Circular RNAs in laryngeal cancer.

Laryngeal cancer remains a significant global health concern, with poor prognosis for advanced-stage disease highlighting the need for novel diagnostic, prognostic, and therapeutic approaches. Circular RNAs (circRNAs), a class of covalently closed non-coding RNAs, have emerged as important regulators of gene expression and cellular processes in various cancers, including laryngeal cancer. This review summarizes the current understanding of circRNAs in laryngeal cancer, covering their biogenesis, regulatory mechanisms, and potential clinical applications. We explore the diverse functions of circRNAs, including their roles as miRNA sponges, protein interactors, and direct mRNA regulators, and their influence on key cellular processes such as proliferation, invasion, and metastasis. The review highlights promising circRNAs as diagnostic and prognostic biomarkers, as well as potential therapeutic targets. We also outline current strategies for circRNA modulation, including suppression techniques like RNA interference and CRISPR/Cas systems, and overexpression methods using vectors and synthetic circRNAs.

Persistent acute kidney injury biomarkers: A systematic review and meta-analysis.

BACKGROUND: Various biomarkers reportedly predict persistent acute kidney injury (AKI) despite their varying predictive performance across clinical trials. This study aims to compare the accuracy of various biomarkers in predicting persistent AKI in different populations and regions. METHODS: In this meta-analysis, we searched for urinary C-C motif chemokine ligand 14 (CCL14), Tissue inhibitor of metalloproteinase-2&insulin-like growth factor-binding protein-7 (TIMP-2&IGFBP7), Neutrophil Gelatinase-Associated Lipocalin (NGAL), plasma Cystatin C (pCysC), Soluble urokinase plasminogen activator receptor (suPAR), Proenkephalin (PenK) and urinary dickkopf-3:urinary creatinine (uDKK3:uCr) from various databases including Medline, PubMed, Embase, and Cochrane. This was geared towards predicting persistent AKI in adults (>18 years). Hierarchically summarized subject work characteristic curves (HSROC) and diagnostic odds ratio (DOR) values were used to summarize the diagnostic accuracy of the biomarkers. Further, meta-regression and subgroup analyses were carried out to identify sources of heterogeneity as well as evaluate the best predictive biomarkers in different populations and regions. RESULTS: We screened 31 studies from 2,356 studies and assessed the diagnostic value of 7 biomarkers for persistent AKI. Overall, CCL14 had the best diagnostic efficacy with an AUC of 0.79 (95 % CI 0.75-0.82), whereas TIMP-2 & IGFBP7, NGAL, and pCysC had diagnostic efficacy of 0.75 (95 % CI 0.71-0.79),0.71 (95 % CI 0.67-0.75), and 0.7007, respectively. Due to a limited number of studies, PenK, uDKK3:uCr, and suPAR were not subjected to meta-analysis; however, relevant literature reported diagnostic efficacy above 0.70. Subgroup analyses based on population, region, biomarker detection time, AKI onset time, and AKI duration revealed that in the intensive care unit (ICU) population, the AUC of CCL14 was 0.8070, the AUC of TIMP-2 & IGFBP7 was 0.726, the AUC of pCysC was 0.72, and the AUC of NGAL was 0.7344; in the sepsis population, the AUC of CCL14 was 0.85, the AUC of TIMP-2&IGFBP7 was 0.7438, and the AUC of NGAL was 0.544; in the post-operative population, the AUC of CCL14 was 0.83-0.93, the AUC of TIMP-2&IGFBP7 was 0.71, and the AUC of pCysC was 0.683. Regional differences were observed in biomarker prediction of persistent kidney injury, with AUCs of 0.8558 for CCL14, 0.7563 for TIMP-2 & IGFBP7, and 0.7116 for NGAL in the Eurasian American population. In the sub-African population, TIMP-2 & IGFBP7 had AUCs of 0.7945, 0.7418 for CCL14, 0.7097 for NGAL, and 0.7007 for pCysC. for TIMP-2 & IGFBP7 was 0.7945, AUC for CCL14 was 0.7418, AUC for NGAL was 0.7097, and AUC for pCysC was 0.7007 in the sub-African population. Duration of biomarker detection, AKI onset, and AKI did not influence the optimal predictive performance of CCL14. Subgroup analysis and meta-regression of CCL14-related studies revealed that CCL14 is the most appropriate biomarker for predicting persistent stage 2-3 AKI, with heterogeneity stemming from sample size and AKI staging. CONCLUSION: This meta-analysis discovered CCL14 as the best biomarker to predict persistent AKI, specifically persistent stage 2-3 AKI.

MRPL13 is a metastatic and prognostic marker of breast cancer: A silico analysis accompanied with experimental validation.

BACKGROUND: Although progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients. METHODS: We were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation. RESULTS: A total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC. CONCLUSION: We proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

Potential use of HSP70 as an indicator of heat stress in dairy cows - a review.

Heat stress (HS) poses significant challenges to the dairy industry, resulting in reduced milk production, impaired reproductive performance, and compromised animal welfare. Therefore, understanding the molecular mechanisms underlying cellular responses to HS is crucial for developing effective strategies to mitigate its adverse effects. Heat shock protein 70 (HSP70) has emerged as a potential player involved in cellular thermotolerance in dairy cows. This review provides a comprehensive overview of the role of HSP70 as a molecular chaperone in cellular thermotolerance in dairy cows under HS. HSP70 facilitates proper protein folding and prevents the aggregation of denatured proteins. By binding to misfolded proteins, it helps maintain protein homeostasis and prevents the accumulation of damaged proteins during HS. Additionally, HSP70 interacts with various regulatory proteins and signaling pathways, contributing to the cellular adaptive response to HS. The upregulation of HSP70 expression in response to HS is regulated by a complex network involving heat-shock factors (HSFs), heat-shock element-binding proteins, and HSF co-chaperones. Therefore, HSP70 holds the potential to be a useful indicator of tissue stress due to its role in maintaining cellular balance, and as it is released both inside and outside cells in response to stress. Traditional methods of measuring HSP70 in blood samples are labor-intensive, and with the process being potentially stressful for the animals and may subsequently affect the results. Therefore, measuring HSP expression in cow's milk has shown promise as an easy, non-invasive, and accurate way to detect HS in dairy cows. Monitoring HSP70 levels in milk can be applied as a supplementary approach to identify HS or HS resistance of individual cows, selection of suitable animals and to guide targeted management strategies. However, despite the potential advantages of using HSP70 as a biomarker for monitoring HS on dairy cows, challenges remain in standardizing measurement protocols, establishing species-specific reference ranges, addressing inter-individual variations, and determining the specificity of changes in HSP70 due to HS. Future research should focus on developing non-invasive techniques for HSP70 detection, with consideration of climatic conditions, and unravelling the molecular interactions and regulatory networks involving HSP70.

Development and validation of the surmising model for volumetric breast density using X-ray exposure conditions in digital mammography.

The use of breast density as a biomarker for breast cancer treatment has not been well established owing to the difficulty in measuring time-series changes in breast density. In this study, we developed a surmising model for breast density using prior mammograms through a multiple regression analysis, enabling a time series analysis of breast density. We acquired 1320 mediolateral oblique view mammograms to construct the surmising model using multiple regression analysis. The dependent variable was the breast density of the mammary gland region segmented by certified radiological technologists, and independent variables included the compressed breast thickness (CBT), exposure current times exposure second (mAs), tube voltage (kV), and patients' age. The coefficient of determination of the surmising model was 0.868. After applying the model, the correlation coefficients of the three groups based on the CBT (thin group, 18-36 mm; standard group, 38-46 mm; and thick group, 48-78 mm) were 0.913, 0.945, and 0.867, respectively, suggesting that the thick breast group had a significantly low correlation coefficient (p = 0.00231). In conclusion, breast density can be accurately surmised using the CBT, mAs, tube voltage, and patients' age, even in the absence of a mammogram image.

Evidence for the Contribution of the miR-206/BDNF Pathway in the Pathophysiology of Depression.

Depression is a complex disorder with substantial impacts on individual health and has major public health implications. Depression results from complex interactions between genetic and environmental factors. Epigenetic mechanisms, including DNA methylation (DNAm), microRNAs (miRNAs), and histone modifications, can produce heritable phenotypic changes without a change in DNA sequence and have been recently proven to mediate lasting increases in the risk of depression following exposure to adverse life events. Of these, miRNAs are gaining attention for their role in the pathogenesis of many stress-associated mental disorders, including depression. One such miRNA is microRNA-206 (miR-206), which is a critical candidate for increasing the susceptibility to stress. Although miR-206 is thought to be a typical muscle-specific miRNA, it is expressed throughout the brain, particularly in the hippocampus and prefrontal cortex (PFC). Until now, only a few studies have been conducted on rodents to understand its role in stress-related abnormalities in neurogenesis. However, the precise underlying molecular mechanism of miR-206-mediated depression-like behaviours remains largely unknown. Here, we reviewed recent advances in the field of biomedical and clinical research on the role of miR-206 in the pathogenesis of depression from studies using different tissues and various experimental designs, and described how abnormalities in miR-206 expression in these tissues can affect neuronal functions. Moreover, we focused on studies investigating the brain-derived neurotrophic factor (BDNF) as a functional target of miR-206, where miR-206 has been implicated in the pathogenesis of depression by suppressing the expression of the BDNF. In summary, these studies confirm the existence of a tight correlation between the pathogenesis of depression and the miR-206/BDNF pathway.

Comparing GBA1-Parkinson's disease and idiopathic Parkinson's disease: α-Synuclein oligomers and synaptic density as biomarkers in the skin biopsy.

The main genetic risk factors for Parkinson's disease (PD) are presently represented by variants in GBA1 gene encoding for the ß-glucocerebrosidase (GCase). Searching for a peripheral biomarker that can be used for selecting and monitoring patients in clinical trials targeting GBA1-associated PD (GBA1-PD) is a current challenge. We previously demonstrated that α-synuclein oligomers expressed as proximity ligation assay (PLA) score in synaptic terminals of skin biopsy are a reliable biomarker for distinguishing idiopathic PD (iPD) from healthy controls (HC). This cross-sectional study investigates an unexplored cohort of GBA1-PD (n = 27) compared to 28 HC, and 36 iPD cases to (i) analyze α-synuclein oligomers and quantify them throughout PLA score, (ii) investigate GCase expression in brain and synaptic terminals targeting the sweat gland, (iii) unravel indicators that could differentiate patients with specific GBA1 mutations. PLA score discriminates GBA1-PD from HC with sensitivity = 88.9% (95% CI 70.84-97.65), specificity = 88.5% (95% CI 69.85-97.55), and PPV = 88.9% (95% CI 73.24-95.90), AUC value = 0.927 (95% CI 0.859-0.996). No difference was found between GBA1-PD patients and iPD, suggesting a common pathological pathway based on α-synuclein oligomers. GCase score did not differ in GBA1-PD, iPD, and HC in the synaptic terminals, whereas a positive correlation was found between PLA score and GCase score. Moreover, a significant increase in synaptic density was observed in GBA1-PD compared to iPD and HC (P < 0.0001). Employing ROC curve to discriminate GBA1-PD from iPD, we found an AUC value for synaptic density = 0.855 (95% CI 0.749-0.961) with sensitivity = 85.2% (95% CI 66.27%-95.81%), specificity = 77.1% (95% CI 59.86%-89.58%), and PPV = 74.19% (60.53%-84.35%). The highest synaptic density values were observed in p.N409S patients. This work points out to the value of both PLA score and synaptic density in distinguishing GBA1-PD from iPD and to their potential to stratify and monitor patients in the context of new pathway-specific therapeutic options.

Comparative Analysis of Circular RNAs Expression and Function between Aortic and Intracranial Aneurysms.

An aneurysm is an abnormal enlargement or bulging of the wall of a blood vessel. Most often, aneurysms occur in large blood vessels - the aorta (Thoracic Aortic Aneurysm (TAA) and Abdominal Aortic Aneurysm (AAA) and brain vessels (Intracranial Aneurysm (IA)). Despite the presence of significant differences in the pathogenesis of the development and progression of IA and TAA/AAA, there are also similarities. For instance, both have been shown to be strongly influenced by shear stress, inflammatory processes, and enzymatic destruction of the elastic lamellae and extracellular matrix (ECM) proteins of the vascular wall. Moreover, although IA and TAA are predominantly considered arteriopathies with different pathological mechanisms, they share risk factors with AAA, such as hypertension and smoking. However, there is a need for a more in- -depth study of the key elements that may influence the formation and progression of a particular aneurysm to find ways of therapeutic intervention or search for a diagnostic tool. Today, it is known that the disruption of gene expression is one of the main mechanisms that contribute to the development of aneurysms. At the same time, growing evidence suggests that aberrant epigenetic regulation of gene function is strongly related to the genesis of aneurysms. Although much has been studied of the known protein-coding genes, circular RNAs (circRNAs), a relatively new and rapidly evolving large family of transcripts, have recently received much scientific attention. CircRNAs regulate gene expression through the sponging of microRNAs (miRNAs) and can also be used as therapeutic targets and biomarkers. Increasing evidence has implicated circRNAs in the pathogenesis of multiple cardiovascular diseases, including the development of aneurysms. However, the mechanism of dysregulation of certain circRNAs in a particular aneurysm remains to be studied. The discovery of circRNAs has recently advanced our understanding of the latest mode of miRNAs/target genes regulation in the development and progression of IA and TAA/AAA. The aim of this study is to compare the expression profiles of circRNAs to search for similar or different effects of certain circRNAs on the formation and progression of IA and TAA/AAA.

Is lack of goal-conflict-specific rhythmicity a biomarker for treatment resistance in generalised anxiety but not social anxiety or major depression?

BACKGROUND: Anxiety and depression cause major detriment to the patient, family, and society - particularly in treatment-resistant (TR) cases, which are highly prevalent. TR prevalence may be due to current diagnoses being based not on biological measures but on symptom lists that suffer from clinical subjectivity, variation in symptom presentation, and comorbidity. AIMS: Goal-conflict-specific rhythmicity (GCSR) measured using the Stop-Signal Task (SST) may provide the first neural biomarker for an anxiety process and disorder. This GCSR has been validated with selective drugs for anxiety. So, we proposed that GCSR could differ between TR and non-TR individuals and do so differently between those diagnoses normally sensitive to selective anxiolytics and those not. METHODS: We recorded electroencephalograms (EEG) from 20 TR participants (4 GAD, 5 SAD and 11 MDD) and 24 non-TR participants (4 GAD, 5 SAD and 15 Comorbid GAD/MDD (GMD)) while they performed the SST. RESULTS: There was significant positive GCSR in all groups except the GAD-TR group. GAD-TR lacked GCSR in the low-frequency range. However, TR had little effect in SAD or MDD/GMD populations with apparent increases not decreases. CONCLUSIONS: Overall, these results suggest that GAD may occur in two forms: one resulting from excessive GCSR and so being drug sensitive, and the other resulting from some other mechanism and so being TR. In SAD and MDD groups, heightened GCSR could be a consequence rather than the cause, driven by mechanisms that are normally more sensitive to non-selective panicolytic antidepressants.

Multi-Biomarker Profiling for Precision Diagnosis of Lung Cancer.

Multi-biomarker analysis can enhance the accuracy of the single-biomarker analysis by reducing the errors caused by genetic and environmental differences. For this reason, multi-biomarker analysis shows higher accuracy in early and precision diagnosis. However, conventional analysis methods have limitations for multi-biomarker analysis because of their long pre-processing times, inconsistent results, and large sample requirements. To solve these, a fast and accurate precision diagnostic method is introduced for lung cancer by multi-biomarker profiling using a single drop of blood. For this, surface-enhanced Raman spectroscopic immunoassay (SERSIA) is employed for the accurate, quick, and reliable quantification of biomarkers. Then, it is checked the statistical relation of the multi-biomarkers to differentiate between healthy controls and lung cancer patients. This approach has proven effective; with 20 µL of blood serum, lung cancer is diagnosed with 92% accuracy. It also accurately identifies the type and stage of cancer with 87% and 85%, respectively. These results show the importance of multi-biomarker analysis in overcoming the challenges posed by single-biomarker diagnostics. Furthermore, it markedly improves multi-biomarker-based analysis methods, illustrating its important impact on clinical diagnostics.

Prognostic Value of Plasma Immunoglobulin G N-Glycome Traits in Pulmonary Arterial Hypertension.

BACKGROUND: B-type natriuretic peptide or N-terminal pro-B-type natriuretic peptide is the only blood biomarker in established risk calculators for pulmonary arterial hypertension (PAH). Profiling systemic-originated plasma immunoglobulin G (IgG) N-glycans, which reflect different components of the pathophysiology of PAH including immune dysregulation and inflammation, may improve PAH risk assessment. OBJECTIVES: This study sought to identify plasma IgG N-glycan biomarkers that predict survival in PAH to improve risk assessment. METHODS: This cohort study examined 622 PAH patients from 2 national centers (Beijing [discovery] cohort: n = 273; Shanghai [validation] cohort: n = 349). Plasma IgG N-glycomes were profiled by a robust mass spectrometry-based method. Prognostic IgG N-glycan traits were identified and validated in the 2 cohorts using Cox regression and Kaplan-Meier survival analyses. The added value of IgG N-glycan traits to previously established risk models was assessed using Harrell C-indexes and survival analysis. RESULTS: Plasma IgG fucosylation was found to predict survival independent of age and sex in the discovery cohort (HR: 0.377; 95% CI: 0.168-0.845; P = 0.018) with confirmation in the validation cohort (HR: 0.445; 95% CI: 0.264-0.751; P = 0.005). IgG fucosylation remained a robust predictor of mortality in combined cohorts after full adjustment and in subgroup analyses. Integrating IgG fucosylation into previously established risk models improved their predictive capacity, marked by an overall elevation in Harrell C-indexes. IgG fucosylation was useful in further stratifying the intermediate-risk patients classified by a previously established model. CONCLUSIONS: Plasma IgG fucosylation informs PAH prognosis independent of established factors, offering additional value for predicting PAH outcomes.

Repeatability of alkaline inorganic phosphate quantification in the skeletal muscle using 31P-magnetic resonance spectroscopy at 3 T.

The detection of a secondary inorganic phosphate (Pi) resonance, a possible marker of mitochondrial content in vivo, using phosphorus magnetic resonance spectroscopy (31P-MRS), poses technical challenges at 3 Tesla (T). Overcoming these challenges is imperative for the integration of this biomarker into clinical research. To evaluate the repeatability and reliability of measuring resting skeletal muscle alkaline Pi (Pialk) using with 31P-MRS at 3 T. After an initial set of experiments on five subjects to optimize the sequence, resting 31P-MRS of the quadriceps muscles were acquired on two visits (~4 days apart) using an intra-subjects design, from 13 sedentary to moderately active young male and female adults (22 ± 3 years old) within a whole-body 3 T MR system. Measurement variability attributed to changes in coil position, shimming procedure, and spectral analysis were quantified. 31P-MRS data were acquired with a 31P/-proton (1H) dual-tuned surface coil positioned on the quadriceps using a pulse-acquire sequence. Test-retest absolute and relative repeatability was analyzed using the coefficient of variation (CV) and intra-class correlation coefficients (ICC), respectively. After sequence parameter optimization, Pialk demonstrated high intra-subject repeatability (CV: 10.6 ± 5.4%, ICC: 0.80). Proximo-distal change in coil position along the length of the quadriceps introduced Pialk quantitation variability (CV: 28 ± 5%), due to magnetic field inhomogeneity with more distal coil locations. In contrast, Pialk measurement variability due to repeated shims from the same muscle volume (0.40 ± 0.09mM; CV: 6.6%), and automated spectral processing (0.37 ± 0.01mM; CV: 2.3%), was minor. The quantification of Pialk in skeletal muscle via surface coil 31P-MRS at 3 T demonstrated excellent reproducibility. However, caution is advised against placing the coil at the distal part of the quadriceps to mitigate shimming inhomogeneity.

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling.

The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard 'omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell-cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Five miRNAs identified in fucosylated extracellular vesicles as non-invasive diagnostic signatures for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that presents significant challenges for early detection. This study introduces the GlyExo-Capture method for isolating fucosylated extracellular vesicles (Fu-EVs) from serum. We analyze microRNA (miRNA) profiles from Fu-EVs in 88 HCC patients and 179 non-HCC controls using next-generation sequencing (NGS) and identify five miRNAs (hsa-let-7a, hsa-miR-21, hsa-miR-125a, hsa-miR-200a, and hsa-miR-150) as biomarkers for HCC diagnosis. The five-miRNA panel demonstrates exceptional HCC diagnostic performance, with a sensitivity of 0.90 and specificity of 0.92 in a combined cohort of 194 HCC and 412 non-HCC controls, significantly surpassing the performance of alpha-fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP). Notably, the miRNA model achieves recall rates of 85.7% and 90.8% for stage 0 and stage A early-stage HCC, respectively, identifies 88.1% of AFP-negative HCC cases, and effectively differentiates HCC from other cancers. This study provides a high-throughput, rapid, and non-invasive approach for early HCC detection.

[Lipoprotein-associated phospholipase A2 (Lp-PLA2) : relevant biomarker and therapeutic target?] / La phospholipase A2 associée aux lipoprotéines (Lp-PLA2) : biomarqueur pertinent et cible thérapeutique?

Over the last fifteen years, numerous studies have sought to decipher the role of lipoprotein-associated phospholipase A2 (Lp-PLA2) in vascular inflammation-related diseases, notably atherosclerosis. Despite the disappointing results of clinical trials using the Lp-PLA2 inhibitor darapladib, new pathophysiological, epidemiological and genetic data have enabled the development of new inhibitors. Recent studies also show that Lp-PLA2 is involved in vascular inflammation-related diseases other than atherosclerosis (ischemic stroke, Alzheimer's disease and vascular dementia, diabetes, cancers…), and inhibition of Lp-PLA2 could have beneficial therapeutic in these diseases. This review aims to present new data on Lp-PLA2 and to evaluate its current interest as a biomarker but also as a therapeutic target.

Association of Declining Prostate-specific Antigen Levels with Clinical Outcomes in Patients with Metastatic Castration-resistant Prostate Cancer Receiving [177Lu]Lu-PSMA-617 in the Phase 3 VISION Trial.

BACKGROUND AND OBJECTIVE: The prognostic value of declining prostate-specific antigen (PSA) levels is under investigation in patients with prostate-specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer (mCRPC) receiving PSMA-targeted radioligand therapy with [177Lu]Lu-PSMA-617 (177Lu-PSMA-617). This post hoc analysis of the phase 3 VISION trial aimed to evaluate associations between PSA decline and clinical and patient-reported outcomes in patients receiving 177Lu-PSMA-617. METHODS: Of 831 enrolled patients with PSMA-positive progressive mCRPC treated previously with one or more androgen receptor pathway inhibitors and one to two taxanes, 551 were randomised to 177Lu-PSMA-617 plus protocol-permitted standard of care (SoC). Radiographic progression-free survival, overall survival, radiographic objective response rate, and patient-reported health-related quality of life (HRQoL) and pain were analysed in subgroups of patients categorised by the magnitude of unconfirmed PSA decline from baseline. KEY FINDINGS AND LIMITATIONS: Patients randomised to 177Lu-PSMA-617 with the best PSA declines of ≥0-<50% (96/551 [17%]), ≥50-<90% (152/551 [28%]), and ≥90% (83/551 [15%]) up to and including week 12 had 61%, 72%, and 88% reduced risks of radiographic disease progression or death, and 51%, 70%, and 87% reduced risks of death, respectively, versus those with increased PSA levels (160/551 [29%]), based on hazard ratios in a multivariate Cox proportional hazard model. In patients with greater PSA declines, radiographic responses were more frequent and median time to worsening in HRQoL and pain scores were longer. CONCLUSIONS AND CLINICAL IMPLICATIONS: The magnitude of PSA decline was associated with improvement in clinical and patient-reported outcomes in patients with mCRPC receiving 177Lu-PSMA-617 plus SoC in VISION. PSA decline therefore appears to have a prognostic value during 177Lu-PSMA-617 treatment in this population.

The Role of Troponin Testing in Patients with Supraventricular Tachycardia, Systematic Review and Meta-Analysis.

BACKGROUND: Supraventricular tachycardia (SVT) is commonly evaluated in the emergency department (ED). While troponin has been shown to be elevated in SVT, its usefulness for predicting coronary artery disease and future adverse cardiovascular outcomes has not been shown. OBJECTIVES: We aimed to evaluate the prognostic utility of troponin measurement as part of SVT management in the ED. METHODS: We performed a literature search in the PubMed and Scopus databases from inception to August 30, 2023, including all studies reporting troponin measurements in adult patients (age > 18 years) presenting to the ED with supraventricular tachycardia. The primary outcome of interest for this study was the prevalence of elevated troponin in patients with SVT. Secondary outcomes included the prevalence of major adverse cardiac events (MACE) and additional cardiac testing with significant findings. RESULTS: We included 7 studies (500 patients) in our analysis. Six studies reported the number of patients with SVT and elevated troponin, with a pooled prevalence of 46% (95% CI 27-66%, I2 93%). The pooled prevalence of all MACE in our study was 6% (95% CI 1-25%), while the prevalence for MACE among patients with elevated serum troponin levels was 11% (95% CI 4-27%). CONCLUSIONS: Troponin levels are frequently ordered for ED patients with SVT and are often elevated. However, this review suggests that they have low prognostic value in predicting MACE.