GPC-3 in hepatocellular carcinoma: current perspectives

Wu, Yongle; Liu, Hui; Ding, Huiguo

doi:10.2147/jhc.s116513

Cited by 71 publications

(51 citation statements)

References 39 publications

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“…Genes implicated in stimulus response, neuronal migration, secretion and extracellular matrix were coherently upregulated across all tumor samples when mixed with NPCs, indicating that GBM cells sense the presence of neuronal cells and reactively amplify the transcription of genes supporting their dispersion. Among the upregulated genes were GJA1 (coding for connexin 43), known to enable multicellular communication via gap junctions in GBM networks in vivo 4 , and GPC-3, which has received little attention in glioblastoma 21 but whose expression evidentially correlates with higher invasive capacity in hepatocellular carcinoma 19 , where it also confers oncogenicity by activating the IGF signaling pathway through IGF1R 22 .…”

Section: Discussionmentioning

confidence: 99%

“…3E). These included the homeobox transcription factor PAX6, normally expressed in forebrain neural stem cells; the gap junction protein alpha 1 (GJA1) coding for connexin-43, which connects tumor microtubes in GBM 4 ; glypican-3 (GPC3), a cell surface heparan sulfate proteoglycan and Wnt activator whose expression correlates with invasiveness of hepatocellular carcinoma 19 ; collagen COL4A5, an extracellular matrix constituent; and several lysosomal, vesicular and secretory proteins ( Fig. 3F and Supplementary Table 2).…”

Section: Mixing Gbm and Organoid Cells Leads To Up-regulation Of A Shmentioning

confidence: 99%

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Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Krieger

Tirier

Park

et al. 2019

Preprint

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AbstractGlioblastoma multiforme (GBM) are devastating neoplasms with high invasive capacity. GBM has been difficult to study in vitro. Therapeutic progress is also limited by cellular heterogeneity within and between tumors. To address these challenges, we present an experimental model using human cerebral organoids as a scaffold for patient-derived glioblastoma cell invasion. By tissue clearing and confocal microscopy, we show that tumor cells within organoids extend a network of long microtubes, recapitulating the in vivo behavior of GBM. Single-cell RNA-seq of GBM cells before and after co-culture with organoid cells reveals transcriptional changes implicated in the invasion process that are coherent across patient samples, indicating that GBM cells reactively upregulate genes required for their dispersion. Functional therapeutic targets are identified by an in silico receptor-ligand pairing screen detecting potential interactions between GBM and organoid cells. Taken together, our model has proven useful for studying GBM invasion and transcriptional heterogeneity in vitro, with applications for both pharmacological screens and patient-specific treatment selection at a time scale amenable to clinical practice.

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Section: Discussionmentioning

confidence: 99%

Section: Mixing Gbm and Organoid Cells Leads To Up-regulation Of A Shmentioning

confidence: 99%

Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Krieger

Tirier

Park

et al. 2019

Preprint

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“…Some studies show association between GPC3 gene and some types of liver cancer such as hepatocellular carcinoma. [30,34,54,55] Therefore, this study can open the door for novel diagnostic biomarkers for hepatocellular carcinoma. Combination detection of serum GPC3 and pathogenic SNPs through clinical and genetic testing must be positively matched; this can enhance accuracy and efficiency of hepatocellular carcinoma diagnosis.…”

Section: Discussionmentioning

confidence: 92%

“…[30,31] Some studies show association between GPC3 gene and some types of human cancers. [32][33][34][35][36] The aim of this study was to identify the pathogenic SNPs in the coding region of GPC3 gene which causes SGBS type I using variant bioinformatics tools, Also to identify the most deleterious nsSNPs that could be used as diagnostic markers. A nsSNP is a single base change in a coding region that causes an amino acid change in its corresponding protein.…”

Section: Introductionmentioning

confidence: 99%

Identification of novel key biomarkers in Simpson-Golabi-Behmel Syndrome: Evidence from bioinformatics analysis

Mustafa

Abdelmoneim

Elfadol

et al. 2019

Preprint

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Background:The Simpson- Golabi-Behmel Syndrome (SGBS) or overgrowth Syndrome is a rare inherited X-linked condition characterized by pre-and postnatal overgrowth. The aim of the present study is to identify functional non-synonymous SNPs of GPC3 gene using various in silico approaches. These SNPs are supposed to have a direct effect on protein stability through conformation changes. Material and methods: The SNPs were retrieved from the Single Nucleotide Polymorphism database (dbSNP) and further used to investigate a damaging effect using SIFT, PolyPhen, PROVEAN, SNAP2, SNPs&GO, PHD-SNP and P-mut, While we used I-mutant and MUPro to study the effect of SNPs on GPC3 protein structure. The 3D structure of human GPC3 protein is not available in the Protein Data Bank, so we used RaptorX to generate a 3D structural model for wild-type GPC3 to visualize the amino acids changes by UCSF Chimera. For biophysical validation we used project HOPE. Lastly we run conservational analysis by BioEdit and Consurf web server respectively. Results: our results revealed three novel missense mutations (rs1460413167, rs1295603457 and rs757475450) that are found to be the most deleterious which effect on the GPC3 structure and function. Conclusion: This present study could provide a novel insight into the molecular basis of overgrowth Syndrome.

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“…B7 family members share same GPI‐linked transmembrane proteins comprised of IgV and IgC domains. Prominent ligands include B7‐H1 (PD‐L1, CD274; Dong, Zhu, Tamada, & Chen, 1999), B7‐H2 (PD‐L2, CD275, ICOSL; Wang et al, 2000), B7‐H3 (CD276; Wu, Liu, & Ding, 2016), B7‐H4 (B7‐S1, B7x; Sica et al, 2003), B7‐H5 (CD28H; Sedykh, Prinz, Buneva, & Nevinsky, 2018), B7‐H6 (Godwin, Gale, & Walter, 2017), B 7 ‐DC (PD‐L2, CD273; Huret et al., 2001), B7‐1 (CD80; Greaves & Gribben, 2013), PD‐1H (VISTA; Flies, Wang, Xu, & Chen, 2011), B7‐2 (CD86; Greaves & Gribben, 2013), and many others (Schildberg, Klein, Freeman, & Sharpe, 2016) as shown in Figure 2.…”

Section: B7 Family Membersmentioning

confidence: 99%

Programmed cell death ligand‐1: A dynamic immune checkpoint in cancer therapy

2020

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Antibody-based immunotherapies play a pivotal role in cancer research with efficient achievements in tumor suppression. Tumor survival is assisted by modulation of immune checkpoints to create imbalances between immune cells and cancer cell's environment. The modulation results in T-cell signal inhibition ultimately inert its proliferation and activation against various tumor cells. PD-L1, a 40 kDa transmembrane protein of B7 family, binds with PD-1 on the membrane of T cells which results in inhibition of T-cell proliferation and activation. PD-L1/PD-1 pathway has generated novel target sites for antibodies that can block PD-L1/PD-1 interactions.The blockage results in T-cell proliferation and tumor cell suppression. The PD-L1 immune checkpoint strategies' development, expression and regulations, signal inhibitions, and developmental stages of PD-L1/PD-1 antibodies are briefly discussed here in this review. All this information will provide a base for new therapeutic development against PD-L1 and PD-1 immune checkpoint interactions and will make available promising treatment options. K E Y W O R D Santibody, immune checkpoint, immunotherapy, PD-1, PD-L1

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GPC-3 in hepatocellular carcinoma: current perspectives

Cited by 71 publications

References 39 publications

Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Identification of novel key biomarkers in Simpson-Golabi-Behmel Syndrome: Evidence from bioinformatics analysis

Programmed cell death ligand‐1: A dynamic immune checkpoint in cancer therapy

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