Location of Repository

Cancer metabolism: new validated targets for drug discovery.

By Federica Sotgia, Ubaldo E. MD Martinez-Outshoorn and Michael P. Lisanti

Abstract

Recent studies in cancer metabolism directly implicate catabolic fibroblasts as a new rich source of i) energy and ii) biomass, for the growth and survival of anabolic cancer cells. Conversely, anabolic cancer cells upregulate oxidative mitochondrial metabolism, to take advantage of the abundant fibroblast fuel supply. This simple model of \u22metabolic-symbiosis\u22 has now been independently validated in several different types of human cancers, including breast, ovarian, and prostate tumors. Biomarkers of metabolic-symbiosis are excellent predictors of tumor recurrence, metastasis, and drug resistance, as well as poor patient survival. New pre-clinical models of metabolic-symbiosis have been generated and they genetically validate that catabolic fibroblasts promote tumor growth and metastasis. Over 30 different stable lines of catabolic fibroblasts and \u3e10 different lines of anabolic cancer cells have been created and are well-characterized. For example, catabolic fibroblasts harboring ATG16L1 increase tumor cell metastasis by \u3e11.5-fold, despite the fact that genetically identical cancer cells were used. Taken together, these studies provide \u3e40 novel validated targets, for new drug discovery and anti-cancer therapy. Since anabolic cancer cells amplify their capacity for oxidative mitochondrial metabolism, we should consider therapeutically targeting mitochondrial biogenesis and OXPHOS in epithelial cancer cells. As metabolic-symbiosis promotes drug-resistance and may represent the escape mechanism during anti-angiogenic therapy, new drugs targeting metabolic-symbiosis may also be effective in cancer patients with recurrent and advanced metastatic disease

Topics: Cancer metabolism: new validated targets for drug discovery, Thomas Jefferson University, Kimmel Cancer Center, Oncology
Publisher: Jefferson Digital Commons
Year: 2013
OAI identifier: oai:jdc.jefferson.edu:kimmelccfp-1043

Suggested articles

Preview


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.