Mehdi Damaghi, PhD

Mehdi Damaghi, PhD
Department of Pathology
Assistant Professor
Stony Brook Cancer Center
Lauterbur Drive, 8M 
Stony Brook, New York 11794
Phone: (631) 216-2926
Email: mehdi.damaghi@stonybrookmedicine.edu
Lab Website

Publications

Research Interest
Evolution of metabolic phenotypes in variable tumor microenvironment
The central aim of my lab research is to use ecological-evolutionary principles to understand molecular mechanism of breast and ovarian cancer initiation, progression, and metastasis through adaptation to microenvironment. I hypothesize that evolution of new metabolic phenotypes under variable microenvironment selection can drive cancer through metabolic reprogramming linked to epigenetics and transcription factors activation and stabilization.

We study how the tumor adaptation can shape the new microenvironment and metabolism that shape emerging selective pressures. This interplay between tumor cells and microenvironment plays a fundamental role in development of ever-changing tumor ecosystem leading to more genotypic heterogeneity and phenotypic plasticity. We use integration of single cell genome, epigenome, transcriptome, proteome and metabolome, and pathomics analysis to capture the heterogeneity and plasticity of cancer cells in their natural context.

Here are the main four projects in the lab:

• Project 1: Ecology and Evolution of Breast Carcinogenesis.
  • Aim 1: How microenvironment selection play role in phenotypic switch of early breast cancer? Single cell RNA seq and single cell ATAC seq will be used to connect phenotypes to cancer cell mutation signatures.
  • Aim 2: Novel single cell barcoding techniques is used to track clonal dynamic and correlate it to the genotypic and phenotypic adaptation.
  • Aim 3: Mechanism of metabolic reprogramming of early breast cancer cells.
• Project 2: Metabolic phenotypes present in DCIS to stratify Disease progression and upstaging.
  • Aim 1: CODEX and Vectra multiplex IHC technique to define metabolic phenotype in longitudinal Breast Cancer patient samples (DCIS -> IDC -> Mets).
  • Aim 2: Omics study on longitudinally collected patient samples to track the evolutionary dynamics to design predictive biomarker of progression and upstaging.
• Project 3: Co-evolution of tumor and stroma in breast cancer.
  • Aim 1: Mouse model (GEM) of breast cancer to study the co-evolution tumor cells and stroma cell.
  • Aim 2: Spheroid and organoid (mouse and patient) culture to model tumor-stroma evolution.
  • Aim 3: Longitudinal patients samples multiplex IHC staining to study tumor ecosystems.
• Project 4: Evolution of resistant phenotype to PARPi in ovarian cancer: genotypic heterogeneity vs phenotypic plasticity.
  • Aim 1: Integration of multi omics (DNA seq, scRNA seq, and proteomics) data to understand mechanism of resistance to PARP1.
  • Aim 2: Fitness landscape dynamics of cancer cells under PARPi treatment.
  • Aim 3: Patient organoid culture to study genetic heterogeneity vs phenotypic plasticity role in PARPi resistance.