Statin use and survival among women with ovarian cancer: an Australian national data-linkage study

Unraveling the extracellular vesicle network: insights into ovarian cancer metastasis and chemoresistance

Ovarian cancer (OC) is one of the most prevalent and lethal gynecological malignancies, with high mortality primarily due to its aggressive nature, frequent metastasis, and resistance to standard therapies. Recent research has highlighted the critical role of extracellular vesicles (EVs) in these processes. EVs, secreted by living organisms and carrying versatile and bioactive cargoes, play a vital role in intercellular communication. Functionally, the transfer of cargoes orchestrates multiple processes that actively affect not only the primary tumor but also local and distant pre-metastatic niche. Furthermore, their unique biological properties position EVs as novel therapeutic targets and promising drug delivery systems, with potential profound implications for cancer patients.This review summarizes recent progress in EV biology, delving into the intricate mechanisms by which EVs contribute to OC metastasis and drug resistance. It also explores the latest advances and therapeutic potential of EVs in the clinical context of OC. Despite the progress made, EV research in OC remains in its nascent stages. Consequently, this review presents existing research limitations and suggests avenues for future investigation. Altogether, the review aims to elucidate the critical roles of EVs in OC and spotlight their promising potential in this field.

Cholesteryl ester transfer protein knock-down in conjunction with a cholesterol-depleting agent decreases tamoxifen resistance in breast cancer cells

The cholesterogenic phenotype, encompassing de novo biosynthesis and accumulation of cholesterol, aids cancer cell proliferation and survival. Previously, the role of cholesteryl ester (CE) transfer protein (CETP) has been implicated in breast cancer aggressiveness, but the molecular basis of this observation is not clearly understood, which this study aims to elucidate. CETP knock-down resulted in a >50% decrease in cell proliferation in both 'estrogen receptor-positive' (ER+; Michigan Cancer Foundation-7 (MCF7) breast cancer cells) and 'triple-negative' breast cancer (TNBC; MDA-MB-231) cell lines. Intriguingly, the abrogation of CETP together with the combination treatment of tamoxifen (5 μM) and acetyl plumbagin (a cholesterol-depleting agent) (5 μM) resulted in twofold to threefold increase in apoptosis in both cell lines. CETP knockdown also showed decreased intracellular CE levels, lipid raft and lipid droplets in both cell lines. In addition, RT2 Profiler PCR array (Qiagen, Germany)-based gene expression analysis revealed an overall downregulation of genes associated in cholesterol biosynthesis, lipid signalling and drug resistance in MCF7 cells post-CETP knock-down. On the contrary, resistance in MDA-MB-231 cells was reduced through increased expression in cholesterol efflux genes and the expression of targetable surface receptors by endocrine therapy. The pilot xenograft mice study substantiated CETP's role as a cancer survival gene as knock-down of CETP stunted the growth of TNBC tumour by 86%. The principal findings of this study potentiate CETP as a driver in breast cancer growth and aggressiveness and thus targeting CETP could limit drug resistance via the reduction in cholesterol accumulation in breast cancer cells, thereby reducing cancer aggressiveness.

Nanoparticle Targeting in Chemo-Resistant Ovarian Cancer Reveals Dual Axis of Therapeutic Vulnerability Involving Cholesterol Uptake and Cell Redox Balance

Platinum (Pt)-based chemotherapy is the main treatment for ovarian cancer (OC); however, most patients develop Pt resistance (Pt-R). This work shows that Pt-R OC cells increase intracellular cholesterol through uptake via the HDL receptor, scavenger receptor type B-1 (SR-B1). SR-B1 blockade using synthetic cholesterol-poor HDL-like nanoparticles (HDL NPs) diminished cholesterol uptake leading to cell death and inhibition of tumor growth. Reduced cholesterol accumulation in cancer cells induces lipid oxidative stress through the reduction of glutathione peroxidase 4 (GPx4) leading to ferroptosis. In turn, GPx4 depletion induces decreased cholesterol uptake through SR-B1 and re-sensitizes OC cells to Pt. Mechanistically, GPx4 knockdown causes lower expression of the histone acetyltransferase EP300, leading to reduced deposition of histone H3 lysine 27 acetylation (H3K27Ac) on the sterol regulatory element binding transcription factor 2 (SREBF2) promoter and suppressing expression of this key transcription factor involved in the regulation of cholesterol metabolism. SREBF2 downregulation leads to decreased SR-B1 expression and diminished cholesterol uptake. Thus, chemoresistance and cancer cell survival under high ROS burden obligates high GPx4 and SR-B1 expression through SREBF2. Targeting SR-B1 to modulate cholesterol uptake inhibits this axis and causes ferroptosis in vitro and in vivo in Pt-R OC.

Pre-operative levels of angiopoietin protein-like 3 (ANGPTL3) in women diagnosed with high-grade serous carcinoma of the ovary

Cancer cells need constant supplies of lipids to survive and grow. Lipid dependence has been observed in various types of cancer, including high-grade serous ovarian carcinomas (HGSOC), which is a lethal form of gynecological malignancy. ANGPTL3, PCSK9, and Apo CIII are pivotal lipid-modulating factors, and therapeutic antibodies have been developed against each one (Evinacumab, Evolocumab and Volanesorsen, respectively). The roles -if any- of ANGPTL3, PCSK9, and Apo CIII in HGSOC are unclear. Moreover, levels of these lipid-modulating factors have never been reported before in HGSOC. In this study, circulating levels of ANGPTL3, PCSK9, and Apo CIII, along with lipid profiles, are examined to verify whether one or many of these lipid-regulating factors are associated with HGSOC. Methods ELISA kits were used to measure ANGPTL3, PCSK9 and Apo CIII levels in plasma samples from 31 women with HGSOC and 40 women with benign ovarian lesions (BOL) before treatment and surgery. A Roche Modular analytical platform measured lipid panels, Apo B and Lp(a) levels.Results ANGPTL3 levels were higher in women with HGSOC (84 ng/mL, SD: 29 ng/mL, n = 31) than in women with BOL (67 ng/mL, SD: 31 ng/mL, n = 40; HGSOC vs. BOL P = 0.019). Associations between the lipid panel and ANGPTL3, and the inverse relationship between HDL-cholesterol and triglycerides, were present in women with BOL but not with HGSOC. PCSK9 and Apo CIII were not associated with HGSOC.Conclusions In this cohort of 71 women, ANGPTL3 levels were increased in HGSOC patients. The presence of HGSOC disrupted the classic inverse relationship between HDL and triglycerides, as well as the association between the lipid panel and ANGPTL3. These associations were only maintained in cancer-free women. Given the availability of Evinacumab, a therapeutic antibody against ANGPTL3, the current finding prompts an assessment of whether ANGPTL3 inhibition has therapeutic potential in HGSOC.

MAPRE3 as an epigenetic target of EZH2 restricts ovarian cancer proliferation in vitro and in vivo

Ovarian cancer (OC) is a lethal gynecologic cancer and the common cause of death within women worldwide. The polycomb group protein enhancer of zeste homolog 2 (EZH2) is a histone methyltransferase highly expressed in various tumors, including OC. However, the mechanistic basis of EZH2 oncogenic activity in OC remain incompletely understood. Bioinformatics analysis showed that the expression of MAPRE3 was lower in OC tissues than in normal tissues, and was positively correlated with the overall survival. MAPRE3 overexpression decreased cell growth, inducing cell cycle arrest and apoptosis in OC cells, whereas MAPRE3 silencing promoted proliferation and accelerated cell cycle progression of OC cells. The in vivo study validated that overexpression of MAPRE3 impeded tumor formation and growth of OC xenografts in nude mice. In addition, knockdown of EZH2 in OC cells downregulated H3K27me3 expression and increased MAPRE3 expression. Inhibiting EZH2 in OC cells reduced the enrichment of H3K27me3 on the promoter of MAPRE3. Furthermore, MAPRE3 silencing significantly reversed changes in the expression of cell cycle and apoptosis-related markers and cell growth mediated by EZH2 knockdown in OC cells. MAPRE3 functions as a suppressor of OC and is epigenetic repressed by EZH2, suggesting a potential therapeutic strategy for OC by targeting EZH2/MAPRE3 axis.

Drug Repositioning for Ovarian Cancer Treatment: An Update

Ovarian cancer (OC) is one of the most prevalent malignancies in female reproductive organs, and its 5-year survival is below 45%. Despite the advances in surgical and chemotherapeutic options, OC treatment is still a challenge, and new anticancer agents are urgently needed. Drug repositioning has gained significant attention in drug discovery, representing a smart way to identify new clinical applications for drugs whose human safety and pharmacokinetics have already been established, with great time and cost savings in pharmaceutical development endeavors. This review offers an update on the most promising drugs repurposable for OC treatment and/or prevention.

Dysregulation of Cholesterol Homeostasis in Ovarian Cancer

Cholesterol plays an essential role in maintaining the rigidity of cell membranes and signal transduction. Various investigations confirmed empirically that the dysregulation of cholesterol homeostasis positively correlates with tumor progression. More specifically, recent studies suggested the distinct role of cholesterol in ovarian cancer cell proliferation, metastasis and chemoresistance. In this review, we summarize the current findings that suggest the contribution of cholesterol homeostasis dysregulation to ovarian cancer progression and resistance to anti-cancer agents. We also discuss the therapeutic implications of cholesterol-lowering drugs in ovarian cancer.

Metabolic dependencies and targets in ovarian cancer

Reprogramming of cellular metabolism is a hallmark of cancer. Cancer cells undergo metabolic adaptations to maintain tumorigenicity and survive under the attack of immune cells and chemotherapy in the tumor microenvironment. Metabolic alterations in ovarian cancer in part overlap with findings from other solid tumors and in part reflect unique traits. Altered metabolic pathways not only facilitate ovarian cancer cells' survival and proliferation but also endow them to metastasize, acquire resistance to chemotherapy, maintain cancer stem cell phenotype and escape the effects of anti-tumor immune defense. In this review, we comprehensively review the metabolic signatures of ovarian cancer and their impact on cancer initiation, progression, and resistance to treatment. We highlight novel therapeutic strategies targeting metabolic pathways under development.

Advances in ovarian cancer treatment using a combination of statins with other drugs

New anti-cancer drugs are constantly being developed, especially targeted drugs. Although these drugs have achieved significant clinical efficacy, they do not play a significant role in ovarian cancer. Moreover, the research cycle and costs of such drugs are often huge. The repositioning of conventional drugs has gradually become a concern. Statins, as traditional lipid-lowering drugs, play a role mainly by inhibiting HMGCR. In recent years, epidemiological studies and in vitro experiments have confirmed its anti-cancer effect, especially the effect of anti-ovarian cancer. The mutation rate of TP53 in ovarian cancer is as high as 95%, while HMGCR is often highly expressed in TP53 mutant tumors. However, the effect of prospective clinical trials is not ideal. This result seems understandable considering that it seems unrealistic for a lipid-lowering drug to completely inhibit tumor growth. Therefore, statins play more synergistic roles in the treatment of ovarian cancer. Because ovarian cancer is a highly heterogeneous tumor, it may be a good choice to deeply understand the mechanism of statins in the treatment of ovarian cancer and achieve precise treatment by combining it with other drugs.

Statin use improves the prognosis of ovarian cancer: An updated and comprehensive meta-analysis

Statins are lipid-lowering agents that have also been found to have anticancer effects. The relationship between statin use and clinical outcomes in ovarian cancer (OC) remains controversial, as previous assessments of the relationship between statin use and OC prognosis have yielded inconsistent results. Therefore, a comprehensive meta-analysis was performed in the present study to investigate this association. Studies were systematically retrieved by searching the PubMed, Embase and Cochrane Library databases, and consulting reference lists of the related studies. The search timeframe was from database creation to September 1, 2022. Pooled hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) were calculated to assess the association. In the present meta-analysis, 16 studies with 37,660 patients with OC were included, of which 11,296 patients had been prescribed statins. The results showed that statin use markedly improved the overall survival time (OS; HR, 0.79; 95% CI, 0.73-0.85; P<0.00001) and OC-specific survival time (HR, 0.84; 95% CI, 0.80-0.89; P<0.00001), especially the OS time in patients with serous OC (HR, 0.81; 95% CI, 0.74-0.89; P<0.0001) and endometrioid OC (HR, 0.80; 95% CI, 0.66-0.98; P=0.03). In addition, survival rate was higher in patients who used statins after OC diagnosis (HR, 0.79; 95% CI, 0.73-0.85; P<0.00001). However, there was no statistically significant association between statin use and the prognosis of mucinous and clear cell OC. The results suggested that statin use markedly improved the OS in patients with OC, including in those with serous and endometrioid OC. Statins were also found to improve the prognosis of patients of both Asian and non-Asian ethnicities. In addition, both lipophilic and hydrophilic statins improved the survival in patients with OC, especially in patients using statins after OC diagnosis. However, the effect may vary depending on the statin type, duration of use and cancer type, and more well-designed studies are needed to further evaluate this.

Peritoneal dissemination of high-grade serous ovarian cancer: pivotal roles of chromosomal instability and epigenetic dynamics

Epithelial ovarian cancer remains the lethal gynecological malignancy in women. The representative histotype is high-grade serous carcinoma (HGSC), and most patients with HGSC present at advanced stages with peritoneal dissemination. Since the peritoneal dissemination is the most important factor for poor prognosis of the patients, complete exploration for its molecular mechanisms is mandatory. In this narrative review, being based on the clinical, pathologic, and genomic findings of HGSC, chromosomal instability and epigenetic dynamics have been discussed as the potential drivers for cancer development in the fallopian tube, acquisition of cancer stem cell (CSC)-like properties, and peritoneal metastasis of HGSC. The natural history of carcinogenesis with clonal evolution, and adaptation to microenvironment of peritoneal dissemination of HGSC should be targeted in the novel development of strategies for prevention, early detection, and precision treatment for patients with HGSC.

Inverse Association between Statin Use and Cancer Mortality Relates to Cholesterol Level

Simple Summary

We observed that the inverse association between statin use and cancer mortality is limited to men with a reduction in cholesterol after the commencement of statins. These findings demonstrate that the observed inverse association between the use of statins and mortality from cancer is related to cholesterol level. To our knowledge, this is the first study to evaluate the separate effects of cholesterol level and statin use on cancer mortality.

Abstract

Statins have been associated with a decreased cancer mortality. However, cholesterol level as such may modify the risk of cancer death. To clarify the complex interplay between statins, cholesterol level, and cancer mortality, we conducted a comprehensive analysis to separate the effects of cholesterol level and statin medication on cancer mortality. Our study population consisted of 16,924 men participating in the Finnish Randomized Study of Screening for Prostate Cancer with at least one cholesterol measurement during follow-up (1996–2017). Cox proportional regression was used to estimate hazard ratios. In total, 1699 cancer deaths were observed during the median follow-up of 19 years. When statins’ association with the risk of cancer death was estimated without adjustment for cholesterol level, statin use was associated with a lowered cancer mortality (HR 0.87; 95% CI 0.79–0.97) compared to non-users. However, with further adjustment for total cholesterol level, statin use was no longer associated with a lower cancer mortality (HR 1.08; 95% CI 0.97–1.20). Upon stratified analysis, statin use was associated with a decreased cancer mortality only if the total cholesterol level decreased after the initiation of statin use (HR 0.66; 95% CI 0.58–0.76). The inverse association between statin use and cancer mortality is limited to men with a reduction in total cholesterol level after the commencement of statins, i.e., statin use is associated with a lowered cancer mortality only if the total cholesterol level decreases. This suggests that the effect of statin use on cancer mortality relates to the decreased total cholesterol level.

Statin use and incidence and mortality of breast and gynecology cancer: A cohort study using the National Health Insurance claims database

Previous studies have reported inconsistent findings concerning the impact of statin use on cancer prevention. This study examined the association between statin use and cancer incidence and mortality related to breast and gynecologic cancers in South Korea. A population-based cohort study was conducted using the National Health Insurance claims database. Women aged 45-70 years old who had taken statins for at least 6 months were compared to statin non-users of the same age from January 2005 to June 2013. The primary outcomes were cancer incidence and mortality related to breast cancer, total gynecologic cancers, cervix uteri cancer, and ovarian cancer. Cox proportional hazards regression was conducted to calculate the adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs). Out of 587 705 women, there were 3591 cases of breast cancer, 2239 cases of gynecologic cancers, and 565 breast and total gynecologic cancer deaths during 7.6 person-years. The aHRs for the association between the risk of each cancer and statin use were 0.88 (95% CI 0.79-0.97) for breast cancer and 0.83 (95% CI 0.67-0.99) for cervix uteri cancer. Statin use was associated with decreased breast cancer mortality (HR = 0.65, 95% CI 0.43-0.99) and total gynecologic cancer mortality (HR = 0.70, 95% CI 0.50-0.98). A dose-response relationship was only found for all-cancer mortality. Statin use for at least 6 months was significantly associated with a lower risk of breast and cervix uteri cancer incidence, and with lower mortality of breast and gynecologic cancers. Further research on these associations will be needed. This article is protected by copyright. All rights reserved.

Predicting obesity and smoking using medication data: A machine-learning approach

PURPOSE

Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to develop and validate machine learning (ML)-based models using medication data from Australia's Pharmaceutical Benefits Scheme (PBS) database to predict obesity and smoking.

METHODS

We used data from the D-Health Trial (N = 18 000) and the QSkin Study (N = 43 794). Smoking history, and height and weight were self-reported at study entry. Linkage to the PBS dataset captured 5 years of medication data after cohort entry. We used age, sex, and medication use, classified using anatomical therapeutic classification codes, as potential predictors of smoking (current or quit <10 years ago; never or quit ≥10 years ago) and obesity (obese; non-obese). We trained gradient-boosted machine learning models using data for the first 80% of participants enrolled; models were validated using the remaining 20%. We assessed model performance overall and by sex and age, and compared models generated using 3 and 5 years of PBS data.

RESULTS

Based on the validation dataset using 3 years of PBS data, the area under the receiver operating characteristic curve was 0.70 (95% confidence interval [CI] 0.68-0.71) for predicting obesity and 0.71 (95% CI 0.70-0.72) for predicting smoking. Models performed better in women than in men. Using 5 years of PBS data resulted in marginal improvement.

CONCLUSIONS

Medication data in combination with age and sex can be used to predict obesity and smoking. These models may be of value to researchers using data collected for administrative purposes.