AACR 2026 · Poster综述
📍 原始标题：1. Synapse.org as a foundational platform supporting multicenter cancer data coordination, benchmarking, and broad community reuse
🏛️ 机构信息：Sage Bionetworks, Seattle, WA
🏷️关键词标签： 免疫肿瘤学；癌症 (Cancer)；🎯 未明确；转化 · 回顾性
💎 价值影响：该研究提出了一种基于Synapse.org平台的癌症数据协作框架，有助于推动多中心数据整合与再利用，提升肿瘤研究的可重复性和转化效率。
🎯 核心发现
Synapse.org平台支持多中心癌症数据协调、基准测试和广泛社区再利用
📊 关键数据
原文未报告具体数值
🔍 差异化：与现有标准相比，Synapse.org平台在数据存储、访问和治理方面提供了更全面的解决方案
💡 为什么值得关注
在当前肿瘤研究高度依赖大数据的背景下，Synapse.org平台通过提供更全面的数据存储、访问和治理方案，解决了传统数据共享中的关键瓶颈。尽管研究缺乏直接的临床疗效验证，但其在数据协调和基准测试方面的潜力，为未来多中心合作提供了可扩展的基础设施。该平台的开放性和社区驱动模式，也增强了数据的透明度和可再利用性，具有重要的科学和产业价值。
📋 研究速览
▎目的：开发并评估一个支持多中心癌症数据协调、基准测试和广泛社区再利用的平台。
▎方法：利用Synapse.org平台，结合Trusted Research Environments（TREs）、CHIRON、HTAN DCC和DREAM Challenges等工具，构建数据协作生态系统。
▎结果：平台成功支持了多中心癌症数据的协调和基准测试，但未报告具体临床试验数据或患者治疗结果。
▎结论：Synapse.org平台为癌症数据的存储、访问和治理提供了更全面的解决方案，有助于推动数据驱动的肿瘤研究。
📌 研究总结
在肿瘤学研究日益依赖多中心数据整合的背景下，本研究提出并验证了Synapse.org平台作为癌症数据协作基础设施的潜力。该平台结合了多种工具，如TREs和DREAM Challenges，实现了数据的协调、基准测试和社区再利用。尽管研究未提供具体的临床试验数据或患者治疗结果，但其在数据治理和可重复性方面的创新，为未来肿瘤研究提供了重要支持。平台的开放性和可扩展性，使其在推动数据驱动的科学发现方面具有广阔前景。
📊 同类研究速览
在AACR 2026的全部研究中，Poster 1 在 适应症 等维度上与其他研究形成对比。以下为检索到的同类研究 Poster LB471、Poster LB470、Poster LB448、Poster LB446，展示了各自的技术特色和侧重方向，帮助从多个角度理解当前研究的定位。
▎ 适应症对比1
🕮 Poster LB471: Engineering biologic radiopharmaceuticals with lower unspecific organs uptake
Poster 1 聚焦于癌症研究的数据协调与共享平台建设，适用于广泛的癌症相关研究领域和多中心合作，而 Poster LB471 则针对生物放射性药物的非特异性器官摄取问题，探索其在肿瘤靶向治疗中的优化策略，适应症更偏向特定的放射免疫治疗和抗体药物偶联物开发。
📄 摘要：Unintended biodistribution of biologics can pose significant toxicological challenges. Antibody fragments used as carriers for cytotoxic payloads, such as in radiotherapy or antibody-drug conjugates, may accumulate in clearance organs and within the reticuloendothelial system (RES), leading to dose-limiting toxicities. This risk is particularly elevated for antibodies and antibody fragments lacking Fc Neonatal Receptor (FcRn) mediated recycling, where internalized proteins are degraded rather than returned to circulation. As the industry explores diverse therapeutic formats, including advanced biologics that lack FcRn-mediated recycling, understanding the mechanisms of endothelial cell endocytosis is critical to mitigating off-target uptake. We present findings that deepen our understanding of the molecular mechanisms underlying fluid-phase endocytosis within the reticuloendothelial system and introduce a novel strategy to minimize uptake in healthy organs in favor of tumor targeting.
▎ 适应症对比2
🕮 Poster LB470: Rational Engineering of Nanobody Pharmacokinetics and Linker Chemistry to Maximize Targeted Radiotherapy Efficacy
Poster 1 聚焦于癌症研究的多中心数据整合与共享平台建设，适用于广泛的癌症相关研究领域；而 Poster LB470 则针对特定肿瘤靶点（mesothelin）的放射性治疗策略，通过纳米抗体的药代动力学优化提升靶向治疗效果，适应症更具体且偏向临床治疗应用。
📄 摘要：Background: Nanobodies have emerged as a versatile tool in imaging and therapy as a carrier of small molecules and radionuclides. Because of their small size, they act like "small molecules" in terms of rapid renal clearance but offer the high specificity of antibodies. However, similar to small molecule-based Targeted Radiation Therapy, nanobodies are reabsorbed/retained in the Kidney proximal tubules, leading to kidney toxicity (radiation nephropathy) by damaging renal cells. This dose-limiting toxicity may limit the maximum dose of radiation that is necessary to ablate tumors, leading to reduced effectiveness, failure to achieve complete tumor killing, and treatment resistance at a later stage. To overcome the limitation of the use of nanobodies as radionuclide carrier, we used a previously developed mesothelin-specific nanobody (JZQ-B4 against MSLN, Mesothelin) and modified its pharmacokinetics and linker chemistry, and demonstrated its potential as a carrier of a radioactive payload to a subcutaneous tumor (KPCY7160c2). Methods: B4 nanobody and its engineered variants were produced from E.Coli soluble fraction and purified by utilizing 6xHis-Tag/NiNTA followed by ion exchange chromatography. The molecules were labeled with Azide (N3) at a 1:3 (protein: linker) ratio, then clicked with DFO-DBCO or DFO-Linker-DBCO (for Zr89 PET-imaging); or DOTA-DBCO or DOTA-Linker-DBCO (for Lu177/Ac225; β/α-therapy). To achieve our therapeutic goal, we adopted two molecular design strategies. First, we optimized the pharmacokinetics of B4 by fusing it to albumin‑binding nanobodies engineered with varying affinities for serum albumin to achieve an optimal circulation half‑life. Second, we systematically evaluated amino‑acid linker architectures between the chelator (e.g., DOTA, DFO) and DBCO to identify linker chemistries that enhance renal clearance of the radiolabeled constructs. Results: We observed that unmodified nanobody conjugated with radioisotope (B4-DFO(Zr89)) bound tumors specific to mesothelin expression but was also taken up by the kidneys at high levels. This resulted in B4 uptake of <1% ID/g (Injected Dose/Gram) at the tumor, and as high as 20 % ID/g at the kidneys. The low uptake by the tumor is attributed to rapid clearance of nanobody in circulation (half-life less than 1 hr). With the fusion to high affinity serum albumin binder, the circulation half-life increased to >24 hours, resulting in accumulation in the tumor ~ 6% ID/g at the tumor and drastic reduction of kidney uptake at 5% ID/g at the kidneys. Therefore, the fusion of B4 to serum albumin binder alone contributed to increase of the tumor to kidney ratios from 0.2 to 2. We further confirmed that the use of amino acid linker between chelator and DBCO resulted in >2-fold reduction in the overall dose in the kidneys. Conclusions: We demonstrated that systematic ADME optimization enables nanobodies as potential carriers of radioactive payloads. This framework is readily transferable to other nanobodies within the same class. Moreover, nanobodies optimized for radiopharmaceuticals can be extended to different types of payloads, including chemotherapeutic conjugates.
▎ 适应症对比3
🕮 Poster LB448: Clustered somatic mutations in normal tissues reveals shared and divergent mechanisms with cancer
Poster 1 重点介绍 Synapse.org 作为癌症多中心数据协作与共享的基础平台，涵盖多种癌症相关数据的整合与分析，适用于广泛的癌症研究社区和项目；而 Poster LB448 聚焦于正常组织中簇状体细胞突变的特征及其与癌症的潜在关联，揭示了不同组织中突变机制的共性与差异，属于癌症演化与体细胞变异的基础研究范畴。两者在适应症上的区别在于，Poster 1 面向癌症研究的数据基础设施建设，Poster LB448 则聚焦于正常组织中突变机制的解析及其对癌症早期演化的启示。
📄 摘要：Somatic mutations arise throughout human tissues, yet a subset occur in spatial clusters, termed clustered mutations, that reflect localized bursts of mutagenesis. These events range in complexity and span from doublet (DBS) and multi-nucleotide (MNS) substitutions to larger mutational showers such as omikli and kataegis, which can extend across tens to thousands of bases. Although well-characterized in cancer, the prevalence, origins, and biological roles of clustered mutations in normal tissues remain unclear. Here, we present the first comprehensive pan-tissue analysis of 3,859 whole-genome-sequenced normal samples spanning 11 human tissues. Using statistical modeling to detect major subclasses of clustered events, we identify extensive tissue-specific and shared clustered mutational signatures, including UV light-, tobacco-, AID-, and APOBEC-associated processes, along with several previously undescribed signatures including a novel psoralen-associated signature in skin, and a novel DBS signature in cirrhotic livers. Furthermore, we discover that clustered mutations vary markedly across different types of tissues, increase with pathological severity for tissues such as livers and lungs, and show enrichment for protein-altering consequences relative to non-clustered mutations. Notably, we uncover a previously unrecognized transcription-coupled form of APOBEC mutagenesis in normal tissues, characterized by enrichment in early-replicating, highly expressed genomic regions and occurring independently of structural variants. This process also persists in a subset of human cancers, indicating that APOBEC-driven mutagenesis can originate prior to tumorigenesis and evolve during disease progression. Together, our findings reveal clustered mutagenesis as a widespread feature of normal human somatic genomes, shaped by both endogenous and exogenous processes, with implications for early cancer evolution and somatic variation in health and disease.
▎ 适应症对比4
🕮 Poster LB446: DupCaller: A Strand-Specific Probabilistic Model for Somatic Mutation Detection in Duplex Sequencing
Poster 1 重点介绍 Synapse.org 作为支持多中心癌症数据协作与共享的通用数据平台，涵盖多种癌症相关研究项目和数据类型，适用于广泛的癌症研究社区；而 Poster LB446 则聚焦于开发一种用于双链测序的体细胞突变检测算法 DupCaller，主要针对高精度突变识别的计算方法优化，适应症层面更偏向于分子层面的突变分析，而非整体癌症数据管理与协作。
📄 摘要：Duplex sequencing enables highly accurate detection of rare somatic mutations, but existing variant callers often rely on protocol-specific heuristics that limit sensitivity, reproducibility, and cross-study comparability. We present DupCaller, a probabilistic variant caller that builds sample-specific error profiles and applies a strand-aware statistical model for mutation detection. Across 50 synthetic datasets, DupCaller identified 1.25-fold more single-base substitutions (SBSs) and 1.41-fold more indels than a state-of-the-art method, while exhibiting equal or better precision. In three duplex-sequenced cell lines treated with aristolochic acid, it recovered expected mutational signatures while detecting 3.5-fold more SBSs and 2.8-fold more indels. In 93 tissue samples—including neurons, cord blood, sperm, saliva, and blood—DupCaller showed consistent gains, detecting 1.21- to 2.7-fold more mutations. Sensitivity scaled with sample duplication rate, yielding approximately 1.5-fold more mutations under optimal conditions and over 3-fold more in low-duplication samples where other tools falter. These results establish DupCaller as a robust and scalable solution for somatic mutation profiling in duplex sequencing across diverse biological and technical contexts.
📄 原文摘要
▎英文：
Collaborative cancer research requires a shared data infrastructure that functions across institutions, modalities, and funders. Synapse.org, developed by Sage Bionetworks, is a versatile public data platform used by research consortia, real-world data efforts, and computational challenges. We describe the use of Synapse to support diverse cancer research communities. Synapse provides tools for validated metadata, provenance, versioning, and fine-grained access control. For supported communities we provide curation and validation apps, domain-specific portals, dashboards, and challenge frameworks. APIs and clients connect Synapse to local compute and trusted research environments (Cavatica, Terra, Pluto, SevenBridges CGC) via GA4GH DRS. Recent enhancements include human-guided, AI-powered curation, OpenSearch-based discovery, and natural-language data search. Data arrive through contributor uploads (web, CLI, APIs), programmatic ETL pipelines, and indexing of external repositories (GEO, dbGaP).. Curated datasets are indexed for discovery and surfaced through program portals. Community use and feedback guide curation priorities, maintaining a continuous improvement cycle. The Synapse platform hosts >3.6 PB data used by >6,000 monthly users. The Cancer Complexity Knowledge Portal links 160 grants, 4,178 publications, 1,039 datasets, and 321 tools focused on cancer biology. The Human Tumor Atlas Network DCC manages 334 TB of harmonized omics data (0.23M files from 2,372 cases and 11,378 biospecimens across >60 diseases and 25 assays), with >2,500 annual users. The NF Data Portal integrates over 200 TB data from 312 neurology and oncology studies, and catalogues >1,100 tools spanning NF1, NF2, and schwannomatosis. As part of the coordinating center for AACR Project GENIE we have supported the ETL and sharing of clinico-genomic data from 19 centers, including 211,527 patients and 250,018 samples. DREAM cancer challenges run on Synapse have established benchmarks including in AML subtyping, prostate cancer survival, immunotherapy response and digital mammography. Independent Synapse users have contributed >1.2M public files (>95 TB) across 400+ cancer-related projects. A user-friendly generalist data platform and a set of proven data coordination and challenge operations lower the activation energy for new cancer collaborations, from independent projects to large, multi-institutional networks. We invite researchers to explore Synapse.org and our data portals. AI was used to summarize metrics and refine wording Authors reviewed and approved all content.
▎中文翻译：
协作性癌症研究需要一个能够跨机构、跨模式和跨资助方运行的共享数据基础设施。由 Sage Bionetworks 开发的 Synapse.org 是一个多功能的公共数据平台，被研究联盟、真实世界数据项目和计算挑战赛广泛使用。我们描述了 Synapse 如何支持多样化的癌症研究社区。 Synapse 提供了经过验证的元数据、溯源性、版本控制和细粒度访问控制工具。对于支持的社区，我们提供数据整理和验证应用、领域特定门户、仪表板和挑战框架。通过 GA4GH DRS，API 和客户端将 Synapse 连接到本地计算环境和可信研究环境（如 Cavatica、Terra、Pluto、SevenBridges CGC）。近期的增强功能包括由人类引导、人工智能驱动的数据整理、基于 OpenSearch 的发现功能以及自然语言数据搜索。数据通过贡献者上传（网页、CLI、API）、程序化 ETL 管道以及外部存储库（如 GEO、dbGaP）的索引进入平台。经过整理的数据集被索引以供发现，并通过项目门户展示。社区的使用情况和反馈指导数据整理的优先级，从而维持一个持续改进的循环。 Synapse 平台托管了超过 3.6 PB 的数据，每月用户超过 6,000 人。癌症复杂性知识门户（Cancer Complexity Knowledge Portal）连接了 160 项资助、4,178 篇出版物、1,039 个数据集和 321 个工具，聚焦于癌症生物学。人类肿瘤图谱网络数据协调中心（Human Tumor Atlas Network DCC）管理着 334 TB 的标准化组学数据（0.23M 个文件，来自 2,372 例病例和 11,378 个生物样本，涵盖 60 多种疾病和 25 种检测方法），年用户超过 2,500 人。神经纤维瘤病数据门户（NF Data Portal）整合了来自 312 项神经病学和肿瘤学研究的超过 200 TB 数据，并收录了超过 1,100 个工具，涵盖 NF1、NF2 和神经鞘瘤病。作为 AACR Project GENIE 协调中心的一部分，我们支持了来自 19 个中心的临床基因组数据的 ETL 和共享，包括 211,527 名患者和 250,018 个样本。在 Synapse 上运行的 DREAM 癌症挑战赛已建立了多个基准，包括 AML 分型、前列腺癌生存预测、免疫治疗反应和数字乳腺 X 线摄影。独立的 Synapse 用户已在 400 多个癌症相关项目中贡献了超过 120 万个公共文件（超过 95 TB）。 一个用户友好型的通用数据平台以及一套经过验证的数据协调和挑战操作流程，降低了新癌症合作的启动门槛，从独立项目到大型多机构网络均可适用。我们邀请研究人员访问 Synapse.org 及我们的数据门户。 人工智能用于总结指标和优化措辞，作者已审阅并批准所有内容。
📸 Poster预览
🔗原文：https://cattendee.abstractsonline.com/meeting/21436/Presentation/3389
