Dataset Information

Bioinformatics analyses of retinoblastoma reveal the retinoblastoma progression subtypes.

ABSTRACT: Introduction:Retinoblastoma (RB) is one common pediatric malignant tumor with dismal outcomes. Heterogeneity of RB and subtypes of RB were identified but the association between the subtypes of RB and RB progression have not been fully investigated. Methods:Four public datasets were downloaded from Gene expression omnibus and normalization was performed to remove batch effect. Two public datasets were explored to obtain the RB progression gene signatures by differentially expression analysis while another two datasets were iterated for RB subtypes identification using consensus clustering. After the RB progressive subtype gene signatures were identified, we tested the diagnostic capacity of these gene signatures by receiver operation curve. Results:Three hundreds and forty six genes that were enriched in cell cycle were identified as the progression signature in RB from two independent datasets. Four subtypes of RB were stratified by consensus clustering. A total of 21 genes from RB progression signature were differentially expressed between RB subtypes. One subtype with low expression cell division genes have less progression of all four subtypes. A panel of five RB subtype genes (CLUL1, CNGB1, ROM1, LRRC39 and RDH12) predict progression of RB. Conclusion:Retinoblastoma is a highly heterogeneous tumor and the level of cell cycle related gene expression is associated with RB progression. A subpopulation of RB with high expression of visual perception has less progressive features. LRRC39 is potentially the RB progression subtype biomarker.

SUBMITTER: Cao M

PROVIDER: S-EPMC7246025 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bioinformatics analyses of retinoblastoma reveal the retinoblastoma progression subtypes.

Cao Manjing M Wang Sha S Zou Jing J Wang Wanpeng W

PeerJ 20200521

<h4>Introduction</h4>Retinoblastoma (RB) is one common pediatric malignant tumor with dismal outcomes. Heterogeneity of RB and subtypes of RB were identified but the association between the subtypes of RB and RB progression have not been fully investigated.<h4>Methods</h4>Four public datasets were downloaded from Gene expression omnibus and normalization was performed to remove batch effect. Two public datasets were explored to obtain the RB progression gene signatures by differentially expressi ...[more]

PMID: 32509443

Similar Datasets

Project description:BackgroundRetinoblastoma is a pediatric eye cancer associated with RB1 loss or MYCN amplification (RB1 (+/+) MYCN(A) ). There are controversies concerning the existence of molecular subtypes within RB1(-/-) retinoblastoma. To test whether these molecular subtypes exist, we performed molecular profiling.MethodsGenome-wide mRNA expression profiling was performed on 76 primary human retinoblastomas. Expression profiling was complemented by genome-wide DNA profiling and clinical, histopathological, and ex vivo drug sensitivity data.FindingsRNA and DNA profiling identified major variability between retinoblastomas. While gene expression differences between RB1 (+/+) MYCN(A) and RB1(-/-) tumors seemed more dichotomous, differences within the RB1(-/-) tumors were gradual. Tumors with high expression of a photoreceptor gene signature were highly differentiated, smaller in volume and diagnosed at younger age compared with tumors with low photoreceptor signature expression. Tumors with lower photoreceptor expression showed increased expression of genes involved in M-phase and mRNA and ribosome synthesis and increased frequencies of somatic copy number alterations.InterpretationMolecular, clinical and histopathological differences between RB1(-/-) tumors are best explained by tumor progression, reflected by a gradual loss of differentiation and photoreceptor expression signature. Since copy number alterations were more frequent in tumors with less photoreceptorness, genomic alterations might be drivers of tumor progression.Research in contextRetinoblastoma is an ocular childhood cancer commonly caused by mutations in the RB1 gene. In order to determine optimal treatment, tumor subtyping is considered critically important. However, except for very rare retinoblastomas without an RB1 mutation, there are controversies as to whether subtypes of retinoblastoma do exist. Our study shows that retinoblastomas are highly diverse but rather than reflecting distinct tumor types with a different etiology, our data suggests that this diversity is a result of tumor progression driven by cumulative genetic alterations. Therefore, retinoblastomas should not be categorized in distinct subtypes, but be described according to their stage of progression.

Project description:BackgroundPrimary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease of the exocrine glands characterized by specific pathological features. Previous studies have pointed out that salivary glands from pSS patients express a unique profile of cytokines, adhesion molecules, and chemokines compared to those from healthy controls. However, there is limited evidence supporting the utility of individual markers for different stages of pSS. This study aimed to explore potential biomarkers associated with pSS disease progression and analyze the associations between key genes and immune cells.MethodsWe combined our own RNA sequencing data with pSS datasets from the NCBI Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) via bioinformatics analysis. Salivary gland biopsies were collected from 14 pSS patients, 6 non-pSS patients, and 6 controls. Histochemical staining and scanning electron micrographs (SEM) were performed to macroscopically and microscopically characterize morphological features of labial salivary glands in different disease stages. Then, we performed quantitative PCR to validate hub genes. Finally, we analyzed correlations between selected hub genes and immune cells using the CIBERSORT algorithm.ResultsWe identified twenty-eight DEGs that were upregulated in pSS patients compared to healthy controls. These were mainly involved in immune-related pathways and infection-related pathways. According to the morphological features of minor salivary glands, severe interlobular and periductal lymphocytic infiltrates, acinar atrophy and collagen in the interstitium, nuclear shrinkage, and microscopic organelle swelling were observed with pSS disease progression. Hub genes based on above twenty-eight DEGs, including MS4A1, CD19, TCL1A, CCL19, CXCL9, CD3G, and CD3D, were selected as potential biomarkers and verified by RT-PCR. Expression of these genes was correlated with T follicular helper cells, memory B cells and M1 macrophages.ConclusionUsing transcriptome sequencing and bioinformatics analysis combined with our clinical data, we identified seven key genes that have potential value for evaluating pSS severity.

Dataset Information

Bioinformatics analyses of retinoblastoma reveal the retinoblastoma progression subtypes.

Publications

Bioinformatics analyses of retinoblastoma reveal the retinoblastoma progression subtypes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets