Suppression of the ABCA1 Cholesterol Transporter Impairs the Growth and Migration of Epithelial Ovarian Cancer

Multiplex immunohistochemistry defines two cholesterol metabolism patterns predicting immunotherapeutic outcomes in gastric cancer

BACKGROUND

The role of cholesterol metabolism in gastric cancer (GC) and its implications for tumor characteristics and immunotherapy response remain poorly understood. In this study, our aim was to investigate this role, identify associated metabolic subtypes, and assess their clinical implications in GC.

METHODS

We conducted a comprehensive analysis of cholesterol metabolism genes (CMGs) using transcriptomic data from TCGA and GEO. Based on 23 representative CMGs, we classified GC into metabolic subtypes. We evaluated clinical features and immune cell infiltration between these subtypes. Additionally, we identified a CMG signature and assessed its clinical relevance in GC. We retrospectively enrolled thirty-five GC patients receiving chemotherapy plus a PD-1 inhibitor to assess the CMG signature using multiplex immunohistochemistry.

RESULTS

Our analysis revealed two cholesterol metabolism subtypes in GC: Cholesterol Metabolism Type 1 (CMT1) and Cholesterol Metabolism Type 2 (CMT2). These subtypes exhibited distinct patterns: CMT1 indicated heightened cholesterol biosynthesis, while CMT2 showed abnormal cholesterol transport. CMT2 was associated with unfavorable clinical features, enriched malignant pathways, and a pro-tumor immune microenvironment. Furthermore, we developed a five-CMG prognostic signature (ABCA1, NR1H3, TSPO, NCEH1, and HMGCR) that effectively predicted the prognosis of patients with GC and their response to chemotherapy plus a PD-1 inhibitor. This signature was validated in a clinical cohort using multiplex immunohistochemistry.

CONCLUSION

Our results highlight the effectiveness of cholesterol metabolism patterns as biomarkers for predicting the prognosis and immunotherapy response in GC. The expression of cholesterol metabolism genes and the assessment of cholesterol metabolism patterns have the potential to predict the outcome of immunotherapy and guide treatment strategies.

Targeting dysregulated lipid metabolism in the tumor microenvironment

The reprogramming of lipid metabolism and its association with oncogenic signaling pathways within the tumor microenvironment (TME) have emerged as significant hallmarks of cancer. Lipid metabolism is defined as a complex set of molecular processes including lipid uptake, synthesis, transport, and degradation. The dysregulation of lipid metabolism is affected by enzymes and signaling molecules directly or indirectly involved in the lipid metabolic process. Regulation of lipid metabolizing enzymes has been shown to modulate cancer development and to avoid resistance to anticancer drugs in tumors and the TME. Because of this, understanding the metabolic reprogramming associated with oncogenic progression is important to develop strategies for cancer treatment. Recent advances provide insight into fundamental mechanisms and the connections between altered lipid metabolism and tumorigenesis. In this review, we explore alterations to lipid metabolism and the pivotal factors driving lipid metabolic reprogramming, which exacerbate cancer progression. We also shed light on the latest insights and current therapeutic approaches based on small molecular inhibitors and phytochemicals targeting lipid metabolism for cancer treatment. Further investigations are worthwhile to fully understand the underlying mechanisms and the correlation between altered lipid metabolism and carcinogenesis.

Integrated analysis of single-cell and bulk RNA-sequencing reveals the poor prognostic value of ABCA1 in gastric adenocarcinoma

PURPOSE

ATP-binding cassette A1 (ABCA1) is a potential prognostic marker for various tumor types. However, the biological effects and prognostic value of ABCA1 in gastric adenocarcinoma (GAC) remain unknown.

METHODS

GAC-associated single-cell RNA and bulk RNA-sequencing (bulk-seq) data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. The differential expression of ABCA1 between GAC and normal gastric tissues was analyzed based on the bulk-seq data. Additionally, the relationship between ABCA1 expression and various clinicopathological features was explored. Furthermore, Kaplan-Meier survival and Cox regression analyses were performed to establish the prognostic value of ABCA1. The relationships between ABCA1 expression and anti-tumor drug sensitivity and immune checkpoints were also explored. Finally, the biological functions of ABCA1 were evaluated at the single-cell level, and in vitro studies were performed to assess the effects of ABCA1 on GAC cell proliferation and invasion.

RESULTS

ABCA1 expression is significantly elevated in GAC samples compared with that in normal gastric tissues. Clinical features and survival analysis revealed that high ABCA1 expression is associated with poor clinical phenotypes and prognosis, whereas Cox analysis identified ABCA1 as an independent risk factor for patients with GAC. Furthermore, high ABCA1 expression suppresses sensitivity to various chemotherapeutic drugs, including cisplatin and mitomycin, while upregulating immune checkpoints. ABCA1-overexpressing macrophages are associated with adverse clinical phenotypes in GAC and express unique ligand-receptor pairs that drive GAC progression. In vitro, ABCA1-knockdown GAC cells exhibit significantly inhibited proliferative and invasive properties.

CONCLUSION

High ABCA1 expression promotes an adverse immune microenvironment and low survival rates in patients with GAC. Furthermore, ABCA1 and ABCA1-producing macrophages may serve as novel molecular targets in GAC treatment.

Drug metabolism-related gene ABCA1 augments temozolomide chemoresistance and immune infiltration abundance of M2 macrophages in glioma

Gliomas are the most prevalent primary tumor in the central nervous system, with an abysmal 5-year survival rate and alarming mortality. The current standard management of glioma is maximum resection of tumors followed by postoperative chemotherapy with temozolomide (TMZ) or radiotherapy. Low chemosensitivity of TMZ in glioma treatment eventuates limited therapeutic efficacy or treatment failure. Hence, overcoming the resistance of glioma to TMZ is a pressing question. Our research centered on identifying the drug metabolism-related genes potentially involved in TMZ-treated resistance of glioma through several bioinformatics datasets and cell experiments. One efflux transporter, ATP-binding cassette transporter subfamily A1 (ABCA1), was discovered with an upregulated expression level and signaled poor clinical outcomes for glioma patients. The transcript level of ABCA1 significantly elevated across the TMZ-resistant glioma cells in contrast with non-resistant cells. Over-expressed ABCA1 restrained the drug activity of TMZ, and ABCA1 knockdown improved the treatment efficacy. Meanwhile, the results of molecular docking between ABCA1 protein and TMZ showed a high binding affinity. Additionally, co-expression and immunological analysis revealed that ABCA1 facilitates the immune infiltration of M2 macrophages in glioma, thereby stimulating tumor growth and aggravating the poor survival of patients. Altogether, we discovered that the ABCA1 transporter was involved in TMZ chemoresistance and the immune infiltration of M2 macrophages in glioma. Treatment with TMZ after ABCA1 knockdown enhances the chemosensitivity, suggesting that inhibition of ABCA1 may be a potential strategy for improving the therapeutic efficacy of gliomas.

The utility of 3D models to study cholesterol in cancer: Insights and future perspectives

Cholesterol remains a vital molecule required for life; however, increasing evidence exists implicating cholesterol in cancer development and progression. Numerous studies investigating the relationship between cholesterol and cancer in 2-dimensional (2D) culture settings exist, however these models display inherent limitations highlighting the incipient need to develop better models to study disease pathogenesis. Due to the multifaceted role cholesterol plays in the cell, researchers have begun utilizing 3-dimensional (3D) culture systems, namely, spheroids and organoids to recapitulate cellular architecture and function. This review aims to describe current studies exploring the relationship between cancer and cholesterol in a variety of cancer types using 3D culture systems. We briefly discuss cholesterol dyshomeostasis in cancer and introduce 3D in-vitro culture systems. Following this, we discuss studies performed in cancerous spheroid and organoid models that focused on cholesterol, highlighting the dynamic role cholesterol plays in various cancer types. Finally, we attempt to provide potential gaps in research that should be explored in this rapidly evolving field of study.

Simultaneous Detection of Ovarian Cancer-Concerned HE4 and CA125 Markers Based on Cu Single-Atom-Triggered CdS QDs and Eu MOF@Isoluminol ECL

Simultaneous detection of different disease markers is significant for clinical diagnosis. In this work, a dual-signal electrochemiluminescence (ECL) immunosensor was constructed for the simultaneous detection of carbohydrate antigen 125 (CA125) and human epithelial protein 4 (HE4) markers of ovarian cancer. The results showed that the Eu metal-organic framework-loaded isoluminol-Au nanoparticles (Eu MOF@Isolu-Au NPs) could generate a strong anodic ECL signal through synergistic interaction; as cathodic luminophore, the composite of carboxyl-functionalized CdS quantum dots and N-doped porous carbon-anchored Cu single-atom catalyst could catalyze H₂O₂ co-reactant to produce a large amount of ^•OH and O₂^•-, making the anodic and cathodic ECL signals significantly increase and become stable. Based on the enhancement strategy, a sandwich immunosensor was constructed for the simultaneous detection of ovarian cancer-associated CA125 and HE4 markers by combining antigen-antibody specific recognition and magnetic separation technique. The resulting ECL immunosensor displayed high sensitivity, a wide linear response range of 0.005∼500 ng mL^-1, and low detection limits of 0.37 and 1.58 pg mL^-1 for CA125 and HE4, respectively. Furthermore, it had excellent selectivity, stability, and practicability in the detection of real serum samples. This work establishes a framework for in-depth design and application of single-atom catalysis in ECL sensing.

Promotion of colorectal cancer cell death by ezetimibe via mTOR signaling-dependent mitochondrial dysfunction

Introduction: Colorectal cancer (CRC) is the fourth most common cancer worldwide, with high morbidity and mortality rates. In recent years, high-fat diet has been shown to increase CRC morbidity, highlighting the possibility of the application of hypolipidemic drugs for CRC treatment. In this study, we preliminarily evaluated the effects and mechnisms of ezetimibe against CRC through the blockage of lipid absorption in small intesine. Methods: In this study, CRC cell proliferation, invasion, apoptosis, and autophagy were evaluated using cellular and molecular assays. Fluorescent microscopy, and a flow cytometric assay were used to assess mitochondrial activity in vitro. A subcutaneous xenograft mouse model was used to evaluate the effects of ezetimibe in vivo. Results: We found that ezetimibe inhibited CRC cell proliferation, and migration, and facilitated autophage-associated apoptosis in HCT116 and Caco2 cells. Ezetimibe-induced mitochondrial dysfunction in CRC cells was found to be correlated with mTOR signaling activity. Discussion: Ezetimibe exhibits effects against CRC through the promotion of cancer cell death via mTOR signaling-dependent mitochondrial dysfunction, highlighting its potential value in CRC therapy.

Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

Background

Gastric cancer is one of the common malignant tumors of the digestive system worldwide, posing a serious threat to human health. A growing number of studies have demonstrated the important role that lipid droplets play in promoting cancer progression. However, few studies have systematically evaluated the role of lipid droplet metabolism-related genes (LDMRGs) in patients with gastric cancer.

Methods

We identified two distinct molecular subtypes in the TCGA-STAD cohort based on LDMRGs expression. We then constructed risk prediction scoring models in the TCGA-STAD cohort by lasso regression analysis and validated the model with the GSE15459 and GSE66229 cohorts. Moreover, we constructed a nomogram prediction model by cox regression analysis and evaluated the predictive efficacy of the model by various methods in STAD. Finally, we identified the key gene in LDMRGs, ABCA1, and performed a systematic multi-omics analysis in gastric cancer.

Results

Two molecular subtypes were identified based on LDMRGs expression with different survival prognosis and immune infiltration levels. lasso regression models were effective in predicting overall survival (OS) of gastric cancer patients at 1, 3 and 5 years and were validated in the GEO database with consistent results. The nomogram prediction model incorporated additional clinical factors and prognostic molecules to improve the prognostic predictive value of the current TNM staging system. ABCA1 was identified as a key gene in LDMRGs and multi-omics analysis showed a strong correlation between ABCA1 and the prognosis and immune status of patients with gastric cancer.

Conclusion

This study reveals the characteristics and possible underlying mechanisms of LDMRGs in gastric cancer, contributing to the identification of new prognostic biomarkers and providing a basis for future research.

ARL4C depletion suppresses the resistance of ovarian cancer to carboplatin by disrupting cholesterol transport and autophagy via notch-RBP-Jκ-H3K4Me3-OSBPL5

Increasing studies indicate that cholesterol plays an important role in drug resistance. ARL4C is implicated in the export and import of cholesterol, therefore this study aimed to explore the effect of ARL4C on the resistance of ovarian cancer (OVC) to Carboplatin. This study collected OVC tissue samples from patients who are sensitive or resistant to carboplatin, and established Carboplatin-resistant OVC cell lines, OVCAR3(R) and SKOV3(R) using OVCAR3 and SKOV3. High throughput sequencing was conducted to find genes that regulated by ARL4C. Cholesterol esterification was performed to evaluate the transport of cholesterol from Lysosome (LY) to Endoplasmic reticulum (ER). The fluorescence of LC3-GFP-mRFP was used to evaluate the function of autophagy flux. As indicated by PCR, western blot and Immunohistochemistry, ARL4C was increased in the Carboplatin-resistant OVC tissues and cells. Knockdown of ARL4C attenuated the resistance of OVCAR3(R) and SKOV3(R) to Carboplatin. By suppressing Notch signal, ARL4C knockdown inhibited the transcriptional function of RBP-Jκ and RBP-Jκ-induced H3K4Me3, which collectively reduced OSBPL5 expression. OSBPL5 deficiency inhibited the transport of cholesterol from LYs to ER, which led to the accumulation of cholesterol in LYs and the dysfunction of autophagy. In summary, ARL4C knockdown attenuated the resistance of OVC to Carboplatin by disrupting cholesterol transport and autophagy. This study revealed a promising target to attenuate the resistance of OVC to Carboplatin and elucidated the potential mechanism.