Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma.
Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma.
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多组学整合揭示了六种恶性肿瘤细胞标记基因特征，可用于预测高风险神经母细胞瘤的预后
DOI：
10.3389/fninf.2022.1034793
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发表时间：
2022
影响因子：
3.5
通讯作者：
Zou, Lin
中科院分区：
文献类型：
--
作者：
Yan, Zijun;Liu, Qiming;Cao, Ziyang;Wang, Jinxia;Zhang, Hongyang;Liu, Jiangbin;Zou, Lin
关键词：
Background Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients. Methods Multi-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated. Results We constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment. Conclusion This study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients.
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DOI：
10.1158/1078-0432.ccr-11-2483
发表时间：
2012-04-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Garcia I;Mayol G;Ríos J;Domenech G;Cheung NK;Oberthuer A;Fischer M;Maris JM;Brodeur GM;Hero B;Rodríguez E;Suñol M;Galvan P;de Torres C;Mora J;Lavarino C
通讯作者：
Lavarino C
影响因子：
64.8
作者：
Helmink BA;Reddy SM;Gao J;Zhang S;Basar R;Thakur R;Yizhak K;Sade-Feldman M;Blando J;Han G;Gopalakrishnan V;Xi Y;Zhao H;Amaria RN;Tawbi HA;Cogdill AP;Liu W;LeBleu VS;Kugeratski FG;Patel S;Davies MA;Hwu P;Lee JE;Gershenwald JE;Lucci A;Arora R;Woodman S;Keung EZ;Gaudreau PO;Reuben A;Spencer CN;Burton EM;Haydu LE;Lazar AJ;Zapassodi R;Hudgens CW;Ledesma DA;Ong S;Bailey M;Warren S;Rao D;Krijgsman O;Rozeman EA;Peeper D;Blank CU;Schumacher TN;Butterfield LH;Zelazowska MA;McBride KM;Kalluri R;Allison J;Petitprez F;Fridman WH;Sautès-Fridman C;Hacohen N;Rezvani K;Sharma P;Tetzlaff MT;Wang L;Wargo JA
通讯作者：
Wargo JA
DOI：
10.1016/j.neo.2020.11.001
发表时间：
2021-01
期刊：
Neoplasia (New York, N.Y.)
影响因子：
--
作者：
Fernández-Blanco B;Berbegall AP;Martin-Vañó S;Castel V;Navarro S;Noguera R
通讯作者：
Noguera R
DOI：
10.1158/1078-0432.ccr-11-0610
发表时间：
2011-12-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
De Preter K;Mestdagh P;Vermeulen J;Zeka F;Naranjo A;Bray I;Castel V;Chen C;Drozynska E;Eggert A;Hogarty MD;Izycka-Swieszewska E;London WB;Noguera R;Piqueras M;Bryan K;Schowe B;van Sluis P;Molenaar JJ;Schramm A;Schulte JH;Stallings RL;Versteeg R;Laureys G;Van Roy N;Speleman F;Vandesompele J
通讯作者：
Vandesompele J
影响因子：
11.2
作者：
Henrich, Kai-Oliver;Bender, Sebastian;Westermann, Frank
通讯作者：
Westermann, Frank