TIR8 protects against nonalcoholic steatohepatitis by antagonizing lipotoxicity-induced PPARα downregulation and reducing the sensitivity of hepatocytes to LPS.

In up to one-third of nonalcoholic fatty liver disease (NAFLD) patients, simple steatosis progresses to its more severe form, nonalcoholic steatohepatitis (NASH), but the precise mechanisms underlying this transition are not fully understood. Toll/interleukin-1 receptor 8 (TIR8), a conventional innate immune regulator highly expressed in hepatic tissue, has shown potential for ameliorating various inflammation-related disorders. However, its role in NASH pathogenesis, especially its regulatory effects on lipid metabolism and inflammatory responses, is still unclear. Here, using a TIR8 knockout (TIR8KO) mouse model and mass spectrometry analyses, we found that TIR8KO mice displayed aggravated hepatic steatosis and inflammation, whereas TIR8 overexpression attenuated these adverse effects. Ectopic TIR8 expression counteracts free fatty acid (FFA)-induced PPARα inhibition and downstream signaling. A decrease in TIR8 levels in hepatocytes heightened lipopolysaccharide (LPS) sensitivity. Notably, FFA stimulation led to a direct interaction between TIR8 and proteasome subunit alpha type 4 (PSMA4), facilitating TIR8 degradation. These results revealed that TIR8 safeguards PPARα-regulated lipid metabolism and mitigates inflammation induced by external factors during NASH progression. Our study highlights TIR8 as a promising target for NASH therapy, indicating the potential of TIR8 agonists in treatment strategies.

Targeting Super-Enhancer-Driven Transcriptional Dependencies Suppresses Aberrant Hedgehog Pathway Activation and Overcomes Smoothened Inhibitor Resistance.

Aberrant activation of the Hedgehog (Hh) signaling pathway plays important roles in oncogenesis and therapeutic resistance in several types of cancer. The clinical application of FDA-approved Hh-targeted Smoothened inhibitors (SMOi) is hindered by the emergence of primary or acquired drug resistance. Epigenetic and transcriptional targeted therapies represent a promising direction for developing improved anti-Hh therapies. In this study, we integrated epigenetic/transcriptional-targeted small-molecule library screening with CRISPR/Cas9 knockout library screening and identified CDK9 and CDK12, two transcription elongation regulators, as therapeutic targets for antagonizing aberrant Hh activation and overcoming SMOi resistance. Inhibition of CDK9 or CDK12 potently suppressed Hh signaling and tumor growth in various SMOi responsive or resistant Hh-driven tumor models. Systemic epigenomic profiling elucidated the Hh-driven super-enhancer (SE) landscape and identified IRS1, encoding a critical component and cytoplasmic adaptor protein of the IGF pathway, as an oncogenic Hh-driven SE target gene and effective therapeutic target in Hh-driven tumor models. Collectively, this study identifies SE-driven transcriptional dependencies that represent promising therapeutic vulnerabilities for suppressing the Hh pathway and overcoming SMOi resistance. As CDK9 and IRS inhibitors have already entered human clinical trials for cancer treatment, these findings provide comprehensive preclinical support for developing trials for Hh-driven cancers.

Improved Prediction of Epidermal Growth Factor Receptor Status by Combined Radiomics of Primary Nonsmall-Cell Lung Cancer and Distant Metastasis.

OBJECTIVES: This study aimed to investigate radiomics based on primary nonsmall-cell lung cancer (NSCLC) and distant metastases to predict epidermal growth factor receptor (EGFR) mutation status. METHODS: A total of 290 patients (mean age, 58.21 ± 9.28) diagnosed with brain (BM, n = 150) or spinal bone metastasis (SM, n = 140) from primary NSCLC were enrolled as a primary cohort. An external validation cohort, consisting of 69 patients (mean age, 59.87 ± 7.23; BM, n = 36; SM, n = 33), was enrolled from another center. Thoracic computed tomography-based features were extracted from the primary tumor and peritumoral area and selected using the least absolute shrinkage and selection operator regression to build a radiomic signature (RS-primary). Contrast-enhanced magnetic resonance imaging-based features were calculated and selected from the BM and SM to build RS-BM and RS-SM, respectively. The RS-BM-Com and RS-SM-Com were developed by integrating the most important features from the primary tumor, BM, and SM. RESULTS: Six computed tomography-based features showed high association with EGFR mutation status: 3 from intratumoral and 3 from peritumoral areas. By combination of features from primary tumor and metastases, the developed RS-BM-Com and RS-SM-Com performed well with areas under curve in the training (RS-BM-Com vs RS-BM, 0.936 vs 0.885, P = 0.177; RS-SM-Com vs RS-SM, 0.929 vs 0.843, P = 0.003), internal validation (RS-BM-Com vs RS-BM, 0.920 vs 0.858, P = 0.492; RS-SM-Com vs RS-SM, 0.896 vs 0.859, P = 0.379), and external validation (RS-BM-Com vs RS-BM, 0.882 vs 0.805, P = 0.263; RS-SM-Com vs RS-SM, 0.865 vs 0.816, P = 0.312) cohorts. CONCLUSIONS: This study indicates that the accuracy of detecting EGFR mutations significantly enhanced in the presence of metastases in primary NSCLC. The established radiomic signatures from this approach may be useful as new predictors for patients with distant metastases.

Innovative modification of cellulose fibers for paper-based electrode materials using metal-organic coordination polymers.

Cellulosic paper-based electrode materials have attracted increasing attention in the field of flexible supercapacitor. As a conductive polymer, polyaniline exhibits high theoretical pseudocapacitive capacitance and has been applied in paper-based electrode materials along with cellulose fibers. However, the stacking of polyaniline usually leads to poor performance of electrodes. In this study, metal-organic coordination polymers of zirconium-alizarin red S and zirconium-phytic acid are applied to modulate the polyaniline layer to obtain high-performance cellulosic paper-based electrode materials. Zirconium hydroxide is firstly loaded on cellulose fibers while alizarin red S and phytic acid are introduced to regulate the morphology of polyaniline through doping and coordination processes. The results show that the introduction of dual coordination polymers is effective to regulate the morphology of polyaniline on cellulose fibers. The performances of the paper-based electrode materials, including electrical conductivity and electrochemistry, are apparently improved. It provides a promising strategy for the potential development of economical and green electrode materials in the conventional paper-making process.

(De)carboxylation mechanisms of heteroaromatic substrates catalyzed by prenylated FMN-dependent UbiD decarboxylases: An in-silico study.

The UbiD enzymes are proposed to catalyze reversible (de)carboxylation reaction of unsaturated carboxylic acids using prenylated flavin mononucleotide (prFMN) as a cofactor. This positions UbiD enzymes as promising candidates for converting CO2 into valuable chemicals. However, their industrial-scale biotransformation is currently constrained by low conversion rates attributed to thermodynamic limitations. To enhance the carboxylation activity of UbiD enzymes, a molecular-level understanding of the (de)carboxylation mechanisms is necessary. In this study, we investigated the reaction mechanisms of heteroaromatic substrates catalyzed by PtHmfF, PaHudA, and AnlnD enzymes using molecular dynamics (MD) simulations and free energy calculations. Our extensive mechanistic study elucidates the mechanisms involved in the formation of the initial prFMN-substrate intermediate. Specifically, we observed nucleophilic attack during decarboxylation, while carboxylation reactions involving furoic acid, pyrrole, and indole tend to favor a 1,3-dipolar cycloaddition mechanism. Furthermore, we identified proton transfer as the rate-limiting step in the carboxylation reaction. In addition, we considered the perspectives of reaction energies and electron transfer to understand the distinct mechanisms underlying decarboxylation and carboxylation. Our calculated free energies are consistent with available experimental kinetics data. Finally, we explored how different rotamers of catalytic residues influence the efficiency of the initial intermediate formation.

Intra- and Peritumoral Based Radiomics for Assessment of Lymphovascular Invasion in Invasive Breast Cancer.

BACKGROUND: Radiomics has been applied for assessing lymphovascular invasion (LVI) in patients with breast cancer. However, associations between features from peritumoral regions and the LVI status were not investigated. PURPOSE: To investigate the value of intra- and peritumoral radiomics for assessing LVI, and to develop a nomogram to assist in making treatment decisions. STUDY TYPE: Retrospective. POPULATION: Three hundred and sixteen patients were enrolled from two centers and divided into training (N = 165), internal validation (N = 83), and external validation (N = 68) cohorts. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI). ASSESSMENT: Radiomics features were extracted and selected based on intra- and peritumoral breast regions in two magnetic resonance imaging (MRI) sequences to create the multiparametric MRI combined radiomics signature (RS-DCE plus DWI). The clinical model was built with MRI-axillary lymph nodes (MRI ALN), MRI-reported peritumoral edema (MPE), and apparent diffusion coefficient (ADC). The nomogram was constructed with RS-DCE plus DWI, MRI ALN, MPE, and ADC. STATISTICAL TESTS: Intra- and interclass correlation coefficient analysis, Mann-Whitney U test, and least absolute shrinkage and selection operator regression were used for feature selection. Receiver operating characteristic and decision curve analyses were applied to compare performance of the RS-DCE plus DWI, clinical model, and nomogram. RESULTS: A total of 10 features were found to be associated with LVI, 3 from intra- and 7 from peritumoral areas. The nomogram showed good performance in the training (AUCs, nomogram vs. clinical model vs. RS-DCE plus DWI, 0.884 vs. 0.695 vs. 0.870), internal validation (AUCs, nomogram vs. clinical model vs. RS-DCE plus DWI, 0.813 vs. 0.695 vs. 0.794), and external validation (AUCs, nomogram vs. clinical model vs. RS-DCE plus DWI, 0.862 vs. 0.601 vs. 0.849) cohorts. DATA CONCLUSION: The constructed preoperative nomogram might effectively assess LVI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Tumor-liver interface in MRI of liver metastasis enables prediction of EGFR mutation in patients with lung cancer: A proof-of-concept study.

BACKGROUND: Preoperative prediction of the epidermal growth factor receptor (EGFR) status in non-small-cell lung cancer (NSCLC) patients with liver metastasis (LM) may have potential clinical values for assisting in treatment decision-making. PURPOSE: To explore the value of tumor-liver interface (TLI)-based magnetic resonance imaging (MRI) radiomics for detecting the EGFR mutation in NSCLC patients with LM. METHODS: This retrospective study included 123 and 44 patients from hospital 1 (between Feb. 2018 and Dec. 2021) and hospital 2 (between Nov. 2015 and Aug. 2022), respectively. The patients received contrast-enhanced T1-weighted (CET1) and T2-weighted (T2W) liver MRI scans before treatment. Radiomics features were extracted from MRI images of TLI and the whole tumor region, separately. The least absolute shrinkage and selection operator (LASSO) regression was used to screen the features and establish radiomics signatures (RSs) based on TLI (RS-TLI) and the whole tumor (RS-W). The RSs were evaluated by the receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 5 and 6 features were identified highly correlated with the EGFR mutation status from TLI and the whole tumor, respectively. The RS-TLI showed better prediction performance than RS-W in the training (AUCs, RS-TLI vs. RS-W, 0.842 vs. 0.797), internal validation (AUCs, RS-TLI vs. RS-W, 0.771 vs. 0.676) and external validation (AUCs, RS-TLI vs. RS-W, 0.733 vs. 0.679) cohort. CONCLUSION: Our study demonstrated that TLI-based radiomics can improve prediction performance of the EGFR mutation in lung cancer patients with LM. The established multi-parametric MRI radiomics models may be used as new markers that can potentially assist in personalized treatment planning.

Ct-based subregional radiomics using hand-crafted and deep learning features for prediction of therapeutic response to anti-PD1 therapy in NSCLC.

PURPOSE: To develop and externally validate subregional radiomics for predicting therapeutic response to anti-PD1 therapy in non-small-cell lung cancer (NSCLC). METHODS: Sixty-six patients from center 1 served as training and internal validation cohorts. Thirty patients from center 2 and thirty patients from center 3 served as external validation 1 and external validation 2 cohorts, respectively. The lesions identified on CT scans were subdivided into two phenotypically consistent subregions by automatic clustering on the patient-level and population-level (denoted as marginal S1 and inner S2). Handcrafted and deep learning-based features were extracted separately from the entire tumor region and subregions, then selected using the intraclass correlation coefficient and least absolute shrinkage and selection operator regression (LASSO). Radiomics signatures (RSs) were built integrating the selected features and correlation coefficients using a logistic regression method. Area under the receiver operating characteristic (ROC) curve (AUC) was calculated to assess the RSs. RESULTS: RSs derived from S1 outperformed those from S2 and the whole tumor region for both handcrafted and deep learning features. The Fusion-RS incorporating the two feature types achieved the best prediction performance in training (AUC = 0.947, 95 % Confidence Interval [CI] 0.905-0.989, SPE = 0.895, SEN = 0.878), internal validation (AUC = 0.875, 95 % CI: 0.782-0.969, SPE = 0.724, SEN = 0.952), external validation 1 (AUC = 0.836, 95 % CI: 0.694-0.977, SPE = 1.000, SEN = 0.533) and external validation 2 (AUC = 0.783, 95 % CI: 0.613-0.953, SPE = 0.765, SEN = 0.692) cohorts. CONCLUSIONS: Subregional radiomics analysis can be useful for predicting therapeutic response to anti-PD1 therapy. The developed Fusion-RS may be considered as a potential non-invasive tool for individual treatment managements.

Inhibitory effect of tannic acid on the growth of Apiospora arundinis and 3-Nitropropionic acid production.

AIMS: This study aimed to investigate the inhibitory effect of tannic acid (TA) on the growth of Apiospora arundinis and 3-Nitropropionic acid (3-NPA) production. METHODS AND RESULTS: To investigate the antifungal mechanism, the effects of TA on the hypha growth, electrical conductivity, hypha morphology, defense-related enzymes, and 3-NPA production of A. arundinis were studied. TA concentrations of 640 and 1280 µg ml-1 exhibited strong antifungal activity against A. arundinis. The results of scanning electron microscopy and transmission electron microscopy showed that the hypha of the A. arundinis was severely deformed after TA treatment, and the cell membrane was blurred and thin, vacuoles were obviously shrunken and smaller, and most of the organelles were decomposed into irregular fragments. The increased electrical conductivity and malondialdehyde content indicated that TA caused peroxidation of unsaturated fatty acids and damaged the structure of the cell membrane. The decrease of intracellular ATPase and succinate dehydrogenase content indicated that TA damaged the function of mitochondria, and participated in the inhibition of respiratory metabolism. In addition, TA significantly reduced 3-NPA production and completely inhibited 3-NPA production at 640 and 1280 µg ml-1. CONCLUSION: TA effectively inhibited both growth of A. arundinis in vitro and 3-NPA production.

Radiomic Signatures Based on Mammography and Magnetic Resonance Imaging as New Markers for Estimation of Ki-67 and HER-2 Status in Breast Cancer.

OBJECTIVE: The aim of the study is to investigate the values of intratumoral and peritumoral regions based on mammography and magnetic resonance imaging for the prediction of Ki-67 and human epidermal growth factor (HER-2) status in breast cancer (BC). METHODS: Two hundred BC patients were consecutively enrolled between January 2017 and March 2021 and divided into training (n = 133) and validation (n = 67) groups. All the patients underwent breast mammography and magnetic resonance imaging screening. Features were derived from intratumoral and peritumoral regions of the tumor and selected using the least absolute shrinkage and selection operator regression to build radiomic signatures (RSs). Receiver operating characteristic curve analysis and the DeLong test were performed to assess and compare each RS. RESULTS: For each modality, the combined RSs integrating features from intratumoral and peritumoral regions always showed better prediction performance for predicting Ki-67 and HER-2 status compared with the RSs derived from intratumoral or peritumoral regions separately. The multimodality and multiregional combined RSs achieved the best prediction performance for predicting the Ki-67 and HER-2 status with an area under the receiver operating characteristic curve of 0.888 and 0.868 in the training cohort and 0.800 and 0.848 in the validation cohort, respectively. CONCLUSIONS: Peritumoral areas provide complementary information to intratumoral regions of BC. The developed multimodality and multiregional combined RSs have good potential for noninvasive evaluation of Ki-67 and HER-2 status in BC.

Combined radiomics of primary tumour and bone metastasis improve the prediction of EGFR mutation status and response to EGFR-TKI therapy for NSCLC.

PURPOSE: To develop radiomics models of primary tumour and spinal metastases to predict epidermal growth factor receptor (EGFR) mutations and therapeutic response to EGFR-tyrosine kinase inhibitor (TKI) in patients with metastatic non-small-cell lung cancer (NSCLC). METHODS: We enrolled 203 patients with spinal metastases between December 2017 and September 2021, classified as patients with the EGFR mutation or EGFR wild-type. All patients underwent thoracic CT and spinal MRI scans before any treatment. Radiomics analysis was performed to extract features from primary tumour and metastases images and identify predictive features with the least absolute shrinkage and selection operator. Radiomics signatures (RS) were constructed based on primary tumour (RS-Pri), metastases (RS-Met), and in combination (RS-Com) to predict EGFR mutation status and response to EGFR-TKI. Receiver operating characteristic (ROC) curve analysis with 10-fold cross-validation was applied to assess the performance of the models. RESULTS: To predict the EGFR mutation status, the RS based on the combination of primary tumour and metastases improved the prediction AUCs compared to those based on the primary tumour or metastasis alone in the training (RS-Com-EGFR: 0.927) and validation (RS-Com-EGFR: 0.812) cohorts. To predict response to EGFR-TKI, the developed RS based on combined primary tumour and metastasis generated the highest AUCs in the training (RS-Com-TKI: 0.880) and validation (RS-Com-TKI: 0.798) cohort. CONCLUSIONS: Primary NSCLC and spinal metastases can provide complementary information to predict the EGFR mutation status and response to EGFR-TKI. The developed models that integrate primary lesions and metastases may be potential imaging markers to guide individual treatment decisions.

L-carnitine reduces acute lung injury via mitochondria modulation and inflammation control in pulmonary macrophages.

Acute lung injury (ALI) or acute respiratory distress syndrome (ARDS) is a critical respiratory syndrome with limited effective interventions. Lung macrophages play a critical role in the pathogenesis of abnormal inflammatory response in the syndrome. Recently, impaired fatty acid oxidation (FAO), one of the key lipid metabolic signalings, was found to participate in the onset and development of various lung diseases, including ALI/ARDS. Lipid/fatty acid contents within mouse lungs were quantified using the Oil Red O staining. The protective effect of FAO activator L-carnitine (Lca, 50, 500, or 5 mg/mL) was evaluated by cell counting kit 8 (CCK-8) assay, real-time quantitative PCR (qPCR), ELISA, immunoblotting, fluorescence imaging, and fluorescence plate reader detection in lipopolysaccharide (LPS) (100 ng/mL)-stimulated THP-1-derived macrophages. The in vivo efficacy of Lca (300 mg/kg) was determined in a 10 mg/kg LPS-induced ALI mouse model. We found for the first time that lipid accumulation in pulmonary macrophages was significantly increased in a classical ALI murine model, which indicated disrupted FAO induced by LPS. Lca showed potent anti-inflammatory and antioxidative effects on THP-1 derived macrophages upon LPS stimulation. Mechanistically, Lca was able to maintain FAO, mitochondrial activity, and ameliorate mitochondrial dynamics. In the LPS-induced ALI mouse model, we further discovered that Lca inhibited neutrophilic inflammation and decreased diffuse damage, which might be due to the preservation of mitochondrial homeostasis. These results broadened our understanding of ALI/ARDS pathogenesis and provided a promising drug candidate for this syndrome.

Development and validation of stable ferroptosis- and pyroptosis-related signatures in predicting prognosis and immune status in breast cancer.

To develop and validate the predictive effects of stable ferroptosis- and pyroptosis-related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis- and pyroptosis-related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high- and low-risk groups. Kaplan-Meier analysis revealed a worse prognosis in the high-risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high-risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.

Reductant-dependent DNA-templated silver nanoparticle formation kinetics.

DNA molecules have been demonstrated to be good templates for producing silver nanoparticles (AgNPs), with the advantages of well-controlled sizes, shapes, and properties. Revealing the formation kinetics of DNA-templated AgNPs is crucial for their efficient synthesis. Herein, using magnetic tweezers, we studied the reduction kinetics of the Ag+-DNA structure and the subsequent nucleation kinetics by adding NaBH4, L-ascorbic acid, and sodium citrate solutions. At [Ag+] = 0.01 mM, the addition of NaBH4 solution with the same concentration resulted in the restoration of DNA. In contrast, by increasing the [NaBH4]/[Ag+] ratio (r) to 10 and 100, the DNA extension initially decreased rapidly and then increased, indicating nucleation-dissolution kinetics. With AgNO3 solutions of higher concentrations (0.1 mM and 1 mM), direct particle nucleation and growth kinetics were observed by adding a tenfold (r = 10) or a hundredfold (r = 100) amount of NaBH4, which were evidenced by a significant reduction in DNA extension. The reductant dependence of the kinetics was further investigated. Addition of L-ascorbic acid to the DNA-Ag+ solution yielded an increase-decrease kinetics that was different from that caused by NaBH4, suggesting that nucleation was not initially favored due to the lack of sufficient Ag atoms; while sodium citrate showed a weak nucleation-promoting ability to form AgNPs. We discussed the findings within the framework of classical nucleation theory, in which the supersaturation of the Ag atom is strongly influenced by multiple factors (including the reducing ability of the reductant), resulting in different kinetics.

Aucubin inhibits hepatic stellate cell activation through stimulating Nrf2/Smad7 axis.

AIM: Liver fibrosis may develop into end-stage liver disease if left unprevented. The study is attempting to identify a compound to ameliorate liver fibrosis progression with high efficiency and low toxicity, as well as to analyze its potential molecular mechanism. METHODS: The drug screening was performed using human hepatic stellate cell line LX-2 for identifying the compound as collagen I inhibitor. Primary Human hepatic stellate cells and LX-2 cell line were used to detect the antifibrotic function activity and molecular mechanism analysis in vitro. The CCl4-induced mouse experimental model was used to measure the amelioration in liver fibrosis. RESULTS: This study identified Aucubin, a natural compound, as a candidate for anti-liver fibrosis. Besides, Aucubin could inhibit the collagen I and α-SMA expressions in LX-2 cells and primary human hepatic stellate cells, as well as the cell proliferation. In terms of mechanism, Aucubin could upregulate Smad7 in hepatic stellate cells in a dose-dependent manner and block TGF-ß signaling. We also found that Nrf2 might be a direct target for the action of Aucubin, whose activation was necessary for Smad7 upregulation. In an in-vivo mouse model, Aucubin efficiency ameliorated the progression of CCl4-induced liver fibrosis, and reduced the hepatic levels of collagen deposition, transaminase and inflammatory cytokines. CONCLUSION: Capable of inhibiting the activation of hepatic stellate cells in vitro and in vivo, Aucubin may be a potential therapeutic candidate for liver fibrosis, which is dependent on the suppression of TGF-ß signaling through stimulating Nrf2/Smad7 axis.

Effect of PTGES3 on the Prognosis and Immune Regulation in Lung Adenocarcinoma.

Background: PTGES3 is upregulated in multiple cancer types and promotes tumorigenesis and progression. However, the clinical outcome and immune regulation of PTGES3 in lung adenocarcinoma (LUAD) are not fully understood. This study aimed to explore the expression level and prognostic value of PTGES3 and its correlation with potential immunotherapy in LUAD. Methods: All data were obtained from several databases, including the Cancer Genome Atlas database. Firstly, gene and protein expression of PTGES3 were analyzed using Tumor Immune Estimation Resource (TIMER), R software, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA). Thereafter, survival analysis was conducted using the R software, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Kaplan-Meier Plotter. In addition, gene alteration and mutation analyses were conducted using the cBio Cancer Genomics Portal (cBioPortal) and Catalog of Somatic Mutations in Cancer (COSMIC) databases. The molecular mechanisms associated with PTGES3 were assessed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), GeneMANIA, GEPIA2, and R software. Lastly, the role of PTGES3 in immune regulation in LUAD was investigated using TIMER, Tumor-Immune System Interaction Database (TISIDB), and SangerBox. Results: The gene and protein expression of PTGES3 were elevated in LUAD tissues and compared to the normal tissues, and the high expression of PTGES3 was correlated with cancer stage and tumor grade. Survival analysis revealed that overexpression of PTGES3 was associated with poor prognosis of LUAD patients. Moreover, gene alteration and mutation analysis revealed the occurrence of several types of PTGES3 gene alterations in LUAD. Moreover, co-expression analysis and cross-analysis revealed that three genes, including CACYBP, HNRNPC, and TCP1, were correlated and interacted with PTGES3. Functional analysis of these genes revealed that PTGES3 was primarily enriched in oocyte meiosis, progesterone-mediated oocyte maturation, and arachidonic acid metabolism pathways. Furthermore, we found that PTGES3 participated in a complex immune regulation network in LUAD. Conclusion: The current study indicated the crucial role of PTGES3 in LUAD prognosis and immune regulation. Altogether, our results suggested that PTGES3 could serve as a promising therapeutic and prognosis biomarker for the LUAD.

Radiomics of Spinal Metastases Originating From Primary Nonsmall Cell Lung Cancer or Breast Cancer and Ability to Predict Epidermal Growth Factor Receptor Mutation/Ki-67 Levels.

OBJECTIVES: The aims of the study are to explore spinal magnetic resonance imaging (MRI)-based radiomics to differentiate spinal metastases from primary nonsmall cell lung cancer (NSCLC) or breast cancer (BC) and to further predict the epidermal growth factor receptor (EGFR) mutation and Ki-67 expression level. METHODS: In total, 268 patients with spinal metastases from primary NSCLC (n = 148) and BC (n = 120) were enrolled between January 2016 and December 2021. All patients underwent spinal contrast-enhanced T1-weighted MRI before treatment. Two- and 3-dimensional radiomics features were extracted from the spinal MRI images of each patient. The least absolute shrinkage and selection operator regression were applied to identify the most important features related to the origin of the metastasis and the EGFR mutation and Ki-67 level. Radiomics signatures (RSs) were established using the selected features and evaluated using receiver operating characteristic curve analysis. RESULTS: We identified 6, 5, and 4 features from spinal MRI to develop Ori-RS, EGFR-RS, and Ki-67-RS for predicting the metastatic origin, EGFR mutation, and Ki-67 level, respectively. The 3 RSs performed well in the training (area under the receiver operating characteristic curves: Ori-RS vs EGFR-RS vs Ki-67-RS, 0.890 vs 0.793 vs 0.798) and validation (area under the receiver operating characteristic curves: Ori-RS vs EGFR-RS vs Ki-67-RS, 0.881 vs 0.744 vs 0.738) cohorts. CONCLUSIONS: Our study demonstrated the value of spinal MRI-based radiomics for identifying the metastatic origin and evaluating the EGFR mutation status and Ki-67 level in patients with NSCLC and BC, respectively, which may have the potential to guide subsequent individual treatment planning.

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest.

OBJECTIVE: To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point. METHODS: Twenty-five patients with BSP and 23 controls underwent resting-state functional MRI, seed-based functional connectivity (FC), correlation analysis, receiver operating characteristic curve (ROC) analysis, and support vector machine (SVM) were applied to process the data. RESULTS: Patients showed that the left medial prefrontal cortex (MPFC), left lingual gyrus, right cerebellar crus I, and right lingual gyrus/cerebellar crus I had enhanced FC with the left SMA, whereas the right inferior temporal gyrus (ITG) had enhanced FC with the right SMA relative to controls. The FC between the left MPFC and left SMA was positively correlated with symptomatic severity. The ROC analysis verified that the abnormal FCs demonstrated in this study can separate patients and controls at high sensitivity and specificity. SVM analysis exhibited that combined FCs of the left SMA were optimal for distinguishing patients and control group at the accuracy of 89.58%, with sensitivity of 92.00% and specificity of 86.96%. CONCLUSIONS: Several brain networks partake in the neurobiology of BSP. SMA plays a vital role in several brain networks and might be the key pathogenic factor in BSP. SIGNIFICANCE: Providing novel evidence for the engagement of the MPFC in the motor symptoms of BSP, enhancing credibility of the thesis that SMA regulates the neurobiology of BSP, and providing ideas of screening susceptible population of BSP using neuroimaging.

Comprehensive analysis of prediction of the EGFR mutation and subtypes based on the spinal metastasis from primary lung adenocarcinoma.

Purpose: To investigate the use of multiparameter MRI-based radiomics in the in-depth prediction of epidermal growth factor receptor (EGFR) mutation and subtypes based on the spinal metastasis in patients with primary lung adenocarcinoma. Methods: A primary cohort was conducted with 257 patients who pathologically confirmed spinal bone metastasis from the first center between Feb. 2016 and Oct. 2020. An external cohort was developed with 42 patients from the second center between Apr. 2017 and Jun. 2021. All patients underwent sagittal T1-weighted imaging (T1W) and sagittal fat-suppressed T2-weight imaging (T2FS) MRI imaging. Radiomics features were extracted and selected to build radiomics signatures (RSs). Machine learning classify with 5-fold cross-validation were used to establish radiomics models for predicting the EGFR mutation and subtypes. Clinical characteristics were analyzed with Mann-Whitney U and Chi-Square tests to identify the most important factors. Nomogram models were developed integrating the RSs and important clinical factors. Results: The RSs derived from T1W showed better performance for predicting the EGFR mutation and subtypes compared with those from T2FS in terms of AUC, accuracy and specificity. The nomogram models integrating RSs from combination of the two MRI sequences and important clinical factors achieved the best prediction capabilities in the training (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.829 vs. 0.885 vs.0.919), internal validation (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.760 vs. 0.777 vs.0.811), external validation (AUCs, EGFR vs. Exon 19 vs. Exon 21, 0.780 vs. 0.846 vs.0.818). DCA curves indicated potential clinical values of the radiomics models. Conclusions: This study indicated potentials of multi-parametric MRI-based radiomics to assess the EGFR mutation and subtypes. The proposed clinical-radiomics nomogram models can be considered as non-invasive tools to assist clinicians in making individual treatment plans.