1
|
Liu J, Ren L, Li S, Li W, Zheng X, Yang Y, Fu W, Yi J, Wang J, Du G. The biology, function, and applications of exosomes in cancer. Acta Pharm Sin B 2021; 11:2783-2797. [PMID: 34589397 PMCID: PMC8463268 DOI: 10.1016/j.apsb.2021.01.001] [Citation(s) in RCA: 200] [Impact Index Per Article: 66.7] [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: 06/23/2020] [Revised: 08/30/2020] [Accepted: 10/12/2020] [Indexed: 02/07/2023] Open
Abstract
Exosomes are cell-derived nanovesicles with diameters from 30 to 150 nm, released upon fusion of multivesicular bodies with the cell surface. They can transport nucleic acids, proteins, and lipids for intercellular communication and activate signaling pathways in target cells. In cancers, exosomes may participate in growth and metastasis of tumors by regulating the immune response, blocking the epithelial-mesenchymal transition, and promoting angiogenesis. They are also involved in the development of resistance to chemotherapeutic drugs. Exosomes in liquid biopsies can be used as non-invasive biomarkers for early detection and diagnosis of cancers. Because of their amphipathic structure, exosomes are natural drug delivery vehicles for cancer therapy.
Collapse
Key Words
- ABCA3, ATP-binding cassette transporter A3
- APCs, antigen-presenting cells
- Biomarkers
- CAFs, cancer-associated fibroblasts
- CCRCC, clear-cell renal cell carcinoma
- CD-UPRT, cytosine deaminase-uracil phosphoribosyltransferase
- CDH3, cadherin 3
- CRC, colorectal cancer
- DC, dendritic cells
- DEXs, DC-derived exosomes
- DLBCL, diffuse large B-cell lymphoma
- DNM3, dynamin 3
- Del-1, developmental endothelial locus-1
- Drug delivery
- Drug resistance
- ECM, extracellular matrix
- EMT, epithelial–mesenchymal transition
- ESCRT, endosomal sorting complex required for transport
- Exosomes
- GPC1, glypican-1
- HA, hyaluronic acid
- HCC, hepatocellular carcinoma
- HIF1, hypoxia-inducible factor 1
- HTR, hormone therapy-resistant
- HUVECs, human umbilical vein endothelial cells
- ILVs, intraluminal vesicles
- MDSCs, myeloid-derived suppressor cells
- MIF, migration inhibitory factor
- MSC, mesenchymal stem cells
- MVB, multivesicular body
- NKEXOs, natural killer cell-derived exosomes
- NNs, nanoparticles
- NSCLC, non-small cell lung cancer
- PA, phosphatidic acid
- PCC, pheochromocytoma
- PD-L1, programmed cell death receptor ligand 1
- PDAC, pancreatic ductal adenocarcinoma
- PGL, paraganglioma
- PI, phosphatidylinositol
- PS, phosphatidylserine
- PTRF, polymerase I and transcript release factor
- RCC, renal cell carcinoma
- SM, sphingomyelin
- SNARE, soluble NSF-attachment protein receptor
- TEX, tumor-derived exosomes
- TSG101, tumor susceptibility gene 101
- Tumor immunity
- Tumor metastasis
- circRNAs, circular RNAs
- dsDNA, double stranded DNA
- hTERT, human telomerase reverse transcriptase
- lamp2b, lysosome-associated membrane glycoprotein 2b
- lncRNAs, long non-coding RNAs
- miRNA, microRNA
- mtDNA, mitochondrial DNA
- ncRNA, non-coding RNAs
Collapse
Affiliation(s)
- Jinyi Liu
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Liwen Ren
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Sha Li
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Wan Li
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Xiangjin Zheng
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Yihui Yang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Weiqi Fu
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Jie Yi
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Beijing 100730, China
| | - Jinhua Wang
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| | - Guanhua Du
- The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
- Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China
| |
Collapse
|
2
|
Chen Y, Li Z, Chen X, Zhang S. Long non-coding RNAs: From disease code to drug role. Acta Pharm Sin B 2021; 11:340-354. [PMID: 33643816 PMCID: PMC7893121 DOI: 10.1016/j.apsb.2020.10.001] [Citation(s) in RCA: 233] [Impact Index Per Article: 77.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 08/06/2020] [Accepted: 08/21/2020] [Indexed: 12/30/2022] Open
Abstract
Enormous studies have corroborated that long non-coding RNAs (lncRNAs) extensively participate in crucial physiological processes such as metabolism and immunity, and are closely related to the occurrence and development of tumors, cardiovascular diseases, nervous system disorders, nephropathy, and other diseases. The application of lncRNAs as biomarkers or intervention targets can provide new insights into the diagnosis and treatment of diseases. This paper has focused on the emerging research into lncRNAs as pharmacological targets and has reviewed the transition of lncRNAs from the role of disease coding to acting as drug candidates, including the current status and progress in preclinical research. Cutting-edge strategies for lncRNA modulation have been summarized, including the sources of lncRNA-related drugs, such as genetic technology and small-molecule compounds, and related delivery methods. The current progress of clinical trials of lncRNA-targeting drugs is also discussed. This information will form a latest updated reference for research and development of lncRNA-based drugs.
Collapse
Key Words
- AD, Alzheimer's disease
- ANRIL, antisense noncoding RNA gene at the INK4 locus
- ASO, antisense oligonucleotide
- ASncmtRNA
- ASncmtRNA, antisense noncoding mitochondrial RNA
- BCAR4, breast cancer anti-estrogen resistance 4
- BDNF-AS, brain-derived neurotrophic factor antisense
- CASC9, cancer susceptibility candidate 9
- CDK, cyclin dependent kinase 1
- CHRF, cardiac hypertrophy related factor
- CRISPR, clustered regularly interspaced short palindromic repeats
- Clinical trials
- DACH1, dachshund homolog 1
- DANCR, differentiation antagonizing non-protein coding RNA
- DKD, diabetic kidney disease
- DPF, diphenyl furan
- Delivery
- EBF3-AS, early B cell factor 3-antisense
- ENE, element for nuclear expression
- Erbb4-IR, Erb-B2 receptor tyrosine kinase 4-immunoreactivity
- FDA, U.S. Food and Drug Administration
- GAPDH, glyceraldehyde-3-phosphate dehydrogenase
- GAS5, growth arrest specific 5
- Gene therapy
- HISLA, HIF-1α-stabilizing long noncoding RNA
- HOTAIR, HOX transcript antisense intergenic RNA
- HULC, highly upregulated in liver cancer
- LIPCAR, long intergenic noncoding RNA predicting cardiac remodeling
- LNAs, locked nucleic acids
- LncRNAs
- MALAT1, metastasis associated lung adenocarcinoma transcript 1
- MEG3, maternally expressed gene 3
- MHRT, myosin heavy chain associated RNA transcripts
- MM, multiple myeloma
- NEAT1, nuclear enriched abundant transcript 1
- NKILA, NF-kappaB interacting lncRNA
- NPs, nanoparticles
- Norad, non-coding RNA activated by DNA damage
- OIP5-AS1, opa-interacting protein 5 antisense transcript 1
- PD, Parkinson's disease
- PEG, polyethylene glycol
- PNAs, peptide nucleic acids
- PTO, phosphorothioate
- PVT1, plasmacytoma variant translocation 1
- RGD, arginine-glycine-aspartic acid peptide
- RISC, RNA-induced silencing complex
- SALRNA1, senescence associated long non-coding RNA 1
- SNHG1, small nucleolar RNA host gene 1
- Small molecules
- SncmtRNA, sense noncoding mitochondrial RNA
- THRIL, TNF and HNRNPL related immunoregulatory
- TTTY15, testis-specific transcript, Y-linked 15
- TUG1, taurine-upregulated gene 1
- TWIST1, twist family BHLH transcription factor 1
- Targeted drug
- TncRNA, trophoblast-derived noncoding RNA
- Translational medicine
- UCA1, urothelial carcinoma-associated 1
- UTF1, undifferentiated transcription factor 1
- XIST, X-inactive specific transcript
- lincRNA-p21, long intergenic noncoding RNA p21
- lncRNAs, long non-coding RNAs
- mtlncRNA, mitochondrial long noncoding RNA
- pHLIP, pH-low insertion peptide
- sgRNA, single guide RNA
- siRNAs, small interfering RNAs
Collapse
|
3
|
Chen X, Cui Y, Ma Y. Long non-coding RNA BLACAT1 expedites osteosarcoma cell proliferation, migration and invasion via up-regulating SOX12 through miR-608. J Bone Oncol 2020; 25:100314. [PMID: 33005563 PMCID: PMC7519359 DOI: 10.1016/j.jbo.2020.100314] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [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: 05/14/2020] [Revised: 07/16/2020] [Accepted: 07/20/2020] [Indexed: 12/26/2022] Open
Abstract
BLACAT1 promotes cell proliferation, migration and invasion, and dampens cell apoptosis in OS. BLACAT1 sponges miR-608 in OS. SOX12 is the target of miR-608. BLACA1 promotes OS cell growth and migration via targeting miR-608/SOX12 axis.
Background Osteosarcoma is the most common type of bone malignancy. Increasing evidence indicated that long non-coding RNAs (lncRNAs) possess multiple functions in the development of cancer and can be used as indicators of prognosis and diagnosis. LncRNA BLACAT1 has been found to promote the proliferation of breast cancer cells. However, the role of BLACAT1 in osteosarcoma remains largely unknown. Methods QRT-PCR analysis was employed to evaluate mRNA expressions. Western blot was performed to measure relevant protein level. Colony formation and EdU assays were conducted to certify proliferative ability. TUNEL assay was finalized to assess apoptotic cells. Wound-healing and transwell assays were utilized for the exploration of migrating and invasive abilities. The subcellular distribution of BLACAT1 was studied by nucleus-cytoplasm separation assay. Relevant mechanical experiments were combined to elucidate molecular relationship between molecules. Results BLACAT1 was highly expressed in osteosarcoma. BLACAT1 promoted the proliferation and migration of osteosarcoma cells. BLACAT1 acted as a sponge for miR-608 to augment the expression of Sex determining region Y-box protein 12 (SOX12), the direct target of miR-608. Further, inhibiting miR-608 recovered the repressive effect of silenced BLACAT1 on the malignant behaviors of osteosarcoma cells. Conclusion This study highlighted the contribution of BLACAT1/miR-608/SOX12 axis to the progression of osteosarcoma, suggesting novel targets for osteosarcoma therapy.
Collapse
Key Words
- ANOVA, analysis of variance
- ATCC, American type culture collection
- BLACAT1
- DMEM, Dulbecco’s modified Eagle’s medium
- FBS, fetal bovine serum
- FISH, Fluorescence in situ hybridization
- HRP, horseradish peroxidase
- Mut, mutant
- OS, osteosarcoma
- Osteosarcoma
- PVDF, polyvinylidene fluoride
- RIPA, radioimmunoprecipitation assay
- RT-qPCR, RNA extraction and quantitative real-time polymerase chain reaction
- SD, standard deviation
- SDS-PAGE, sulphate-polyacrylamide gel electrophoresis
- SOX, sex-determining region Y (SRY)-box
- SOX12
- SOX12, sex determining region Y-box protein 12
- WT, wild-type
- ceRNAs, competing endogenous RNAs
- lncRNAs, long non-coding RNAs
- mRNA, messenger RNA
- miR-608
- miRNAs, microRNAs
Collapse
Affiliation(s)
- Xiaotao Chen
- Department of Orthopedics, Qinghai Provincial People's Hospital, Xining City, Qinghai Province 810007, China
| | - Yubao Cui
- Department of Orthopadics, Hubei Aerospace Hospital, Xiaogan City, Hubei Province 432000, China
| | - Yanming Ma
- Department of Orthopedics, No. 2 Hospital of Yulin City, The South Road of Wenhua, Yuyang District, Yulin City, Shaanxi Province 719000, China
| |
Collapse
|
4
|
Niu M, Zhang J, Li Y, Wang C, Liu Z, Ding H, Zou Q, Ma Q. CirRNAPL: A web server for the identification of circRNA based on extreme learning machine. Comput Struct Biotechnol J 2020; 18:834-42. [PMID: 32308930 DOI: 10.1016/j.csbj.2020.03.028] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Revised: 03/29/2020] [Accepted: 03/29/2020] [Indexed: 12/27/2022] Open
Abstract
Circular RNA (circRNA) plays an important role in the development of diseases, and it provides a novel idea for drug development. Accurate identification of circRNAs is important for a deeper understanding of their functions. In this study, we developed a new classifier, CirRNAPL, which extracts the features of nucleic acid composition and structure of the circRNA sequence and optimizes the extreme learning machine based on the particle swarm optimization algorithm. We compared CirRNAPL with existing methods, including blast, on three datasets and found CirRNAPL significantly improved the identification accuracy for the three datasets, with accuracies of 0.815, 0.802, and 0.782, respectively. Additionally, we performed sequence alignment on 564 sequences of the independent detection set of the third data set and analyzed the expression level of circRNAs. Results showed the expression level of the sequence is positively correlated with the abundance. A user-friendly CirRNAPL web server is freely available at http://server.malab.cn/CirRNAPL/.
Collapse
Key Words
- ACC, Accuracy
- CNN, Convolutional Neural Networks
- Circular RNA
- DAC, Dinucleotide-based auto-covariance
- DACC, Dinucleotide-based auto-cross-covariance
- DCC, Dinucleotide-based cross-covariance
- ELM, extreme learning machine
- Expression level
- Extreme learning machine
- GAC, Geary autocorrelation
- Identification
- MAC, Moran autocorrelation
- MCC, Matthews Correlation Coefficient
- MRMD, Maximum-Relevance-Maximum-Distance
- NMBAC, Normalized Moreau–Broto autocorrelation
- PC-PseDNC-General, General parallel correlation pseudo-dinucleotide composition
- PCGs, protein coding genes
- PSO, particle swarm optimization algorithm
- Particle swarm optimization algorithm
- PseDPC, Pseudo-distance structure status pair composition
- PseSSC, Pseudo-structure status composition
- RBF, radial basis function
- RF, random forest
- SC-PseDNC-General, General series correlation pseudo-dinucleotide composition
- SE, Sensitivity
- SP, Specifity
- SVM, support vector machine
- Triplet, Local structure-sequence triplet element
- circRNA, circular RNA
- lncRNAs, long non-coding RNAs
Collapse
|
5
|
Yan W, Hu H, Tang B. Progress in understanding the relationship between long noncoding RNA and endometriosis. Eur J Obstet Gynecol Reprod Biol X 2019; 5:100067. [PMID: 32021971 PMCID: PMC6994393 DOI: 10.1016/j.eurox.2019.100067] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 06/05/2019] [Accepted: 06/10/2019] [Indexed: 12/26/2022] Open
Abstract
Endometriosis is a common gynecological disease. However, the etiology of endometriosis is still unclear, and current theories cannot fully elaborate its specific pathogenesis. Recently, some research has suggested that the occurrence and development of endometriosis may be related to genetics. Long-chain non-coding RNA (lncRNAs) is a kind of non-protein-coding RNA molecule with a length of 200-100,000 bp. With complex biological functions, lncRNAs play an important role in the normal development of individuals and the progression of various diseases, and lncRNAs have become an important field of medical research in recent years. This paper mainly illustrates the research progress on lncRNAs as they relate to endometriosis. We also provide some ideas for exploring the pathogenesis of endometriosis.
Collapse
Key Words
- CDK6, cyclin dependent kinase 6
- EMs, Endometriosis
- Early diagnosis
- Endometriosis
- HIF-1α, Hypoxia inducible factor-1alpha
- Igf1r, insulin-like growth factor-1 receptor
- Igf2, insulin-like growth factor 2
- NATs, natural antisense transcripts
- Non-coding RNA
- SRA, Steroid receptor RNA activator
- SRAP, steroid receptor activator protein
- lncRNAs
- lncRNAs, long non-coding RNAs
- ncRNAs, non-coding RNAs
- piRNAs, PIWI-interacting RNAs
- siRNAs, short inhibitory RNAs
- snRNAs, small nuclear RNAs
Collapse
Affiliation(s)
- Wenying Yan
- Department of Gynecology, Wangjiang Hospital, Sichuan University, China, No. 24, South Section of First Ring Road, Chengdu City, Sichuan Province, China
| | - Hongmei Hu
- Department of Gynecology, Sichuan Maternal and Child Health Hospital, No. 290 Shayan West Second Street, Jinyang Road, Chengdu City, Sichuan Province, China
| | - Biao Tang
- Department of Gynecology, Sichuan Maternal and Child Health Hospital, No. 290 Shayan West Second Street, Jinyang Road, Chengdu City, Sichuan Province, China
- Corresponding author.
| |
Collapse
|
6
|
Xu L, Zhu H, Gao F, Tang Y, Zhu Y, Sun Z, Wang J. Upregulation of the long non-coding RNA CBR3-AS1 predicts tumor prognosis and contributes to breast cancer progression. Gene 2019; 721S:100014. [PMID: 32550547 PMCID: PMC7285981 DOI: 10.1016/j.gene.2019.100014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [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: 08/15/2018] [Revised: 03/13/2019] [Accepted: 03/16/2019] [Indexed: 01/14/2023]
Abstract
Breast cancer is the most common female malignancy and the major cause of cancer-related death in women. Long non-coding RNAs (lncRNAs), as oncogenic or tumor suppressor factor, involved in the development and progression of various cancers. In this study, we sought to investigate the function of lncRNA CBR3-AS1 in breast cancer. We evaluated the expression pattern of CBR3-AS1 in breast cancer tissues and cell lines, explored the correlation between CBR3-AS1 expression and the survival time of breast cancer patients, and probed the effect of CBR3-AS1 on tumor progression of breast cancer through loss-of-function and gain-of-function strategies. Our results showed that CBR3-AS1 was overexpressed in breast cancer tissues and cell lines and predicted the prognosis of breast cancer patients. And CBR3-AS1 exerted biological function as an oncogenic lncRNA, involved in the regulation of cell proliferation, colony formation, apoptosis and tumor growth in breast cancer. Taken together, CBR3-AS1 was up-regulated in breast cancer and promoted the risk of breast cancer. It may be a novel therapeutic target and potential prognostic marker for breast cancer. lncRNA CBR3-AS1 is up-regulated in breast cancer tissues and cell lines. High CBR3-AS1 expression predicted poor prognosis in breast cancer patients. CBR3-AS1 promote breast cancer cell growth in vitro and in vivo.
Collapse
Affiliation(s)
- Lingyun Xu
- Department of Breast Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213001, China
| | - Hong Zhu
- Department of Radiation Oncology, Minhang Branch of Cancer Hospital of Fudan University, Shanghai 200240, China
| | - Fei Gao
- Family Planning Department, The Affiliated Changzhou Maternal and Child Health Care Hospital of Nanjing Medical University, Changzhou 213001, China
| | - Yinghua Tang
- Breast Surgery Department, The Affiliated Changzhou Maternal and Child Health Care Hospital of Nanjing Medical University, Changzhou 213001, China
| | - Yajun Zhu
- Department of Radiation Oncology, Changzhou Jintan District People's Hospital of Jiangsu University, Changzhou 213200, China
| | - Zhiqiang Sun
- Department of Radiotherapy, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213001, China
| | - Jian Wang
- Department of Radiotherapy, Jiangyin People's Hospital, Affiliated Hospital of Southeast University, Jiangyin, 214400, China
| |
Collapse
|
7
|
Gomes CP, Salgado-Somoza A, Creemers EE, Dieterich C, Lustrek M, Devaux Y. Circular RNAs in the cardiovascular system. Noncoding RNA Res 2018; 3:1-11. [PMID: 30159434 PMCID: PMC6084836 DOI: 10.1016/j.ncrna.2018.02.002] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [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: 10/31/2017] [Revised: 01/16/2018] [Accepted: 02/22/2018] [Indexed: 02/06/2023] Open
Abstract
Until recently considered as rare, circular RNAs (circRNAs) are emerging as important regulators of gene expression. They are ubiquitously expressed and represent a novel branch of the family of non-coding RNAs. Recent investigations showed that circRNAs are regulated in the cardiovascular system and participate in its physiological and pathological development. In this review article, we will provide an overview of the role of circRNAs in cardiovascular health and disease. After a description of the biogenesis of circRNAs, we will summarize what is known of the expression, regulation and function of circRNAs in the cardiovascular system. We will then address some technical aspects of circRNAs research, discussing how artificial intelligence may aid in circRNAs research. Finally, the potential of circRNAs as biomarkers of cardiovascular disease will be addressed and directions for future research will be proposed.
Collapse
Key Words
- Artificial intelligence
- Biomarker
- CRISPR, clustered regularly interspaced short palindromic repeats
- CV, cardiovascular
- Cardiovascular disease
- Cardiovascular system
- Circular RNAs
- DCM, dilated cardiomyopathy
- EMT, epithelial-mesenchymal transition
- Non-coding RNAs
- RNA-seq, RNA sequencing
- RPAD, RNase R treatment followed by polyadenylation and poly(A)+ RNA depletion
- RT-qPCR, reverse transcription quantitative polymerase chain reaction
- circRNAs, circular RNAs
- lncRNAs, long non-coding RNAs
- miRNAs, microRNAs
- ncRNAs, non-coding RNAs
Collapse
Affiliation(s)
- Clarissa P.C. Gomes
- Cardiovascular Research Unit, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | | | - Esther E. Creemers
- Experimental Cardiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Christoph Dieterich
- German Center for Cardiovascular Research, University Hospital Heidelberg, Heidelberg, Germany
| | - Mitja Lustrek
- Department of Intelligent Systems, Jozef Stefan Institute, Ljubljana, Slovenia
| | - Yvan Devaux
- Cardiovascular Research Unit, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | | |
Collapse
|
8
|
Gao C, He Z, Li J, Li X, Bai Q, Zhang Z, Zhang X, Wang S, Xiao X, Wang F, Yan Y, Li D, Chen L, Zeng X, Xiao Y, Dong G, Zheng Y, Wang Q, Chen W. Specific long non-coding RNAs response to occupational PAHs exposure in coke oven workers. Toxicol Rep 2016; 3:160-166. [PMID: 28959535 PMCID: PMC5615781 DOI: 10.1016/j.toxrep.2015.12.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [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: 11/19/2015] [Revised: 12/29/2015] [Accepted: 12/29/2015] [Indexed: 11/21/2022] Open
Abstract
To explore whether the alteration of lncRNA expression is correlated with polycyclic aromatic hydrocarbons (PAHs) exposure and DNA damage, we examined PAHs external and internal exposure, DNA damage and lncRNAs (HOTAIR, MALAT1, TUG1 and GAS5) expression in peripheral blood lymphocytes (PBLCs) of 150 male coke oven workers and 60 non-PAHs exposure workers. We found the expression of HOTAIR, MALAT1, and TUG1 were enhanced in PBLCs of coke oven workers and positively correlated with the levels of external PAHs exposure (adjusted Ptrend < 0.001 for HOTAIR and MALAT1, adjusted Ptrend = 0.006 for TUG1). However, only HOTAIR and MALAT1 were significantly associated with the level of internal PAHs exposure (urinary 1-hydroxypyrene) with adjusted β = 0.298, P = 0.024 for HOTAIR and β = 0.090, P = 0.034 for MALAT1. In addition, the degree of DNA damage was positively associated with MALAT1 and HOTAIR expression in PBLCs of all subjects (adjusted β = 0.024, P = 0.002 for HOTAIR and β = 0.007, P = 0.003 for MALAT1). Moreover, we revealed that the global histone 3 lysine 27 trimethylation (H3K27me3) modification was positively associated with the degree of genetic damage (β = 0.061, P < 0.001) and the increase of HOTAIR expression (β = 0.385, P = 0.018). Taken together, our findings suggest that altered HOTAIR and MALAT1 expression might be involved in response to PAHs-induced DNA damage.
Collapse
Affiliation(s)
- Chen Gao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhini He
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jie Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiao Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Qing Bai
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhengbao Zhang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiao Zhang
- Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shan Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xinhua Xiao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Fangping Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yan Yan
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Daochuan Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Liping Chen
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiaowen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yongmei Xiao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yuxin Zheng
- Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qing Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Wen Chen
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| |
Collapse
|
9
|
Abstract
The drug metabolism is a biochemical process on modification of pharmaceutical substances through specialized enzymatic systems. Changes in the expression of drug-metabolizing enzyme genes can affect drug metabolism. Recently, epigenetic regulation of drug-metabolizing enzyme genes has emerged as an important mechanism. Epigenetic regulation refers to heritable factors of genomic modifications that do not involve changes in DNA sequence. Examples of such modifications include DNA methylation, histone modifications, and non-coding RNAs. This review examines the widespread effect of epigenetic regulations on genes involved in drug metabolism, and also suggests a network perspective of epigenetic regulation. The epigenetic mechanisms have important clinical implications and may provide insights into effective drug development and improve safety of drug therapy.
Collapse
Key Words
- CAR, constitutive androstane receptor
- DNA methylation
- DNMTs, DNA methyltransferases
- Drug metabolism
- Epigenetics
- H3K27me3, histone 3 lysine 27 trimethylation
- H3K36me3, histone 3 lysine 36 trimethylation
- H3K4me1, histone 3 lysine 4 monomethylation
- H3K4me2, histone 3 lysine 4 dimethylation
- H3K4me3, histone 3 lysine 4 trimethylation
- H3K9me2, histone 3 lysine 9 dimethylation
- H3K9me3, histone 3 lysine 9 trimethylation
- HATs, histone acetyltransferases
- HDAC, histone deacetylases
- Histone modification
- Non-coding RNA
- P450s, cytochrome P450s
- SULTs, sulfotransferases
- TSS, transcription start sites
- Transporter
- UGTs, UDP-glucuronosyltransferases
- UTR, untranslated region
- lncRNAs, long non-coding RNAs
- miRNAs, microRNAs
- ncRNAs, non-coding RNAs
Collapse
|
10
|
Abstract
A significant portion of the mammalian genome encodes numerous transcripts that are not translated into proteins, termed long non-coding RNAs. Initial studies identifying long non-coding RNAs inferred these RNA sequences were a consequence of transcriptional noise or promiscuous RNA polymerase II activity. However, the last decade has seen a revolution in the understanding of regulation and function of long non-coding RNAs. Now it has become apparent that long non-coding RNAs play critical roles in a wide variety of biological processes. In this review, we describe the current understanding of long non-coding RNA-mediated regulation of cellular processes: differentiation, development, and disease.
Collapse
Key Words
- Bvht, braveheart
- CDT, C-terminal domain
- DBE-T, D4Z4-binding element
- DMD, Duchenne muscular dystrophy
- ES, embryonic stem
- FSHD, facioscapulohumeral muscular dystrophy
- Fendrr, Foxf1a called fetal-lethal non-coding developmental regulatory RNA
- MEF2, myocyte enhancer factor-2
- MRFs, myogenic regulatory factors
- Malat1, metastasis associated lung adenocarcinoma transcript 1
- Mesp1, mesoderm progenitor 1
- Neat2, nuclear-enriched abundant transcript 2
- PRC2, polycomb group repressive complex 2
- RNAP II, RNA polymerase II
- SINE, short interspersed element
- SR, serine arginine
- SRA, steroid receptor activator
- SRY, sex-determining region Y
- YAM 1-4, YY1-associated muscle 1-4
- ceRNAs, competing endogenous RNAs
- ciRS-7, circular RNA sponge for miR-7
- development
- differentiation
- disease
- gene expression
- iPS, induced pluripotent stem
- lncRNAs, long non-coding RNAs
- long non-coding RNAs
- ncRNAa, non-coding RNA activating
- skeletal muscle
Collapse
Affiliation(s)
- Bijan K Dey
- a Department of Biochemistry and Molecular Genetics ; University of Virginia School of Medicine ; Charlottesville , VA USA
| | | | | |
Collapse
|