Jiang Yanan, Sun Huimeng, Xu Hong, Hu Xin, Wu Wenqi, Lv Yangyang, Wang Jinhuan, Liu Su, Zhai Yixin, Tian Linyan, Wang Yafei, Zhao Zhigang
Key Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Key Laboratory of Cancer Prevention and Therapy of Tianjin, Key Laboratory of Molecular Cancer Epidemiology, Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Front Genet. 2022 Jun 8;13:872001. doi: 10.3389/fgene.2022.872001. eCollection 2022.
Diffuse large B cell lymphoma (DLBCL) exhibits a tightly complexity immune landscape. In this study, we intended to identify different immune phenotype and to examine the immune related mRNA signature for clinical characteristic, therapeutic responsiveness as well as risk stratification and survival prediction in DLBCL. We identified two immune infiltration subtypes of DLBCL patients based on 28 immune cell types. GSEA analysis uncovered the concordant classification of two robust significant subtypes of DLBCL. Considering the convenient application of the immune infiltration subtypes for prognostic prediction, we developed a risk score based on the differentially expressed genes between the Immunity-H and Immunity-L groups. By a least absolute shrinkage and selection operator (LASSO)-Cox regression model, a sixteen-gene risk signature, comprising ANTXR1, CD3D, TIMP1, FPR3, NID2, CTLA4, LPAR6, GPR183, LYZ, PTGDS, ITK, FBN1, FRMD6, PLAU, MICAL2, C1S, was established. The comprehensive results showed that the high-risk group was correlated with lower immune infiltration, more aggressive phenotypes, lower overall survival and more sensitive to lenalidomide. In contrast, a low-risk group score was associated with higher immune infiltration, less aggressive phenotypes, better overall survival and more likely to benefit from PD-1/PD-L1 inhibitors. Finally, a nomogram comprised of the risk score and IPI score was verified to more accurately predict the overall survival of DLBCL than traditional clinical prediction models. Altogether, our data demonstrate the heterogeneity of immune patterns within DLBCL and deepen our molecular understanding of this tumor entity.
弥漫性大B细胞淋巴瘤（DLBCL）呈现出紧密复杂的免疫格局。在本研究中，我们旨在识别不同的免疫表型，并检查免疫相关的mRNA特征，以了解DLBCL的临床特征、治疗反应性以及风险分层和生存预测。我们基于28种免疫细胞类型确定了DLBCL患者的两种免疫浸润亚型。基因集富集分析（GSEA）揭示了DLBCL两种强大显著亚型的一致分类。考虑到免疫浸润亚型在预后预测中的便捷应用，我们基于免疫-H组和免疫-L组之间的差异表达基因开发了一个风险评分。通过最小绝对收缩和选择算子（LASSO）-Cox回归模型，建立了一个包含ANTXR1、CD3D、TIMP1、FPR3、NID2、CTLA4、LPAR6、GPR183、LYZ、PTGDS、ITK、FBN1、FRMD6、PLAU、MICAL2、C1S的16基因风险特征。综合结果表明，高危组与较低的免疫浸润、更具侵袭性的表型、较低的总生存率以及对来那度胺更敏感相关。相比之下，低风险组评分与较高的免疫浸润、侵袭性较小的表型、较好的总生存率以及更有可能从PD-1/PD-L1抑制剂中获益相关。最后，验证了一个由风险评分和国际预后指数（IPI）评分组成的列线图比传统临床预测模型更准确地预测DLBCL的总生存率。总之，我们的数据证明了DLBCL内免疫模式的异质性，并加深了我们对这种肿瘤实体的分子理解。
