Mining TCGA database for genes of prognostic value in glioblastoma microenvironment.
Mining TCGA database for genes of prognostic value in glioblastoma microenvironment.
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DOI：
10.18632/aging.101415
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发表时间：
2018-04-16
期刊：
影响因子：
--
通讯作者：
Liu Y
中科院分区：
文献类型：
--
作者：
Jia D;Li S;Li D;Xue H;Yang D;Liu Y
胶质母细胞瘤(GBM)是最致命的脑肿瘤之一。通过方便地访问癌症基因组图谱(TCGA)数据库，可以进行大规模的全球基因表达谱分析和数据库挖掘，以确定基因之间的潜在相关性和包括基底膜在内的各种恶性肿瘤的总体存活率。以往的研究表明，肿瘤的微环境、免疫细胞和间质细胞在肿瘤中的侵袭程度对预后有重要影响。基于估计算法计算的免疫评分和间质评分可以帮助对肿瘤中的免疫和间质成分进行量化。为了更好地了解免疫和基质细胞参与的基因对预后的影响，我们根据免疫/基质评分将TCGA数据库中的GBM病例分为高分组和低分组，并确定了与GBM患者预后显著相关的差异表达基因。功能丰富分析和蛋白质-蛋白质相互作用网络进一步表明，这些基因主要参与免疫反应、细胞外基质和细胞黏附。最后，我们在来自中国胶质瘤基因组图谱(CGGA)的一个独立的GBM队列中验证了这些基因。因此，我们获得了一份与肿瘤微环境相关的基因清单，这些基因可以预测GBM患者的不良预后。
Glioblastoma (GBM) is one of the most deadly brain tumors. The convenient access to The Cancer Genome Atlas (TCGA) database allows for large-scale global gene expression profiling and database mining for potential correlation between genes and overall survival of a variety of malignancies including GBM. Previous reports have shown that tumor microenvironment cells and the extent of infiltrating immune and stromal cells in tumors contribute significantly to prognosis. Immune scores and stromal scores calculated based on the ESTIMATE algorithm could facilitate the quantification of the immune and stromal components in a tumor. To better understand the effects of genes involved in immune and stromal cells on prognosis, we categorized GBM cases in the TCGA database according to their immune/stromal scores into high and low score groups, and identified differentially expressed genes whose expression was significantly associated with prognosis in GBM patients. Functional enrichment analysis and protein-protein interaction networks further showed that these genes mainly participated in immune response, extracellular matrix, and cell adhesion. Finally, we validated these genes in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Thus, we obtained a list of tumor microenvironment-related genes that predict poor outcomes in GBM patients.
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影响因子：
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作者：
Piao Y;Henry V;Tiao N;Park SY;Martinez-Ledesma J;Dong JW;Balasubramaniyan V;de Groot JF
通讯作者：
de Groot JF
影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
影响因子：
50.3
作者：
Hanahan, Douglas;Coussens, Lisa M.
通讯作者：
Coussens, Lisa M.
影响因子：
64.5
作者：
Ceccarelli M;Barthel FP;Malta TM;Sabedot TS;Salama SR;Murray BA;Morozova O;Newton Y;Radenbaugh A;Pagnotta SM;Anjum S;Wang J;Manyam G;Zoppoli P;Ling S;Rao AA;Grifford M;Cherniack AD;Zhang H;Poisson L;Carlotti CG Jr;Tirapelli DP;Rao A;Mikkelsen T;Lau CC;Yung WK;Rabadan R;Huse J;Brat DJ;Lehman NL;Barnholtz-Sloan JS;Zheng S;Hess K;Rao G;Meyerson M;Beroukhim R;Cooper L;Akbani R;Wrensch M;Haussler D;Aldape KD;Laird PW;Gutmann DH;TCGA Research Network;Noushmehr H;Iavarone A;Verhaak RG
通讯作者：
Verhaak RG
DOI：
10.1056/nejmoa1402121
发表时间：
2015-06-25
期刊：
The New England journal of medicine
影响因子：
--
作者：
Cancer Genome Atlas Research Network;Brat DJ;Verhaak RG;Aldape KD;Yung WK;Salama SR;Cooper LA;Rheinbay E;Miller CR;Vitucci M;Morozova O;Robertson AG;Noushmehr H;Laird PW;Cherniack AD;Akbani R;Huse JT;Ciriello G;Poisson LM;Barnholtz-Sloan JS;Berger MS;Brennan C;Colen RR;Colman H;Flanders AE;Giannini C;Grifford M;Iavarone A;Jain R;Joseph I;Kim J;Kasaian K;Mikkelsen T;Murray BA;O'Neill BP;Pachter L;Parsons DW;Sougnez C;Sulman EP;Vandenberg SR;Van Meir EG;von Deimling A;Zhang H;Crain D;Lau K;Mallery D;Morris S;Paulauskis J;Penny R;Shelton T;Sherman M;Yena P;Black A;Bowen J;Dicostanzo K;Gastier-Foster J;Leraas KM;Lichtenberg TM;Pierson CR;Ramirez NC;Taylor C;Weaver S;Wise L;Zmuda E;Davidsen T;Demchok JA;Eley G;Ferguson ML;Hutter CM;Mills Shaw KR;Ozenberger BA;Sheth M;Sofia HJ;Tarnuzzer R;Wang Z;Yang L;Zenklusen JC;Ayala B;Baboud J;Chudamani S;Jensen MA;Liu J;Pihl T;Raman R;Wan Y;Wu Y;Ally A;Auman JT;Balasundaram M;Balu S;Baylin SB;Beroukhim R;Bootwalla MS;Bowlby R;Bristow CA;Brooks D;Butterfield Y;Carlsen R;Carter S;Chin L;Chu A;Chuah E;Cibulskis K;Clarke A;Coetzee SG;Dhalla N;Fennell T;Fisher S;Gabriel S;Getz G;Gibbs R;Guin R;Hadjipanayis A;Hayes DN;Hinoue T;Hoadley K;Holt RA;Hoyle AP;Jefferys SR;Jones S;Jones CD;Kucherlapati R;Lai PH;Lander E;Lee S;Lichtenstein L;Ma Y;Maglinte DT;Mahadeshwar HS;Marra MA;Mayo M;Meng S;Meyerson ML;Mieczkowski PA;Moore RA;Mose LE;Mungall AJ;Pantazi A;Parfenov M;Park PJ;Parker JS;Perou CM;Protopopov A;Ren X;Roach J;Sabedot TS;Schein J;Schumacher SE;Seidman JG;Seth S;Shen H;Simons JV;Sipahimalani P;Soloway MG;Song X;Sun H;Tabak B;Tam A;Tan D;Tang J;Thiessen N;Triche T Jr;Van Den Berg DJ;Veluvolu U;Waring S;Weisenberger DJ;Wilkerson MD;Wong T;Wu J;Xi L;Xu AW;Yang L;Zack TI;Zhang J;Aksoy BA;Arachchi H;Benz C;Bernard B;Carlin D;Cho J;DiCara D;Frazer S;Fuller GN;Gao J;Gehlenborg N;Haussler D;Heiman DI;Iype L;Jacobsen A;Ju Z;Katzman S;Kim H;Knijnenburg T;Kreisberg RB;Lawrence MS;Lee W;Leinonen K;Lin P;Ling S;Liu W;Liu Y;Liu Y;Lu Y;Mills G;Ng S;Noble MS;Paull E;Rao A;Reynolds S;Saksena G;Sanborn Z;Sander C;Schultz N;Senbabaoglu Y;Shen R;Shmulevich I;Sinha R;Stuart J;Sumer SO;Sun Y;Tasman N;Taylor BS;Voet D;Weinhold N;Weinstein JN;Yang D;Yoshihara K;Zheng S;Zhang W;Zou L;Abel T;Sadeghi S;Cohen ML;Eschbacher J;Hattab EM;Raghunathan A;Schniederjan MJ;Aziz D;Barnett G;Barrett W;Bigner DD;Boice L;Brewer C;Calatozzolo C;Campos B;Carlotti CG Jr;Chan TA;Cuppini L;Curley E;Cuzzubbo S;Devine K;DiMeco F;Duell R;Elder JB;Fehrenbach A;Finocchiaro G;Friedman W;Fulop J;Gardner J;Hermes B;Herold-Mende C;Jungk C;Kendler A;Lehman NL;Lipp E;Liu O;Mandt R;McGraw M;Mclendon R;McPherson C;Neder L;Nguyen P;Noss A;Nunziata R;Ostrom QT;Palmer C;Perin A;Pollo B;Potapov A;Potapova O;Rathmell WK;Rotin D;Scarpace L;Schilero C;Senecal K;Shimmel K;Shurkhay V;Sifri S;Singh R;Sloan AE;Smolenski K;Staugaitis SM;Steele R;Thorne L;Tirapelli DP;Unterberg A;Vallurupalli M;Wang Y;Warnick R;Williams F;Wolinsky Y;Bell S;Rosenberg M;Stewart C;Huang F;Grimsby JL;Radenbaugh AJ;Zhang J
通讯作者：
Zhang J