Shi Peiqin, Zhang Wenwen, Yao Qingqing, Yuan Zhanna, Wang Jiaqi, Yang Ziye, Qu Pengpeng
Clinical School of Obstetrics and Gynecology Center, Tianjin Medical University, Tianjin, China.
Tianjin Institute of Gynecology Obstetrics, Tianjin Central Hospital of Gynecology Obstetrics, Tianjin, China.
Front Oncol. 2025 Aug 27;15:1547529. doi: 10.3389/fonc.2025.1547529. eCollection 2025.
The tumor microenvironment (TME) plays a crucial role in cancer progression but its complex structure significant variability among patients present considerable challenges for research. Recent studies have demonstrated that macrophage polarization states defined by the expression levels of CXCL9 SPP1 (CS Ratio) are more prognostically relevant than traditional M1/M2 markers. The CS polarization state reflects a highly coordinated network of pro-tumor anti-tumor variables offering a simplified yet effective immune response indicator for the complex TME. The CS Ratio has been shown to correlate with the abundance of anti-tumor immune cells the gene expression programs of tumor-infiltrating cells responses to immunotherapy. Cervical cancer, one of the most common gynecological malignancies, still faces limited therapeutic options. CXCL9, a member of the CXC chemokine family, plays a critical role in immune regulation, inflammation, tumor growth, angiogenesis, and metastasis. Similarly, SPP1, a cytokine, influences immune-related pathways by regulating molecules such as interferon-γ and interleukin-12. However, no studies have systematically investigated the role of the CS Ratio in cervical cancer or its relationship with immunotherapy characteristics. Research in this area could provide critical insights into the role and clinical potential of the CS Ratio in cervical cancer and related tumors.
The expression ratio of CXCL9 to SPP1 was analyzed in cervical cancer patients using data from the Gene Expression Omnibus (GEO) database, which revealed significant differences. Data for cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. The optimal cutoff value for the CS Ratio was determined using the maxstat package in R, and Kaplan-Meier (KM) survival curves were constructed. Patients were categorized into High and Low groups based on the median CS Ratio. Immune scores were analyzed, and immune cell infiltration was assessed using CIBERSORT. Differences in the CS Ratio were evaluated across patients with varying pathological T stages and FIGO stages. Additionally, receiver operating characteristic (ROC) analysis was performed using the pROC package in R to calculate the area under the curve (AUC). Univariate and multivariate Cox regression analyses were performed to evaluate the potential of the CS Ratio as an independent prognostic factor in cervical cancer. A Cox regression-based nomogram integrating four key features was subsequently developed for the TCGA-CESC cohort. Nomogram performance was assessed using calibration curves and ROC analysis.
The CS Ratio was significantly lower in cervical cancer patients compared to normal controls (P < 0.05). KM survival curves indicated that patients in the CS High group exhibited better prognoses. Immune score analysis revealed significantly higher immune scores (P < 0.05) and lower tumor purity (P < 0.05)in the CS High group compared to the Low group. CIBERSORT analysis revealed significantly higher proportions of CD8+ T cells (P < 0.05) and M1 macrophages (P < 0.05), and a significantly lower proportion of M2 macrophages (P < 0.05), in the CS High group compared to the Low group. The CS Ratio significantly decreased with advancing FIGO stage (P < 0.05). Both univariate (P < 0.05) and multivariate Cox regression analyses (P < 0.05) confirmed the CS Ratio as an independent prognostic factor. ROC analysis demonstrated that the CS Ratio had higher AUC values for predicting 1-year (AUC=0.69), 3-year (AUC=0.66), and 5-year OS (AUC=0.68) than CXCL9 or SPP1 alone. The Cox regression-based nomogram integrating four key features demonstrated predictive capability for 1-, 3-, and 5-year OS in CESC patients (Concordance Index = 0.751; 95% CI: 0.678-0.824; p = 1.50Í10-11). Significant survival differences were observed between the high-risk and low-risk groups based on the nomogram score. ROC analysis yielded high AUC values for survival prediction: 0.85 (95% CI: 0.94-0.75) at 1-year, 0.74 (95% CI:0.84-0.64) at 3-year, and 0.72 (95% CI:0.84-0.61) at 5-year.
The CS Ratio may serve as a more effective prognostic biomarker for cervical cancer patients.
肿瘤微环境（TME）在癌症进展中起关键作用，但其复杂结构以及患者间的显著变异性给研究带来了巨大挑战。最近的研究表明，由CXCL9与SPP1表达水平定义的巨噬细胞极化状态（CS比值）比传统的M1/M2标志物更具预后相关性。CS极化状态反映了一个高度协调的促肿瘤和抗肿瘤变量网络，为复杂的肿瘤微环境提供了一个简化而有效的免疫反应指标。CS比值已被证明与抗肿瘤免疫细胞的丰度、肿瘤浸润细胞的基因表达程序以及免疫治疗反应相关。宫颈癌是最常见的妇科恶性肿瘤之一，其治疗选择仍然有限。CXCL9是CXC趋化因子家族的成员，在免疫调节、炎症、肿瘤生长、血管生成和转移中起关键作用。同样，细胞因子SPP1通过调节干扰素-γ和白细胞介素-12等分子影响免疫相关途径。然而，尚无研究系统地探讨CS比值在宫颈癌中的作用或其与免疫治疗特征的关系。该领域的研究可为CS比值在宫颈癌及相关肿瘤中的作用和临床潜力提供关键见解。
利用基因表达综合数据库（GEO）的数据，分析宫颈癌患者中CXCL9与SPP1的表达比值，结果显示存在显著差异。宫颈癌患者的数据来自癌症基因组图谱（TCGA）数据库。使用R语言中的maxstat软件包确定CS比值的最佳临界值，并构建Kaplan-Meier（KM）生存曲线。根据CS比值的中位数将患者分为高分组和低分组。分析免疫评分，并使用CIBERSORT评估免疫细胞浸润情况。评估不同病理T分期和国际妇产科联盟（FIGO）分期患者的CS比值差异。此外，使用R语言中的pROC软件包进行受试者操作特征（ROC）分析，以计算曲线下面积（AUC）。进行单因素和多因素Cox回归分析，以评估CS比值作为宫颈癌独立预后因素的潜力。随后为TCGA-CESC队列开发了一个基于Cox回归的列线图，整合了四个关键特征。使用校准曲线和ROC分析评估列线图的性能。
与正常对照组相比，宫颈癌患者的CS比值显著降低（P < 0.05）。KM生存曲线表明，CS高分组患者的预后更好。免疫评分分析显示，与低分组相比，CS高分组的免疫评分显著更高（P < 0.05），肿瘤纯度显著更低（P < 0.05）。CIBERSORT分析显示，与低分组相比，CS高分组中CD8 + T细胞比例显著更高（P < 0.05），M1巨噬细胞比例显著更高（P < 0.05），M2巨噬细胞比例显著更低（P < 0.05）。随着FIGO分期的进展，CS比值显著降低（P < 0.05）。单因素（P < 0.05）和多因素Cox回归分析（P < 0.05）均证实CS比值是一个独立的预后因素。ROC分析表明，与单独的CXCL9或SPP1相比，CS比值在预测1年（AUC = 0.69）、3年（AUC = 0.66）和5年总生存期（AUC = 0.68）方面具有更高的AUC值。基于Cox回归的列线图整合四个关键特征，对CESC患者的1年、3年和5年总生存期具有预测能力（一致性指数 = 0.751；95%置信区间：0.678 - 0.824；p = 1.50×10 - 11）。根据列线图评分，高风险组和低风险组之间存在显著的生存差异。ROC分析在生存预测方面产生了较高的AUC值：1年时为0.85（95%置信区间：0.94 - 0.75），3年时为0.74（95%置信区间：0.84 - 0.64），5年时为0.72（95%置信区间：0.84 - 0.61）。
CS比值可能是宫颈癌患者更有效的预后生物标志物。
