Identification of GSPT1 as prognostic biomarker and promoter of malignant colon cancer cell phenotypes via the GSK-3β/CyclinD1 pathway

Long, Xuan; Zhao, Lijun; Li, Guoqiang; Wang, Ziwei; Deng, Zhigang

doi:10.18632/aging.202796

Cited by 16 publications

(8 citation statements)

References 26 publications

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“…This indicates that neosubstrate expression is not in itself a reliable predictor of degradation outcome in cells and tissues. We also show that the weak degradation of GSPT1 by CC-885 correlates with a modest cell growth inhibition in HCT116 (IC50 = 0.198 μM) (Figure C, Figure S5), highlighting that more potent GSPT degraders could be used in colorectal cancer. , …”

Section: Resultsmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

“…We also show that the weak degradation of GSPT1 by CC-885 correlates with a modest cell growth inhibition in HCT116 (IC50 = 0.198 μM) (Figure 5C, Figure S5), highlighting that more potent GSPT degraders could be used in colorectal cancer. 60,61 Some compounds that were shown to be inactive based on phenotypic screens (Figure S7B) may still induce drugdependent protein degradation events in cells (Figure S7C, S7D). As an example, cluster1 compounds (e.g., CC-92480) do not inhibit HL60 proliferation despite showing strong degradation of IKZF1 (Figure S7E).…”

Section: Structure−target Degradation Relationships Of Cereblon E3 Li...mentioning

confidence: 99%

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SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics

et al. 2022

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Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4 CRBN ). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.

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Section: Resultsmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

Section: Structure−target Degradation Relationships Of Cereblon E3 Li...mentioning

confidence: 99%

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SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics

et al. 2022

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“…Previous studies have shown the involvement of GSPT1 in translation termination and cell proliferation. Furthermore, GSPT1 silencing suppresses colony formation and cell invasion ( Hoshino et al, 1989 ; Long et al, 2021 ). Based on the decrease in expression of lncRNA NEAT1 in bald lesions, we hypothesize that the Neat1-miR-27b-3p -Gspt1 ceRNA network may be involved in AGA progression.…”

Section: Discussionmentioning

confidence: 99%

An integrative analysis of the lncRNA-miRNA-mRNA competitive endogenous RNA network reveals potential mechanisms in the murine hair follicle cycle

Ding

Chen²,

Yang³

et al. 2022

Front. Genet.

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Alopecia is a common progressive disorder associated with abnormalities of the hair follicle cycle. Hair follicles undergo cyclic phases of hair growth (anagen), regression (catagen), and rest (telogen), which are precisely regulated by various mechanisms. However, the specific mechanism associated with hair follicle cycling, which includes noncoding RNAs and regulation of competitive endogenous RNA (ceRNA) network, is still unclear. We obtained data from publicly available databases and performed real-time quantitative polymerase chain reaction validations. These analyses revealed an increase in the expression of miRNAs and a decrease in the expression of target mRNAs and lncRNAs from the anagen to telogen phase of the murine hair follicle cycle. Subsequently, we constructed the ceRNA networks and investigated their functions using enrichment analysis. Furthermore, the androgenetic alopecia (AGA) microarray data analysis revealed that several novel alopecia-related genes were identified in the ceRNA networks. Lastly, GSPT1 expression was detected using immunohistochemistry. Our analysis revealed 11 miRNAs (miR-148a-3p, miR-146a-5p, miR-200a-3p, miR-30e-5p, miR-30a-5p, miR-27a-3p, miR-143-3p, miR-27b-3p, miR-126a-3p, miR-378a-3p, and miR-22-3p), 9 target mRNAs (Atp6v1a, Cdkn1a, Gadd45a, Gspt1, Mafb, Mitf, Notch1, Plk2, and Slc7a5), and 2 target lncRNAs (Neat1 and Tug1) were differentially expressed in hair follicle cycling. The ceRNA networks were made of 12 interactive miRNA-mRNA pairs and 13 miRNA-lncRNA pairs. The functional enrichment analysis revealed the enrichment of hair growth–related signaling pathways. Additionally, GSPT1 was downregulated in androgenetic alopecia patients, possibly associated with alopecia progression. The ceRNA network identified by our analysis could be involved in regulating the hair follicle cycle.

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“…The GSPT1/ GSK pathway exerts tumor-promoting actions in colon cancer oncogenesis and progression. The GSPT1/GSK pathway may thus be an effective target for controlling colon cancer (26). Recently, LPP has emerged as a critical inducer of tumor cell migration, invasion and metastasis (27).…”

Section: Recognition Of Critical State Of Prostate Cancermentioning

confidence: 99%

Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence

Yan

Gao

et al. 2021

Front. Oncol.

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MotivationThe evolution of complex diseases can be modeled as a time-dependent nonlinear dynamic system, and its progression can be divided into three states, i.e., the normal state, the pre-disease state and the disease state. The sudden deterioration of the disease can be regarded as the state transition of the dynamic system at the critical state or pre-disease state. How to detect the critical state of an individual before the disease state based on single-sample data has attracted many researchers’ attention.MethodsIn this study, we proposed a novel approach, i.e., single-sample-based Jensen-Shannon Divergence (sJSD) method to detect the early-warning signals of complex diseases before critical transitions based on individual single-sample data. The method aims to construct score index based on sJSD, namely, inconsistency index (ICI).ResultsThis method is applied to five real datasets, including prostate cancer, bladder urothelial carcinoma, influenza virus infection, cervical squamous cell carcinoma and endocervical adenocarcinoma and pancreatic adenocarcinoma. The critical states of 5 datasets with their corresponding sJSD signal biomarkers are successfully identified to diagnose and predict each individual sample, and some “dark genes” that without differential expressions but are sensitive to ICI score were revealed. This method is a data-driven and model-free method, which can be applied to not only disease prediction on individuals but also targeted drug design of each disease. At the same time, the identification of sJSD signal biomarkers is also of great significance for studying the molecular mechanism of disease progression from a dynamic perspective.

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Identification of GSPT1 as prognostic biomarker and promoter of malignant colon cancer cell phenotypes via the GSK-3β/CyclinD1 pathway

Cited by 16 publications

References 26 publications

SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics

SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics

An integrative analysis of the lncRNA-miRNA-mRNA competitive endogenous RNA network reveals potential mechanisms in the murine hair follicle cycle

Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence

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