CURRENT CHALLENGES AND FUTURE DIRECTIONS

Single Cell RNA‐sequencing and radiotherapy biobanking

Currently, research on proton therapy primarily focuses on bulk RNA sequencing in cancers such as BC, GBM, head and neck cancer, prostate cancer, lung cancer, and pancreatic cancer (Table 1). Because single‐cell RNA sequencing better describes biological changes in different cell types, it has been applied to GBM, 141 BC, 142 NSCLC, 143 and head and neck cancer 144 during photon therapy. However, the application of single‐cell transcriptomics in proton therapy is limited at present. Using single‐cell RNA sequencing, Shiau et al. discovered that proton therapy was associated with a reduction in lymphatic endothelial cells (ECs) and an increase in reactive endothelial‐to‐mesenchymal transition (EndMT) in PDAC. These findings suggest that incorporating nintedanib, an EndMT‐inhibiting drug, into proton therapy may provide a more effective therapeutic strategy. 145 Furthermore, as biological data accumulate, establishing radiotherapy biobanks could promote data sharing across multiple centers and prevent duplicated efforts. 146 In summary, utilizing the single‐cell RNA sequencing and establishing an authentic, large‐sample radiotherapy biobanking could improve the personalization of proton therapy.

Technical challenges in clinical applications

The clinical implementation of proton therapy is subject to several technical challenges that hinder its widespread adoption. These challenges include the high costs of building and maintaining proton therapy facilities, complexity of treatment planning systems, and need for specialized training of medical personnel. 147 In addition, precise delivery of proton beams requires advanced imaging techniques. Robust quality assurance protocols are essential for accurately targeting tumors while sparing the surrounding healthy tissue. Variability in patient anatomy and tumor characteristics further complicates treatment planning, necessitating the development of more sophisticated computational models and machine learning algorithms to predict treatment outcomes. 148 Overcoming these technical hurdles is essential to optimize proton therapy and establish it as a standard treatment for various cancers.

High quality clinical research

Proton therapy is expensive and has strict indications. Therefore, conducting large‐scale clinical trials is challenging. However, multi‐center collaborative research may be a potential solution. Because combining proton therapy with other treatment strategies, such as immunotherapy and chemotherapy, may produce synergistic effects, hospitals should collaborate with pharmaceutical companies to facilitate clinical trials of these combination therapies. By performing multi‐cooperative, large‐sample, prospective, authoritative clinical studies, we may accumulate robust evidence regarding the efficacy and safety of proton therapy across various cancer types, which would ultimately benefit patients with cancer through improved treatment options.