Evanthia T. Roussos Torres

The paper develops an agent-based model of breast cancer metastases to predict responses to dual checkpoint inhibition and identifies spatially-informed treatment strategies.

The paper shows HDAC1 inhibition in MDSCs increases Malat1, decreases pSTAT3, induces apoptosis and cell cycle arrest, and reduces T cell suppression.

The paper develops mathematical models and Bayesian inference methods to analyze tumor-immune dynamics in metastatic breast cancer, revealing immune suppressive parameters as key predictors of response to immunotherapy.

The paper investigates how myeloid-T cell interactions and B cell activation influence response to checkpoint inhibition in metastatic breast cancer using multi-omics and computational methods.

This paper introduces iterative logistic regression (iLR) to identify small sets of marker genes for subtle cell state changes, showing high accuracy in distinguishing cell subtypes and predicting therapeutic effects.

The paper models EMT dynamics across cancers to identify genes associated with intermediate states and plasticity, finding SFN and NRG1 as key markers.

This study shows CXCL12 gradients around TMEM doorways promote tumor cell invasion and create immunosuppressive niches by affecting CD8+ T cell function and distribution.

The paper identifies HTR2B on MDSCs as a target to enhance immune checkpoint inhibitors in breast-to-brain metastasis using clozapine and anti-PD-1 therapy.

This study shows that the cell of origin in lung adenocarcinoma affects the immunosuppressive state of the tumor microenvironment, with AT1-derived tumors showing an anti-tumor immune profile and AT2-derived tumors showing immunosuppressive features.

The paper characterizes a novel syngeneic murine breast cancer model (NT2.5-LM) that exhibits rapid and widespread metastases, enabling study of metastatic progression and therapeutic responses.

This paper identifies a cis-regulatory mechanism in triple-negative breast cancer where targeting circadian transcription factors with small molecules represses a circadian transcriptional program, offering a new therapeutic strategy.

This study develops a mathematical model to analyze MDSC dynamics in metastatic niches, showing that MDSC delays and suppression capabilities significantly impact metastasis outcomes.

This paper introduces EVAsc, a method to analyze expression variation in scRNA-seq data to quantify tumor heterogeneity across cell types, subtypes, and patients.