DNA-PKcs controls calcineurin mediated IL-2 production in T lymphocytes

<div><p>Loss of DNA-dependent protein kinase catalytic subunit (DNA-PKcs) activity in mammals results in severe combined immuno-deficiency (SCID). This SCID phenotype has been postulated to be due solely to the function of DNA-PKcs in V(D)J recombination, a process critical for lymphocyte maturation. However; we show that DNA-PKcs is required for IL-2 production via regulation of the calcineurin signaling pathway. Reducing DNA-PKcs activity in activated T cells either by shRNA or an inhibitor significantly reduced IL-2 production by blocking calcineurin activity and the translocation of NFAT into the nucleus. Additionally, we show that DNA-PKcs exerts its effect on calcineurin by altering the expression of the endogenous calcineurin inhibitor Cabin1 through activation of the kinase CHK2, a known Cabin1 regulator. The discovery of DNA-PKcs as a potent regulator of IL-2 production will drive continued investigation of small molecule inhibition of this enzyme within the clinic.</p></div

Inhibition of DNA-PKcs reduces phosphorylation of CHK2 and stabilizes the calcineurin inhibitor, Cabin1.

<p>A) Western blot analysis of Jurkat lysates following activation with PMA+PHA and NU7441 treatment. Activation increased phosphorylation of DNA-PKcs and CHK2. DNA-PKcs inhibition reduced CHK2 phosphorylation and elevated Cabin1 expression. GAPDH was used as a loading control. B) Schematic depicting the signaling pathway in T cells used by DNA-PKcs to regulate IL-2 production. DNA-PKcs phosphorylates CHK2 which in turns phosphorylates Cabin1 targeting it for destruction. This alleviates calcineurin inhibition causing an increase in translocation of NFAT and IL-2 production. CaN, calcineurin.</p

DNA-PKcs inhibition blocks calcineurin activity in T cells.

<p>A) Jurkat cells were activated with PMA+PHA, treated with the DNA-PKcs inhibitor NU7441 (2.5μM) and monitored for calcineurin phosphatase activity. Inhibition caused a significant reduction in calcineurin activity. B) Level of Ca²⁺ in Jurkat cell lysates following activation with PMA+PHA was monitored. Ca²⁺ levels were not affected by the addition of the NU7441 inhibitor. C) Western blot and Elisa analysis of active phosphorylated mTOR in activated Jurkat cells indicated that inhibition of DNA-PKcs does not alter mTOR activation. ***p<0.001 error bars = s.d.</p

Inhibition of DNA-PKcs blocks translocation of NFAT to the nucleus.

<p>A) Western blot analysis of Jurkat cell lysates showed activation of T cells with PMA+PHA induced phosphorylation of DNA-PKcs at site s2056 (pDNA-PK) and dephosphorylated NFAT at s237 (pNFAT). Treatment with NU7441 inhibited the dephosphorylation of NFAT at site s237 which is critical for its translocation to the nucleus. GAPDH was used as a loading control. B) Immunocytochemistry analysis of Jurkat cells treated with NU7441. The inhibitor (2.5 μM) blocked translocation of NFAT to the nucleus following activation with PMA+PHA. Nuclei were stained with Dapi. 40X images are shown.</p

Inhibition of DNA-PKcs in T cells and PBMCs blocks IL-2 production.

<p>A) Jurkat cells were treated with the DNA-PKcs inhibitor NU7441 at varying concentrations for 48 hours and no significant reduction in viability was detected. B) Jurkat cells were stimulated with PMA (50 ng/mL)+PHA (1 μg/mL), treated with NU7441, and analyzed for IL-2 production 24 hours later. NU7441 treatment significantly blocked IL-2 secretion. C) IL-2 production stimulated by activation of Jurkat cells with anti-CD28/CD3 dynabeads at a 1:1 ratio for 24 hours was inhibited by NU7441 treatment. D) Treatment of Jurkat cells with shRNA reduced DNA-PKcs expression at 2.5 and 5 μg as seen by western blot analysis. Loss of DNA-PKcs expression significantly reduced IL-2 production. E) NU7441 significantly reduce IL-2 production following activation with PHA+PMA in PBMCs. ** p< 0.002 *** p<0.001 error bars = s.d.</p

A Formula to Calculate Standard Liver Volume Using Thoracoabdominal Circumference.

BackgroundWith the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates.MethodsLDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression.ResultsThe optimal formula using TAC was determined to be SLV = (TAC × 3.5816) - (Age × 3.9844) - (Sex × 109.7386) - 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025).ConclusionWe report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts

A Formula to Calculate Standard Liver Volume Using Thoracoabdominal Circumference.

Background:With the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates. Methods:LDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression. Results:The optimal formula using TAC was determined to be SLV = (TAC × 3.5816) - (Age × 3.9844) - (Sex × 109.7386) - 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025). Conclusion:We report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts

Proteomic Identification of DNA-PK Involvement within the RET Signaling Pathway

<div><p>Constitutive activation of the Rearranged during Transfection (RET) proto-oncogene leads to the development of MEN2A medullary thyroid cancer (MTC). The relatively clear genotype/phenotype relationship seen with RET mutations and the development of MEN2A is unusual in the fact that a single gene activity can drive the progression towards metastatic disease. Despite knowing the oncogene responsible for MEN2A, MTC, like most tumors of neural crest origin, remains largely resistant to chemotherapy. Constitutive activation of RET in a SK-N-MC cell line model reduces cell sensitivity to chemotherapy. In an attempt to identify components of the machinery responsible for the observed RET induced chemoresistance, we performed a proteomic screen of histones and associated proteins in cells with a constitutively active RET signaling pathway. The proteomic approach identified DNA-PKcs, a DNA damage response protein, as a target of the RET signaling pathway. Active DNA-PKcs, which is phosphorylated at site serine 2056 and localized to chromatin, was elevated within our model. Treatment with the RET inhibitor RPI-1 significantly reduced s2056 phosphorylation in RET cells as well as in a human medullary thyroid cancer cell line. Additionally, inhibition of DNA-PKcs activity diminished the chemoresistance observed in both cell lines. Importantly, we show that activated DNA-PKcs is elevated in medullary thyroid tumor samples and that expression correlates with expression of RET in thyroid tumors. These results highlight one mechanism by which RET signaling likely primes cells for rapid response to DNA damage and suggests DNA-PKcs as an additional target in MTC.</p></div

Components of an active RET signaling pathway are observed in MTC and correlate to DNA-PKcs.

<p>Immunohistochemistry of MTC array samples for phosphorylated ERK 1/2 and phosphorylated AKT indicated the presence of both of these components of an active RET signaling pathway in MTC similar to staining observed for ps2056 DNA-PKcs. 10x images of whole tissue array sample are shown.</p

List of proteins found to be significantly altered in RET 9 and RET 51 lines compared to control lines.

<p>Fold change ≤1.5 is considered increased expression and between 0.2 and 0.6 is decreased expression.</p><p>List of proteins found to be significantly altered in RET 9 and RET 51 lines compared to control lines.</p