Distinct Gene Expression Profiles Define Anaplastic Grade in Retinoblastoma

Abstract

Morbidity and mortality associated with retinoblastoma have decreased drastically in recent decades, in large part owing to better prediction of high-risk disease and appropriate treatment stratification. High-risk histopathologic features and severe anaplasia both predict the need for more aggressive treatment; however, not all centers are able to assess tumor samples easily for the degree of anaplasia. Instead, identification of genetic signatures that are able to distinguish among anaplastic grades and thus predict high- versus low-risk retinoblastoma would facilitate appropriate risk stratification in a wider patient population. A better understanding of genes dysregulated in anaplasia also would yield valuable insights into pathways underlying the development of more severe retinoblastoma. Here, we present the histopathologic and gene expression analysis of 28 retinoblastoma cases using microarray analysis. Tumors of differing anaplastic grade show clear differential gene expression, with significant dysregulation of unique genes and pathways in severe anaplasia. Photoreceptor and nucleoporin expression in particular are identified as highly dysregulated in severe anaplasia and suggest particular cellular processes contributing to the development of increased retinoblastoma severity. A limited set of highly differentially expressed genes also are able to predict severe anaplasia accurately in our data set. Together, these data contribute to the understanding of the development of anaplasia and facilitate the identification of genetic markers of high-risk retinoblastoma.

Conservative management of retinoblastoma: Challenging orthodoxy without compromising the state of metastatic grace. “Alive, with good vision and no comorbidity”

“…Clinical classification of the choroidal occlusive vasculopathy after intra-arterial chemotherapy. Munier, et al Progress in Retinal and Eye Research 73 (2019) 100764 (Golabchi et al, 2018;Hudson et al, 2018;Kapatai et al, 2013;Kooi et al, 2016b;Naru et al, 2017) is expected to allow not only a better understanding of the mechanisms underlying tumor biology (MYCN vs non-MYCN) and progression (somatic chromosomal copy-number alterations, epigenetic changes) including seeding, metastasis and relapse, but also novel diagnostic and therapeutic applications. Last but not least, this section also proposes to unveil some new potential therapeutic avenues, including gene therapy (see 8.2), cell-of-origin targeted therapy (see 8.3), personalized management (see 8.4) as well as new drugs (see 8.5) or new Galenic formulation of known drugs (see 8.6).…”

Identification of co‑expression modules and hub genes of retinoblastoma via co‑expression analysis and protein‑protein interaction networks

“…nih.gov/geo/). The dataset contains the gene expression profiles of 28 retinoblastoma samples based on the GPl16686 platform (Human Gene 2.0 ST array; affymetrix; Thermo Fisher Scientific, Inc.) (12). Annotation information of microarray data was used to match probes with corresponding gene information.…”

“…For example, tumor staging, pathological grade and tumor laterality show associations with the patient's age at diagnosis, overall survival and second malignancy in retinoblastoma (11). High-risk histopathologic features (HrPFs) are closely related to poor prognosis, including tumor invasion of the optic nerve, choroid or anterior chamber, suggesting the need for postenucleation adjuvant chemotherapy (12). Therefore, it is necessary to identify gene coexpression modules associated with these clinical traits.…”

TRIM59 Promotes Retinoblastoma Progression by Activating the p38–MAPK Signaling Pathway

“…Three microarray, gene expression datasets (GSE24673, 14 GSE97508, 15 and GSE110811 16 ) were retrieved from the Gene Expression Omnibus (GEO) database (https://www. ncbi.nlm.nih.gov/geo/).…”