The times they are AI-changing: AI-powered advances in the application of extracellular vesicles to liquid biopsy in breast cancer
Vanesa García-Barberán , María Elena Gómez Del Pulgar , Heidy M. Guamán , Alberto Benito-Martin
Extracellular Vesicles and Circulating Nucleic Acids ›› 2025, Vol. 6 ›› Issue (1) : 128 -40.
The times they are AI-changing: AI-powered advances in the application of extracellular vesicles to liquid biopsy in breast cancer
Artificial intelligence (AI) is revolutionizing scientific research by facilitating a paradigm shift in data analysis and discovery. This transformation is characterized by a fundamental change in scientific methods and concepts due to AI’s ability to process vast datasets with unprecedented speed and accuracy. In breast cancer research, AI aids in early detection, prognosis, and personalized treatment strategies. Liquid biopsy, a noninvasive tool for detecting circulating tumor traits, could ideally benefit from AI’s analytical capabilities, enhancing the detection of minimal residual disease and improving treatment monitoring. Extracellular vesicles (EVs), which are key elements in cell communication and cancer progression, could be analyzed with AI to identify disease-specific biomarkers. AI combined with EV analysis promises an enhancement in diagnosis precision, aiding in early detection and treatment monitoring. Studies show that AI can differentiate cancer types and predict drug efficacy, exemplifying its potential in personalized medicine. Overall, the integration of AI in biomedical research and clinical practice promises significant changes and advancements in diagnostics, personalized medicine-based approaches, and our understanding of complex diseases like cancer.
Extracellular vesicles / breast cancer / artificial intelligence / liquid biopsy
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
Mueller ST, Hoffman RR, Clancey W, Emrey A, Klein G. Explanation in human-AI systems: a literature meta-review, synopsis of key ideas and publications, and bibliography for explainable AI. arXiv 2019;arXiv:1902.01876. Available from https://arxiv.org/abs/1902.01876 [accessed 11 February 2025]. |
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
|
| [40] |
|
| [41] |
|
| [42] |
|
| [43] |
World Health Organization. Obesity and overweight. Available from https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight [accessed 11 February 2025]. |
| [44] |
|
| [45] |
Dorling L, Carvalho S, Allen J, et al; Breast Cancer Association Consortium. Breast cancer risk genes - association analysis in more than 113,000 women. N Engl J Med. 2021;384:428-39. PMCID:PMC7611105 |
| [46] |
|
| [47] |
|
| [48] |
|
| [49] |
|
| [50] |
|
| [51] |
Yee D, DeMichele AM, Yau C, et al; I-SPY2 Trial Consortium. Association of event-free and distant recurrence-free survival with individual-level pathologic complete response in neoadjuvant treatment of stages 2 and 3 breast cancer: three-year follow-up analysis for the I-SPY2 adaptively randomized clinical trial. JAMA Oncol. 2020;6:1355-62. PMCID:PMC7378873 |
| [52] |
|
| [53] |
|
| [54] |
|
| [55] |
|
| [56] |
|
| [57] |
|
| [58] |
|
| [59] |
|
| [60] |
|
| [61] |
|
| [62] |
|
| [63] |
|
| [64] |
|
| [65] |
|
| [66] |
|
| [67] |
|
| [68] |
|
| [69] |
|
| [70] |
|
| [71] |
|
| [72] |
|
| [73] |
|
| [74] |
|
| [75] |
|
| [76] |
|
| [77] |
|
| [78] |
|
| [79] |
|
| [80] |
|
| [81] |
|
| [82] |
|
| [83] |
Welsh JA, Goberdhan DCI, O’Driscoll L, et al; MISEV Consortium. Minimal information for studies of extracellular vesicles (MISEV2023): from basic to advanced approaches. J Extracell Vesicles. 2024;13:e12404. PMCID:PMC10850029 |
| [84] |
|
| [85] |
|
| [86] |
|
| [87] |
|
| [88] |
|
| [89] |
|
| [90] |
|
| [91] |
|
| [92] |
|
| [93] |
|
| [94] |
|
| [95] |
|
| [96] |
|
| [97] |
|
| [98] |
|
| [99] |
|
| [100] |
|
/
| 〈 |
|
〉 |