RESUMEN
We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.
Asunto(s)
Genoma/genética , MicroARNs/genética , Neoplasias/genética , Programas Informáticos , Estudios Controlados Antes y Después , Conjuntos de Datos como Asunto , Perfilación de la Expresión Génica , Genoma Humano , Genómica , Intercambio de Información en Salud , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Anotación de Secuencia Molecular , Reproducibilidad de los ResultadosRESUMEN
We studied 137 primary testicular germ cell tumors (TGCTs) using high-dimensional assays of genomic, epigenomic, transcriptomic, and proteomic features. These tumors exhibited high aneuploidy and a paucity of somatic mutations. Somatic mutation of only three genes achieved significance-KIT, KRAS, and NRAS-exclusively in samples with seminoma components. Integrated analyses identified distinct molecular patterns that characterized the major recognized histologic subtypes of TGCT: seminoma, embryonal carcinoma, yolk sac tumor, and teratoma. Striking differences in global DNA methylation and microRNA expression between histology subtypes highlight a likely role of epigenomic processes in determining histologic fates in TGCTs. We also identified a subset of pure seminomas defined by KIT mutations, increased immune infiltration, globally demethylated DNA, and decreased KRAS copy number. We report potential biomarkers for risk stratification, such as miRNA specifically expressed in teratoma, and others with molecular diagnostic potential, such as CpH (CpA/CpC/CpT) methylation identifying embryonal carcinomas.
Asunto(s)
Neoplasias de Células Germinales y Embrionarias/patología , Neoplasias Testiculares/patología , Variaciones en el Número de Copia de ADN , Metilación de ADN , Regulación Neoplásica de la Expresión Génica , Humanos , Masculino , MicroARNs/metabolismo , Neoplasias de Células Germinales y Embrionarias/clasificación , Neoplasias de Células Germinales y Embrionarias/metabolismo , Proteínas Proto-Oncogénicas c-kit/genética , Proteínas Proto-Oncogénicas c-kit/metabolismo , Seminoma/metabolismo , Seminoma/patología , Neoplasias Testiculares/clasificación , Neoplasias Testiculares/metabolismo , Proteínas ras/genética , Proteínas ras/metabolismoRESUMEN
On the basis of multidimensional and comprehensive molecular characterization (including DNA methalylation and copy number, RNA, and protein expression), we classified 894 renal cell carcinomas (RCCs) of various histologic types into nine major genomic subtypes. Site of origin within the nephron was one major determinant in the classification, reflecting differences among clear cell, chromophobe, and papillary RCC. Widespread molecular changes associated with TFE3 gene fusion or chromatin modifier genes were present within a specific subtype and spanned multiple subtypes. Differences in patient survival and in alteration of specific pathways (including hypoxia, metabolism, MAP kinase, NRF2-ARE, Hippo, immune checkpoint, and PI3K/AKT/mTOR) could further distinguish the subtypes. Immune checkpoint markers and molecular signatures of T cell infiltrates were both highest in the subtype associated with aggressive clear cell RCC. Differences between the genomic subtypes suggest that therapeutic strategies could be tailored to each RCC disease subset.
Asunto(s)
Carcinoma de Células Renales/patología , Genómica , Neoplasias Renales/patología , Factores de Transcripción Básicos con Cremalleras de Leucinas y Motivos Hélice-Asa-Hélice/genética , Factores de Transcripción Básicos con Cremalleras de Leucinas y Motivos Hélice-Asa-Hélice/metabolismo , Carcinoma de Células Renales/genética , Carcinoma de Células Renales/mortalidad , Cromatina/metabolismo , Perfilación de la Expresión Génica , Humanos , Neoplasias Renales/genética , Neoplasias Renales/mortalidad , MicroARNs/metabolismo , Mutación , Fosfatidilinositol 3-Quinasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , ARN Mensajero/metabolismo , Transducción de Señal/genética , Tasa de Supervivencia , Serina-Treonina Quinasas TOR/metabolismoRESUMEN
SUMMARY: We have developed Nozzle, an R package that provides an Application Programming Interface to generate HTML reports with dynamic user interface elements. Nozzle was designed to facilitate summarization and rapid browsing of complex results in data analysis pipelines where multiple analyses are performed frequently on big datasets. The package can be applied to any project where user-friendly reports need to be created. AVAILABILITY: The R package is available on CRAN at http://cran.r-project.org/package=Nozzle.R1. Examples and additional materials are available at http://gdac.broadinstitute.org/nozzle. The source code is also available at http://www.github.com/parklab/Nozzle. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.