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Guo Y, Jiang Z, Chen Q, Xie D, Zhou Y, Yin W, Wang Z, Wang B, Ren C, Jiang X. Construction and experimental validation of a signature for predicting prognosis and immune infiltration analysis of glioma based on disulfidptosis-related lncRNAs. Front Immunol 2023; 14:1291385. [PMID: 38022537 PMCID: PMC10655028 DOI: 10.3389/fimmu.2023.1291385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Backgrounds Disulfidptosis, a newly discovered mechanism of programmed cell death, is believed to have a unique role in elucidating cancer progression and guiding cancer therapy strategies. However, no studies have yet explored this mechanism in glioma. Methods We downloaded data on glioma patients from online databases to address this gap. Subsequently, we identified disulfidptosis-related genes from published literature and verified the associated lncRNAs. Results Through univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) regression algorithms analyses, we identified 10 lncRNAs. These were then utilized to construct prognostic prediction models, culminating in a risk-scoring signature. Reliability and validity tests demonstrated that the model effectively discerns glioma patients' prognosis outcomes. We also analyzed the relationship between the risk score and immune characteristics, and identified several drugs that may be effective for high-risk patients. In vitro experiments revealed that LINC02525 could enhances glioma cells' migration and invasion capacities. Additionally, knocking down LINC02525 was observed to promote glioma cell disulfidptosis. Conclusion This study delves into disulfidptosis-related lncRNAs in glioma, offering novel insights into glioma therapeutic strategies.
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Affiliation(s)
- Youwei Guo
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhipeng Jiang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Quan Chen
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dongcheng Xie
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yi Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Wen Yin
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zihan Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Binbin Wang
- Department of Neurosurgery, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Caiping Ren
- Cancer Research Institute, Department of Neurosurgery, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Health Commission (NHC) Key Laboratory of Carcinogenesis and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Xingjun Jiang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
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Ng A, Lovat F, Shih AJ, Ma Y, Pekarsky Y, DiCaro F, Crichton L, Sharma E, Yan XJ, Sun D, Song T, Zou YR, Will B, Croce CM, Chiorazzi N. Complete miRNA-15/16 loss in mice promotes hematopoietic progenitor expansion and a myeloid-biased hyperproliferative state. Proc Natl Acad Sci U S A 2023; 120:e2308658120. [PMID: 37844234 PMCID: PMC10614620 DOI: 10.1073/pnas.2308658120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023] Open
Abstract
Dysregulated apoptosis and proliferation are fundamental properties of cancer, and microRNAs (miRNA) are critical regulators of these processes. Loss of miR-15a/16-1 at chromosome 13q14 is the most common genomic aberration in chronic lymphocytic leukemia (CLL). Correspondingly, the deletion of either murine miR-15a/16-1 or miR-15b/16-2 locus in mice is linked to B cell lymphoproliferative malignancies. However, unexpectedly, when both miR-15/16 clusters are eliminated, most double knockout (DKO) mice develop acute myeloid leukemia (AML). Moreover, in patients with CLL, significantly reduced expression of miR-15a, miR-15b, and miR-16 associates with progression of myelodysplastic syndrome to AML, as well as blast crisis in chronic myeloid leukemia. Thus, the miR-15/16 clusters have a biological relevance for myeloid neoplasms. Here, we demonstrate that the myeloproliferative phenotype in DKO mice correlates with an increase of hematopoietic stem and progenitor cells (HSPC) early in life. Using single-cell transcriptomic analyses, we presented the molecular underpinning of increased myeloid output in the HSPC of DKO mice with gene signatures suggestive of dysregulated hematopoiesis, metabolic activities, and cell cycle stages. Functionally, we found that multipotent progenitors (MPP) of DKO mice have increased self-renewing capacities and give rise to significantly more progeny in the granulocytic compartment. Moreover, a unique transcriptomic signature of DKO MPP correlates with poor outcome in patients with AML. Together, these data point to a unique regulatory role for miR-15/16 during the early stages of hematopoiesis and to a potentially useful biomarker for the pathogenesis of myeloid neoplasms.
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Affiliation(s)
- Anita Ng
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Francesca Lovat
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH43210
| | - Andrew J. Shih
- Boas Center for Human Genetics and Genomics, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Yuhong Ma
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY10461
| | - Yuri Pekarsky
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH43210
| | - Frank DiCaro
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Lita Crichton
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Esha Sharma
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Xiao Jie Yan
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Daqian Sun
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY10461
| | - Tengfei Song
- The Center for Autoimmune, Musculoskeletal, and Hematopoietic Diseases, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
| | - Yong-Rui Zou
- The Center for Autoimmune, Musculoskeletal, and Hematopoietic Diseases, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
- Departments of Medicine and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY11549
| | - Britta Will
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY10461
| | - Carlo M. Croce
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH43210
| | - Nicholas Chiorazzi
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research Northwell Health, Manhasset, NY11030
- Departments of Medicine and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY11549
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Wei X, Zhou Z, Long M, Lin Q, Qiu M, Chen P, Huang Q, Qiu J, Jiang Y, Wen Q, Liu Y, Li R, Nong C, Guo Q, Yu H, Zhou X. A novel signature constructed by super-enhancer-related genes for the prediction of prognosis in hepatocellular carcinoma and associated with immune infiltration. Front Oncol 2023; 13:1043203. [PMID: 36845708 PMCID: PMC9948016 DOI: 10.3389/fonc.2023.1043203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Background Super-enhancer (SE) refers to a regulatory element with super transcriptional activity, which can enrich transcription factors and drive gene expression. SE-related genes play an important role in the pathogenesis of malignant tumors, including hepatocellular carcinoma (HCC). Methods The SE-related genes were obtained from the human super-enhancer database (SEdb). Data from the transcriptome analysis and related clinical information with HCC were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The upregulated SE-related genes from TCGA-LIHC were identified by the DESeq2R package. Multivariate Cox regression analysis was used to construct a four-gene prognostic signature. According to the median risk score, HCC patients were divided into high-risk and low-risk group patients. Results The Kaplan-Meier (KM) curve showed that a significantly worse prognosis was found for the high-risk group (P<0.001). In the TCGA-LIHC dataset, the area under the curve (AUC) values were 0.737, 0.662, and 0.667 for the model predicting overall survival (OS) over 1-, 3-, and 5- years, respectively, indicating the good prediction ability of our prediction model. This model's prognostic value was further validated in the LIRI-JP dataset and HCC samples (n=65). Furthermore, we found that higher infiltration level of M0 macrophages and upregulated of CTLA4 and PD1 in the high-risk group, implying that immunotherapy could be effective for those patients. Conclusion These results provide further evidence that the unique SE-related gene model could accurately predict the prognosis of HCC.
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Affiliation(s)
- Xueyan Wei
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zihan Zhou
- Department of Cancer Prevention and Control, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Meiying Long
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Qiuling Lin
- Department of Clinical Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Moqin Qiu
- Department of Respiratory Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Peiqin Chen
- Editorial Department of Chinese Journal of Oncology Prevention and Treatment, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiongguang Huang
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Jialin Qiu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yanji Jiang
- Scientific Research Department, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiuping Wen
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yingchun Liu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Runwei Li
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, United States
| | - Cunli Nong
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Qian Guo
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Hongping Yu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Key Laboratory of Early Prevention and Treatment for Regional High-Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, China,Key Cultivated Laboratory of Cancer Molecular Medicine, Health Commission of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
| | - Xianguo Zhou
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
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Zhuang HH, Qu Q, Teng XQ, Dai YH, Qu J. Superenhancers as master gene regulators and novel therapeutic targets in brain tumors. Exp Mol Med 2023; 55:290-303. [PMID: 36720920 PMCID: PMC9981748 DOI: 10.1038/s12276-023-00934-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 11/27/2022] [Accepted: 12/04/2022] [Indexed: 02/02/2023] Open
Abstract
Transcriptional deregulation, a cancer cell hallmark, is driven by epigenetic abnormalities in the majority of brain tumors, including adult glioblastoma and pediatric brain tumors. Epigenetic abnormalities can activate epigenetic regulatory elements to regulate the expression of oncogenes. Superenhancers (SEs), identified as novel epigenetic regulatory elements, are clusters of enhancers with cell-type specificity that can drive the aberrant transcription of oncogenes and promote tumor initiation and progression. As gene regulators, SEs are involved in tumorigenesis in a variety of tumors, including brain tumors. SEs are susceptible to inhibition by their key components, such as bromodomain protein 4 and cyclin-dependent kinase 7, providing new opportunities for antitumor therapy. In this review, we summarized the characteristics and identification, unique organizational structures, and activation mechanisms of SEs in tumors, as well as the clinical applications related to SEs in tumor therapy and prognostication. Based on a review of the literature, we discussed the relationship between SEs and different brain tumors and potential therapeutic targets, focusing on glioblastoma.
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Affiliation(s)
- Hai-Hui Zhuang
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, 410011, PR China
| | - Qiang Qu
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, 410007, PR China.,Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410007, PR China
| | - Xin-Qi Teng
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, 410011, PR China
| | - Ying-Huan Dai
- Department of Pathology, the Second Xiangya Hospital, Central South University, Changsha, 410011, PR China
| | - Jian Qu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, 410011, PR China.
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Li W, Yuan P, Liu W, Xiao L, Xu C, Mo Q, Xu S, He Y, Jiang D, Wang X. Hypoxia–Immune-Related Gene SLC19A1 Serves as a Potential Biomarker for Prognosis in Multiple Myeloma. Front Immunol 2022; 13:843369. [PMID: 35958555 PMCID: PMC9358019 DOI: 10.3389/fimmu.2022.843369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
Background Multiple myeloma (MM) remains an incurable malignant tumor of plasma cells. Increasing evidence has reported that hypoxia and immune status contribute to the progression of MM. In this research, the prognostic value of the hypoxia–immune-related gene SLC19A1 in MM was evaluated by bioinformatics analysis. Method RNA-sequencing (RNA-seq) data along with clinical information on MM were downloaded from the Gene Expression Omnibus (GEO) database. Consistent clustering analysis and ESTIMATE algorithms were performed to establish the MM sample subgroups related to hypoxia and immune status, respectively, based on the GSE24080 dataset. The differentially expressed analysis was performed to identify the hypoxia–immune-related genes. Subsequently, a hypoxia–immune-gene risk signature for MM patients was constructed by univariate and multivariate Cox regression analyses, which was also verified in the GSE4581 dataset. Furthermore, the mRNA expression of SLC19A1 was determined using qRT-PCR in 19 MM patients, and the correlations between the genetic expression of SLC19A1 and clinical features were further analyzed. Result A total of 47 genes were identified as hypoxia–immune-related genes for MM. Among these genes, SLC19A1 was screened to construct a risk score model that had better predictive power for MM. The constructed prognostic signature based on SLC19A1 was verified in the GSE4581 dataset. All independent prognostic factors (age, β2-microglobulin, LDH, albumin, MRI, and gene risk score) were used to develop a nomogram that showed a better performance for predicting the survival probability of MM patients for 1–5 years. Furthermore, SLC19A1 was highly expressed in newly diagnosed and relapsed MM patients, and high expression of SLC19A1 is correlated with higher bone marrow aspiration plasma cells and β2-microglobulin levels in MM patients. Conclusion In conclusion, our results suggest that SLC19A1 is aberrantly expressed in MM and highly expressed SLC19A1 might be a biomarker correlated with inferior prognosis. More importantly, we identified SLC19A1 as a hypoxia–immune-related gene in MM. Future functional and mechanistic studies will further clarify the roles of SLC19A1 in MM.
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Affiliation(s)
- Wenjin Li
- Department of Hematology, Pingxiang People’s Hospital, Pingxiang, China
| | - Peng Yuan
- Department of Hematology, Pingxiang People’s Hospital, Pingxiang, China
| | - Weiqin Liu
- Department of Hematology, Pingxiang People’s Hospital, Pingxiang, China
| | - Lichan Xiao
- Department of Hematology, Pingxiang People’s Hospital, Pingxiang, China
| | - Chun Xu
- Department of Hematology, Pingxiang People’s Hospital, Pingxiang, China
| | - Qiuyu Mo
- Department of Hematology, Affiliated Hospital of Guilin Medical University, Guilin, China
- Department of Hematology, Second Affiliated Hospital of Hainan Medical College, Haikou, China
| | - Shujuan Xu
- Department of Hematology, Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Yuchan He
- Department of Hematology, The Second Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Duanfeng Jiang
- Department of Hematology, Second Affiliated Hospital of Hainan Medical College, Haikou, China
- Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xiaotao Wang
- Department of Hematology, Affiliated Hospital of Guilin Medical University, Guilin, China
- *Correspondence: Xiaotao Wang,
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Xu Q, Chen S, Hu Y, Huang W. Clinical M2 macrophages-related genes to aid therapy in pancreatic ductal adenocarcinoma. Cancer Cell Int 2021; 21:582. [PMID: 34717651 PMCID: PMC8557582 DOI: 10.1186/s12935-021-02289-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/21/2021] [Indexed: 12/25/2022] Open
Abstract
Background Increasing evidence supports that infiltration M2 Macrophages act as pivotal player in tumor progression of pancreatic ductal adenocarcinoma (PDAC). Nonetheless, comprehensive analysis of M2 Macrophage infiltration and biological roles of hub genes (FAM53B) in clinical outcome and immunotherapy was lack. Method The multiomic data of PDAC samples were downloaded from distinct datasets. CIBERSORT algorithm was performed to uncover the landscape of TIME. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate module and significant genes associated with M2 Macrophages. Kaplan-Meier curve and receiver operating characteristic (ROC) curves were applied for prognosis value validation. Mutation data was analyzed by using “maftools” R package. Gene set variation analysis (GSVA) was employed to assign pathway activity estimates to individual sample. Immunophenoscore (IPS) was implemented to estimate immunotherapeutic significance of risk score. The half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs was predicted by using the pRRophetic algorithm. Finally, quantitative real-time polymerase chain reaction was used to determine FAM53B mRNA expression and TIMER database was utilized to uncover its possible role in immune infiltration of PDAC. Results Herein, 17,932 genes in 234 samples (214 tumor and 20 normal) were extracted from three platforms. Taking advantage of WGCNA, significant module (royalblue) and 135 candidate genes were considered as M2 Macrophages-related genes. Subsequently, risk signature including 5 hub genes was developed by multiple analysis, which exhibited excellent prognostic performance. Besides, comprehensive prognostic nomogram was constructed to quantitatively estimate risk. Then, intrinsic link between risk score with tumor mutation burden (TMB) was explored. Additionally, risk score significantly correlated with diversity of tumor immune microenvironment (TIME). PDAC samples within different risk presented diverse signaling pathways activity and experienced significantly distinct sensitivity to administering chemotherapeutic or immunotherapeutic agents. Finally, the biological roles of FAM53B were revealed in PDAC. Conclusions Taken together, comprehensive analyses of M2 Macrophages profiling will facilitate prognostic prediction, delineating complexity of TIME, and contribute insight into precision therapy for PDAC. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-02289-w.
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Affiliation(s)
- Qianhui Xu
- The Second Affiliated Hospital, Yuying Children's Hospital of Wenzhou Medical University, No 109. Xueyuan West Road, Wenzhou, 325000, Zhejiang, China.,Zhejiang University School of Medicine, Zhejiang, Hangzhou, 310009, China
| | - Shaohuai Chen
- The Second Affiliated Hospital, Yuying Children's Hospital of Wenzhou Medical University, No 109. Xueyuan West Road, Wenzhou, 325000, Zhejiang, China
| | - Yuanbo Hu
- The Second Affiliated Hospital, Yuying Children's Hospital of Wenzhou Medical University, No 109. Xueyuan West Road, Wenzhou, 325000, Zhejiang, China
| | - Wen Huang
- The Second Affiliated Hospital, Yuying Children's Hospital of Wenzhou Medical University, No 109. Xueyuan West Road, Wenzhou, 325000, Zhejiang, China.
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Liu L, Qu J, Dai Y, Qi T, Teng X, Li G, Qu Q. An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients. Aging (Albany NY) 2021; 13:18442-18463. [PMID: 34260414 PMCID: PMC8351694 DOI: 10.18632/aging.203294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 06/23/2021] [Indexed: 12/29/2022]
Abstract
Although novel drugs and treatments have been developed and improved, multiple myeloma (MM) is still recurrent and difficult to cure. In the present study, the magenta module containing 400 hub genes was determined from the training dataset of GSE24080 through weighted gene co-expression network analysis (WGCNA). Then, using the least absolute shrinkage and selection operator (Lasso) analysis, a fifteen-gene signature was firstly selected and the predictive performance for overall survival (OS) was favorable, which was identified by Receiver Operating Characteristic (ROC) curves. The risk score model was constructed based on survival-associated fifteen genes from the Lasso model, which classified MM patients into high-risk and low-risk groups. Areas under the curve (AUC) of ROC curve and log-rank test showed that the high-risk group was correlated to the dismal survival outcome of MM patients, which was also identified in testing dataset of GSE9782. The calibration plot, the AUC value of the ROC curve and Concordance-index showed that the interactive nomogram with risk score could favorably predict the probability of multi-year OS of MM patients. Therefore, it may help clinicians make a precise therapeutic decision based on the easy-to-use tool of the nomogram.
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Affiliation(s)
- Linxin Liu
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, China
| | - Jian Qu
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, China
| | - Yuxin Dai
- Department of Biochemistry and Molecular Biology, School of Life Sciences, Central South University, Changsha, China
| | - Tingting Qi
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, China
| | - Xinqi Teng
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, China
| | - Guohua Li
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy, Central South University, Changsha, China
| | - Qiang Qu
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China.,Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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8
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Pan Y, Meng Y, Zhai Z, Xiong S. Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis. PeerJ 2021; 9:e11320. [PMID: 34249481 PMCID: PMC8247704 DOI: 10.7717/peerj.11320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 03/31/2021] [Indexed: 12/05/2022] Open
Abstract
Background Multiple myeloma (MM), the second most hematological malignancy, has high incidence and remains incurable till now. The pathogenesis of MM is poorly understood. This study aimed to identify novel prognostic model for MM on gene expression profiles. Methods Gene expression datas of MM (GSE6477, GSE136337) were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in GSE6477 between case samples and normal control samples were screened by the limma package. Meanwhile, enrichment analysis was conducted, and a protein-protein interaction (PPI) network of these DEGs was established by STRING and cytoscape software. Co-expression modules of genes were built by Weighted Correlation Network Analysis (WGCNA). Key genes were identified both from hub genes and the DEGs. Univariate and multivariate Cox congression were performed to screen independent prognostic genes to construct a predictive model. The predictive power of the model was evaluated by Kaplan–Meier curve and time-dependent receiver operating characteristic (ROC) curves. Finally, univariate and multivariate Cox regression analyse were used to investigate whether the prognostic model could be independent of other clinical parameters. Results GSE6477, including 101 case and 15 normal control, were screened as the datasets. A total of 178 DEGs were identified, including 59 up-regulated and 119 down-regulated genes. In WGCNA analysis, module black and module purple were the most relevant modules with cancer traits, and 92 hub genes in these two modules were selected for further analysis. Next, 47 genes were chosen both from the DEGs and hub genes as key genes. Three genes (LYVE1, RNASE1, and RNASE2) were finally screened by univariate and multivariate Cox regression analyses and used to construct a risk model. In addition, the three-gene prognostic model revealed independent and accurate prognostic capacity in relation to other clinical parameters for MM patients. Conclusion In summary, we identified and constructed a three-gene-based prognostic model that could be used to predict overall survival of MM patients.
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Affiliation(s)
- Ying Pan
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ye Meng
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhimin Zhai
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shudao Xiong
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
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9
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Li GH, Qu Q, Qi TT, Teng XQ, Zhu HH, Wang JJ, Lu Q, Qu J. Super-enhancers: a new frontier for epigenetic modifiers in cancer chemoresistance. J Exp Clin Cancer Res 2021; 40:174. [PMID: 34011395 PMCID: PMC8132395 DOI: 10.1186/s13046-021-01974-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/05/2021] [Indexed: 02/06/2023] Open
Abstract
Although new developments of surgery, chemotherapy, radiotherapy, and immunotherapy treatments for cancer have improved patient survival, the emergence of chemoresistance in cancer has significant impacts on treatment effects. The development of chemoresistance involves several polygenic, progressive mechanisms at the molecular and cellular levels, as well as both genetic and epigenetic heterogeneities. Chemotherapeutics induce epigenetic reprogramming in cancer cells, converting a transient transcriptional state into a stably resistant one. Super-enhancers (SEs) are central to the maintenance of identity of cancer cells and promote SE-driven-oncogenic transcriptions to which cancer cells become highly addicted. This dependence on SE-driven transcription to maintain chemoresistance offers an Achilles' heel for chemoresistance. Indeed, the inhibition of SE components dampens oncogenic transcription and inhibits tumor growth to ultimately achieve combined sensitization and reverse the effects of drug resistance. No reviews have been published on SE-related mechanisms in the cancer chemoresistance. In this review, we investigated the structure, function, and regulation of chemoresistance-related SEs and their contributions to the chemotherapy via regulation of the formation of cancer stem cells, cellular plasticity, the microenvironment, genes associated with chemoresistance, noncoding RNAs, and tumor immunity. The discovery of these mechanisms may aid in the development of new drugs to improve the sensitivity and specificity of cancer cells to chemotherapy drugs.
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Affiliation(s)
- Guo-Hua Li
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Qiang Qu
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China
| | - Ting-Ting Qi
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Xin-Qi Teng
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Hai-Hong Zhu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Jiao-Jiao Wang
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Qiong Lu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China.
| | - Jian Qu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University; Institute of Clinical Pharmacy, Central South University, 139 Middle Renmin Road, Changsha, Hunan, 410011, People's Republic of China.
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