越来越多的证据表明，肿瘤细胞（TCs）与肿瘤相关巨噬细胞（TAMs）之间的通讯在促进低级别胶质瘤（LGG）的进展方面起到重要作用。因此，对TAM-TC相互作用进行建模并探究其对LGG患者预后的影响变得至关重要。本文提出了一种转化性研究流程，构建了多细胞相互作用基因网络（MIGN），用于鉴定可药物靶点以开发新的治疗策略。首先，我们使用临床前试验中胶质瘤小鼠的RNA-seq数据，选择与免疫治疗相关的特征基因（IFGs）用于TAMs和TCs。将这些IFGs转化为人类基因组后，分别构建了TAM-和TC-相关网络，使用524例人类LGG的训练集。随后，在每个网络内进行聚类分析，并采用一致性度量K指数，将基因聚类与患者生存率相关联。MIGN是通过将与TAM-和TC-关联网络中的生存高度相关的聚类组合而成。然后，我们开发了一种基于MIGN的生存模型，以识别由配体、受体和中心基因组成的预后标志。我们利用一个独立的包含172个人类LGG样本的队列来验证标志的预测准确性。在验证集中，与1年、3年和5年生存率相关的时间依赖ROC曲线下面积分别为0.881、0.867和0.839。此外，还对标志基因进行了文献调查，并评估了针对LGG患者的靶向药物的潜在临床反应，进一步凸显了MIGN标志的潜在实用性，以开发新的免疫疗法，延长LGG患者的生存期。

Increasing evidence suggests that communication between tumor cells (TCs) and tumor-associated macrophages (TAMs) plays a substantial role in promoting progression of low-grade gliomas (LGG). Hence, it is becoming critical to model TAM-TC interplay and interrogate how the crosstalk affects prognosis of LGG patients. This paper proposed a translational research pipeline to construct the multicellular interaction gene network (MIGN) for identification of druggable targets to develop novel therapeutic strategies. Firstly, we selected immunotherapy-related feature genes (IFGs) for TAMs and TCs using RNA-seq data of glioma mice from preclinical trials. After translating the IFGs to human genome, we constructed TAM- and TC- associated networks separately, using a training set of 524 human LGGs. Subsequently, clustering analysis was performed within each network, and the concordance measure K-index was adopted to correlate gene clusters with patient survival. The MIGN was built by combining the clusters highly associated with survival in TAM- and TC-associated networks. We then developed a MIGN-based survival model to identify prognostic signatures comprised of ligands, receptors and hub genes. An independent cohort of 172 human LGG samples was leveraged to validate predictive accuracy of the signature. The areas under time-dependent ROC curves were 0.881, 0.867, and 0.839 with respect to 1-year, 3-year, and 5-year survival rates respectively in the validation set. Furthermore, literature survey was conducted on the signature genes, and potential clinical responses to targeted drugs were evaluated for LGG patients, further highlighting potential utilities of the MIGN signature to develop novel immunotherapies to extend survival of LGG patients.