Department of Radiation Oncology, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital, Yunnan Cancer Center), 519 Kunzhou Road, Kunming, 650118, China.
Department of Radiology, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital, Yunnan Cancer Center), 519 Kunzhou Road, Kunming, 650118, China.
J Transl Med. 2024 Oct 28;22(1):972. doi: 10.1186/s12967-024-05774-8.
We aimed to determine the potential predictive value of the intra-tumoral microbiome as a marker of the response to external beam radiation therapy (EBRT) in cervical cancer (CC).
A prospective longitudinal trial of 36 CC patients receiving pelvic radiotherapy was designed to investigate microbial characteristic signatures and diversity (alpha and beta) of multiple sites (tumor, vaginal, gut, urethral, and oral) in the superior response (SR) and inferior response (IR) groups of CC patients by 16S rRNA sequencing. Utilized the least absolute shrinkage and selection operator (LASSO) logistic regression method to analyze clinicopathological factors that potentially influenced the efficacy of EBRT. LEfSe analysis highlighted the microbiome features that best distinguished the categorized patient samples. Selected parameters were validated with Spearman correlation analysis, receiver operating characteristic (ROC) area under the curve (AUC) analysis and Kaplan-Meier survival analysis.
Firstly, in our cohort, LASSO logistic regression analysis revealed no association between clinicopathological factors and EBRT efficacy. Subsequently, we employed 16S rRNA sequencing to compare microbiome differences across multiple sites and their correlations with major clinicopathological factors. We discovered that the intra-tumoral microbiome was independent of clinicopathologic features and represented the most direct and reliable reflection of the microbial differences between the SR and IR groups. We found lower alpha diversity in the tumor microbiome of SR group and identified the most relevant microbiome taxa (Bifidobacteriaceae, Beijerinckiaceae, and Orbaceae) associated with the efficacy of the response to EBRT in CC patients. We then conducted ROC analysis, finding that specific microbial taxa had an AUC of 0.831 (95% CI, 0.667-0.995), indicating the potential of these taxa as biomarkers for predicting EBRT efficacy. Kaplan-Meier survival analysis showed a better prognosis for patients with lower alpha diversity and higher relative abundance of Bifidobacteriaceae.
Our data suggested that intra-tumoral specific microbiome taxa and lower alpha diversity may play an important role in the CC patient sensitivity to EBRT and offer novel potential biomarkers for predicting the response to EBRT efficacy.
本研究旨在探讨宫颈癌（CC）患者肿瘤内微生物组作为对外照射放射治疗（EBRT）反应的潜在预测标志物的价值。
我们设计了一项前瞻性纵向试验，纳入 36 例接受盆腔放疗的 CC 患者，通过 16S rRNA 测序，研究肿瘤、阴道、肠道、尿道和口腔等多个部位（肿瘤、阴道、肠道、尿道和口腔）的微生物特征和多样性（α和β）在 CC 患者的上反应（SR）和下反应（IR）组中的变化。采用最小绝对收缩和选择算子（LASSO）逻辑回归方法分析可能影响 EBRT 疗效的临床病理因素。LEfSe 分析突出了区分分类患者样本的最佳微生物组特征。选择的参数通过 Spearman 相关分析、受试者工作特征（ROC）曲线下面积（AUC）分析和 Kaplan-Meier 生存分析进行验证。
首先，在我们的队列中，LASSO 逻辑回归分析未发现临床病理因素与 EBRT 疗效之间存在相关性。随后，我们采用 16S rRNA 测序比较了多个部位的微生物组差异及其与主要临床病理因素的相关性。我们发现肿瘤内微生物组与临床病理特征无关，是 SR 和 IR 组之间微生物差异最直接、最可靠的反映。我们发现 SR 组肿瘤微生物组的α多样性较低，并确定了与 CC 患者对 EBRT 反应疗效最相关的微生物类群（双歧杆菌科、贝日阿托氏菌科和 Orbaceae）。然后，我们进行了 ROC 分析，发现特定的微生物类群具有 0.831 的 AUC（95%CI，0.667-0.995），表明这些类群具有作为预测 EBRT 疗效的生物标志物的潜力。Kaplan-Meier 生存分析显示，α多样性较低且双歧杆菌科相对丰度较高的患者预后更好。
我们的数据表明，肿瘤内特定的微生物类群和较低的α多样性可能在 CC 患者对 EBRT 的敏感性中发挥重要作用，并为预测 EBRT 疗效提供了新的潜在生物标志物。
