Silencing of ARL14 Gene Induces Lung Adenocarcinoma Cells to a Dormant State

Mapping the global interactome of the ARF family reveals spatial organization in cellular signaling pathways

The ADP-ribosylation factors (ARFs) and ARF-like (ARL) GTPases serve as essential molecular switches governing a wide array of cellular processes. In this study, we used proximity-dependent biotin identification (BioID) to comprehensively map the interactome of 28 out of 29 ARF and ARL proteins in two cellular models. Through this approach, we identified ∼3000 high-confidence proximal interactors, enabling us to assign subcellular localizations to the family members. Notably, we uncovered previously undefined localizations for ARL4D and ARL10. Clustering analyses further exposed the distinctiveness of the interactors identified with these two GTPases. We also reveal that the expression of the understudied member ARL14 is confined to the stomach and intestines. We identified phospholipase D1 (PLD1) and the ESCPE-1 complex, more precisely, SNX1, as proximity interactors. Functional assays demonstrated that ARL14 can activate PLD1 in cellulo and is involved in cargo trafficking via the ESCPE-1 complex. Overall, the BioID data generated in this study provide a valuable resource for dissecting the complexities of ARF and ARL spatial organization and signaling.

Unveiling cancer dormancy: Intrinsic mechanisms and extrinsic forces

Tumor cells disseminate in various distant organs at early stages of cancer progression. These disseminated tumor cells (DTCs) can stay dormant/quiescent without causing patient symptoms for years or decades. These dormant tumor cells survive despite curative treatments by entering growth arrest, escaping immune surveillance, and/or developing drug resistance. However, these dormant cells can reactivate to proliferate, causing metastatic progression and/or relapse, posing a threat to patients' survival. It's unclear how cancer cells maintain dormancy and what triggers their reactivation. What are better approaches to prevent metastatic progression and relapse through harnessing cancer dormancy? To answer these remaining questions, we reviewed the studies of tumor dormancy and reactivation in various types of cancer using different model systems, including the brief history of dormancy studies, the intrinsic characteristics of dormant cells, and the external cues at the cellular and molecular levels. Furthermore, we discussed future directions in the field and the strategies for manipulating dormancy to prevent metastatic progression and recurrence.

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

Mapping the global interactome of the ARF family reveals spatial organization in cellular signaling pathways

The ADP-ribosylation factors (ARFs) and ARF-like (ARLs) GTPases serve as essential molecular switches governing a wide array of cellular processes. In this study, we utilized proximity-dependent biotin identification (BioID) to comprehensively map the interactome of 28 out of 29 ARF and ARL proteins in two cellular models. Through this approach, we identified ~3000 high-confidence proximal interactors, enabling us to assign subcellular localizations to the family members. Notably, we uncovered previously undefined localizations for ARL4D and ARL10. Clustering analyses further exposed the distinctiveness of the interactors identified with these two GTPases. We also reveal that the expression of the understudied member ARL14 is confined to the stomach and intestines. We identified phospholipase D1 (PLD1) and the ESCPE-1 complex, more precisely SNX1, as proximity interactors. Functional assays demonstrated that ARL14 can activate PLD1 in cellulo and is involved in cargo trafficking via the ESCPE-1 complex. Overall, the BioID data generated in this study provide a valuable resource for dissecting the complexities of ARF and ARL spatial organization and signaling.

Dormant cancer cells and polyploid giant cancer cells: The roots of cancer recurrence and metastasis

Tumour cell dormancy is critical for metastasis and resistance to chemoradiotherapy. Polyploid giant cancer cells (PGCCs) with giant or multiple nuclei and high DNA content have the properties of cancer stem cell and single PGCCs can individually generate tumours in immunodeficient mice. PGCCs represent a dormant form of cancer cells that survive harsh tumour conditions and contribute to tumour recurrence. Hypoxic mimics, chemotherapeutics, radiation and cytotoxic traditional Chinese medicines can induce PGCCs formation through endoreduplication and/or cell fusion. After incubation, dormant PGCCs can recover from the treatment and produce daughter cells with strong proliferative, migratory and invasive abilities via asymmetric cell division. Additionally, PGCCs can resist hypoxia or chemical stress and have a distinct protein signature that involves chromatin remodelling and cell cycle regulation. Dormant PGCCs form the cellular basis for therapeutic resistance, metastatic cascade and disease recurrence. This review summarises regulatory mechanisms governing dormant cancer cells entry and exit of dormancy, which may be used by PGCCs, and potential therapeutic strategies for targeting PGCCs.

Phosphorylation and stabilization of EZH2 by DCAF1/VprBP trigger aberrant gene silencing in colon cancer

Our recent work has shown that DCAF1 (also known as VprBP) is overexpressed in colon cancer and phosphorylates histone H2AT120 to drive epigenetic gene inactivation and oncogenic transformation. We have extended these observations by investigating whether DCAF1 also phosphorylates non-histone proteins as an additional mechanism linking its kinase activity to colon cancer development. We now demonstrate that DCAF1 phosphorylates EZH2 at T367 to augment its nuclear stabilization and enzymatic activity in colon cancer cells. Consistent with this mechanistic role, DCAF1-mediated EZH2 phosphorylation leads to elevated levels of H3K27me3 and altered expression of growth regulatory genes in cancer cells. Furthermore, our preclinical studies using organoid and xenograft models revealed that EZH2 requires phosphorylation for its oncogenic function, which may have therapeutic implications for gene reactivation in colon cancer cells. Together, our data define a mechanism underlying DCAF1-driven colonic tumorigenesis by linking DCAF1-mediated EZH2 phosphorylation to EZH2 stability that is crucial for establishing H3K27me3 and gene silencing program.

ARL9 is upregulated and serves as a biomarker for a poor prognosis in colon adenocarcinoma

BACKGROUND

ARL9 is a newly identified member of the ARF family, and the clinical significance of ARL9 in colon adenocarcinoma is unknown. In this study, we aimed to explore the expression of ARL9 mRNA in colon adenocarcinoma, and its effect on the prognosis of patients with colon adenocarcinoma.

METHODS

We investigated the differential expression of ARL9 between colon adenocarcinoma tissue and adjacent tissues through a bioinformatics analysis using The Cancer Genome Atlas (TCGA) database. The correlation between clinical characteristics and the mRNA expression level of ARL9 were analyzed. A survival analysis and a Cox regression analysis were used to determine the prognostic significance of ARL9. Finally, we conducted a gene set enrichment analysis (GSEA) to explore the ARL9 signaling pathways involved in the development of colon adenocarcinoma. The effect of the expression of ARL9 on the proliferation and migration of colon adenocarcinoma was analyzed by the CCK8 method and a cell scratch test, respectively.

RESULTS

The mRNA expression of ARL9 in colon adenocarcinoma tissues was higher in comparison to the level in normal adjacent tissues (P < 0.05). The mRNA expression of ARL9 was not related to sex, tumor stage, T stage, N stage, M stage, but to age. The 5-year survival rate of colon adenocarcinoma patients with high ARL9 mRNA expression levels was significantly lower than that of patients with low ARL9 mRNA expression levels (P < 0.05). Age and the high mRNA expression of ARL9 were independent risk factors for a poor prognosis in patients with colon adenocarcinoma. The GSEA suggested that ARL9 may be able to upregulate cell adhesion, extracellular matrix receptor interactions, tumor-associated pathways, and downregulate the citrate cycle and tricarboxylic acid cycle pathway, which are involved in the development of colon adenocarcinoma. After knocking down ARL9, the proliferation and migration abilities of colon adenocarcinoma cells were decreased (P < 0.01).

CONCLUSION

The mRNA expression of ARL9 is upregulated in colon adenocarcinoma, and higher mRNA expression levels are associated with a poor prognosis. Knocking down ARL9 can reduce the proliferation and migration of colon adenocarcinoma cells. ARL9 mRNA can be used as a prognostic biomarker in patients with colon adenocarcinoma.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

A new risk model for CSTA, FAM83A, and MYCT1 predicts poor prognosis and is related to immune infiltration in lung squamous cell carcinoma

OBJECTIVES

To create a prognostic model based on differentially expressed genes (DEGs) in early lung squamous cell carcinoma (LUSC) and characterize the relationship between risk scores and tumor immune infiltration.

METHODS

We identified DEGs in normal and tumor tissues that overlapped between LUSC-related data sets from the Gene Expression Omnibus and the Cancer Genome Atlas and evaluated their roles in the diagnosis and prognosis of LUSC by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) analysis, meta-analysis and nomogram analysis. We then constructed a risk model based on Cox regression analysis and the Akaike information criterion and identified the relationship between LUSC risk scores and immune infiltration.

RESULTS

Sixty-two overlapping DEGs were involved with keratinocyte differentiation, epidermal cell differentiation, neutrophil migration, granulocyte chemotaxis, granulocyte migration, leukocyte aggregation, and positive regulation of nuclear factor-κB (NF-κB) activity. Overexpression of family with sequence similarity 83 member A (FAM83A) and MYC target 1 (MYCT1), kallikrein related peptidase 8 (KLK8), and downregulation of ADP ribosylation factor like GTPase 14 (ARL14), caspase recruitment domain family member 14 (CARD14), cystatin A (CSTA), dickkopf WNT signaling pathway inhibitor 4 (DKK4), desmoglein 3 (DSG3), and keratin 6B (KRT6B) were associated with a poor prognosis in LUSC and had significant value for LUSC diagnosis. The expression of CSTA, FAM83A, and MYCT1 and high-risk scores were independent risk factors for a poor prognosis in LUSC. A risk nomogram revealed that risk scores could predict the prognosis of LUSC. The risk score was associated with neutrophils, naive B cells, helper follicular T cells, and activated dendritic cells.

CONCLUSIONS

The expression levels of CSTA, FAM83A, and MYCT1 are related to the diagnosis and prognosis of LUSC and may have potential as therapeutic targets in LUSC. A risk model and nomogram based on CSTA, FAM83A, and MYCT1 can predict the prognosis of LUSC.

Recent Advances on the Role of ATGL in Cancer

The hypoxic state of the tumor microenvironment leads to reprogramming lipid metabolism in tumor cells. Adipose triglyceride lipase, also known as patatin-like phospholipase= domain-containing protein 2 and Adipose triglyceride lipase (ATGL), as an essential lipid metabolism-regulating enzyme in cells, is regulated accordingly under hypoxia induction. However, studies revealed that ATGL exhibits both tumor-promoting and tumor-suppressing effects, which depend on the cancer cell type and the site of tumorigenesis. For example, elevated ATGL expression in breast cancer is accompanied by enhanced fatty acid oxidation (FAO), enhancing cancer cells’ metastatic ability. In prostate cancer, on the other hand, tumor activity tends to be negatively correlated with ATGL expression. This review outlined the regulation of ATGL-mediated lipid metabolism pathways in tumor cells, emphasizing the Hypoxia-inducible factors 1 (HIF-1)/Hypoxia-inducible lipid droplet-associated (HIG-2)/ATGL axis, peroxisome proliferator-activated receptor (PPAR)/G0/G1 switch gene 2 (G0S2)/ATGL axis, and fat-specific protein 27 (FSP-27)/Early growth response protein 1 (EGR-1)/ATGL axis. In the light of recent research on different cancer types, the role of ATGL on tumorigenesis, tumor proliferation, and tumor metastasis was systemically reviewed.

Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.

Methods

The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.

Results

We constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.

Conclusion

Our study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.

SIGNET: single-cell RNA-seq-based gene regulatory network prediction using multiple-layer perceptron bagging

High-throughput single-cell RNA-seq data have provided unprecedented opportunities for deciphering the regulatory interactions among genes. However, such interactions are complex and often nonlinear or nonmonotonic, which makes their inference using linear models challenging. We present SIGNET, a deep learning-based framework for capturing complex regulatory relationships between genes under the assumption that the expression levels of transcription factors participating in gene regulation are strong predictors of the expression of their target genes. Evaluations based on a variety of real and simulated scRNA-seq datasets showed that SIGNET is more sensitive to ChIP-seq validated regulatory interactions in different types of cells, particularly rare cells. Therefore, this process is more effective for various downstream analyses, such as cell clustering and gene regulatory network inference. We demonstrated that SIGNET is a useful tool for identifying important regulatory modules driving various biological processes.

ARL14 as a Prognostic Biomarker in Non-Small Cell Lung Cancer

Purpose

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. The mechanisms underlying NSCLC initiation and progression require further investigation. The purpose of this study was to investigate the role of ADP ribosylation factor-like GTPase 14 (ARL14) related to the progression of NSCLC.

Patients and Methods

We analyzed the correlation between clinical characteristics and ARL14 expression using data from The Cancer Genome Atlas (TCGA). Kaplan–Meier analysis was conducted to evaluate the prognostic value of ARL14 in NSCLC. Functions of ARL14 were identified by enrichment analysis. The relationship between ARL14 expression and immune cell infiltration was also studied. Furthermore, ARL14 expression was examined using immunohistochemistry, and its clinical significance was analyzed in 120 patients with NSCLC.

Results

Our study revealed that the expression level of ARL14 in patients with NSCLC was higher than that in normal tissues. Using TCGA data, higher ARL14 expression in lung adenocarcinoma was associated with residual tumor (P = 0.017), while it was associated with age (P = 0.003) and N stage (P = 0.009) in lung squamous cell carcinoma. Similar results were obtained from 120 patients with NSCLC. High ARL14 expression was associated with poor overall survival and progression-free survival in NSCLC. Multivariate analysis revealed that ARL14 was an independent risk factor for patients with NSCLC. Functional enrichment analysis indicated that ARL14 was related to the occurrence and development of tumors.

Conclusion

Increased ARL14 expression was considerably correlated with poor survival in NSCLC, and it might be a promising prognostic biomarker for NSCLC.

MicroRNA-302s Might Regulate ARL4C-Mediated Gastric Cancer Progression via p53 Signaling: Bioinformatics Analysis and Experiments Validation

Background

Our previous studies demonstrate that ARL4C is the most critical clinical biomarker for gastric cancer (GC) patients among ARL family members (ARLs) and functions as an oncogene in GC. However, its underlying mechanisms in GC need to be further illustrated. In this study, we aim to explore the upstream and downstream molecular mechanisms of ARL4C in GC cells.

Methods

The genetic alteration of ARL4C in GC is analyzed by cBioPortal database. Potential ARL4C-targeted microRNAs (miRs) are predicted by three databases. The high-throughput RNA sequencing is performed to explore the underlying mechanisms of ARL4C in GC cells. The effects of predicted microRNAs on ARL4C, the RNA-sequencing results validation and the biological functions of ARL4C in GC cells are illustrated by in vitro experiments.

Results

Genetic analyses indicate that ARL4C is significantly upregulated in GC, which is not caused by gene amplification. MicroRNAs prediction shows the high relevance between ARL4C and miR-302 members. Moreover, miR-302c or miR-302d transfection reduces ARL4C protein expression in GC cells. Based on the high-throughput RNA sequencing of ARL4C-knockdown cells, enrichment analyses demonstrate that ARL4C is closely related to cell growth and involved in p53 signaling. Moreover, there are strong gene–gene interactions between ARL4C and genes in p53 signaling, and ARL4C downregulation could inhibit the protein expression of MDM2, a critical gene in p53 pathway. Further functional experiments demonstrate that ARL4C silencing leads to cell cycle arrest and increased cell apoptosis in AGS and MKN45 cells.

Conclusion

Our data suggest that miR-302c and miR-302d may function as the upstream regulators of ARL4C. And, ARL4C might promote GC cell cycle progression via regulating p53 signaling. Our findings provide novel insights into the key role of ARL4C and the underlying mechanisms in GC progression, thus facilitating the development of ARL4C-targeted therapy.

The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective

The Adenosine diphosphate-Ribosylation Factor (ARF) family belongs to the RAS superfamily of small GTPases and is involved in a wide variety of physiological processes, such as cell proliferation, motility and differentiation by regulating membrane traffic and associating with the cytoskeleton. Like other members of the RAS superfamily, ARF family proteins are activated by Guanine nucleotide Exchange Factors (GEFs) and inactivated by GTPase-Activating Proteins (GAPs). When active, they bind effectors, which mediate downstream functions. Several studies have reported that cancer cells are able to subvert membrane traffic regulators to enhance migration and invasion. Indeed, members of the ARF family, including ARF-Like (ARL) proteins have been implicated in tumorigenesis and progression of several types of cancer. Here, we review the role of ARF family members, their GEFs/GAPs and effectors in tumorigenesis and cancer progression, highlighting the ones that can have a pro-oncogenic behavior or function as tumor suppressors. Moreover, we propose possible mechanisms and approaches to target these proteins, toward the development of novel therapeutic strategies to impair tumor progression.