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image of Targeting Non-coding RNAs in Neurodegeneration: Advances in Therapeutic RNA Modalities and Next-Gen Delivery Technologies

Abstract

Non-coding RNA (ncRNA)-based therapies represent an emerging and transformative approach in the treatment of neurodegenerative diseases (NDs), such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS)/Motor Neuron Disease (MND). This review explored the potential for targeting microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and exosomal RNAs, reinforced by promising results from clinical trials demonstrating their capacity to modulate disease pathways. The incorporation of cutting-edge computational methodologies, including RNA structure prediction and gene regulatory network analysis, has been at the forefront in enhancing the efficacy of ncRNA-based treatments. Moreover, chemical methods have improved RNA molecules' stability, accuracy, and directed delivery, enhancing their therapeutic effects. Moreover, cutting-edge RNA editing technologies like Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 13 (CRISPR/Cas13) are advancing our ability to directly manipulate ncRNA expression, offering a powerful avenue for addressing the molecular origins of neurodegeneration. Despite these advances, challenges persist, particularly in ensuring the specificity, delivery efficiency, and long-term efficacy of these treatments. Nanotechnology provides innovative solutions to these obstacles, facilitating more efficient and precise RNA delivery, especially to neuronal tissue. In conclusion, ncRNA-based therapies, while still in nascent stages, represent a hopeful frontier in the fight against NDs. With ongoing research and technological advancements, these therapies could not only halt disease progression but also redefine the future of ND treatment, offering new avenues for patients’ care and clinical success.

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2026-01-21
2026-01-29
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References

  1. Gupta A. Sharma B. Neurodegenerative Diseases (ND): An Introduction.In: Synaptic Plasticity in Neurodegenerative Disorders CRC Press 2025 3 20 10.1201/9781003464648
    [Google Scholar]
  2. Alqahtani T. Deore S.L. Kide A.A. Mitochondrial dysfunction and oxidative stress in Alzheimer’s disease, and Parkinson’s disease, Huntington’s disease and Amyotrophic Lateral Sclerosis -An updated review. Mitochondrion 2023 71 83 92 10.1016/j.mito.2023.05.007 37269968
    [Google Scholar]
  3. Anthony K. RNA-based therapeutics for neurological diseases. RNA Biol. 2022 19 1 176 190 10.1080/15476286.2021.2021650 35067193
    [Google Scholar]
  4. Zhu Y. Zhu L. Wang X. Jin H. RNA-based therapeutics: an overview and prospectus. Cell Death Dis. 2022 13 7 644 10.1038/s41419‑022‑05075‑2 35871216
    [Google Scholar]
  5. Toomer G. Gan H. Sztuba-Solinska J. Long non-coding RNAs diversity in form and function: from microbes to humans. In: Chemical Biology of Long Noncoding RNAs. Cham Springer 2020 1 57 10.1007/978‑3‑030‑44743‑4_1
    [Google Scholar]
  6. Khorkova O. Stahl J. Joji A. Volmar C.H. Wahlestedt C. Amplifying gene expression with RNA-targeted therapeutics. Nat. Rev. Drug Discov. 2023 22 7 539 561 10.1038/s41573‑023‑00704‑7 37253858
    [Google Scholar]
  7. Zhuang J. Liu Q. Wu D. Tie L. Current strategies and progress for targeting the “undruggable” transcription factors. Acta Pharmacol. Sin. 2022 43 10 2474 2481 10.1038/s41401‑021‑00852‑9 35132191
    [Google Scholar]
  8. Tani H. Recent advances and prospects in RNA drug development. Int. J. Mol. Sci. 2024 25 22 12284 10.3390/ijms252212284 39596348
    [Google Scholar]
  9. Bhatti G.K. Khullar N. Sidhu I.S. Emerging role of non‐coding RNA in health and disease. Metab. Brain Dis. 2021 36 6 1119 1134 10.1007/s11011‑021‑00739‑y 33881724
    [Google Scholar]
  10. George T.P. Subramanian S. Supriya M.H. A brief review of noncoding RNA. Egypt. J. Med. Hum. Genet. 2024 25 1 98 10.1186/s43042‑024‑00553‑y
    [Google Scholar]
  11. Chao H.M. Wang T.W. Chern E. Hsu S.H. Regulatory RNAs, microRNA, long-non coding RNA and circular RNA roles in colorectal cancer stem cells. World J. Gastrointest. Oncol. 2022 14 4 748 764 10.4251/wjgo.v14.i4.748 35582099
    [Google Scholar]
  12. Toden S. Zumwalt T.J. Goel A. Non-coding RNAs and potential therapeutic targeting in cancer. Biochim. Biophys. Acta Rev. Cancer 2021 1875 1 188491 10.1016/j.bbcan.2020.188491 33316377
    [Google Scholar]
  13. Entezari M. Taheriazam A. Orouei S. LncRNA-miRNA axis in tumor progression and therapy response: An emphasis on molecular interactions and therapeutic interventions. Biomed. Pharmacother. 2022 154 113609 10.1016/j.biopha.2022.113609 36037786
    [Google Scholar]
  14. Chen B. Dragomir M.P. Yang C. Li Q. Horst D. Calin G.A. Targeting non-coding RNAs to overcome cancer therapy resistance. Signal Transduct. Target. Ther. 2022 7 1 121 10.1038/s41392‑022‑00975‑3 35418578
    [Google Scholar]
  15. Soreq L. Mohamed W. Computational analysis of biological data: Where are we? In: Computational modeling and simulation in biomedical research. Bentham Science Publishers 2024 14 39 10.2174/9789815165463124010005
    [Google Scholar]
  16. Childs-Disney J.L. Yang X. Gibaut Q.M.R. Tong Y. Batey R.T. Disney M.D. Targeting RNA structures with small molecules. Nat. Rev. Drug Discov. 2022 21 10 736 762 10.1038/s41573‑022‑00521‑4 35941229
    [Google Scholar]
  17. Zhou Y. Chen S.J. Advances in machine-learning approaches to RNA-targeted drug design. Artificial Intelligence Chemistry 2024 2 1 100053 10.1016/j.aichem.2024.100053 38434217
    [Google Scholar]
  18. Pan Y. Zhou X. Yang Z. Progress of oligonucleotide therapeutics target to rna: review on modification, conjugation, and delivery. Nucleic Acids Med Chem Chem Biol Drug Dev Clin Appl 2023 373 427 10.1002/9781119692799.ch11
    [Google Scholar]
  19. Gosselet F. Loiola R.A. Roig A. Rosell A. Culot M. Central nervous system delivery of molecules across the blood-brain barrier. Neurochem. Int. 2021 144 104952 10.1016/j.neuint.2020.104952 33400964
    [Google Scholar]
  20. Doherty T. Yao Z. Khleifat A.A. Artificial intelligence for dementia drug discovery and trials optimization. Alzheimers Dement. 2023 19 12 5922 5933 10.1002/alz.13428 37587767
    [Google Scholar]
  21. Li Y. Bhinge A. Inoue S. Garcia G. Editorial: Noncoding RNAs in neurodegenerative disorders: from current insights and future directions to translational modeling and therapeutic approaches. Front. Neurosci. 2024 18 1497673 10.3389/fnins.2024.1497673 39534022
    [Google Scholar]
  22. Kumar P. Intersections of heavy metal toxicity, protein misfolding, and neurodegenerative disorders in humans. Protein Misfolding in Neurodegenerative Diseases. In: Elsevier 2025 413 461 10.1016/B978‑0‑443‑18716‑2.00012‑0
    [Google Scholar]
  23. Misrani A. Tabassum S. Yang L. Mitochondrial dysfunction and oxidative stress in Alzheimer’s disease. Front. Aging Neurosci. 2021 13 617588 10.3389/fnagi.2021.617588 33679375
    [Google Scholar]
  24. Murshid M.N. Lubis A.F. Makpol S. Epigenetic changes and its intervention in age-related neurodegenerative diseases. Cell. Mol. Neurobiol. 2022 42 3 577 595 10.1007/s10571‑020‑00979‑z 33074454
    [Google Scholar]
  25. Poliseno L. Lanza M. Pandolfi P.P. Coding, or non-coding, that is the question. Cell Res. 2024 34 9 609 629 10.1038/s41422‑024‑00975‑8 39054345
    [Google Scholar]
  26. Patranabis S. Recent advances in the miRNA-mediated regulation of neuronal differentiation and death. Neuromolecular Med. 2024 26 1 52 10.1007/s12017‑024‑08820‑2 39648193
    [Google Scholar]
  27. Nemeth K. Bayraktar R. Ferracin M. Calin G.A. Non-coding RNAs in disease: from mechanisms to therapeutics. Nat. Rev. Genet. 2024 25 3 211 232 10.1038/s41576‑023‑00662‑1 37968332
    [Google Scholar]
  28. Ebrahimi R. Golestani A. The emerging role of noncoding RNAs in neuroinflammation: Implications in pathogenesis and therapeutic approaches. J. Cell. Physiol. 2022 237 2 1206 1224 10.1002/jcp.30624 34724212
    [Google Scholar]
  29. Xiong Jia-Rui Yan Zi-Yi Shi Meng-Qiong miR-146a regulates neuroinflammation and immune cell function in neurodegenerative diseases Curr Med Sci 2025 45 4 725 44 10.1007/s11596‑025‑00080‑w
    [Google Scholar]
  30. Rastegar-Moghaddam S.H. Ebrahimzadeh-Bideskan A. Shahba S. Malvandi A.M. Mohammadipour A. Roles of the miR-155 in neuroinflammation and neurological disorders: A potent biological and therapeutic target. Cell. Mol. Neurobiol. 2023 43 2 455 467 10.1007/s10571‑022‑01200‑z 35107690
    [Google Scholar]
  31. Tripathi S. Shree B. Mohapatra S. Swati, Basu A, Sharma V. The expanding regulatory mechanisms and cellular functions of long non-coding RNAs (lncRNAs) in neuroinflammation. Mol. Neurobiol. 2021 58 6 2916 2939 10.1007/s12035‑020‑02268‑8 33555549
    [Google Scholar]
  32. Deogharia M. Gurha P. The “guiding” principles of noncoding RNA function. Wiley Interdiscip. Rev. RNA 2022 13 4 e1704 10.1002/wrna.1704 34856642
    [Google Scholar]
  33. Mohammadi A.H. Seyedmoalemi S. Moghanlou M. MicroRNAs and synaptic plasticity: from their molecular roles to response to therapy. Mol. Neurobiol. 2022 59 8 5084 5102 10.1007/s12035‑022‑02907‑2 35666404
    [Google Scholar]
  34. Jiang H. Zhang Y. Yue J. Non-coding RNAs: The neuroinflammatory regulators in neurodegenerative diseases. Front. Neurol. 2022 13 929290 10.3389/fneur.2022.929290 36034298
    [Google Scholar]
  35. He C. Li Z. Yang M. Non-coding RNA in microglia activation and neuroinflammation in Alzheimer’s disease. J. Inflamm. Res. 2023 16 4165 4211 10.2147/JIR.S422114 37753266
    [Google Scholar]
  36. Ma Y.M. Zhao L. Mechanism and therapeutic prospect of miRNAs in neurodegenerative diseases. Behav. Neurol. 2023 2023 1 1 24 10.1155/2023/8537296 38058356
    [Google Scholar]
  37. Li S. Lei Z. Sun T. The role of microRNAs in neurodegenerative diseases: a review. Cell Biol. Toxicol. 2023 39 1 53 83 10.1007/s10565‑022‑09761‑x 36125599
    [Google Scholar]
  38. Moda F. Ciullini A. Dellarole I.L. Secondary protein aggregates in neurodegenerative diseases: almost the rule rather than the exception. Front. Biosci (Landmark Ed) 2023 28 10 255 10.31083/j.fbl2810255 37919089
    [Google Scholar]
  39. Mu C. Gao M. Xu W. Mechanisms of microRNA-132 in central neurodegenerative diseases: A comprehensive review. Biomed. Pharmacother. 2024 170 116029 10.1016/j.biopha.2023.116029 38128185
    [Google Scholar]
  40. Arora T. Prashar V. Singh R. Dysregulated miRNAs in progression and pathogenesis of Alzheimer’s disease. Mol. Neurobiol. 2022 59 10 6107 6124 10.1007/s12035‑022‑02950‑z 35867206
    [Google Scholar]
  41. Luo Y. Tang W. Xiang S. Feng J. Zu X. Non-coding RNAs in breast cancer: Implications for programmed cell death. Cancer Lett. 2022 550 215929 10.1016/j.canlet.2022.215929 36202173
    [Google Scholar]
  42. Abuelezz N.Z. Nasr F.E. AbdulKader MA, Bassiouny AR, Zaky A. AbdulKader MA, Bassiouny AR, Zaky A. MicroRNAs as potential orchestrators of Alzheimer’s disease-related pathologies: insights on current status and future possibilities. Front. Aging Neurosci. 2021 13 743573 10.3389/fnagi.2021.743573 34712129
    [Google Scholar]
  43. Chang C.P. Wu K.C. Lin C.Y. Chern Y. Emerging roles of dysregulated adenosine homeostasis in brain disorders with a specific focus on neurodegenerative diseases. J. Biomed. Sci. 2021 28 1 70 10.1186/s12929‑021‑00766‑y 34635103
    [Google Scholar]
  44. Mattick J.S. Amaral P.P. Carninci P. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat. Rev. Mol. Cell Biol. 2023 24 6 430 447 10.1038/s41580‑022‑00566‑8 36596869
    [Google Scholar]
  45. Bhattacharyya N. Pandey V. Bhattacharyya M. Dey A. Regulatory role of long non coding RNAs (lncRNAs) in neurological disorders: From novel biomarkers to promising therapeutic strategies. Asian J Pharm Sci 2021 16 5 533 550 10.1016/j.ajps.2021.02.006 34849161
    [Google Scholar]
  46. Zhou S. Yu X. Wang M. Long non-coding RNAs in pathogenesis of neurodegenerative diseases. Front. Cell Dev. Biol. 2021 9 719247 10.3389/fcell.2021.719247 34527672
    [Google Scholar]
  47. Statello L. Guo C.J. Chen L.L. Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat. Rev. Mol. Cell Biol. 2021 22 2 96 118 10.1038/s41580‑020‑00315‑9 33353982
    [Google Scholar]
  48. Lauretti E. Dabrowski K. Praticò D. The neurobiology of non-coding RNAs and Alzheimer’s disease pathogenesis: Pathways, mechanisms and translational opportunities. Ageing Res. Rev. 2021 71 101425 10.1016/j.arr.2021.101425 34384901
    [Google Scholar]
  49. Ao Y.Q. Gao J. Jiang J.H. Wang H.K. Wang S. Ding J.Y. Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village. Mol. Ther. 2023 31 12 3389 3413 10.1016/j.ymthe.2023.09.015 37740493
    [Google Scholar]
  50. Qu Y. Tan H.Y. Chan Y.T. Jiang H. Wang N. Wang D. The functional role of long noncoding RNA in resistance to anticancer treatment. Ther. Adv. Med. Oncol. 2020 12 1758835920927850 10.1177/1758835920927850 32536982
    [Google Scholar]
  51. Zhu L. Guo M. Li K. Guo C. He K. The association and prognostic implications of long non-coding RNAs in major psychiatric disorders, Alzheimer’s diseases and Parkinson’s diseases: A systematic review. Int. J. Mol. Sci. 2024 25 20 10995 10.3390/ijms252010995 39456775
    [Google Scholar]
  52. Khani-Habibabadi F. Zare L. Sahraian M.A. Javan M. Behmanesh M. Hotair and Malat1 long noncoding RNAs regulate BDNF expression and oligodendrocyte precursor cell differentiation. Mol. Neurobiol. 2022 59 7 4209 4222 10.1007/s12035‑022‑02844‑0 35499794
    [Google Scholar]
  53. Dempsey J.L. Cui J.Y. Long non-coding RNAs: a novel paradigm for toxicology. Toxicol. Sci. 2017 155 1 3 21 10.1093/toxsci/kfw203 27864543
    [Google Scholar]
  54. García-Fonseca Á. Martin-Jimenez C. Barreto G.E. Pachón A.F.A. González J. The emerging role of long non-coding RNAs and microRNAs in neurodegenerative diseases: a perspective of machine learning. Biomolecules 2021 11 8 1132 10.3390/biom11081132 34439798
    [Google Scholar]
  55. He L. Chen Z. Wang J. Feng H. Expression relationship and significance of NEAT1 and miR-27a-3p in serum and cerebrospinal fluid of patients with Alzheimer’s disease. BMC Neurol. 2022 22 1 203 10.1186/s12883‑022‑02728‑9 35659599
    [Google Scholar]
  56. Akbar A. Haider R. Agnello L. CRISPR in Neurodegenerative diseases treatment: An alternative approach to current therapies. Genes 2025 16 8 850 10.3390/genes16080850 40869897
    [Google Scholar]
  57. Bereczki Z. Benczik B. Balogh O.M. Mitigating off‐target effects of small RNAs: conventional approaches, network theory and artificial intelligence. Br. J. Pharmacol. 2025 182 2 340 379 10.1111/bph.17302 39293936
    [Google Scholar]
  58. Seyhan A.A. Trials and Tribulations of MicroRNA Therapeutics. Int. J. Mol. Sci. 2024 25 3 1469 10.3390/ijms25031469 38338746
    [Google Scholar]
  59. Ahmad A. Ashraf S. Majeed H.N. Bioinformatic tools in CRISPR/Cas platform. In: The CRISPR/Cas Tool Kit for Genome Editing. Springer 2022 53 111 10.1007/978‑981‑16‑6305‑5_3
    [Google Scholar]
  60. Shi Y. Zhen X. Zhang Y. Chemically modified platforms for better RNA therapeutics. Chem. Rev. 2024 124 10 6690 6692 10.1021/acs.chemrev.4c00191 38688000
    [Google Scholar]
  61. Tasset A. Bellamkonda A. Wang W. Overcoming barriers in non-viral gene delivery for neurological applications. Nanoscale 2022 14 10 3698 3719 10.1039/D1NR06939J 35195645
    [Google Scholar]
  62. Nance E. Pun S.H. Saigal R. Sellers D.L. Drug delivery to the central nervous system. Nat. Rev. Mater. 2021 7 4 314 331 10.1038/s41578‑021‑00394‑w 38464996
    [Google Scholar]
  63. Waqas M.Y. Javid M.A. Nazir M.M. Extracellular vesicles and exosome: insight from physiological regulatory perspectives. J. Physiol. Biochem. 2022 78 3 573 580 10.1007/s13105‑022‑00877‑6 35102530
    [Google Scholar]
  64. Han W. Zhang H. Feng L. The emerging role of exosomes in communication between the periphery and the central nervous system. MedComm 2023 4 6 e410 10.1002/mco2.410 37916034
    [Google Scholar]
  65. Polanco J.C. Götz J. Exosomal and vesicle‐free tau seeds-propagation and convergence in endolysosomal permeabilization. FEBS J. 2022 289 22 6891 6907 10.1111/febs.16055 34092031
    [Google Scholar]
  66. Li C. Ni Y.Q. Xu H. Roles and mechanisms of exosomal non-coding RNAs in human health and diseases. Signal Transduct. Target. Ther. 2021 6 1 383 10.1038/s41392‑021‑00779‑x 34753929
    [Google Scholar]
  67. Guo M. Hao Y. Feng Y. Microglial exosomes in neurodegenerative disease. Front. Mol. Neurosci. 2021 14 630808 10.3389/fnmol.2021.630808 34045943
    [Google Scholar]
  68. Liu Z. Cheng L. Cao W. Present and future use of exosomes containing proteins and RNAs in neurodegenerative diseases for synaptic function regulation: A comprehensive review. Int. J. Biol. Macromol. 2024 280 Pt 3 135826 10.1016/j.ijbiomac.2024.135826 39322147
    [Google Scholar]
  69. Weng S. Lai Q.L. Wang J. The role of exosomes as mediators of neuroinflammation in the pathogenesis and treatment of Alzheimer’s disease. Front. Aging Neurosci. 2022 14 899944 10.3389/fnagi.2022.899944 35837481
    [Google Scholar]
  70. Sharma M. Pal P. Gupta S.K. Deciphering the role of miRNAs in Alzheimer’s disease: Predictive targeting and pathway modulation – A systematic review. Ageing Res. Rev. 2024 101 102483 10.1016/j.arr.2024.102483 39236856
    [Google Scholar]
  71. Thangavelu L. Moglad E. Afzal M. Non-coding RNAs in Parkinson’s disease: Regulating SNCA and alpha-synuclein aggregation. Pathol. Res. Pract. 2024 261 155511 10.1016/j.prp.2024.155511 39094523
    [Google Scholar]
  72. Si X.L. Fang Y.J. Li L.F. From inflammasome to Parkinson’s disease: Does the NLRP3 inflammasome facilitate exosome secretion and exosomal alpha-synuclein transmission in Parkinson’s disease? Exp. Neurol. 2021 336 113525 10.1016/j.expneurol.2020.113525 33161049
    [Google Scholar]
  73. Oyarce K. Cepeda M.Y. Lagos R. Neuroprotective and neurotoxic effects of glial-derived exosomes. Front. Cell. Neurosci. 2022 16 920686 10.3389/fncel.2022.920686 35813501
    [Google Scholar]
  74. Liu J. Long Y. Xu P. Guo H. Cui G. Pathogenesis of miR-155 on nonmodifiable and modifiable risk factors in Alzheimer’s disease. Alzheimers Res. Ther. 2023 15 1 122 10.1186/s13195‑023‑01264‑z 37452431
    [Google Scholar]
  75. Fan C. Li Y. Lan T. Wang W. Long Y. Yu S.Y. Microglia secrete miR-146a-5p-containing exosomes to regulate neurogenesis in depression. Mol. Ther. 2022 30 3 1300 1314 10.1016/j.ymthe.2021.11.006 34768001
    [Google Scholar]
  76. Zhu Z. Huang X. Du M. Recent advances in the role of miRNAs in post-traumatic stress disorder and traumatic brain injury. Mol. Psychiatry 2023 28 7 2630 2644 10.1038/s41380‑023‑02126‑8 37340171
    [Google Scholar]
  77. Banerjee S. Sharma V. Das Mukhopadhyay C. Exploring emerging concepts of exosomes for the diagnosis, prognosis, and therapeutics of brain cancers. Extracell Vesicle 2024 3 100038 10.1016/j.vesic.2024.100038
    [Google Scholar]
  78. Chunhui G. Yanqiu Y. Jibing C. Ning L. Fujun L. Exosomes and non-coding RNAs: bridging the gap in Alzheimer’s pathogenesis and therapeutics. Metab. Brain Dis. 2025 40 1 84 10.1007/s11011‑024‑01520‑7 39754674
    [Google Scholar]
  79. Feng J. Zhang Y. Zhu Z. Gu C. Waqas A. Chen L. Emerging exosomes and exosomal MiRNAs in spinal cord injury. Front. Cell Dev. Biol. 2021 9 703989 10.3389/fcell.2021.703989 34307384
    [Google Scholar]
  80. Irwin A.B. Bahabry R. Lubin F.D. A putative role for lncRNAs in epigenetic regulation of memory. Neurochem. Int. 2021 150 105184 10.1016/j.neuint.2021.105184 34530054
    [Google Scholar]
  81. Narang P. Shah M. Beljanski V. Exosomal RNAs in diagnosis and therapies. Noncoding RNA Res. 2022 7 1 7 15 10.1016/j.ncrna.2022.01.001 35087990
    [Google Scholar]
  82. Pandit R. Chen L. Götz J. The blood-brain barrier: Physiology and strategies for drug delivery. Adv. Drug Deliv. Rev. 2020 165-166 1 14 10.1016/j.addr.2019.11.009 31790711
    [Google Scholar]
  83. Shirmast P. Shahri M.A. Brent A. Idris A. McMillan N.A.J. Delivering therapeutic RNA into the brain using extracellular vesicles. Mol. Ther. Nucleic Acids 2024 35 4 102373 10.1016/j.omtn.2024.102373 39618821
    [Google Scholar]
  84. Hamdy N.M. Basalious E.B. El-Sisi M.G. Rana A.Y. Sultan A.S. Toward applicability of exosomal-ncRNA precision vs. nanoparticles to the brain. In: nanocarriers in neurodegenerative disorders 294 308 10.1201/9781003383376‑20
    [Google Scholar]
  85. Naimi N. Seyedmirzaei H. Hassannejad Z. Soltani Khaboushan A. Advanced nanoparticle strategies for optimizing RNA therapeutic delivery in neurodegenerative disorders. Biomed. Pharmacother. 2024 175 116691 10.1016/j.biopha.2024.116691 38713941
    [Google Scholar]
  86. Teodori L. Omer M. Kjems J. RNA nanostructures for targeted drug delivery and imaging. RNA Biol. 2024 21 1 391 409 10.1080/15476286.2024.2328440 38555519
    [Google Scholar]
  87. Wu D. Chen Q. Chen X. Han F. Chen Z. Wang Y. The blood–brain barrier: Structure, regulation and drug delivery. Signal Transduct. Target. Ther. 2023 8 1 217 10.1038/s41392‑023‑01481‑w 37231000
    [Google Scholar]
  88. Paunovska K. Loughrey D. Dahlman J.E. Drug delivery systems for RNA therapeutics. Nat. Rev. Genet. 2022 23 5 265 280 10.1038/s41576‑021‑00439‑4 34983972
    [Google Scholar]
  89. Eygeris Y. Gupta M. Kim J. Sahay G. Chemistry of lipid nanoparticles for RNA delivery. Acc. Chem. Res. 2022 55 1 2 12 10.1021/acs.accounts.1c00544 34850635
    [Google Scholar]
  90. Almohaimeed H.M. Assiri R. Althubaiti E.H. Non-coding RNAs as key players in the neurodegenerative diseases: Multi-platform strategies and approaches for exploring the Genome’s dark matter. J. Chem. Neuroanat. 2023 129 102236 10.1016/j.jchemneu.2023.102236 36709005
    [Google Scholar]
  91. van den Berg A.I.S. Yun C.O. Schiffelers R.M. Hennink W.E. Polymeric delivery systems for nucleic acid therapeutics: Approaching the clinic. J. Control. Release 2021 331 121 141 10.1016/j.jconrel.2021.01.014 33453339
    [Google Scholar]
  92. Piotrowski-Daspit A.S. Kauffman A.C. Bracaglia L.G. Saltzman W.M. Polymeric vehicles for nucleic acid delivery. Adv. Drug Deliv. Rev. 2020 156 119 132 10.1016/j.addr.2020.06.014 32585159
    [Google Scholar]
  93. Cano A. Sánchez-López E. Ettcheto M. Current advances in the development of novel polymeric nanoparticles for the treatment of neurodegenerative diseases. Nanomedicine (Lond.) 2020 15 12 1239 1261 10.2217/nnm‑2019‑0443 32370600
    [Google Scholar]
  94. Xiao X. Li H. Zhao L. Zhang Y. Liu Z. Oligonucleotide aptamers: Recent advances in their screening, molecular conformation and therapeutic applications. Biomed. Pharmacother. 2021 143 112232 10.1016/j.biopha.2021.112232 34649356
    [Google Scholar]
  95. Khan I. Preeti K. Fernandes V. Khatri D.K. Singh S.B. Role of MicroRNAs, aptamers in neuroinflammation and neurodegenerative disorders. Cell. Mol. Neurobiol. 2022 42 7 2075 2095 10.1007/s10571‑021‑01093‑4 33934227
    [Google Scholar]
  96. Li C. Samulski R.J. Engineering adeno-associated virus vectors for gene therapy. Nat. Rev. Genet. 2020 21 4 255 272 10.1038/s41576‑019‑0205‑4 32042148
    [Google Scholar]
  97. Di Francesco V. Chua A.J. Huang D. RNA therapies for CNS diseases. Adv. Drug Deliv. Rev. 2024 208 115283 10.1016/j.addr.2024.115283 38494152
    [Google Scholar]
  98. Saw P.E. Song E. Advancements in clinical RNA therapeutics: Present developments and prospective outlooks. Cell Rep. Med. 2024 5 5 101555 10.1016/j.xcrm.2024.101555 38744276
    [Google Scholar]
  99. Qian L. Lin X. Gao X. The dawn of a new era: Targeting the “undruggables” with antibody-based therapeutics. Chem. Rev. 2023 123 12 7782 7853 10.1021/acs.chemrev.2c00915 37186942
    [Google Scholar]
  100. Graczyk A. Radzikowska-Cieciura E. Kaczmarek R. Pawlowska R. Chworos A. Modified nucleotides for chemical and enzymatic synthesis of therapeutic RNA. Curr. Med. Chem. 2023 30 11 1320 1347 10.2174/0929867330666221014111403 36239720
    [Google Scholar]
  101. Zheng Y.Y. Wu Y. Begley T.J. Sheng J. Sulfur modification in natural RNA and therapeutic oligonucleotides. RSC Chem Biol 2021 2 4 990 1003 10.1039/D1CB00038A 34458821
    [Google Scholar]
  102. Kotikam V. Rozners E. Amide-modified RNA: using protein backbone to modulate function of short interfering RNAs. Acc. Chem. Res. 2020 53 9 1782 1790 10.1021/acs.accounts.0c00249 32658452
    [Google Scholar]
  103. Policarpo R. Sierksma A. De Strooper B. d’Ydewalle C. From junk to function: LncRNAs in CNS health and disease. Front. Mol. Neurosci. 2021 14 714768 10.3389/fnmol.2021.714768 34349622
    [Google Scholar]
  104. Piperno A. Sciortino M.T. Giusto E. Montesi M. Panseri S. Scala A. Recent advances and challenges in gene delivery mediated by polyester-based nanoparticles. Int. J. Nanomedicine 2021 16 5981 6002 10.2147/IJN.S321329 34511901
    [Google Scholar]
  105. Quilez-Molina A.I. Niño Sanchez J. Merino D. The role of polymers in enabling RNAi-based technology for sustainable pest management. Nat. Commun. 2024 15 1 9158 10.1038/s41467‑024‑53468‑y 39443470
    [Google Scholar]
  106. Yang S. Lim K.H. Kim S.H. Joo J.Y. Molecular landscape of long noncoding RNAs in brain disorders. Mol. Psychiatry 2021 26 4 1060 1074 10.1038/s41380‑020‑00947‑5 33173194
    [Google Scholar]
  107. Qadir M.I. Bukhat S. Rasul S. Manzoor H. Manzoor M. RNA therapeutics: Identification of novel targets leading to drug discovery. J. Cell. Biochem. 2020 121 2 898 929 10.1002/jcb.29364 31478252
    [Google Scholar]
  108. Rinaldi S. Moroni E. Rozza R. Magistrato A. Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation. J. Chem. Theory Comput. 2024 20 3 993 1018 10.1021/acs.jctc.3c01239 38287883
    [Google Scholar]
  109. Wu Y. Zhang K. Tools for the analysis of high-dimensional single-cell RNA sequencing data. Nat. Rev. Nephrol. 2020 16 7 408 421 10.1038/s41581‑020‑0262‑0 32221477
    [Google Scholar]
  110. Rawoof A. Kumar A. Tiwari S. Kumar L.D. Bioinformatics of microRNA Target Prediction. In: Bioinformatics and Human Genomics Research. CRC Press 2021 242 276 10.1201/9781003005926‑12
    [Google Scholar]
  111. Morovat P. Morovat S. Hosseinpour M. Moslabeh F.G.Z. Kamali M.J. Samadani A.A. Survival-based bioinformatics analysis to identify hub long non-coding RNAs along with lncRNA-miRNA-mRNA network for potential diagnosis/prognosis of thyroid cancer. J. Cell Commun. Signal. 2023 17 3 639 655 10.1007/s12079‑022‑00697‑9 36149574
    [Google Scholar]
  112. Winkle M. El-Daly S.M. Fabbri M. Calin G.A. Noncoding RNA therapeutics - challenges and potential solutions. Nat. Rev. Drug Discov. 2021 20 8 629 651 10.1038/s41573‑021‑00219‑z 34145432
    [Google Scholar]
  113. Mollica L. Cupaioli F.A. Rossetti G. Chiappori F. An overview of structural approaches to study therapeutic RNAs. Front. Mol. Biosci. 2022 9 1044126 10.3389/fmolb.2022.1044126 36387283
    [Google Scholar]
  114. Singh K.P. Gupta S. 3D Modeling of Non-coding RNA Interactions. Systems Biology of MicroRNAs in Cancer. Springer 2022 281 317 10.1007/978‑3‑031‑08356‑3_11
    [Google Scholar]
  115. Wei Y. Wang Z. Qin Z. The contribution of extracellular RNA and its derived biomaterials in disease management. BMEMat 2025 3 2 e12127 10.1002/bmm2.12127
    [Google Scholar]
  116. Fullenkamp C.R. Liang X. Pettersson M. Schneekloth J. Outlook: A perspective on RNA: The next frontier for small molecule therapeutics. In: RNA as a drug target: The next frontier for medicinal chemistry. Wiley 2024
    [Google Scholar]
  117. Piras A. Chenghao S. Sebek M. Ispirova G. Menichetti G. CPIExtract: A software package to collect and harmonize small molecule and protein interactions. bioRxiv 2024 10.1101/2024.07.03.601957
    [Google Scholar]
  118. Cai Z. Zafferani M. Akande O.M. Hargrove A.E. Quantitative structure–activity relationship (QSAR) study predicts small-molecule binding to RNA structure. J. Med. Chem. 2022 65 10 7262 7277 10.1021/acs.jmedchem.2c00254 35522972
    [Google Scholar]
  119. Marceca G.P. Romano G. Acunzo M. Nigita G. ncRNA editing: Functional characterization and computational resources. Comput Biol Non-Coding RNA Methods Protoc 2024 2883 455 495 10.1007/978‑1‑0716‑4290‑0_20
    [Google Scholar]
  120. Thakur A. Kumar M. Computational resources for lncRNA functions and targetome. Comput Biol Non-Coding RNA Methods Protoc 2024 299 323 10.1007/978‑1‑0716‑4290‑0_13
    [Google Scholar]
  121. Luo X. Tu T. Zhong Y. AGAP2-AS1 may promote the occurrence and development of glioblastoma by sponging miR-9-5p: evidence from a ceRNA network. Front. Oncol. 2021 11 607989 10.3389/fonc.2021.607989 33889541
    [Google Scholar]
  122. Qi Y. Xu R. Song C. A comprehensive database of exosome molecular biomarkers and disease-gene associations. Sci. Data 2024 11 1 210 10.1038/s41597‑024‑03015‑7 38360815
    [Google Scholar]
  123. Gummadi S. Chitti S.V. Kang T. Shahi S. Mathivanan S. Fonseka P. ExoCarta 2024: A web-based repository of small extracellular vesicles cargo. J. Mol. Biol. 2025 437 15 169218 10.1016/j.jmb.2025.169218 40381982
    [Google Scholar]
  124. Liu S. Li J. Shao Q. Chen J. Zou C. Ai Y. Uncovering biomarkers and pathways in oral squamous cell carcinoma through integrated lncRNA-mRNA regulatory network analysis. Discov Oncol 2025 16 1 1462 10.1007/s12672‑025‑02922‑4 40760230
    [Google Scholar]
  125. Kumar A. Chand G.B. Azad G.K. In silico study identifies hub genes and regulatory network associated with the pathogenesis of Japanese encephalitis virus. Egypt. J. Med. Hum. Genet. 2025 26 1 95 10.1186/s43042‑025‑00729‑0
    [Google Scholar]
  126. Zhai J. Lyu T. Guo Y. OTX2 expression contributes progression of gastric cancer in young adults. Sci. Rep. 2025 15 1 16146 10.1038/s41598‑025‑99632‑2 40341176
    [Google Scholar]
  127. Barker H.R. Parkkila S. Tolvanen M.E. TFBSFootprinter: A multiomics tool for prediction of transcription factor binding sites in vertebrate species. Transcription 2025 16 2-3 204 223 10.1080/21541264.2025.2521764 40646689
    [Google Scholar]
  128. Saadat M. Enrichment analysis of loci associated with psoriasis susceptibility identified in genome-wide association studies. Arch. Dermatol. Res. 2025 317 1 564 10.1007/s00403‑025‑04100‑6 40088290
    [Google Scholar]
  129. Fan T. Su Z. Wang X. TarP: A microRNA target gene prediction tool utilizing a polymorphic structured alignment approach. Int. J. Biol. Macromol. 2025 314 144320 10.1016/j.ijbiomac.2025.144320 40383335
    [Google Scholar]
  130. Dar M Suddal T Awan MF Sarwar MF Shakoor S Rab SO dentification of potential target sites in cotton leaf Curl Multan Virus (CLCuMuV) after hybridization through candidate miRNAs in cotton to induce virus resistance 3 Biotech 2025 15 234 10.1007/s13205‑025‑04401‑7
    [Google Scholar]
  131. Athanasopoulou K. Michalopoulou V.I. Scorilas A. Adamopoulos P.G. Integrating Artificial intelligence in next-generation sequencing: Advances, challenges, and future directions. Curr. Issues Mol. Biol. 2025 47 6 470 10.3390/cimb47060470 40699869
    [Google Scholar]
  132. Shi T.L. Wang L. Wong L. Incorporating graph representation and mutual attention mechanism for MiRNA-MRNA interaction prediction. Front. Genet. 2025 16 1637427 10.3389/fgene.2025.1637427 40747104
    [Google Scholar]
  133. Langeberg C.J. Kim T. Nagle R. Improving RNA secondary structure prediction through expanded training data. bioRxiv 2025 2025 05 10.1101/2025.05.03.652028
    [Google Scholar]
  134. Chaturvedi M. Rashid M.A. Paliwal K.K. Transformers in RNA structure prediction: A review. Comput. Struct. Biotechnol. J. 2025 27 1187 1203 10.1016/j.csbj.2025.03.021 40213272
    [Google Scholar]
  135. Mittal A. Mathews D.H. AlignmentFold and AlignmentPartition: Improving the align-then-fold approach for RNA secondary structure prediction. bioRxiv 2025 10.1101/2025.07.23.666478
    [Google Scholar]
  136. Yi W. Yan J. Decoding RNA–Protein Interactions: Methodological Advances and Emerging Challenges. Adv. Genet. 2025 6 2 2500011 10.1002/ggn2.202500011 40657556
    [Google Scholar]
  137. Li J. Xu S. Liu Z. A noncanonical role of roX RNAs in autosomal epigenetic repression. Nat. Commun. 2025 16 1 155 10.1038/s41467‑024‑55711‑y 39747148
    [Google Scholar]
  138. Mishra S. Pandey G.C. Genomic, proteomic and transcriptomic approaches to understanding water stress. In: Water stress in crop plants and its management. CRC Press 2025 159 181 10.1201/9781003433989‑7
    [Google Scholar]
  139. Zhou R. Zhen Y. Ma H. Transcriptome profiling of serum exosomes by RNA-Seq reveals lipid metabolic changes as a potential biomarker for evaluation of roxadustat treatment of chronic kidney diseases. Mol. Omics 2025 21 3 240 249 10.1039/D4MO00025K 40094436
    [Google Scholar]
  140. Guo R. Wang X. Yang Y. Prognostic value of a lncRNA signature in early-stage invasive breast cancer patients. Cancer Cell Int. 2025 25 1 233 10.1186/s12935‑025‑03832‑9 40556001
    [Google Scholar]
  141. Qi D. Wu C. Hao Z. Zhang Z. Liu L. Prediction of lncRNA-miRNA interaction based on sequence and structural information of potential binding site. Int. J. Biol. Macromol. 2025 307 Pt 4 142255 10.1016/j.ijbiomac.2025.142255 40107526
    [Google Scholar]
  142. Mandal A. Jain B.P. Ghosh D.K. High-throughput virtual screening of small molecule modulators against viral proteins. In: Artificial intelligence (AI) in cell and genetic engineering. Springer 2025 193 218 10.1007/978‑1‑0716‑4690‑8_11
    [Google Scholar]
  143. Zeng S. Li Z. Li X. Inhibition of triglyceride metabolism‐associated enhancers alters lipid deposition during adipocyte differentiation. FASEB J. 2025 39 2 e70347 10.1096/fj.202401137R 39873971
    [Google Scholar]
  144. Samuels M. Besta S. Betrán A.L. CRISPR screening approaches in breast cancer research. Cancer Metastasis Rev. 2025 44 3 59 10.1007/s10555‑025‑10275‑1 40650785
    [Google Scholar]
  145. Malekos E. Montano C. Carpenter S. CRISPRware: A software package for contextual gRNA library design. BMC Genomics 2025 26 1 607 10.1186/s12864‑025‑11775‑8
    [Google Scholar]
  146. Ma H. Gao L. Jin Y. RNA–ligand interaction scoring via data perturbation and augmentation modeling. Nat Comput Sci 2025 5 8 648 660 10.1038/s43588‑025‑00820‑x 40555786
    [Google Scholar]
  147. Chen W. Yu Z. Leng L. Artificial intelligence-curated repository of gene-encoded natural diverse components from herbal medicines. Innovation (Camb) 2025 101011 10.1016/j.xinn.2025.101011
    [Google Scholar]
  148. Ursu A. Childs-Disney J.L. Andrews R.J. Design of small molecules targeting RNA structure from sequence. Chem. Soc. Rev. 2020 49 20 7252 7270 10.1039/D0CS00455C 32935689
    [Google Scholar]
  149. Joshi R. Missong H. Mishra J. Nanotheranostics revolutionizing neurodegenerative diseases: From precision diagnosis to targeted therapies. J. Drug Deliv. Sci. Technol. 2023 89 105067 10.1016/j.jddst.2023.105067
    [Google Scholar]
  150. Thakur S. Sinhari A. Jain P. Jadhav H.R. A perspective on oligonucleotide therapy: Approaches to patient customization. Front. Pharmacol. 2022 13 1006304 10.3389/fphar.2022.1006304 36339619
    [Google Scholar]
  151. Panda P. Kar S.S. Mohapatra R. DNA polymer conjugates: Revolutionizing neurological disorder treatment through targeted drug delivery. Next Materials 2025 7 100336 10.1016/j.nxmate.2024.100336
    [Google Scholar]
  152. Yang L. Li S. Hou C. Wang Z. He W. Zhang W. Recent advances in mRNA-based therapeutics for neurodegenerative diseases and brain tumors. Nanoscale 2025 17 7 3537 3548 10.1039/D4NR04394D 39750745
    [Google Scholar]
  153. Wang M.Y. Zhao R. Wang Y.L. Wang D.P. Cao J.M. Challenges with the discovery of RNA-based therapeutics for flaviviruses. Expert Opin. Drug Discov. 2023 18 4 371 383 10.1080/17460441.2023.2195164 36995192
    [Google Scholar]
  154. Basavarajappa B.S. Subbanna S. Unlocking the epigenetic symphony: histone acetylation’s impact on neurobehavioral change in neurodegenerative disorders. Epigenomics 2024 16 5 331 358 10.2217/epi‑2023‑0428 38321930
    [Google Scholar]
  155. Bazrgar M. Khodabakhsh P. Prudencio M. Mohagheghi F. Ahmadiani A. The role of microRNA-34 family in Alzheimer’s disease: A potential molecular link between neurodegeneration and metabolic disorders. Pharmacol. Res. 2021 172 105805 10.1016/j.phrs.2021.105805 34371173
    [Google Scholar]
  156. Bahlakeh G. Gorji A. Soltani H. Ghadiri T. MicroRNA alterations in neuropathologic cognitive disorders with an emphasis on dementia: Lessons from animal models. J. Cell. Physiol. 2021 236 2 806 823 10.1002/jcp.29908 32602584
    [Google Scholar]
  157. Baylot V. Le T.K. Taïeb D. Rocchi P. Colleaux L. Between hope and reality: Treatment of genetic diseases through nucleic acid-based drugs. Commun. Biol. 2024 7 1 489 10.1038/s42003‑024‑06121‑9
    [Google Scholar]
  158. Cheng Y. Zhang S. Shang H. Latest advances on new promising molecular-based therapeutic approaches for Huntington’s disease. J. Transl. Int. Med. 2024 12 2 134 10.2478/jtim‑2023‑0142
    [Google Scholar]
  159. Saade J. Mestre T.A. Huntington’s disease: Latest frontiers in therapeutics. Curr. Neurol. Neurosci. Rep. 2024 24 8 255 264 10.1007/s11910‑024‑01345‑y 38861215
    [Google Scholar]
  160. Parkin G.M. Corey-Bloom J. Considerations and advances in Huntington’s disease clinical trial design. In: Biomarkers for Huntington’s Disease: Improving Clinical Outcomes. Springer 2023 405 431 10.1007/978‑3‑031‑32815‑2_17
    [Google Scholar]
  161. Lozupone M. Dibello V. Sardone R. The development of peptide- and oligonucleotide-based drugs to prevent the formation of abnormal tau in tauopathies. Expert Opin. Drug Discov. 2023 18 5 515 526 10.1080/17460441.2023.2200245 37042028
    [Google Scholar]
  162. Estevez-Fraga C. Tabrizi S.J. Wild E.J. Huntington’s disease clinical trials corner. J. Huntingtons Dis. 2023 12 2 169 185 10.3233/JHD‑239001 37483021
    [Google Scholar]
  163. Wu Y.C. Ku M.H. Huang W.L. Dias L. Chen C.W. NEAT1 in ovarian cancer: A key regulator of tumor progression, follicular fluid dynamics, and therapeutic resistance. Anticancer Res. 2025 45 3 825 842 10.21873/anticanres.17472 40037884
    [Google Scholar]
  164. Țica O. Țica O. Molecular diagnostics in heart failure: from biomarkers to personalized medicine. Diagnostics 2025 15 14 1807 10.3390/diagnostics15141807 40722556
    [Google Scholar]
  165. Ou S. Nie X. Qiu X. Deciphering the mechanisms of long non-coding RNAs in ferroptosis: insights into its clinical significance in cancer progression and immunology. Cell Death Discov. 2025 11 1 14 10.1038/s41420‑025‑02290‑6 39827195
    [Google Scholar]
  166. Li X. Bedlack R. Evaluating emerging drugs in phase II & III for the treatment of amyotrophic lateral sclerosis. Expert Opin. Emerg. Drugs 2024 29 2 93 102 10.1080/14728214.2024.2333420 38516735
    [Google Scholar]
  167. Thongchot S. Duangkaew S. Yotchai W. Novel CSF1R-positive tenosynovial giant cell tumor cell lines and their pexidartinib (PLX3397) and sotuletinib (BLZ945)-induced apoptosis. Hum. Cell 2022 36 1 456 467 10.1007/s13577‑022‑00823‑0 36456782
    [Google Scholar]
  168. Wang P. Zhou Y. Richards A.M. Effective tools for RNA-derived therapeutics: siRNA interference or miRNA mimicry. Theranostics 2021 11 18 8771 8796 10.7150/thno.62642 34522211
    [Google Scholar]
  169. Liao J. Fan L. Li Y. Recent advances in biomimetic nanodelivery systems: New brain-targeting strategies. J. Control. Release 2023 358 439 464 10.1016/j.jconrel.2023.05.009 37169179
    [Google Scholar]
  170. Teixeira L.C.R. Mamede I. Luizon M.R. Gomes K.B. Role of long non-coding RNAs in the pathophysiology of Alzheimer’s disease and other dementias. Mol. Biol. Rep. 2024 51 1 270 10.1007/s11033‑023‑09178‑7 38302810
    [Google Scholar]
  171. Ebrahimi P. Davoudi E. Sadeghian R. In vivo and ex vivo gene therapy for neurodegenerative diseases: a promise for disease modification. Naunyn Schmiedebergs Arch. Pharmacol. 2024 397 10 7501 7530 10.1007/s00210‑024‑03141‑4 38775852
    [Google Scholar]
  172. Mir F.A. Amanullah A. Jain B.P. Hyderi Z. Gautam A. Neuroepigenetics of ageing and neurodegeneration-associated dementia: An updated review. Ageing Res. Rev. 2023 91 102067 10.1016/j.arr.2023.102067 37689143
    [Google Scholar]
  173. Ali A. Khatoon A. Shao C. Murtaza B. Tanveer Q. Su Z. Therapeutic potential of natural antisense transcripts and various mechanisms involved for clinical applications and disease prevention. RNA Biol. 2024 21 1 127 144 10.1080/15476286.2023.2293335 38090817
    [Google Scholar]
  174. Morselli Gysi D. Barabási A.L. Noncoding RNAs improve the predictive power of network medicine. Proc. Natl. Acad. Sci. USA 2023 120 45 e2301342120 10.1073/pnas.2301342120 37906646
    [Google Scholar]
  175. Youness R.A. Hassan H.A. Abaza T. A comprehensive insight and in Silico analysis of CircRNAs in hepatocellular carcinoma: a step toward ncRNA-based precision medicine. Cells 2024 13 15 1245 10.3390/cells13151245 39120276
    [Google Scholar]
  176. Smail C. Montgomery S.B. RNA Sequencing in disease diagnosis. Annu. Rev. Genomics Hum. Genet. 2024 25 1 353 367 10.1146/annurev‑genom‑021623‑121812 38360541
    [Google Scholar]
  177. Alahdal M. Elkord E. Non‐coding RNAs in cancer immunotherapy: Predictive biomarkers and targets. Clin. Transl. Med. 2023 13 9 e1425 10.1002/ctm2.1425 37735815
    [Google Scholar]
  178. Louie A.D. Huntington K. Carlsen L. Zhou L. El-Deiry W.S. Integrating molecular biomarker inputs into development and use of clinical cancer therapeutics. Front. Pharmacol. 2021 12 747194 10.3389/fphar.2021.747194 34737704
    [Google Scholar]
  179. Aledhari M Rahouti M. Gene and RNA Editing: Methods, enabling technologies, applications, and future directions. preprint 2024
  180. Akyuz E. Aslan F.S. Gokce E. Ilmaz O. Topcu F. Kakac S. Extracellular vesicle and CRISPR gene therapy: Current applications in Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease. Eur. J. Neurosci. 2024 60 8 6057 6090 10.1111/ejn.16541 39297377
    [Google Scholar]
  181. Rasheed A. Barqawi A.A. Mahmood A. CRISPR/Cas9 is a powerful tool for precise genome editing of legume crops: a review. Mol. Biol. Rep. 2022 49 6 5595 5609 10.1007/s11033‑022‑07529‑4 35585381
    [Google Scholar]
  182. Javaid D. Ganie S.Y. Hajam Y.A. Reshi M.S. CRISPR/Cas9 system: a reliable and facile genome editing tool in modern biology. Mol. Biol. Rep. 2022 49 12 12133 12150 10.1007/s11033‑022‑07880‑6 36030476
    [Google Scholar]
  183. DeJulius C.R. Walton B.L. Colazo J.M. Engineering approaches for RNA-based and cell-based osteoarthritis therapies. Nat. Rev. Rheumatol. 2024 20 2 81 100 10.1038/s41584‑023‑01067‑4 38253889
    [Google Scholar]
  184. Bhushan B. Singh K. Kumar S. Bhardwaj A. Advancements in CRISPR-Based therapies for genetic modulation in neurodegenerative disorders. Curr. Gene Ther. 2025 25 1 34 45 10.2174/0115665232292246240426125504 38738727
    [Google Scholar]
  185. Qin M. Deng C. Wen L. Luo G. Meng Y. CRISPR-Cas and CRISPR-based screening system for precise gene editing and targeted cancer therapy. J. Transl. Med. 2024 22 1 516 10.1186/s12967‑024‑05235‑2 38816739
    [Google Scholar]
  186. Lam S. Thomas J.C. Jackson S.P. Genome-aware annotation of CRISPR guides validates targets in variant cell lines and enhances discovery in screens. Genome Med. 2024 16 1 139 10.1186/s13073‑024‑01414‑4 39593080
    [Google Scholar]
  187. Esposto J. Epigenetic manipulation and gene regulation using the CRISPR/Cas system for neurodegenerative diseases. In: Genome Editing for Neurodegenerative Diseases. Elsevier 2025 119 133 10.1016/B978‑0‑443‑23826‑0.00006‑4
    [Google Scholar]
  188. Tao J. Bauer D.E. Chiarle R. Assessing and advancing the safety of CRISPR-Cas tools: from DNA to RNA editing. Nat. Commun. 2023 14 1 212 10.1038/s41467‑023‑35886‑6 36639728
    [Google Scholar]
  189. Yang H. Patel D.J. Structures, mechanisms and applications of RNA-centric CRISPR–Cas13. Nat. Chem. Biol. 2024 20 6 673 688 10.1038/s41589‑024‑01593‑6 38702571
    [Google Scholar]
  190. Kordyś M. Sen R. Warkocki Z. Applications of the versatile CRISPR‐Cas13 RNA targeting system. Wiley Interdiscip. Rev. RNA 2022 13 3 e1694 10.1002/wrna.1694 34553495
    [Google Scholar]
  191. Mengstie A.M. Azezew T.M. Dejenie A.T. Recent advancements in reducing the off-target effect of CRISPR-Cas9 Genome editing. Biol Targets Ther 2024 21 28 10.2147/BTT.S429411
    [Google Scholar]
  192. Neumeier J. Meister G. siRNA specificity: RNAi mechanisms and strategies to reduce off-target effects. Front Plant Sci 2021 11 526455 10.3389/fpls.2020.526455 33584737
    [Google Scholar]
  193. Chen H. Yao H. Chi J. Engineered exosomes as drug and RNA co-delivery system: new hope for enhanced therapeutics? Front. Bioeng. Biotechnol. 2023 11 1254356 10.3389/fbioe.2023.1254356 37823027
    [Google Scholar]
  194. Hashmi M.A.T.S. Fatima H. Ahmad S. Rehman A. Safdar F. The interplay between epitranscriptomic RNA modifications and neurodegenerative disorders: Mechanistic insights and potential therapeutic strategies. Ibrain 2024 11 10 10.1002/ibra.12183
    [Google Scholar]
  195. Conklin B. Conley B.M. Hou Y. Chen M. Lee K.B. Advanced theragnostics for the central nervous system (CNS) and neurological disorders using functional inorganic nanomaterials. Adv. Drug Deliv. Rev. 2023 192 114636 10.1016/j.addr.2022.114636 36481291
    [Google Scholar]
  196. Shang J. Song F. Zhang Z. Chen D. Yang S. Application of novel CRISPR tools in brain therapy. Life Sci. 2024 352 122855 10.1016/j.lfs.2024.122855 38908787
    [Google Scholar]
  197. Chen X.Q. Zuo X. Becker A. Antisense oligonucleotides directed against App and Rab5 normalized endosomal Rab activity and reversed DS‐AD‐linked degenerative phenotypes in the Dp16 mouse model of Down syndrome. Alzheimers Dement. 2025 21 5 e70022 10.1002/alz.70022 40339155
    [Google Scholar]
  198. Bunting E.L. Donaldson J. Cumming S.A. Antisense oligonucleotide–mediated MSH3 suppression reduces somatic CAG repeat expansion in Huntington’s disease iPSC–derived striatal neurons. Sci. Transl. Med. 2025 17 785 eadn4600 10.1126/scitranslmed.adn4600 39937881
    [Google Scholar]
  199. Sano T. Nagata T. Ebihara S. Effects of local reduction of endogenous α-synuclein using antisense oligonucleotides on the fibril-induced propagation of pathology through the neural network in wild-type mice. Acta Neuropathol. Commun. 2024 12 1 75 10.1186/s40478‑024‑01766‑3 38745295
    [Google Scholar]
  200. DeVos S.L. Miller R.L. Schoch K.M. Tau reduction prevents neuronal loss and reverses pathological tau deposition and seeding in mice with tauopathy. Sci. Transl. Med. 2017 9 374 eaag0481 10.1126/scitranslmed.aag0481 28123067
    [Google Scholar]
  201. Cole T.A. Zhao H. Collier T.J. α-Synuclein antisense oligonucleotides as a disease-modifying therapy for Parkinson’s disease. JCI Insight 2021 6 5 e135633 10.1172/jci.insight.135633 33682798
    [Google Scholar]
  202. Tran H. Moazami M.P. Yang H. Suppression of mutant C9orf72 expression by a potent mixed backbone antisense oligonucleotide. Nat. Med. 2022 28 1 117 124 10.1038/s41591‑021‑01557‑6 34949835
    [Google Scholar]
  203. Han Y. Khodr C.E. Sapru M.K. Pedapati J. Bohn M.C. A microRNA embedded AAV α-synuclein gene silencing vector for dopaminergic neurons. Brain Res. 2011 1386 15 24 10.1016/j.brainres.2011.02.041 21338582
    [Google Scholar]
  204. Cook BE Pickel TC Nag S PET imaging of antisense oligonucleotide distribution in rat and nonhuman primate brains using click chemistry. Sci Transl Med 2025 17 797 : eadl1732 10.1126/scitranslmed.adl1732
    [Google Scholar]
  205. Mortberg M.A. Gentile J.E. Nadaf N.M. A single-cell map of antisense oligonucleotide activity in the brain. Nucleic Acids Res. 2023 51 14 7109 7124 10.1093/nar/gkad371 37188501
    [Google Scholar]
  206. Ahammad R.U. Spencer B. Quach B. Salehi S. Rissman R.A. A splice‐switching antisense oligonucleotide targeting APP reduces accumulation of α‐synuclein in a mouse model of Parkinson’s disease. Alzheimers Dement. (N. Y.) 2025 11 2 e70117 10.1002/trc2.70117 40556661
    [Google Scholar]
  207. Everett W.H. Bucelli R.C. Tofersen for SOD1 ALS. Neurodegener. Dis. Manag. 2024 14 5 149 160 10.1080/17582024.2024.2402216 39330700
    [Google Scholar]
  208. Liu Y. Dodart J.C. Tran H. Variant-selective stereopure oligonucleotides protect against pathologies associated with C9orf72-repeat expansion in preclinical models. Nat. Commun. 2021 12 1 847 10.1038/s41467‑021‑21112‑8 33558503
    [Google Scholar]
  209. Weiss A. Gilbert J.W. Rivera Flores I.V. RNAi-mediated silencing of SOD1 profoundly extends survival and functional outcomes in ALS mice. Mol. Ther. 2025 33 8 3917 3938 10.1016/j.ymthe.2025.05.010 40349108
    [Google Scholar]
  210. Goyenvalle A. Jimenez-Mallebrera C. van Roon W. Considerations in the preclinical assessment of the safety of antisense oligonucleotides. Nucleic Acid Ther. 2023 33 1 1 16 10.1089/nat.2022.0061 36579950
    [Google Scholar]
  211. Andersson P. Preclinical safety assessment of therapeutic oligonucleotides BT - antisense RNA design, delivery, and analysis. Arechavala-Gomeza V. Garanto A. Springer US. 2022 355 370 10.1007/978‑1‑0716‑2010‑6_25
    [Google Scholar]
  212. Hagedorn P.H. Brown J.M. Easton A. Acute neurotoxicity of antisense oligonucleotides after intracerebroventricular injection into mouse brain can be predicted from sequence features. Nucleic Acid Ther. 2022 32 3 151 162 10.1089/nat.2021.0071 35166597
    [Google Scholar]
  213. Crooke S.T. Baker B.F. Kwoh T.J. Integrated safety assessment of 2′-O-methoxyethyl chimeric antisense oligonucleotides in nonhuman primates and healthy human volunteers. Mol. Ther. 2016 24 10 1771 1782 10.1038/mt.2016.136 27357629
    [Google Scholar]
  214. Miller R. Paquette J. Barker A. Preventing acute neurotoxicity of CNS therapeutic oligonucleotides with the addition of Ca2+ and Mg2+ in the formulation. Mol. Ther. Nucleic Acids 2024 35 4 102359 10.1016/j.omtn.2024.102359 39554992
    [Google Scholar]
  215. Morris G. Schorge S. Gene therapy for neurological disease: state of the art and opportunities for next-generation approaches. Neuroscience 2022 490 309 314 10.1016/j.neuroscience.2022.03.010 35304290
    [Google Scholar]
  216. Muolokwu C.E. Chaulagain B. Gothwal A. Functionalized nanoparticles to deliver nucleic acids to the brain for the treatment of Alzheimer’s disease. Front. Pharmacol. 2024 15 1405423 10.3389/fphar.2024.1405423 38855744
    [Google Scholar]
  217. Xu Y. Fourniols T. Labrak Y. Préat V. Beloqui A. des Rieux A. Surface modification of lipid-based nanoparticles. ACS Nano 2022 16 5 7168 7196 10.1021/acsnano.2c02347 35446546
    [Google Scholar]
  218. Mo J. Weng X. Zhou X. Detection, Clinical Application, and Manipulation of RNA Modifications. Acc. Chem. Res. 2023 56 20 2788 2800 10.1021/acs.accounts.3c00395 37769231
    [Google Scholar]
  219. Mondal J. Pillarisetti S. Junnuthula V. Hybrid exosomes, exosome-like nanovesicles and engineered exosomes for therapeutic applications. J. Control. Release 2023 353 1127 1149 10.1016/j.jconrel.2022.12.027 36528193
    [Google Scholar]
  220. Shariati L. Esmaeili Y. Rahimmanesh I. Advances in nanobased platforms for cardiovascular diseases: Early diagnosis, imaging, treatment, and tissue engineering. Environ. Res. 2023 238 Pt 1 116933 10.1016/j.envres.2023.116933 37652218
    [Google Scholar]
  221. O’Brien K. Breyne K. Ughetto S. Laurent L.C. Breakefield X.O. RNA delivery by extracellular vesicles in mammalian cells and its applications. Nat. Rev. Mol. Cell Biol. 2020 21 10 585 606 10.1038/s41580‑020‑0251‑y 32457507
    [Google Scholar]
  222. Bashyal S. Thapa C. Lee S. Recent progresses in exosome-based systems for targeted drug delivery to the brain. J. Control. Release 2022 348 723 744 10.1016/j.jconrel.2022.06.011 35718214
    [Google Scholar]
  223. Herrera-Barrera M. Ryals R.C. Gautam M. Peptide-guided lipid nanoparticles deliver mRNA to the neural retina of rodents and nonhuman primates. Sci. Adv. 2023 9 2 eadd4623 10.1126/sciadv.add4623 36630502
    [Google Scholar]
  224. Gao J. Nutan B. Gargouri D. Unlocking the potential of chemically modified nucleic acid therapeutics. Adv. Ther. (Weinh.) 2024 7 11 2400231 10.1002/adtp.202400231
    [Google Scholar]
  225. Egli M. Manoharan M. Chemistry, structure and function of approved oligonucleotide therapeutics. Nucleic Acids Res. 2023 51 6 2529 2573 10.1093/nar/gkad067 36881759
    [Google Scholar]
  226. Butterfield L.H. Najjar Y.G. Immunotherapy combination approaches: Mechanisms, biomarkers and clinical observations. Nat. Rev. Immunol. 2024 24 6 399 416 10.1038/s41577‑023‑00973‑8 38057451
    [Google Scholar]
  227. Gao Q. Feng J. Liu W. Opportunities and challenges for co-delivery nanomedicines based on combination of phytochemicals with chemotherapeutic drugs in cancer treatment. Adv. Drug Deliv. Rev. 2022 188 114445 10.1016/j.addr.2022.114445 35820601
    [Google Scholar]
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