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Yue J, Guo H, Ma J, Shi W, Wu Y. Novel prognostic signature for lung adenocarcinoma based on immune-related mRNA pairs. Heliyon 2024; 10:e24397. [PMID: 38317924 PMCID: PMC10839877 DOI: 10.1016/j.heliyon.2024.e24397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 12/16/2023] [Accepted: 01/08/2024] [Indexed: 02/07/2024] Open
Abstract
Lung adenocarcinoma (LUAD) is a highly lethal malignant tumor. While the involvement of multiple mRNAs in the progression of LUAD is well established, the potential diagnostic value of immune-related mRNAs (irmRNAs) in LUAD remains largely unexplored. In this study, we utilized RNA-seq, clinical data, and immune-related gene information from LUAD patients to identify differentially expressed immune-related mRNAs (DEirmRNAs) and developed a predictive risk model based on specific DEirmRNA pairs closely linked with patient prognosis. We classified patients into high-risk and low-risk groups and analyzed factors such as survival rate, clinical characteristics, gene enrichment, immune cell infiltration, tumor mutation load, and drug susceptibility. We confirmed the expression levels of these DEirmRNAs in tumor tissues using qRT-PCR assay. Our results showed that the low-risk group had a longer survival time and lower tumor mutation burden (TMB) and microsatellite instability (MSI) compared to the high-risk group. The high-risk group also had a significant reduction in the number of certain immune cells and a lower half-maximum inhibitor concentration (IC50). We identified specific DEirmRNA pairs that were up-regulated or down-regulated in tumor tissues compared to adjacent tissues. Our prognostic risk model based on DEirmRNA pairs could be used to predict the prognosis of LUAD patients and provide reference for better treatment.
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Affiliation(s)
- Jiawei Yue
- Department of Orthopaedics, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China
| | - Hui Guo
- Department of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China
| | - Jinhong Ma
- Department of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China
| | - Weifeng Shi
- Department of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China
| | - Yumin Wu
- Department of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China
- Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices Institute of Nano and Soft Materials (FUNSOM) College of Nano Science &Technology (CNST) Suzhou, Jiangsu, 215123, China
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2
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Xing X, Liu M, Wang X, Guo Q, Wang H, Wang W. FKBP3 aggravates the malignant phenotype of diffuse large B-cell lymphoma by PARK7-mediated activation of Wnt/β-catenin signalling. J Cell Mol Med 2024; 28:e18041. [PMID: 37987202 PMCID: PMC10805489 DOI: 10.1111/jcmm.18041] [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: 04/02/2023] [Revised: 10/15/2023] [Accepted: 10/19/2023] [Indexed: 11/22/2023] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) is difficult to treat due to the high recurrence rate and therapy intolerance, so finding potential therapeutic targets for DLBCL is critical. FK506-binding protein 3 (FKBP3) contributes to the progression of various cancers and is highly expressed in DLBCL, but the role of FKBP3 in DLBCL and its mechanism are not clear. Our study demonstrated that FKBP3 aggravated the proliferation and stemness of DLBCL cells, and tumour growth in a xenograft mouse model. The interaction between FKBP3 and parkinsonism associated deglycase (PARK7) in DB cells was found using co-immunoprecipitation assay. Knockdown of FKBP3 enhanced the degradation of PARK7 through increasing its ubiquitination modification. Forkhead Box O3 (FOXO3) belongs to the forkhead family of transcription factors and inhibits DLBCL, but the underlying mechanism has not been reported. We found that FOXO3 bound the promoter of FKBP3 and then suppressed its transcription, eventually weakening DLBCL. Mechanically, FKBP3 activated Wnt/β-catenin signalling pathway mediated by PARK7. Together, FKBP3 increased PARK7 and then facilitated the malignant phenotype of DLBCL through activating Wnt/β-catenin pathway. These results indicated that FKBP3 might be a potential therapeutic target for the treatment of DLBCL.
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Affiliation(s)
- Xiaojing Xing
- Department of Hematology and Breast CancerCancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute)ShenyangChina
| | - Meichen Liu
- Department of Hematology and Breast CancerCancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute)ShenyangChina
| | - Xuguang Wang
- Department of PathologyShenyang Medical CollegeShenyangChina
| | - Qianxue Guo
- Department of Hematology and Breast CancerCancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute)ShenyangChina
| | - Hongyue Wang
- Department of Scientific Research and AcademicCancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute)ShenyangChina
| | - Wenxue Wang
- State Key Laboratory of Robotics, Shenyang Institute of AutomationChinese Academy of SciencesShenyangChina
- Institutes for Robotics and Intelligent ManufacturingChinese Academy of SciencesShenyangChina
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3
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Park SG, Kim WJ, Moon JI, Kim KT, Ryoo HM. MESIA: multi-epigenome sample integration approach for precise peak calling. Sci Rep 2023; 13:20859. [PMID: 38012291 PMCID: PMC10681995 DOI: 10.1038/s41598-023-47948-2] [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: 09/18/2023] [Accepted: 11/20/2023] [Indexed: 11/29/2023] Open
Abstract
The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.
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Grants
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
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Affiliation(s)
- Seung Gwa Park
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Woo-Jin Kim
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Jae-I Moon
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Ki-Tae Kim
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea.
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea.
| | - Hyun-Mo Ryoo
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea.
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea.
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Ma Z, Wang L, Huang X, Ji H, Wang H, Yang Y, Ma Y, Chen J. Construction of the metabolism-related models for predicting prognosis and infiltrating immune phenotype in lung squamous cell carcinoma. J Cancer 2023; 14:3539-3549. [PMID: 38021151 PMCID: PMC10647197 DOI: 10.7150/jca.86942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 10/07/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose: Cancers often display disorder metabolism, which closely related to the poor outcome of patients. We aimed to establish prognostic models using metabolism-associated genes, and identify the key factor involved in metabolism in lung squamous cell carcinoma (LUSC). Materials and Methods: R package 'TCGA biolinks' was used to download the mRNA sequencing data of LUSC from TCGA. The clusterProfiler package was performed to analyze biological pathways. The online tool GEPIA2 and cox regression method were applied to identify the two gene lists associated with metabolism and prognosis of LUSC. The lasso modeling was conducted to establish prognostic models. The quantiseq method was used to identify the cellular abundance of expression matrix in TCGA-LUSC dataset. Immunohistochemistry and western blotting were done to evaluate the STXBP1 expression in LUSC samples. Lactate assay and ATP detection were performed to assess metabolic effect, and CCK8 assay was done to test cell proliferation in the LUSC cells with overexpression and suppression of STXBP1. Results: Two lists of survival-metabolism-associated genes (11 and 28 genes) were identified and applied in the prognostic model 1 and model 2 construction from TCGA-LUSC dataset. High-risk LUSC patients associated with poor survival in the training cohort and the test cohort of both model 1 and model 2. Higher ROC values for 10- year survival was shown in model 2 than in model 1. In addition, macrophage M1, macrophage M2, neutrophil, and T regulatory cell were enriched in the high-risk group of model 2. STXBP1 was the only optimized gene in both model 1 and model 2, and related to the poor outcome of LUSC patients. Furthermore, STXBP1 associated with infiltrating immune cells, and increased lactate, ATP levels, and cell proliferation. Conclusion: Our finding provides the metabolism-associated models to predict prognosis of LUSC patients. STXBP1, as the key optimized gene in the model, promotes metabolic progress to increase lactate and ATP levels in LUSC cells.
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Affiliation(s)
- Zeming Ma
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, People's Republic of China
| | - Liang Wang
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, People's Republic of China
| | - Xiaoyun Huang
- Department of Computational Oncology, Intelliphecy, Shenzhen, China; Center for Systems Biology, Intelliphecy, Shenzhen, China
| | - Hong Ji
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, 100142, People's Republic of China
| | - Haoyang Wang
- Beijing International Bilingual Academy, People's Republic of China
| | - Yue Yang
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, People's Republic of China
| | - Yuanyuan Ma
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, People's Republic of China
| | - Jinfeng Chen
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, People's Republic of China
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Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma. J Pers Med 2022; 13:jpm13010049. [PMID: 36675710 PMCID: PMC9862762 DOI: 10.3390/jpm13010049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
The complexity of lung adenocarcinoma (LUAD), the development of which involves many interacting biological processes, makes it difficult to find therapeutic biomarkers for treatment. FK506-binding proteins (FKBPs) are composed of 12 members classified as conservative intracellular immunophilin family proteins, which are often connected to cyclophilin structures by tetratricopeptide repeat domains and have peptidyl prolyl isomerase activity that catalyzes proline from residues and turns the trans form into the cis form. Since FKBPs belong to chaperone molecules and promote protein folding, previous studies demonstrated that FKBP family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. In this research, we adopted high-throughput bioinformatics technology to analyze FKBP family genes in LUAD to provide credible information to clinicians and promote the development of novel cancer target drugs in the future. The current data revealed that the messenger (m)RNA levels of FKBP2, FKBP3, FKBP4, FKBP10, FKBP11, and FKBP14 were overexpressed in LUAD, and FKBP10 had connections to poor prognoses among LUAD patients in an overall survival (OS) analysis. Based on the above results, we selected FKBP10 to further conduct a comprehensive analysis of the downstream pathway and network. Through a DAVID analysis, we found that FKBP10 was involved in mitochondrial electron transport, NADH to ubiquinone transport, mitochondrial respiratory chain complex I assembly, etc. The MetaCore pathway analysis also indicated that FKBP10 was involved in "Ubiquinone metabolism", "Translation_(L)-selenoaminoacid incorporation in proteins during translation", and "Transcription_Negative regulation of HIF1A function". Collectively, this study revealed that FKBP family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, thus providing new targets for treating LUAD patients.
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6
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Jiang F, Lin H, Yan H, Sun X, Yang J, Dong M. Construction of mRNA prognosis signature associated with differentially expressed genes in early stage of stomach adenocarcinomas based on TCGA and GEO datasets. Eur J Med Res 2022; 27:205. [PMID: 36253873 PMCID: PMC9578190 DOI: 10.1186/s40001-022-00827-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/11/2022] [Indexed: 12/24/2022] Open
Abstract
Background Stomach adenocarcinomas (STAD) are the most common malignancy of the human digestive system and represent the fourth leading cause of cancer-related deaths. As early-stage STAD are generally mild or asymptomatic, patients with advanced STAD have short overall survival. Early diagnosis of STAD has a considerable influence on clinical outcomes. Methods The mRNA expression data and clinical indicators of STAD and normal tissues were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The gene expression differences were analyzed by R packages, and gene function enrichment analysis was performed. Kaplan–Meier method and univariate Cox proportional risk regression analysis were used to screen differential expressed genes (DEGs) related to survival of STAD patients. Multivariate Cox proportional risk regression analysis was used to further screen and determine the prognostic DEGs in STAD patients, and to construct a multigene prognostic prediction signature. The accuracy of predictive signature was tested by receiver operating characteristic (ROC) curve software package, and the nomogram of patients with STAD was drawn. Cox regression was used to investigate the correlation between multigene prognostic signature and clinical factors. The predictive performance of this model was compared with two other models proposed in previous studies using KM survival analysis, ROC curve analysis, Harrell consistency index and decision curve analysis (DCA). qRT-PCR and Western blot were used to verify the expression levels of prognostic genes. The pathways and functions of possible involvement of features were predicted using the GSEA method. Results A total of 569 early-stage specific DEGs were retrieved from TCGA-STAD dataset, including 229 up-regulated genes and 340 down-regulated genes. Enrichment analysis showed that the early-stage specific DEGs were associated with cytokine–cytokine receptor interaction, neuroactive ligand–receptor interaction, and calcium signaling pathway. Multiple Cox regression algorithm was used to identify 10 early-stage specific DEGs associated with overall survival (P < 0.01) of STAD patients, and a multi-mRNA prognosis signature was established. The patients were divided into high-risk group and low-risk group according to the risk score. In the training set, the prognostic signature was positively correlated with tumor size and stage (P < 0.05), survival curve (P < 0.001) and time-dependent ROC (AUC = 0.625). In the training dataset and test dataset, the both signatures had good predictive efficiencies. Cox regression and DCA analysis revealed that the prognostic signature was an independent factor and had a better predict effect than the conventional TNM stage classification method and the earlier published biomarkers on the prognosis of STAD patients. Conclusion In this study, based on the early-stage specifically expressed genes, the prognostic signature constructed through TCGA and GEO datasets may become an indicator for clinical prognosis assessment of STAD and a new strategy for targeted therapy in the future. Supplementary Information The online version contains supplementary material available at 10.1186/s40001-022-00827-4.
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Affiliation(s)
- Fuquan Jiang
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China
| | - Haiguan Lin
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China
| | - Hongfeng Yan
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China
| | - Xiaomin Sun
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China
| | - Jianwu Yang
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China.
| | - Manku Dong
- Department of General Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, People's Republic of China.
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7
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Penick ER, Bateman NW, Rojas C, Magana C, Conrads K, Zhou M, Hood BL, Wang G, Parikh N, Huang Y, Darcy KM, Casablanca Y, Mhawech-Fauceglia P, Conrads TP, Maxwell GL. Proteomic alterations associated with residual disease in neoadjuvant chemotherapy treated ovarian cancer tissues. Clin Proteomics 2022; 19:35. [PMID: 36195845 PMCID: PMC9531351 DOI: 10.1186/s12014-022-09372-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 09/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome for high-grade serous ovarian cancer (HGSOC) patients. Treatment of HGSOC patients with neoadjuvant chemotherapy, however, may select for tumor cells harboring alterations in hallmark cancer pathways including metastatic potential. This study assessed this hypothesis by performing proteomic analysis of matched, chemotherapy naïve and neoadjuvant chemotherapy (NACT)-treated HGSOC tumors obtained from patients who had suboptimal (R1, n = 6) versus optimal (R0, n = 14) debulking at interval debulking surgery (IDS). METHODS Tumor epithelium was harvested by laser microdissection from formalin-fixed, paraffin-embedded tissues from matched, pre- and post-NACT treated tumors for twenty HGSOC patients and analyzed by quantitative mass spectrometry-based proteomics. RESULTS Differential analysis of patient matched pre- and post-NACT treated tumors revealed proteins associated with cell survival and metabolic signaling to be significantly altered in post-NACT treated tumor cells. Comparison of pre-NACT treated tumors from suboptimal (R1) versus optimally (R0) debulked patients identified proteins associated with tumor cell viability and invasion signaling enriched in R1 patients. We identified five proteins altered between R1 and R0 patients in pre- NACT treated tumors that significantly correlated with PFS in an independent cohort of HGSOC patients, including Fermitin family homolog 2 (FERMT2), a protein elevated in R1 that correlated with disease progression in HGSOC patients (multivariate Cox HR = 1.65, Wald p = 0.022) and increased metastatic potential in solid-tumor malignancies. CONCLUSIONS This study identified distinct proteome profiles in patient matched pre- and post-NACT HGSOC tumors that correlate with NACT resistance and that may predict residual disease status at IDS that collectively warrant further pre-clinical investigation.
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Affiliation(s)
- Emily R Penick
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
| | - Nicholas W Bateman
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Christine Rojas
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
| | - Cuauhtemoc Magana
- Department of Anatomic Pathology, Division of Gynecologic Pathology, University of Southern California, Los Angeles, CA, 9007, USA
| | - Kelly Conrads
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Ming Zhou
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Women's Health Integrated Research Center, Women's Service Line, Inova Health System, 3289 Woodburn Rd, Falls Church, VA, 22003, USA
| | - Brian L Hood
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Guisong Wang
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Niyati Parikh
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Ying Huang
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Kathleen M Darcy
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr., Suite 100, Bethesda, MD, 20817, USA
| | - Yovanni Casablanca
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.,Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
| | - Paulette Mhawech-Fauceglia
- Department of Anatomic Pathology, Division of Gynecologic Pathology, University of Southern California, Los Angeles, CA, 9007, USA
| | - Thomas P Conrads
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA. .,Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA. .,Women's Health Integrated Research Center, Women's Service Line, Inova Health System, 3289 Woodburn Rd, Falls Church, VA, 22003, USA.
| | - G Larry Maxwell
- Women's Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA. .,Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA. .,Women's Health Integrated Research Center, Women's Service Line, Inova Health System, 3289 Woodburn Rd, Falls Church, VA, 22003, USA.
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8
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Lin W, Wang Q, Chen Y, Wang N, Ni Q, Qi C, Wang Q, Zhu Y. Identification of a 6-RBP gene signature for a comprehensive analysis of glioma and ischemic stroke: Cognitive impairment and aging-related hypoxic stress. Front Aging Neurosci 2022; 14:951197. [PMID: 36118697 PMCID: PMC9476601 DOI: 10.3389/fnagi.2022.951197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
There is mounting evidence that ischemic cerebral infarction contributes to vascular cognitive impairment and dementia in elderly. Ischemic stroke and glioma are two majorly fatal diseases worldwide, which promote each other's development based on some common underlying mechanisms. As a post-transcriptional regulatory protein, RNA-binding protein is important in the development of a tumor and ischemic stroke (IS). The purpose of this study was to search for a group of RNA-binding protein (RBP) gene markers related to the prognosis of glioma and the occurrence of IS, and elucidate their underlying mechanisms in glioma and IS. First, a 6-RBP (POLR2F, DYNC1H1, SMAD9, TRIM21, BRCA1, and ERI1) gene signature (RBPS) showing an independent overall survival prognostic prediction was identified using the transcriptome data from TCGA-glioma cohort (n = 677); following which, it was independently verified in the CGGA-glioma cohort (n = 970). A nomogram, including RBPS, 1p19q codeletion, radiotherapy, chemotherapy, grade, and age, was established to predict the overall survival of patients with glioma, convenient for further clinical transformation. In addition, an automatic machine learning classification model based on radiomics features from MRI was developed to stratify according to the RBPS risk. The RBPS was associated with immunosuppression, energy metabolism, and tumor growth of gliomas. Subsequently, the six RBP genes from blood samples showed good classification performance for IS diagnosis (AUC = 0.95, 95% CI: 0.902–0.997). The RBPS was associated with hypoxic responses, angiogenesis, and increased coagulation in IS. Upregulation of SMAD9 was associated with dementia, while downregulation of POLR2F was associated with aging-related hypoxic stress. Irf5/Trim21 in microglia and Taf7/Trim21 in pericytes from the mouse cerebral cortex were identified as RBPS-related molecules in each cell type under hypoxic conditions. The RBPS is expected to serve as a novel biomarker for studying the common mechanisms underlying glioma and IS.
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Affiliation(s)
- Weiwei Lin
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases of Zhejiang, Hangzhou, China
| | - Qiangwei Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases of Zhejiang, Hangzhou, China
| | - Yisheng Chen
- Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ning Wang
- Brain Center, Affiliated Zhejiang Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qingbin Ni
- Postdoctoral Workstation, Department of Central Laboratory, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Chunhua Qi
- Postdoctoral Workstation, Department of Central Laboratory, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Qian Wang
- Postdoctoral Workstation, Department of Central Laboratory, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
- *Correspondence: Qian Wang
| | - Yongjian Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases of Zhejiang, Hangzhou, China
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, China
- Yongjian Zhu
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Liu TT, Li R, Huo C, Li JP, Yao J, Ji XL, Qu YQ. Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis. Front Cell Dev Biol 2021; 9:682002. [PMID: 34409029 PMCID: PMC8366777 DOI: 10.3389/fcell.2021.682002] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 07/06/2021] [Indexed: 12/12/2022] Open
Abstract
Background Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD). Methods “GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs. Results A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05. Conclusion In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.
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Affiliation(s)
- Ting-Ting Liu
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Rui Li
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Chen Huo
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Jian-Ping Li
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Jie Yao
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Xiu-Li Ji
- Department of Pulmonary Disease, Jinan Traditional Chinese Medicine Hospital, Jinan, China
| | - Yi-Qing Qu
- Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China.,Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China
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