Discovery of a transcriptomic core of genes shared in 8 primary retinoblastoma with a novel detection score analysis.

Autor: Alvarez-Suarez DE; Medical Research Unit in Infectious Diseases, Hospital de Pediatría, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.; Pharmacology Department, CINVESTAV, Mexico City, Mexico., Tovar H; Computational Genomics Division, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico., Hernández-Lemus E; Computational Genomics Division, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico., Orjuela M; Epidemiology Department, Columbia University, Columbia, NY, USA., Sadowinski-Pine S; Pathology Department, Hospital Infantil de México Federico Gómez, Secretaría de Salud, Mexico City, Mexico., Cabrera-Muñoz L; Pathology Department, Hospital Infantil de México Federico Gómez, Secretaría de Salud, Mexico City, Mexico., Camacho J; Pharmacology Department, CINVESTAV, Mexico City, Mexico., Favari L; Pharmacology Department, CINVESTAV, Mexico City, Mexico., Hernández-Angeles A; Medical Research Unit in Infectious Diseases, Hospital de Pediatría, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico., Ponce-Castañeda MV; Medical Research Unit in Infectious Diseases, Hospital de Pediatría, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico. vponce@ifc.unam.mx.
Jazyk: angličtina
Zdroj: Journal of cancer research and clinical oncology [J Cancer Res Clin Oncol] 2020 Aug; Vol. 146 (8), pp. 2029-2040. Date of Electronic Publication: 2020 May 30.
DOI: 10.1007/s00432-020-03266-y
Abstrakt: Purpose: Expression microarrays are powerful technology that allows large-scale analysis of RNA profiles in a tissue; these platforms include underexploited detection scores outputs. We developed an algorithm using the detection score, to generate a detection profile of shared elements in retinoblastoma as well as to determine its transcriptomic size and structure.
Methods: We analyzed eight briefly cultured primary retinoblastomas with the Human transcriptome array 2.0 (HTA2.0). Transcripts and genes detection scores were determined using the Detection Above Background algorithm (DABG). We used unsupervised and supervised computational tools to analyze detected and undetected elements; WebGestalt was used to explore functions encoded by genes in relevant clusters and performed experimental validation.
Results: We found a core cluster with 7,513 genes detected and shared by all samples, 4,321 genes in a cluster that was commonly absent, and 7,681 genes variably detected across the samples accounting for tumor heterogeneity. Relevant pathways identified in the core cluster relate to cell cycle, RNA transport, and DNA replication. We performed a kinome analysis of the core cluster and found 4 potential therapeutic kinase targets. Through analysis of the variably detected genes, we discovered 123 differentially expressed transcripts between bilateral and unilateral cases.
Conclusions: This novel analytical approach allowed determining the retinoblastoma transcriptomic size, a shared active transcriptomic core among the samples, potential therapeutic target kinases shared by all samples, transcripts related to inter tumor heterogeneity, and to determine transcriptomic profiles without the need of control tissues. This approach is useful to analyze other cancer or tissue types.
Databáze: MEDLINE
Externí odkaz: