EHMT2-mediated transcriptional reprogramming drives neuroendocrine transformation in non-small cell lung cancer.

The transformation of lung adenocarcinoma to small cell lung cancer (SCLC) is a recognized resistance mechanism and a hindrance to therapies using epidermal growth factor receptor tyrosine kinase inhibitors (TKIs). The paucity of pretranslational/posttranslational clinical samples limits the deeper understanding of resistance mechanisms and the exploration of effective therapeutic strategies. Here, we developed preclinical neuroendocrine (NE) transformation models. Next, we identified a transcriptional reprogramming mechanism that drives resistance to erlotinib in NE transformation cell lines and cell-derived xenograft mice. We observed the enhanced expression of genes involved in the EHMT2 and WNT/ß-catenin pathways. In addition, we demonstrated that EHMT2 increases methylation of the SFRP1 promoter region to reduce SFRP1 expression, followed by activation of the WNT/ß-catenin pathway and TKI-mediated NE transformation. Notably, the similar expression alterations of EHMT2 and SFRP1 were observed in transformed SCLC samples obtained from clinical patients. Importantly, suppression of EHMT2 with selective inhibitors restored the sensitivity of NE transformation cell lines to erlotinib and delayed resistance in cell-derived xenograft mice. We identify a transcriptional reprogramming process in NE transformation and provide a potential therapeutic target for overcoming resistance to erlotinib.

Multiregion exome sequencing indicates a monoclonal origin of esophageal spindle-cell squamous cell carcinoma.

Esophageal spindle-cell squamous cell carcinoma (ESS) is a rare biphasic neoplasm composed of a carcinomatous component (CaC) and a sarcomatous component (SaC). However, the genomic origin and gene signature of ESS remain unclear. Using whole-exome sequencing of laser-capture microdissection (LCM) tumor samples, we determined that CaC and SaC showed high mutational commonality, with the same top high-frequency mutant genes, mutation signatures, and tumor mutation burden; paired samples shared a median of 25.5% mutation sites. Focal gains were found on chromosomes 3q29, 5p15.33, and 11q13.3. Altered genes were mainly enriched in the RTK-RAS signaling pathway. Phylogenetic trees showed a monoclonal origin of ESS. The most frequently mutated oncogene in the trunk was TP53, followed by NFE2L2, KMT2D, and MUC16. Prognostic associations were found for CDC27, LRP2, APC, and SNAPC4. Our data highlight the monoclonal origin of ESS with TP53 as a potent driver oncogene, suggesting new targeted therapies and immunotherapies as treatment options. © 2024 The Pathological Society of Great Britain and Ireland.

Photobiocatalytic Platform for the Efficient Enantio-Divergent Synthesis of ß-Fluoromethylated Ketones.

ß-Fluoromethyl (CH2F, CHF2, and CF3)-substituted chiral ketones are essential moieties and are vital building blocks in pharmaceutical and agrochemistry. However, general and convenient methods for enantio-diverse access to diverse ß-fluoromethylated ketones are lacking, hindering the further development of these functional moieties. In this study, we developed an ene-reductase-based photobiocatalytic platform for efficient synthesis of enantio-divergent ß-fluoromethylated chiral ketones. Our method highlights substrate-type diversity, excellent enantioselectivity, enzymatic enantio-divergent synthesis, as well as a dicyanopyrazine (DPZ)-type photosensitizer for biocompatible olefin E/Z isomerization in enzymatic stereoconvergent olefin asymmetric reduction, thereby providing a general photobiocatalytic solution to diverse ß-fluoromethylated chiral ketones.

Single-Cell Transcriptome Analysis Reveals 2 Subtypes of Tumor Cells of Sclerosing Pneumocytoma With Distinct Molecular Features and Clinical Implications.

Pulmonary sclerosing pneumocytoma (PSP) is a rare, distinctive benign lung adenoma of pneumocyte origin. Despite its rarity, the tumor's unique cellular morphology has sparked ongoing debates regarding the origin of its constituent cells. This study aimed to elucidate the molecular features of PSP tumor cells and enhance our understanding of the cellular processes contributing to PSP formation and biological behavior. Tissue samples from PSP and corresponding normal lung tissues (n = 4) were collected. We employed single-cell RNA sequencing and microarray-based spatial transcriptomic analyses to identify cell types and investigate their transcriptomes, with a focus on transcription factors, enriched gene expression, and single-cell trajectory evaluations. Our analysis identified 2 types of tumor cells: mesenchymal-epithelial dual-phenotype (MEDP) cells and a distinct subpopulation of type II alveolar epithelial cells exhibiting characteristics slightly reminiscent of type I alveolar epithelial cells (AT2Cs) corresponding to histologic round stromal cells and surface cuboidal cells, respectively. MEDP cells displayed weak alveolar epithelial differentiation but strong collagen production capabilities, as indicated by the expression of both TTF-1 and vimentin. These cells played a pivotal role in forming the solid and sclerotic areas of PSP. Moreover, MEDP cells exhibited a pronounced propensity for epithelial-mesenchymal transition, suggesting a greater potential for metastasis compared with AT2Cs. The capillary endothelial cells of PSP displayed notable diversity. Overall, this study provides, for the first time, a comprehensive mapping of the single-cell transcriptome profile of PSP. Our findings delineate 2 distinct subtypes of tumor cells, MEDP cells and AT2Cs, each with its own biological characteristics and spatial distribution. A deeper understanding of these cell types promises insights into the histology and biological behaviors of this rare tumor.

Unraveling the Significance of MET Focal Amplification in Lung Cancer: Integrative NGS, FISH, and IHC Investigation.

MET amplification (METamp) represents a promising therapeutic target in non-small cell lung cancer, but no consensus has been established to identify METamp-dependent tumors that could potentially benefit from MET inhibitors. In this study, an analysis of MET amplification/overexpression status was performed in a retrospectively recruited cohort comprising 231 patients with non-small cell lung cancer from Shanghai Chest Hospital (SCH cohort) using 3 methods: fluorescence in situ hybridization (FISH), hybrid capture-based next-generation sequencing, and immunohistochemistry for c-MET and phospho-MET. The SCH cohort included 130 cases known to be METamp positive by FISH and 101 negative controls. The clinical relevance of these approaches in predicting the efficacy of MET inhibitors was evaluated. Additionally, next-generation sequencing data from another 2 cohorts including 22,010 lung cancer cases were utilized to examine the biological characteristics of different METamp subtypes. Of the 231 cases, 145 showed MET amplification/overexpression using at least 1 method, whereas only half of them could be identified by all 3 methods. METamp can occur as focal amplification or polysomy. Our study revealed that the inconsistency between next-generation sequencing and FISH primarily occurred in the polysomy subtype. Further investigations indicated that compared with polysomy, focal amplification correlated with fewer co-occurring driver mutations, higher protein expressions of c-MET and phospho-MET, and higher incidence in acquired resistance than in de novo setting. Moreover, patients with focal amplification presented a more robust response to MET inhibitors compared with those with polysomy. Notably, a strong correlation was observed between focal amplification and programmed cell death ligand-1 expression, indicating potential therapeutic implications with combined MET inhibitor and immunotherapy for patients with both alterations. Our findings provide insights into the molecular complexity and clinical relevance of METamp in lung cancer, highlighting the role of MET focal amplification as an oncogenic driver and its feasibility as a primary biomarker to further investigate the clinical activity of MET inhibitors in future studies.

Development of a double antibody sandwich ELISA method for the quantitative detection of serum C-reactive protein based on nanobody.

In this study, we successfully developed a nanobody-based double antibody sandwich ELISA kit for the detection of clinical serum C-reactive protein (CRP) by using two novel CRP specific nanobodies. The developed method exhibited a linear detection range of approximately 6-200 ng/mL, with a detection limit of 1 ng/mL. Furthermore, the method demonstrated excellent specificity, as there was no cross-reactivity with interfering substances such as total bilirubin and hemoglobin and so on. To assess reproducibility, independent measurements of the samples were conducted under experimental conditions, resulting in intra- and inter-batch coefficients of variation below 10% and a recovery rate of 93%-102%. These results indicate robust reproducibility of the method. To evaluate the performance of the developed kit, we collected 90 clinical samples for correlation analysis with commercial kits. The results showed a high correlation coefficient value (R2) of 0.98, indicating accurate concordance between the developed and commercial kits. In conclusion, our study successfully developed a nanobody-based double antibody sandwich ELISA kit to detect clinical serum CRP. The utilization of nanobodies represents a significant advancement in the field of CRP immunoassay development. The developed kit demonstrates excellent performance characteristics and holds promise for clinical applications.

Global burden of atrial fibrillation/atrial flutter and its attributable risk factors from 1990 to 2021.

AIMS: To devise effective preventive measures, a profound understanding of the evolving patterns and trends in atrial fibrillation (AF) and atrial flutter (AFL) burdens is pivotal. Our study was designed to quantify the burden and delineate the risk factors associated with AF and AFL across 204 countries and territories spanning 1990-2021. METHODS AND RESULTS: Data pertaining to AF and AFL were sourced from the Global Burden of Disease Study 2021. The burden of AF/AFL was evaluated using metrics such as incidence, disability-adjusted life years (DALYs), deaths, and their corresponding age-standardized rates (ASRs), stratified by age, sex, socio-demographic index (SDI), and human development index (HDI). The estimated annual percentage change was employed to quantify changes in ASRs. Population attributable fractions were calculated to determine the proportional contributions of major risk factors to age-standardized AF/AFL deaths. This analysis encompassed the period from 1990 to 2021. Globally, in 2021, there were 4.48 million incident cases [95% uncertainty interval (UI): 3.61-5.70], 8.36 million DALYs (95% UI: 6.97-10.13) and 0.34 million deaths (95% UI: 0.29-0.37) attributed to AF/AFL. The AF/AFL burden in 2021, as well as its trends from 1990 to 2021, displayed substantial variations based on gender, SDI quintiles, and geographical regions. High systolic blood pressure emerged as the leading contributor to age-standardized AF/AFL incidence, prevalence, death, and DALY rate globally among all potential risk factors, followed closely by high body mass index. CONCLUSION: Our study underscores the enduring significance of AF/AFL as a prominent public health concern worldwide, marked by profound regional and national variations. Despite the substantial potential for prevention and management of AF/AFL, there is a pressing imperative to adopt more cost-effective strategies and interventions to target modifiable risk factors, particularly in areas where the burden of AF/AFL is high or escalating.

Comparisons between atypical anorexia nervosa and anorexia nervosa: Psychological and comorbidity patterns.

OBJECTIVE: Literature comparing "atypical" anorexia nervosa (atypical AN) and anorexia nervosa (AN) suggests these diagnoses share significant similarities in eating disorder (ED) pathology and psychiatric comorbidities. This study evaluated potential differences in ED pathology, psychiatric comorbidity, associated mechanisms (i.e., ED fears and perfectionism), and demographic factors (i.e., ethnicity and age) between individuals with atypical AN and AN. METHOD: Data from seven protocols were combined for a total 464 individuals diagnosed with atypical AN (n = 215) or AN (n = 249). Between-group differences in ED severity and behaviors, psychiatric comorbidities, ED fears, perfectionism, and demographic factors were assessed using t-tests, Wilcoxon rank-sum tests, and Fisher's exact test. RESULTS: Participants with atypical AN reported higher levels of overvaluation of weight and shape than those with AN. Participants with AN scored higher on food-related fears (anxiety about eating, food avoidance behaviors, and feared concerns) and fears of social eating, as well as obsessive-compulsive symptoms. Participants with AN were more likely to identify as Asian or Pacific Islander. No other statistically significant differences were found between groups for overall ED severity, ED behaviors, psychiatric comorbidities, general ED fears, perfectionism, or demographic factors. DISCUSSION: Overall, results support previous literature indicating limited differences between individuals with atypical AN and AN, though individuals with atypical AN reported more overvaluation of weight and shape and those with AN reported higher food and social eating fears and obsessive-compulsive symptoms. Relatively few overall differences between atypical AN and AN highlight the importance of exploring dimensional conceptualizations of AN as an alternative to the current categorical conceptualization. PUBLIC SIGNIFICANCE: This study assessed differences among individuals with atypical anorexia nervosa and anorexia nervosa in eating disorder severity and behaviors, comorbid psychiatric diagnoses, associated mechanisms, and demographic factors. Few differences emerged, though participants with atypical anorexia nervosa reported more overvaluation of weight and shape, while those with anorexia nervosa reported more food and social eating fears and higher obsessive-compulsive symptoms. Results support exploration of these diagnoses as a spectrum disorder.

Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning.

OBJECTIVE: Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two. METHODS: Using an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI. RESULTS: Model performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%). DISCUSSION: Model performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered. PUBLIC SIGNIFICANCE: There is a growing debate about the differences between anorexia nervosa and atypical anorexia nervosa as their diagnostic differentiation relies on BMI despite being similar otherwise. We aimed to see if machine learning could distinguish between the two disorders and found accurate classification only if BMI was used as a feature. This finding calls into question the need to differentiate between the two disorders.

Peroxygenase-Enabled Reductive Kinetic Resolution for the Enantioenrichment of Organoperoxides.

Enantiomerically pure organoperoxides serve as valuable precursors in organic transformations. Herein, we present the first examples of unspecific peroxygenase catalyzed kinetic resolution of racemic organoperoxides through asymmetric reduction. Through meticulous investigation of the reaction conditions, it is shown that the unspecific peroxygenase from Agrocybe aegerita (AaeUPO) exhibits robust catalytic activity in the kinetic resolution reactions of the model substrate with turnover numbers up to 60000 and turnover frequency of 5.6 s-1. Various aralkyl organoperoxides were successfully resolved by AaeUPO, achieving excellent enantioselectivities (e.g., up to 99 % ee for the (S)-organoperoxide products). Additionally, we screened commercial peroxygenase variants to obtain the organoperoxides with complementary chirality, with one mutant yielding the (R)-products. While unspecific peroxygenases have been extensively demonstrated as a powerful oxidative catalysts, this study highlights their usefulness in catalyzing the reduction of organoperoxides and providing versatile chiral synthons.

Hantzsch Ester as Efficient and Economical NAD(P)H Mimic for In Vitro Bioredox Reactions.

Biocatalysis has emerged as a valuable and reliable tool for industrial and academic societies, particularly in fields related to bioredox reactions. The cost of cofactors, especially those needed to be replenished at stoichiometric amounts or more, is the chief economic concern for bioredox reactions. In this study, a readily accessible, inexpensive, and bench-stable Hantzsch ester is verified as the viable and efficient NAD(P)H mimic by four enzymatic redox transformations, including two non-heme diiron N-oxygenases and two flavin-dependent reductases. This finding provides the potential to significantly reduce the costs of NAD(P)H-relying bioredox reactions.

Novel marine metalloprotease-new approaches for inhibition of biofilm formation of Stenotrophomonas maltophilia.

Many marine organisms produce bioactive molecules with unique characteristics to survive in their ecological niches. These enzymes can be applied in biotechnological processes and in the medical sector to replace aggressive chemicals that are harmful to the environment. Especially in the human health sector, there is a need for new approaches to fight against pathogens like Stenotrophomonas maltophilia which forms thick biofilms on artificial joints or catheters and causes serious diseases. Our approach was to use enrichment cultures of five marine resources that underwent sequence-based screenings in combination with deep omics analyses in order to identify enzymes with antibiofilm characteristics. Especially the supernatant of the enrichment culture of a stony coral caused a 40% reduction of S. maltophilia biofilm formation. In the presence of the supernatant, our transcriptome dataset showed a clear stress response (upregulation of transcripts for metal resistance, antitoxins, transporter, and iron acquisition) to the treatment. Further investigation of the enrichment culture metagenome and proteome indicated a series of potential antimicrobial enzymes. We found an impressive group of metalloproteases in the proteome of the supernatant that is responsible for the detected anti-biofilm effect against S. maltophilia. KEY POINTS: • Omics-based discovery of novel marine-derived antimicrobials for human health management by inhibition of S. maltophilia • Up to 40% reduction of S. maltophilia biofilm formation by the use of marine-derived samples • Metalloprotease candidates prevent biofilm formation of S. maltophilia K279a by up to 20.

Panoramic three-dimensional optical digitization system assisted by a bi-mirror.

The digitization of objects' full surfaces finds widespread applications in fields such as virtual reality, art and design, and medical and biological sciences. For the realization of three-dimensional full-surface digitization of objects within complex sceneries, we propose a straightforward, efficient, and robust panoramic three-dimensional optical digitization system. This system contains a laser-based optical three-dimensional measurement system and a bi-mirror. By integrating mirrors into the system, we enable the illumination of the object from all angles using the projected laser beam in a single scanning process. Moreover, the main camera employed in the system can acquire three-dimensional information of the object from several different viewpoints. The rotational scanning method enhances the efficiency and applicability of the three-dimensional scanning process, enabling the acquisition of surface information of large-scale objects. After obtaining the three-dimensional data of the sample from different viewpoints using laser triangulation, mirror reflection transformation was employed to obtain the full-surface three-dimensional data of the object in the global coordinate system. The proposed method has been subjected to precision and validity experiments using samples with different surface characteristics and sizes, resulting in the demonstration of its capability for achieving correct three-dimensional digitization of the entire surface in diverse complex sceneries.

Plasmapheresis compared with conventional treatment for hypertriglyceridemia-induced acute pancreatitis: A systematic review and meta-analysis.

BACKGROUND: The treatment of acute pancreatitis (AP) induced by hypertriglyceridemia (HTG) remains controversial with regard to plasmapheresis vs conventional treatment. We reviewed relevant articles to explore the efficacy of plasmapheresis in the management of HTG-induced AP. METHODS: We systematically reviewed studies that compared plasmapheresis with conventional treatment for HTG-induced AP using three databases: PubMed, Embase, and Cochrane Library, as well as relevant references. The primary outcomes were 24 h triglyceride reduction rate and in-hospital mortality. RESULTS: A total of 791 articles were retrieved. Finally, 15 observational studies (1080 participants) were included, most of which were historical cohort studies. Compared with conventional treatment, plasmapheresis assisted in the reduction of serum triglyceride (TG) levels in the first 24 h after hospital admission (standardized mean difference [SMD]: 0.58; 95% confidence interval [CI]: 0.17 to 0.99; P = 0.005). However, it resulted in increased hospitalization costs (thousand yuan) (weighted mean difference [WMD]: 24.32; 95% CI: 12.96 to 35.68; P < 0.001). With regard to in-hospital mortality, although the mortality rate in the plasmapheresis group was higher than that in the conventional treatment group (relative risk [RR]: 1.74; 95% CI: 1.03 to 2.94; P = 0.038), the result was disturbed by confounding factors as per the subgroup and sensitivity analysis, as well as trial sequential analysis (TSA). No significant differences were found in other outcomes, including systematic complications, local complications, the requirement for surgery, and hospitalization duration. CONCLUSION: The effect of plasmapheresis in HTG-induced AP is not superior to that of conventional treatment, even resulting in a greater economic burden to patients and health care system. High quality randomized control trials are required to obtain a more a definitive understanding of this issue.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

A Fusion Positioning Method for Indoor Geomagnetic/Light Intensity/Pedestrian Dead Reckoning Based on Dual-Layer Tent-Atom Search Optimization-Back Propagation.

Indoor positioning using smartphones has garnered significant research attention. Geomagnetic and sensor data offer convenient methods for achieving this goal. However, conventional geomagnetic indoor positioning encounters several limitations, including low spatial resolution, poor accuracy, and stability issues. To address these challenges, we propose a fusion positioning approach. This approach integrates geomagnetic data, light intensity measurements, and inertial navigation data, utilizing a hierarchical optimization strategy. We employ a Tent-ASO-BP model that enhances the traditional Back Propagation (BP) algorithm through the integration of chaos mapping and Atom Search Optimization (ASO). In the offline phase, we construct a dual-resolution fingerprint database using Radial Basis Function (RBF) interpolation. This database amalgamates geomagnetic and light intensity data. The fused positioning results are obtained via the first layer of the Tent-ASO-BP model. We add a second Tent-ASO-BP layer and use an improved Pedestrian Dead Reckoning (PDR) method to derive the walking trajectory from smartphone sensors. In PDR, we apply the Biased Kalman Filter-Wavelet Transform (BKF-WT) for optimal heading estimation and set a time threshold to mitigate the effects of false peaks and valleys. The second-layer model combines geomagnetic and light intensity fusion coordinates with PDR coordinates. The experimental results demonstrate that our proposed positioning method not only effectively reduces positioning errors but also improves robustness across different application scenarios.

Improving Indoor Pedestrian Dead Reckoning for Smartphones under Magnetic Interference Using Deep Learning.

As micro-electro-mechanical systems (MEMS) technology continues its rapid ascent, a growing array of smart devices are integrating lightweight, compact, and cost-efficient magnetometers and inertial sensors, paving the way for advanced human motion analysis. However, sensors housed within smartphones frequently grapple with the detrimental effects of magnetic interference on heading estimation, resulting in diminished accuracy. To counteract this challenge, this study introduces a method that synergistically employs convolutional neural networks (CNNs) and support vector machines (SVMs) for adept interference detection. Utilizing a CNN, we automatically extract profound features from single-step pedestrian motion data that are then channeled into an SVM for interference detection. Based on these insights, we formulate heading estimation strategies aptly suited for scenarios both devoid of and subjected to magnetic interference. Empirical assessments underscore our method's prowess, boasting an impressive interference detection accuracy of 99.38%. In indoor environments influenced by such magnetic disturbances, evaluations conducted along square and equilateral triangle trajectories revealed single-step heading absolute error averages of 2.1891° and 1.5805°, with positioning errors averaging 0.7565 m and 0.3856 m, respectively. These results lucidly attest to the robustness of our proposed approach in enhancing indoor pedestrian positioning accuracy in the face of magnetic interferences.

SIRT2 Deficiency Aggravates Diet-Induced Nonalcoholic Fatty Liver Disease through Modulating Gut Microbiota and Metabolites.

Non-alcoholic fatty liver disease (NAFLD), characterized by excessive lipid accumulation in hepatocytes, is an increasing global healthcare burden. Sirtuin 2 (SIRT2) functions as a preventive molecule for NAFLD with incompletely clarified regulatory mechanisms. Metabolic changes and gut microbiota imbalance are critical to the pathogenesis of NAFLD. However, their association with SIRT2 in NAFLD progression is still unknown. Here, we report that SIRT2 knockout (KO) mice are susceptible to HFCS (high-fat/high-cholesterol/high-sucrose)-induced obesity and hepatic steatosis accompanied with an aggravated metabolic profile, which indicates SIRT2 deficiency promotes NAFLD-NASH (nonalcoholic steatohepatitis) progression. Under palmitic acid (PA), cholesterol (CHO), and high glucose (Glu) conditions, SIRT2 deficiency promotes lipid deposition and inflammation in cultured cells. Mechanically, SIRT2 deficiency induces serum metabolites alteration including upregulation of L-proline and downregulation of phosphatidylcholines (PC), lysophosphatidylcholine (LPC), and epinephrine. Furthermore, SIRT2 deficiency promotes gut microbiota dysbiosis. The microbiota composition clustered distinctly in SIRT2 KO mice with decreased Bacteroides and Eubacterium, and increased Acetatifactor. In clinical patients, SIRT2 is downregulated in the NALFD patients compared with healthy controls, and is associated with exacerbated progression of normal liver status to NAFLD to NASH in clinical patients. In conclusion, SIRT2 deficiency accelerates HFCS-induced NAFLD-NASH progression by inducing alteration of gut microbiota and changes of metabolites.

Distinct mutational features across preinvasive and invasive subtypes identified through comprehensive profiling of surgically resected lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a heterogeneous disease. Our study aimed to understand the unique molecular features of preinvasive to invasive LUAD subtypes. We retrospectively analyzed the clinical, histopathological, and molecular data of 3,254 Chinese patients with preinvasive lesions (n = 252), minimally invasive adenocarcinomas (n = 479), and invasive LUAD (n = 2,523). Molecular data were elucidated using a targeted 68-gene next-generation sequencing panel. Our findings revealed four preinvasive lesion-predominant gene mutations, including MAP2K1 insertion-deletions (indels), BRAF non-V600E kinase mutations, and exon 20 insertions (20ins) in both EGFR and ERBB2, which we referred to as mutations enriched in AIS (MEA). The detection rate of MEA in invasive tumors was relatively lower. MAP2K1 missense mutations, which were likely passenger mutations, co-occurred with oncogenic driver mutations, while small indels were mutually exclusive from other genes regardless of the invasion level. BRAF non-V600E kinase-mutant invasive adenocarcinomas (IAC) had significantly higher mutation rates in tumor suppressor genes but lower frequency of co-occurring oncogenic driver mutations than non-kinase-mutant IAC, suggesting the potential oncogenic activity of BRAF non-V600E kinase mutations albeit weaker than BRAF V600E. Moreover, similar to the extremely low frequency of MAP2K1 indels in IAC, BRAF non-V600E kinase domain mutations co-occurring with TSC1 mutations were exclusively found in preinvasive lesions. Compared with EGFR L858R and exon 19 deletion, patients with preinvasive lesions harboring 20ins in either EGFR or ERBB2 were significantly younger, while those with IAC had similar age. Furthermore, our study demonstrated distinct mutational features for subtypes of oncogene mutations favored by different invasion patterns in adenocarcinomas. In conclusion, our data demonstrate distinct mutational features between preinvasive lesions and invasive tumors with MEA, suggesting the involvement of MEA in the early stages of tumorigenesis. Further pre-clinical studies are required to establish the role of these genes in the malignant transformation of LUAD.

LSD1-Demethylated LINC01134 Confers Oxaliplatin Resistance Through SP1-Induced p62 Transcription in HCC.

BACKGROUND AND AIMS: Oxaliplatin (OXA) is one of the most common chemotherapeutics in advanced hepatocellular carcinoma (HCC), the resistance of which poses a big challenge. Long noncoding RNAs (lncRNAs) play vital roles in chemoresistance. Therefore, elucidating the underlying mechanisms and identifying predictive lncRNAs for OXA resistance is needed urgently. METHODS: RNA sequencing (RNA-seq) and fluorescence in situ hybridization (FISH) were used to investigate the OXA-resistant (OXA-R) lncRNAs. Survival analysis was performed to determine the clinical significance of homo sapiens long intergenic non-protein-coding RNA 1134 (LINC01134) and p62 expression. Luciferase, RNA immunoprecipitation (RIP), chromatin immunoprecipitation (ChIP), and chromatin isolation by RNA purification (ChIRP) assays were used to explore the mechanisms by which LINC01134 regulates p62 expression. The effects of LINC01134/SP1/p62 axis on OXA resistance were evaluated using cell viability, apoptosis, and mitochondrial function and morphology analysis. Xenografts were used to estimate the in vivo regulation of OXA resistance by LINC01134/SP1/p62 axis. ChIP, cell viability, and xenograft assays were used to identify the demethylase for LINC01134 up-regulation in OXA resistance. RESULTS: LINC01134 was identified as one of the most up-regulated lncRNAs in OXA-R cells. Higher LINC01134 expression predicted poorer OXA therapeutic efficacy. LINC01134 activates anti-oxidative pathway through p62 by recruiting transcription factor SP1 to the p62 promoter. The LINC01134/SP1/p62 axis regulates OXA resistance by altering cell viability, apoptosis, and mitochondrial homeostasis both in vitro and in vivo. Furthermore, the demethylase, lysine specific demethylase 1 (LSD1) was responsible for LINC01134 up-regulation in OXA-R cells. In patients with HCC, LINC01134 expression was positively correlated with p62 and LSD1 expressions, whereas SP1 expression positively correlated with p62 expression. CONCLUSIONS: LSD1/LINC01134/SP1/p62 axis is critical for OXA resistance in HCC. Evaluating LINC01134 expression in HCC will be effective in predicting OXA efficacy. In treatment-naive patients, targeting the LINC01134/SP1/p62 axis may be a promising strategy to overcome OXA chemoresistance.