Table_2_Gene Panel of Persister Cells as a Prognostic Indicator for Tumor Repopulation After Radiation.xlsx

Tumor repopulation during cycles of radiotherapy limits the radio-response in ensuing cycles and causes failure of treatment. It is thus of vital importance to unveil the mechanisms underlying tumor repopulating cells. Increasing evidence suggests that a subpopulation of drug-tolerant persister cancer cells (DTPs) could survive the cytotoxic treatment and resume to propagate. Whether these persister cells contribute to development of radio-resistance remains elusive. Based on the genetic profiling of DTPs by integrating datasets from Gene Expression Omnibus database, this study aimed to provide novel insights into tumor-repopulation mediated radio-resistance and identify predictive biomarkers for radio-response in clinic. A prognostic risk index, grounded on four persister genes (LYNX1, SYNPO, GADD45B, and PDLIM1), was constructed in non-small-cell lung cancer patients from The Cancer Genome Atlas Program (TCGA) using stepwise Cox regression analysis. Weighted gene co-expression network analysis further confirmed the interaction among persister-gene based risk score, radio-response and overall survival time. In addition, the predictive role of risk index was validated in vitro and in other types of TCGA patients. Gene set enrichment analysis was performed to decipher the possible biological signaling, which indicated that two forces behind persister cells, stress response and survival adaptation, might fuel the tumor repopulation after radiation. Targeting these persister cells may represent a new prognostic and therapeutic approach to enhance radio-response and prevent radio-resistance induced by tumor repopulation.

放疗周期中的肿瘤再增殖会限制后续疗程的放射响应，并导致治疗失败。因此，阐明肿瘤再增殖细胞背后的作用机制至关重要。越来越多的证据表明，一类药物耐受性持久癌细胞（drug-tolerant persister cancer cells, DTPs）亚群可在细胞毒性治疗后存活并恢复增殖。然而此类持久细胞是否参与放射抗性的形成仍未明确。本研究通过整合基因表达综合数据库（Gene Expression Omnibus, GEO）中的数据集对DTPs进行遗传特征分析，旨在为肿瘤再增殖介导的放射抗性提供新见解，并筛选可用于临床放射敏感性预测的生物标志物。本研究依托逐步Cox回归分析，在来自癌症基因组图谱计划（The Cancer Genome Atlas Program, TCGA）的非小细胞肺癌患者队列中，基于4个持久细胞相关基因（LYNX1、SYNPO、GADD45B及PDLIM1）构建了预后风险指数。加权基因共表达网络分析进一步验证了基于持久细胞基因的风险评分与放射响应、总生存时间之间的关联。此外，该风险指数的预测性能在体外实验及其他TCGA队列患者中得到了验证。通过基因集富集分析解析潜在的生物学信号通路，结果显示持久细胞背后的两大驱动因素——应激反应与存活适应——可能促进放疗后的肿瘤再增殖。靶向此类持久细胞或可成为提升放射敏感性、预防肿瘤再增殖诱导的放射抗性的新型预后评估与治疗策略。