Glutathione determines chronic myeloid leukemia vulnerability to an inhibitor of CMPK and TMPK.

Bcr-Abl transformation leads to chronic myeloid leukemia (CML). The acquirement of T315I mutation causes tyrosine kinase inhibitors (TKI) resistance. This study develops a compound, JMF4073, inhibiting thymidylate (TMP) and cytidylate (CMP) kinases, aiming for a new therapy against TKI-resistant CML. In vitro and in vivo treatment of JMF4073 eliminates WT-Bcr-Abl-32D CML cells. However, T315I-Bcr-Abl-32D cells are less vulnerable to JMF4073. Evidence is presented that ATF4-mediated upregulation of GSH causes T315I-Bcr-Abl-32D cells to be less sensitive to JMF4073. Reducing GSH biosynthesis generates replication stress in T315I-Bcr-Abl-32D cells that require dTTP/dCTP synthesis for survival, thus enabling JMF4073 susceptibility. It further shows that the levels of ATF4 and GSH in several human CML blast-crisis cell lines are inversely correlated with JMF4073 sensitivity, and the combinatory treatment of JMF4073 with GSH reducing agent leads to synthetic lethality in these CML blast-crisis lines. Altogether, the investigation indicates an alternative option in CML therapy.

Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry.

PURPOSE: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. MATERIALS AND METHODS: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. RESULTS: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88-0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. CONCLUSIONS: Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Reliability of the Montreal Cognitive Assessment in people with stroke.

This study examined the relative and absolute reliability of the Taiwanese version of the MoCA (MoCA-T) in people with stroke. The study recruited 114 individuals who were at least 3 months after the onset of a first-ever unilateral stroke. The MoCA-T was administered twice, at a 6-week interval, to all participants. The relative reliability was assessed using the intraclass correlation coefficient (ICC), and the absolute reliability was assessed using standard error of measurement (SEM), the smallest real difference (SRD), the SRD percentage, and the Bland-Altman method. The ICC analysis showed the MoCA-T was highly reliable (ICC = 0.85). The absolute reliability was between an acceptable and excellent level, where the SEM and the SRD at the 95% confidence interval were 1.38 and 3.83, respectively. The Bland-Altman analyses showed no systematic bias between repeated measurements. The range of the 95% limits of agreement was narrow, indicating a high level of stability over time. These findings suggest that the MoCA-T has high agreement between repeated measurements without systematic bias. The threshold to detect real change stands between an acceptable and excellent level. The MoCA-T is a reliable tool for cognitive screening in stroke rehabilitation.