Carlo C. Maley

This paper reviews 49 experiments showing that therapy-resistant cancer clones often have a fitness cost, with two-thirds demonstrating competitive disadvantage in untreated environments.

PHYFUM reconstructs the evolutionary history of normal and pre-malignant tissues using methylation data, revealing early gland divergence in the gut and later divergence in the endometrium.

TEATIME estimates evolutionary parameters and fitness diversity from bulk sequencing data, revealing patterns of intratumor heterogeneity across 33 cancer types.

This study compares microbial growth in kombucha and sweet tea after introducing human hand swabs, finding kombucha resists microbial invasion better due to its SCOBY and fermentation byproducts.

This paper argues for integrating phylogenetic comparative methods into evolutionary medicine, using comparative oncology to show how these methods can reveal evolutionary patterns in disease traits.

The paper analyzes immune-cancer tradeoffs across mammals, finding a negative correlation between cancer and trauma mortality, mediated by platelet size and trophic level.

This paper quantifies spatial cancer-stroma topology in post-TNT PDAC and shows it independently predicts disease-free survival better than traditional response assessments.

The paper introduces TLA, a computational framework using ecological principles to analyze tumor spatial heterogeneity and link it to clinical outcomes.

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.

The paper adapts a human cancer driver gene detection model to mice using transfer learning, identifying 24 driver genes in mouse breast cancer exomes.

This study reconstructs DCIS growth dynamics using somatic mutation topography, revealing a multiclonal, branching morphogenesis-like pattern consistent with a new Comet model of tumorigenesis.

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.

The paper investigates the development and evolution of extrachromosomal DNA (ecDNA) in Barrett's esophagus patients progressing to esophageal adenocarcinoma, finding ecDNA is strongly associated with cancer progression and enriched for oncogenes and immunomodulatory genes.

The paper uses genomic profiling to show that some invasive breast cancers are clonally unrelated to their preceding DCIS, suggesting DCIS may act as both a precursor and independent risk factor.

This paper develops and validates a new bioinformatic algorithm to accurately identify somatic SNVs from small DNA amounts in FFPE breast cancer samples, showing improved performance over existing methods.

This study introduces a computational method to classify cancer driver genes as oncogenes or tumor suppressors based on mutation patterns across 33 cancer types, identifying novel genes and revealing context-specific functions.

MAGOS improves subclone detection in tumors sequenced at standard depths by correcting sequencing errors and outperforms existing methods in accuracy and efficiency.

The paper introduces CryptSim, a simulator of crypt evolution in Barrett’s esophagus, showing that interactions between neighboring crypts are crucial in carcinogenesis.