Machine Learning-based Nomograms for Predicting Clinical Stages of Initial Prostate Cancer: A Multicenter Retrospective Study.

OBJECTIVE: To construct and externally validate machine learning-based nomograms for predicting progression stages of initial prostate cancer (PCa) using biomarkers and clinicopathologic features. METHODS: Three hundred sixty-two inpatients diagnosed with PCa at the First Affiliated Hospital were randomly assigned to training and testing sets in a 3:7 ratio, while 136 PCa patients from People's Hospital formed the external validation set. Imaging and clinicopathologic information were collected. Optimal features distinguishing advanced prostate cancer (APC) and metastatic PCa (mPCa) were identified through logistic regression (LR). ML algorithms were employed to build and compare ML models. The best-performing algorithm established models for PCa progression stage. Models performance was evaluated using metrics, ROC curves, calibration, and decision curve analysis (DCA) in training, testing, and external validation sets. RESULTS: Following LR analyses, PSA (P = .001), maximum tumor diameter (P = .026), Gleason score (P <.001), and RNF41 (P <.001) were optimal features for predicting APC, while ALP (P <.001), PSA (P <.001), and GS score (P = .024) were for mPCa. Among ML models, the LR models exhibited superior performance. Consequently, the LR algorithm was used for the APC-risk-nomogram and mPCa-risk-nomogram construction, with AUC values of 0.848, 0.814, 0.810, and 0.940, 0.913, 0.910, in the training, testing, and external validation sets, respectively. Calibration and DCA curves affirmed nomograms' consistency and net benefits for clinical decision-making. CONCLUSION: In summary, ML-based APC-risk-nomogram and mPCa-risk-nomogram exhibit outstanding predictive performance for PCa progression stages. These nomograms can assist clinicians in finely categorizing newly diagnosed PCa patients, facilitating personalized treatment plans and prognosis assessment.

Rapid phagosome isolation enables unbiased multiomic analysis of human microglial phagosomes.

Microglia are the resident macrophages of the central nervous system (CNS). Their phagocytic activity is central during brain development and homeostasis-and in a plethora of brain pathologies. However, little is known about the composition, dynamics, and function of human microglial phagosomes under homeostatic and pathological conditions. Here, we developed a method for rapid isolation of pure and intact phagosomes from human pluripotent stem cell-derived microglia under various in vitro conditions, and from human brain biopsies, for unbiased multiomic analysis. Phagosome profiling revealed that microglial phagosomes were equipped to sense minute changes in their environment and were highly dynamic. We detected proteins involved in synapse homeostasis, or implicated in brain pathologies, and identified the phagosome as the site where quinolinic acid was stored and metabolized for de novo nicotinamide adenine dinucleotide (NAD+) generation in the cytoplasm. Our findings highlight the central role of phagosomes in microglial functioning in the healthy and diseased brain.

Machine learning-based CT radiomics enhances bladder cancer staging predictions: A comparative study of clinical, radiomics, and combined models.

BACKGROUND: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, especially machine learning-based computed tomography (CT) image-based radiomics, hold promise in improving stage prediction accuracy in various tumors. However, the comparative performance and clinical utility of models for BLCA are under investigation. PURPOSE: We aimed to investigate the application value of machine learning-based CT radiomics in preoperative staging prediction by comparing the performance of clinical, radiomics, and clinical-radiomics combined models. METHODS: A retrospective cohort of 105 patients with initial BLCA was randomized into training (70%) and testing (30%) cohorts. Radiomics features were extracted from CT images using the optimal feature filter, followed by the application of the least absolute shrinkage and selection operator algorithm for optimum feature selection. Furthermore, machine learning algorithms were used to establish a radiomics model within the training cohort. Independent risk factors for muscle-invasive BLCA (MIBC) obtained by multivariate logistic regression (LR) analysis were separately used to construct a clinical model. For a clinical-radiomics fusion model, radiomics features were combined with clinical parameters. Performance was evaluated based on receiver operating characteristic curves, calibration curves, decision curve analysis (DCA), and standard performance metrics. RESULTS: Patients exhibited a significantly higher age (p = 0.029), larger tumor size (p = 0.01), and an increased neutrophil-to-lymphocyte ratio (NLR; p = 0.045) in the MIBC group than in the NMIBC group. LR analysis revealed age (p = 0.026), tumor size (p = 0.007), and NLR (p = 0.019) as significant predictors for constructing the clinical model. In the testing cohort, the radiomics model, which used an Support Vector Machine classifier, achieved the highest area under the curve (AUC) value of 0.857. The clinical-radiomics model outperformed the remaining two models, with AUC values of 0.958 and 0.893 in the training and testing cohorts, respectively. DeLong's test indicated significant differences between the three models. Calibration curves showed good agreement, and DCA confirmed the superior clinical utility of the clinical-radiomics model. CONCLUSIONS: Machine learning-based CT radiomics combined with clinical parameters was a promising approach in staging BLCA accurately, which outperformed the individual models. Integrating radiomics features with clinical information holds the potential to improve personalized treatment planning and patient outcomes in BLCA.

Preoperative prediction of histopathological grading in patients with chondrosarcoma using MRI-based radiomics with semantic features.

BACKGROUND: Distinguishing high-grade from low-grade chondrosarcoma is extremely vital not only for guiding the development of personalized surgical treatment but also for predicting the prognosis of patients. We aimed to establish and validate a magnetic resonance imaging (MRI)-based nomogram for predicting preoperative grading in patients with chondrosarcoma. METHODS: Approximately 114 patients (60 and 54 cases with high-grade and low-grade chondrosarcoma, respectively) were recruited for this retrospective study. All patients were treated via surgery and histopathologically proven, and they were randomly divided into training (n = 80) and validation (n = 34) sets at a ratio of 7:3. Next, radiomics features were extracted from two sequences using the least absolute shrinkage and selection operator (LASSO) algorithms. The rad-scores were calculated and then subjected to logistic regression to develop a radiomics model. A nomogram combining independent predictive semantic features with radiomic by using multivariate logistic regression was established. The performance of each model was assessed by the receiver operating characteristic (ROC) curve analysis and the area under the curve, while clinical efficacy was evaluated via decision curve analysis (DCA). RESULTS: Ultimately, six optimal radiomics signatures were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging with fat suppression (T2WI-FS) sequences to develop the radiomics model. Tumour cartilage abundance, which emerged as an independent predictor, was significantly related to chondrosarcoma grading (p < 0.05). The AUC values of the radiomics model were 0.85 (95% CI, 0.76 to 0.95) in the training sets, and the corresponding AUC values in the validation sets were 0.82 (95% CI, 0.65 to 0.98), which were far superior to the clinical model AUC values of 0.68 (95% CI, 0.58 to 0.79) in the training sets and 0.72 (95% CI, 0.57 to 0.87) in the validation sets. The nomogram demonstrated good performance in the preoperative distinction of chondrosarcoma. The DCA analysis revealed that the nomogram model had a markedly higher clinical usefulness in predicting chondrosarcoma grading preoperatively than either the rad-score or clinical model alone. CONCLUSION: The nomogram based on MRI radiomics combined with optimal independent factors had better performance for the preoperative differentiation between low-grade and high-grade chondrosarcoma and has potential as a noninvasive preoperative tool for personalizing clinical plans.

High Tibial Osteotomy With Medial Meniscal Posterior Root Tear Reconstruction Yields Improved Radiographic and Functional Outcomes and Healing Rates Compared With Osteotomy Alone.

PURPOSE: To compare preoperative and postoperative clinical and radiologic outcomes between patients undergoing high tibial osteotomy (HTO) with medial meniscal posterior root tear (MMPRT) reconstruction using gracilis tendon graft and those undergoing HTO without MMPRT reconstruction. METHODS: Patients with MMPRTs who underwent HTO between January 2018 and December 2021 with minimum 2-year follow-up were included. All patients were divided into 2 groups based on whether they underwent meniscal root reconstruction with tendon graft: HTO alone (33 cases) and HTO with MMPRT reconstruction (21 cases). Clinical evaluation included the Lysholm score, International Knee Documentation Committee (IKDC) score, and visual analog scale (VAS) score. Functional recovery and radiologic outcomes of the knees were evaluated at the latest follow-up. Meniscal root healing rates and medial meniscal extrusion according to a second magnetic resonance imaging reading were compared between the 2 groups at the latest follow-up. RESULTS: The results showed statistically significant improvements in the postoperative Lysholm score, IKDC score, and VAS score in both groups at the latest follow-up (P < .001). Analysis of the minimal clinically important difference for postoperative outcomes revealed that the percentage of patients who reached the minimal clinically important difference threshold was 100% for the Lysholm score, 100% for the IKDC score, and 100% for the VAS score in the HTO-MMPRT reconstruction group. In comparison, the percentages were 87.9% for the Lysholm score, 90.9% for the IKDC score, and 100% for the VAS score in the HTO-alone group. Additionally, compared with the HTO-alone group, the HTO-MMPRT reconstruction group using gracilis tendon graft showed significantly improved meniscal root healing rates (complete healing, 85.7% vs 45.4% [95% confidence interval, 0.003-0.007]; P = .001) and functional recovery (P < .005) at the final follow-up. Additionally, the HTO-MMPRT reconstruction group showed significantly more improvement in the Kellgren-Lawrence grade (10 of 21 knees vs 6 of 33 knees with improved Kellgren-Lawrence grade, P = .033) and medial meniscal extrusion (2.1 ± 1.0 mm vs 3.1 ± 1.6 mm [95% confidence interval, 0.3-1.7 mm]; P = .007) compared with the HTO-alone group. CONCLUSIONS: HTO with reconstruction of the meniscal root using a tendon graft resulted in improved radiographic and patient-reported outcomes, as well as improved healing rates, compared with HTO alone. LEVEL OF EVIDENCE: Level III, retrospective case-series comparison.

MFSD1 with its accessory subunit GLMP functions as a general dipeptide uniporter in lysosomes.

The lysosomal degradation of macromolecules produces diverse small metabolites exported by specific transporters for reuse in biosynthetic pathways. Here we deorphanized the major facilitator superfamily domain containing 1 (MFSD1) protein, which forms a tight complex with the glycosylated lysosomal membrane protein (GLMP) in the lysosomal membrane. Untargeted metabolomics analysis of MFSD1-deficient mouse lysosomes revealed an increase in cationic dipeptides. Purified MFSD1 selectively bound diverse dipeptides, while electrophysiological, isotope tracer and fluorescence-based studies in Xenopus oocytes and proteoliposomes showed that MFSD1-GLMP acts as a uniporter for cationic, neutral and anionic dipeptides. Cryoelectron microscopy structure of the dipeptide-bound MFSD1-GLMP complex in outward-open conformation characterized the heterodimer interface and, in combination with molecular dynamics simulations, provided a structural basis for its selectivity towards diverse dipeptides. Together, our data identify MFSD1 as a general lysosomal dipeptide uniporter, providing an alternative route to recycle lysosomal proteolysis products when lysosomal amino acid exporters are overloaded.

NADPH composite index analysis quantifies the relationship between compartmentalized NADPH dynamics and growth rates in cancer cells.

NADPH, a highly compartmentalized electron donor in mammalian cells, plays essential roles in cell metabolism. However, little is known about how cytosolic and mitochondrial NADPH dynamics relate to cancer cell growth rates in response to varying nutrient conditions. To address this issue, we present NADPH composite index analysis, which quantifies the relationship between compartmentalized NADPH dynamics and growth rates using genetically encoded NADPH sensors, automated image analysis pipeline, and correlation analysis. Through this analysis, we demonstrated that compartmentalized NADPH dynamics patterns were cancer cell-type dependent. Specifically, cytosolic and mitochondrial NADPH dynamics of MDA-MB-231 decreased in response to serine deprivation, while those of HCT-116 increased in response to serine or glutamine deprivation. Furthermore, by introducing a fractional contribution parameter, we correlated cytosolic and mitochondrial NADPH dynamics to growth rates. Using this parameter, we identified cancer cell lines whose growth rates were selectively inhibited by targeting cytosolic or mitochondrial NADPH metabolism. Mechanistically, we identified citrate transporter as a key mitochondrial transporter that maintains compartmentalized NADPH dynamics and growth rates. Altogether, our results present a significant advance in quantifying the relationship between compartmentalized NADPH dynamics and cancer cell growth rates, highlighting a potential of targeting compartmentalized NADPH metabolism for selective cancer cell growth inhibitions.

METTL3 inhibits BMSC apoptosis and facilitates osteonecrosis repair via an m6A-IGF2BP2-dependent mechanism.

Hypoxia-induced apoptosis of bone marrow mesenchymal stem cells (BMSCs) limits the efficacy of their transplantation for steroid-induced osteonecrosis of the femoral head (SONFH). As apoptosis and RNA methylation are closely related, exploring the role and mechanism of RNA methylation in hypoxic apoptosis of BMSCs is expected to identify new targets for transplantation of BMSCs for SONFH and enhance transplantation efficacy. We performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) combined with RNA-seq on a hypoxia-induced apoptosis BMSC model and found that the RNA methyltransferase-like 3 (METTL3) is involved in hypoxia-induced BMSC apoptosis. The expression of METTL3 was downregulated in BMSCs after hypoxia and in BMSCs implanted in osteonecrosis areas. Knockdown of METLL3 under normoxic conditions promoted apoptosis of BMSCs. In contrast, overexpression of METTL3 promoted the survival of BMSCs under hypoxic conditions, and overexpression of METTL3 promoted the survival of BMSCs in the osteonecrosis area and the repair of the osteonecrosis area. Regarding the mechanism, the m6A levels of the mRNAs of anti-apoptotic genes Bcl-2, Mcl-1, and BIRC5 were significantly increased upon the overexpression of METTL3 under hypoxic conditions, which promoted the binding of Bcl-2, Mcl-1, and BIRC5 mRNAs to IGF2BP2, enhanced the mRNA stability, and increased the protein expression of the three anti-apoptotic genes. In conclusion, overexpression of METTL3 promoted m6A modification of mRNAs of Bcl-2, Mcl-1, and BIRC5, promoted the binding of IGF2BP2 to the above-mentioned mRNAs, enhanced mRNA stability, inhibited hypoxia-induced BMSC apoptosis, and promoted repair of SONFH, thereby providing novel targets for transplantation of BMSCs for SONFH.

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy.

The nonphysiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels affect therapeutic response by performing drug screening in human plasma-like medium. We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that recently failed in phase III clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism end product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. These results demonstrate the broad and dramatic effects nutrient levels can have on drug response and how incorporation of human-specific physiological nutrient medium might help identify compounds whose efficacy could be influenced in humans.

Route planning of mobile robot based on improved RRT star and TEB algorithm.

This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot.

Cystatin C Attenuates Perihematomal Secondary Brain Injury by Inhibiting the Cathepsin B/NLRP3 Signaling Pathway in a Rat Model of Intracerebral Hemorrhage.

Secondary brain injury (SBI) is a noticeable contributor to the high mortality and morbidity rates associated with intracerebral hemorrhage (ICH), and effective treatment options remain limited. Cystatin C (CysC) emerges as a novel candidate for SBI intervention. The therapeutic effects and underlying mechanisms of CysC in mitigating SBI following ICH were explored in the current research. An in vivo ICH rat model was established by injecting autologous blood into the right caudate nucleus. Western blotting (WB) was utilized to assess the levels of CysC, cathepsin B (CTSB), and the NLRP3 inflammasome. Subsequently, the ICH rat model was treated with exogenous CysC supplementation or CysC knockdown plasmids. Various parameters, including Evans blue (EB) extravasation, brain water content, and neurological function in rats, were examined. RT-qPCR and WB were employed to determine the expression levels of CTSB and the NLRP3 inflammasome. The co-expression of CTSB, CysC, and NLRP3 inflammasome with GFAP, NeuN, and Iba1 was assessed through double-labeled immunofluorescence. The interaction between CysC and CTSB was investigated using double-labeled immunofluorescence and co-immunoprecipitation. The findings revealed an elevation of CysC expression level, particularly at 24 h after ICH. Exogenous CysC supplementation alleviated severe brain edema, neurological deficit scores, and EB extravasation induced by ICH. Conversely, CysC knockdown produced opposite effects. The expression levels of CTSB and the NLRP3 inflammasome were significantly risen following ICH, and exogenous CysC supplement attenuated their expression levels. Double-labeled immunofluorescence illustrated that CysC, CTSB, and the NLRP3 inflammasome were predominantly expressed in microglial cells, and the interaction between CysC and CTSB was evidenced. CysC exhibited potential in ameliorating SBI following ICH via effectively suppressing the activation of the NLRP3 inflammasome mediated by CTSB specifically in microglial cells. These findings underscore the prospective therapeutic efficacy of CysC in the treatment of ICH-induced complications.

A self-amplifying loop of TP53INP1 and P53 drives oxidative stress-induced apoptosis of bone marrow mesenchymal stem cells.

Bone marrow mesenchymal stem cell (BMSC) transplantation is a promising regenerative therapy; however, the survival rate of BMSCs after transplantation is low. Oxidative stress is one of the main reasons for the high apoptosis rate of BMSCs after transplantation, so there is an urgent need to explore the mechanism of oxidative stress-induced apoptosis of BMSCs. Our previous transcriptome sequencing results suggested that the expression of P53-induced nuclear protein 1 (TP53INP1) and the tumor suppressor P53 (P53) was significantly upregulated during the process of oxidative stress-induced apoptosis of BMSCs. The present study further revealed the role and mechanism of TP53INP1 and P53 in oxidative stress-induced apoptosis in BMSCs. Overexpression of TP53INP1 induced apoptosis of BMSCs, knockdown of TP53INP1 alleviated oxidative stress apoptosis of BMSCs. Under oxidative stress conditions, P53 is regulated by TP53INP1, while P53 can positively regulate the expression of TP53INP1, so the two form a positive feedback loop. To clarify the mechanism of feedback loop formation. We found that TP53INP1 inhibited the ubiquitination and degradation of P53 by increasing the phosphorylation level of P53, leading to the accumulation of P53 protein. P53 can act on the promoter of the TP53INP1 gene and increase the expression of TP53INP1 through transcriptional activation. This is the first report on a positive feedback loop formed by TP53INP1 and P53 under oxidative stress. The present study clarified the formation mechanism of the positive feedback loop. The TP53INP1-P53 positive feedback loop may serve as a potential target for inhibiting oxidative stress-induced apoptosis in BMSCs.

Glycerophosphodiesters inhibit lysosomal phospholipid catabolism in Batten disease.

Batten disease, the most prevalent form of neurodegeneration in children, is caused by mutations in the CLN3 gene, which encodes a lysosomal transmembrane protein. CLN3 loss leads to significant accumulation of glycerophosphodiesters (GPDs), the end products of glycerophospholipid catabolism in the lysosome. Despite GPD storage being robustly observed upon CLN3 loss, the role of GPDs in neuropathology remains unclear. Here, we demonstrate that GPDs act as potent inhibitors of glycerophospholipid catabolism in the lysosome using human cell lines and mouse models. Mechanistically, GPDs bind and competitively inhibit the lysosomal phospholipases PLA2G15 and PLBD2, which we establish to possess phospholipase B activity. GPDs effectively inhibit the rate-limiting lysophospholipase activity of these phospholipases. Consistently, lysosomes of CLN3-deficient cells and tissues accumulate toxic lysophospholipids. Our work establishes that the storage material in Batten disease directly disrupts lysosomal lipid homeostasis, suggesting GPD clearance as a potential therapeutic approach to this fatal disease.

APOE4/4 is linked to damaging lipid droplets in Alzheimer's disease microglia.

Several genetic risk factors for Alzheimer's disease implicate genes involved in lipid metabolism and many of these lipid genes are highly expressed in glial cells1. However, the relationship between lipid metabolism in glia and Alzheimer's disease pathology remains poorly understood. Through single-nucleus RNA sequencing of brain tissue in Alzheimer's disease, we have identified a microglial state defined by the expression of the lipid droplet-associated enzyme ACSL1 with ACSL1-positive microglia being most abundant in patients with Alzheimer's disease having the APOE4/4 genotype. In human induced pluripotent stem cell-derived microglia, fibrillar Aß induces ACSL1 expression, triglyceride synthesis and lipid droplet accumulation in an APOE-dependent manner. Additionally, conditioned media from lipid droplet-containing microglia lead to Tau phosphorylation and neurotoxicity in an APOE-dependent manner. Our findings suggest a link between genetic risk factors for Alzheimer's disease with microglial lipid droplet accumulation and neurotoxic microglia-derived factors, potentially providing therapeutic strategies for Alzheimer's disease.

High-accuracy 3D segmentation of wet age-related macular degeneration via multi-scale and cross-channel feature extraction and channel attention.

Wet age-related macular degeneration (AMD) is the leading cause of visual impairment and vision loss in the elderly, and optical coherence tomography (OCT) enables revolving biotissue three-dimensional micro-structure widely used to diagnose and monitor wet AMD lesions. Many wet AMD segmentation methods based on deep learning have achieved good results, but these segmentation results are two-dimensional, and cannot take full advantage of OCT's three-dimensional (3D) imaging characteristics. Here we propose a novel deep-learning network characterizing multi-scale and cross-channel feature extraction and channel attention to obtain high-accuracy 3D segmentation results of wet AMD lesions and show the 3D specific morphology, a task unattainable with traditional two-dimensional segmentation. This probably helps to understand the ophthalmologic disease and provides great convenience for the clinical diagnosis and treatment of wet AMD.

Association of NLRPs with pathogenesis of dry age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly population, and Dry AMD is the most common clinical subtype. However, effective measures for the early diagnosis and treatment of dry AMD have not been proposed. In recent years, NOD-like receptors (NLRs) have received attention in the study of AMD as an important class of pattern recognition receptors. We attempted to elucidate the pathogenesis of NLRs in dry AMD from the perspective of chronic inflammation. METHODS: This study involved 13 patients with dry AMD, 10 age- and sex-matched normal population without any history of disease and 8 patients with wet AMD as controls. Using RT-qPCR, the mRNA expression levels of NLRs in peripheral blood peripheral blood mononuclear cells (PBMCs) were compared to analyze the statistical differences in the expression contents among the three populations. RESULTS: The relative RNA expression of nucleotide-binding oligomerization-like receptor protein 12 (NLRP12) with negative regulation of inflammation was significantly lower in dry AMD patients than in normal people and wet AMD patients. And NLRX1, which also has an anti-inflammatory effect, was lower in dry AMD patients than in wet AMD patients. However, NLRP3 with proinflammatory effect was significantly expressed in wet AMD. CONCLUSION: The significant decrease in NLRP12 in dry AMD may become a breakthrough in the study of dry AMD and systemic chronic inflammatory response. However, NLRP3 may have a more important role in wet AMD.

Stable Isotope-Assisted Untargeted Metabolomics Identifies ALDH1A1-Driven Erythronate Accumulation in Lung Cancer Cells.

Using an untargeted stable isotope-assisted metabolomics approach, we identify erythronate as a metabolite that accumulates in several human cancer cell lines. Erythronate has been reported to be a detoxification product derived from off-target glycolytic metabolism. We use chemical inhibitors and genetic silencing to define the pentose phosphate pathway intermediate erythrose 4-phosphate (E4P) as the starting substrate for erythronate production. However, following enzyme assay-coupled protein fractionation and subsequent proteomics analysis, we identify aldehyde dehydrogenase 1A1 (ALDH1A1) as the predominant contributor to erythrose oxidation to erythronate in cell extracts. Through modulating ALDH1A1 expression in cancer cell lines, we provide additional support. We hence describe a possible alternative route to erythronate production involving the dephosphorylation of E4P to form erythrose, followed by its oxidation by ALDH1A1. Finally, we measure increased erythronate concentrations in tumors relative to adjacent normal tissues from lung cancer patients. These findings suggest the accumulation of erythronate to be an example of metabolic reprogramming in cancer cells, raising the possibility that elevated levels of erythronate may serve as a biomarker of certain types of cancer.

The Batten disease gene product CLN5 is the lysosomal bis(monoacylglycero)phosphate synthase.

Lysosomes critically rely on bis(monoacylglycero)phosphate (BMP) to stimulate lipid catabolism, cholesterol homeostasis, and lysosomal function. Alterations in BMP levels in monogenic and complex neurodegeneration suggest an essential function in human health. However, the site and mechanism responsible for BMP synthesis have been subject to debate for decades. Here, we report that the Batten disease gene product CLN5 is the elusive BMP synthase (BMPS). BMPS-deficient cells exhibited a massive accumulation of the BMP synthesis precursor lysophosphatidylglycerol (LPG), depletion of BMP species, and dysfunctional lipid metabolism. Mechanistically, we found that BMPS mediated synthesis through an energy-independent base exchange reaction between two LPG molecules with increased activity on BMP-laden vesicles. Our study elucidates BMP biosynthesis and reveals an anabolic function of late endosomes/lysosomes.