PO.CL05.13 · 临床研究
24,000 多项免疫肿瘤学试验中生物标志物应用的时间趋势
Temporal trends in biomarker utilization across 24,000+ immuno-oncology trials
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
随着免疫肿瘤学(IO)超越检查点抑制剂时代而日趋成熟,理解生物标志物指导的试验设计如何随治疗手段的多样化而演变,对于优化未来的研发决策至关重要。癌症研究所(CRI)建立了一个全面的 IO 临床试验数据库,涵盖了跨癌症类型和治疗模式的全球活动 [1]。在此,我们利用这一资源分析 IO 治疗开发和生物标志物采用的时间趋势,以揭示该领域随时间的演变方式。
我们整理了超过 24,000 项干预性 IO 临床试验(数据截止:2025 年 6 月),提取了治疗模式、分子靶点、癌症适应症、试验分期、申办方类型和生物标志物数据。我们分析了试验启动、模式和生物标志物使用的时间趋势。生物标志物(n=9,849)按分子类型、功能作用和适应症特异性使用模式进行分类。
IO 格局显示出明显的成熟,目前有超过 10,000 项活跃试验,以 II 期研究为主。虽然检查点抑制剂仍占主导地位,但 IO 药物靶点的多样性显著增加,这主要由旨在克服耐药的多靶点联合所驱动。此外,生物标志物策略在不同癌症类型之间显示出显著差异。血液系统恶性肿瘤在生物标志物使用方面领先,采用率约为 65%,双重选择/监测使用率为 31%,相比之下实体瘤分别为 58% 和 23%。在实体瘤中,呼吸系统癌症的采用率最高,约为 66%,由 PD-L1 和驱动突变等成熟标志物所驱动,而胃肠道癌症尽管代表最大的试验量却落后于约 50%。蛋白质生物标志物占总数的 80% 以上,占主导地位,肿瘤突变负荷和微卫星不稳定性标志物正成为泛癌种标准。值得注意的是,2024 年生物标志物使用率自 2012 年以来首次降至 50% 以下。这可能反映了该领域策略的转变:在追求更广泛患者人群的同时,也为特定适应症开发更智能的多标志物方法,代表了 IO 开发中的一个重要转折点。
更新后的 CRI IO 格局数据库整合了全球 IO 临床试验活动和生物标志物应用,为研究界提供了一个独特的视角,了解免疫疗法如何演变,帮助研究者和申办方看清自身工作在大局中的定位,发现新兴趋势,并识别生物标志物开发未能跟上新疗法步伐的领域。这些格局洞见对于就在何处投入资源和精力以产生最大患者影响做出更明智的决策具有重要意义。
参考文献 1. Benthani F, Upadhaya S, Zhou A. Cancer cell therapies: Global clinical trial trends and emerging directions. Nature Reviews Drug Discovery.
查看英文原文 English abstract
As immuno-oncology (IO) matures beyond the checkpoint inhibitor era, understanding how biomarker-informed trial design is evolving along with therapeutic diversification is important for optimizing future development decisions. The Cancer Research Institute (CRI) has built a comprehensive IO clinical trial database, capturing global activity across cancer types and therapeutic modalities [1]. Here, we leveraged this resource to analyze temporal trends in IO therapeutic development and biomarker adoption to reveal how the field is evolving over time.
We curated over 24,000 interventional IO clinical trials (data cut-off: June 2025), extracting therapeutic modality, molecular targets, cancer indication, trial phase, sponsor type, and biomarker data. We analyzed temporal trends in trial initiation, modality, and biomarker usage. Biomarkers (n=9,849) were classified by molecular type, functional role, and indication-specific usage patterns.
The IO landscape shows clear maturation with over 10,000 currently active trials dominated by phase II studies. While checkpoint inhibitors remain dominant, IO drug target diversity has significantly increased, driven primarily by multi-target combinations designed to overcome resistance. Furthermore, biomarker strategies show striking differences across cancer types. Hematologic malignancies lead in biomarker usage, with about 65% adoption and 31% dual selection/monitoring use, compared to solid tumors (58% and 23% respectively). Among solid tumors, respiratory cancers show the highest adoption at around 66%, driven by established markers like PD-L1 and driver mutations, while gastrointestinal cancers lag at about 50% despite representing the largest trial volume. Protein biomarkers dominate at over 80% of total, with tumor mutational burden and microsatellite instability markers emerging as pan-cancer standards. Notably, biomarker usage dropped below 50% in 2024 for the first time since 2012. This may reflect how the field's strategy is shifting: pursuing broader patient populations while also developing smarter multi-marker approaches for specific indications, representing an important turning point in IO development.
The updated CRI IO landscape database, which integrates global IO clinical trial activity and biomarker utilization, gives the research community a unique look into how immunotherapy is evolving, helping investigators and sponsors see where their work fits in the bigger picture, spot emerging trends, and identify areas where biomarker development hasn't kept pace with new therapies. These landscape insights are important for making better decisions about where to invest resources and effort to have the greatest patient impact.
Reference 1. Benthani F, Upadhaya S, Zhou A. Cancer cell therapies: Global clinical trial trends and emerging directions. Nature Reviews Drug Discovery.
利益披露 Disclosure
F. Benthani, None..
S. Upadhaya, None..
C. L. Neben, None..
K. R. McDonald, None..
A. Y. Zhou, None.