TNFα increases the degradation of pyruvate dehydrogenase kinase 4 by the Lon protease to support proinflammatory genes.

The endothelium is a major target of the proinflammatory cytokine, tumor necrosis factor alpha (TNFα). Exposure of endothelial cells (EC) to proinflammatory stimuli leads to an increase in mitochondrial metabolism; however, the function and regulation of elevated mitochondrial metabolism in EC in response to proinflammatory cytokines remain unclear. Studies using high-resolution metabolomics and 13C-glucose and 13C-glutamine labeling flux techniques showed that pyruvate dehydrogenase activity (PDH) and oxidative tricarboxylic acid cycle (TCA) flux are elevated in human umbilical vein ECs in response to overnight (16 h) treatment with TNFα (10 ng/mL). Mechanistic studies indicated that TNFα mediated these metabolic changes via mitochondrial-specific protein degradation of pyruvate dehydrogenase kinase 4 (PDK4, inhibitor of PDH) by the Lon protease via an NF-κB-dependent mechanism. Using RNA sequencing following siRNA-mediated knockdown of the catalytically active subunit of PDH, PDHE1α (PDHA1 gene), we show that PDH flux controls the transcription of approximately one-third of the genes that are up-regulated by TNFα stimulation. Notably, TNFα-induced PDH flux regulates a unique signature of proinflammatory mediators (cytokines and chemokines) but not inducible adhesion molecules. Metabolomics and ChIP sequencing for acetylated modification on lysine 27 of histone 3 (H3K27ac) showed that TNFα-induced PDH flux promotes histone acetylation of specific gene loci via citrate accumulation and ATP-citrate lyase-mediated generation of acetyl CoA. Together, these results uncover a mechanism by which TNFα signaling increases oxidative TCA flux of glucose to support TNFα-induced gene transcription through extramitochondrial acetyl CoA generation and histone acetylation.

A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems.

The differentiation of pluripotent stem cells (PSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variabilities, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, PSC-to-cardiomyocyte (CM) differentiation is vulnerable to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), PSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial PSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor that can further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize PSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications.

An Accurate and Individualized Preoperative Estimation Method for the Linear Insertion Depth of Cochlear Implant Electrode Arrays Based on Computed Tomography.

OBJECTIVES: Cochlear implantation or auditory brainstem implantation is currently the only accepted method for improving severe or profound sensorineural hearing loss. The length of the electrodes implanted during cochlear implantation is closely related to the degree of hearing improvement of hearing after the surgery. We aimed to explore new methods to accurately estimate the electrode array (EA) linear insertion depth based on computed tomography (CT) images prior surgery, which could help surgeons select the appropriate EA length for each patient. DESIGN: Previous studies estimated the linear insertion depth by measuring the length of the lateral wall of the cochlea rather than the electrode's path in the cochlea duct. Here, we determined the actual position of the EA on the CT image after cochlear surgery in order to predict the path of the EA, and the length of the predicted EA path was measured by the contouring technique (CoT) to estimate the linear insertion depth of the EA. Because CoT can only measure the length of the estimated EA path on a two-dimensional plane, we further modified the measurement by weighting the height of the cochlea and the length of the EA tail (the length of the last stimulating electrode to the end, which cannot be displayed on the CT image), which we termed the modified CoT + height + tail (MCHT) measurement. RESULTS: Based on our established method, MCHT could reduce the error to the submillimeter range (0.67 ± 0.37 mm) when estimating the linear insertion depth of various kinds of EAs compared with the actual implant length. The correlation coefficient between the linear insertion depth as predicted by MCHT and the actual was 0.958. The linear insertion depth estimated by this method was more accurate than that estimated using the classical CoT technique ( R = 0.442) and using the modified Escudé's method ( R = 0.585). CONCLUSIONS: MCHT is a method based on CT images that can accurately predict the linear insertion depth of cochlear implants preoperatively. This is the first report that we are aware of a method for predicting linear insertion depth before cochlear implantation with only submillimeter errors and that is tailored to different types of EAs.

Development and validation of a cost-effective virtual reality educational tool to reduce anxiety and improve set-up accuracy in radiotherapy patients.

PURPOSE: This study proposes a cost-effective method for educating radiotherapy patients through an immersive virtual reality (VR) system. METHODS: The VR educational tool comprises VR glasses, a handheld controller, the scientific knowledge of radiotherapy, radiotherapy demonstration, and an audio introduction. To verify its efficacy, 120 radiotherapy patients with tumors were prospectively enrolled and divided into the control group or VR intervention group. After the first treatment, set-up errors, including three translation errors and three rotation errors, were recorded in six directions. In addition, participants were required to complete a questionnaire before radiotherapy to assess anxiety and understanding degrees. The questionnaire was scored using a five-point Likert Scale. Finally, Spearman's rank correlation test was used to evaluate set-up errors and questionnaire scores. RESULTS: The set-up errors are significantly reduced in AP, SI, total translation, Roll and total rotation in the intervention group compared with the control group (p < 0.05). The scores are higher in the intervention group than in the control group in question 1 (2.1 ± 0.58 vs. 3.3 ± 0.55), question 2 (1.3 ± 0.44 vs. 2.5 ± 0.65), question 4 (2.2 ± 0.65 vs. 3.2 ± 0.82), question 5 (1.8 ± 0.59 vs. 3.1 ± 0.79), and all subscales (5.5 ± 1.2 vs. 8.9 ± 1.3 and 6.4 ± 1.3 vs. 9.2 ± 1.5). The scores of high, moderate, and low correlation are 47 (74%), 15 (23%), and 2 (3%) for the control group and 44 (69%), 17 (26%), and 3 (5%) for the intervention group, respectively. CONCLUSION: The VR educational tool can significantly improve comprehension and reduce anxiety. There is a strong correlation between set-up errors and questionnaire scores. The VR educational tool may help reduce set-up errors for radiotherapy patients.

UCP2-dependent redox sensing in POMC neurons regulates feeding.

Paradoxically, glucose, the primary driver of satiety, activates a small population of anorexigenic pro-opiomelanocortin (POMC) neurons. Here, we show that lactate levels in the circulation and in the cerebrospinal fluid are elevated in the fed state and the addition of lactate to glucose activates the majority of POMC neurons while increasing cytosolic NADH generation, mitochondrial respiration, and extracellular pyruvate levels. Inhibition of lactate dehydrogenases diminishes mitochondrial respiration, NADH production, and POMC neuronal activity. However, inhibition of the mitochondrial pyruvate carrier has no effect. POMC-specific downregulation of Ucp2 (Ucp2PomcKO), a molecule regulated by fatty acid metabolism and shown to play a role as transporter in the malate-aspartate shuttle, abolishes lactate- and glucose-sensing of POMC neurons. Ucp2PomcKO mice have impaired glucose metabolism and are prone to obesity on a high-fat diet. Altogether, our data show that lactate through redox signaling and blocking mitochondrial glucose utilization activates POMC neurons to regulate feeding and glucose metabolism.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action.

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

CIEGAN: A Deep Learning Tool for Cell Image Enhancement.

Long-term live-cell imaging technology has emerged in the study of cell culture and development, and it is expected to elucidate the differentiation or reprogramming morphology of cells and the dynamic process of interaction between cells. There are some advantages to this technique: it is noninvasive, high-throughput, low-cost, and it can help researchers explore phenomena that are otherwise difficult to observe. Many challenges arise in the real-time process, for example, low-quality micrographs are often obtained due to unavoidable human factors or technical factors in the long-term experimental period. Moreover, some core dynamics in the developmental process are rare and fleeting in imaging observation and difficult to recapture again. Therefore, this study proposes a deep learning method for microscope cell image enhancement to reconstruct sharp images. We combine generative adversarial nets and various loss functions to make blurry images sharp again, which is much more convenient for researchers to carry out further analysis. This technology can not only make up the blurry images of critical moments of the development process through image enhancement but also allows long-term live-cell imaging to find a balance between imaging speed and image quality. Furthermore, the scalability of this technology makes the methods perform well in fluorescence image enhancement. Finally, the method is tested in long-term live-cell imaging of human-induced pluripotent stem cell-derived cardiomyocyte differentiation experiments, and it can greatly improve the image space resolution ratio.

Anisomycin inhibits angiogenesis, growth, and survival of triple-negative breast cancer through mitochondrial dysfunction, AMPK activation, and mTOR inhibition.

Aberrant upregulation of mitochondrial biogenesis is observed in breast cancer and holds potential therapeutic option. In our work, we showed that inhibition of mitochondrial function by anisomycin is effective against triple-negative breast cancer (TNBC). Anisomycin inhibits growth and induces caspase-dependent apoptosis in a panel of TNBC cell lines. Of note, anisomycin at a tolerable dose remarkably suppresses growth of TNBC in mice. In addition, anisomycin effectively targets breast cancer angiogenesis through inhibiting capillary network formation, migration, proliferation, and survival. Mechanistic studies show that although anisomycin activates p38 and JNK, their activations are not required for anisomycin's action. In contrast, anisomycin inhibits mitochondrial respiration, and decreases mitochondrial membrane potential and adenosine triphosphate (ATP) level. The inhibitory effect of anisomycin is significantly reversed in mitochondria respiration-deficient ρ0 cells. As a consequence, anisomycin activates AMPK and inhibits mammalian target-of-rapamycin signaling pathways. Our work demonstrated that anisomycin is a useful addition to the treatment armamentarium for TNBC.

Memory-like response in platelet attenuates platelet hyperactivation in arterial thrombosis.

Recent studies showed that in responding of pathogens stimulation, immune cells and other cells display memory-like effects. Platelets are primary effectors of hemostasis and thrombosis which also participate in immune responses. However, there is no relevant research on whether memory-like effect exists in platelets. In our study after recovery from repetitive LPS stimulus, platelets aggregation, diffusion and clot retraction exhibit a significant reduction. It proves that memory-like response could be aroused in platelets. Furthermore, in the mouse arterial thrombosis model, LPS pretreated platelets showed lower integrin activation, shorter thrombus length and longer occlusion time, indicating that the memory-like response of platelet could alleviate arterial thrombosis. Moreover, memory-like response of platelets was also found to be related to PI3K/AKT signaling pathway. The decreased mitochondrial DNA methylation reveal that platelet memory-like responses may be produced from epigenetic reprogramming. Our research proves for the first time that memory-like response in platelets protects mice from arterial thrombosis, extends the understanding of trained memory.

Reduced DMPC and PMPC in lung surfactant promote SARS-CoV-2 infection in obesity.

OBJECTIVE: Obesity is an established risk factor for higher SARS-CoV-2 viral loads, severe COVID-19 pneumonia requiring hospitalization, and worse outcomes. However, the underlying mechanisms for the increased risk are not well understood. SARS-CoV-2 is a respiratory virus with the primary route of entry through the lungs, where the Spike protein of SARS-CoV-2 binds to the ACE2 receptor on pneumocytes. Lung surfactant produced by type II pneumocytes plays a major role in respiratory defense against infections. Surfactant predominantly contains lipids, especially phosphatidylcholines (PC), and obesity is characterized by aberrant lipid metabolism. We hypothesized that altered lipid composition in lung surfactant in obesity may promote SARS-CoV-2 infection, leading to severe COVID-19 disease. METHODS: Lipidomic analysis of lung tissue and bronchoalveolar lavage fluid (BALF) was performed using LC-MS/MS. The effects of PCs on SARS-CoV-2 pseudovirus infection were studied in HEK293T cells with ACE2 overexpression and in Vero-E6 cells with endogenous ACE2 expression. For the cell-cell fusion assay, HEK293T-ACE2 and HEK293T expressing SARS-CoV-2 Spike/eGFP were used as the target and effector cells, respectively. RESULTS: Lipidomic analysis revealed that myristic acid-containing dimyristoyl-PC (DMPC) and palmitoylmyristoyl-PC (PMPC) were reduced in lung tissue and BALF from high fat diet-induced obese mice. DMPC and PMPC markedly inhibited wild type and D614G mutant SARS-CoV-2 infection in HEK293T-ACE2 and Vero-E6 cells. Feeding obese mice with trimyristin, the triglycerides of myristic acid, increased DMPC and PMPC levels in lung surfactant. Lipid extract from BALF of trimyristin-treated obese mice mitigated the elevated wild type and D614G mutant SARS-CoV-2 infection. The inhibitory effects of DMPC and PMPC on SARS-CoV-2 infection were reversed by cholesterol. CONCLUSIONS: The reduced DMPC and PMPC in lung surfactant may promote SARS-CoV-2 infection. Increasing DMPC and PMPC in lung surfactant could be an innovative strategy for preventing and treating severe COVID-19 disease in obesity.

Piezo1 initiates platelet hyperreactivity and accelerates thrombosis in hypertension.

BACKGROUND: Thrombosis is the pathological basis of cardiovascular and cerebrovascular diseases, which seriously threaten human life and health. Among them, nearly half of cardiovascular disease patients suffer from severe hypertension complications. Hypertension is thought to cause abnormal platelet activation and increases the risk of thrombosis, but the related mechanism is still vague. OBJECTIVES: This study hypothesized that the abnormal hemodynamics of blood under hypertension might affect platelet function and accelerate thrombosis by activating mechanoreceptor Piezo1. METHODS: To assess the activation effect of hypertension on mechanoreceptor Piezo1, we injected Piezo1 agonist Yoda1 and antagonist GsMTx-4 through the tail vein, then examined the platelet activation status and thrombosis. RESULTS: Our results displayed that antagonist GsMTx-4 effectively inhibited calcium influx caused by hypertension and agonist Yoda1. Antithrombotic studies proved that the inhibition of Piezo1 effectively inhibited arterial thrombosis and reduced the infarct size of stroke in hypertensive mice. CONCLUSIONS: Our study explains the activation of mechanoreceptor Piezo1 under hypertension is the key to abnormal platelet activation and thrombosis while providing novel platelet intervention strategies to prevent thrombosis.

Anterograde regulation of mitochondrial genes and FGF21 signaling by hepatic LSD1.

Mitochondrial biogenesis and function are controlled by anterograde regulatory pathways involving more than 1000 nuclear-encoded proteins. Transcriptional networks controlling the nuclear-encoded mitochondrial genes remain to be fully elucidated. Here, we show that histone demethylase LSD1 KO from adult mouse liver (LSD1-LKO) reduces the expression of one-third of all nuclear-encoded mitochondrial genes and decreases mitochondrial biogenesis and function. LSD1-modulated histone methylation epigenetically regulates nuclear-encoded mitochondrial genes. Furthermore, LSD1 regulates gene expression and protein methylation of nicotinamide mononucleotide adenylyltransferase 1 (NMNAT1), which controls the final step of NAD+ synthesis and limits NAD+ availability in the nucleus. Lsd1 KO reduces NAD+-dependent SIRT1 and SIRT7 deacetylase activity, leading to hyperacetylation and hypofunctioning of GABPß and PGC-1α, the major transcriptional factor/cofactor for nuclear-encoded mitochondrial genes. Despite the reduced mitochondrial function in the liver, LSD1-LKO mice are protected from diet-induced hepatic steatosis and glucose intolerance, partially due to induction of hepatokine FGF21. Thus, LSD1 orchestrates a core regulatory network involving epigenetic modifications and NAD+ synthesis to control mitochondrial function and hepatokine production.

Sall4 and Myocd Empower Direct Cardiac Reprogramming From Adult Cardiac Fibroblasts After Injury.

Direct conversion of fibroblasts into induced cardiomyocytes (iCMs) holds promising potential to generate functional cardiomyocytes for drug development and clinical applications, especially for direct in situ heart regeneration by delivery of reprogramming genes into adult cardiac fibroblasts in injured hearts. For a decade, many cocktails of transcription factors have been developed to generate iCMs from fibroblasts of different tissues in vitro and some were applied in vivo. Here, we aimed to develop genetic cocktails that induce cardiac reprogramming directly in cultured cardiac fibroblasts isolated from adult mice with myocardial infarction (MICFs), which could be more relevant to heart diseases. We found that the widely used genetic cocktail, Gata4, Mef2c, and Tbx5 (GMT) were inefficient in reprogramming cardiomyocytes from MICFs. In a whole well of a 12-well plate, less than 10 mCherry+ cells (<0.1%) were observed after 2 weeks of GMT infection with Myh6-reporter transgenic MICFs. By screening 22 candidate transcription factors predicted through analyzing the gene regulatory network of cardiac development, we found that five factors, GMTMS (GMT plus Myocd and Sall4), induced more iCMs expressing the cardiac structural proteins cTnT and cTnI at a frequency of about 22.5 ± 2.7% of the transduced MICFs at day 21 post infection. What is more, GMTMS induced abundant beating cardiomyocytes at day 28 post infection. Specifically, Myocd contributed mainly to inducing the expression of cardiac proteins, while Sall4 accounted for the induction of functional properties, such as contractility. RNA-seq analysis of the iCMs at day 28 post infection revealed that they were reprogrammed to adopt a cardiomyocyte-like gene expression profile. Overall, we show here that Sall4 and Myocd play important roles in cardiac reprogramming from MICFs, providing a cocktail of genetic factors that have potential for further applications in in vivo cardiac reprogramming.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks.

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS1 readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS1 with its long acquisition time, while acquiring MS2 data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS1/data-independent(DI)-HR-MS2 method to trace the fate of 13C atoms from [13C6]-glucose ([13C6]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously 13C/15N atoms from [13C5,15N2]-glutamine ([13C5,15N2]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS1 while simultaneously acquiring substructure label information via DI-MS2. These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

Inosine is an alternative carbon source for CD8+-T-cell function under glucose restriction.

T cells undergo metabolic rewiring to meet their bioenergetic, biosynthetic and redox demands following antigen stimulation. To fulfil these needs, effector T cells must adapt to fluctuations in environmental nutrient levels at sites of infection and inflammation. Here, we show that effector T cells can utilize inosine, as an alternative substrate, to support cell growth and function in the absence of glucose in vitro. T cells metabolize inosine into hypoxanthine and phosphorylated ribose by purine nucleoside phosphorylase. We demonstrate that the ribose subunit of inosine can enter into central metabolic pathways to provide ATP and biosynthetic precursors, and that cancer cells display diverse capacities to utilize inosine as a carbon source. Moreover, the supplementation with inosine enhances the anti-tumour efficacy of immune checkpoint blockade and adoptive T-cell transfer in solid tumours that are defective in metabolizing inosine, reflecting the capability of inosine to relieve tumour-imposed metabolic restrictions on T cells.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks.

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium.

Juvenile neuronal ceroid lipofuscinosis (JNCL, aka. juvenile Batten disease or CLN3 disease) is a lysosomal storage disease characterized by progressive blindness, seizures, cognitive and motor failures, and premature death. JNCL is caused by mutations in the Ceroid Lipofuscinosis, Neuronal 3 (CLN3) gene, whose function is unclear. Although traditionally considered a neurodegenerative disease, CLN3 disease displays eye-specific effects: Vision loss not only is often one of the earliest symptoms of JNCL, but also has been reported in non-syndromic CLN3 disease. Here we described the roles of CLN3 protein in maintaining healthy retinal pigment epithelium (RPE) and normal vision. Using electroretinogram, fundoscopy and microscopy, we showed impaired visual function, retinal autofluorescent lesions, and RPE disintegration and metaplasia/hyperplasia in a Cln3 ~ 1 kb-deletion mouse model [1] on C57BL/6J background. Utilizing a combination of biochemical analyses, RNA-Seq, Seahorse XF bioenergetic analysis, and Stable Isotope Resolved Metabolomics (SIRM), we further demonstrated that loss of CLN3 increased autophagic flux, suppressed mTORC1 and Akt activities, enhanced AMPK activity, and up-regulated gene expression of the autophagy-lysosomal system in RPE-1 cells, suggesting autophagy induction. This CLN3 deficiency induced autophagy induction coincided with decreased mitochondrial oxygen consumption, glycolysis, the tricarboxylic acid (TCA) cycle, and ATP production. We also reported for the first time that loss of CLN3 led to glycogen accumulation despite of impaired glycogen synthesis. Our comprehensive analyses shed light on how loss of CLN3 affect autophagy and metabolism. This work suggests possible links among metabolic impairment, autophagy induction and lysosomal storage, as well as between RPE atrophy/degeneration and vision loss in JNCL.

Utility of urinary ctDNA to monitoring minimal residual disease in early breast cancer patients.

BACKGROUND: Cancer recurrence for patients with early breast cancer is significant. Patients will benefit from more non-invasive modes of monitoring and we aim to study the feasibility of urinary circulating tumor DNA (ctDNA) to monitor for residual disease (MRD). METHODS: In this longitudinal study, 300 early breast cancer patients were recruited prospectively. Measurements were taken prior to treatment and at different time points thereafter for a total of 8 measurements. Comparisons were made with healthy volunteers and patients without detectable mutations in urine specimens. Disease free relapse were correlated to both urinary DNA quantity and ctDNA concentration. RESULTS: Baseline index measurements showed 38% of patients with detectable mutations. The concordance with biopsy tissues was 97.3%. Overall, breast cancer patients had higher urinary DNA compared with healthy volunteers. Over time, fluctuations in urinary DNA was negligible in healthy volunteers, indicating the stability of the marker. Among the patients with detectable mutations, we observed that higher urinary DNA quantity measurements at 6-month and patients with positive mutations were associated with greater risk of relapse. Hazard ratios for patients in this category was 1.65 (95% CI 1.26-2.16) and 1.98 (95% CI 1.48-2.63) respectively. CONCLUSION: Urinary DNA offers non-invasive probing and real-time monitoring of breast cancer relapse. Our results demonstrated clear clinical relevance in breast cancer and significant risk profiling of early breast cancer patients. This potentially aids to complement current cancer relapse monitoring and may help in early intervention.