PanCancer insights from The Cancer Genome Atlas: the pathologist's perspective.
PanCancer insights from The Cancer Genome Atlas: the pathologist's perspective.
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DOI：
10.1002/path.5028
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发表时间：
2018-04
期刊：
影响因子：
--
通讯作者：
Lazar AJ
中科院分区：
文献类型：
--
作者：
Cooper LA;Demicco EG;Saltz JH;Powell RT;Rao A;Lazar AJ
癌症基因组图谱（TCGA）是致力于对选定的肿瘤类型进行全面的基因组和表观基因组分析的几个国际联盟之一，以促进我们对疾病的理解，并为全球癌症研究提供开放获取的资源。33种肿瘤类型（通过组织学或组织来源选择，包括常见和罕见疾病），包括>11 000个样本，进行DNA测序，拷贝数和甲基化分析，以及转录组学，蛋白质组学和组织学评价。对每种癌症类型进行单独分析，以确定组织特异性改变，并在不同的分子平台之间建立相关性。然后将最终的数据集标准化并合并用于PanCancer Initiative，该计划旨在确定不同癌症类型或起源/谱系细胞之间或解剖学或形态学相关组内的共性。沿着丰富的分子研究而产生的一个重要资源是广泛的数字病理学幻灯片档案，包括与作为TCGA一部分分析的组织直接相关的冷冻切片组织，以及代表性的福尔马林固定石蜡包埋、苏木精和伊红（H&E）染色的诊断幻灯片。这些H&E图像资源主要用于验证诊断和组织学亚型，并对标准病理学变量（如有丝分裂活性、分级和淋巴细胞浸润）进行了一些有限的提取。最重要的是忽略了这些扫描图像的丰富性，以便更复杂的特征提取方法与机器学习相结合，并最终与分子特征和临床终点相关联。在这里，我们记录了利用TCGA成像档案的初步尝试，并描述了一些工具，以及快速发展的图像分析/特征提取领域。我们的希望是通知，并最终激励和挑战，病理学和癌症研究界利用这些成像资源，使TCGA的这个整体平台的全部潜力可以用来补充和加强从基因组和表观基因组平台的有见地的综合分析。
The Cancer Genome Atlas (TCGA) represents one of several international consortia dedicated to performing comprehensive genomic and epigenomic analyses of selected tumour types to advance our understanding of disease and provide an open-access resource for worldwide cancer research. Thirty-three tumour types (selected by histology or tissue of origin, to include both common and rare diseases), comprising >11 000 specimens, were subjected to DNA sequencing, copy number and methylation analysis, and transcriptomic, proteomic and histological evaluation. Each cancer type was analysed individually to identify tissue-specific alterations, and make correlations across different molecular platforms. The final dataset was then normalized and combined for the PanCancer Initiative, which seeks to identify commonalities across different cancer types or cells of origin/lineage, or within anatomically or morphologically related groups. An important resource generated along with the rich molecular studies is an extensive digital pathology slide archive, composed of frozen section tissue directly related to the tissues analysed as part of TCGA, and representative formalin-fixed paraffin-embedded, haematoxylin and eosin (H&E)-stained diagnostic slides. These H&E image resources have primarily been used to verify diagnoses and histological subtypes with some limited extraction of standard pathological variables such as mitotic activity, grade, and lymphocytic infiltrates. Largely overlooked is the richness of these scanned images for more sophisticated feature extraction approaches coupled with machine learning, and ultimately correlation with molecular features and clinical endpoints. Here, we document initial attempts to exploit TCGA imaging archives, and describe some of the tools, and the rapidly evolving image analysis/feature extraction landscape. Our hope is to inform, and ultimately inspire and challenge, the pathology and cancer research communities to exploit these imaging resources so that the full potential of this integral platform of TCGA can be used to complement and enhance the insightful integrated analyses from the genomic and epigenomic platforms.
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影响因子：
64.5
作者：
Ciriello G;Gatza ML;Beck AH;Wilkerson MD;Rhie SK;Pastore A;Zhang H;McLellan M;Yau C;Kandoth C;Bowlby R;Shen H;Hayat S;Fieldhouse R;Lester SC;Tse GM;Factor RE;Collins LC;Allison KH;Chen YY;Jensen K;Johnson NB;Oesterreich S;Mills GB;Cherniack AD;Robertson G;Benz C;Sander C;Laird PW;Hoadley KA;King TA;TCGA Research Network;Perou CM
通讯作者：
Perou CM
影响因子：
64.5
作者：
Hoadley KA;Yau C;Wolf DM;Cherniack AD;Tamborero D;Ng S;Leiserson MDM;Niu B;McLellan MD;Uzunangelov V;Zhang J;Kandoth C;Akbani R;Shen H;Omberg L;Chu A;Margolin AA;Van't Veer LJ;Lopez-Bigas N;Laird PW;Raphael BJ;Ding L;Robertson AG;Byers LA;Mills GB;Weinstein JN;Van Waes C;Chen Z;Collisson EA;Cancer Genome Atlas Research Network;Benz CC;Perou CM;Stuart JM
通讯作者：
Stuart JM
影响因子：
28.2
作者：
Corcoran RB;Ebi H;Turke AB;Coffee EM;Nishino M;Cogdill AP;Brown RD;Della Pelle P;Dias-Santagata D;Hung KE;Flaherty KT;Piris A;Wargo JA;Settleman J;Mino-Kenudson M;Engelman JA
通讯作者：
Engelman JA
影响因子：
30.8
作者：
Ciriello, Giovanni;Miller, Martin L.;Aksoy, Buelent Arman;Senbabaoglu, Yasin;Schultz, Nikolaus;Sander, Chris
通讯作者：
Sander, Chris
影响因子：
64.5
作者：
Cancer Genome Atlas Network
通讯作者：
Cancer Genome Atlas Network