Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes.
Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes.
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DOI：
10.3389/fonc.2022.832715
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发表时间：
2022
影响因子：
4.7
通讯作者：
Mao F
中科院分区：
文献类型：
--
作者：
Wang X;Li L;Yang Y;Fan L;Ma Y;Mao F
目前胰腺导管腺癌（PDAC）的临床分型不能很好地预测患者对治疗方案的可能反应，也不能预测患者的预后。我们使用PDAC患者的基因表达模式来揭示胰腺癌肿瘤微环境的异质性，并分析不同免疫亚型的预后和免疫治疗反应的差异。首先，利用ICGC的PACA-AU PDAC表达谱数据，结合ssGSEA算法，分析患者肿瘤微环境的免疫富集情况。随后采用谱聚类算法提取不同分类，将PDAC队列分为4个亚型，建立免疫亚型与临床特征及生存预后的相关性。通过预后预测模型得到患者的风险指数，提示风险指数与免疫细胞的相关性。我们可以将PDAC组群分为四种亚型：免疫细胞和基质细胞富集（免疫富集-基质）、非免疫富集但基质细胞富集（非免疫-基质）、免疫富集集体但非基质富集（免疫富集-非基质）和非免疫富集和非基质细胞富集（非免疫-非基质）。PACA-CA免疫富集基质组与非免疫基质组的5年生存率有显著差异。TCGA-PAAD的免疫-富集-基质组和免疫-富集-非基质组在一年内的生产率有很大差异。风险指数与免疫细胞的相关性分析结果显示，患者的疾病风险与上皮细胞、巨核细胞-红系祖细胞（MEP）和Th 2细胞显著相关。胰腺癌患者的肿瘤基因表达特征与免疫应答相关，导致形态学上可识别的PDAC亚型具有预后/预测意义。
The current clinical classification of pancreatic ductal adenocarcinoma (PDAC) cannot well predict the patient’s possible response to the treatment plan, nor can it predict the patient’s prognosis. We use the gene expression patterns of PDAC patients to reveal the heterogeneity of the tumor microenvironment of pancreatic cancer and analyze the differences in the prognosis and immunotherapy response of different immune subtypes. Firstly, use ICGC’s PACA-AU PDAC expression profile data, combined with the ssGSEA algorithm, to analyze the immune enrichment of the patient’s tumor microenvironment. Subsequently, the spectral clustering algorithm was used to extract different classifications, the PDAC cohort was divided into four subtypes, and the correlation between immune subtypes and clinical characteristics and survival prognosis was established. The patient’s risk index is obtained through the prognostic prediction model, and the correlation between the risk index and immune cells is prompted. We can divide the PDAC cohort into four subtypes: immune cell and stromal cell enrichment (Immune-enrich-Stroma), non-immune enrichment but stromal cell enrichment (Non-immune-Stroma), immune-enriched Collective but non-matrix enrichment (Immune-enrich-non-Stroma) and non-immune enrichment and non-stromal cell enrichment (Non-immune-non-Stroma). The five-year survival rate of immune-enrich-Stroma and non-immune-Stroma of PACA-CA is quite different. TCGA-PAAD’s immune-enrich-Stroma and immune-enrich-non-Stroma groups have a large difference in productivity in one year. The results of the correlation analysis between the risk index and immune cells show that the patient’s disease risk is significantly related to epithelial cells, megakaryocyte-erythroid progenitor (MEP), and Th2 cells. The tumor gene expression characteristics of pancreatic cancer patients are related to immune response, leading to morphologically recognizable PDAC subtypes with prognostic/predictive significance.
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影响因子：
11.4
作者：
Giordano, Marilyn;Henin, Coralie;Verdeil, Gregory
通讯作者：
Verdeil, Gregory
影响因子：
50.3
作者：
Calon A;Espinet E;Palomo-Ponce S;Tauriello DV;Iglesias M;Céspedes MV;Sevillano M;Nadal C;Jung P;Zhang XH;Byrom D;Riera A;Rossell D;Mangues R;Massagué J;Sancho E;Batlle E
通讯作者：
Batlle E
DOI：
10.1126/science.aar3593
发表时间：
2018-10-12
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Cristescu R;Mogg R;Ayers M;Albright A;Murphy E;Yearley J;Sher X;Liu XQ;Lu H;Nebozhyn M;Zhang C;Lunceford JK;Joe A;Cheng J;Webber AL;Ibrahim N;Plimack ER;Ott PA;Seiwert TY;Ribas A;McClanahan TK;Tomassini JE;Loboda A;Kaufman D
通讯作者：
Kaufman D
影响因子：
64.8
作者：
Bailey, Peter;Chang, David K.;Grimmond, Sean M.
通讯作者：
Grimmond, Sean M.
影响因子：
4.8
作者：
Ju, Hyoungseok;Lim, Byungho;Kang, Changwon
通讯作者：
Kang, Changwon