Orchestra：基于组合生物信息学MCP智能体的协同验证式调控候选发现

中文摘要 AI 辅助

Orchestra将两个独立构建的生物信息学MCP服务器——RegNetAgents（从ARACNe网络推断基因调控网络拓扑）和CASCADE（提供四个独立证据来源：LINCS敲低、DepMap必需性、超级增强子状态、DoRothEA转录因子置信度）——组合成一个通过模型上下文协议暴露的多智能体工作流。其核心架构主张是，要求RegNetAgents的拓扑证据和CASCADE的实验证据在候选调控因子上达成一致，比任一单独来源产生更可信的候选——此前未直接测试过，因为RegNetAgents自身的验证仅询问其候选列表是否优于随机。我们在TCGA肿瘤获得性调控因子层级（基因肿瘤ARACNe网络中存在但GREmLN群体平均基线中缺失的调控因子）上测试这一点，通过ARACNe互信息（MI）边权重选择候选。在RegNetAgents已发表的BRCA/COAD焦点基因面板加上匹配的阴性对照上，CASCADE四个来源中至少两个的一致性能预测焦点基因中的OncoKB癌症基因状态（优势比2.89，Benjamini-Hochberg校正p=0.0166），但在阴性对照中不具预测性（p=0.0721）；单一来源对两组均无诊断性。该模式在第三种癌症类型STAD上，在单独构建的面板上（优势比5.82）以及针对独立整理的黄金标准（Sanger COSMIC癌症基因普查）上重复并增强。MI边权重是整体最强的单一预测因子（p=0.0003）；逻辑回归似然比检验确认协同验证在两种面板中均在其之上增加价值（p=0.0234；p=0.0001）。每个实验都调用Orchestra真实的智能体入口点。

英文摘要

Orchestra composes two independently built bioinformatics MCP servers -- RegNetAgents, which infers gene regulatory network topology from ARACNe networks, and CASCADE, which supplies four independent evidence sources (LINCS knockdown, DepMap essentiality, super-enhancer status, DoRothEA transcription-factor confidence) -- into one multi-agent workflow exposed via the Model Context Protocol. Its central architectural claim is that requiring RegNetAgents' topology evidence and CASCADE's experimental evidence to agree on a candidate regulator yields a more trustworthy candidate than either alone -- not previously tested directly, since RegNetAgents' own validation asked only whether its candidate lists beat chance. We test this on the TCGA tumor-acquired regulator tier (regulators in a gene's tumor ARACNe network but absent from the GREmLN population-averaged baseline), selecting candidates by ARACNe mutual-information (MI) edge weight. On RegNetAgents' published BRCA/COAD focal-gene panel plus matched negative controls, agreement among at least 2 of the 4 CASCADE sources predicts OncoKB cancer-gene status among focal genes (odds ratio 2.89, Benjamini-Hochberg-adjusted p=0.0166) but not among negative controls (p=0.0721); a single source is not diagnostic for either group. The pattern replicates and strengthens in a third cancer type, STAD, on a separately constructed panel (odds ratio 5.82), and against an independently curated ground truth (the Sanger COSMIC Cancer Gene Census). MI edge weight is the strongest single predictor overall (p=0.0003); a logistic-regression likelihood-ratio test confirms corroboration adds value beyond it in both panels (p=0.0234; p=0.0001). Every experiment invokes Orchestra's real agentic entry point.

发表机构

• Bird AI Solutions（Bird AI解决方案）

机构由 AI 辅助整理，请以论文原文为准。