Ovarian cancer (OC) remains the leading cause of cancer-related deaths among women, often diagnosed at advanced stages due to the lack of effective early diagnostic procedures. To reduce the high mortality rates in OC, reliable biomarkers are urgently needed, especially to detect OC at its earliest stage, predict specific drug responses, and monitor patients. The cytokine interleukin-6 (IL6) is associated with low survival rates, treatment resistance, and recurrence. In this review, we summarize the role of IL6 in inflammation and how IL6 contributes to ovarian tumorigenesis within the tumor microenvironment, influencing whether the tumor is subsequently classified as “hot” or “cold”. We further dissect the molecular and cellular mechanisms through which IL6 production and downstream signaling are regulated, to enhance our understanding of its involvement in OC development, as well as OC resistance to treatment. We highlight the potential of IL6 to be used as a reliable diagnostic biomarker to help detect OC at its earliest stage, and as a part of predictive and prognostic signatures to improve OC management. We further discuss ways to leverage artificial intelligence and machine learning to integrate IL6 into diverse biomarker-based strategies.
卵巢癌（OC）仍是女性癌症相关死亡的主要原因，由于缺乏有效的早期诊断手段，该疾病常在晚期才被确诊。为降低卵巢癌的高死亡率，亟需寻找可靠的生物标志物，尤其是在卵巢癌最早期阶段进行检测、预测特定药物反应以及监测患者病情。细胞因子白细胞介素-6（IL6）与低生存率、治疗耐药及复发密切相关。本综述总结了IL6在炎症中的作用，并阐释了IL6如何在肿瘤微环境中促进卵巢肿瘤发生，进而影响肿瘤被归类为“热肿瘤”或“冷肿瘤”。我们进一步剖析了IL6产生及其下游信号传导的分子与细胞调控机制，以深化对其参与卵巢癌发展及治疗耐药过程的理解。我们重点探讨了IL6作为可靠诊断标志物的潜力——既可用于早期卵巢癌检测，也可作为预测和预后特征谱的组成部分以改善卵巢癌临床管理。此外，我们还讨论了如何利用人工智能和机器学习技术，将IL6整合到基于多种生物标志物的诊疗策略中。
肿瘤(癌症)患者之家