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T cells need to adapt their cellular metabolism for effector cell differentiation. This relies on alterations in mitochondrial physiology. Which signals and molecules regulate those alterations remains unclear. We recently reported, that the mitochondrial protein TCAIM inhibits activation-induced changes in mitochondrial morphology and function and thus, CD effector T cell formation. Using conditional TCAIM knock-in (KI) and knockout (KO) mice, w now show that it also applies to CD8+ T cells and more importantly, delineate the molecular processes in mitochondria by which TCAIM controls effector cell differentiation. TCAIM KI resulted in reduced activation-induced HIF1α protein expression. Metabolomics and transcriptional data in combination with mathematical flux modeling revealed an impaired induction of anabolic pathways, especially of the mevalonate pathway and cholesterol biosynthesis in TCAIM KI CD8+ T cells. Addition of cholesterol completely rescued HIF1α protein expression, activation and proliferation of TCAIM KI CD8+ T cells. At the molecular level, TCAIM delayed activation-induced mitochondria-ER contact (MERC) formation by binding to MERC promoting proteins such as RMD3 and VDAC2. In summary, we demonstrate that TCAIM suppresses effector cell differentiation by inhibiting MERC formation, which induce HIF1α-mediated increase in cellular metabolism and cholesterol biosynthesis.
Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case–control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis.