Connecting Cholesterol Efflux Factors to Lung Cancer Biology and Therapeutics

lncRNAs: New players of cancer drug resistance via targeting ABC transporters

Cancer drug resistance poses a significant obstacle to successful chemotherapy, primarily driven by the activity of ATP-binding cassette (ABC) transporters, which actively efflux chemotherapeutic agents from cancer cells, reducing their intracellular concentrations and therapeutic efficacy. Recent studies have highlighted the pivotal role of long noncoding RNAs (lncRNAs) in regulating this resistance, positioning them as crucial modulators of ABC transporter function. lncRNAs, once considered transcriptional noise, are now recognized for their complex regulatory capabilities at various cellular levels, including chromatin modification, transcription, and post-transcriptional processing. This review synthesizes current research demonstrating how lncRNAs influence cancer drug resistance by modulating the expression and activity of ABC transporters. lncRNAs can act as molecular sponges, sequestering microRNAs that would otherwise downregulate ABC transporter genes. Additionally, they can alter the epigenetic landscape of these genes, affecting their transcriptional activity. Mechanistic insights reveal that lncRNAs contribute to the activity of ABC transporters, thereby altering the efflux of chemotherapeutic drugs and promoting drug resistance. Understanding these interactions provides a new perspective on the molecular basis of chemoresistance, emphasizing the regulatory network of lncRNAs and ABC transporters. This knowledge not only deepens our understanding of the biological mechanisms underlying drug resistance but also suggests novel therapeutic strategies. In conclusion, the intricate interplay between lncRNAs and ABC transporters is crucial for developing innovative solutions to combat cancer drug resistance, underscoring the importance of continued research in this field.

Intersecting Blood Cytokines With Cholesterol Parameters to Profile Patients With Advanced Solid Tumors Receiving Immune Checkpoint Inhibitors

The study investigated the relationship between serum proinflammatory cytokine levels, cholesterol metabolism, and clinical outcome in cancer patients undergoing immune checkpoint inhibitors (ICIs). Peripheral blood was collected before therapy from ICI-treated advanced cancer patients. We retrospectively assessed plasma total cholesterol (TC), ABCA1- and ABCG1-mediated cholesterol efflux (CE), passive diffusion (PD), cholesterol loading capacity (CLC), and serum IL-6, IL-10, and TNF-α. The association between blood cholesterol parameters and inflammatory cytokines and their effect on overall survival (OS), progression-free survival (PFS), and clinical benefit (CB) from ICIs were statistically assessed. Among 70 consecutively enrolled patients (nonsmall cell lung cancer: 94%; renal cell carcinoma: 6%), TC, CLC, and cholesterol PD resulted significantly higher in IL-6low and IL-10low cases (P<0.05), whereas ABCA1-mediated CE was increased in IL-10high patients (P=0.018). Uni- and multivariable analysis revealed meaningfully longer OS and PFS in IL-6low (HR 2.13 and 2.97, respectively) and IL-10low (HR 3.17 and 2.62) groups. At univariate analysis all cholesterol-related indices significantly correlated with OS and PFS, whereas at multivariate only high PD was validated as a protection factor (OS, HR 0.75; PFS, HR 0.84). Finally, uni- and multivariable showed a statistically significant inverse association of CB with ABCG1-CE (OR 0.62), as with IL-6 (OR 0.13) and IL-10 (OR 0.10). In-depth characterization of the interplay between blood cholesterol metabolism and immune-inflammatory cytokines might provide novel insights into the complex relationship among cancer, inflammation, lipids profile, and response to immunotherapy.

Prognostic models for immunotherapy in non-small cell lung cancer: A comprehensive review

The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.

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.

The role of blood cholesterol quality in patients with advanced cancer receiving immune checkpoint inhibitors

INTRODUCTION

Immune checkpoint inhibitors (ICIs) became the standard of care for several solid tumors. A limited fraction of patients (pts) achieves a long-term benefit. Plasmatic and intracellular cholesterol levels have emerged as promising biomarkers. The aim of the present study was to determine whether cholesterol efflux capacity (CEC), mediated by serum transporters (ABCA1 and ABCG1) and passive diffusion (PD), impacts on clinical outcome of advanced non-small cell lung cancer (NSCLC) and metastatic renal cell carcinoma (mRCC) pts treated with ICIs.

MATERIAL AND METHODS

We retrospectively enrolled advanced NSCLC and mRCC pts consecutively treated with ICIs between October 2013 and October 2018. CEC and cholesterol loading capacity (CLC) were assessed by well-established specific cell models. As primary endpoint, CEC, PD and CLC were correlated with overall survival (OS) while the effects of these parameters on progression-free survival (PFS) and clinical benefit (CB), defined as complete/partial response or stable disease, represented secondary endpoints.

RESULTS

NSCLC accounted for 94.2% of 70 enrolled cases, and serum sample suitable for CEC and PD determination was available in 68. Blood cholesterol and serum ABCA1, ABCG1, PD and CLC were associated with outcomes (OS, PFS and CB) at univariate analysis. At the multivariate analysis, only PD confirmed its positive prognostic value in terms of OS, PFS and CB.

CONCLUSION

The favorable impact of cholesterol PD on clinical outcome might reflect its main conformation in mature HDL particles which potentially shape an inflamed context, ultimately promoting ICI efficacy. Further prospective studies are needed to support our findings and uncover targetable pathways.

High nuclear ABCG1 expression is a poor predictor for hepatocellular carcinoma patient survival

BACKGROUND

ATP-binding cassette transporter G1 (ABCG1) regulates cellular cholesterol homeostasis and plays a significant role in tumor immunity. But, for hepatocellular carcinoma (HCC), the role of ABCG1 has not been investigated. Thus, the aim of this study was to evaluate the prognostic value and clinicopathological significance of ABCG1 in HCC.

METHODS

One hundred and four adult patients with HCC were enrolled, and ABCG1 expression in paired HCC specimens was determined by immunohistochemistry. All these patients were stratified by ABCG1 expression, Kaplan-Meier analysis was used to compare the overall survival (OS) and recurrence-free survival (RFS), and Cox regression analysis was used to determine independent predictors of tumor recurrence.

RESULTS

Upregulation of ABCG1 was observed in HCC samples compared to matched tumor-adjacent tissues. Patients with high nuclear ABCG1 expression had lower OS and RFS (P = 0.012 and P = 0.020, respectively). High nuclear ABCG1 expression was related to larger tumor size (P = 0.004) and tumor recurrence (P = 0.027). Although ABCG1 was expressed in the cytoplasm, cytosolic expression could not predict the outcome in patients with HCC. A new stratification pattern was established based on the heterogenous ABCG1 expression pattern: high risk (High^nucleus/Low^cytosol), moderate risk (High^nucleus/High^cytosol or Low^nucleus/Low^cytosol), and low risk (Low^nucleus/High^cytosol). This ABCG1-based risk stratification could distinguish the different OS and RFS in patients with HCC. Multivariate Cox regression analysis indicated that ABCG1 high risk was an independent predictor of poor RFS (P = 0.015).

CONCLUSIONS

High nuclear ABCG1 expression indicates poor prognosis in patients with HCC. Asymmetric distribution of ABCG1 in the nucleus and cytoplasm may have an important role in tumor recurrence.

Linking Late Endosomal Cholesterol with Cancer Progression and Anticancer Drug Resistance

Cancer cells undergo drastic metabolic adaptions to cover increased bioenergetic needs, contributing to resistance to therapies. This includes a higher demand for cholesterol, which often coincides with elevated cholesterol uptake from low-density lipoproteins (LDL) and overexpression of the LDL receptor in many cancers. This implies the need for cancer cells to accommodate an increased delivery of LDL along the endocytic pathway to late endosomes/lysosomes (LE/Lys), providing a rapid and effective distribution of LDL-derived cholesterol from LE/Lys to other organelles for cholesterol to foster cancer growth and spread. LDL-cholesterol exported from LE/Lys is facilitated by Niemann–Pick Type C1/2 (NPC1/2) proteins, members of the steroidogenic acute regulatory-related lipid transfer domain (StARD) and oxysterol-binding protein (OSBP) families. In addition, lysosomal membrane proteins, small Rab GTPases as well as scaffolding proteins, including annexin A6 (AnxA6), contribute to regulating cholesterol egress from LE/Lys. Here, we summarize current knowledge that links upregulated activity and expression of cholesterol transporters and related proteins in LE/Lys with cancer growth, progression and treatment outcomes. Several mechanisms on how cellular distribution of LDL-derived cholesterol from LE/Lys influences cancer cell behavior are reviewed, some of those providing opportunities for treatment strategies to reduce cancer progression and anticancer drug resistance.