Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer.

IF 3.5 3区 医学 Q2 ONCOLOGY
Frontiers in Oncology Pub Date : 2025-03-25 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1439516
Jianguang Lin, Hainan Yang, Rongfu Huang, Tianwen Xu
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Abstract

Purpose: Radiotherapy is a cornerstone of breast cancer (BRCA) treatment. Accurately predicting tumor radiosensitivity is critical for optimizing therapeutic outcomes and personalizing treatment strategies. DNA repair pathways are key determinants of radiotherapy response. Thus, we aimed to develop a novel DNA repair-related radiosensitivity model and to identify potential targets for enhancing radiotherapy efficacy.

Methods: A retrospective study was conducted using data from 942 BRCA patients from TCGA database. A radiosensitivity model, comprising a radiosensitivity index, was developed using LASSO regression analysis. Patients were stratified into radiosensitive (RS) and radioresistant (RR) groups based on their radiosensitivity index (RSI). Associations between the RSI, clinicopathological parameters, and PD-L1 status were analyzed. The CIBERSORT and ESTIMATE algorithms were employed to characterize the immune landscape of the tumor microenvironment. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and pRRophetic platform were used to predict treatment responses. Key genes identified in the radiosensitivity model were further validated using in vitro qRT-PCR experiments.

Results: We successfully constructed a radiosensitivity index incorporating 10 DNA repair-related genes. Patients in the RS group exhibited significantly better prognosis compared to the RR group, but this benefit was limited to those receiving radiotherapy. This survival benefit associated with the radiosensitivity signature was absent in patients who did not receive radiotherapy. The RS group displayed a distinct molecular profile characterized by enrichment of TGF-β signaling and protein secretion pathways, potentially contributing to enhanced radiosensitivity. Furthermore, the RS group exhibited increased infiltration of immune cells. Notably, the RS-PD-L1-high subgroup demonstrated the most favorable survival outcomes and highest immune cell infiltration, highlighting their potential responsiveness to immunotherapy. In addition, the RR group exhibited a distinct profile characterized by enrichment of DNA repair pathways and a heightened sensitivity to CDK and HER2 inhibitors. Conversely, this group displayed resistance to DNA-damaging drugs. These findings were supported by in vitro experiments using MCF-7 and radioresistant MCF-7/IR cell lines, confirming differential expression of key radiosensitivity index genes.

Conclusion: In conclusion, we established a radiosensitivity model for predicting radiotherapy benefit in breast cancer. Our study reveals a strong association between radiosensitivity, enhanced antitumor immunity, and potential immunotherapy benefit, particularly within the RS-PD-L1-high subgroup.

预测乳腺癌放疗疗效的DNA修复相关放射敏感性指数的发现。
目的:放疗是乳腺癌(BRCA)治疗的基石。准确预测肿瘤放射敏感性对于优化治疗结果和个性化治疗策略至关重要。DNA修复途径是放疗反应的关键决定因素。因此,我们的目标是建立一个新的DNA修复相关的放射敏感性模型,并确定潜在的靶点,以提高放疗疗效。方法:采用TCGA数据库942例BRCA患者资料进行回顾性研究。利用LASSO回归分析,建立了包含放射敏感性指数的放射敏感性模型。根据患者的放射敏感性指数(RSI)将患者分为放射敏感组(RS)和放射耐药组(RR)。分析RSI、临床病理参数和PD-L1状态之间的关系。采用CIBERSORT和ESTIMATE算法表征肿瘤微环境的免疫景观。使用肿瘤免疫功能障碍和排斥(TIDE)算法和prophytic平台预测治疗反应。通过体外qRT-PCR实验进一步验证放射敏感性模型中鉴定的关键基因。结果:成功构建了包含10个DNA修复相关基因的放射敏感性指数。与RR组相比,RS组患者的预后明显更好,但这种益处仅限于接受放疗的患者。这种与放射敏感性特征相关的生存获益在未接受放疗的患者中不存在。RS组表现出独特的分子特征,其特征是TGF-β信号和蛋白质分泌途径的富集,可能有助于增强放射敏感性。此外,RS组免疫细胞浸润增加。值得注意的是,rs - pd - l1高亚组表现出最有利的生存结果和最高的免疫细胞浸润,突出了他们对免疫治疗的潜在反应性。此外,RR组表现出独特的特征,其特征是DNA修复途径的富集以及对CDK和HER2抑制剂的敏感性提高。相反,这一组表现出对dna损伤药物的抵抗力。这些发现得到了MCF-7和耐辐射MCF-7/IR细胞系的体外实验的支持,证实了关键放射敏感性指数基因的差异表达。结论:建立了预测乳腺癌放疗疗效的放射敏感性模型。我们的研究揭示了放射敏感性、增强的抗肿瘤免疫和潜在的免疫治疗益处之间的密切联系,特别是在rs - pd - l1高亚组中。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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