Citations

Background Remote limb ischemic postconditioning (RLIPoC) has been demonstrated to protect against ischemic stroke. However, the underlying mechanisms of RLIPoC mediating cross‐organ protection remain to be fully elucidated. Methods and Results Ischemic stroke was induced by middle cerebral artery occlusion for 60 minutes. RLIPoC was performed with 3 cycles of 10‐minute ischemia followed by 10‐minute reperfusion of the bilateral femoral arteries immediately after middle cerebral artery reperfusion. The percentage of regulatory T cells (Tregs) in the spleen, blood, and brain was detected using flow cytometry, and the number of Tregs in the ischemic hemisphere was counted using transgenic mice with an enhanced green fluorescent protein‐tagged Foxp3. Furthermore, the metabolic status was monitored dynamically using a multispectral optical imaging system. The Tregs were conditionally depleted in the depletion of Treg transgenic mice after the injection of the diphtheria toxin. The inflammatory response and neuronal apoptosis were investigated using immunofluorescent staining. Infarct volume and neurological deficits were evaluated using magnetic resonance imaging and the modified neurological severity score, respectively. The results showed that RLIPoC substantially reduced infarct volume, improved neurological function, and significantly increased Tregs in the spleen, blood, and ischemic hemisphere after middle cerebral artery occlusion. RLIPoC was followed by subsequent alteration in metabolites, such as flavin adenine dinucleotide and nicotinamide adenine dinucleotide hydrate, both in RLIPoC‐conducted local tissues and circulating blood. Furthermore, nicotinamide adenine dinucleotide hydrate can mimic RLIPoC in increasing Tregs. Conversely, the depletion of Tregs using depletion of Treg mice compromised the neuroprotective effects conferred by RLIPoC. Conclusions RLIPoC protects against ischemic brain injury, at least in part by activating and maintaining the Tregs through the nicotinamide adenine dinucleotide/nicotinamide adenine dinucleotide hydrate pathway.

Abstract Dissemination of ovarian cancer cells can lead to inoperable metastatic lesions in the bowel and omentum that cause patient death. Here we show that LRRC15, a type-I 15-leucine–rich repeat-containing membrane protein, highly overexpressed in ovarian cancer bowel metastases compared with matched primary tumors and acts as a potent promoter of omental metastasis. Complementary models of ovarian cancer demonstrated that LRRC15 expression leads to inhibition of anoikis-induced cell death and promotes adhesion and invasion through matrices that mimic omentum. Mechanistically, LRRC15 interacted with β1-integrin to stimulate activation of focal adhesion kinase (FAK) signaling. As a therapeutic proof of concept, targeting LRRC15 with the specific antibody–drug conjugate ABBV-085 in both early and late metastatic ovarian cancer cell line xenograft models prevented metastatic dissemination, and these results were corroborated in metastatic patient-derived ovarian cancer xenograft models. Furthermore, treatment of 3D-spheroid cultures of LRRC15-positive patient-derived ascites with ABBV-085 reduced cell viability. Overall, these data uncover a role for LRRC15 in promoting ovarian cancer metastasis and suggest a novel and promising therapy to target ovarian cancer metastases. Significance: This study identifies that LRRC15 activates β1-integrin/FAK signaling to promote ovarian cancer metastasis and shows that the LRRC15-targeted antibody–drug conjugate ABBV-085 suppresses ovarian cancer metastasis in preclinical models.

A considerable subset of gynecologic cancer patients experience disease recurrence or acquired resistance, which contributes to high mortality rates in ovarian cancer (OC). Our prior studies showed that quinacrine (QC), an antimalarial drug, enhanced chemotherapy sensitivity in treatment-refractory OC cells, including artificially generated chemoresistant and high-grade serous OC cells. In this study, we investigated QC-induced transcriptomic changes to uncover its cytotoxic mechanisms of action. Isogenic pairs of OC cells generated to be chemoresistant and their chemosensitive counterparts were treated with QC followed by RNA-seq analysis. Validation of selected expression results and database comparison analyses indicated the ribosomal biogenesis (RBG) pathway is inhibited by QC. RBG is commonly upregulated in cancer cells and is emerging as a drug target. We found that QC attenuates the in vitro and in vivo expression of nucleostemin (NS/GNL3), a nucleolar RBG and DNA repair protein, and the RPA194 catalytic subunit of Pol I that results in RBG inhibition and nucleolar stress. QC promotes the redistribution of fibrillarin in the form of extranuclear foci and nucleolar caps, an indicator of nucleolar stress conditions. In addition, we found that QC-induced downregulation of NS disrupted homologous recombination repair both by reducing NS protein levels and PARylation resulting in reduced RAD51 recruitment to DNA damage. Our data suggest that QC inhibits RBG and this inhibition promotes DNA damage by directly downregulating the NS–RAD51 interaction. Additionally, QC showed strong synergy with PARP inhibitors in OC cells. Overall, we found that QC downregulates the RBG pathway, induces nucleolar stress, supports the increase of DNA damage, and sensitizes cells to PARP inhibition, which supports new therapeutic stratagems for treatment-refractory OC. Our work offers support for targeting RBG in OC and determines NS to be a novel target for QC.

AbstractBackground:The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.Methods:Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.Results:We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.Conclusions:We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.Impact:A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

Rationale: Anthracycline-induced cardiotoxicity (AIC) is a major side effect that limits the use of anthracyclines as effective chemotherapeutics. No mechanism-based therapy is available when cardiac function deteriorates. Objective: We aim to elucidate the dynamic autophagic defects in AIC and to identify a mechanism-based therapy via both genetic and pharmacological studies. Method and Results: Through phenotyping an adult AIC zebrafish model, we detected a biphasic response in autophagy: activation in the early stage and suppression in the later phase that is characterized by a decline in cardiac function. We conducted conditional genetic studies with atg7 , which encodes a rate-limiting autophagy core protein, and found that atg7 overexpression leads to therapeutic effects in the late phase but deleterious effects in the early phase of adult AIC. We then assessed the therapeutic effects of 37 Food and Drug Administration–approved autophagy activators using an embryonic AIC zebrafish model and identified spironolactone, pravastatin, and minoxidil as top-ranking drugs. We demonstrated the therapeutic efficacy of these Food and Drug Administration–approved autophagy activators in the adult AIC model and confirmed that these drugs exert therapeutic effects in the late phase but not in the early AIC phase. Finally, we demonstrated that the time-dependent therapeutic effects are conserved in a mouse AIC model and that spironolactone and rapamycin activated autophagy in an Atg7-dependent fashion. Conclusions: Our findings suggest that atg7-based autophagy activation is an effective therapeutic avenue to reversing the decline in cardiac function in AIC, highlighting the time-dependent nature of autophagy-based therapy.

Purpose: Hypsarrhythmia is one of the major diagnostic and treatment response criteria in infantile spasms (IS). The clinical and electrophysiological effect of repository corticotropin injection treatment on IS was evaluated using electrophysiological biomarkers. Methods: Consecutive infants (<24 months) treated with repository corticotropin injection for IS were included in this retrospective descriptive study. Inclusion criteria were (1) clinical IS diagnosis, (2) repository corticotropin injection treatment, and (3) consecutive EEG recordings before and after repository corticotropin injection treatment. Patients with tuberous sclerosis complex were excluded. Response to treatment was defined as freedom from IS for at least 7 consecutive days during the treatment and resolution of hypsarrhythmia. The authors defined “relapse” as the recurrence of seizures after an initial response. Electrophysiological biomarker assessment included evaluation of semiautomatic spike counting algorithm, delta power, and delta coherence calculation during non-REM sleep EEG. Results: One hundred fifty patients (83 males; 55%; median age of IS onset: 5.9 months) with complete data were included, including 101 responders (67%, 71 with sustained response, and 30 relapses). Fifty patients (33%) with complete EEG data also underwent advanced EEG analysis. Baseline delta coherence was higher in sustained responders than in nonresponders or patients who relapsed. Greater decreases in semiautomatic spike counting algorithm, delta power, and delta coherence were found in sustained responders compared with nonresponders or patients who relapsed. Conclusions: Repository corticotropin injection treatment was associated with a 67% response rate in patients with IS. Computational biomarkers beyond hypsarrhythmia may provide additional information during IS treatment, such as early determination of treatment response and outcome assessment.

AbstractAcute kidney injury (AKI) may develop in patients with coronavirus disease 2019 (COVID‐19) and is associated with in‐hospital death. We investigated the incidence of AKI in 223 hospitalized COVID‐19 patients and analyzed the influence factors of AKI. The incidence of cytokine storm syndrome and its correlation with other clinicopathologic variables were also investigated. We retrospectively enrolled adult patients with virologically confirmed COVID‐19 who were hospitalized at three hospitals in Wuhan and Guizhou, China between February 13, 2020, and April 8, 2020. We included 124 patients with moderate COVID‐19 and 99 with severe COVID‐19. AKI was present in 35 (15.7%) patients. The incidence of AKI was 30.3% for severe COVID‐19 and 4.0% for moderate COVID‐19 (p < 0.001). Furthermore, cytokine storm was found in 30 (13.5%) patients and only found in the severe group. Kidney injury at admission (odds ratio [OR]: 3.132, 95% confidence interval [CI]: 1.150–8.527; p = 0.025), cytokine storm (OR: 4.234, 95% CI: 1.361–13.171; p = 0.013), and acute respiratory distress syndrome (ARDS) (OR: 7.684, 95% CI: 2.622–22.523; p < 0.001) were influence factors of AKI. Seventeen (48.6%) patients who received invasive mechanical ventilation developed AKI, of whom 64.7% (11/17) died. Up to 86.7% of AKI patients with cytokine storms may develop a secondary bacterial infection. The leukocyte counts were significantly higher in AKI patients with cytokine storm than in those without (13.0 × 10⁹/L, interquartile range [IQR] 11.3 vs. 8.3 × 10⁹/L, IQR 7.5, p = 0.005). Approximately 1/6 patients with COVID‐19 eventually develop AKI. Kidney injury at admission, cytokine storm and ARDS are influence factors of AKI. Cytokine storm and secondary bacterial infections may be responsible for AKI development in COVID‐19 patients.

AbstractIntroductionThe efficacy of cardiac resynchronization therapy (CRT) has been widely studied in the medical literature; however, about 30% of candidates fail to respond to this treatment strategy. Smart computational approaches based on clinical data can help expose hidden patterns useful for identifying CRT responders.MethodsWe retrospectively analyzed the electronic health records of 1664 patients who underwent CRT procedures from January 1, 2002 to December 31, 2017. An ensemble of ensemble (EoE) machine learning (ML) system composed of a supervised and an unsupervised ML layers was developed to generate a prediction model for CRT response.ResultsWe compared the performance of EoE against traditional ML methods and the state‐of‐the‐art convolutional neural network (CNN) model trained on raw electrocardiographic (ECG) waveforms. We observed that the models exhibited improvement in performance as more features were incrementally used for training. Using the most comprehensive set of predictors, the performance of the EoE model in terms of the area under the receiver operating characteristic curve and F1‐score were 0.76 and 0.73, respectively. Direct application of the CNN model on the raw ECG waveforms did not generate promising results.ConclusionThe proposed CRT risk calculator effectively discriminates which heart failure (HF) patient is likely to respond to CRT significantly better than using clinical guidelines and traditional ML methods, thus suggesting that the tool can enhanced care management of HF patients by helping to identify high‐risk patients.