Despite therapeutic advancements, disease-free survival and overall survival of patients with locally advanced rectal cancer have not improved in most trials as a result of distant metastases. For treatment decision-making, both long-term oncologic outcomes and impact on quality-of-life indices should be considered (for example, bowel function). Total neoadjuvant therapy (TNT), comprised of chemotherapy and radiotherapy or chemoradiotherapy, is now a standard treatment approach in patients with features of high-risk disease to prevent local recurrence and distant metastases. In selected patients who have a clinical complete response, subsequent surgery might be avoided through non-operative management, but patients who do not respond to TNT have a poor prognosis. Refined molecular characterization might help to predict which patients would benefit from TNT and non-operative management. Specifically, integrated analysis of spatiotemporal multi-omics using artificial intelligence and machine learning is promising. Three prospective trials of TNT and non-operative management in Japan, the USA and Germany are collaborating to better understand drivers of response to TNT. Here, we address the future direction for TNT.

尽管治疗取得了进展，但在大多数试验中，由于远处转移，局部晚期直肠癌患者的无病生存率和总生存率并未得到改善。对于治疗决策，应考虑长期肿瘤学结果和对生活质量指数的影响（例如肠道功能）。全新辅助治疗（TNT）由化疗和放疗或放化疗组成，现已成为具有高危疾病特征的患者的标准治疗方法，以防止局部复发和远处转移。在某些具有临床完全缓解的患者中，可以通过非手术治疗避免后续手术，但对 TNT 无反应的患者预后较差。精细的分子表征可能有助于预测哪些患者将从 TNT 和非手术治疗中受益。具体来说，使用人工智能和机器学习进行时空多组学的综合分析是有前途的。日本、美国和德国正在合作进行三项 TNT 和非手术治疗的前瞻性试验，以更好地了解 TNT 反应的驱动因素。在这里，我们谈谈 TNT 的未来发展方向。