miRNA interplay: Mechanisms and therapeutic interventions in cancer

Zehua Wang, Hangxuan Wang, Shuhan Zhou, Jiasheng Mao, Zhiqing Zhan, Shiwei Duan

MEDCOMM - Oncology ›› 2024, Vol. 3 ›› Issue (4) : e93.

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MEDCOMM - Oncology ›› 2024, Vol. 3 ›› Issue (4) : e93. DOI: 10.1002/mog2.93
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miRNA interplay: Mechanisms and therapeutic interventions in cancer

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Abstract

MicroRNAs (miRNAs) are key molecules that regulate gene expression. miRNAs regulate protein synthesis by binding to mRNA, influencing processes such as cell proliferation, metastasis, and apoptosis. They play a pivotal role in cancer development. Current research mainly explores miRNA mechanisms and applications, and the techniques underpinning this research are foundational to both basic science and clinical translation. However, no review has comprehensively examined miRNA mechanisms and applications from a technical perspective, creating a need for this work. Advances in RNA sequencing technology, CRISPR/Cas9 technology, and bioinformatics tools have deepened our understanding of miRNA interactions. miRNA can serve as a biomarker for cancer diagnosis and prognosis, with significant clinical potential. The development of miRNA mimics and inhibitors has brought new hope for cancer treatment, especially in reversing cancer drug resistance. This article reviews the vital role of miRNA interactions in cancer occurrence, development, diagnosis, and treatment, providing new perspectives and strategies for personalized medicine and cancer therapy.

Keywords

biomarkers / cancer / microRNAs / therapeutics

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Zehua Wang, Hangxuan Wang, Shuhan Zhou, Jiasheng Mao, Zhiqing Zhan, Shiwei Duan. miRNA interplay: Mechanisms and therapeutic interventions in cancer. MEDCOMM - Oncology, 2024, 3(4): e93 https://doi.org/10.1002/mog2.93

References

[1]
MacfarlaneLA, R. Murphy P. MicroRNA: biogenesis, function and role in cancer. Curr Genomics. 2010;11(7):537-561.
CrossRef Google scholar
[2]
HeB, ZhaoZ, CaiQ, et al. miRNA-based biomarkers, therapies, and resistance in cancer. Int J Biol Sci. 2020;16(14):2628-2647.
CrossRef Google scholar
[3]
O’BrienJ, HayderH, ZayedY, et al. Overview of MicroRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol. 2018;9:402.
CrossRef Google scholar
[4]
SaliminejadK, Khorram Khorshid HR, Soleymani FardS, GhaffariSH. An overview of microRNAs: biology, functions, therapeutics, and analysis methods. J Cell Physiol. 2019;234(5):5451-5465.
CrossRef Google scholar
[5]
RyczekN, Łyś A, MakałowskaI. The functional meaning of 5’UTR in protein-coding genes. Int J Mol Sci. 2023;24(3):2976.
CrossRef Google scholar
[6]
TufekciKU, Meuwissen RL, GencS. The role of microRNAs in biological processes. Methods Mol Biol. 2014;1107:15-31.
CrossRef Google scholar
[7]
VishnoiA, RaniS. MiRNA biogenesis and regulation of diseases: an overview. Methods Mol Biol. 2017;1509:1-10.
CrossRef Google scholar
[8]
WithanageMHH, LiangH, ZengE. RNA-Seq experiment and data analysis. Methods Mol Biol. 2022;2418:405-424.
CrossRef Google scholar
[9]
BenesovaS, Kubista M, ValihrachL. Small RNA-sequencing: approaches and considerations for miRNA analysis. Diagnostics. 2021;11(6):964.
CrossRef Google scholar
[10]
PengJ, SunBF, ChenCY, et al. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Res. 2019;29(9):725-738.
CrossRef Google scholar
[11]
TanZ, ChenX, ZuoJ, FuS, WangH, Wang J. Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model. J Transl Med. 2023;21(1):223.
CrossRef Google scholar
[12]
NookaewI, PapiniM, PornputtapongN, et al. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in saccharomyces cerevisiae. Nucleic Acids Res. 2012;40(20):10084-10097.
CrossRef Google scholar
[13]
ShiJ, ZhangY, TanD, et al. PANDORA-seq expands the repertoire of regulatory small RNAs by overcoming RNA modifications. Nat Cell Biol. 2021;23(4):424-436.
CrossRef Google scholar
[14]
SekiM, Katsumata E, SuzukiA, et al. Evaluation and application of RNA-Seq by MinION. DNA Res. 2019;26(1):55-65.
CrossRef Google scholar
[15]
ChangH, YiB, MaR, ZhangX, ZhaoH, Xi Y. CRISPR/cas9, a novel genomic tool to knock down microRNA in vitro and in vivo. Sci Rep. 2016;6:22312.
CrossRef Google scholar
[16]
ZhangY, WangLY, LiJZ, JiangPF, HuJD, ChenBY. CRISPR/Cas9-mediated microRNA-21 knockout increased imatinib sensitivity in chronic myeloid leukemia cells. Zhonghua xue ye xue za zhi =Zhonghua xueyexue zazhi. 2021;42(3):243-249.
[17]
HussenBM, RasulMF, AbdullahSR, et al. Targeting miRNA by CRISPR/Cas in cancer: advantages and challenges. Mil Med Res. 2023;10(1):32.
CrossRef Google scholar
[18]
FonfaraI, Richter H, BratovičM, Le RhunA, Charpentier E. The CRISPR-associated DNA-cleaving enzyme Cpf1 also processes precursor CRISPR RNA. Nature. 2016;532(7600):517-521.
CrossRef Google scholar
[19]
LuY, ChanYT, WuJ, et al. CRISPR/Cas9 screens unravel miR-3689a-3p regulating sorafenib resistance in hepatocellular carcinoma via suppressing CCS/SOD1-dependent mitochondrial oxidative stress. Drug Resist Updates. 2023;71:101015.
CrossRef Google scholar
[20]
PacesaM, PeleaO, JinekM. Past, present, and future of CRISPR genome editing technologies. Cell. 2024;187(5):1076-1100.
CrossRef Google scholar
[21]
Ali SyedaZ, Langden SSS, MunkhzulC, LeeM, SongSJ. Regulatory mechanism of MicroRNA expression in cancer. Int J Mol Sci. 2020;21(5):1723.
CrossRef Google scholar
[22]
HuangZ, KallerM, HermekingH. CRISPR/Cas9-mediated inactivation of miR-34a and miR-34b/c in HCT116 colorectal cancer cells: comprehensive characterization after exposure to 5-FU reveals EMT and autophagy as key processes regulated by miR-34. Cell Death Differ. 2023;30(8):2017-2034.
CrossRef Google scholar
[23]
ChenL, Heikkinen L, WangC, YangY, SunH, WongG. Trends in the development of miRNA bioinformatics tools. Brief Bioinform. 2019;20(5):1836-1852.
CrossRef Google scholar
[24]
BetelD, KoppalA, AgiusP, Sander C, LeslieC. Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol. 2010;11(8):R90.
CrossRef Google scholar
[25]
KozomaraA, Birgaoanu M, Griffiths-JonesS. miRBase: from microRNA sequences to function. Nucleic Acids Res. 2019;47(D1):D155-D162.
CrossRef Google scholar
[26]
AgarwalV, BellGW, NamJW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. eLife. 2015;4:e05005.
CrossRef Google scholar
[27]
LallS, Grün D, KrekA, et al. A genome-wide map of conserved microRNA targets in C. elegans. Curr Biol. 2006;16(5):460-471.
CrossRef Google scholar
[28]
KrugerJ, Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 2006;34(Web Server issue):W451-W454.
CrossRef Google scholar
[29]
KaragkouniD, Paraskevopoulou MD, ChatzopoulosS, et al. DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA-gene interactions. Nucleic Acids Res. 2018;46(D1):D239-D245.
CrossRef Google scholar
[30]
LoherP, Rigoutsos I. Interactive exploration of RNA22 microRNA target predictions. Bioinformatics. 2012;28(24):3322-3323.
CrossRef Google scholar
[31]
HuangJC, BabakT, CorsonTW, et al. Using expression profiling data to identify human microRNA targets. Nat Methods. 2007;4(12):1045-1049.
CrossRef Google scholar
[32]
BhattacharyaA, Ziebarth JD, CuiY. PolymiRTS database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res. 2014;42(Database issue):D86-D91.
CrossRef Google scholar
[33]
ChenY, WangX. miRDB: an online database for prediction of functional microRNA targets. Nucleic Acids Res. 2020;48(D1):D127-D131.
CrossRef Google scholar
[34]
ChoS, JangI, JunY, et al. MiRGator v3.0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting. Nucleic Acids Res. 2013;41:252-257.
CrossRef Google scholar
[35]
XiaoF, ZuoZ, CaiG, KangS, GaoX, LiT. miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 2009;37:D105-D110.
CrossRef Google scholar
[36]
HeikkinenL, Kolehmainen M, WongG. Prediction of microRNA targets in Caenorhabditis elegans using a self-organizing map. Bioinformatics. 2011;27(9):1247-1254.
CrossRef Google scholar
[37]
TokarT, Pastrello C, RossosAEM, et al. mirDIP 4.1-integrative database of human microRNA target predictions. Nucleic Acids Res. 2018;46(D1):D360-D370.
CrossRef Google scholar
[38]
ChouCH, Shrestha S, YangCD, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018;46(D1):D296-D302.
[39]
DaiX, ZhaoPX. psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 2011;39:W155-W159.
CrossRef Google scholar
[40]
ChengS, GuoM, WangC, Liu X, LiuY, WuX. MiRTDL: a deep learning approach for miRNA target prediction. IEEE/ACM Trans Comput Biol Bioinf. 2016;13(6):1161-1169.
CrossRef Google scholar
[41]
TastsoglouS, Alexiou A, KaragkouniD, SkoufosG, Zacharopoulou E, HatzigeorgiouAG. DIANA-microT 2023: including predicted targets of virally encoded miRNAs. Nucleic Acids Res. 2023;51(W1):W148-W153.
CrossRef Google scholar
[42]
Van PeerG, De Paepe A, StockM, et al. miSTAR: miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure. Nucleic Acids Res. 2017;45(7):e51.
[43]
PerdikopanisN, Georgakilas GK, GrigoriadisD, et al. DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs. Nucleic Acids Res. 2021;49(D1):D151-D159.
CrossRef Google scholar
[44]
TastsoglouS, Skoufos G, MiliotisM, et al. DIANA-miRPath v4.0: expanding target-based miRNA functional analysis in cell-type and tissue contexts. Nucleic Acids Res. 2023;51(W1):W154-W159.
CrossRef Google scholar
[45]
LiJH, LiuS, ZhouH, Qu LH, YangJH. starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 2014;42:D92-D97.
CrossRef Google scholar
[46]
DweepH, GretzN. miRWalk2.0: a comprehensive Atlas of microRNA-target interactions. Nat Methods. 2015;12(8):697.
CrossRef Google scholar
[47]
ChouCH, LinFM, ChouMT, et al. A computational approach for identifying microRNA-target interactions using high-throughput CLIP and PAR-CLIP sequencing. BMC Genom. 2013;14(suppl 1):S2.
CrossRef Google scholar
[48]
BottiniS, Hamouda-Tekaya N, TanasaB, et al. From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data. Nucleic Acids Res. 2017;45(9):gkx007.
CrossRef Google scholar
[49]
AhadiA, SablokG, HutvagnerG. miRTar2GO: a novel rule-based model learning method for cell line specific microRNA target prediction that integrates Ago2 CLIP-Seq and validated microRNA-target interaction data. Nucleic Acids Res. 2017;45(6):e42.
CrossRef Google scholar
[50]
YangS, WangY, LinY, ShaoD, HeK, HuangL. LncMirNet: predicting LncRNA-miRNA interaction based on deep learning of ribonucleic acid sequences. Molecules. 2020;25(19):4372.
CrossRef Google scholar
[51]
WuR, MaR, DuanX, et al. Identification of specific prognostic markers for lung squamous cell carcinoma based on tumor progression, immune infiltration, and stem index. Front Immunol. 2023;14:1236444.
CrossRef Google scholar
[52]
ChenY, YaoL, TangY, et al. CircNet 2.0: an updated database for exploring circular RNA regulatory networks in cancers. Nucleic Acids Res. 2022;50(D1):D93-D101.
CrossRef Google scholar
[53]
FengJ, ChenW, DongX, et al. CSCD2: an integrated interactional database of cancer-specific circular RNAs. Nucleic Acids Res. 2022;50(D1):D1179-D1183.
CrossRef Google scholar
[54]
LiuM, WangQ, ShenJ, Yang BB, DingX. Circbank: a comprehensive database for circRNA with standard nomenclature. RNA Biol. 2019;16(7):899-905.
CrossRef Google scholar
[55]
DudekulaDB, PandaAC, GrammatikakisI, DeS, Abdelmohsen K, GorospeM. CircInteractome: a web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biol. 2016;13(1):34-42.
CrossRef Google scholar
[56]
WeiMM, YuCQ, LiLP, YouZH, WangL. BCMCMI: a fusion model for predicting circRNA-miRNA interactions combining semantic and meta-path. J Chem Inf Model. 2023;63(16):5384-5394.
CrossRef Google scholar
[57]
AlsayedRKME, Sheikhan KSAM, AlamMA, et al. Epigenetic programing of cancer stemness by transcription factors-non-coding RNAs interactions. Sem Cancer Biol. 2023;92:74-83.
CrossRef Google scholar
[58]
LeTD, LiuL, ZhangJ, Liu B, LiJ. From miRNA regulation to miRNA-TF co-regulation: computational approaches and challenges. Brief Bioinform. 2015;16(3):475-496.
CrossRef Google scholar
[59]
de VeldeJV, Heyndrickx KS, VandepoeleK. Inference of transcriptional networks inarabidopsisthrough conserved noncoding sequence analysis. Plant Cell. 2014;26(7):2729-2745.
CrossRef Google scholar
[60]
ZhangX, ShenB, CuiY. Ago HITS-CLIP expands microRNA-mRNA interactions in nucleus and cytoplasm of gastric cancer cells. BMC Cancer. 2019;19(1):29.
CrossRef Google scholar
[61]
HuangGT, Athanassiou C, BenosPV. mirConnX: condition-specific mRNA-microRNA network integrator. Nucleic Acids Res. 2011;39(Web Server issue):W416-W423.
CrossRef Google scholar
[62]
FeitosaRMMW, Prieto-Oliveira P, BrentaniH, Machado-LimaA. MicroRNA target prediction tools for animals: where we are at and where we are going to -A systematic review. Comput Biol Chem. 2022;100:107729.
CrossRef Google scholar
[63]
FanJ, Slowikowski K, ZhangF. Single-cell transcriptomics in cancer: computational challenges and opportunities. Exp Mol Med. 2020;52(9):1452-1465.
CrossRef Google scholar
[64]
ChaudharyK, Poirion OB, LuL, GarmireLX. Deep learning-based multi-omics integration robustly predicts survival in liver cancer. Clin Cancer Res. 2018;24(6):1248-1259.
CrossRef Google scholar
[65]
SumathipalaM, WeissST. Predicting miRNA-based disease-disease relationships through network diffusion on multi-omics biological data. Sci Rep. 2020;10(1):8705.
CrossRef Google scholar
[66]
ChhabraR. miRNA and methylation: a multifaceted liaison. ChemBioChem. 2015;16(2):195-203.
CrossRef Google scholar
[67]
LinY, QiX, ChenJ, Shen B. Multivariate competing endogenous RNA network characterization for cancer microRNA biomarker discovery: a novel bioinformatics model with application to prostate cancer metastasis. Precis Clin Med. 2022;5(1):pbac001.
CrossRef Google scholar
[68]
TianL, ChenF, MacoskoEZ. The expanding vistas of spatial transcriptomics. Nat Biotechnol. 2023;41(6):773-782.
CrossRef Google scholar
[69]
KongM, HongDH, PaudelS, et al. Metabolomics and miRNA profiling reveals feature of gallbladder cancer-derived biliary extracellular vesicles. Biochem Biophys Res Commun. 2024;705:149724.
CrossRef Google scholar
[70]
ZhangS, ShenC, LiJ, et al. Identification of hub genes for colorectal cancer with liver metastasis using miRNA-mRNA network. Dis Markers. 2023;2023:2295788.
CrossRef Google scholar
[71]
HeK, LiWX, GuanD, et al. Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. Funct Integr Genomics. 2019;19(4):645-658.
CrossRef Google scholar
[72]
ShaoT, WangG, ChenH, et al. Survey of miRNA-miRNA cooperative regulation principles across cancer types. Brief Bioinform. 2019;20(5):1621-1638.
CrossRef Google scholar
[73]
KumeH, HinoK, GaliponJ, Ui-Tei K. A-to-I editing in the miRNA seed region regulates target mRNA selection and silencing efficiency. Nucleic Acids Res. 2014;42(15):10050-10060.
CrossRef Google scholar
[74]
CherayM, Etcheverry A, JacquesC, et al. Cytosine methylation of mature microRNAs inhibits their functions and is associated with poor prognosis in glioblastoma multiforme. Mol Cancer. 2020;19(1):36.
CrossRef Google scholar
[75]
ZhangX, ZhuWY, ShenSY, Shen JH, ChenXD. Biological roles of RNA m7G modification and its implications in cancer. Biol Direct. 2023;18(1):58.
CrossRef Google scholar
[76]
Correia de SousaM, Gjorgjieva M, DolickaD, et al. Deciphering miRNAs’action through miRNA editing. Int J Mol Sci. 2019;20(24):6249.
CrossRef Google scholar
[77]
HillM, TranN. miRNA interplay: mechanisms and consequences in cancer. Dis Models Mech. 2021;14(4):dmm047662.
CrossRef Google scholar
[78]
DienerC, KellerA, MeeseE. The miRNA-target interactions: an underestimated intricacy. Nucleic Acids Res. 2024;52(4):1544-1557.
CrossRef Google scholar
[79]
DharapA, Pokrzywa C, MuraliS, PandiG, Vemuganti R. MicroRNA miR-324-3p induces promoter-mediated expression of RelA gene. PLoS ONE. 2013;8(11):e79467.
CrossRef Google scholar
[80]
YaoW, GuoG, ZhangQ, Fan L, WuN, BoY. The application of multiple miRNA response elements enables oncolytic adenoviruses to possess specificity to glioma cells. Virology. 2014;458-459:69-82.
CrossRef Google scholar
[81]
HaM, KimVN. Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol. 2014;15(8):509-524.
CrossRef Google scholar
[82]
KangD, LeeY, LeeJS. RNA-binding proteins in cancer: functional and therapeutic perspectives. Cancers. 2020;12(9):2699.
CrossRef Google scholar
[83]
SeoY, RhimJ, KimJH. RNA-binding proteins and exoribonucleases modulating miRNA in cancer: the enemy within. Exp Mol Med. 2024;56(5):1080-1106.
CrossRef Google scholar
[84]
HillM, TranN. MicroRNAs regulating MicroRNAs in cancer. Trends Cancer. 2018;4(7):465-468.
CrossRef Google scholar
[85]
OdameE, ChenY, ZhengS, et al. Enhancer RNAs: transcriptional regulators and workmates of NamiRNAs in myogenesis. Cell Mol Biol Lett. 2021;26(1):4.
CrossRef Google scholar
[86]
LiangY, LuQ, LiW, et al. Reactivation of tumour suppressor in breast cancer by enhancer switching through NamiRNA network. Nucleic Acids Res. 2021;49(15):8556-8572.
CrossRef Google scholar
[87]
FusoA, RaiaT, OrticelloM, Lucarelli M. The complex interplay between DNA methylation and miRNAs in gene expression regulation. Biochimie. 2020;173:12-16.
CrossRef Google scholar
[88]
GebertLFR, MacRaeIJ. Regulation of microRNA function in animals. Nat Rev Mol Cell Biol. 2019;20(1):21-37.
CrossRef Google scholar
[89]
XieZ, ZhongC, ShenJ, Jia Y, DuanS. LINC00963: a potential cancer diagnostic and therapeutic target. Biomed Pharmacother. 2022;150:113019.
CrossRef Google scholar
[90]
DongQ, QiuH, PiaoC, Li Z, CuiX. LncRNA SNHG4 promotes prostate cancer cell survival and resistance to enzalutamide through a let-7a/RREB1 positive feedback loop and a ceRNA network. J Exp Clin Cancer Res. 2023;42(1):209.
CrossRef Google scholar
[91]
ChenP, NieZY, LiuXF, Zhou M, LiuXX, WangB. CircXRCC5, as a potential novel biomarker, promotes glioma progression via the miR-490-3p/XRCC5/CLC3 competing endogenous RNA network. Neuroscience. 2022;494:104-118.
CrossRef Google scholar
[92]
IftikharH, CarneyGE. Evidence and potential in vivo functions for biofluid miRNAs: from expression profiling to functional testing: potential roles of extracellular miRNAs as indicators of physiological change and as agents of intercellular information exchange. BioEssays. 2016;38(4):367-378.
CrossRef Google scholar
[93]
TurchinovichA, Tonevitsky AG, BurwinkelB. Extracellular miRNA: a collision of two paradigms. Trends Biochem Sci. 2016;41(10):883-892.
CrossRef Google scholar
[94]
MishraS, YadavT, RaniV. Exploring miRNA based approaches in cancer diagnostics and therapeutics. Crit Rev Oncol Hematol. 2016;98:12-23.
CrossRef Google scholar
[95]
UzunerE, UluGT, GurlerSB, et al. The role of MiRNA in cancer: pathogenesis, diagnosis, and treatment. Methods Mol Biol. 2022;2257:375-422.
CrossRef Google scholar
[96]
InoueJ, Inazawa J. Cancer-associated miRNAs and their therapeutic potential. J Hum Genet. 2021;66(9):937-945.
CrossRef Google scholar
[97]
HussenBM, Hidayat HJ, SalihiA, SabirDK, TaheriM, Ghafouri-FardS. MicroRNA: a signature for cancer progression. Biomed Pharmacother. 2021;138:111528.
CrossRef Google scholar
[98]
ArghianiN, MatinMM. miR-21: a key small molecule with great effects in combination cancer therapy. Nucleic Acid Ther. 2021;31(4):271-283.
CrossRef Google scholar
[99]
MenonA, Abd-Aziz N, KhalidK, PohCL, NaiduR. miRNA: a promising therapeutic target in cancer. Int J Mol Sci. 2022;23(19):11502.
CrossRef Google scholar
[100]
MensMMJ, Ghanbari M. Cell cycle regulation of stem cells by MicroRNAs. Stem Cell Rev Rep. 2018;14(3):309-322.
CrossRef Google scholar
[101]
DongB, LiS, ZhuS, YiM, LuoS, WuK. MiRNA-mediated EMT and CSCs in cancer chemoresistance. Exp Hematol Oncol. 2021;10(1):12.
CrossRef Google scholar
[102]
WangH. MicroRNAs and apoptosis in colorectal cancer. Int J Mol Sci. 2020;21(15):5353.
CrossRef Google scholar
[103]
Ferragut CardosoAP, Banerjee M, NailAN, LykoudiA, StatesJC. miRNA dysregulation is an emerging modulator of genomic instability. Sem Cancer Biol. 2021;76:120-131.
CrossRef Google scholar
[104]
GuptaJ, TayyibNA, JalilAT, et al. Angiogenesis and prostate cancer: MicroRNAs comes into view. Pathol Res Pract. 2023;248:154591.
CrossRef Google scholar
[105]
PinwehaP, Rattanapornsompong K, CharoensawanV, JitrapakdeeS. MicroRNAs and oncogenic transcriptional regulatory networks controlling metabolic reprogramming in cancers. Comput Struct Biotechnol J. 2016;14:223-233.
CrossRef Google scholar
[106]
KumarR, MishraA, GautamP, et al. Metabolic pathways, enzymes, and metabolites: opportunities in cancer therapy. Cancers. 2022;14(21):5268.
CrossRef Google scholar
[107]
YangY, YuanH, ZhaoL, et al. Targeting the miR-34a/LRPPRC/MDR1 axis collapse the chemoresistance in P53 inactive colorectal cancer. Cell Death Differ. 2022;29(11):2177-2189.
CrossRef Google scholar
[108]
XingY, WangZ, LuZ, et al. MicroRNAs: immune modulators in cancer immunotherapy. Immunother Adv. 2021;1(1):ltab006.
CrossRef Google scholar
[109]
YaoQ, ChenY, ZhouX. The roles of microRNAs in epigenetic regulation. Curr Opin Chem Biol. 2019;51:11-17.
CrossRef Google scholar
[110]
MoutinhoC, Esteller M. MicroRNAs and epigenetics. Adv Cancer Res. 2017;135:189-220.
CrossRef Google scholar
[111]
WangS, WuW, ClaretFX. Mutual regulation of microRNAs and DNA methylation in human cancers. Epigenetics. 2017;12(3):187-197.
CrossRef Google scholar
[112]
BerulavaT, Rahmann S, RademacherK, Klein-HitpassL, Horsthemke B. N6-adenosine methylation in MiRNAs. PLoS ONE. 2015;10(2):e0118438.
CrossRef Google scholar
[113]
AmodioN, RossiM, RaimondiL, et al. miR-29s: a family of epi-miRNAs with therapeutic implications in hematologic malignancies. Oncotarget. 2015;6(15):12837-12861.
CrossRef Google scholar
[114]
YanF, ShenN, PangJ, et al. Restoration of miR-101 suppresses lung tumorigenesis through inhibition of DNMT3a-dependent DNA methylation. Cell Death Dis. 2014;5(9):e1413.
CrossRef Google scholar
[115]
AmodioN, Stamato MA, GullàAM, et al. Therapeutic targeting of miR-29b/HDAC4 epigenetic loop in multiple myeloma. Mol Cancer Ther. 2016;15(6):1364-1375.
CrossRef Google scholar
[116]
HaigD, Mainieri A. The evolution of imprinted microRNAs and their RNA targets. Genes. 2020;11(9):1038.
CrossRef Google scholar
[117]
ArtsFA, KeoghL, SmythP, et al. miR-223 potentially targets SWI/SNF complex protein SMARCD1 in atypical proliferative serous tumor and high-grade ovarian serous carcinoma. Hum Pathol. 2017;70:98-104.
CrossRef Google scholar
[118]
FaniniF, FabbriM. Cancer-derived exosomic microRNAs shape the immune system within the tumor microenvironment: state of the art. Semin Cell Dev Biol. 2017;67:23-28.
CrossRef Google scholar
[119]
RupaimooleR, CalinGA, Lopez-BeresteinG, SoodAK. miRNA deregulation in cancer cells and the tumor microenvironment. Cancer Discov. 2016;6(3):235-246.
CrossRef Google scholar
[120]
ZhouX, ZhangJ, LvW, et al. The pleiotropic roles of adipocyte secretome in remodeling breast cancer. J Exp Clin Cancer Res. 2022;41(1):203.
CrossRef Google scholar
[121]
TomasettiM, LeeW, SantarelliL, Neuzil J. Exosome-derived microRNAs in cancer metabolism: possible implications in cancer diagnostics and therapy. Exp Mol Med. 2017;49(1):e285.
CrossRef Google scholar
[122]
TanS, XiaL, YiP, et al. Exosomal miRNAs in tumor microenvironment. J Exp Clin Cancer Res. 2020;39(1):67.
CrossRef Google scholar
[123]
XingY, RuanG, NiH, et al. Tumor immune microenvironment and its related miRNAs in tumor progression. Front Immunol. 2021;12:624725.
CrossRef Google scholar
[124]
WangJ, GeJ, WangY, et al. EBV miRNAs BART11 and BART17-3p promote immune escape through the enhancer-mediated transcription of PD-L1. Nat Commun. 2022;13(1):866.
CrossRef Google scholar
[125]
ZhuangJ, ShenL, LiM, et al. Cancer-associated fibroblast-derived miR-146a-5p generates a niche that promotes bladder cancer stemness and chemoresistance. Cancer Res. 2023;83(10):1611-1627.
CrossRef Google scholar
[126]
ZhaoS, MiY, ZhengB, et al. Highly-metastatic colorectal cancer cell released miR-181a-5p-rich extracellular vesicles promote liver metastasis by activating hepatic stellate cells and remodelling the tumour microenvironment. J Extracell Vesicles. 2022;11(1):e12186.
CrossRef Google scholar
[127]
DuY, TuG, YangG, et al. MiR-205/YAP1 in activated fibroblasts of breast tumor promotes VEGF-independent angiogenesis through STAT3 signaling. Theranostics. 2017;7(16):3972-3988.
CrossRef Google scholar
[128]
ZhangZ, LiX, SunW, et al. Loss of exosomal miR-320a from cancer-associated fibroblasts contributes to HCC proliferation and metastasis. Cancer Lett. 2017;397:33-42.
CrossRef Google scholar
[129]
SunZ, ShiK, YangS, et al. Effect of exosomal miRNA on cancer biology and clinical applications. Mol Cancer. 2018;17(1):147.
CrossRef Google scholar
[130]
Ghafouri-FardS, HussenBM, ShooreiH, et al. Interactions between non-coding RNAs and HIF-1alpha in the context of cancer. Eur J Pharmacol. 2023;943:175535.
CrossRef Google scholar
[131]
WuF, LiF, LinX, et al. Exosomes increased angiogenesis in papillary thyroid cancer microenvironment. Endocr Relat Cancer. 2019;26(5):525-538.
CrossRef Google scholar
[132]
YanW, WuX, ZhouW, et al. Cancer-cell-secreted exosomal miR-105 promotes tumour growth through the MYC-dependent metabolic reprogramming of stromal cells. Nature Cell Biol. 2018;20(5):597-609.
CrossRef Google scholar
[133]
Carles-FontanaR, HeatonN, PalmaE, Khorsandi S. Extracellular Vesicle-Mediated mitochondrial reprogramming in cancer. Cancers. 2022;14(8):1865.
CrossRef Google scholar
[134]
SchmittgenTD. Exosomal miRNA cargo as mediator of immune escape mechanisms in neuroblastoma. Cancer Res. 2019;79(7):1293-1294.
CrossRef Google scholar
[135]
ZhangZ, HuangQ, YuL, et al. The Role of miRNA in Tumor Immune Escape and miRNA-Based Therapeutic Strategies. Front Immunol. 2021;12:807895.
CrossRef Google scholar
[136]
DesvignesT, BatzelP, SydesJ, Eames BF, PostlethwaitJH. miRNA analysis with prost! reveals evolutionary conservation of organ-enriched expression and post-transcriptional modifications in three-spined stickleback and zebrafish. Sci Rep. 2019;9(1):3913.
CrossRef Google scholar
[137]
KellerA, Gröger L, TschernigT, et al. miRNATissueAtlas2: an update to the human miRNA tissue Atlas. Nucleic Acids Res. 2022;50(D1):D211-D221.
CrossRef Google scholar
[138]
DexheimerPJ, Cochella L. MicroRNAs: from mechanism to organism. Front Cell Dev Biol. 2020;8:409.
CrossRef Google scholar
[139]
BalakittnenJ, Ekanayake Weeramange C, WallaceDF, et al. A novel saliva-based miRNA profile to diagnose and predict oral cancer. Int J Oral Sci. 2024;16(1):14.
CrossRef Google scholar
[140]
MarkouA, Tzanikou E, LianidouE. The potential of liquid biopsy in the management of cancer patients. Sem Cancer Biol. 2022;84:69-79.
CrossRef Google scholar
[141]
MugoniV, CianiY, NardellaC, Demichelis F. Circulating RNAs in prostate cancer patients. Cancer Lett. 2022;524:57-69.
CrossRef Google scholar
[142]
SzelenbergerR, Kacprzak M, Saluk-BijakJ, ZielinskaM, BijakM. Plasma MicroRNA as a novel diagnostic. Clin Chim Acta. 2019;499:98-107.
CrossRef Google scholar
[143]
SynNL, WangL, ChowEKH, Lim CT, GohBC. Exosomes in cancer nanomedicine and immunotherapy: prospects and challenges. Trends Biotechnol. 2017;35(7):665-676.
CrossRef Google scholar
[144]
WuP, ZhangC, TangX, et al. Pan-cancer characterization of cell-free immune-related miRNA identified as a robust biomarker for cancer diagnosis. Mol Cancer. 2024;23(1):31.
CrossRef Google scholar
[145]
Di LevaG, Garofalo M, CroceCM. MicroRNAs in cancer. Annu Rev Pathol: Mech Dis. 2014;9:287-314.
CrossRef Google scholar
[146]
ChakrabortyDS, LahiryS, ChoudhuryS. Hypertension clinical practice guidelines (ISH, 2020): what is new? Med Princ Pract. 2021;30(6):579-584.
CrossRef Google scholar
[147]
BhardwajAR, PandeyR, AgarwalM, et al. Northern blotting technique for detection and expression analysis of mRNAs and small RNAs. Methods Mol Biol. 2021;2170:155-183.
CrossRef Google scholar
[148]
WuJ, LuAD, ZhangLP, Zuo YX, JiaYP. Study of clinical outcome and prognosis in pediatric core binding factor-acute myeloid leukemia. Zhonghua xue ye xue za zhi. 2019;40(1):52-57.
[149]
YaylakB, AkgulB. Experimental MicroRNA detection methods. Methods Mol Biol. 2022;2257:33-55.
CrossRef Google scholar
[150]
LiuK, TongH, LiT, WangX, ChenY. Research progress in molecular biology related quantitative methods of MicroRNA. Am J Transl Res. 2020;12(7):3198-3211.
[151]
MaiHT, Vanness BC, LinzTH. Reverse transcription-free digital-quantitative-PCR for microRNA analysis. Analyst. 2023;148(13):3019-3027.
CrossRef Google scholar
[152]
ChuYH, HardinH, ZhangR, Guo Z, LloydRV. In situ hybridization: introduction to techniques, applications and pitfalls in the performance and interpretation of assays. Semin Diagn Pathol. 2019;36(5):336-341.
CrossRef Google scholar
[153]
MuthamilselvanS, Ramasami Sundhar Baabu P, PalaniappanA. Microfluidics for profiling miRNA biomarker panels in AI-assisted cancer diagnosis and prognosis. Technol Cancer Res Treat. 2023;22:15330338231185284.
CrossRef Google scholar
[154]
HoPTB, ClarkIM, LeLTT. MicroRNA-based diagnosis and therapy. Int J Mol Sci. 2022;23(13):7167.
CrossRef Google scholar
[155]
BhowmickSS, SahaI, BhattacharjeeD, GenoveseLM, GeraciF. Genome-wide analysis of NGS data to compile cancer-specific panels of miRNA biomarkers. PLoS ONE. 2018;13(7):e0200353.
CrossRef Google scholar
[156]
FiammengoR. Can nanotechnology improve cancer diagnosis through miRNA detection? Biomark Med. 2017;11(1):69-86.
CrossRef Google scholar
[157]
YuS, LeiX, QuC. MicroRNA sensors based on CRISPR/Cas12a technologies: evolution from indirect to direct detection. Crit Rev Anal Chem. 2024. In press.
CrossRef Google scholar
[158]
WeiJ, ZhangJ, WangW, et al. Precision miRNA profiling: electrochemiluminescence powered by CRISPR-Cas13a and hybridization chain reaction. Anal Chim Acta. 2024;1307:342641.
CrossRef Google scholar
[159]
QiuX, LiuC, ZhuC, et al. MicroRNA detection with CRISPR/Cas. Methods Mol Biol. 2023;2630:25-45.
CrossRef Google scholar
[160]
Al-HawarySIS, SalehRO, MansouriS, et al. Isothermal amplification methods in cancer-related miRNA detection;a new paradigm in study of cancer pathology. Pathol Res Prac. 2024;254:155072.
CrossRef Google scholar
[161]
YanH, WenY, TianZ, et al. A one-pot isothermal Cas12-based assay for the sensitive detection of microRNAs. Nat Biomed Eng. 2023;7(12):1583-1601.
CrossRef Google scholar
[162]
HanY, HuH, YuL, ZengS, MinJZ, Cai S. A duplex-specific nuclease (DSN) and catalytic hairpin assembly (CHA)-mediated dual amplification method for miR-146b detection. Analyst. 2023;148(3):556-561.
CrossRef Google scholar
[163]
ZhaoS, ZhangS, HuH, et al. Selective in situ analysis of mature microRNAs in extracellular vesicles using a DNA cage-based thermophoretic assay. Angew Chem Int Ed. 2023;62(24):e202303121.
CrossRef Google scholar
[164]
TreerattrakoonK, Roeksrungruang P, DharakulT, et al. Detection of a miRNA biomarker for cancer diagnosis using SERS tags and magnetic separation. Anal Methods. 2022;14(20):1938-1945.
CrossRef Google scholar
[165]
LiY, JiangL, YuZ, JiangC, ZhangF, Jin S. SPRi/SERS dual-mode biosensor based on ployA-DNA/miRNA/AuNPs-enhanced probe sandwich structure for the detection of multiple miRNA biomarkers. Spectrochim Acta Part A. 2024;308:123664.
CrossRef Google scholar
[166]
SunZ, TongY, ZhaoL, et al. MoS(2)@Ti(3)C(2) nanohybrid-based photoelectrochemical biosensor: A platform for ultrasensitive detection of cancer biomarker exosomal miRNA. Talanta. 2022;238(Pt 2):123077.
CrossRef Google scholar
[167]
SiY, XuL, WangN, Zheng J, YangR, LiJ. Target MicroRNA-responsive DNA hydrogel-based surface-enhanced Raman scattering sensor arrays for MicroRNA-marked cancer screening. Anal Chem. 2020;92(3):2649-2655.
CrossRef Google scholar
[168]
YaoS, XiangL, WangL, Gong H, ChenF, CaiC. pH-responsive DNA hydrogels with ratiometric fluorescence for accurate detection of miRNA-21. Anal Chim Acta. 2022;1207:339795.
CrossRef Google scholar
[169]
GuoJ, ZhuY, MiaoP. Nano-impact electrochemical biosensing based on a CRISPR-responsive DNA hydrogel. Nano Lett. 2023;23(23):11099-11104.
CrossRef Google scholar
[170]
AntonelliG, Filippi J, D’OrazioM, et al. Integrating machine learning and biosensors in microfluidic devices: a review. Biosens Bioelectron. 2024;263:116632.
CrossRef Google scholar
[171]
RamshaniZ, ZhangC, RichardsK, et al. Extracellular vesicle microRNA quantification from plasma using an integrated microfluidic device. Commun Biol. 2019;2:189.
CrossRef Google scholar
[172]
HøgdallD, O’Rourke CJ, LarsenFO, et al. Whole blood microRNAs capture systemic reprogramming and have diagnostic potential in patients with biliary tract cancer. J Hepatol. 2022;77(4):1047-1058.
CrossRef Google scholar
[173]
MiyoshiJ, ZhuZ, LuoA, et al. A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study. Mol Cancer. 2022;21(1):44.
CrossRef Google scholar
[174]
MatsuzakiJ, OchiyaT. Circulating microRNAs: next-generation cancer detection. Keio J Med. 2020;69(4):88-96.
CrossRef Google scholar
[175]
SuarezB, SoleC, MarquezM, et al. Circulating MicroRNAs as cancer biomarkers in liquid biopsies. Adv Exp Med Biol. 2022;1385:23-73.
CrossRef Google scholar
[176]
WangN, ZhangJ, XiaoB, Sun X, XieR, ChenA. Recent advances in the rapid detection of microRNA with lateral flow assays. Biosens Bioelectron. 2022;211:114345.
CrossRef Google scholar
[177]
MoroG, FratteCD, NormannoN, Polo F, CintiS. Point-of-care testing for the detection of MicroRNAs: towards liquid biopsy on a chip. Angew Chem Int Ed. 2023;62(51):e202309135.
CrossRef Google scholar
[178]
ArdizzoneA, Calabrese G, CampoloM, et al. Role of miRNA-19a in cancer diagnosis and poor prognosis. Int J Mol Sci. 2021;22(9):4697.
CrossRef Google scholar
[179]
WangW, LouW, DingB, et al. A novel mRNA-miRNA-lncRNA competing endogenous RNA triple sub-network associated with prognosis of pancreatic cancer. Aging. 2019;11(9):2610-2627.
CrossRef Google scholar
[180]
ShangC, LiY, HeT, et al. The prognostic miR-532-5p-correlated ceRNA-mediated lipid droplet accumulation drives nodal metastasis of cervical cancer. J Adv Res. 2022;37:169-184.
CrossRef Google scholar
[181]
BaoJ, LiJ, LinH, et al. Deciphering a novel necroptosis-related miRNA signature for predicting the prognosis of clear cell renal carcinoma. Anal Cell Pathol. 2022;2022:2721005.
CrossRef Google scholar
[182]
MazumderS, DattaS, RayJG, Chaudhuri K, ChatterjeeR. Liquid biopsy: miRNA as a potential biomarker in oral cancer. Cancer Epidemiology. 2019;58:137-145.
CrossRef Google scholar
[183]
PanC, LuoJ, ZhangJ. Computational identification of RNA-Seq based miRNA-mediated prognostic modules in cancer. IEEE J Biomed Health Inform. 2020;24(2):626-633.
CrossRef Google scholar
[184]
Yerukala SathipatiS, Tsai MJ, ShuklaSK, HoSY. Artificial intelligence-driven pan-cancer analysis reveals miRNA signatures for cancer stage prediction. Human Genet Genomics Adv. 2023;4(3):100190.
CrossRef Google scholar
[185]
BertoliG, CavaC, CastiglioniI. MicroRNAs: new biomarkers for diagnosis, prognosis, therapy prediction and therapeutic tools for breast cancer. Theranostics. 2015;5(10):1122-1143.
CrossRef Google scholar
[186]
SinghS, SainiH, SharmaA, Gupta S, HuddarVG, TripathiR. Breast cancer: miRNAs monitoring chemoresistance and systemic therapy. Front Oncol. 2023;13:1155254.
CrossRef Google scholar
[187]
GrendaA, Krawczyk P. New dancing couple: PD-L1 and MicroRNA. Scand J Immunol. 2017;86(3):130-134.
CrossRef Google scholar
[188]
SeijoLM, PeledN, AjonaD, et al. Biomarkers in lung cancer screening: achievements, promises, and challenges. J Thorac Oncol. 2019;14(3):343-357.
CrossRef Google scholar
[189]
SestiniS, BoeriM, MarchianoA, et al. Circulating microRNA signature as liquid-biopsy to monitor lung cancer in low-dose computed tomography screening. Oncotarget. 2015;6(32):32868-32877.
CrossRef Google scholar
[190]
KimHS, NaMJ, SonKH, et al. ADAR1-dependent miR-3144-3p editing simultaneously induces MSI2 expression and suppresses SLC38A4 expression in liver cancer. Exp Mol Med. 2023;55(1):95-107.
CrossRef Google scholar
[191]
LiaoY, JungSH, KimT. A-to-I RNA editing as a tuner of noncoding RNAs in cancer. Cancer Lett. 2020;494:88-93.
CrossRef Google scholar
[192]
JayasreePJ, DuttaS, KaremoreP, Khandelia P. Crosstalk between m6A RNA methylation and miRNA biogenesis in cancer: an unholy nexus. Mol Biotechnol. 2023. In press.
CrossRef Google scholar
[193]
KimT, CroceCM. MicroRNA: trends in clinical trials of cancer diagnosis and therapy strategies. Exp Mol Med. 2023;55(7):1314-1321.
CrossRef Google scholar
[194]
ZylaJ, Dziadziuszko R, MarczykM, et al. miR-122 and miR-21 are stable components of miRNA signatures of early lung cancer after validation in three independent cohorts. J Mol Diagn. 2024;26(1):37-48.
CrossRef Google scholar
[195]
SoJBY, KapoorR, ZhuF, et al. Development and validation of a serum microRNA biomarker panel for detecting gastric cancer in a high-risk population. Gut. 2021;70(5):829-837.
CrossRef Google scholar
[196]
FredsøeJ, GludE, BoesenL, et al. Danish prostate cancer consortium study 1 (DPCC-1) protocol: multicentre prospective validation of the urine-based three-microRNA biomarker model uCaP. BMJ Open. 2023;13(11):e077020.
CrossRef Google scholar
[197]
SøreideK, WatsonMM, LeaD, et al. Assessment of clinically related outcomes and biomarker analysis for translational integration in colorectal cancer (ACROBATICC): study protocol for a population-based, consecutive cohort of surgically treated colorectal cancers and resected colorectal liver metastasis. J Transl Med. 2016;14(1):192.
CrossRef Google scholar
[198]
TeufelM, SeidelH, KöchertK, et al. Biomarkers associated with response to regorafenib in patients with hepatocellular carcinoma. Gastroenterology. 2019;156(6):1731-1741.
CrossRef Google scholar
[199]
Duroux-RichardI, GagezAL, AlaterreE, et al. miRNA profile at diagnosis predicts treatment outcome in patients with b-chronic lymphocytic leukemia: a FILO study. Front Immunol. 2022;13:983771.
CrossRef Google scholar
[200]
MonsellatoI, Garibaldi E, CassinottiE, et al. Expression levels of circulating miRNAs as biomarkers during multimodal treatment of rectal cancer -TiMiSNAR-mirna: a substudy of the TiMiSNAR trial (NCT03962088). Trials. 2020;21(1):678.
CrossRef Google scholar
[201]
WiemerEAC, Wozniak A, BurgerH, et al. Identification of microRNA biomarkers for response of advanced soft tissue sarcomas to eribulin: translational results of the EORTC 62052 trial. Eur J Cancer. 2017;75:33-40.
CrossRef Google scholar
[202]
HedayatS, Cascione L, CunninghamD, et al. Circulating microRNA analysis in a prospective co-clinical trial identifies MIR652-3p as a response biomarker and driver of regorafenib resistance mechanisms in colorectal cancer. Clin Cancer Res. 2024;30(10):2140-2159.
CrossRef Google scholar
[203]
MollaeiH, Safaralizadeh R, RostamiZ. MicroRNA replacement therapy in cancer. J Cell Physiol. 2019;234(8):12369-12384.
CrossRef Google scholar
[204]
RupaimooleR, SlackFJ. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases. Nat Rev Drug Discovery. 2017;16(3):203-222.
CrossRef Google scholar
[205]
GasparelloJ, PapiC, ZurloM, et al. Cationic Calix[4]arene vectors to efficiently deliver AntimiRNA peptide nucleic acids (PNAs) and miRNA mimics. Pharmaceutics. 2023;15(8):2121.
CrossRef Google scholar
[206]
ManikkathJ, JishnuPV, WichPR, Manikkath A, RadhakrishnanR. Nanoparticulate strategies for the delivery of miRNA mimics and inhibitors in anticancer therapy and its potential utility in oral submucous fibrosis. Nanomedicine. 2022;17(3):181-195.
CrossRef Google scholar
[207]
OtoukeshB, AbbasiM, GorganiHL, et al. MicroRNAs signatures, bioinformatics analysis of miRNAs, miRNA mimics and antagonists, and miRNA therapeutics in osteosarcoma. Cancer Cell Int. 2020;20:254.
CrossRef Google scholar
[208]
RomanoG, KwongLN. Diagnostic and therapeutic applications of miRNA-based strategies to cancer immunotherapy. Cancer Metastasis Rev. 2018;37(1):45-53.
CrossRef Google scholar
[209]
IqbalMA, AroraS, PrakasamG, Calin GA, SyedMA. MicroRNA in lung cancer: role, mechanisms, pathways and therapeutic relevance. Mol Aspects Med. 2019;70:3-20.
CrossRef Google scholar
[210]
DienerC, KellerA, MeeseE. Emerging concepts of miRNA therapeutics: from cells to clinic. TIG. 2022;38(6):613-626.
CrossRef Google scholar
[211]
TangL, ChenHY, HaoNB, et al. microRNA inhibitors: natural and artificial sequestration of microRNA. Cancer Lett. 2017;407:139-147.
CrossRef Google scholar
[212]
KangS, ParkS, YoonS, Min H. Machine learning-based identification of endogenous cellular microRNA sponges against viral microRNAs. Methods. 2017;129:33-40.
CrossRef Google scholar
[213]
Abu-LabanM, HamalP, ArrizabalagaJH, et al. Combinatorial delivery of miRNA-nanoparticle conjugates in human adipose stem cells for amplified osteogenesis. Small. 2019;15(50):e1902864.
CrossRef Google scholar
[214]
LucasT, Schäfer F, MüllerP, EmingSA, HeckelA, DimmelerS. Light-inducible antimiR-92a as a therapeutic strategy to promote skin repair in healing-impaired diabetic mice. Nat Commun. 2017;8:15162.
CrossRef Google scholar
[215]
van ZandwijkN, Pavlakis N, KaoSC, et al. Safety and activity of microRNA-loaded minicells in patients with recurrent malignant pleural mesothelioma: a first-in-man, phase 1, open-label, dose-escalation study. Lancet Oncol. 2017;18(10):1386-1396.
CrossRef Google scholar
[216]
ReidG, KaoSC, PavlakisN, et al. Clinical development of TargomiRs, a miRNA mimic-based treatment for patients with recurrent thoracic cancer. Epigenomics. 2016;8(8):1079-1085.
CrossRef Google scholar
[217]
BegMS, Brenner AJ, SachdevJ, et al. Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors. Invest New Drugs. 2017;35(2):180-188.
CrossRef Google scholar
[218]
DaigeCL, Wiggins JF, PriddyL, Nelligan-DavisT, ZhaoJ, BrownD. Systemic delivery of a miR34a mimic as a potential therapeutic for liver cancer. Mol Cancer Ther. 2014;13(10):2352-2360.
CrossRef Google scholar
[219]
YanY, LiuXY, LuA, WangXY, JiangLX, Wang JC. Non-viral vectors for RNA delivery. J Control Release. 2022;342:241-279.
CrossRef Google scholar
[220]
WittenL, SlackFJ. miR-155 as a novel clinical target for hematological malignancies. Carcinogenesis. 2020;41(1):2-7.
CrossRef Google scholar
[221]
RomanoG, AcunzoM, Nana-SinkamP. microRNAs as novel therapeutics in cancer. Cancers. 2021;13(7):1526.
CrossRef Google scholar
[222]
BinzelDW, ShuY, LiH, et al. Specific delivery of MiRNA for high efficient inhibition of prostate cancer by RNA nanotechnology. Mol Ther. 2016;24(7):1267-1277.
CrossRef Google scholar
[223]
FengR, SangQ, ZhuY, et al. MiRNA-320 in the human follicular fluid is associated with embryo quality in vivo and affects mouse embryonic development in vitro. Sci Rep. 2015;5:8689.
CrossRef Google scholar
[224]
DasguptaI, Chatterjee A. Recent advances in miRNA delivery systems. Methods Protocols. 2021;4(1):10.
CrossRef Google scholar
[225]
FortunatoO, BoeriM, VerriC, Moro M, SozziG. Therapeutic use of microRNAs in lung cancer. BioMed Res Int. 2014;2014:756975.
CrossRef Google scholar
[226]
LeeSWL, Paoletti C, CampisiM, et al. MicroRNA delivery through nanoparticles. J Control Release. 2019;313:80-95.
CrossRef Google scholar
[227]
ZhangW, LiuM, LiuA, ZhaiG. Advances in functionalized mesoporous silica nanoparticles for tumor targeted drug delivery and theranostics. Curr Pharm Des. 2017;23(23):3367-3382.
CrossRef Google scholar
[228]
DahlmanJE, Kauffman KJ, XingY, et al. Barcoded nanoparticles for high throughput in vivo discovery of targeted therapeutics. Proc Nat Acad Sci. 2017;114(8):2060-2065.
CrossRef Google scholar
[229]
RuseskaI, ZimmerA. Cellular uptake and trafficking of peptide-based drug delivery systems for miRNA. Eur J Pharmaceut Biopharmaceut. 2023;191:189-204.
CrossRef Google scholar
[230]
AndersonCF, SinghA, StephensT, Hoang CD, SchneiderJP. Kinetically controlled polyelectrolyte complex assembly of microRNA-peptide nanoparticles toward treating mesothelioma. Adv Mater. 2024;36(24):e2314367.
CrossRef Google scholar
[231]
LiuL, YiH, HeH, PanH, CaiL, MaY. Tumor associated macrophage-targeted microRNA delivery with dual-responsive polypeptide nanovectors for anti-cancer therapy. Biomaterials. 2017;134:166-179.
CrossRef Google scholar
[232]
GaoS, TianH, GuoY, et al. miRNA oligonucleotide and sponge for miRNA-21 inhibition mediated by PEI-PLL in breast cancer therapy. Acta Biomater. 2015;25:184-193.
CrossRef Google scholar
[233]
IsaacR, ReisFCG, YingW, Olefsky JM. Exosomes as mediators of intercellular crosstalk in metabolism. Cell Metab. 2021;33(9):1744-1762.
CrossRef Google scholar
[234]
ReidG, Johnson TG, van ZandwijkN. Manipulating microRNAs for the treatment of malignant pleural mesothelioma: past, present and future. Front Oncol. 2020;10:105.
CrossRef Google scholar
[235]
ZhangL, LiaoY, TangL. MicroRNA-34 family: a potential tumor suppressor and therapeutic candidate in cancer. J Exp Clin Cancer Res. 2019;38(1):53.
CrossRef Google scholar
[236]
GuptaA, Andresen JL, MananRS, LangerR. Nucleic acid delivery for therapeutic applications. Adv Drug Deliv Rev. 2021;178:113834.
CrossRef Google scholar
[237]
ParodiA, Quattrocchi N, van de VenAL, et al. Synthetic nanoparticles functionalized with biomimetic leukocyte membranes possess cell-like functions. Nat Nanotechnol. 2013;8(1):61-68.
CrossRef Google scholar
[238]
DuJ, LaneLA, NieS. Stimuli-responsive nanoparticles for targeting the tumor microenvironment. J Control Release. 2015;219:205-214.
CrossRef Google scholar
[239]
ParodiA, CorboC, CeveniniA, et al. Enabling cytoplasmic delivery and organelle targeting by surface modification of nanocarriers. Nanomedicine. 2015;10(12):1923-1940.
CrossRef Google scholar
[240]
ZhangT, XueX, HeD, HsiehJT. A prostate cancer-targeted polyarginine-disulfide linked PEI nanocarrier for delivery of microRNA. Cancer Lett. 2015;365(2):156-165.
CrossRef Google scholar
[241]
van BeijnumJR, Giovannetti E, PoelD, Nowak-SliwinskaP, Griffioen AW. miRNAs: micro-managers of anticancer combination therapies. Angiogenesis. 2017;20(2):269-285.
CrossRef Google scholar
[242]
CurtinNJ. DNA repair dysregulation from cancer driver to therapeutic target. Nat Rev Cancer. 2012;12(12):801-817.
CrossRef Google scholar
[243]
SmolleMA, CalinHN, PichlerM, Calin GA. Noncoding RNAs and immune checkpoints-clinical implications as cancer therapeutics. FEBS J. 2017;284(13):1952-1966.
CrossRef Google scholar
[244]
CoenenM, HinzeAV, MengelM, et al. Immune-and miRNA-response to recombinant interferon beta-1a: a biomarker evaluation study to guide the development of novel type I interferon-based therapies. BMC Pharmacol Toxicol. 2015;16:25.
CrossRef Google scholar
[245]
JiY, HockerJD, GattinoniL. Enhancing adoptive T cell immunotherapy with microRNA therapeutics. Sem Immunol. 2016;28(1):45-53.
CrossRef Google scholar
[246]
ZhangT, ZhangZ, LiF, et al. miR-143 regulates memory T cell differentiation by reprogramming T cell metabolism. J Immunol. 2018;201(7):2165-2175.
CrossRef Google scholar
[247]
OhnoM, OhkuriT, KosakaA, et al. Expression of miR-17-92 enhances anti-tumor activity of T-cells transduced with the anti-EGFRvIII chimeric antigen receptor in mice bearing human GBM xenografts. J Immunother Cancer. 2013;1:21.
CrossRef Google scholar
[248]
WangLQ, KumarS, CalinGA, Li Z, ChimCS. Frequent methylation of the tumour suppressor miR-1258 targeting PDL1: implication in multiple myeloma-specific cytotoxicity and prognostification. Br J Haematol. 2020;190(2):249-261.
CrossRef Google scholar
[249]
Pérez-HerreroE, Fernández-Medarde A. Advanced targeted therapies in cancer: drug nanocarriers, the future of chemotherapy. Eur J Pharmaceut Biopharmaceut. 2015;93:52-79.
CrossRef Google scholar
[250]
SiW, ShenJ, ZhengH, Fan W. The role and mechanisms of action of microRNAs in cancer drug resistance. Clin Epigenetics. 2019;11(1):25.
CrossRef Google scholar
[251]
SantosP, Almeida F. Role of exosomal miRNAs and the tumor microenvironment in drug resistance. Cells. 2020;9(6):1450.
CrossRef Google scholar
[252]
Peixoto da SilvaS, Caires HR, BergantimR, GuimarãesJE, Vasconcelos MH. miRNAs mediated drug resistance in hematological malignancies. Sem Cancer Biol. 2022;83:283-302.
CrossRef Google scholar
[253]
LinG, XuK. Advances in tumor chemo-resistance regulated by MicroRNA. Zhongguo Fei Ai Za Zhi. 2014;17(10):741-749.
[254]
GiovannettiE, Erozenci A, SmitJ, DanesiR, PetersGJ. Molecular mechanisms underlying the role of microRNAs (miRNAs) in anticancer drug resistance and implications for clinical practice. Crit Rev Oncol Hematol. 2012;81(2):103-122.
CrossRef Google scholar
[255]
GaoM, MiaoL, LiuM, et al. miR-145 sensitizes breast cancer to doxorubicin by targeting multidrug resistance-associated protein-1. Oncotarget. 2016;7(37):59714-59726.
CrossRef Google scholar
[256]
YangH, LiuY, ChenL, et al. MiRNA-based therapies for lung cancer: opportunities and challenges? Biomolecules. 2023;13(6):877.
CrossRef Google scholar
[257]
BachDH, HongJY, ParkHJ, Lee SK. The role of exosomes and miRNAs in drug-resistance of cancer cells. Int J Cancer. 2017;141(2):220-230.
CrossRef Google scholar
[258]
WangX, ZhouY, DingK. Roles of exosomes in cancer chemotherapy resistance, progression, metastasis and immunity, and their clinical applications (Review). Int J Oncol. 2021;59(1):44.
CrossRef Google scholar
[259]
JanjiB, Berchem G, ChouaibS. Targeting autophagy in the tumor microenvironment: new challenges and opportunities for regulating tumor immunity. Front Immunol. 2018;9:887.
CrossRef Google scholar
[260]
NallasamyP, Nimmakayala RK, ParteS, AreAC, BatraSK, PonnusamyMP. Tumor microenvironment enriches the stemness features: the architectural event of therapy resistance and metastasis. Mol Cancer. 2022;21(1):225.
CrossRef Google scholar
[261]
CuiTX, Kryczek I, ZhaoL, et al. Myeloid-derived suppressor cells enhance stemness of cancer cells by inducing microRNA101 and suppressing the corepressor CtBP2. Immunity. 2013;39(3):611-621.
CrossRef Google scholar
[262]
Abu SamaanTM, SamecM, LiskovaA, Kubatka P, BüsselbergD. Paclitaxel’s mechanistic and clinical effects on breast cancer. Biomolecules. 2019;9(12):789.
CrossRef Google scholar
[263]
YangQ, ZhaoS, ShiZ, et al. Chemotherapy-elicited exosomal miR-378a-3p and miR-378d promote breast cancer stemness and chemoresistance via the activation of EZH2/STAT3 signaling. J Exp Clin Cancer Res. 2021;40(1):120.
CrossRef Google scholar
[264]
TufailM, HuJJ, LiangJ, et al. Hallmarks of cancer resistance. iScience. 2024;27(6):109979.
CrossRef Google scholar
[265]
CarielloM, Squilla A, PiacenteM, VenutoloG, FasanoA. Drug resistance: the role of exosomal miRNA in the microenvironment of hematopoietic tumors. Molecules. 2022;28(1):116.
CrossRef Google scholar
[266]
WuD, HuangC, GuanK. Mechanistic and therapeutic perspectives of miRNA-PTEN signaling axis in cancer therapy resistance. Biochem Pharmacol. 2024;226:116406.
CrossRef Google scholar
[267]
ZhaoY, HanM, XiongY, et al. A miRNA-200c/cathepsin L feedback loop determines paclitaxel resistance in human lung cancer A549 cells in vitro through regulating epithelial-mesenchymal transition. Acta Pharmacol Sin. 2018;39(6):1034-1047.
CrossRef Google scholar
[268]
WangY, WangH, DingY, et al. N-peptide of vMIP-II reverses paclitaxel-resistance by regulating miRNA-335 in breast cancer. Int J Oncol. 2017;51(3):918-930.
CrossRef Google scholar
[269]
ShiC, RenS, ZhaoX, Li Q. lncRNA MALAT1 regulates the resistance of breast cancer cells to paclitaxel via the miR-497-5p/SHOC2 axis. Pharmacogenomics. 2022;23(18):973-985.
CrossRef Google scholar
[270]
ShiT, LiR, DuanP, et al. TRPM2-AS promotes paclitaxel resistance in prostate cancer by regulating FOXK1 via sponging miR-497-5p. Drug Dev Res. 2022;83(4):967-978.
CrossRef Google scholar
[271]
MiyamotoM, SawadaK, NakamuraK, et al. Paclitaxel exposure downregulates miR-522 expression and its downregulation induces paclitaxel resistance in ovarian cancer cells. Sci Rep. 2020;10(1):16755.
CrossRef Google scholar
[272]
YuAM, JianC, YuAH, TuMJ. RNA therapy: are we using the right molecules? Pharmacol Ther. 2019;196:91-104.
CrossRef Google scholar
[273]
Montero-CondeC, Graña-Castro O, Martín-SerranoG, et al. Hsa-miR-139-5p is a prognostic thyroid cancer marker involved in HNRNPF-mediated alternative splicing. Int J Cancer. 2020;146(2):521-530.
CrossRef Google scholar
[274]
YuAM, TianY, TuMJ, HoPY, JilekJL. MicroRNA pharmacoepigenetics: posttranscriptional regulation mechanisms behind variable drug disposition and strategy to develop more effective therapy. Drug Metab Dispos. 2016;44(3):308-319.
CrossRef Google scholar
[275]
LiangD, Minikes AM, JiangX. Ferroptosis at the intersection of lipid metabolism and cellular signaling. Mol Cell. 2022;82(12):2215-2227.
CrossRef Google scholar
[276]
WangY, WuX, RenZ, et al. Overcoming cancer chemotherapy resistance by the induction of ferroptosis. Drug Resist Updates. 2023;66:100916.
CrossRef Google scholar
[277]
ZhangC, LiuX, JinS, ChenY, GuoR. Ferroptosis in cancer therapy: a novel approach to reversing drug resistance. Mol Cancer. 2022;21(1):47.
CrossRef Google scholar
[278]
ZhangH, DengT, LiuR, et al. CAF secreted miR-522 suppresses ferroptosis and promotes acquired chemo-resistance in gastric cancer. Mol Cancer. 2020;19(1):43.
CrossRef Google scholar
[279]
MaSC, ZhangJQ, YanTH, et al. Novel strategies to reverse chemoresistance in colorectal cancer. Cancer Med. 2023;12(10):11073-11096.
CrossRef Google scholar
[280]
SharmaP, SinghS. Combinatorial effect of DCA and Let-7a on Triple-Negative MDA-MB-231 cells: a metabolic approach of treatment. Integr Cancer Ther. 2020;19:1534735420911437.
CrossRef Google scholar
[281]
PagoniM, CavaC, SiderisDC, et al. miRNA-based technologies in cancer therapy. J Pers Med. 2023;13(11):1586.
CrossRef Google scholar
[282]
GanH, LinL, HuN, et al. Aspirin ameliorates lung cancer by targeting the miR-98/WNT1 axis. Thorac Cancer. 2019;10(4):744-750.
CrossRef Google scholar
[283]
KarlicH, ThalerR, GernerC, et al. Inhibition of the mevalonate pathway affects epigenetic regulation in cancer cells. Cancer Genetics. 2015;208(5):241-252.
CrossRef Google scholar
[284]
BazavarM, FazliJ, ValizadehA, et al. miR-192 enhances sensitivity of methotrexate drug to MG-63 osteosarcoma cancer cells. Pathol Res Pract. 2020;216(11):153176.
CrossRef Google scholar
[285]
AnsariMA, Thiruvengadam M, FarooquiZ, et al. Nanotechnology, in silico and endocrine-based strategy for delivering paclitaxel and miRNA: prospects for the therapeutic management of breast cancer. Sem Cancer Biol. 2021;69:109-128.
CrossRef Google scholar
[286]
ChenQX, WangWP, ZengS, Urayama S, YuAM. A general approach to high-yield biosynthesis of chimeric RNAs bearing various types of functional small RNAs for broad applications. Nucleic Acids Res. 2015;43(7):3857-3869.
CrossRef Google scholar
[287]
WangWP, HoPY, ChenQX, et al. Bioengineering novel chimeric microRNA-34a for prodrug cancer therapy: high-yield expression and purification, and structural and functional characterization. J Pharmacol Exp Ther. 2015;354(2):131-141.
CrossRef Google scholar
[288]
HoPY, YuAM. Bioengineering of noncoding RNAs for research agents and therapeutics. WIREs RNA. 2016;7(2):186-197.
CrossRef Google scholar
[289]
HoPY, DuanZ, BatraN, et al. Bioengineered noncoding RNAs selectively change cellular miRNome profiles for cancer therapy. J Pharmacol Exp Ther. 2018;365(3):494-506.
CrossRef Google scholar
[290]
WangH, Ellipilli S, LeeWJ, et al. Multivalent rubber-like RNA nanoparticles for targeted co-delivery of paclitaxel and MiRNA to silence the drug efflux transporter and liver cancer drug resistance. J Control Release. 2021;330:173-184.
CrossRef Google scholar
[291]
JacquetK, Vidal-Cruchez O, RezzonicoR, et al. New technologies for improved relevance in miRNA research. TIG. 2021;37(12):1060-1063.
CrossRef Google scholar
[292]
SasakiHM, Tadakuma H, TomariY. Single-molecule analysis for RISC assembly and target cleavage. Methods Mol Biol. 2018;1680:145-164.
CrossRef Google scholar
[293]
AhmedKT, SunJ, ChengS, Yong J, ZhangW. Multi-omics data integration by generative adversarial network. Bioinformatics. 2021;38(1):179-186.
CrossRef Google scholar
[294]
KishikawaM, InoueJ, HamamotoH, Kobayashi K, AsakageT, InazawaJ. Augmentation of lenvatinib efficacy by topical treatment of miR-634 ointment in anaplastic thyroid cancer. Biochem Biophys Rep. 2021;26:101009.
CrossRef Google scholar

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