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Safdar, M.

Publications and source records attributed to Safdar, M..

2 recordsLinked to original sources

Hypoxia-mediated suppression of pyruvate carboxylase drives tumor microenvironment immunosuppression

Metabolic reprogramming and immune evasion are established hallmarks of the tumor microenvironment (TME). Growing evidence supports tumor metabolic dysregulation as an important mediator of tumor immune evasion. High TME levels of lactate potently suppress antitumor immunity. Pyruvate carboxylase (PC), the enzyme responsible for the anaplerotic conversion of pyruvate to oxaloacetate, is essential for lung metastasis in breast cancer. Moreover, PC may be dispensable in some cells within the TME, and loss of PC expression is associated with immunosuppression. Here we test whether PC suppression alters tumor metabolism and immunosuppression. Using multiple animal models of breast cancer, we identify a dimorphic role for PC expression in mammary cancer cells. Specifically, PC supports metastatic colonization of the lungs, while suppression of PC promotes primary tumor growth and suppresses histological and transcriptomic markers of antitumor immunity. We demonstrate that PC is potently suppressed by hypoxia, and that PC is frequently suppressed in solid tumors, particularly those with higher levels of hypoxia. Using metabolomics, high-resolution respirometry, and extracellular flux analysis, we show that PC-suppressed cells produce more lactate and undergo less oxidative phosphorylation than controls. Finally, we identify lactate metabolism as a targetable dependency of PC-suppressed cells, which is sufficient to restore T cell populations to the TME of PC-suppressed tumors. Taken together, these data demonstrate that elevated lactate following PC suppression by hypoxia may be a key mechanism through which primary tumors limit antitumor immunity. Thus, these data highlight that PC-directed tumor metabolism is a nexus of tumor progression and antitumor immunity.

cancer biology↗

TISON: a next-generation multi-scale modeling theatre for in silico systems oncology

Multi-scale models integrating biomolecular data from genetic, transcriptional, and translational levels, coupled with extracellular microenvironments can assist in decoding the complex mechanisms underlying system-level diseases such as cancer. To investigate the emergent properties and clinical translation of such cancer models, we present Theatre for in silico Systems Oncology (TISON, https://tison.lums.edu.pk), a next-generation web-based multi-scale modeling and simulation platform for in silico systems oncology. TISON provides a "zero-code" environment for multi-scale model development by seamlessly coupling scale-specific information from biomolecular networks, microenvironments, cell decision circuits, in silico cell lines, and organoid geometries. To compute the temporal evolution of multi-scale models, a simulation engine and data analysis features are also provided. Furthermore, TISON integrates patient-specific gene expression data to evaluate patient-centric models towards personalized therapeutics. Several literature-based case studies have been developed to exemplify and validate TISONs modeling and analysis capabilities. TISON provides a cutting-edge multi-scale modeling pipeline for scale-specific as well as integrative systems oncology that can assist in drug target discovery, repositioning, and development of personalized therapeutics.

systems biology↗