Nolan Ben, O'Sullivan Brian, Golden Aaron
Discipline of Bioinformatics, School of Mathematical and Statistical Sciences, National University of Ireland Galway, University Road, Galway H91 TK33, Ireland.
School of Natural Sciences, National University of Ireland Galway, University Road, Galway H91 TK33, Ireland.
Clin Transl Radiat Oncol. 2022 Aug 9;36:127-131. doi: 10.1016/j.ctro.2022.08.002. eCollection 2022 Sep.
The use of a 10 gene transcriptional signature as part of the GARD model has been shown to be predictive of radiotherapy benefit for a range of cancers, with the potential to determine an optimal overall dose per patient. We used publicly available RNA-seq transcriptomics data from a luminal B breast cancer patient and from 14 prostate cancer patients to explore the radiosensitivity indices (RSI) and so GARD estimates of both tumour and proximal normal biopsies from each individual. Clear differences of clinical relevance in derived radiobiological properties between tumour and proximal normal tissues were evident for the breast cancer patient, whilst such differences across the prostate cancer cohort were more equivocal. Using the prostate cancer cohort's median tumour predicted GARD value as a threshold for high therapeutic effect for radiotherapy, we found evidence that a higher overall prescribed dose than the widely used 72 Gy/36fx could benefit half of these patients. This exploratory study demonstrates the potential combining the GARD model with sequencing based transcriptomics could have in informing personalised radiotherapeutic practise for both breast and prostate cancer patients.
10基因转录特征作为GARD模型的一部分,已被证明可预测多种癌症的放疗获益,并有可能为每位患者确定最佳总剂量。我们使用了来自一名腔面B型乳腺癌患者和14名前列腺癌患者的公开RNA测序转录组学数据,以探索放射敏感性指数(RSI),从而对每个个体的肿瘤和近端正常活检组织进行GARD估计。乳腺癌患者的肿瘤组织和近端正常组织之间在衍生的放射生物学特性上存在明显的临床相关差异,而前列腺癌队列中的此类差异则更为模糊。以前列腺癌队列中肿瘤预测GARD值的中位数作为放疗高治疗效果的阈值,我们发现有证据表明,高于广泛使用的72 Gy/36次分割的总处方剂量可能使这些患者中的一半受益。这项探索性研究表明,将GARD模型与基于测序的转录组学相结合,有可能为乳腺癌和前列腺癌患者的个性化放射治疗实践提供依据。