Table1_Tumor Microenvironment Profiling Identifies Prognostic Signatures and Suggests Immunotherapeutic Benefits in Neuroblastoma.xlsx

The tumor microenvironment (TME) influences disease initiation and progression. Cross-talks of cells within TME can affect the efficacy of immunotherapies. However, a precise, concise, and comprehensive TME landscape in neuroblastoma (NB) has not been established. Here, we profiled the TME landscape of 498 NB-related patients on a self-curated gene list and identified three prognostic TMEsubgroups. The differentially expressed genes in these three TMEsubgroups were used to construct a genetic signature of the TME landscape and characterize three GeneSubgroups. The subgroup with the worst overall survival prognosis, the TMEsubgroup/GeneSubgroup3, lacked immune cell infiltration and received the highest scores of MYCN- and ALK-related signatures and lowest scores of immune pathways. Additionally, we found that the GeneSubgroup3 might be benefited from anti-GD2 instead of anti-PD-1 therapy. We further created a 48-gene signature, the TMEscore, to infer prognosis and validated it in three independent NB cohorts and a pan-cancer cohort of 9,460 patients. We did RNA-seq on 16 samples and verified that TMEscore was higher in patients with stage 3/4 than stage 1/2 diseases. The TMEscore could also predict responses for several immunotherapies. After adding clinical features, we found that the nomogram-based score system, the TMEIndex, surpassed the current risk system at predicting survivals. Our analysis explained TME at the transcriptome level and paved the way for immunotherapies in NB.

肿瘤微环境（tumor microenvironment, TME）可影响疾病的发生与进展。肿瘤微环境内细胞间的交叉对话能够调控免疫治疗的疗效。然而，目前尚未构建出精准、简洁且全面的神经母细胞瘤（neuroblastoma, NB）TME图谱。本研究依托自建基因列表，对498例NB相关患者的TME图谱进行了解析，并鉴定出3个预后相关的TME亚组。本研究将这3个TME亚组中的差异表达基因用于构建TME图谱的基因特征（gene signature），并据此划分出3个基因亚组（GeneSubgroups）。其中总生存期预后最差的亚组——TME亚组3/基因亚组3（TMEsubgroup/GeneSubgroup3），呈现免疫细胞浸润缺失的特征，同时获得最高的MYCN及ALK相关特征评分，且免疫通路评分最低。此外，本研究发现基因亚组3或可从抗GD2（anti-GD2）治疗中获益，而非抗PD-1（anti-PD-1）治疗。本研究进一步构建了包含48个基因的特征标记——TMEscore，用于推断患者预后，并在3个独立NB队列及1个涵盖9460例患者的泛癌队列中完成了验证。我们对16例样本进行了RNA测序（RNA-seq），验证发现3/4期患者的TMEscore显著高于1/2期患者。TMEscore还可预测多种免疫治疗的临床响应。在纳入临床特征后，本研究构建了基于列线图（nomogram）的评分系统TMEIndex，其在生存预测性能上优于当前主流的风险分层系统。本研究从转录组层面解析了神经母细胞瘤的TME特征，为其免疫治疗奠定了理论基础。