Human TTK blocking peptide

Background: A proper restoration of sagittal alignment is essential in AIS patients, but few studies provided a formula to predict an optimal surgical thoracic kyphosis (TK) gain in adolescent idiopathic scoliosis (AIS) patients. A formula was recently proposed (LL = (PI+TK)/2 + 10) to predict the optimal lumbar lordosis (LL) in adult spinal deformity patients, which has not been validated in adolescents. The aim of this study is to establish a formula with TK and pelvic parameters in normal adolescents and predict an optimal TK with this formula pre-and post-operatively in Lenke 1 AIS patients. Methods: A total of 60 asymptomatic adolescents were used to validate the proposed formula. The subject was considered to match with the formula, if the difference between the virtual TK and the theoretical TK was less than 10 degrees. Then regression analysis was performed to establish a new formula to predict TK in adolescents. The predictive efficiency of the new formula was also validated in 40 Lenke 1 AIS patients. Results: Of the 60 asymptomatic adolescents, only 26 (43.33%) asymptomatic adolescents matched with the adjusted formula: TK = 2 x (LL-10)-PI. The paired t test revealed a significantly different theoretical TK (tTK) compared to the virtual TK (41.23 +/- 18.29 degrees vs. 24.80 +/- 8.75 degrees, P < 0.001). Multiple linear regression showed that TK had a relationship with LL, SS and age (R-2 = 0.331): TK = -0.785 x LL-0.843 x SS + 0.858 x age + 3.754. There were 27 (67.50%), 32 (80.00%) and 35 (87.50%) Lenke 1 AIS patients matched this formula preoperatively, postoperatively and at the last follow-up. Conclusion: Our results revealed that the predictive formula for sagittal alignment for adults was not applicable in adolescents. This study established a new predictive formula for TK based on asymptomatic adolescents. In Lenke 1 AIS patients, post-op TK in 87.5% of patients matched the predictive value, indicating that the new formula can be considered as a reference when making a surgery strategy.

Ovarian cancer is characterized by frequent mutations at TP53. These tumors also harbor germline mutations at homologous recombination repair genes, so they rely on DNA-damage checkpoint proteins, like the checkpoint kinase 1 (CHEK1) to induce G(2) arrest. In our study, by using an in silico approach, we identified a synthetic lethality interaction between CHEK1 and mitotic aurora kinase A (AURKA) inhibitors. Gene expression analyses were used for the identification of relevant biological functions. OVCAR3, OVCAR8, IGROV1, and SKOV3 were used for proliferation studies. Alisertib was tested as AURKA inhibitor and LY2603618 as CHEK1 inhibitor. Analyses of cell cycle and intracellular mediators were performed by flow cytometry and Western blot analysis. Impact on stem cell properties was evaluated by flow cytometry analysis of surface markers and sphere formation assays. Gene expression analyses followed by functional annotation identified a series of deregulated genes that belonged to cell cycle, including AURKA/B, TTK kinase, and CHEK1. AURKA and CHEK1 were amplified in 8.7% and 3.9% of ovarian cancers, respectively. AURKA and CHEK1 inhibitors showed a synergistic interaction in different cellular models. Combination of alisertib and LY2603618 triggered apoptosis, reduced the stem cell population, and increased the effect of taxanes and platinum compounds. Finally, expression of AURKA and CHEK1 was linked with detrimental outcome in patients. Our data describe a synthetic lethality interaction between CHEK1 and AURKA inhibitors with potential translation to the clinical setting. (C) 2017 AACR.