BEX1 supports the stemness of hepatoblastoma by facilitating Warburg effect in a PPARγ/PDK1 dependent manner.

BACKGROUND: Hepatoblastoma (HB) is a highly aggressive paediatric malignancy that exhibits a high presence of cancer stem cells (CSCs), which related to tumour recurrence and chemotherapy resistance. Brain expressed X-linked protein 1 (BEX1) plays a pivotal role in ciliogenesis, axon regeneration and differentiation of neural stem cells. However, the role of BEX1 in metabolic and stemness programs in HB remains unclear. METHODS: BEX1 expression in human and mouse HB was analyzed using gene expression profile data from NCBI GEO and immunohistochemical validation. Seahorse extracellular flux analyzer, ultra-high-performance liquid-chromatography mass spectrometry (LC-MS), flow cytometry, qRT-PCR, Western Blot, sphere formation assay, and diluted xenograft tumour formation assay were used to analyze metabolic and stemness features. RESULTS: Our results indicated that overexpression of BEX1 significantly enhanced the Warburg effect in HB cells. Furthermore, glycolysis inhibition largely attenuated the effects of BEX1 on HB cell growth and self-renewal, suggesting that BEX1 promotes stemness maintenance of HB cells by regulating the Warburg effect. Mechanistically, BEX1 enhances Warburg effect through the downregulation of peroxisome proliferator-activated receptor-gamma (PPARγ). Furthermore, pyruvate dehydrogenase kinase isozyme 1 (PDK1) is required for PPARγ-induced inhibition of Warburg effect in HB. In addition, BEX1 supports the stemness of HB by enhancing Warburg effect in a PPARγ/PDK1 dependent manner. CONCLUSIONS: HB patients with high BEX1 and PDK1 expression had a poor prognosis. BEX1 promotes the stemness maintenance of HB cells via modulating the Warburg effect, which depends on PPARγ/PDK1 axis. Pioglitazone could be used to target BEX1-mediated stemness properties in HB by upregulating PPARγ.

Causes of death among early-onset colorectal cancer population in the United States: a large population-based study.

Background: Early-onset colorectal cancer (EOCRC) has an alarmingly increasing trend and arouses increasing attention. Causes of death in EOCRC population remain unclear. Methods: Data of EOCRC patients (1975-2018) were extracted from the Surveillance, Epidemiology, and End Results database. Distribution of death was calculated, and death risk of each cause was compared with the general population by calculating standard mortality ratios (SMRs) at different follow-up time. Univariate and multivariate Cox regression models were utilized to identify independent prognostic factors for overall survival (OS). Results: The study included 36,013 patients, among whom 9,998 (27.7%) patients died of colorectal cancer (CRC) and 6,305 (17.5%) patients died of non-CRC causes. CRC death accounted for a high proportion of 74.8%-90.7% death cases within 10 years, while non-CRC death (especially cardiocerebrovascular disease death) was the major cause of death after 10 years. Non-cancer death had the highest SMR in EOCRC population within the first year after cancer diagnosis. Kidney disease [SMR = 2.10; 95% confidence interval (CI), 1.65-2.64] and infection (SMR = 1.92; 95% CI, 1.48-2.46) were two high-risk causes of death. Age at diagnosis, race, sex, year of diagnosis, grade, SEER stage, and surgery were independent prognostic factors for OS. Conclusion: Most of EOCRC patients died of CRC within 10-year follow-up, while most of patients died of non-CRC causes after 10 years. Within the first year after cancer diagnosis, patients had high non-CRC death risk compared to the general population. Our findings help to guide risk monitoring and management for US EOCRC patients.

Mass spectrometry-based identification of new serum biomarkers in patients with latent infection pulmonary tuberculosis.

Noninvasive and simple indicators for diagnosing latent tuberculosis (TB) infection (LTBI) and tracking progression from latent infection to active TB infection are still desperately needed. The aim of this study was to screen and identify possible biomarkers for diagnosing LTBI and monitoring the progression from latent infection to active TB infection, as well as to investigate the underlying processes and functions. To assess changes in metabolite composition associated with active tuberculosis infection in humans, whole blood supernatants were collected from patients with LTBI, drug-susceptible TB patients, drug-resistant TB patients, and healthy controls. The metabolites in all serum samples were extracted by oscillatory, deproteinization, and then detected by liquid chromatography-tandem mass spectrometry/MS analysis. Normalization by Pareto-scaling method, the difference analysis was carried out by Metaboanalyst 4.0 software, and 1-way analysis of variance analysis among groups showed that P-value < 0.05 was regarded as a different metabolite. To clarify the dynamic changes and functions of differential metabolites with disease progression, and explore its significance and mechanism as a marker by further cluster analysis, functional enrichment analysis, and relative content change analysis of differential metabolites. 65 metabolites were substantially different in four groups. Differential metabolites such as Inosine and Prostaglandin E1 may be important blood indicators for diagnosing mycobacterium tuberculosis latent infection, which were all tightly connected to amino acid metabolism, Biosynthesis of various secondary metabolites, Nucleotide metabolism, Endocrine system, Immune system, Lipid metabolism, and Nervous system. This study screened and identified Inosine, 16, 16-dimethyl-6-keto Prostaglandin E1, Theophylline, and Cotinine as potential serum biomarkers for diagnosing latent TB infection, and Cotinine as potential biomarkers for monitoring disease progression from healthy population to LTBI and then to active TB including drug-resistant TB infection and sensitive TB infection. Furthermore, this research provides a preliminary experimental basis to further investigate the development of metabolomics-based diagnosis of LTBI and monitoring the progress from latent infection to active TB infection.

Performance evaluation of optical platelet counting of BC-6000Plus automated hematology analyzer.

BACKGROUND: The BC-6000Plus (Mindray, Shenzhen, China) is a recently developed hematology analyzer that utilizes fluorescent technology. Based on fluorescent nucleic acid stain and optical detection, the optical platelet counting (PLT-O) on the BC-6000Plus has strong anti-interference potential in platelet (PLT) detection. Its Auto 8×PLT-O Counting Tech can be automatically triggered in low-PLT samples, which enables the PLT-O on the BC-6000Plus to count low PLT more efficiently. Here, we evaluated the performance of the BC-6000Plus automated hematology analyzer in optical PLT counting. METHODS: The basic features (including blank counting, carryover, trueness, and accuracy) of the BC-6000Plus for PLT counting were evaluated according to the Analytical Quality Specifications for Routine Tests in Clinical Hematology (WST 406-2012). Low-PLT samples with a PLT count of below 100×109/L were selected for repeatability tests. Meanwhile, the potential correlations of BC-6000Plus with the XN-L 350 and manual microscopy within different PLT ranges or under interferences of small red blood cells (RBCs) or PLT aggregation were analyzed. RESULTS: The PLT-O on BC-6000Plus met the technical requirements of PLT counting in terms of blank count, carryover, trueness, and accuracy. The repeatability of the enhanced mode (PLT-O 8×) on the BC-6000Plus was better than that of the XN-L 350 in three low PLT count ranges, including 10-20, 20-60, and 60-100 (×109/L). Under the interference-free conditions, the BC-6000Plus correlated well with the XN-L 350 in different PLT counting ranges. Under the interferences of small RBCs and PLT aggregation, the PLT-O on BC-6000Plus correlated better with microscopy than with the platelet impedance count (PLT-I). CONCLUSIONS: The PLT-O on BC-6000Plus can meet the technical requirements of PLT counting in terms of blank counting, carryover rate, trueness, and accuracy. The PLT-O 8× has good repeatability, correlates well with the XN-L 350, and demonstrates good anti-interference ability. It can thus meet the needs of blood cell analysis in clinical settings.

Nomogram predictive model of post-operative recurrence in non-functioning pituitary adenoma.

BACKGROUND: To analyze and predict the possibility of post-operative recurrence in non-functioning pituitary adenoma (NFPA) patients, we investigated the clinical factors leading to tumor recurrence and built a nomogram predictive model based on these risk factors. METHODS: A single-center retrospective study was performed. A total of 145 NFPA patients who underwent surgical treatment at Shenzhen People's Hospital from September 2013 to January 2019 were selected. Among them, 52 patients were diagnosed with recurrence of NFPA according to follow-up investigations. Binary logistic regression analysis was used to determine the significant risk factors. A nomogram model was then built to predict recurrence using these factors. RESULTS: The univariate analysis and the binary logistic regression analysis showed that age, tumor size, cavernous invasion, sphenoid sinus invasion, and surgical extension were significant factors affecting tumor recurrence. We then built a nomogram model to predict post-operative recurrence in NFPA patients using these factors. The correlation analysis indicated that sphenoid sinus invasion [hazard ratio (HR) =13.14, 95% confidence interval (CI): 7.03-24.58, P<0.0001], cavernous sinus invasion (HR =7.53, 95% CI: 4.27-13.28, P<0.0001), and tumor size (HR =11.06, 95% CI: 6.11-20.03, P<0.0001) could promote the recurrence of NFPA. In contrast, advanced age (HR =0.50, 95% CI: 0.28-0.86, P<0.0001) and gross total resection (HR =0.12, 95% CI: 0.07-0.22, P<0.0001) could effectively inhibit recurrence. CONCLUSIONS: In this study, we developed a nomogram predictive model based on the significant recurrence-associated factors for NFPA. This nomogram may aid neurosurgeons in the post-operative prediction of recurrence, and may facilitate tailored counseling of individual patients.