RNF173 suppresses RAF/MEK/ERK signaling to regulate invasion and metastasis via GRB2 ubiquitination in Hepatocellular Carcinoma

FBXO32 ubiquitination of SUFU promotes progression and lenvatinib resistance in hepatocellular carcinoma via hedgehog signaling

Lenvatinib is a prevalent treatment for hepatocellular carcinoma (HCC), yet resistance to the drug significantly limits its effectiveness. This study investigates the role of FBXO32 (F-Box Protein 32) in HCC progression and lenvatinib resistance. Methods: We utilized the GSE211850 and GSE46408 datasets to identify an E3 ubiquitin ligase that is highly expressed in both lenvatinib-resistant HCC cells and HCC tissues. The expression and clinical relevance of this E3 ubiquitin ligase were further validated using lenvatinib-resistant HCC cells, online databases, and HCC clinical tissue samples. The phenotype was verified by cell and animal experiments. Techniques such as RNA sequencing, western blotting, immunofluorescence, Co-immunoprecipitation (Co‑IP), Ubiquitination, and cycloheximide (CHX) chase assay reveal the mechanism. FBXO32 is highly expressed in both lenvatinib-resistant HCC cells and HCC tissues. High FBXO32 expression correlated with increased ALT, AFP levels, larger tumors, and advanced TNM stages, serving as an independent risk factor for overall survival (OS) and recurrence-free survival (RFS). Functional assays demonstrated that FBXO32 overexpression enhanced cell proliferation, stemness, apoptosis resistance, and lenvatinib resistance, while knockdown had opposing effects. KEGG enrichment analysis indicated a link between FBXO32 and the Hedgehog signaling pathway. FBXO32-mediated degradation of SUFU, a Hedgehog pathway inhibitor, activated this pathway. Inhibiting Hedgehog signaling counteracted FBXO32's impact on HCC growth and resistance. Conclusion: FBXO32 is a critical marker for lenvatinib efficacy and HCC prognosis, suggesting that targeting FBXO32 or the Hedgehog pathway could provide innovative strategies for overcoming lenvatinib resistance in HCC.

ROR1 facilitates glioblastoma growth via stabilizing GRB2 to promote c-Fos expression in glioma stem cells

BACKGROUND

Glioma stem cells (GSCs) are the root cause of tumorigenesis, recurrence, and therapeutic resistance in glioblastoma (GBM), the most prevalent and lethal type of primary adult brain malignancy. The exploitation of novel methods targeting GSCs is crucial for the treatment of GBM. In this study, we investigate the function of the novel ROR1-GRB2-c-Fos axis in GSCs maintenance and GBM progression.

METHODS

The expression characteristics of ROR1 in GBM and GSCs were assessed by bioinformatic analysis, patient specimens, and patient-derived GSCs. Lentivirus-mediated gene knockdown and overexpression were conducted to evaluate the effect of ROR1 on GSCs proliferation and self-renewal both in vitro and in vivo. The downstream signaling of ROR1 in GSCs maintenance was unbiasedly determined by RNA-seq and validated both in vitro and in vivo. Finally, rescue assays were performed to further validate the function of the ROR1-GRB2-c-Fos axis in GSCs maintenance and GBM progression.

RESULTS

ROR1 is upregulated in GBM and preferentially expressed in GSCs. Disruption of ROR1 markedly impairs GSC proliferation and self-renewal, and inhibits GBM growth in vivo. Moreover, ROR1 stabilizes GRB2 by directly binding and reducing its lysosomal degradation, and ROR1 knockdown significantly inhibits GRB2/ERK/c-Fos signaling in GSCs. Importantly, ectopic expression of c-Fos counteracts the effects caused by ROR1 silencing both in vitro and in vivo.

CONCLUSIONS

ROR1 plays essential roles in GSCs maintenance through binding to GRB2 and activation of ERK/c-Fos signaling, which highlights the therapeutic potential of targeting the ROR1-GRB2-c-Fos axis.

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction system for HCC patients before and after LT. Data from patients with HCC who underwent LT were retrospectively collected from three specialist centres in China. Pre- and post-operative variables were selected using support vector machine, random forest, and logistic regression (LR). Then, pre- and post-operative models were developed using three machine learning methods: LR, stacking, and two survival-based approaches. Models were evaluated using seven assessment indices, and patients were classified as either high- or low-risk based on recurrence risk. 466 patients were included and followed for a median of 51.0 months (95% CI 47.8-54.2). The pre-DeepSurv model (pre-DSM) had a C-index of 0.790 ± 0.003 during training, 0.775 ± 0.037 during testing, and 0.765 ± 0.001 and 0.819 ± 0.002 during external validation. After incorporating clinicopathologic variables, the post-DeepSurv model (post-DSM) had a 0.835 ± 0.008 C-index during training, 0.812 ± 0.082 during testing, and 0.839 ± 0.001 and 0.831 ± 0.002 during external validation. The post-DSM outperformed the Milan criteria by more accurately identifying patients at high risk of recurrence. Tumour recurrence predictions also improved significantly with DeepSurv. Both pre- and post-DSMs have the potential to guide personalised surveillance strategies for LT patients with HCC.

The role of GRB2 in diabetes, diabetes complications and related disorders

Growth factor receptor-bound protein 2 (GRB2) is a key adaptor protein involved in multiple signalling pathways, and its dysregulation is associated with various diseases. Type 2 diabetes is a systemic condition characterized by insulin resistance and impaired β-cell function. The complications of diabetes significantly reduce life expectancy and quality of life, imposing a substantial burden on society. However, the role of GRB2 in diabetes and associated complications is largely unknown. Emerging evidence suggests that GRB2 plays a crucial role in insulin resistance, inflammation, immune activation and the regulation of cellular processes such as cell proliferation, growth, metabolism, angiogenesis, apoptosis and differentiation. Dysregulation of GRB2-mediated pathways contributes to the progression of diabetic neuropathy, cognitive dysfunction, nephropathy, retinopathy and related disorders. This review provides a comprehensive overview of the current understanding of the role of GRB2 in diabetes, diabetes complications and related disorders, alongside recent advances in the development of GRB2-targeted therapies. Elucidating the complex role of GRB2 in these disorders provides valuable insights into potential therapeutic strategies targeting GRB2-mediated pathways.

Identification of potential biomarkers for hepatocellular carcinoma based on machine learning and bioinformatics analysis

Metastasis is the major cause of hepatocellular carcinoma (HCC) mortality. But the effective biomarkers for HCC metastasis remain underexplored. Here we integrated GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) datasets to screen candidate genes for hepatocellular carcinoma metastasis, a consensus metastasis-derived prognostic signature (MDPS) was constructed by machine learning. Based on the risk scores, HCC patients were stratified into high-risk and low-risk groups. Comprehensive analyses were conducted to investigate various aspects including survival outcomes, clinical characteristics, immune cell infiltration, as well as in vitro experiments. Together, we develop a comprehensive machine learning-based program for constructing a consensus MDPS including four genes (SPP1, TYMS, HMMR and MYCN). Our findings revealed that four genes could serve as efficient prognostic biomarkers and therapeutic targets in HCC. In addition, in vitro experiments showed that HMMR overregulation exacerbated tumor progression, including proliferation, migration and invasion.

DUS4L suppresses invasion and metastasis in LUAD via modulation of PI3K/AKT and ERK/MAPK signaling through GRB2

OBJECTIVE

Limited research has focused on the role of dihydrouridine synthases (DUS) family members in human tumors. Our previous findings indicated an impact of dihydrouridine synthase 4 like (DUS4L) on cell proliferation and apoptosis in lung adenocarcinoma (LUAD) A549 cell, yet its broader functions and regulatory mechanisms in LUAD remain elusive.

METHODS

Using a LUAD tissue microarray and immunohistochemical (IHC) staining, we validated variations in DUS4L protein expression levels among LUAD patients and assessed its clinical significance. Additional experiments using short hairpin RNA (shRNA) against DUS4L (sh-DUS4L-2), LUAD cell lines, cell function assays (including wound healing, transwell migration and invasion, colony formation, and apoptosis assays), and mouse tumor xenografts were performed to examine the biological roles of DUS4L in LUAD progression. RNA sequencing, proteomic analyses, mass spectrometry, and co-immunoprecipitation experiments were conducted to identify and validate DUS4L-regulated downstream target genes and signaling pathways.

RESULTS

We identified a consistent upregulation of DUS4L in LUAD tissues. In vitro and in vivo experiments underscored the inhibitory effect of DUS4L downregulation on LUAD progression, including migration, invasion, and proliferation. Mechanistically, DUS4L was found to interact with the signaling molecule GRB2, promoting LUAD progression and metastasis by inducing epithelial-mesenchymal transition (EMT) via the PI3K/AKT and ERK/MAPK pathways.

CONCLUSION

Our results establish the functional role of DUS4L in driving the progression and metastasis of LUAD, implicating its potential as a candidate therapeutic target for LUAD.

Degradation of PARP1 by MARCHF3 in tumor cells triggers cCAS-STING activation in dendritic cells to regulate antitumor immunity in hepatocellular carcinoma

BACKGROUND

Resistance to immune checkpoint inhibitors (ICIs) significantly limits the efficacy of immunotherapy in patients with hepatocellular carcinoma (HCC). However, the mechanisms underlying immunotherapy resistance remain poorly understood. Our aim was to clarify the role of membrane-associated ring-CH-type finger 3 (MARCHF3) in HCC within the framework of anti-programmed cell death protein-1 (PD-1) therapy.

METHODS

MARCHF3 was identified in the transcriptomic profiles of HCC tumors exhibiting different responses to ICIs. In humans, the correlation between MARCHF3 expression and the tumor microenvironment (TME) was assessed via multiplex immunohistochemistry. In addition, MARCHF3 expression in tumor cells and immune cell infiltration were assessed by flow cytometry.

RESULTS

MARCHF3 was significantly upregulated in tumors from patients who responded to ICIs. Increased MARCHF3 expression in HCC cells promoted dendritic cell (DC) maturation and stimulated CD8+ T-cell activation, thereby augmenting tumor control. Mechanistically, we identified MARCHF3 as a pivotal regulator of the DNA damage response. It directly interacted with Poly(ADP-Ribose) Polymerase 1 (PARP1) via K48-linked ubiquitination, leading to PARP1 degradation. This process promoted the release of double-strand DNA and activated cCAS-STING in DCs, thereby initiating DC-mediated antigen cross-presentation and CD8+ T-cell activation. Additionally, ATF4 transcriptionally regulated MARCHF3 expression. Notably, the PARP1 inhibitor olaparib augmented the efficacy of anti-PD-1 immunotherapy in both subcutaneous and orthotopic HCC mouse models.

CONCLUSIONS

MARCHF3 has emerged as a pivotal regulator of the immune landscape in the HCC TME and is a potent predictive biomarker for HCC. Combining interventions targeting the DNA damage response with ICIs is a promising treatment strategy for HCC.

RNF19A inhibits bladder cancer progression by regulating ILK ubiquitination and inactivating the AKT/mTOR signalling pathway

BACKGROUND

The role of the RING finger protein superfamily in carcinogenesis has been widely studied, but one member of this family, RNF19A, has not yet been thoroughly explored in bladder cancer (BCa).

METHODS

The expression levels of RNF19A in BCa samples and cell lines were analysed through data mining of public resources and further experiments. BCa cells in which RNF19A was stably overexpressed or knocked down were generated through lentivirus infection. The effects of RNF19A on cell proliferation, migration, and invasion were explored by performing a series of in vitro experiments, including CCK-8, colony formation, wound healing, and Transwell invasion assays. Using bioinformatics methods and multiple experiments, including western blot, qRT‒PCR, immunoprecipitation, cycloheximide, ubiquitination, and rescue assays, the mechanism underlying the effect of RNF19A on the progression of BCa was investigated.

RESULTS

Here, we found that RNF19A expression was reduced in BCa samples and cell lines and that lower RNF19A expression predicted shorter overall survival of BCa patients. Functionally, forced expression of RNF19A suppressed BCa cell proliferation, migration, and invasion by inactivating the AKT/mTOR signalling pathway, whereas silencing RNF19A had the opposite effects. Mechanistically, RNF19A could directly interact with ILK and promote its ubiquitination and degradation. Rescue experiments revealed that forced ILK expression partially rescued the decreased phosphorylation of AKT, mTOR, and S6K1 caused by RNF19A overexpression and that the increased levels of the p-AKT, p-mTOR, and p-S6K1 proteins induced by RNF19A knockdown were eliminated after silencing ILK. Similarly, the effects of RNF19A overexpression or knockdown on the phenotypes of cell proliferation, migration, and invasion could also be restored by forced or decreased ILK expression.

CONCLUSIONS

RNF19A suppressed the proliferation, migration, and invasion abilities of BCa cells by regulating ILK ubiquitination and inactivating the AKT/mTOR signalling pathway. RNF19A might be a potential prognostic biomarker and promising therapeutic target for BCa.

Signaling, cancer cell plasticity, and intratumor heterogeneity

Cancer's complexity is in part due to the presence of intratumor heterogeneity and the dynamic nature of cancer cell plasticity, which create substantial obstacles in effective cancer management. Variability within a tumor arises from the existence of diverse populations of cancer cells, impacting the progression, spread, and resistance to treatments. At the core of this variability is the concept of cellular plasticity - the intrinsic ability of cancer cells to alter their molecular and cellular identity in reaction to environmental and genetic changes. This adaptability is a cornerstone of cancer's persistence and progression, making it a formidable target for treatments. Emerging studies have emphasized the critical role of such plasticity in fostering tumor diversity, which in turn influences the course of the disease and the effectiveness of therapeutic strategies. The transformative nature of cancer involves a network of signal transduction pathways, notably those that drive the epithelial-to-mesenchymal transition and metabolic remodeling, shaping the evolutionary path of cancer cells. Despite advancements, our understanding of the precise molecular machinations and signaling networks driving these changes is still evolving, underscoring the necessity for further research. This editorial presents a series entitled "Signaling Cancer Cell Plasticity and Intratumor Heterogeneity" in Cell Communication and Signaling, dedicated to unraveling these complex processes and proposing new avenues for therapeutic intervention.

S. Systems and computational analysis of gene expression datasets reveals GRB-2 suppression as an acute immunomodulatory response against enteric infections in endemic settings

Introduction

Enteric infections are a major cause of under-5 (age) mortality in low/middle-income countries. Although vaccines against these infections have already been licensed, unwavering efforts are required to boost suboptimalefficacy and effectiveness in regions that are highly endemic to enteric pathogens. The role of baseline immunological profiles in influencing vaccine-induced immune responses is increasingly becoming clearer for several vaccines. Hence, for the development of advanced and region-specific enteric vaccines, insights into differences in immune responses to perturbations in endemic and non-endemic settings become crucial.

Materials and methods

For this reason, we employed a two-tiered system and computational pipeline (i) to study the variations in differentially expressed genes (DEGs) associated with immune responses to enteric infections in endemic and non-endemic study groups, and (ii) to derive features (genes) of importance that keenly distinguish between these two groups using unsupervised machine learning algorithms on an aggregated gene expression dataset. The derived genes were further curated using topological analysis of the constructed STRING networks. The findings from these two tiers are validated using multilayer perceptron classifier and were further explored using correlation and regression analysis for the retrieval of associated gene regulatory modules.

Results

Our analysis reveals aggressive suppression of GRB-2, an adaptor molecule integral for TCR signaling, as a primary immunomodulatory response against S. typhi infection in endemic settings. Moreover, using retrieved correlation modules and multivariant regression models, we found a positive association between regulators of activated T cells and mediators of Hedgehog signaling in the endemic population, which indicates the initiation of an effector (involving differentiation and homing) rather than an inductive response upon infection. On further exploration, we found STAT3 to be instrumental in designating T-cell functions upon early responses to enteric infections in endemic settings.

Conclusion

Overall, through a systems and computational biology approach, we characterized distinct molecular players involved in immune responses to enteric infections in endemic settings in the process, contributing to the mounting evidence of endemicity being a major determiner of pathogen/vaccine-induced immune responses. The gained insights will have important implications in the design and development of region/endemicity-specific vaccines.

Assessing TGF-β Prognostic Model Predictions for Chemotherapy Response and Oncogenic Role of FKBP1A in Liver Cancer

BACKGROUND

The Transforming Growth Factor-Beta (TGF-β) signaling pathway plays a crucial role in the pathogenesis of diseases. This study aimed to identify differentially expressed TGF-β-related genes in liver cancer patients and to correlate these findings with clinical features and immune signatures.

METHODS

The TCGA-STAD and LIRI-JP cohorts were utilized for a comprehensive analysis of TGF-β- related genes. Differential gene expression, functional enrichment, survival analysis, and machine learning techniques were employed to develop a prognostic model based on a TGF-β-related gene signature (TGFBRS).

RESULTS

We developed a prognostic model for liver cancer based on the expression levels of nine TGF-β- related genes. The model indicates that higher TGFBRS values are associated with poorer prognosis, higher tumor grades, more advanced pathological stages, and resistance to chemotherapy. Additionally, the TGFBRS-High subtype was characterized by elevated levels of immune-suppressive cells and increased expression of immune checkpoint molecules. Using a Gradient Boosting Decision Tree (GBDT) machine learning approach, the FKBP1A gene was identified as playing a significant role in liver cancer. Notably, knocking down FKBP1A significantly inhibited the proliferation and metastatic capabilities of liver cancer cells both in vitro and in vivo.

CONCLUSION

Our study highlights the potential of TGFBRS in predicting chemotherapy responses and in shaping the tumor immune microenvironment in liver cancer. The results identify FKBP1A as a promising molecular target for developing preventive and therapeutic strategies against liver cancer. Our findings could potentially guide personalized treatment strategies to improve the prognosis of liver cancer patients.