Modern advanced radiotherapy techniques have improved the precision and accuracy of radiotherapy delivery, with resulting plans being highly personalised based on individual anatomy. Adaptation for individual tumour biology remains elusive. There is an unmet need for biomarkers of intrinsic radiosensitivity that can predict tumour response to radiation to facilitate individualised decision-making, dosing and treatment planning. Over the last few decades, the use of high throughput molecular biology technologies has led to an explosion of newly discovered cancer biomarkers. Gene expression signatures are now used routinely in clinic to aid decision-making regarding adjuvant systemic therapy. They have great potential as radiotherapy biomarkers. A previous systematic review published in 2015 reported only five studies of signatures evaluated for their ability to predict radiotherapy benefits in clinical cohorts. This updated systematic review encompasses the expanded number of studies reported in the last decade. An additional 27 studies were identified. In total, 22 distinct signatures were recognised (5 pre-2015, 17 post-2015). Seventeen signatures were ‘radiosensitivity’ signatures and five were breast cancer prognostic signatures aiming to identify patients at an increased risk of local recurrence and therefore were more likely to benefit from adjuvant radiation. Most signatures (15/22) had not progressed beyond the discovery phase of development, with no suitable validated clinical-grade assay for application. Very few signatures (4/17 ‘radiosensitivity’ signatures) had undergone any laboratory-based biological validation of their ability to predict tumour radiosensitivity. No signatures have been assessed prospectively in a phase III biomarker-led trial to date and none are recommended for routine use in clinical guidelines. A phase III prospective evaluation is ongoing for two breast cancer prognostic signatures. The most promising radiosensitivity signature remains the radiosensitivity index (RSI), which is used to calculate a genomic adjusted radiation dose (GARD). There is an ongoing phase II prospective biomarker-led study of RSI/GARD in triple negative breast cancer. The results of these trials are eagerly anticipated over the coming years. Future work in this area should focus on (1) robust biological validation; (2) building biobanks alongside large radiotherapy randomised controlled trials with dose variance (to demonstrate an interaction between radiosensitivity signature and dose); (3) a validation of clinical-grade cost-effective assays that are deliverable within current healthcare infrastructure; and (4) an integration with biomarkers of other determinants of radiation response.
现代先进放射治疗技术提升了放疗实施的精确性与准确性，由此产生的治疗方案能基于个体解剖结构实现高度个性化。然而针对个体肿瘤生物学的适应性调整仍面临挑战。目前亟需能够预测肿瘤放射反应的内在放射敏感性生物标志物，以推动个体化决策、剂量规划和治疗方案制定。过去几十年间，高通量分子生物学技术的应用催生了大量新发现的癌症生物标志物。基因表达特征谱目前已常规应用于临床，辅助辅助性全身治疗的决策制定。这些特征谱作为放疗生物标志物具有巨大潜力。2015年发表的系统性综述仅报告了五项在临床队列中评估预测放疗获益能力的研究。本次更新的系统性综述涵盖了近十年来大幅增长的研究数量，新增27项研究。共识别出22个独立特征谱（5个为2015年前发现，17个为2015年后发现）。其中17个为“放射敏感性”特征谱，5个为旨在识别局部复发风险增高、因而更可能从辅助放疗中获益的乳腺癌预后特征谱。多数特征谱（15/22）仍停留在发现阶段，缺乏适用于临床的验证级检测方法。极少数特征谱（4/17的“放射敏感性”特征谱）进行了基于实验室的生物学验证，以评估其预测肿瘤放射敏感性的能力。迄今为止，尚无特征谱在III期生物标志物引导试验中进行前瞻性评估，临床指南中也未推荐任何特征谱用于常规临床实践。目前有两项乳腺癌预后特征谱正在进行III期前瞻性评估。最具前景的放射敏感性特征谱仍是放射敏感性指数（RSI），该指数用于计算基因组调整放射剂量（GARD）。目前正在开展一项针对三阴性乳腺癌的RSI/GARD II期前瞻性生物标志物引导研究。这些试验结果在未来数年内备受期待。该领域未来工作应聚焦于：（1）开展严谨的生物学验证；（2）在大型放疗随机对照试验（包含剂量变异）中同步建立生物样本库（以证明放射敏感性特征谱与剂量间的交互作用）；（3）开发适用于现有医疗体系、具有成本效益的临床级检测验证方法；（4）与放射反应其他决定因素的生物标志物进行整合。
肿瘤(癌症)患者之家