Identification of the ferroptosis-related prognostic gene signature in mesothelioma
Gene. 2024 Apr 24:148498. doi: 10.1016/j.gene.2024.148498. Online ahead of print.ABSTRACTMesothelioma, an uncommon yet highly aggressive malignant neoplasm, presents challenges in the effectiveness of current therapeutic approaches. Ferroptosis, a non-apoptotic mechanism of cellular demise, exhibits a substantial association with the progression of diverse cancer forms. It is important to acknowledge that there exists a significant association between ferroptosis and the advancement of various forms of cancer. Nevertheless, the precise role of ferroptosis regulatory factors within the context of mesothelioma remains enigma...
Source: Gene - April 26, 2024 Category: Genetics & Stem Cells Authors: Zairui Wang Jialin Huang None MinYang Liren Fu Shijie Liu Jianghua Huang Jingjing Han Xiaohui Zhao Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: The American Journal of Pathology - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: Am J Pathol - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Synergistic impact of bioavailable PHEs and alkalinity on microbial diversity and traits in agricultural soil adjacent to chromium-asbestos mines
This study aims to explore the combined effects of soil alkalinity and bioavailable PHEs on microbial diversity and traits in agricultural soil adjacent to a chromium-asbestos mining area. By employing a comprehensive analysis, this study indicated that microbiological attributes were reduced in contaminated areas (zone 1), whereas both the levels of bioavailable PHEs (CrWs: 31.08 mg/kg, NiWs: 13.90 mg/kg) and alkalinity indices (CROSS, MCAR, MH) were significantly higher. The spatial distribution of soil alkalinity and bioavailable PHEs, primarily originating from chromium-asbestos mines, has been determined. This study a...
Source: Environmental Pollution - April 24, 2024 Category: Environmental Health Authors: Sonali Banerjee Saibal Ghosh Shreya Chakraborty Dibyendu Sarkar Rupali Datta Pradip Bhattacharyya Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: The American Journal of Pathology - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: Am J Pathol - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Synergistic impact of bioavailable PHEs and alkalinity on microbial diversity and traits in agricultural soil adjacent to chromium-asbestos mines
This study aims to explore the combined effects of soil alkalinity and bioavailable PHEs on microbial diversity and traits in agricultural soil adjacent to a chromium-asbestos mining area. By employing a comprehensive analysis, this study indicated that microbiological attributes were reduced in contaminated areas (zone 1), whereas both the levels of bioavailable PHEs (CrWs: 31.08 mg/kg, NiWs: 13.90 mg/kg) and alkalinity indices (CROSS, MCAR, MH) were significantly higher. The spatial distribution of soil alkalinity and bioavailable PHEs, primarily originating from chromium-asbestos mines, has been determined. This study a...
Source: Environmental Pollution - April 24, 2024 Category: Environmental Health Authors: Sonali Banerjee Saibal Ghosh Shreya Chakraborty Dibyendu Sarkar Rupali Datta Pradip Bhattacharyya Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: The American Journal of Pathology - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers...
Source: Am J Pathol - April 24, 2024 Category: Pathology Authors: Yige Yin Qianwen Cui Jiarong Zhao Qiang Wu Qiuyan Sun Hong-Qiang Wang Wulin Yang Source Type: research
Combination of calretinin, MALAT1, and GAS5 as a potential prognostic biomarker to predict disease progression in surgically treated mesothelioma patients
Pleural mesothelioma is a fatal cancer of the pleural cavity, primarily caused by asbestos. Overall survival (OS) after diagnosis is poor and the long latency period of the disease after asbestos exposure is responsible for the still increasing incidence of mesothelioma worldwide [1,2]. Several options are available for the treatment of pleural mesothelioma to improve OS, ranging from multimodal therapy including surgery and chemotherapy to, chemotherapy or immunotherapy [3,4]. Monitoring the disease progression after treatment is essential, but imaging techniques are of limited value in mesothelioma, in contrast to severa...
Source: Lung Cancer - April 24, 2024 Category: Cancer & Oncology Authors: Laura V. Klotz, Swaantje Casjens, Georg Johnen, Dirk Taeger, Alexander Brik, Florian Eichhorn, Laura F örster, Nina Kaiser, Thomas Muley, Christa Stolp, Marc Schneider, Jan Gleichenhagen, Thomas Brüning, Hauke Winter, Martin Eichhorn, Daniel G. Weber Tags: Research Paper Source Type: research
Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells
This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. (Source: American Journal of Pathology)
Source: American Journal of Pathology - April 21, 2024 Category: Pathology Authors: Yige Yin, Qianwen Cui, Jiarong Zhao, Qiang Wu, Qiuyan Sun, Hong-qiang Wang, Wulin Yang Tags: Regular Article Source Type: research
Genomic characterization and detection of potential therapeutic targets for peritoneal mesothelioma in current practice
Clin Exp Med. 2024 Apr 20;24(1):80. doi: 10.1007/s10238-024-01342-y.ABSTRACTPeritoneal mesothelioma (PeM) is an aggressive tumor with limited treatment options. The current study aimed to evaluate the value of next generation sequencing (NGS) of PeM samples in current practice. Foundation Medicine F1CDx NGS was performed on 20 tumor samples. This platform assesses 360 commonly somatically mutated genes in solid tumors and provides a genomic signature. Based on the detected mutations, potentially effective targeted therapies were identified. NGS was successful in 19 cases. Tumor mutational burden (TMB) was low in 10 cases, ...
Source: Clinical Lung Cancer - April 20, 2024 Category: Cancer & Oncology Authors: Job P van Kooten Michelle V Dietz Hendrikus Jan Dubbink Cornelis Verhoef Joachim G J V Aerts Eva V E Madsen Jan H von der Th üsen Source Type: research
Analysis of invasive diagnostic techniques for pathological confirmation of pleural mesothelioma
CONCLUSIONS: In our review, pleural biopsy performed with image guidance was the test that had the highest diagnostic yield, so it should be considered as the initial invasive test for the study of mesothelioma.PMID:38642958 | DOI:10.1016/j.rxeng.2023.03.005 (Source: Radiologia)
Source: Radiologia - April 20, 2024 Category: Radiology Authors: H G ómez Herrero B Álvarez Galván Source Type: research
Analysis of invasive diagnostic techniques for pathological confirmation of pleural mesothelioma
CONCLUSIONS: In our review, pleural biopsy performed with image guidance was the test that had the highest diagnostic yield, so it should be considered as the initial invasive test for the study of mesothelioma.PMID:38642958 | DOI:10.1016/j.rxeng.2023.03.005 (Source: Radiologia)
Source: Radiologia - April 20, 2024 Category: Radiology Authors: H G ómez Herrero B Álvarez Galván Source Type: research
Analysis of invasive diagnostic techniques for pathological confirmation of pleural mesothelioma
CONCLUSIONS: In our review, pleural biopsy performed with image guidance was the test that had the highest diagnostic yield, so it should be considered as the initial invasive test for the study of mesothelioma.PMID:38642958 | DOI:10.1016/j.rxeng.2023.03.005 (Source: Radiologia)
Source: Radiologia - April 20, 2024 Category: Radiology Authors: H G ómez Herrero B Álvarez Galván Source Type: research
