1
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Chen M, Huang M, Chen X, Lin X, Chen X. Multiomics blueprint of PANoptosis in deciphering immune characteristics and prognosis stratification of glioma patients. J Gene Med 2024; 26:e3621. [PMID: 37997255 DOI: 10.1002/jgm.3621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 10/10/2023] [Accepted: 10/15/2023] [Indexed: 11/25/2023] Open
Abstract
BACKGROUND As the most prevalent primary brain tumor in adults, glioma accounts for the majority of all central nervous system malignant tumors. The concept of PANoptosis is a relatively new, underlining the interconnection and synergy among three distinct pathways: pyroptosis, apoptosis and necroptosis. METHODS We performed single-cell annotations of glioma cells and determined crucial signaling pathways through cell chat analysis. Using least absolute shrinkage and selection operator (LASSO) and Cox analyses, we identified a gene set with prognostic values. Our model was validated using independent external cohort. In addition, we employed single-sample gene set enrichment analysis and xCell analyses to describe the detailed profile of infiltrated immune cells and depicted the gene mutation landscape in the two groups. RESULTS We identified seven distinct cell clusters in glioma samples, including oligodendrocyte precursor cells (OPCs), myeloid cells, tumor cells, oligodendrocytes, astrocytes, vascular cells and neuronal cells. We found that myeloid cells showed the highest PANoptosis activity. An intense mutual cell communication pattern between the tumor cells and OPCs and oligodendrocytes was observed. Differentially expressed genes between the high-PANoptosis and low-PANoptosis cell groups were obtained, which were enriched to actin cytoskeleton, cell adhesion molecules and gamma R-mediated phagocytosis pathways. We determined a set of five genes of prognostic significance: SAA1, SLPI, DCX, S100A8 and TNR. The prognostic differences between the two groups in the internal and external sets were found to be statistically significant. We found a marked correlation between S100A8 and activated dendritic cell, macrophage, mast cell, myeloid derived suppressor cell and Treg infiltration. Moreover, we have observed a significant increase of PTEN mutation in the high risk (HR) group of glioma patients. CONCLUSIONS In the present study, we have constructed a prognostic model that is based on the PANoptosis, and we have demonstrated its significant efficacy in stratifying patients with glioma. This innovative prognostic model offers novel insights into precision immune treatments that could be used to combat this disease and improve patient outcomes, thereby providing a new avenue for personalized treatment options.
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Affiliation(s)
- Maohua Chen
- Department of Neurosurgery, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou Central Hospital, Zhejiang, China
| | - Min Huang
- Department of Obstetrics and Gynecology, E Gang Hospital, Hubei, China
| | - Xiaoxiang Chen
- Department of Neurosurgery, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou Central Hospital, Zhejiang, China
| | - Xiaoyu Lin
- Department of Neurosurgery, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou Central Hospital, Zhejiang, China
| | - Xianglin Chen
- Department of Neurosurgery, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Guangzhou, China
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2
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He Z, Gu Y, Yang H, Fu Q, Zhao M, Xie Y, Liu Y, Du W. Identification and verification of a novel anoikis-related gene signature with prognostic significance in clear cell renal cell carcinoma. J Cancer Res Clin Oncol 2023; 149:11661-11678. [PMID: 37402968 DOI: 10.1007/s00432-023-05012-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/19/2023] [Indexed: 07/06/2023]
Abstract
PURPOSE Clear cell renal cell carcinomas (ccRCCs) are the most common form of renal cancer in the world. The loss of extracellular matrix (ECM) stimulates cell apoptosis, known as anoikis. A resistance to anoikis in cancer cells is believed to contribute to tumor malignancy, particularly metastasis; however, the potential influence of anoikis on the prognosis of ccRCC patients is not fully understood. METHODS In this study, anoikis-related genes (ARGs) with discrepant expression were selected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The anoikis-related gene signature (ARS) was built using a combination of the univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. ARS was also evaluated for their prognostic value. We explored the tumor microenvironment and enrichment pathways between different clusters of ccRCC. We also examined differences in clinical characteristics, immune cell infiltration and drug sensitivity between the high- and low-risk sets. In addition, we utilized three external databases and quantitative real-time polymerase chain reaction (qRT-PCR) to validate the expression and prognosis of ARGs. RESULTS Eight ARGs (PLAUR, HMCN1, CDKN2A, BID, GLI2, PLG, PRKCQ and IRF6) were identified as anoikis-related prognostic factors. According to Kaplan-Meier (KM) analysis, ccRCC patients with high-risk ARGs have a worse prognosis. The risk score was found to be a significant independent prognostic indicator. According to tumor microenvironment (TME) scores, stromal score, immune score, and estimated score of the high-risk group were superior to those of the low-risk group. There were significant differences between the two groups regarding the amount of infiltrated immune cells, immune checkpoint expression as well as drug sensitivity. A nomogram was constructed using ccRCC clinical features and risk scores. The signature and the nomogram both performed well in predicting overall survival (OS) for ccRCC patients. According to a decision curve analysis (DCA), clinical treatment options for patients with ccRCC could be improved using this model. CONCLUSION The results of validation from external databases and qRT-PCR were basically agreement with findings in TCGA and GEO databases. The ARS serving as biomarkers may provide an important reference for individual therapy of ccRCC patients.
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Affiliation(s)
- Zhiqiang He
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Yufan Gu
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Huan Yang
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Qian Fu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Maofang Zhao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Yuhan Xie
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China
| | - Yi Liu
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
| | - Wenlong Du
- Department of Bioinformatics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
- Department of Biophysics, School of Life Sciences, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
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Apanovich N, Matveev A, Ivanova N, Burdennyy A, Apanovich P, Pronina I, Filippova E, Kazubskaya T, Loginov V, Braga E, Alimov A. Prediction of Distant Metastases in Patients with Kidney Cancer Based on Gene Expression and Methylation Analysis. Diagnostics (Basel) 2023; 13:2289. [PMID: 37443682 DOI: 10.3390/diagnostics13132289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 06/28/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive histological type of cancer in this location. Distant metastases are present in approximately 30% of patients at the time of first examination. Therefore, the ability to predict the occurrence of metastases in patients at early stages of the disease is an urgent task aimed at personalized treatment. Samples of tumor and paired histologically normal kidney tissue from patients with metastatic and non-metastatic ccRCC were studied. Gene expression was analyzed using real-time PCR. The level of gene methylation was evaluated using bisulfite conversion followed by quantitative methylation-specific PCR. Two groups of genes were analyzed in this study. The first group includes genes whose expression is significantly reduced during metastasis: CA9, NDUFA4L2, EGLN3, and BHLHE41 (p < 0.001, ROC analysis). The second group includes microRNA genes: MIR125B-1, MIR137, MIR375, MIR193A, and MIR34B/C, whose increased methylation levels are associated with the development of distant metastases (p = 0.002 to <0.001, ROC analysis). Based on the data obtained, a combined panel of genes was formed to identify patients whose tumors have a high metastatic potential. The panel can estimate the probability of metastasis with an accuracy of up to 92%.
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Affiliation(s)
- Natalya Apanovich
- Research Centre for Medical Genetics, 1 Moskvorechye St., Moscow 115522, Russia
| | - Alexey Matveev
- Federal State Budgetary Institution (N.N. Blokhin National Medical Research Center of Oncology) of the Ministry of Health of the Russian Federation, 24 Kashirskoe Shosse, Moscow 115478, Russia
| | - Natalia Ivanova
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Alexey Burdennyy
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Pavel Apanovich
- Research Centre for Medical Genetics, 1 Moskvorechye St., Moscow 115522, Russia
| | - Irina Pronina
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Elena Filippova
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Tatiana Kazubskaya
- Federal State Budgetary Institution (N.N. Blokhin National Medical Research Center of Oncology) of the Ministry of Health of the Russian Federation, 24 Kashirskoe Shosse, Moscow 115478, Russia
| | - Vitaly Loginov
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Eleonora Braga
- Research Centre for Medical Genetics, 1 Moskvorechye St., Moscow 115522, Russia
- Institute of General Pathology and Pathophysiology, Baltijskaya St. 8, Moscow 125315, Russia
| | - Andrei Alimov
- Research Centre for Medical Genetics, 1 Moskvorechye St., Moscow 115522, Russia
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4
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Chen Y, Zhang P, Liao J, Cheng J, Zhang Q, Li T, Zhang H, Jiang Y, Zhang F, Zeng Y, Mo L, Yan H, Liu D, Zhang Q, Zou C, Wei GH, Mo Z. Single-cell transcriptomics reveals cell type diversity of human prostate. J Genet Genomics 2022; 49:1002-1015. [PMID: 35395421 DOI: 10.1016/j.jgg.2022.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/06/2022] [Accepted: 03/16/2022] [Indexed: 12/29/2022]
Abstract
Extensive studies have been performed to describe the phenotypic changes occurring during malignant transformation of the prostate. However, the cell types and associated changes that contribute to the development of prostate diseases and cancer remain elusive, largely due to the heterogeneous composition of prostatic tissues. Here, we conduct a comprehensive evaluation of four human prostate tissues by single-cell RNA sequencing (scRNA-seq) to analyze their cellular compositions. We identify 18 clusters of cell types, each with distinct gene expression profiles and unique features; of these, one cluster of epithelial cells (Ep) is found to be associated with immune function. In addition, we characterize a special cluster of fibroblasts and aberrant signaling changes associated with prostate cancer (PCa). Moreover, we provide insights into the epithelial changes that occur during the cellular senescence and aging. These results expand our understanding of the unique functional associations between the diverse prostatic cell types and the contributions of specific cell clusters to the malignant transformation of prostate tissues and PCa development.
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Affiliation(s)
- Yang Chen
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Peng Zhang
- Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education & Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 201114, China
| | - Jinling Liao
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Jiwen Cheng
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Qin Zhang
- Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland
| | - Tianyu Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Haiying Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Yonghua Jiang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Fangxing Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Yanyu Zeng
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Linjian Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Haibiao Yan
- Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Deyun Liu
- Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Qinyun Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Chunlin Zou
- Key Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Center for Translational Medicine and School of Preclinical Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China.
| | - Gong-Hong Wei
- Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education & Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 201114, China; Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland.
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China; Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China.
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5
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Apanovich N, Apanovich P, Mansorunov D, Kuzevanova A, Matveev V, Karpukhin A. The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer. Front Oncol 2021; 11:615787. [PMID: 34046336 PMCID: PMC8144703 DOI: 10.3389/fonc.2021.615787] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 03/25/2021] [Indexed: 12/18/2022] Open
Abstract
We aimed to identify and investigate genes that are essential for the development of clear cell renal cell carcinoma (ccRCC) and sought to shed light on the mechanisms of its progression and create prognostic markers for the disease. We used real-time PCR to study the expression of 20 genes that were preliminarily selected based on their differential expression in ccRCC, in 68 paired tumor/normal samples. Upon ccRCC progression, seven genes that showed an initial increase in expression showed decreased expression. The genes whose expression levels did not significantly change during progression were associated mainly with metabolic and inflammatory processes. The first group included CA9, NDUFA4L2, EGLN3, BHLHE41, VWF, IGFBP3, and ANGPTL4, whose expression levels were coordinately decreased during tumor progression. This expression coordination and gene function is related to the needs of tumor development at different stages. Specifically, the high correlation coefficient of EGLN3 and NDUFA4L2 expression may indicate the importance of the coordinated regulation of glycolysis and mitochondrial metabolism. A panel of CA9, EGLN3, BHLHE41, and VWF enabled the prediction of survival for more than 3.5 years in patients with ccRCC, with a probability close to 90%. Therefore, a coordinated change in the expression of a gene group during ccRCC progression was detected, and a new panel of markers for individual survival prognosis was identified.
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Affiliation(s)
- Natalya Apanovich
- Laboratory of Molecular Genetics of Complex Inherited Diseases, Research Centre for Medical Genetics, Moscow, Russia
| | - Pavel Apanovich
- Laboratory of Molecular Genetics of Complex Inherited Diseases, Research Centre for Medical Genetics, Moscow, Russia
| | - Danzan Mansorunov
- Laboratory of Molecular Genetics of Complex Inherited Diseases, Research Centre for Medical Genetics, Moscow, Russia
| | - Anna Kuzevanova
- Laboratory of Molecular Genetics of Complex Inherited Diseases, Research Centre for Medical Genetics, Moscow, Russia
| | - Vsevolod Matveev
- Department of Oncourology, Federal State Budgetary Institution "N.N. Blokhin National Medical Research Center of Oncology" of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Alexander Karpukhin
- Laboratory of Molecular Genetics of Complex Inherited Diseases, Research Centre for Medical Genetics, Moscow, Russia
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6
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Ren H, He G, Lu Z, He Q, Li S, Huang Z, Chen Z, Cao C, Wang A. Arecoline induces epithelial-mesenchymal transformation and promotes metastasis of oral cancer by SAA1 expression. Cancer Sci 2021; 112:2173-2184. [PMID: 33626219 PMCID: PMC8177782 DOI: 10.1111/cas.14866] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 02/16/2021] [Accepted: 02/20/2021] [Indexed: 12/15/2022] Open
Abstract
Arecoline, the main alkaloid of areca nut, is well known for its role in inducing submucosal fibrosis and oral squamous cell carcinoma (OSCC), however the mechanism remains unclear. The aim of this study was to establish an arecoline‐induced epithelial‐mesenchymal transformation (EMT) model of OSCC cells and to investigate the underlying mechanisms. CAL33 and UM2 cells were induced with arecoline to establish an EMT cell model and perform RNA‐sequence screening. Luminex multiplex cytokine assays, western blot, and RT‐qPCR were used to investigate the EMT mechanism. Arecoline at a concentration of 160 μg/ml was used to induce EMT in OSCC cells, which was confirmed using morphological analysis, transwell assays, and EMT marker detection. RNA‐sequence screening and Luminex multiplex cytokine assays showed that many inflammatory cytokines (such as serum amyloid A1 [SAA1], interleukin [IL]‐6, IL‐36G, chemokine [CCL]2, and CCL20) were significantly altered during arecoline‐induced EMT. Of these cytokines, SAA1 was the most highly upregulated. SAA1 overexpression induced EMT and promoted the migration and invasion of CAL33 cells, while SAA1 knockdown attenuated arecoline‐induced EMT. Moreover, arecoline enhanced cervical lymph node metastasis in an orthotopic xenograft model of the tongue established using BALB/c nude mice. Our findings revealed that arecoline induced EMT and enhanced the metastatic capability of OSCC by the regulation of inflammatory cytokine secretion, especially that of SAA1. Our study provides a basis for understanding the mechanism of OSCC metastasis and suggests possible therapeutic targets to prevent the occurrence and development of OSCC associated with areca nut chewing.
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Affiliation(s)
- Hui Ren
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Guoqin He
- Department of Stomatology, Maoming People's Hospital, Maoming, People's Republic of China
| | - Zhiyuan Lu
- Department of Oral and Maxillofacial Surgery, Stomatology Medical Center, Guangzhou Women and Children's Medical Center, Guangzhou, People's Republic of China
| | - Qianting He
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Shuai Li
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Zhexun Huang
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Zheng Chen
- Department of Stomatology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Congyuan Cao
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Anxun Wang
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
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7
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Giulietti M, Cecati M, Sabanovic B, Scirè A, Cimadamore A, Santoni M, Montironi R, Piva F. The Role of Artificial Intelligence in the Diagnosis and Prognosis of Renal Cell Tumors. Diagnostics (Basel) 2021; 11:206. [PMID: 33573278 PMCID: PMC7912267 DOI: 10.3390/diagnostics11020206] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/22/2021] [Accepted: 01/26/2021] [Indexed: 02/07/2023] Open
Abstract
The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.
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Affiliation(s)
- Matteo Giulietti
- Department of Specialistic Clinical & Odontostomatological Sciences, Polytechnic University of Marche, 60126 Ancona, Italy; (M.G.); (M.C.); (B.S.)
| | - Monia Cecati
- Department of Specialistic Clinical & Odontostomatological Sciences, Polytechnic University of Marche, 60126 Ancona, Italy; (M.G.); (M.C.); (B.S.)
| | - Berina Sabanovic
- Department of Specialistic Clinical & Odontostomatological Sciences, Polytechnic University of Marche, 60126 Ancona, Italy; (M.G.); (M.C.); (B.S.)
| | - Andrea Scirè
- Department of Life and Environmental Sciences, Polytechnic University of Marche, 60126 Ancona, Italy;
| | - Alessia Cimadamore
- Section of Pathological Anatomy, Polytechnic University of Marche, United Hospitals, 60126 Ancona, Italy; (A.C.); (R.M.)
| | - Matteo Santoni
- Oncology Unit, Macerata Hospital, 62012 Macerata, Italy;
| | - Rodolfo Montironi
- Section of Pathological Anatomy, Polytechnic University of Marche, United Hospitals, 60126 Ancona, Italy; (A.C.); (R.M.)
| | - Francesco Piva
- Department of Specialistic Clinical & Odontostomatological Sciences, Polytechnic University of Marche, 60126 Ancona, Italy; (M.G.); (M.C.); (B.S.)
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8
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Liu Y, Nie X, Zhu J, Wang T, Li Y, Wang Q, Sun Z. NDUFA4L2 in smooth muscle promotes vascular remodeling in hypoxic pulmonary arterial hypertension. J Cell Mol Med 2021; 25:1221-1237. [PMID: 33340241 PMCID: PMC7812284 DOI: 10.1111/jcmm.16193] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 11/10/2020] [Accepted: 11/21/2020] [Indexed: 12/12/2022] Open
Abstract
Pulmonary arterial hypertension (PAH) is characterized by a progressive increase in pulmonary vascular resistance and obliterative pulmonary vascular remodelling (PVR). The imbalance between the proliferation and apoptosis of pulmonary artery smooth muscle cells (PASMCs) is an important cause of PVR leading to PAH. Mitochondria play a key role in the production of hypoxia-induced pulmonary hypertension (HPH). However, there are still many issues worth studying in depth. In this study, we demonstrated that NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4 like 2 (NDUFA4L2) was a proliferation factor and increased in vivo and in vitro through various molecular biology experiments. HIF-1α was an upstream target of NDUFA4L2. The plasma levels of 4-hydroxynonene (4-HNE) were increased both in PAH patients and hypoxic PAH model rats. Knockdown of NDUFA4L2 decreased the levels of malondialdehyde (MDA) and 4-HNE in human PASMCs in hypoxia. Elevated MDA and 4-HNE levels might be associated with excessive ROS generation and increased expression of 5-lipoxygenase (5-LO) in hypoxia, but this effect was blocked by siNDUFA4L2. Further research found that p38-5-LO was a downstream signalling pathway of PASMCs proliferation induced by NDUFA4L2. Up-regulated NDUFA4L2 plays a critical role in the development of HPH, which mediates ROS production and proliferation of PASMCs, suggesting NDUFA4L2 as a potential new therapeutic target for PAH.
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MESH Headings
- Aldehydes/metabolism
- Animals
- Arachidonate 5-Lipoxygenase/metabolism
- Cell Hypoxia
- Cell Proliferation
- Disease Models, Animal
- Electron Transport Complex I/genetics
- Electron Transport Complex I/metabolism
- Endothelial Cells/metabolism
- Gene Expression Regulation
- Gene Silencing
- Humans
- Hypoxia/complications
- Hypoxia/physiopathology
- Male
- Malondialdehyde/metabolism
- Models, Biological
- Muscle, Smooth, Vascular/pathology
- Muscle, Smooth, Vascular/physiopathology
- Myocytes, Smooth Muscle/metabolism
- Myocytes, Smooth Muscle/pathology
- Oxidation-Reduction
- Oxygen Consumption
- Pulmonary Arterial Hypertension/complications
- Pulmonary Arterial Hypertension/metabolism
- Pulmonary Arterial Hypertension/pathology
- Pulmonary Arterial Hypertension/physiopathology
- Pulmonary Artery/pathology
- RNA, Messenger/genetics
- RNA, Messenger/metabolism
- Rats, Wistar
- Reactive Oxygen Species/metabolism
- Vascular Remodeling/genetics
- p38 Mitogen-Activated Protein Kinases/metabolism
- Rats
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Affiliation(s)
- Yun Liu
- Department of Pharmacy, The First People's Hospital of Lianyungang, Lianyungang, China
- Department of Pharmacy, The Affiliated Lianyungang Hospital of Xuzhou Medical University/The First People's Hospital of Lianyungang, Lianyungang, China
| | - Xiaowei Nie
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China
- Lung Transplant Group, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Jinquan Zhu
- Department of Pharmacy, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Tianyan Wang
- Department of Pharmacy, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Yanli Li
- Department of Pharmacy, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Qian Wang
- Department of Anesthesiology, Children's Hospital of Soochow University, Suzhou, China
| | - Zengxian Sun
- Department of Pharmacy, The First People's Hospital of Lianyungang, Lianyungang, China
- Department of Pharmacy, The Affiliated Lianyungang Hospital of Xuzhou Medical University/The First People's Hospital of Lianyungang, Lianyungang, China
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9
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Zhang D, Qian C, Wei H, Qian X. Identification of the Prognostic Value of Tumor Microenvironment-Related Genes in Esophageal Squamous Cell Carcinoma. Front Mol Biosci 2020; 7:599475. [PMID: 33381521 PMCID: PMC7767869 DOI: 10.3389/fmolb.2020.599475] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 11/24/2020] [Indexed: 01/04/2023] Open
Abstract
Background: Esophageal squamous cell carcinoma (ESCC) is the most prevalent histological type of esophageal cancer, but there is a lack of definite prognostic markers for this cancer. Methods: We used the ESTIMATE algorithm to access the tumor microenvironment (TME) of ESCC cases deposited in the TCGA database, and identified TME-related prognostic genes using Cox regression analysis. A least absolute shrinkage and selector operation or LASSO algorithm was used to identify key prognostic genes. Risk scores were calculated, and a clinical predictive model was constructed to evaluate the prognostic value of TME-related genes. Results: We found that high immune and stromal scores were significantly associated with poor overall survival (p < 0.05). We identified a total of 1,151 TME-related differently expression genes, among which 67 were prognosis-related genes. Through the LASSO method, 13 key prognostic genes were selected, namely, ADAMTS16, LOC51089, CH25H, CORO2B, DLGAP1, GYS2, HAL, MXRA8, NPTX1, OTX1, RET, SLC24A2, and SPI1, and a 13-gene risk score was constructed. A higher score was indicative of a poorer prognosis than a lower risk score (hazard ratio = 8.21, 95% confidence interval: 2.56-26.31; P < 0.001). The risk score was significantly correlated with immune/stromal scores and various types of infiltrating immune cells, including CD8 cells, regulatory T cells, and resting macrophages. Conclusion: We characterized the tumor microenvironment in ESCC, and identified the key prognosis genes. The risk score based on the expression profiles of these genes is proposed as an indicator of TME status and is instrumental in predicting patient prognosis.
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Affiliation(s)
- Donglei Zhang
- Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Changlin Qian
- Department of General Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Huabing Wei
- Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Xiaozhe Qian
- Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
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