Immune and stromal scoring system associated with tumor microenvironment and prognosis: a gene-based multi-cancer analysis.
Immune and stromal scoring system associated with tumor microenvironment and prognosis: a gene-based multi-cancer analysis.
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与肿瘤微环境和预后相关的免疫和基质评分系统:基于基因的多癌症分析
DOI:
10.1186/s12967-021-03002-1
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发表时间:
2021-08-03
影响因子:
7.4
通讯作者:
Xie C
中科院分区:
文献类型:
--
作者:
Zeng Z;Li J;Zhang J;Li Y;Liu X;Chen J;Huang Z;Wu Q;Gong Y;Xie C
BackgroundTumor microenvironment (TME) is associated with tumor progression and prognosis. Previous studies provided tools to estimate immune and stromal cell infiltration in TME. However, there is still a lack of single index to reflect both immune and stromal status associated with prognosis and immunotherapy responses.MethodsA novel immune and stromal scoring system named ISTMEscore was developed. A total of 15 datasets were used to train and validate this system, containing 2965 samples from lung adenocarcinoma, skin cutaneous melanoma and head and neck squamous cell carcinoma.ResultsThe patients with high immune and low stromal scores (HL) were associated with low ratio of T cell co-inhibitory/stimulatory molecules and low levels of angiogenesis markers, while the patients with low immune and high stromal scores (LH) had the opposite characteristics. The HL patients had immune-centered networks, while the patients with low immune and low stromal scores (LL) had desert-like networks. Moreover, copy number alteration burden was decreased in the HL patients. For the clinical characteristics, our TME classification was an independent prognostic factor. In the 5 cohorts with immunotherapy, the LH patients were linked to the lowest response rate.ConclusionsISTMEscore system could reflect the TME status and predict the prognosis. Compared to previous TME scores, our ISTMEscore was superior in the prediction of prognosis and immunotherapy response.
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影响因子:
28.2
作者:
Chen PL;Roh W;Reuben A;Cooper ZA;Spencer CN;Prieto PA;Miller JP;Bassett RL;Gopalakrishnan V;Wani K;De Macedo MP;Austin-Breneman JL;Jiang H;Chang Q;Reddy SM;Chen WS;Tetzlaff MT;Broaddus RJ;Davies MA;Gershenwald JE;Haydu L;Lazar AJ;Patel SP;Hwu P;Hwu WJ;Diab A;Glitza IC;Woodman SE;Vence LM;Wistuba II;Amaria RN;Kwong LN;Prieto V;Davis RE;Ma W;Overwijk WW;Sharpe AH;Hu J;Futreal PA;Blando J;Sharma P;Allison JP;Chin L;Wargo JA
通讯作者:
Wargo JA
影响因子:
64.8
作者:
Cabrita, Rita;Lauss, Martin;Jonsson, Goran
通讯作者:
Jonsson, Goran
影响因子:
64.5
作者:
Kim C;Gao R;Sei E;Brandt R;Hartman J;Hatschek T;Crosetto N;Foukakis T;Navin NE
通讯作者:
Navin NE
影响因子:
3.8
作者:
Chifman J;Pullikuth A;Chou JW;Bedognetti D;Miller LD
通讯作者:
Miller LD
影响因子:
--
作者:
Hanley CJ;Noble F;Ward M;Bullock M;Drifka C;Mellone M;Manousopoulou A;Johnston HE;Hayden A;Thirdborough S;Liu Y;Smith DM;Mellows T;Kao WJ;Garbis SD;Mirnezami A;Underwood TJ;Eliceiri KW;Thomas GJ
通讯作者:
Thomas GJ