling as a mechanism that activates a GPCR-mediated immune checkpoint in ADGRG1+ CD8+ T cells, influencing response to immunotherapy.

This study uses a 3D computational model to show that tumor growth rates depend on tissue density and metabolic strategies like glycolysis or angiogenesis in lung cancer.

This paper develops and validates a treatment strategy called evolutionary antifragile therapy, which uses treatment fluctuations to limit tumor resistance evolution.

This paper develops mathematical biomarkers to predict treatment outcomes for adaptive therapy in cancer, showing personalized strategies outperform standard-of-care protocols.

This study uses computational modeling to explore how spatial interactions between immune cells and collagen fibers influence tumor growth and immune infiltration.

The paper models tumors as ecological communities using the Generalized Lotka-Volterra model to understand intra-tumor heterogeneity and its implications for cancer progression and treatment resistance.

The paper develops spatial descriptors using mathematical tools to analyze cell interactions in colorectal cancer progression and demonstrates their utility in identifying disease-related pathways.

This study combines radiotherapy and NK cell immunotherapy to exploit an evolutionary double-bind strategy in prostate cancer, showing that RT-resistant cells become more vulnerable to NK cell killing.

This study tests adaptive therapy protocols using gemcitabine and capecitabine on a mouse model of endocrine-resistant breast cancer, finding improved survival with adaptive strategies over high-dose combination therapy.

This paper investigates adaptive therapy with single cytotoxic or cytostatic drugs, finding it effective under specific conditions and dosing strategies.

This paper evaluates adaptive therapy strategies using two cytotoxic or two cytostatic drugs, finding that dose modulation protocols perform better with cytotoxic drugs while ping-pong protocols are more effective with cytostatic drugs under specific conditions.

This paper uses agent-based models to analyze how metastatic tumor dynamics inform adaptive therapy schedules and identifies how tumor heterogeneity affects treatment outcomes.

The paper introduces rapidly oscillating molecular clocks to quantify human stem cell dynamics and finds differences in stem cell replacement rates between small intestine and colon, as well as effects of germline mutations.

NeoPredPipe predicts and assesses neoantigen recognition potential from tumor variants in single and multi-region samples, providing insights into neoantigen burden and tumor heterogeneity.

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.

The paper introduces the Hybrid Automata Library (HAL), a Java platform for building hybrid models in mathematical oncology, with real-time visualization and modular components.

This study develops a hybrid model showing stromal reactivity influences prostate cancer progression and prognosis by shaping tumor cell evolution and aggressiveness.

The paper introduces a hybrid method to estimate parameters in agent-based models using glioblastoma data to improve model calibration.

The paper introduces MultiCellDS, a standard and community-driven initiative for sharing multicellular data to enhance research in cell biology.

The paper introduces MultiCellDS, a standard for multicellular data curation, and presents MultiCellDB as a database to store associated data, enhancing data sharing and utility in biological and clinical research.

This paper models how space limitation drives intratumoral heterogeneity through competition for space, focusing on proliferation and migration traits using an off-lattice individual-based model.