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While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.
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BACKGROUND: To investigate the optimal B1,rms value of renal amide proton transfer-weighted (APTw) images and the reproducibility of this value, and to explore the utility of APT imaging of renal masses and kidney tissues. METHODS: APTw images with different B1,rms values were repeatedly recorded in 15 healthy volunteers to determine the optimal value. Two 4-point Likert scales (poor [1] to excellent [4]) were used to evaluate contour clarity and artifacts in masses and normal tissues. The APTw values of masses and normal tissues were then compared in evaluable images (contour clarity score > 1, artifacts score > 1). The APTw of malignant masses, normal tissues, and benign masses were calculated and compared with the Mann-Whitney U test. RESULTS: The optimal scanning parameter of B1,rms was 2 µT, and the APTw images had good agreement in the volunteers. Our study of APTw imaging examined 70 renal masses (13 benign, 57 malignant) and 49 normal kidneys (including those from 15 healthy volunteers). The mean APTw value for renal malignant masses (2.28(1.55)) was different from that for benign masses (0.91(1.30)) (P<0.001), renal cortex (1.30 (1.25)) (P<0.001), renal medulla (1.64 (1.33)) (P<0.05), and renal pelvis (5.49 (2.65)) (P<0.001). CONCLUSION: These preliminary data demonstrate that APTw imaging of the kidneys has potential use as an imaging biomarker for the differentiation of normal tissues, malignant masses, and benign masses.
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Purpose: The objective of this study was to create and validate a novel prediction model that incorporated both multi-modal radiomics features and multi-clinical features, with the aim of accurately identifying acute ischemic stroke (AIS) patients who faced a higher risk of poor outcomes. Methods: A cohort of 461 patients diagnosed with AIS from four centers was divided into a training cohort and a validation cohort. Radiomics features were extracted and selected from diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images to create a radiomic signature. Prediction models were developed using multi-clinical and selected radiomics features from DWI and ADC. Results: A total of 49 radiomics features were selected from DWI and ADC images by the least absolute shrinkage and selection operator (LASSO). Additionally, 20 variables were collected as multi-clinical features. In terms of predicting poor outcomes in validation set, the area under the curve (AUC) was 0.727 for the DWI radiomics model, 0.821 for the ADC radiomics model, 0.825 for the DWI + ADC radiomics model, and 0.808 for the multi-clinical model. Furthermore, a prediction model was built using all selected features, the AUC for predicting poor outcomes increased to 0.86. Conclusion: Radiomics features extracted from DWI and ADC images can serve as valuable biomarkers for predicting poor clinical outcomes in patients with AIS. Furthermore, when these radiomics features were combined with multi-clinical features, the predictive performance was enhanced. The prediction model has the potential to provide guidance for tailoring rehabilitation therapies based on individual patient risks for poor outcomes.
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OBJECTIVE: Non-small cell lung cancer (NSCLC) often exhibits resistance to radiotherapy, posing significant treatment challenges. This study investigates the role of SMAD3 in NSCLC, focusing on its potential in influencing radiosensitivity via the ITGA6/PI3K/Akt pathway. METHODS: The study utilized gene expression data from the GEO database to identify differentially expressed genes related to radiotherapy resistance in NSCLC. Using the GSE37745 dataset, prognostic genes were identified through Cox regression and survival analysis. Functional roles of target genes were explored using Gene Set Enrichment Analysis (GSEA) and co-expression analyses. Gene promoter methylation levels were assessed using databases like UALCAN, DNMIVD, and UCSC Xena, while the TISCH database provided insights into the correlation between target genes and CAFs. Experiments included RT-qPCR, Western blot, and immunohistochemistry on NSCLC patient samples, in vitro studies on isolated CAFs cells, and in vivo nude mouse tumor models. RESULTS: Fifteen key genes associated with radiotherapy resistance in NSCLC cells were identified. SMAD3 was recognized as an independent prognostic factor for NSCLC, linked to poor patient outcomes. High expression of SMAD3 was correlated with low DNA methylation in its promoter region and was enriched in CAFs. In vitro and in vivo experiments confirmed that SMAD3 promotes radiotherapy resistance by activating the ITGA6/PI3K/Akt signaling pathway. CONCLUSION: High expression of SMAD3 in NSCLC tissues, cells, and CAFs is closely associated with poor prognosis and increased radiotherapy resistance. SMAD3 is likely to enhance radiotherapy resistance in NSCLC cells by activating the ITGA6/PI3K/Akt signaling pathway.
Subject(s)
Cancer-Associated Fibroblasts , Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Animals , Mice , Humans , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/radiotherapy , Carcinoma, Non-Small-Cell Lung/metabolism , Lung Neoplasms/genetics , Lung Neoplasms/radiotherapy , Lung Neoplasms/metabolism , Cancer-Associated Fibroblasts/metabolism , Proto-Oncogene Proteins c-akt/metabolism , DNA Methylation/genetics , Phosphatidylinositol 3-Kinases/genetics , Phosphatidylinositol 3-Kinases/metabolism , Radiation Tolerance/genetics , Promoter Regions, Genetic/genetics , Gene Expression Profiling , Cell Line, Tumor , Smad3 Protein/genetics , Smad3 Protein/metabolismABSTRACT
Background: Distant metastasis is the leading cause of death in patients with rectal cancer. This study aims to comprehensively analyze the risk factors of distant metastasis in T3 T4 rectal cancer using magnetic resonance imaging (MRI), pathological features, and serum indicators. Methods: The clinicopathological data of 146 cases of T3 T4 rectal cancer after radical resection from January 2015 to March 2023 were retrospectively analyzed. Pre- and postoperative follow-up data of all cases were collected to screen for distant metastatic lesions. Univariate and multivariate Logistic regression methods were used to analyze the relationship between MRI features, pathological results, serum test indexes, and distant metastasis. Results: Of the 146 included patients, synchronous or metachronous distance metastasis was confirmed in 43 (29.4%) cases. The patients' baseline data and univariate analysis showed that mrEMVI, maximum tumor diameter, mr T Stage, pathological N stage, number of lymph node metastasis, cancer nodules, preoperative serum CEA, (Carcinoembryonic antigen) and CA199 were associated with distant metastasis. In the multiple logistic regression model, mrEMVI, pathological N stage, number of lymph node metastasis, maximum tumor diameter, and preoperative serum CEA were identified as independent risk factors for distant metastasis: mrEMVI [odds ratio (OR) = 3.06], pathological N stage (OR = 6.52 for N1 vs N0; OR = 63.47 for N2 vs N0), preoperative serum CEA (OR = 0.27), tumor maximum diameter (OR = 1.03), number of lymph nodes metastasis (OR = 0.62). And, the receiver operating characteristic (ROC) curve was plotted and the area under the curve was calculated (area under the curve [AUC) = 0.817, 95% CI = 0.744-0.890, P < .001]. Conclusions: mrEMVI, pathological N stage, number of lymph node metastasis, maximum tumor diameter and preoperative serum CEA are the independent risk factors for distant metastasis in T3 T4 rectal cancer. A comprehensive analysis of the risk factors for distant metastasis in rectal cancer can provide a reliable basis for formulating individualized treatment strategies, follow-up plans, and evaluating prognosis.
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Polycystic ovary syndrome (PCOS) is a highly heterogeneous and genetically complex endocrine disorder. Although the etiology remains mostly elusive, growing evidence suggests that abnormal changes of DNA methylation correlate well with systemic and tissue-specific dysfunctions in PCOS. Herein, a dehydroepiandrosterone-induced PCOS-like mouse model which has a similar metabolic and reproductive phenotype as human patients with PCOS was generated. It was used to experimentally validate the potential role of aberrant DNA methylation in PCOS in this study. Integrated DNA methylation and transcriptome analysis revealed the potential role of genomic DNA hypomethylation in transcription regulation of PCOS and identified several key candidate genes, including BMP4, Adcy7, Tnfaip3, and Fas, which were regulated by aberrant DNA hypomethylation. Moreover, i.p. injection of S-adenosylmethionine increased the overall DNA methylation level of PCOS-like mice and restored expression of the candidate genes to similar levels as the control, alleviating reproductive and metabolic abnormalities in PCOS-like mice. These findings provide direct evidence showing the importance of normal DNA methylation in epigenetic regulation of PCOS and potential targets for diagnosis and treatment of the disease.
Subject(s)
DNA Methylation , Polycystic Ovary Syndrome , Polycystic Ovary Syndrome/genetics , Polycystic Ovary Syndrome/metabolism , Polycystic Ovary Syndrome/pathology , DNA Methylation/genetics , Animals , Female , Mice , Disease Models, Animal , Transcription, Genetic , Epigenesis, Genetic , Gene Expression Regulation , Humans , Mice, Inbred C57BLABSTRACT
Inorganic metal halide perovskite CsPbX3 (X = I, Br, and Cl) nanocrystals (NCs) are rapidly developed due to their excellent photophysical properties and potential applications in lighting, lasers, and scintillators. However, the materials for growing perovskite NCs are insoluble or hydrolyzed in most green solvents, limiting their further development. Based on rational chemical analysis, an alkali-metal-assisted green-solvent synthesis method for in situ growth of CsPbBr3 NCs within SAPO-34 zeolite with bright luminescence is developed. Water is the only solvent used in the whole process. Surprisingly, by the synergistic effect of the channel structure of SAPO-34 and alkali-metal ions crystallization regulation, the CsPbBr3 NCs embedded in SAPO-34 assisted by Na+ emit bright blue light under ultraviolet illumination, with a 30 nm blue shift comparing to the CsPbBr3 NCs assisted by K+. Moreover, CsPbBr3 NCs can also be grown in mesoporous SiO2 SBA-15 and zeolites including ZSM-5, AlPO-5, and SOD, indicating that the method is universal for in situ growth of luminescent perovskite NCs in porous materials. This alkali-metal-assisted green-solvent synthesis provides a new strategy for developing high-quantum-yield, tunable-emission, and stable perovskite luminescent materials.
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BACKGROUND: Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB. PURPOSE: To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI. STUDY TYPE: Prospective. SUBJECTS: Eighty patients with UB lesions. FIELD STRENGTH/SEQUENCE: A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging. ASSESSMENT: Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTRasym). MTRasym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions. STATISTICAL TESTS: Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05. RESULTS: Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTRasym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10-3 mm2/s vs. 1.43 ± 0.22 × 10-3 mm2/s) than benign UB lesions. The MTRasym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722). DATA CONCLUSION: APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
Subject(s)
Diffusion Magnetic Resonance Imaging , Urinary Bladder Neoplasms , Humans , Female , Male , Middle Aged , Diffusion Magnetic Resonance Imaging/methods , Urinary Bladder Neoplasms/diagnostic imaging , Aged , Prospective Studies , Adult , Urinary Bladder/diagnostic imaging , Urinary Bladder/pathology , Aged, 80 and over , Magnetic Resonance Imaging/methods , Protons , Diagnosis, Differential , Sensitivity and Specificity , Amides , Reproducibility of Results , ROC CurveABSTRACT
OBJECTIVE: To investigate the potential of amide proton transfer-weighted (APTw) MRI in identifying benign and malignant renal tumors and to evaluate whether APTw MRI can add diagnostic value to diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Participants with renal tumor underwent preoperative multiparametric MRI, including APTw MRI and DWI. The APTw and apparent diffusion coefficient (ADC) of malignant tumors and benign tumors were calculated independently by two radiologists and compared. The value of the mean APTw and the mean ADC for differentiating malignant and benign tumors was evaluated by receiver operating characteristic analysis. RESULTS: In total, 65 participants (mean age, 59 years ±14; 41 men) were evaluated: 54 with malignant and 11 with benign renal tumors. Malignant renal tumors showed higher mean APTw values [2.03% (1.63) vs 1.00% (1.60); P < 0.01] and lower mean ADC values (1.22 × 10-3 mm2/s ± 0.37 vs 1.51 × 10-3 mm2/s ± 0.37; P < 0.05) than benign renal tumors. The area under the receiver operating characteristic curve (AUC) of APTw, ADC and the combination of them for the identification of benign and malignant renal tumors was 0.78(95% CI: 0.66, 0.87; P < 0.001),0.70(95% CI: 0.54, 0.86; P < 0.05) and 0.79 (95% CI: 0.67, 0.88; P < 0.001). The optimal cutoff value for mean APTw was 2.14% (sensitivity, 74%; specificity, 73%). There was no difference between these three parameters for differentiating malignant from benign renal tumors (P > 0.05). CONCLUSION: The APTw MRI has the potential use as an imaging biomarker for renal malignant and benign tumors.