Enhancing clinical decision-making: A novel nomogram for stratifying cancer-specific survival in middle-aged individuals with follicular thyroid carcinoma utilizing SEER data.

Background: Thyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients. Methods: We collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model. Results: A total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805-0.927), for the validation cohort it was 0.944 (95 % CI: 0.903-0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997-1.001). Calibration curves and AUC suggest that the model has good accuracy. Conclusions: We developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.

Leukotriene B4 receptor 1 (BLT1) does not mediate disease progression in a mouse model of liver fibrosis.

MASH is a prevalent liver disease that can progress to fibrosis, cirrhosis, hepatocellular carcinoma (HCC), and ultimately death, but there are no approved therapies. Leukotriene B4 (LTB4) is a potent pro-inflammatory chemoattractant that drives macrophage and neutrophil chemotaxis, and genetic loss or inhibition of its high affinity receptor, leukotriene B4 receptor 1 (BLT1), results in improved insulin sensitivity and decreased hepatic steatosis. To validate the therapeutic efficacy of BLT1 inhibition in an inflammatory and pro-fibrotic mouse model of MASH and fibrosis, mice were challenged with a choline-deficient, L-amino acid defined high fat diet and treated with a BLT1 antagonist at 30 or 90 mg/kg for 8 weeks. Liver function, histology, and gene expression were evaluated at the end of the study. Treatment with the BLT1 antagonist significantly reduced plasma lipids and liver steatosis but had no impact on liver injury biomarkers or histological endpoints such as inflammation, ballooning, or fibrosis compared to control. Artificial intelligence-powered digital pathology analysis revealed a significant reduction in steatosis co-localized fibrosis in livers treated with the BLT1 antagonist. Liver RNA-seq and pathway analyses revealed significant changes in fatty acid, arachidonic acid, and eicosanoid metabolic pathways with BLT1 antagonist treatment, however, these changes were not sufficient to impact inflammation and fibrosis endpoints. Targeting this LTB4-BLT1 axis with a small molecule inhibitor in animal models of chronic liver disease should be considered with caution, and additional studies are warranted to understand the mechanistic nuances of BLT1 inhibition in the context of MASH and liver fibrosis.

Discovery and characterization of novel potent BCR-ABL degraders by conjugating allosteric inhibitor.

The oncogenic fusion protein BCR-ABL is the driving force of leukemogenesis in chronic myeloid leukemia (CML). Despite the great advance in CML treatment through the application of tyrosine kinase inhibitors (TKIs) against BCR-ABL, disease recurrence after TKI discontinuation and clinical resistance mainly due to BCR-ABL mutations continue to be an issue. Herein we report our efforts to synthesize a novel series of CRBN-recruiting proteolysis-targeting chimeras (PROTACs) targeting BCR-ABL based on the allosteric inhibitor asciminib. Our efforts have led to the discovery of compound 30 (SIAIS100) through extensive SAR studies by the optimization of linker parameters as well as linker attachment points of both target-binding warhead and CRBN ligands, which exhibited the most potent degradative activity with a DC50 value of 2.7 nM and Dmax of 91.2% against BCR-ABL and has an IC50 value of 12 nM in BCR-ABL + K562 cells. The binding model and the stability evaluation of 30-induced ternary complex formation were also elucidated through computational simulations. Furthermore, 30 induced sustained and robust BCR-ABL degradation and maintained the efficacy for 96 h post-washout. Moreover, the proteomics analysis showed that 30 degraded BCR-ABL and three CRBN's neo-substrates, including IKZF1, IKZF3, and ZFP91. Additionally, 30 also exerted degradative activity against a panel of clinically relevant resistance-conferring mutations of BCR-ABL, including gatekeeper mutation T315I, several single mutations associated with TKI resistance, and certain highly resistant compound mutations. Our study provided a deeper understanding of the development of PROTACs targeting BCR-ABL and novel potential therapeutic agents for CML treatment.