Islet Co-Expression of CD133 and ABCB5 in Human Retinoblastoma Specimens

Zschoche, Marco; Skosyrski, Sergej; Babst, Neele; Ranjbar, Mahdy; Rommel, Felix; Kurz, Maximilian; Tura, Aysegül; Joachim, Stephanie C.; Kociok, Norbert; Kakkassery, Vinodh

doi:10.1055/a-1525-2588

Cited by 3 publications

(2 citation statements)

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“…To identify the mechanisms of chemotherapy resistance, the etoposide-resistant subclone WERI-ETOR was established by harvesting surviving cells after incubation with increasing etoposide doses from WERI-RB1, as described by Stephan et al [ 12 ]. Previous studies also examined the parental WERI-RB1 and the etoposide-resistant subclone WERI-ETOR on the molecular level [ 13 , 14 , 15 , 16 , 17 , 18 ]. Furthermore, Busch et al demonstrated a higher proliferation rate in WERI-ETOR as well as increased tumor formation and tumor size in an in vivo chick chorioallantoic-membrane assay [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Protein Profiling of WERI-RB1 and Etoposide-Resistant WERI-ETOR Reveals New Insights into Topoisomerase Inhibitor Resistance in Retinoblastoma

Kakkassery

Gemoll²,

Kraemer

et al. 2022

IJMS

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Chemotherapy resistance is one of the reasons for eye loss in patients with retinoblastoma (RB). RB chemotherapy resistance has been studied in different cell culture models, such as WERI-RB1. In addition, chemotherapy-resistant RB subclones, such as the etoposide-resistant WERI-ETOR cell line have been established to improve the understanding of chemotherapy resistance in RB. The objective of this study was to characterize cell line models of an etoposide-sensitive WERI-RB1 and its etoposide-resistant subclone, WERI-ETOR, by proteomic analysis. Subsequently, quantitative proteomics data served for correlation analysis with known drug perturbation profiles. Methodically, WERI-RB1 and WERI-ETOR were cultured, and prepared for quantitative mass spectrometry (MS). This was carried out in a data-independent acquisition (DIA) mode. The raw SWATH (sequential window acquisition of all theoretical mass spectra) files were processed using neural networks in a library-free mode along with machine-learning algorithms. Pathway-enrichment analysis was performed using the REACTOME-pathway resource, and correlated to the molecular signature database (MSigDB) hallmark gene set collections for functional annotation. Furthermore, a drug-connectivity analysis using the L1000 database was carried out to associate the mechanism of action (MOA) for different anticancer reagents to WERI-RB1/WERI-ETOR signatures. A total of 4756 proteins were identified across all samples, showing a distinct clustering between the groups. Of these proteins, 64 were significantly altered (q < 0.05 & log2FC |>2|, 22 higher in WERI-ETOR). Pathway analysis revealed the “retinoid metabolism and transport” pathway as an enriched metabolic pathway in WERI-ETOR cells, while the “sphingolipid de novo biosynthesis” pathway was identified in the WERI-RB1 cell line. In addition, this study revealed similar protein signatures of topoisomerase inhibitors in WERI-ETOR cells as well as ATPase inhibitors, acetylcholine receptor antagonists, and vascular endothelial growth factor receptor (VEGFR) inhibitors in the WERI-RB1 cell line. In this study, WERI-RB1 and WERI-ETOR were analyzed as a cell line model for chemotherapy resistance in RB using data-independent MS. Analysis of the global proteome identified activation of “sphingolipid de novo biosynthesis” in WERI-RB1, and revealed future potential treatment options for etoposide resistance in RB.

show abstract

Section: Introductionmentioning

confidence: 99%

Protein Profiling of WERI-RB1 and Etoposide-Resistant WERI-ETOR Reveals New Insights into Topoisomerase Inhibitor Resistance in Retinoblastoma

Kakkassery

Gemoll²,

Kraemer

et al. 2022

IJMS

Self Cite

View full text Add to dashboard Cite

show abstract

“…To identify the mechanisms of chemotherapy resistance, the etoposide resistant subclone WERI ETOR was established by harvesting surviving cells after incubation with increasing etoposide doses from WERI RB1 as described by Stephan et al (12). Previous studies also examined the parental WERI RB1 and the etoposide resistant subclone WERI ETOR on the molecular level (13)(14)(15)(16)(17)(18). Furthermore, Busch et al demonstrated a higher proliferation rate in WERI ETOR as well as an increased tumor formation and tumor size in an in vivo chick chorioallantoic membrane assay (17).…”

Section: Introductionmentioning

confidence: 99%

Protein profiling of WERI RB1 and etoposide resistant WERI ETOR reveals new insights into topoisomerase inhibitor resistance in retinoblastoma

Kakkassery

Gemoll

Kraemer

et al. 2022

Preprint

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Chemotherapy resistance is one of the reasons for eye loss in patients with retinoblastoma (RB). RB chemotherapy resistance has been studied in different cell culture models such as WERI RB1. In addition, chemotherapy resistant RB subclones like the etoposide resistant WERI ETOR cell line have been established to improve the understanding of chemotherapy resistance in RB. The objective of this study was to characterize cell line models of an etoposide sensitive WERI RB1 and its etoposide resistant subclone WERI ETOR by proteomic analysis. Subsequently, quantitative proteomic data served for correlation analysis with known drug perturbation profiles. Methodically, WERI RB1 and WERI ETOR were cultured and prepared for quantitative mass spectrometry (MS). This was carried out in a data-independent acquisition (DIA) mode (Sequential Window Acquisition of All Theoretical Mass Spectra, SWATH-MS). The raw SWATH files were processed using neural networks in a library free mode along with machine learning algorithms. Pathway enrichment was performed using the REACTOME pathway resource and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. Furthermore, a drug connectivity analysis using the L1000 database was used to correlate the mechanism-of-action (MOA) for different anticancer reagents to WERI RB1/WERI ETOR signatures. A total of 4,756 proteins were identified across all samples, showing a distinct clustering between the groups. Of these proteins, 64 were significantly altered (q < 0.05 & log2FC |>2|, 22% higher in WERI ETOR). Pathway analysis revealed an enriched metabolic pathway for retinoid metabolism and transport in WERI ETOR and for sphingolipid de novo biosynthesis in WERI RB1. In addition, this study revealed similar protein signatures of topoisomerase inhibitors in WERI ETOR as well as ATPase inhibitors, acetylcholine receptor antagonists and vascular endothelial growth factor receptor (VEGFR) inhibitors in WERI RB1. In this study, WERI RB1 and WERI ETOR were analyzed as a cell line model for chemotherapy resistance in RB using data-independent MS. The global proteome identified activation of sphingolipid de novo biosynthesis in WERI RB1 and revealed future potential treatment options for etoposide resistance in RB.

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Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

et al. 2023

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Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune–stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments.

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Islet Co-Expression of CD133 and ABCB5 in Human Retinoblastoma Specimens

Cited by 3 publications

References 62 publications

Protein Profiling of WERI-RB1 and Etoposide-Resistant WERI-ETOR Reveals New Insights into Topoisomerase Inhibitor Resistance in Retinoblastoma

Protein Profiling of WERI-RB1 and Etoposide-Resistant WERI-ETOR Reveals New Insights into Topoisomerase Inhibitor Resistance in Retinoblastoma

Protein profiling of WERI RB1 and etoposide resistant WERI ETOR reveals new insights into topoisomerase inhibitor resistance in retinoblastoma

Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

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