Biomarker identification for statin sensitivity of cancer cell lines

Association of Wild-Type TP53 with Downregulation of Lovastatin Sensitivity in Human Non-Small Cell Lung Cancer Cells

Statins inhibit 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the rate-limiting enzyme of the mevalonate pathway, and reduce cholesterol synthesis. They also have been demonstrated to improve prognosis in patients with various cancers, suggesting a potential anti-cancer effect of statins. However, there is no consensus on the molecular targets of statins for their anti-cancer effects. Docetaxel (DOC) is a microtubule-stabilizing agent currently used as a chemotherapeutic drug in several cancers, including lung cancer. Interestingly, the anti-cancer effects of either drug that are related to abnormal or wild-type TP53 gene have been implied. Therefore, the drug sensitivity of DOC and lovastatin in human lung cancer cells was evaluated. We found that H1355 (mutant TP53-E285K), CL1 (mutant TP53-R248W), and H1299 (TP53-null) human non-small cell lung cancer cells were more sensitive to lovastatin than A549 and H460 cells expressing wild-type TP53. Conversely, A549 and H460 cells showed higher sensitivity to DOC than H1299 and CL1 cells, as demonstrated by the MTT assay. When endogenous TP53 activity was inhibited by pifithrin-α in A549 and H460 cells, lovastatin sensitivities significantly increased, and cancer cell viabilities markedly reduced. These results indicate that TP53 status is associated with the anti-cancer effect of statins in human lung cancer cells. Mutated or null TP53 status is correlated with higher statin sensitivity. Furthermore, DOC-resistant H1299 (H1299/D8) cells showed significant sensitivity to lovastatin treatment compared to DOC-resistant A549 (A549/D16) cells, indicating a potential application of statins/chemotherapy combination therapy to control wild-type and abnormal TP53-containing human lung tumors.

A plasma peptidomic signature reveals extracellular matrix remodeling and predicts prognosis in alcohol-associated hepatitis

BACKGROUND

Alcohol-associated hepatitis (AH) is plagued with high mortality and difficulty in identifying at-risk patients. The extracellular matrix undergoes significant remodeling during inflammatory liver injury and could potentially be used for mortality prediction.

METHODS

EDTA plasma samples were collected from patients with AH (n = 62); Model for End-Stage Liver Disease score defined AH severity as moderate (12-20; n = 28) and severe (>20; n = 34). The peptidome data were collected by high resolution, high mass accuracy UPLC-MS. Univariate and multivariate analyses identified differentially abundant peptides, which were used for Gene Ontology, parent protein matrisomal composition, and protease involvement. Machine-learning methods were used to develop mortality predictors.

RESULTS

Analysis of plasma peptides from patients with AH and healthy controls identified over 1600 significant peptide features corresponding to 130 proteins. These were enriched for extracellular matrix fragments in AH samples, likely related to the turnover of hepatic-derived proteins. Analysis of moderate versus severe AH peptidomes was dominated by changes in peptides from collagen 1A1 and fibrinogen A proteins. The dominant proteases for the AH peptidome spectrum appear to be CAPN1 and MMP12. Causal graphical modeling identified 3 peptides directly linked to 90-day mortality in >90% of the learned graphs. These peptides improved the accuracy of mortality prediction over the Model for End-Stage Liver Disease score and were used to create a clinically applicable mortality prediction assay.

CONCLUSIONS

A signature based on plasma peptidome is a novel, noninvasive method for prognosis stratification in patients with AH. Our results could also lead to new mechanistic and/or surrogate biomarkers to identify new AH mechanisms.

Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study

BACKGROUND

Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function.

METHODS AND FINDINGS

We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment: 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity).

CONCLUSIONS

This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.

Overcoming statin resistance in prostate cancer cells by targeting the 3-hydroxy-3-methylglutaryl-CoA-reductase

Prostate cancer is the most prevalent malignancy in men. While diagnostic and therapeutic interventions have substantially improved in recent years, disease relapse, treatment resistance, and metastasis remain significant contributors to prostate cancer-related mortality. Therefore, novel therapeutic approaches are needed. Statins are inhibitors of the 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the rate-limiting enzyme of the mevalonate pathway which plays an essential role in cholesterol homeostasis. Numerous preclinical studies have provided evidence for the pleiotropic antitumor effects of statins. However, results from clinical studies remain controversial and have shown substantial benefits to even no effects on human malignancies including prostate cancer. Potential statin resistance mechanisms of tumor cells may account for such discrepancies. In our study, we treated human prostate cancer cell lines (PC3, C4-2B, DU-145, LNCaP) with simvastatin, atorvastatin, and rosuvastatin. PC3 cells demonstrated high statin sensitivity, resulting in a significant loss of vitality and clonogenic potential (up to - 70%; p < 0.001) along with an activation of caspases (up to 4-fold; p < 0.001). In contrast, C4-2B and DU-145 cells were statin-resistant. Statin treatment induced a restorative feedback in statin-resistant C4-2B and DU-145 cells through upregulation of the HMGCR gene and protein expression (up to 3-folds; p < 0.01) and its transcription factor sterol-regulatory element binding protein 2 (SREBP-2). This feedback was absent in PC3 cells. Blocking the feedback using HMGCR-specific small-interfering (si)RNA, the SREBP-2 activation inhibitor dipyridamole or the HMGCR degrader SR12813 abolished statin resistance in C4-2B and DU-145 and induced significant activation of caspases by statin treatment (up to 10-fold; p < 0.001). Consistently, long-term treatment with sublethal concentrations of simvastatin established a stable statin resistance of a PC3SIM subclone accompanied by a significant upregulation of both baseline as well as post-statin HMGCR protein (gene expression up to 70-fold; p < 0.001). Importantly, the statin-resistant phenotype of PC3SIM cells was reversible by HMGCR-specific siRNA and dipyridamole. Our investigations reveal a key role of a restorative feedback driven by the HMGCR/SREBP-2 axis in statin resistance mechanisms of prostate cancer cells.

Comparison of the anticancer effects of various statins on canine oral melanoma cells

Canine oral melanoma is a highly malignant cancer with a poor prognosis. Statins, commonly used drugs for treating dyslipidemia, exhibit pleiotropic anticancer effects and marked anti-proliferative effects against melanoma cells. The anticancer effects among statins vary; in human cancers, lipophilic statins have shown stronger anticancer effects compared with hydrophilic statins. However, data on the differences in the effects of various statins on canine cancer cells are lacking, hence the optimal statins for treating canine melanoma remain unknown. Therefore, this study aimed to clarify the most effective statin by comparing the anticancer effects of hydrophilic rosuvastatin and lipophilic atorvastatin, simvastatin, fluvastatin and pitavastatin on three canine oral melanoma cell lines. Time-dependent measurement of cell confluence showed that lipophilic statins had a stronger anti-proliferative effect on all cell lines than hydrophilic rosuvastatin. Quantification of lactate dehydrogenase release, an indicator of cytotoxicity, showed that lipophilic statins more effectively induced cell death than hydrophilic rosuvastatin. Lipophilic statins affected both inhibition of cell proliferation and induction of cell death. The anticancer effects of statins on canine oral melanoma cells differed in the following ascending order of IC50 values: pitavastatin < fluvastatin = simvastatin < atorvastatin < rosuvastatin. The required concentration of pitavastatin was approximately 1/20th that of rosuvastatin. Among the statins used in this study, pitavastatin had the highest anticancer effect. Our results suggest lipophilic pitavastatin as the optimal statin for treating canine oral melanoma.

Exploration of Novel Metabolic Features Reflecting Statin Sensitivity in Lung Cancer Cells

Statins are cholesterol-lowering drugs often used for the treatment of dyslipidemia. Statins also exert anti-cancer effects by inhibiting hydroxymethylglutaryl-CoA reductase (HMGCR), a rate-limiting enzyme in cholesterol synthesis. We previously reported that the susceptibility to statin treatment differs among cancer cells and that functional E-cadherin expression on the plasma membrane could be a biomarker of statin sensitivity in cancer cells. However, the detailed qualitative and molecular differences between statin-sensitive and statin-resistant cancer cells remain unclear. Here, we explored novel parameters related to statin sensitivity by comparing gene expression profiles and metabolite contents between statin-sensitive and statin-resistant lung cancer cell lines. We found that the expression of most cholesterol synthesis genes was lower in the statin-sensitive cancer cell line, HOP-92, than in the statin-resistant cancer cell line, NCI-H322M. Moreover, HOP-92 cells originally exhibited lower levels of CoA and HMG-CoA. Additionally, atorvastatin decreased the mRNA expression of PANK2, a rate-limiting enzyme in CoA synthesis. Atorvastatin also reduced the mRNA levels of the cholesterol esterification enzyme SOAT1, which was consistent with a decrease in the ratio of cholesterol ester to total cholesterol in HOP-92 cells. Our data suggest that the cholesterol synthetic flow and CoA content may be limited in statin-sensitive cancer cells. We also suggest that CoA synthesis and cholesterol storage may fluctuate with atorvastatin treatment in statin-sensitive cancer cells.

A plasma peptidomic signature reveals extracellular matrix remodeling and predicts prognosis in alcohol-related hepatitis

Alcohol-related hepatitis (AH) is plagued with high mortality and difficulty in identifying at-risk patients. The extracellular matrix undergoes significant remodeling during inflammatory liver injury that can be detected in biological fluids and potentially used for mortality prediction. EDTA plasma samples were collected from AH patients (n= 62); Model for End-Stage Liver Disease (MELD) score defined AH severity as moderate (12-20; n=28) and severe (>20; n=34). The peptidome data was collected by high resolution, high mass accuracy UPLC-MS. Univariate and multivariate analyses identified differentially abundant peptides, which were used for Gene Ontology, parent protein matrisomal composition and protease involvement. Machine learning methods were used on patient-specific peptidome and clinical data to develop mortality predictors. Analysis of plasma peptides from AH patients and healthy controls identified over 1,600 significant peptide features corresponding to 130 proteins. These were enriched for ECM fragments in AH samples, likely related to turnover of hepatic-derived proteins. Analysis of moderate versus severe AH peptidomes showed a shift in abundance of peptides from collagen 1A1 and fibrinogen A proteins. The dominant proteases for the AH peptidome spectrum appear to be CAPN1 and MMP12. Increase in hepatic expression of these proteases was orthogonally-validated in RNA-seq data of livers from AH patients. Causal graphical modeling identified four peptides directly linked to 90-day mortality in >90% of the learned graphs. These peptides improved the accuracy of mortality prediction over MELD score and were used to create a clinically applicable mortality prediction assay. A signature based on plasma peptidome is a novel, non-invasive method for prognosis stratification in AH patients. Our results could also lead to new mechanistic and/or surrogate biomarkers to identify new AH mechanisms.

Lay summary

We used degraded proteins found the blood of alcohol-related hepatitis patients to identify new potential mechanisms of injury and to predict 90 day mortality.

CYP11A1 silencing suppresses HMGCR expression via cholesterol accumulation and sensitizes CRPC cell line DU-145 to atorvastatin

Statins, which are cholesterol synthesis inhibitors, are well-known therapeutics for dyslipidemia; however, some studies have anticipated their use as anticancer agents. However, epithelial cancer cells show strong resistance to statins through an increased expression of HMG-CoA reductase (HMGCR), an inhibitory target of statins. Castration-resistant prostate cancer (CRPC) cells synthesize androgens from cholesterol on their own. We performed suppression of CYP11A1, a rate-limiting enzyme in androgen synthesis from cholesterol, using siRNA or inhibitors, to examine the effect of steroidogenesis inhibition on statin sensitivity in CRPC cells. Here, we suggested that CYP11A1 silencing sensitized the statin-resistant CRPC cell line DU-145 to atorvastatin via HMGCR downregulation by an increase in intracellular free cholesterol. We further demonstrated that CYP11A1 silencing induced epithelial-mesenchymal transition, which converted DU-145 cells into a statin-sensitive phenotype. This suggests that concomitant use of CYP11A1 inhibitors could be an effective approach for overcoming statin resistance in CRPC. Moreover, we showed that ketoconazole, a CYP11A1 inhibitor, sensitized DU-145 cells to atorvastatin, although not all the molecular events observed in CYP11A1 silencing were reproducible. Although further studies are necessary to clarify the detailed mechanisms, ketoconazole may be effective as a concomitant drug that potentiates the anticancer effect of atorvastatin.

Expression of housekeeping genes varies depending on mevalonate pathway inhibition in cancer cells

Statins have anticancer effects and may be used as anticancer agents via drug repositioning. In reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays, the internal reference gene must not be affected by any experimental conditions. As statins exert a wide range of effects on cells by inhibiting the mevalonate pathway, it is possible that statin treatment might alter the expression of housekeeping genes used as internal reference genes, thereby misleading the assessment of obtained gene expression data. Here, we evaluated the expression stability of internal reference genes in atorvastatin-treated cancer cell lines. We treated both statin-sensitive and statin-resistant cancer cell lines with atorvastatin at seven different concentrations and performed RT-qPCR on 15 housekeeping genes whose expression stability was then assessed using five different algorithms. In both statin-sensitive and statin-resistant cancer cell lines, atorvastatin affected the expression of certain internal reference genes in a dose-dependent and cancer cell line-dependent manner; therefore, caution should be exercised when comparing target gene expression between cells. Our findings emphasize the importance of the validation of internal reference genes in gene expression analyses in drug treatment-based cancer research.

The prognosis of lipid reprogramming with the HMG-CoA reductase inhibitor, rosuvastatin, in castrated Egyptian prostate cancer patients: Randomized trial

AIM

The role of surgical castration and rosuvastatin treatment on lipid profile and lipid metabolism related markers was evaluated for their prognostic significance in metastatic prostate cancer (mPC) patients.

METHODS

A total of 84 newly diagnosed castrated mPC patients treated with castration were recruited and divided into two groups: Group I served as control (statin non-users) while group II treated with Rosuvastatin (20 mg/day) for 6 months and served as statin users. Prostate specific antigen (PSA), epidermal growth factor receptor (EGFR), Caveolin-1 (CAV1), lipid profile (LDL, HDL, triglycerides (TG) and total cholesterol (TC)) and lipid metabolism related markers (aldoketoreductase (AKR1C4), HMG-CoA reductase (HMGCR), ATP-binding cassette transporter A1 (ABCA1), and soluble low density lipoprotein receptor related protein 1 (SLDLRP1)) were measured at baseline, after 3 and 6 months. Overall survival (OS) was analyzed by Kaplan-Meier and COX regression for prognostic significance.

RESULTS

Before castration, HMG-CoA reductase was elevated in patients <65 years (P = 0.009). Bone metastasis was associated with high PSA level (P = 0.013), but low HMGCR (P = 0.004). Patients with positive family history for prostate cancer showed high levels of EGFR, TG, TC, LDL, alkaline phosphatase (ALP), but low AKR1C4, SLDLRP1, CAV1 and ABCA-1 levels. Smokers had high CAV1 level (P = 0.017). After 6 months of castration and rosuvastatin administration, PSA, TG, LDL and TC were significantly reduced, while AKR1C4, HMGCR, SLDLRP1, CAV1 and ABCA-1 were significantly increased. Overall survival was reduced in patients with high baseline of SLDLRP1 (>3385 pg/ml, P = 0.001), PSA (>40 ng/ml, P = 0.003) and CAV1 (>4955 pg/ml, P = 0.021).

CONCLUSION

Results of the current study suggest that the peripheral lipidogenic effects of rosuvastatin may have an impact on the treatment outcome and survival of castrated mPC patients.

TRAIL REGISTRATION

This trial was registered at the Pan African Clinical Trial Registry with identification number PACTR202102664354163 and at ClinicalTrials.gov with identification number NCT04776889.

Atorvastatin improves cisplatin sensitivity through modulation of cholesteryl ester homeostasis in breast cancer cells

BACKGROUND

Acquired treatment resistance is a significant problem in breast cancer management, and alterations in lipid metabolism have been proposed to contribute to the development of drug resistance as well as other aspects of tumor progression. The present study aimed to identify the role of cholesterol metabolism in MCF-7 and MDA-MB-231 breast cancer cell response to cisplatin (CDDP) treatment in the acute setting and in a model of CDDP resistance.

METHODS

MCF-7 (luminal A), MDA-MB-231 (triple-negative) and CDDP-resistant MDA-MB-231 (MDACR) cell lines were grown in the presence or absence of CDDP in combination with atorvastatin (ATV), lipid depletion or low-density lipoprotein loading and were analyzed by a variety of biochemical and radiometric techniques.

RESULTS

Co-administration of CDDP and ATV strongly reduced cell proliferation and viability to a greater extent than CDDP alone, especially in MDA-MB-231 cells. These findings were associated with reduced cholesteryl ester synthesis and storage in MDA-MB-231 cells. In MDACR cells, acetyl-CoA acetyltransferase 1 (ACAT-1) was upregulated compared to naïve MDA-MB-231 cells and ATV treatment restored CDDP sensitivity, suggesting that aberrant ACAT-1 expression and associated changes in cholesterol metabolism contribute to CDDP resistance in MDA-MB-231 cells.

CONCLUSION

These findings indicate that the elevated susceptibility of MDA-MB-231 cells to co-administration of CDDP and ATV, is associated with an increased reliance on cholesteryl ester availability. Our data from these cell culture-based studies identifies altered cholesterol homeostasis as an adaptive response to CDDP treatment that contributes to aggressiveness and chemotherapy resistance.

Alterations in the omics profiles in mevalonate pathway-inhibited cancer cells

AIMS

Statins, cholesterol-lowering drugs, are potential therapeutic agents for inhibiting cancer proliferation. However, the mechanisms that mediate the effects of statins, the homeostatic responses of tumor cells to statin therapy, and the modes underlying the antitumor effects of statins remain unclear.

MAIN METHODS

To uncover the effects of statins on cancer cells in vitro, we performed transcriptome and metabolome analyses on atorvastatin-treated statin-resistant and statin-sensitive lung cancer cells.

KEY FINDINGS

The results of Gene Ontology terms and pathway enrichment analyses showed that after 24 h of atorvastatin treatment, the expression of cell cycle- and DNA replication-related genes was significantly decreased in the statin-sensitive cancer cells. The results of metabolome analysis showed that the components of polyamine metabolism and purine metabolism, glycolysis, and pentose phosphate pathway were decreased in the statin-sensitive cancer cells.

SIGNIFICANCE

Differences in cellular properties between statin-sensitive and statin-resistant cancer cells revealed additional candidates for therapeutic targets in statin-treated cancer cells and suggested that inhibiting these metabolic pathways could improve efficacy. In conclusion, combining statins with inhibitors of polyamine metabolism (cell proliferation and protein translation), purine metabolism (DNA synthesis), glycolytic system (energy production), and pentose phosphate pathway (antioxidant stress) might enhance the anticancer effects of statins.

Computational pharmacogenomic screen identifies drugs that potentiate the anti-breast cancer activity of statins

Statins, a family of FDA-approved cholesterol-lowering drugs that inhibit the rate-limiting enzyme of the mevalonate metabolic pathway, have demonstrated anticancer activity. Evidence shows that dipyridamole potentiates statin-induced cancer cell death by blocking a restorative feedback loop triggered by statin treatment. Leveraging this knowledge, we develop an integrative pharmacogenomics pipeline to identify compounds similar to dipyridamole at the level of drug structure, cell sensitivity and molecular perturbation. To overcome the complex polypharmacology of dipyridamole, we focus our pharmacogenomics pipeline on mevalonate pathway genes, which we name mevalonate drug-network fusion (MVA-DNF). We validate top-ranked compounds, nelfinavir and honokiol, and identify that low expression of the canonical epithelial cell marker, E-cadherin, is associated with statin-compound synergy. Analysis of remaining prioritized hits led to the validation of additional compounds, clotrimazole and vemurafenib. Thus, our computational pharmacogenomic approach identifies actionable compounds with pathway-specific activities.

Essential Regression: A generalizable framework for inferring causal latent factors from multi-omic datasets

High-dimensional cellular and molecular profiling of biological samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate prioritized causal inferences. Current methods are limited by high dimensionality of the combined datasets, the differences in their data distributions, and their integration to infer causal relationships. Here, we present Essential Regression (ER), a novel latent-factor-regression-based interpretable machine-learning approach that addresses these problems by identifying latent factors and their likely cause-effect relationships with system-wide outcomes/properties of interest. ER can integrate many multi-omic datasets without structural or distributional assumptions regarding the data. It outperforms a range of state-of-the-art methods in terms of prediction. ER can be coupled with probabilistic graphical modeling, thereby strengthening the causal inferences. The utility of ER is demonstrated using multi-omic system immunology datasets to generate and validate novel cellular and molecular inferences in a wide range of contexts including immunosenescence and immune dysregulation.

Neurological Complications Acquired During Pediatric Critical Illness: Exploratory "Mixed Graphical Modeling" Analysis Using Serum Biomarker Levels

OBJECTIVES

Neurologic complications, consisting of the acute development of a neurologic disorder, that is, not present at admission but develops during the course of illness, can be difficult to detect in the PICU due to sedation, neuromuscular blockade, and young age. We evaluated the direct relationships of serum biomarkers and clinical variables to the development of neurologic complications. Analysis was performed using mixed graphical models, a machine learning approach that allows inference of cause-effect associations from continuous and discrete data.

DESIGN

Secondary analysis of a previous prospective observational study.

SETTING

PICU, single quaternary-care center.

PATIENTS

Individuals admitted to the PICU, younger than18 years old, with intravascular access via an indwelling catheter.

INTERVENTIONS

None.

MEASUREMENTS

About 101 patients were included in this analysis. Serum (days 1-7) was analyzed for glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, and alpha-II spectrin breakdown product 150 utilizing enzyme-linked immunosorbent assays. Serum levels of neuron-specific enolase, myelin basic protein, and S100 calcium binding protein B used in these models were reported previously. Demographic data, use of selected clinical therapies, lengths of stay, and ancillary neurologic testing (head CT, brain MRI, and electroencephalogram) results were recorded. The Mixed Graphical Model-Fast-Causal Inference-Maximum algorithm was applied to the dataset.

MAIN RESULTS

About 13 of 101 patients developed a neurologic complication during their critical illness. The mixed graphical model identified peak levels of the neuronal biomarker neuron-specific enolase and ubiquitin C-terminal hydrolase-L1, and the astrocyte biomarker glial fibrillary acidic protein to be the direct causal determinants for the development of a neurologic complication; in contrast, clinical variables including age, sex, length of stay, and primary neurologic diagnosis were not direct causal determinants.

CONCLUSIONS

Graphical models that include biomarkers in addition to clinical data are promising methods to evaluate direct relationships in the development of neurologic complications in critically ill children. Future work is required to validate and refine these models further, to determine if they can be used to predict which patients are at risk for/or with early neurologic complications.

The newly identified MEK1 tyrosine phosphorylation target MACC1 is druggable by approved MEK1 inhibitors to restrict colorectal cancer metastasis

Cancer metastasis causes >90% of cancer deaths and remains a major treatment challenge. Here we deciphered the impact of tyrosine phosphorylation of MACC1, a causative driver for cancer metastasis, for cancer cell signaling and novel interventions to restrict cancer metastasis. We identified MACC1 as new MEK1 substrate. MEK1 directly phosphorylates MACC1, leading to accelerated and increased ERK1 activation. Mutating in silico predicted hierarchical MACC1 tyrosine phosphorylation sites abrogates MACC1-induced migration, invasion, and MET expression, a transcriptional MACC1 target. Targeting MEK1 by RNAi or clinically applicable MEK1 inhibitors AZD6244 and GSK1120212 reduces MACC1 tyrosine phosphorylation and restricts MACC1-induced metastasis formation in mice. Although MEK1 levels, contrary to MACC1, are not of prognostic relevance for CRC patients, MEK1 expression was found indispensable for MACC1-induced metastasis. This study identifies MACC1 as new MEK1 substrate for tyrosine phosphorylation decisively impacting cell motility, tumor growth, and metastasis. Thus, MAP kinase signaling is not linear leading to ERK activation, but branches at the level of MEK1. This fundamental finding opens new therapeutic options for targeting the MEK1/MACC1 axis as novel vulnerability in patients at high risk for metastasis. This might be extended from CRC to further solid tumor entities.

Concomitant attenuation of HMGCR expression and activity enhances the growth inhibitory effect of atorvastatin on TGF-β-treated epithelial cancer cells

Epithelial-mesenchymal transition (EMT) in primary tumor cells is a key prerequisite for metastasis initiation. Statins, cholesterol-lowering drugs, can delay metastasis formation in vivo and attenuate the growth and proliferation of tumor cells in vitro. The latter effect is stronger in tumor cells with a mesenchymal-like phenotype than in those with an epithelial one. However, the effect of statins on epithelial cancer cells treated with EMT-inducing growth factors such as transforming growth factor-β (TGF-β) remains unclear. Here, we examined the effect of atorvastatin on two epithelial cancer cell lines following TGF-β treatment. Atorvastatin-induced growth inhibition was stronger in TGF-β-treated cells than in cells not thusly treated. Moreover, treatment of cells with atorvastatin prior to TGF-β treatment enhanced this effect, which was further potentiated by the simultaneous reduction in the expression of the statin target enzyme, 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR). Dual pharmacological targeting of HMGCR can thus strongly inhibit the growth and proliferation of epithelial cancer cells treated with TGF-β and may also improve statin therapy-mediated attenuation of metastasis formation in vivo.

Importance of Mevalonate Pathway Lipids on the Growth and Survival of Primary and Metastatic Gastric Carcinoma Cells

Purpose

This preclinical study aims to determine the effect of drugs that alter isoprenoids and cholesterol metabolism in the homeostasis of gastric carcinoma cell lines in the search for new therapeutic targets for stomach cancer.

Materials and Methods

Primary (AGS) and metastatic (NCI-N87) gastric cancer cell lines were treated with simvastatin and terbinafine, two inhibitors of the mevalonate pathway, and avasimibe, an inhibitor of cholesterol esterification. Cell viability and growth were measured as well as cholesterol levels and the expression of the hydroxy methyl-glutaryl CoA reductase (HMGCR) and the LDL receptor (LDLR).

Results

Primary and metastatic gastric carcinoma cells show different sensitivity to drugs that affect isoprenoid synthesis and the metabolism and uptake of cholesterol. Isoprenoids are involved in the growth and viability of both types of cells, but the role of free and esterified cholesterol for metastatic gastric cell survival is not as evident as for primary gastric cancer cells. Differential expression of LDLR due to mevalonate pathway inhibition suggests variations in the regulation of cholesterol uptake between primary and metastatic cancer cells.

Conclusion

These results indicate that at least for primary gastric cancer, statins and avasimibe are promising candidates as potential novel antitumor drugs that target the metabolism of isoprenoids and cholesterol of gastric tumors.

Metabolic labeling with an alkyne probe reveals similarities and differences in the prenylomes of several brain-derived cell lines and primary cells

Protein prenylation involves the attachment of one or two isoprenoid group(s) onto cysteine residues positioned near the C-terminus. This modification is essential for many signal transduction processes. In this work, the use of the probe C15AlkOPP for metabolic labeling and identification of prenylated proteins in a variety of cell lines and primary cells is explored. Using a single isoprenoid analogue, 78 prenylated protein groups from the three classes of prenylation substrates were identified including three novel prenylation substrates in a single experiment. Applying this method to three brain-related cell lines including neurons, microglia, and astrocytes showed substantial overlap (25%) in the prenylated proteins identified. In addition, some unique prenylated proteins were identified in each type. Eight proteins were observed exclusively in neurons, five were observed exclusively in astrocytes and three were observed exclusively in microglia, suggesting their unique roles in these cells. Furthermore, inhibition of farnesylation in primary astrocytes revealed the differential responses of farnesylated proteins to an FTI. Importantly, these results provide a list of 19 prenylated proteins common to all the cell lines studied here that can be monitored using the C15AlkOPP probe as well as a number of proteins that were observed in only certain cell lines. Taken together, these results suggest that this chemical proteomic approach should be useful in monitoring the levels and exploring the underlying role(s) of prenylated proteins in various diseases.

Clinical, Cellular, and Molecular Evidence of the Additive Antitumor Effects of Biguanides and Statins in Prostate Cancer

CONTEXT

Prostate cancer (PCa) is one of the leading causes of cancer-related death among the male population worldwide. Unfortunately, current medical treatments fail to prevent PCa progression in a high percentage of cases; therefore, new therapeutic tools to tackle PCa are urgently needed. Biguanides and statins have emerged as antitumor agents for several endocrine-related cancers.

OBJECTIVE

To evaluate: (1) the putative in vivo association between metformin and/or statins treatment and key tumor and clinical parameters and (2) the direct effects of different biguanides (metformin/buformin/phenformin), statins (atorvastatin/simvastatin/lovastatin), and their combination, on key functional endpoints and associated signalling mechanisms.

METHODS

An exploratory/observational retrospective cohort of patients with PCa (n = 75) was analyzed. Moreover, normal and tumor prostate cells (normal [RWPE-cells/primary prostate cell cultures]; tumor [LNCaP/22RV1/PC3/DU145 cell lines]) were used to measure proliferation/migration/tumorsphere-formation/signalling pathways.

RESULTS

The combination of metformin+statins in vivo was associated to lower Gleason score and longer biochemical recurrence-free survival. Moreover, biguanides and statins exerted strong antitumor actions (ie, inhibition of proliferation/migration/tumorsphere formation) on PCa cells, and that their combination further decreased; in addition, these functional parameters compared with the individual treatments. These actions were mediated through modulation of key oncogenic and metabolic signalling pathways (ie, AR/mTOR/AMPK/AKT/ERK) and molecular mediators (MKI67/cMYC/androgen receptor/cell-cycle inhibitors).

CONCLUSIONS

Biguanides and statins significantly reduced tumor aggressiveness in PCa, with this effect being more potent (in vitro and in vivo) when both compounds are combined. Therefore, given the demonstrated clinical safety of biguanides and statins, our results suggest a potential therapeutic role of these compounds, especially their combination, for the treatment of PCa.

Pleiotropic effects of statins: A focus on cancer

The statin drugs ('statins') potently inhibit hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase by competitively blocking the active site of the enzyme. Statins decrease de novo cholesterol biosynthesis and thereby reduce plasma cholesterol levels. Statins exhibit "pleiotropic" properties that are independent of their lipid-lowering effects. For example, preclinical evidence suggests that statins inhibit tumor growth and induce apoptosis in specific cancer cell types. Furthermore, statins show chemo-sensitizing effects by impairing Ras family GTPase signaling. However, whether statins have clinically meaningful anti-cancer effects remains an area of active investigation. Both preclinical and clinical studies on the potential mechanisms of action of statins in several cancers have been reviewed in the literature. Considering the contradictory data on their efficacy, we present an up-to-date summary of the pleiotropic effects of statins in cancer therapy and review their impact on different malignancies. We also discuss the synergistic anti-cancer effects of statins when combined with other more conventional anti-cancer drugs to highlight areas of potential therapeutic development.

Causal network perturbations for instance-specific analysis of single cell and disease samples

MOTIVATION

Complex diseases involve perturbation in multiple pathways and a major challenge in clinical genomics is characterizing pathway perturbations in individual samples. This can lead to patient-specific identification of the underlying mechanism of disease thereby improving diagnosis and personalizing treatment. Existing methods rely on external databases to quantify pathway activity scores. This ignores the data dependencies and that pathways are incomplete or condition-specific.

RESULTS

ssNPA is a new approach for subtyping samples based on deregulation of their gene networks. ssNPA learns a causal graph directly from control data. Sample-specific network neighborhood deregulation is quantified via the error incurred in predicting the expression of each gene from its Markov blanket. We evaluate the performance of ssNPA on liver development single-cell RNA-seq data, where the correct cell timing is recovered; and two TCGA datasets, where ssNPA patient clusters have significant survival differences. In all analyses ssNPA consistently outperforms alternative methods, highlighting the advantage of network-based approaches.

AVAILABILITY AND IMPLEMENTATION

http://www.benoslab.pitt.edu/Software/ssnpa/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Wnt signaling mediates oncogenic synergy between Akt and Dlx5 in T-cell lymphomagenesis by enhancing cholesterol synthesis

The Dlx5 homeobox gene was first implicated as an oncogene in a T-ALL mouse model expressing myristoylated (Myr) Akt2. Furthermore, overexpression of Dlx5 was sufficient to drive T-ALL in mice by directly activating Akt and Notch signaling. These findings implied that Akt2 cooperates with Dlx5 in T-cell lymphomagenesis. To test this hypothesis, Lck-Dlx5;Lck-MyrAkt2 transgenic mice were generated. MyrAkt2 synergized with Dlx5 to greatly accelerate and enhance the dissemination of T-lymphomagenesis. RNA-seq analysis performed on lymphomas from Lck-Dlx5;Lck-MyrAkt mice revealed upregulation of genes involved in the Wnt and cholesterol biosynthesis pathways. Combined RNA-seq and ChIP-seq analysis of lymphomas from Lck-Dlx5;Lck-MyrAkt mice demonstrated that β-catenin directly regulates genes involved in sterol regulatory element binding transcription factor 2 (Srebf2)-cholesterol synthesis. These lymphoma cells had high Lef1 levels and were highly sensitive to β-catenin and Srebf2-cholesterol synthesis inhibitors. Similarly, human T-ALL cell lines with activated NOTCH and AKT and elevated LEF1 levels were sensitive to inhibition of β-catenin and cholesterol pathways. Furthermore, LEF1 expression positively correlated with expression of genes involved in the cholesterol synthesis pathway in primary human T-ALL specimens. Together, these data suggest that targeting β-catenin and/or cholesterol biosynthesis, together with AKT, could have therapeutic efficacy in a subset of T-ALL patients.

Statins in risk-reduction and treatment of cancer

Statins, which are competitive inhibitors of 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase, reduce cholesterol blood levels and the risk of developing cardiovascular diseases and their related complications. In addition to this main activity, statins show pleiotropic effects such as antioxidant, anti-inflammatory and antiproliferative properties, with applications in many pathologies. Based on their antiproliferative properties, in vitro and in vivo studies have investigated their effects on various types of cancer (i.e., breast cancer, prostate cancer, colorectal cancer, ovarian cancer, lung cancer) with different genetic and molecular characteristics. Many positive results were obtained, but they were highly dependent on the physiochemical properties of the statins, their dose and treatment period. Combined therapies of statins and cytotoxic drugs have also been tested, and synergistic or additive effects were observed. Moreover, observational studies performed on patients who used statins for different pathologies, revealed that statins reduced the risk of developing various cancers, and improved the outcomes for cancer patients. Currently, there are many ongoing clinical trials aimed at exploring the potential of statins to lower the mortality and the disease-recurrence risk. All these results are the foundation of new treatment directions in cancer therapy.

Anti-tumor effects of mevalonate pathway inhibition in ovarian cancer

BACKGROUND

Ovarian cancer remains the most fatal gynecological malignancy. Current therapeutic options are limited due to late diagnosis in the majority of the cases, metastatic spread to the peritoneal cavity and the onset of chemo-resistance. Thus, novel therapeutic approaches are required. Statins and amino-bisphosphonates are inhibitors of the mevalonate pathway, which is a fundamental pathway of cellular metabolism, essential for cholesterol production and posttranslational protein farnesylation and geranylgeranylation. While this pathway has emerged as a promising treatment target in several human malignancies, its potential as a therapeutic approach in ovarian cancer is still not fully understood.

METHODS

Human ovarian cancer cell lines (IGROV-1, A2780, A2780cis) were treated with increasing concentrations (0.5-100 μM) of statins (simvastatin, atorvastatin, rosuvastatin) and zoledronic acid. Effects on cell vitality and apoptosis were assessed using Cell Titer Blue®, Caspase 3/7 Glo®, clonogenic assays as well as cleaved poly (ADP-ribose) polymerase (cPARP) detection. The inhibition of the mevalonate pathway was confirmed using Western Blot of unprenylated Ras and Rap1a proteins. Quantitative real-time PCR and ELISA were used to analyze modulations on several key regulators of ovarian cancer tumorigenesis.

RESULTS

The treatment of IGROV-1 and A2780 cells with statins and zoledronic acid reduced vitality (by up to 80%; p < 0.001) and induced apoptosis by up to 8-folds (p < 0.001) in a dose-dependent fashion. Rescue experiments using farnesyl pyrophosphate or geranylgeranyl pyrophosphate evidenced that blocked geranylgeranylation is the major underlying mechanism of the pro-apoptotic effects. Gene expression of the tumor-promoting cytokines and mediators, such as transforming growth factor (TGF)-β1, vascular endothelial growth factor (VEGF), interleukin (IL)-8, and IL-6 were significantly suppressed by statins and zoledronic acid by up to 90% (p < 0.001). For all readouts, simvastatin was most potent of all agents used. Cisplatin-resistant A2780cis cells showed a relative resistance to statins and zoledronic acid. However, similar to the effects in A2780 cells, simvastatin and zoledronic acid significantly induced caspase 3/7 activation (6-folds; p < 0.001).

CONCLUSION

Our in vitro findings point to promising anti-tumor effects of statins and zoledronic acid in ovarian cancer and warrant additional validation in preclinical and clinical settings.

Identifying Drug Repurposing Opportunities in Oncology

The never-ending explosion in the cost of new oncology drugs is reducing in many countries the access to the most recent, effective anticancer therapies and represents a significant obstacle to the design and realization of combinatorial trials. Already approved, anticancer and nonanticancer drugs can be considered for in silico, preclinical, and clinical repurposing approaches and offer the significant advantages of a potentially cheaper, faster, and safer validation. This review discusses recent advances and challenges in the field.

Impact of statin use on cancer-specific mortality and recurrence: A meta-analysis of 60 observational studies

This meta-analysis mainly summarized the studies reporting an association between statin use and cancer-specific mortality and recurrence or progression of cancer patients.We systematically searched for studies about the statin used in cancer patients in electronic databases, including PubMed, Web of Science, Cochrane, Clinical Trials, from inception through the November 2019. A total of 60 studies which included 953,177 participants were eligible with 233,322 cancer patients used statin. Our analysis selected studies presented with outcome based on hazard ratios (HRs) and 95% confidence intervals (CIs) of cancer-specific mortality and cancer recurrence-free survival or progression-free survival. Heterogeneity between the studies was examined using I statistics, and sensitivity analyses were conducted to assess the robustness of the findings. All statistical analyses were performed using RevMan software (version 5.3).The use of statin was potentially associated with a decline in cancer-specific mortality in cancer patients (HR = 0.78; 95% CI: 0.74, 0.84; n = 39; I = 85%). Furthermore, statin use was associated with improved recurrence-free survival (HR = 0.87; 95% CI: 0.78,0.97; n = 23; I = 64%), but not with improvement in progression-free survival (HR = 1.05; 95% CI: 0.95,1.16; n = 14; I2 = 38%).The meta-analysis demonstrated that statin use could exhibit potential survival benefit in the prognosis of cancer patients. But our results are conservative for statins to improve disease recurrence and progression. These findings should be assessed in a prospective randomized cohort.

Cholesterol and beyond - The role of the mevalonate pathway in cancer biology

Cancer is a multifaceted global disease. Transformation of a normal to a malignant cell takes several steps, including somatic mutations, epigenetic alterations, metabolic reprogramming and loss of cell growth control. Recently, the mevalonate pathway has emerged as a crucial regulator of tumor biology and a potential therapeutic target. This pathway controls cholesterol production and posttranslational modifications of Rho-GTPases, both of which are linked to several key steps of tumor progression. Inhibitors of the mevalonate pathway induce pleiotropic antitumor-effects in several human malignancies, identifying the pathway as an attractive candidate for novel therapies. In this review, we will provide an overview about the role and regulation of the mevalonate pathway in certain aspects of cancer initiation and progression and its potential for therapeutic intervention in oncology.

PARP1 rs1805407 Increases Sensitivity to PARP1 Inhibitors in Cancer Cells Suggesting an Improved Therapeutic Strategy

Personalized cancer therapy relies on identifying patient subsets that benefit from a therapeutic intervention and suggest alternative regimens for those who don't. A new data integrative approach, based on graphical models, was applied on our multi-modal -omics, and clinical data cohort of metastatic melanoma patients. We found that response to chemotherapy is directly linked to ten gene expression, four methylation variables and PARP1 SNP rs1805407. PARP1 is a DNA repair gene critical for chemotherapy response and for which FDA-approved inhibitors are clinically available (olaparib). We demonstrated that two PARP inhibitors (ABT-888 and olaparib) make SNP carrier cancer cells of various histologic subtypes more sensitive to alkylating agents, but they have no effect in wild-type cells. Furthermore, PARP1 inhibitors act synergistically with chemotherapy in SNP carrier cells (especially in ovarian cancer for which olaparib is FDA-approved), but they are additive at best in wild-type cancer cells. Taken together, our results suggest that the combination of chemotherapy and PARP1 inhibition may benefit the carriers of rs1805407 in the future and may be used in personalized therapy strategies to select patients that are more likely to respond to PARP inhibitors.

Induction of 3-hydroxy-3-methylglutaryl-CoA reductase mediates statin resistance in breast cancer cells

The mevalonate pathway has emerged as a promising target for several solid tumors. Statins are inhibitors of the 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the rate-limiting enzyme of this pathway, and are commonly used to treat patients with hypercholesterolemia. Pleiotropic antitumor mechanisms of statins have been demonstrated for several human cancer types. However, cancer cells differ in their individual statin sensitivity and some cell lines have shown relative resistance. In this study we demonstrate, that the human breast cancer cell lines MDA-MB-231, MDA-MB-468, MCF-7, and T47D are differentially affected by statins. Whereas the vitality of MDA-MB-231 and MDA-MB-468 cells was reduced by up to 60% using atorvastatin, simvastatin, or rosuvastatin (p < 0.001), only marginal effects were seen in T47D and MCF-7 cells following exposure to statins. Statin treatment led to an upregulation of HMGCR mRNA and protein expression by up to sixfolds in the statin-resistant cells lines (p < 0.001), but no alterations of HMGCR were observed in the statin-sensitive MDA-MB-231 and MDA-MB-468 cells. The knockdown of HMGCR prior to statin treatment sensitized the resistant cell lines, reflected by a 70% reduction in vitality, increased apoptotic DNA fragmentation (sixfold) and by accumulation of the apoptosis marker cleaved poly-ADP ribose polymerase. Statins induced a cleavage of the sterol-regulatory element-binding protein (SREBP)-2, a transcriptional activator of the HMGCR, in T47D and MCF-7 cells. The inhibition of SREBP-2 activation by co-administration of dipyridamole sensitized MCF-7 and T47D cells for statins (loss of vitality by 80%; p < 0.001). Furthermore, assessment of a statin-resistant MDA-MB-231 clone, generated by long-term sublethal statin exposure, revealed a significant induction of HMGCR expression by up to 12-folds (p < 0.001). Knockdown of HMGCR restored statin sensitivity back to levels of the parental cells. In conclusion, these results indicate a resistance of cancer cells against statins, which is in part due to the induction of HMGCR.

Identification of tRNA-derived ncRNAs in TCGA and NCI-60 panel cell lines and development of the public database tRFexplorer

Next-generation sequencing is increasing our understanding and knowledge of non-coding RNAs (ncRNAs), elucidating their roles in molecular mechanisms and processes such as cell growth and development. Within such a class, tRNA-derived ncRNAs have been recently associated with gene expression regulation in cancer progression. In this paper, we characterize, for the first time, tRNA-derived ncRNAs in NCI-60. Furthermore, we assess their expression profile in The Cancer Genome Atlas (TCGA). Our comprehensive analysis allowed us to report 322 distinct tRNA-derived ncRNAs in NCI-60, categorized in tRNA-derived fragments (11 tRF-5s, 55 tRF-3s), tRNA-derived small RNAs (107 tsRNAs) and tRNA 5' leader RNAs (149 sequences identified). In TCGA, we were able to identify 232 distinct tRNA-derived ncRNAs categorized in 53 tRF-5s, 58 tRF-3s, 63 tsRNAs and 58 5' leader RNAs. This latter group represents an additional evidence of tRNA-derived ncRNAs originating from the 5' leader region of precursor tRNA. We developed a public database, tRFexplorer, which provides users with the expression profile of each tRNA-derived ncRNAs in every cell line in NCI-60 as well as for each TCGA tumor type. Moreover, the system allows us to perform differential expression analyses of such fragments in TCGA, as well as correlation analyses of tRNA-derived ncRNAs expression in TCGA and NCI-60 with gene and miRNA expression in TCGA samples, in association with all omics and compound activities data available on CellMiner. Hence, the tool provides an important opportunity to investigate their potential biological roles in absence of any direct experimental evidence. Database URL: https://trfexplorer.cloud/.

Statins attenuate outgrowth of breast cancer metastases

Background

Metastasis in breast cancer foreshadows mortality, as clinically evident disease is aggressive and generally chemoresistant. Disseminated breast cancer cells often enter a period of dormancy for years to decades before they emerge as detectable cancers. Harboring of these dormant cells is not individually predictable, and available information suggests that these micrometastatic foci cannot be effectively targeted by existing therapies. As such, long-term, relatively non-toxic interventions that prevent metastatic outgrowth would be an advance in treatment. Epidemiological studies have found that statins reduce breast cancer specific mortality but not the incidence of primary cancer. However, the means by which statins reduce mortality without affecting primary tumor development remains unclear.

Methods

We examine statin efficacy against two breast cancer cell lines in models of breast cancer metastasis: a 2D in vitro co-culture model of breast cancer cell interaction with the liver, a 3D ex vivo microphysiological system model of breast cancer metastasis, and two independent mouse models of spontaneous breast cancer metastasis to the lung and liver, respectively.

Results

We demonstrate that statins can directly affect the proliferation of breast cancer cells, specifically at the metastatic site. In a 2D co-culture model of breast cancer cell interaction with the liver, we demonstrate that atorvastatin can directly suppress proliferation of mesenchymal but not epithelial breast cancer cells. Further, in an ex vivo 3D liver microphysiological system of breast cancer metastasis, we found that atorvastatin can block stimulated emergence of dormant breast cancer cells. In two independent models of spontaneous breast cancer metastasis to the liver and to the lung, we find that statins significantly reduce proliferation of the metastatic but not primary tumor cells.

Conclusions

As statins can block metastatic tumor outgrowth, they should be considered for use as long-term adjuvant drugs to delay clinical emergence and decrease mortality in breast cancer patients.

Concomitant attenuation of HMG-CoA reductase expression potentiates the cancer cell growth-inhibitory effect of statins and expands their efficacy in tumor cells with epithelial characteristics

HMG-CoA reductase (HMGCR) inhibitors, statins, are potent cholesterol reducing drugs that exhibit anti-tumor effects in vitro and in animal models, including attenuation of metastasis formation, and their use correlates with reduced cancer-specific mortality in retrospective human cohort studies. However, E-cadherin expressing epithelial- and mixed epithelial-mesenchymal cancer cell lines (reflective of primary and outgrowing metastatic tumor cells, respectively) require higher statin concentrations than mesenchymal-like tumor cells (reflective of in-circulation metastatic tumor cells) to achieve the same degree of growth inhibition. Here, we show that attenuation of HMGCR expression in the presence of atorvastatin leads to stronger growth inhibition than dual target blockade of the mevalonate pathway in relatively statin resistant cell lines, mainly through inhibition of protein prenylation pathways. Thus, combined inhibition of the mevalonate pathway's rate-limiting enzyme, HMGCR, can improve atorvastatin's growth inhibitory effect on epithelial- and mixed mesenchymal-epithelial cancer cells, a finding that may have implications for the design of future anti-metastatic cancer therapies.

The poor design of clinical trials of statins in oncology may explain their failure - Lessons for drug repurposing

Statins are widely used to treat hypercholesterolaemia. However, by inhibiting the production of mevalonate, they also reduce the production of several isoprenoids that are necessary for the function of small GTPase oncogenes such as Ras. As such, statins offer an attractive way to inhibit an "undruggable" target, suggesting that they may be usefully repurposed to treat cancer. However, despite numerous studies, there is still no consensus whether statins are useful in the oncology arena. Numerous preclinical studies have provided evidence justifying the evaluation of statins in cancer patients. Some retrospective studies of patients taking statins to control cholesterol have identified a reduced risk of cancer mortality. However, prospective clinical studies have mostly not been successful. We believe that this has occurred because many of the prospective clinical trials have been poorly designed. Many of these trials have failed to take into account some or all of the factors identified in preclinical studies that are likely to be necessary for statins to be efficacious. We suggest an improved trial design which takes these factors into account. Importantly, we suggest that the design of clinical trials of drugs which are being considered for repurposing should not assume it is appropriate to use them in the same way as they are used in their original indication. Rather, such trials deserve to be informed by preclinical studies that are comparable to those for any novel drug.