Retrospective Validation of a 168-Gene Expression Signature for Glioma Classification on a Single Molecule Counting Platform.
Retrospective Validation of a 168-Gene Expression Signature for Glioma Classification on a Single Molecule Counting Platform.
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在单分子计数平台上回顾性验证用于胶质瘤分类的168个基因表达特征。
DOI：
10.3390/cancers13030439
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发表时间：
2021-01-25
期刊：
影响因子：
5.2
通讯作者：
She JX
中科院分区：
文献类型：
--
作者：
Tran PMH;Tran LKH;Satter KB;Purohit S;Nechtman J;Hopkins DI;Dos Santos B;Bollag R;Kolhe R;Sharma S;She JX
癌症的分子分类有可能实现自动化并减少癌症分类的错误。我们之前表明，转录组学分类与神经胶质瘤分类的甲基组学和突变方法相当，并且可能有助于预测生存预后。在这里，我们使用福尔马林固定石蜡包埋的样品在单分子计数基因表达平台上验证转录组分类方法。基因表达谱已被证明与神经胶质瘤分类的其他分子方法相当。我们试图验证基于基因表达的神经胶质瘤分类方法。对 2000 年至 2019 年在奥古斯塔大学 (AU) 病理学系收集的福尔马林固定石蜡包埋组织和快速冷冻组织进行了鉴定，并取了 2 mm 的核心。脱蜡和珠匀浆后从这些核心中提取 RNA。在 nCounter 仪器上对 RNA 样本中的 168 个基因进行了评估。使用监督学习算法对 48 例神经胶质瘤进行分类，该算法是使用癌症基因组图谱的数据进行训练的。 1000 个线性支持向量模型的集合将 30 个神经胶质瘤样本分类为 TP1，分类置信度为 0.99。与非 TP1 组相比，TP1 组胶质瘤患者的生存期较差（HR (95% CI) = 4.5 (1.3–15.4)，p = 0.005），中位生存时间为 12.1 个月。网络分析表明，细胞周期基因在区分 TP1 和非 TP1 病例中发挥着重要作用，并且这些基因可能在神经胶质瘤存活中发挥重要作用。这可能是神经胶质瘤分子分类的良好临床管道。
Molecular classification of cancers has the potential to automate and decrease errors in cancer classification. We previously showed that transcriptomic classification is comparable to methylomic and mutation methods for glioma classification and may provide benefit in predicting survival prognosis. Here we validate the transcriptomic classification method on a single molecule counting gene expression platform using formalin-fixed paraffin embedded samples. Gene expression profiling has been shown to be comparable to other molecular methods for glioma classification. We sought to validate a gene-expression based glioma classification method. Formalin-fixed paraffin embedded tissue and flash frozen tissue collected at the Augusta University (AU) Pathology Department between 2000–2019 were identified and 2 mm cores were taken. The RNA was extracted from these cores after deparaffinization and bead homogenization. One hundred sixty-eight genes were evaluated in the RNA samples on the nCounter instrument. Forty-eight gliomas were classified using a supervised learning algorithm trained by using data from The Cancer Genome Atlas. An ensemble of 1000 linear support vector models classified 30 glioma samples into TP1 with classification confidence of 0.99. Glioma patients in TP1 group have a poorer survival (HR (95% CI) = 4.5 (1.3–15.4), p = 0.005) with median survival time of 12.1 months, compared to non-TP1 groups. Network analysis revealed that cell cycle genes play an important role in distinguishing TP1 from non-TP1 cases and that these genes may play an important role in glioma survival. This could be a good clinical pipeline for molecular classification of gliomas.
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影响因子：
64.8
作者：
Capper D;Jones DTW;Sill M;Hovestadt V;Schrimpf D;Sturm D;Koelsche C;Sahm F;Chavez L;Reuss DE;Kratz A;Wefers AK;Huang K;Pajtler KW;Schweizer L;Stichel D;Olar A;Engel NW;Lindenberg K;Harter PN;Braczynski AK;Plate KH;Dohmen H;Garvalov BK;Coras R;Hölsken A;Hewer E;Bewerunge-Hudler M;Schick M;Fischer R;Beschorner R;Schittenhelm J;Staszewski O;Wani K;Varlet P;Pages M;Temming P;Lohmann D;Selt F;Witt H;Milde T;Witt O;Aronica E;Giangaspero F;Rushing E;Scheurlen W;Geisenberger C;Rodriguez FJ;Becker A;Preusser M;Haberler C;Bjerkvig R;Cryan J;Farrell M;Deckert M;Hench J;Frank S;Serrano J;Kannan K;Tsirigos A;Brück W;Hofer S;Brehmer S;Seiz-Rosenhagen M;Hänggi D;Hans V;Rozsnoki S;Hansford JR;Kohlhof P;Kristensen BW;Lechner M;Lopes B;Mawrin C;Ketter R;Kulozik A;Khatib Z;Heppner F;Koch A;Jouvet A;Keohane C;Mühleisen H;Mueller W;Pohl U;Prinz M;Benner A;Zapatka M;Gottardo NG;Driever PH;Kramm CM;Müller HL;Rutkowski S;von Hoff K;Frühwald MC;Gnekow A;Fleischhack G;Tippelt S;Calaminus G;Monoranu CM;Perry A;Jones C;Jacques TS;Radlwimmer B;Gessi M;Pietsch T;Schramm J;Schackert G;Westphal M;Reifenberger G;Wesseling P;Weller M;Collins VP;Blümcke I;Bendszus M;Debus J;Huang A;Jabado N;Northcott PA;Paulus W;Gajjar A;Robinson GW;Taylor MD;Jaunmuktane Z;Ryzhova M;Platten M;Unterberg A;Wick W;Karajannis MA;Mittelbronn M;Acker T;Hartmann C;Aldape K;Schüller U;Buslei R;Lichter P;Kool M;Herold-Mende C;Ellison DW;Hasselblatt M;Snuderl M;Brandner S;Korshunov A;von Deimling A;Pfister SM
通讯作者：
Pfister SM
DOI：
10.1056/nejmoa1407279
发表时间：
2015-06-25
期刊：
The New England journal of medicine
影响因子：
--
作者：
Eckel-Passow JE;Lachance DH;Molinaro AM;Walsh KM;Decker PA;Sicotte H;Pekmezci M;Rice T;Kosel ML;Smirnov IV;Sarkar G;Caron AA;Kollmeyer TM;Praska CE;Chada AR;Halder C;Hansen HM;McCoy LS;Bracci PM;Marshall R;Zheng S;Reis GF;Pico AR;O'Neill BP;Buckner JC;Giannini C;Huse JT;Perry A;Tihan T;Berger MS;Chang SM;Prados MD;Wiemels J;Wiencke JK;Wrensch MR;Jenkins RB
通讯作者：
Jenkins RB
影响因子：
45.3
作者：
Laenkholm, Anne-Vibeke;Jensen, Maj-Britt;Ejlertsen, Bent
通讯作者：
Ejlertsen, Bent
影响因子：
3.9
作者：
Peereboom DM;Supko JG;Carson KA;Batchelor T;Phuphanich S;Lesser G;Mikkelsen T;Fisher J;Desideri S;He X;Grossman SA;New Approaches to Brain Tumor Therapy (NABTT) Consortium
通讯作者：
New Approaches to Brain Tumor Therapy (NABTT) Consortium
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