Cancer cells can inhibit effector T cells (Teff) through both immunomodulatory receptors and the impact of cancer metabolism on the tumor microenvironment. Indeed, Teff require high rates of glucose metabolism, and consumption of essential nutrients or generation of waste products by tumor cells may impede essential T cell metabolic pathways. Clear cell renal cell carcinoma (ccRCC) is characterized by loss of the tumor suppressor von Hippel-Lindau (VHL) and altered cancer cell metabolism. Here, we assessed how ccRCC influences the metabolism and activation of primary patient ccRCC tumor infiltrating lymphocytes (TIL). CD8 TIL were abundant in ccRCC, but they were phenotypically distinct and both functionally and metabolically impaired. ccRCC CD8 TIL were unable to efficiently uptake glucose or perform glycolysis and had small, fragmented mitochondria that were hyperpolarized and generated large amounts of ROS. Elevated ROS was associated with downregulated mitochondrial SOD2. CD8 T cells with hyperpolarized mitochondria were also visible in the blood of ccRCC patients. Importantly, provision of pyruvate to bypass glycolytic defects or scavengers to neutralize mitochondrial ROS could partially restore TIL activation. Thus, strategies to improve metabolic function of ccRCC CD8 TIL may promote the immune response to ccRCC.
Peter J. Siska, Kathryn E. Beckermann, Frank M. Mason, Gabriela Andrejeva, Allison R. Greenplate, Adam B. Sendor, Yun-Chen J. Chiang, Armando L. Corona, Lelisa F. Gemta, Benjamin G. Vincent, Richard C. Wang, Bumki Kim, Jiyong Hong, Chiu-lan Chen, Timothy N. Bullock, Jonathan M. Irish, W. Kimryn Rathmell, Jeffrey C. Rathmell
Usage data is cumulative from August 2021 through August 2022.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.