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| Home > Publications database > Raman Spectroscopies for Cancer Research and Clinical Applications: a Focus on Cancer Stem Cells. > print |
| 001 | 298935 | ||
| 005 | 20250425093418.0 | ||
| 024 | 7 | _ | |a 10.1093/stmcls/sxae084 |2 doi |
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| 024 | 7 | _ | |a 1066-5099 |2 ISSN |
| 024 | 7 | _ | |a 0737-1454 |2 ISSN |
| 024 | 7 | _ | |a 1549-4918 |2 ISSN |
| 037 | _ | _ | |a DKFZ-2025-00369 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Pagliari, Francesca |0 P:(DE-He78)d06e5bb2d0828caa2be79a51825e84e1 |b 0 |e First author |u dkfz |
| 245 | _ | _ | |a Raman Spectroscopies for Cancer Research and Clinical Applications: a Focus on Cancer Stem Cells. |
| 260 | _ | _ | |a Oxford |c 2025 |b Oxford University Press |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a #EA:E041# / Volume 43, Issue 4, April 2025, sxae084 |
| 520 | _ | _ | |a Over the last two decades, research has increasingly focused on Cancer Stem Cells (CSCs), considered responsible for tumor formation, resistance to therapies, and relapse. The traditional 'static' CSC model used to describe tumor heterogeneity has been challenged by the evidence of CSC dynamic nature and plasticity. A comprehensive understanding of the mechanisms underlying this plasticity, and the capacity to unambiguously identify cancer markers to precisely target CSCs are crucial aspects for advancing cancer research and introducing more effective treatment strategies. In this context, Raman spectroscopy (RS) and specific Raman schemes, including CARS, SRS, SERS, have emerged as innovative tools for molecular analyses both in vitro and in vivo. In fact, these techniques have demonstrated considerable potential in the field of cancer detection, as well as in intraoperative settings, thanks to their label-free nature and minimal invasiveness. However, the RS integration in pre-clinical and clinical applications, particularly in the CSC field, remains limited. This review provides a concise overview of the historical development of RS and its advantages. Then, after introducing the CSC features and the challenges in targeting them with traditional methods, we review and discuss the current literature about the application of RS for revealing and characterizing CSCs and their inherent plasticity, including a brief paragraph about the integration of artificial intelligence with RS. By providing the possibility to better characterize the cellular diversity in their microenvironment, RS could revolutionize current diagnostic and therapeutic approaches, enabling early identification of CSCs and facilitating the development of personalized treatment strategies. |
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| 650 | _ | 7 | |a Cancer Stem Cells |2 Other |
| 650 | _ | 7 | |a Cancer detection |2 Other |
| 650 | _ | 7 | |a Cancer markers |2 Other |
| 650 | _ | 7 | |a Label-free imaging |2 Other |
| 650 | _ | 7 | |a Raman spectroscopy |2 Other |
| 700 | 1 | _ | |a Tirinato, Luca |b 1 |
| 700 | 1 | _ | |a Di Fabrizio, Enzo |0 0000-0001-9826-2129 |b 2 |
| 773 | _ | _ | |a 10.1093/stmcls/sxae084 |g p. sxae084 |0 PERI:(DE-600)2030643-X |n 4 |p sxae084 |t Stem cells |v 43 |y 2025 |x 1066-5099 |
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