Lin Wanzun, Gao Jing, Zhang Haojiong, Chen Li, Qiu Xianxin, Huang Qingting, Hu Jiyi, Kong Lin, Lu Jiade J
Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, 4365 Kangxin Rd, Shanghai, 201321, China.
Shanghai Key Laboratory of Radiation Oncology (20dz2261000), Shanghai, China.
Inflamm Regen. 2022 Oct 1;42(1):29. doi: 10.1186/s41232-022-00215-9.
Inflammatory response is an important characteristic affecting prognosis and therapeutic response in lower-grade glioma (LGG). However, the molecular subtypes based on inflammatory response are still under exploitation.
The RNA sequencing, somatic mutation, and corresponding clinical data from 1205 LGG patients were obtained from the TCGA, CGGA, and Rembrandt cohorts. Consensus clustering was performed to identify molecular subtypes associated with inflammation. Prognosis, clinicopathologic features, immune cell infiltration, and somatic mutation profile were compared among these inflammation-associated subtypes.
Our results demonstrate that LGG could be categorized into inflammation-, low, -mid, and -high subtypes with distinct clinicopathologic features, prognostic and tumor microenvironment. We established that this categorization was reproducible, as well as predictable. In general, inflammation-high subtype presents a dismal prognosis with the immunosuppressive microenvironment and high frequency of oncogene mutation. Inversely, inflammation-low subtype was associated with the most favorable clinical outcomes with the immunoreactive microenvironment among three subtypes. Moreover, we develop and validate an inflammation-related prognostic model, which shows strong power for prognosis assessment.
In conclusion, we established a novel glioma classification based on the inflammation subtype. This classification had significant outcomes for estimating the prognosis, as well as the tumor microenvironment.
炎症反应是影响低级别胶质瘤（LGG）预后和治疗反应的重要特征。然而，基于炎症反应的分子亚型仍在探索之中。
从TCGA、CGGA和Rembrandt队列中获取1205例LGG患者的RNA测序、体细胞突变及相应临床数据。进行一致性聚类以识别与炎症相关的分子亚型。比较这些炎症相关亚型之间的预后、临床病理特征、免疫细胞浸润和体细胞突变谱。
我们的结果表明，LGG可分为炎症型、低、中、高亚型，具有不同的临床病理特征、预后和肿瘤微环境。我们确定这种分类是可重复的，也是可预测的。一般来说，炎症高亚型预后较差，具有免疫抑制微环境和高频致癌基因突变。相反，炎症低亚型在三种亚型中与最有利的临床结果相关，具有免疫反应性微环境。此外，我们开发并验证了一种炎症相关的预后模型，该模型显示出强大的预后评估能力。
总之，我们基于炎症亚型建立了一种新的胶质瘤分类。这种分类对于估计预后以及肿瘤微环境具有重要意义。
