Ashiq Masood: Mapping pancreatic cancer ecosystems across primary tumors and metastases

Ashiq Masood shared a post on X about a recent paper by Ateeq Khaliq et al. published in Nature Genetics.

“Spatial transcriptomic analysis of primary and metastatic pancreatic cancers highlights tumor microenvironmental heterogeneity”

Authors: Ateeq Khaliq, Meenakshi Rajamohan, Omer Saeed, Bassel El Rayes, Ashiq Masood et al.

“Checkout new paper from our lab in Nature Genetics. We mapped pancreatic cancer ecosystems across primary tumors and metastases using spatial transcriptomics on matched samples.

We introduce ‘spatial ecotypes’ as multicellular neighborhoods in a spatial context, contributing to the growing field of spatial transcriptomics and cancer ecology.

Our analysis revealed greater tumor microenvironment heterogeneity than previously known, with multiple ecotypes coexisting within individual patients.

• Primary tumors: Dense stroma, hypoxia, EMT, immunosuppressive features
• Metastases: Less stroma, high proliferation, metabolic reprogramming
• Immunogenic border ecotype: Diverse immune cells, potential immunotherapy target

By analyzing matched samples, we highlight interpatient variability and the need for personalized treatment strategies based on individual tumor ecosystems.

This integrated spatial atlas provides a framework for understanding pancreatic cancer progression and may guide development of targeted therapies for diverse tumor ecosystems.

We thank our great collaborators and colleagues: Julienne Carstens, Alan Wang, Anita Turk, Mateusz Opyrchal, IU Simon Comprehensive Cancer Center, IU School of Medicine.

Thank you Jennifer Schwartz for all the support!!”

Source: Ashiq Masood/X

Ashiq Masood is an Adjunct Associate Professor at the IU School of Informatics and an Associate Professor of Medicine in the Division of Hematology/Oncology at the IU School of Medicine. He is also an associate member of the Experimental and Developmental Therapeutics Program. His research focuses on single-cell RNA sequencing, spatial transcriptomics in gastrointestinal cancers, and organoid modeling.