Precision Medicine of Cancer

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

"Cancer Microbiome" In our recent publication in Oncogenesis (2024), we showed that A. temperans plays a driver role in lung tumor development, as modeled by repeated A. temperans intranasal instillation into a mouse model of lung adenocarcinoma (LUAD) harboring K-ras and p53 mutations. We showed that mice exposed to A. temperans exhibit higher lung tumor burden and reduced survival compared to mice instilled with sham (PBS) or with the commensal bacteria L. gasseri. Using single cell RNA sequencing (scRNA seq) we investigated the mouse lung tumor immune microenvironment. We identified a pro-inflammatory pathway, specifically increased in A. temperans mice, where TLR4/NF-kB signaling was activated in macrophages, which upregulated MHC II to activate effector CD4+ T cells, polarizing them to TH17 states. These TH17 cells recruited neutrophils to the lungs which acquired tissue residency and pro-tumorigenic phenotypes. This work was published in Oncogenesis in 2024. In collaboration with Giorgio Trinchieri, we are using high parametric flow cytometry to further investigate the lung tumor microenvironment of A. temperans mice. We validated our scRNAseq findings and identified a population of double negative T cells (DNTs), a population of T cells characterized by expression of CD3 and TCRalphabeta, but lacking CD4, CD8 and NKT cell marker expression, that is dramatically enhanced in A. temperans and is associated with disease progression. These DNT cells have a pro-inflammatory effector/memory-like phenotype, as shown by expression of CD44, CD103 and IL-17. These data suggest that DNTs, together with infiltrated neutrophils and TH17 cells, contribute to A. temperans-driven lung tumorigenesis and may serve as potential therapeutic targets to ameliorate lung tumor progression. A manuscript to report these data is currently under preparation. It has long been known that the gut and lungs are connected through the gut-lung axis, where the gut microbiome can influence lung health and immune responses. Previous studies showed that the probiotic Bifidobacterium genus protects against lung inflammation in severe asthma by decreasing neutrophil and eosinophil infiltration to the lungs. In collaboration with Giorgio Trinchieri, We are currently investigating whether Bifidobacterium protects against A. temperans-mediated lung inflammation by suppressing infiltration of pro-tumorigenic neutrophil populations. These studies may unravel a novel therapeutic approach using Bifidobacterium probiotics for the treatment of lung cancer. "Metabolomics" This multicohort study investigates the diagnostic and prognostic utility of urinary creatine riboside (CR)-a novel metabolite arising from tumor-associated metabolic reprogramming-as a biomarker for prostate cancer (PCa). CR has previously shown promise in other malignancies, including lung and liver cancers, but its relevance in PCa remains unexplored. We measured CR levels in 927 prostate cancer cases and 960 population controls across two independent cohorts: the racially diverse, well-annotated NCI-Maryland (NCI-MD) cohort and an external Ghanaian validation set. CR concentrations were quantified via targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). CR levels were significantly elevated in PCa cases compared to controls (median 4.52 nM vs. 0.67 nM, p < 0.00001) and correlated positively with Gleason score, PSA, NCCN risk group, and adverse clinical outcomes. To evaluate its clinical applicability, we developed a machine learning-based CR-integrated risk score using LASSO-regularized logistic regression, incorporating CR alongside PSA, age, Gleason score, and race. The resulting model achieved high diagnostic accuracy (AUC more than 0.88) and stratified patients into distinct risk categories. Survival analysis demonstrated that patients in the highest-risk group-defined by elevated CR, PSA, and Gleason score-had significantly worse outcomes (median 8 vs. 13 years; p < 0.001). We are currently extending this work by integrating cytokine profiling into the model to explore whether host immune status further refines risk prediction. This extension is grounded in growing evidence that tumor metabolism and inflammation act synergistically to drive prostate cancer progression. By incorporating inflammatory cytokines, we aim to construct a multi-analyte panel that captures both tumor-intrinsic and immune-modulatory risk components. In parallel, we are pursuing the development of a digital clinical decision support tool that embeds this risk model for deployment in real-world clinical settings. Given that CR can be measured non-invasively in urine with minimal biospecimen handling, this platform holds particular promise for application in low-resource or community-based care settings, where standard diagnostic tools may be inaccessible or impractical. This work introduces a scalable, biomarker-informed strategy for precision early detection and risk stratification in prostate cancer. Through integration of metabolomics, immunoprofiling, and AI-based modeling, this approach offers an analytically robust and clinically actionable path forward to reduce overdiagnosis, enhance prognostication, and improve outcomes across diverse populations.