Analysis Of Drug Interactions Research Articles

#1982 Transcriptomic approach to predict drug targets in late-stage hypertensive nephropathy

Abstract Background and Aims Hypertensive nephropathy (HN) is a significant contributor to chronic kidney disease, yet the factors influencing the disease progression remains elusive. Notably, late-stage chronic kidney disease significantly impacts patient outcome. This project aims to unveil novel therapeutic targets for late-stage of HN using transcriptomic approach. Method A cohort of adult patients (n = 21; n = 9 females, mean age 57 years) with biopsy-confirmed HN were selected from the Norwegian Kidney Biopsy Registry (NKBR). Patients were classified as late-stage if eGFR≤45 ml/min/1.73 m2 at the time of biopsy. Patients were thereafter divided into “stable” (eGFR decline <3 ml/min/year) or “progressive” (eGFR decline ≥3 ml/min/year or start of renal replacement therapy) after a median follow-up of 9 years (5-15). TruSeq Exome sequencing was performed post-RNA extraction (miRNeasy FFPE kit, Qiagen) at Novogene, Cambridge, UK. R Studio (v4.2.0) and drug CTD repository in ShinyGO 0.80 facilitated data and drug interaction analysis. Results We focused on two distinct subgroups of HN patients: late stable (LS, n = 9) and late progressive (LP, n = 12). A total of n = 674 of differentially expressed genes (DEG, p-value < 0.05 and fold change (FC) ≥1.5) was identified in LS vs. LP. The subsequent drug interactive analysis of these DEGs unveiled 336 pathways with false discovery rate (FDR) < 0.05. Notably, the probenecid-related pathway demonstrated significant fold enrichment (FE=9, FDR = 1.5E-04), as depicted in Fig. 1. Particularly, key members of the SLC22 family, including SLC22A6 (FC=2.49, p-value = 0.002), SLC22A8 (FC=2.65, p-value = 0.004), SLC22A11 (FC=1.65, p-value = 0.036) and SLC22A12 (FC=1.97, p-value = 0.009) were prominently featured in this pathway. Besides their role as sole transporters, it is postulated that these proteins have central role in modulating local and systemic physiology, such as blood pressure, suggesting a potential significance of probenecid in the context of hypertensive nephropathy. Conclusion Transcriptomic profiling of kidney biopsies has strong potential to discover novel therapeutic targets, such as the probenecid-related pathway, in hypertensive nephropathy patients.

KiSS-1 Modulation by Epigenetic Agents Improves the Cisplatin Sensitivity of Lung Cancer Cells.

Epigenetic alterations my play a role in the aggressive behavior of Non-Small Cell Lung Cancer (NSCLC). Treatment with the histone deacetylase inhibitor suberoylanilide hydroxamic acid (SAHA, vorinostat) has been reported to interfere with the proliferative and invasive potential of NSCLC cells. In addition, the DNA methyltransferase inhibitor azacytidine (AZA, vidaza) can modulate the levels of the metastasis suppressor KiSS-1. Thus, since cisplatin is still clinically available for NSCLC therapy, the aim of this study was to evaluate drug combinations between cisplatin and SAHA as well as AZA using cisplatin-sensitive H460 and -resistant H460/Pt NSCLC cells in relation to KiSS-1 modulation. An analysis of drug interaction according to the Combination-Index values indicated a more marked synergistic effect when the exposure to SAHA or AZA preceded cisplatin treatment with respect to a simultaneous schedule. A modulation of proteins involved in apoptosis (p53, Bax) was found in both sensitive and resistant cells, and compared to the treatment with epigenetic agents alone, the combination of cisplatin and SAHA or AZA increased apoptosis induction. The epigenetic treatments, both as single agents and in combination, increased the release of KiSS-1. Finally, the exposure of cisplatin-sensitive and -resistant cells to the kisspeptin KP10 enhanced cisplatin induced cell death. The efficacy of the combination of SAHA and cisplatin was tested in vivo after subcutaneous inoculum of parental and resistant cells in immunodeficient mice. A significant tumor volume inhibition was found when mice bearing advanced tumors were treated with the combination of SAHA and cisplatin according to the best schedule identified in cellular studies. These results, together with the available literature, support that epigenetic drugs are amenable for the combination treatment of NSCLC, including patients bearing cisplatin-resistant tumors.

Evaluation of Medication Errors in One of the Largest Public Hospital: A Retrospective Study

BackgroundIn hospitals, medication errors still occur, especially in developing countries such as Indonesia. However, most incidents can be prevented. ObjectiveTo evaluate medication prescription errors for in and out-patients at hospitals based on pharmacists' reports of medical errors. MethodsA retrospective study was carried out between January and December 2021. Pharmacists analyzed medication error reports based on age, sex, drug name list or quantity recorded, prescription listed in the medication error report, and length of hospital stay.Statistical analysis of drug interaction and the factors affecting potential drug interactions was carried out by using multiple linear regression. ResultsApproximately 338 medication errors from 251,491 prescriptions were recorded by pharmacists across hospital departments in 2021. The age of patients with medication errors ranged from newborn babies to 86 years old, with an average of 40.9 years old (±21.03). The most common types of medication errors were prescribing errors (184, 54.4%). The average length of hospital stay was 11.35 days (±10.36). A total of 557 potential drug interactions were recorded in 182 (53.85%) prescriptions. The risk for potential drug interaction is increased by the number of medications per prescription (COR = 3.361, P < 0.001) and the age (COR = 1.001, P = 0.033). ConclusionsThe number of medication errors reported was 0.13 per 100 prescriptions, and most of these errors did not affect patients and were, therefore, not harmful. However, further research is needed to analyze medication error reports through collaboration with hospital healthcare professionals.

Assessment of education in a community hospital on healthcare providers' knowledge of and attitudes toward medical marijuana

IntroductionAlthough medical marijuana usage continues to become more socially acceptable and is increasingly regarded as a legitimate treatment alternative for certain medical conditions such as cancer and epilepsy, stigma remains. MethodsThis study examined whether offering an educational session addressing several key aspects of medical marijuana (e.g., pharmacology, legality) to healthcare providers in a community hospital setting improved knowledge about and/or altered attitudes toward marijuana use. This information was collected through administration of pre- and post-education session surveys. Multiple choice questions were utilized to assess knowledge of marijuana pharmacotherapy, pharmacodynamic interactions, and regulations, whereas descriptive analyses via Likert-scale questions determined attitudes toward medical marijuana. A secondary outcome entailed analysis of drug interactions with marijuana users via retrospective chart review. ResultsA total of 43 healthcare providers participated in the study. There were statistically significant increases in healthcare provider knowledge post-education session across multiple occupations (physician, P < .01; nurse, P < .001; pharmacist, P < .01; and nurse technician, P < .05). A total of 72 patients (83%) who self-reported marijuana use for medical or recreational purposes had a potential drug-drug interaction with marijuana. ConclusionsAs both medical and recreational marijuana continue to become legalized across the United States, formal education surrounding marijuana use and laws becomes increasingly important for healthcare providers and can be highly effective in preventing misinformation.

Retrospective Analysis of Potential Adverse Drug Interactions in the Drugs Prescribed to the Elderly at a Tertiary Health Care Center in Raipur, Chhattisgarh, Central India.

Background The elderly population differs from adults in having various physiological changes and multiple diseases, which demand the use of multiple medications. The practice of polypharmacy in the elderly leads to numerous harmful effects like adverse drug reactions, adverse drug-drug interactions (DDIs), poor compliance, etc. Methodology This study collected 295 case files of elderly patients retrospectively in the Departments of General Medicine, Cardiology and Nephrology after obtaining Institute Ethics Committee approval to look for the potential adverse DDIs with their severity according to the clinical significance. Results and interpretation The total numberof adverse DDIs identified was 156, the maximum in Category 'C.' Salbutamol plus carvedilol/propranolol, ramipril plus telmisartan and ivabradine plus diltiazem were the adverse DDIs categorized under severity 'X'. The identified DDIs were categorised according to the mechanism such as increased bleeding risk, hypokalemia, hyperkalaemia, reduced effect of drugs and increased effect of drugs. Conclusion Polypharmacy can lead to several adverse consequences in the elderly, of whichadverse DDIs play a crucial role in harmful health outcomes. This study brings out the significance of predicting drug interactions beforehand which can reduce the risk of bleeding and other risks of hyper/hypokalaemia, hyponatremia and hypoglycaemia.

A low-cost machine learning framework for predicting drug-drug interactions based on fusion of multiple features and a parameter self-tuning strategy.

Poly-drug therapy is now recognized as a crucial treatment, and the analysis of drug-drug interactions (DDIs) offers substantial theoretical support and guidance for its implementation. Predicting potential DDIs using intelligent algorithms is an emerging approach in pharmacological research. However, the existing supervised models and deep learning-based techniques still have several limitations. This paper proposes a novel DDI analysis and prediction framework called the Multi-View Semi-supervised Graph-based (MVSG) framework, which provides a comprehensive judgment by integrating multiple DDI features and functions without any time-consuming training process. Unlike conventional approaches, MVSG can search for the most suitable similarity (or distance) measurement among DDI data and construct graph structures for each feature. By employing a parameter self-tuning strategy, MVSG fuses multiple graphs according to the contributions of features' information. The actual anticancer drug data are extracted from the authoritative public database for evaluating the effectiveness of our framework, including 904 drugs, 7730 DDI records and 19 types of drug interactions. Validation results indicate that the prediction is more accurate when multiple features are adopted by our framework. In comparison to conventional machine learning techniques, MVSG can achieve higher performance even with less labeled data and without a training process. Finally, MVSG is employed to narrow down the search for potential valuable combinations.

Electroanalysis in Pharmacogenomic Studies: Mechanisms of Drug Interaction with DNA.

The review discusses electrochemical methods for analysis of drug interactions with DNA. The electroanalysis method is based on the registration of interaction-induced changes in the electrochemical oxidation potential of heterocyclic nitrogenous bases in the DNA molecule and in the maximum oxidation current amplitude. The mechanisms of DNA-drug interactions can be identified based on the shift in the electrooxidation potential of heterocyclic nitrogenous bases toward more negative (cathodic) or positive (anodic) values. Drug intercalation into DNA shifts the electrochemical oxidation potential to positive values, indicating thermodynamically unfavorable process that hinders oxidation of nitrogenous bases in DNA. The potential shift toward the negative values indicates electrostatic interactions, e.g., drug binding in the DNA minor groove, since this process does not interfere with the electrochemical oxidation of bases. The concentration-dependent decrease in the intensity of electrochemical oxidation of DNA bases allows to quantify the type of interaction and calculate the binding constants.

Pyrazoline B-Paclitaxel or Doxorubicin Combination Drugs Show Synergistic Activity Against Cancer Cells: In silico Study.

Multidrug resistance in various cancer types is a major obstacle in cancer treatment. The concept of a single drug molecular target often causes treatment failure due to the complexity of the cellular processes. Therefore, combination chemotherapy, in which two or more anticancer drugs are co-administered, can overcome this problem because it potentially have synergistic efficacy besides reducing resistance, and drug doses. Previously, we reported that pyrazoline B had promising anticancer activity in both in silico and in vitro studies. To increase the efficacy of this drug, co-administration with established anticancer drugs such as doxorubicin and paclitaxel is necessary. In this study, we used an in silico approach to predict the synergistic effect of pyrazoline B with paclitaxel or doxorubicin using various computational frameworks and compared the results with those of an established study on the combination of doxorubicin-cyclophosphamide and paclitaxel-ascorbic acid. Drug interaction analysis showed the combination was safe with no contraindications or side effects. Furthermore, molecular docking studies revealed that doxorubicin-pyrazoline B and doxorubicin-cyclophosphamide may synergistically inhibit cancer cell proliferation by inhibiting the binding of topoisomerase I to the DNA chain. Moreover, the combination of pyrazoline B-paclitaxel may has synergistic activity to cause apoptosis by inhibiting Bcl2 binding to the Bax fragment or inhibiting cell division by inhibiting α-β tubulin disintegration. Paclitaxel-ascorbic acid had a synergistic effect on the inhibition of α-β tubulin disintegration. The results show that this combination is promising for further in vitro and in vivo studies.

"Optimizing Pharmaceutical Formulations: Advancements in Nanosuspension Pre-Formulation to Enhance Solubility and Bioavailability of Active Agents"

This study aimed to enhance the bioavailability of a poorly water soluble drug by developing a nanosuspension through an innovative formulation method. The nanosuspension was produced with meticulous attention to the materials reliability and excellent quality. Nepafenac was characterised in the pre-formulation study by establishing its melting point, solubility in different solvents, organoleptic properties, and creating a calibration curve. We utilised UV spectroscopy to determine the maximum wavelength (?max) of Nepafenac and construct a standard calibration curve in ethanol. To ensure the compatibility of the medicine with the polymers (Pluronic F127 and HPMC E 5), Fourier Transform Infrared Spectroscopy (FTIR) was utilised for drug interaction analysis. The nanosuspension was produced using the solvent diffusion approach. The effect of different concentrations of Poloxamer 407 and HPMC E 5 on the formulation's effectiveness was investigated experimentally using a 32 complete factorial design. We used Response Surface Methodology (RSM) and statistical analysis to enhance the formulation concerning in vitro release, particle size, and viscosity. The pre-formulation characteristics of Nepafenac met the standards outlined in the Pharmacopoeial regulations. The maximum absorption wavelength (?max) of Nepafenac was confirmed by UV spectroscopy, and a reliable calibration curve was created. The FTIR analysis showed no chemical interaction between the medicine and polymers. RSM and experimental design indicated that Poloxamer 407 and HPMC E 5 had a substantial impact on the performance of the nanosuspension. Analysis of variance (ANOVA) confirmed the model and parameters that influence controlled drug release percentage, particle size, and viscosity. Optimal conditions for enhancing drug delivery and reducing particle size were determined by the analysis of contour and response surface plots. The optimal parameter values, as indicated in the desirability plots, closely matched the anticipated values. The experimentation confirmed the viability and effectiveness of the nanosuspension formulation generated based on the RSM findings.

Potential drug-drug interactions of frequently prescribed medications in long COVID detected by two electronic databases.

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to a wide range of acute and chronic complications including long COVID, a well-known chronic sequela. Long COVID often necessitates long-term treatment, which may lead to an increased potential for drug-drug interactions (DDIs). The objective of this study was to assess potential DDIs among frequently prescribed medications in long COVID by using two electronic databases. Sixty frequently prescribed agents were selected from Thailand's National List of Essential Medicine 2022 for potential DDI analysis by Micromedex and Drugs.com. From these databases, 488 potential DDIs were identified. There were 271 and 434 DDI pairs based on Micromedex and Drugs.com, respectively. Among these DDIs, 77 pairs were labeled as contraindicated or major by both databases. The most common mechanisms for these serious interactions are cytochrome P450 (CYP) inhibition (45%), CYP induction (19%), and QT interval prolongation (7.8%). Based on Fleiss' kappa (0.073), there was only slight agreement of the DDI severity classifications between these two databases. In conclusion, a large number of potential DDIs were detected among frequently prescribed medications for long COVID. Health care providers should be aware of these DDIs, particularly those that are deemed as contraindicated or major. These DDIs are most likely to cause significant adverse events in patients with long COVID because polypharmacy is common.

Venetoclax Synergizes Sunitinib in Renal Cell Carcincoma through Inhibition of Bcl-2.

More effective treatment options for patients with renal cell carcinoma (RCC) are needed, in particular advanced RCC. Sunitinib, a multitarget tyrosine kinase inhibitor, is a first-line treatment of metastatic RCC. However, the management of sunitinib-induced adverse events and resistance is complex. In hematological malignancies, effective targeting of anti-apoptotic proteins such as Bcl-2 has been achieved, but limited progress has been made in solid tumors. This work systematically investigated the therapeutic potential of the combination of sunitinib and venetoclax, a Bcl-2 inhibitor, in preclinical RCC models. Quantitative analysis of drug interactions was performed. Cell viability was examined after drug treatment or Bcl-2 siRNA depletion. RCC xenograft mouse model was applied to validate the efficacy of sunitinib and venetoclax. A strong synergistic interaction between sunitinib and venetoclax was observed across a range of different dose levels in all tested RCC cell lines. Sequential treatment studies show that the sequential addition of venetoclax and then sunitinib is superior to concurrent treatment and the sequential addition of sunitinib and then venetoclax in decreasing RCC cell viability. The sensitivity of RCC cell lines to venetoclax treatment negatively correlates with their Bcl-2 levels. Specific depletion of Bcl-2 mimics the synergistic effects of venetoclax with sunitinib. Treatment of mice implanted with high Bcl-2-expressing RCC cells reveals that a combination of venetoclax and sunitinib at a non-toxic dose displays complete regression of tumor growth throughout the whole duration of treatment. Our work demonstrates that inhibiting Bcl-2 by venetoclax synergistically enhances sunitinib's efficacy in RCC. Venetoclax holds great potential as a viable option for clinical use.

Targeting multiple disease hallmarks using a synergistic disease-modifying drug combination ameliorates osteoarthritis via inhibition of senescence and inflammation

AimsOsteoarthritis (OA), is a debilitating disease characterized by progressive cartilage degradation, synovial inflammation, and chondrocyte senescence. Various treatment agents independently targeting these hallmarks have been investigated. However, due to the complex multifaceted nature of OA, no disease-modifying osteoarthritis drugs are clinically available. In an attempt to overcome this, we developed a combinatorial approach and demonstrated the efficacy of TsC [Tissue inhibitor of metalloproteinase-3 (TIMP3) + sulfated carboxymethylcellulose (sCMC)] and piperlongumine (PL) combination for the amelioration of OA in a goat ex vivo OA model. Main methodsThe efficacy of the drug combination was evaluated using the goat ex vivo OA explant model and results were validated in clinically relevant human OA cartilage explants. The chondroprotective effects were evaluated in terms of reduced inflammation and cartilage matrix loss, reduction in chondrosenescence, and reduced oxidative stress. Key findingsA combination of TsC and PL (TsC-PL) significantly reduced inflammation, cartilage matrix loss, chondrosenescence, and oxidative stress in the goat ex vivo OA model and showed chondroprotective effects. Further, similar chondroprotective effects were observed in human OA cartilage. Additionally, the coefficient of drug interaction analysis indicated that the combination of TsC and PL had a synergistic effect in reducing matrix degrading proteases and inflammation (goat ex vivo OA model) and Reactive oxygen species (ROS) production (human OA cartilage). SignificanceCombinatorial treatment with TsC and PL demonstrated potential disease-modifying effects for the treatment of osteoarthritis via inhibition of inflammation and senescence and supports the usage of treatment strategies targeting multiple pathological factors of OA simultaneously.

Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach.

Frontal temporal dementia (FTD) is a neurological disorder known to have fewer therapeutic options. So far, only a few biomarkers are available for FTD that can be used as potential comorbidity targets. For example, genes such as VCP, which has a role in breast cancer, and WFS1, which has a role in COVID-19, are known to show a role in FTD as well. To this end, in the present study, we aim to identify potential biomarkers or susceptible genes for FTD that show comorbidities with diseases such as COVID-19 and breast cancer. A dataset from Gene Expression Omnibus containing FTD expression profiles from African American and white ethnicity backgrounds was included in our study. In FTD samples of the GSE193391 dataset, we identified 305 DEGs, with 168 genes being up-regulated and 137 genes being down-regulated. We conducted a comorbidity analysis for COVID-19 and breast cancer, followed by an analysis of potential drug interactions, pathogenicity, analysis of genetic variants, and functional enrichment analysis. Our results showed that the genes AKT3, GFAP, ADCYAP1R1, VDAC1, and C4A have significant transcriptomic alterations in FTD along with the comorbidity status with COVID-19 and breast cancer. Functional pathway analysis revealed that these comorbid genes were significantly enriched in the pathways such as glioma, JAK/STAT signaling, systematic lupus erythematosus, neurodegeneration-multiple diseases, and neuroactive ligand-receptor interaction. Overall, from these results, we concluded that these genes could be recommended as potential therapeutic targets for the treatment of comorbidities (breast cancer and COVID-19) in patients with FTD.

Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex

Opioid use disorder (OUD) is influenced by genetic and environmental factors. While recent research suggests epigenetic disturbances in OUD, this is mostly limited to DNA methylation (5mC). DNA hydroxymethylation (5hmC) has been widely understudied. We conducted a multi-omics profiling of OUD in a male cohort, integrating neuronal-specific 5mC and 5hmC as well as gene expression profiles from human postmortem orbitofrontal cortex (OUD = 12; non-OUD = 26). Single locus methylomic analysis and co-methylation analysis showed a higher number of OUD-associated genes and gene networks for 5hmC compared to 5mC; these were enriched for GPCR, Wnt, neurogenesis, and opioid signaling. 5hmC marks also showed a higher correlation with gene expression patterns and enriched for GWAS of psychiatric traits. Drug interaction analysis revealed interactions with opioid-related drugs, some used as OUD treatments. Our multi-omics findings suggest an important role of 5hmC and reveal loci epigenetically dysregulated in OFC neurons of individuals with OUD.

Drug repurposing: databases and pipelines.

The concept of drug repurposing is focused on the repositioning of drug molecules that have already undergone safety trials. There are different strategies for drug repurposing. Network-based strategy focuses on the evaluation of drug combinations in a molecular environment with multi-target hits and analysis of drug interactions. Implementation of any in silico strategy requires several databases and pipelines for executing the process of shortlisting appropriate drugs.

Pharmacoepidemiological and drug interaction analysis in the treatment of chronic renal and hepatic failure

Pharmacoepidemiological and drug interaction analysis in the treatment of chronic renal and hepatic failure

Analysis of drug interactions and their implications for laboratory test results

Analysis of drug interactions and their implications for laboratory test results

Pola Pengobatan Dan Analisis Potensi Interaksi Obat Pada Pasien Anak Demam Berdarah Dengue (Dbd) Di Rumah Sakit Kalimantan Timur

Background: Dengue hemorrhagic fever is caused by transmission of the dengue virus by the Aedes aegypti mosquito. Dengue hemorrhagic fever is common in tropical countries such as Indonesia, where new cases are found every year. According to WHO that dengue fever is the leading cause of hospitalization for children. Dengue hemorrhagic disease is more susceptible to infection in children because the child's immune system is still very weak, so the virus is easy to multiply quickly in the body. Knowing the pattern of treatment and analysis of potential drug interactions in pediatric patients with dengue hemorrhagic fever at the East Kalimantan Hospital. Methods: The research is non-experimental observational with a descriptive research design. The approach method used is the cross sectional method. Identification of data collection is carried out retrospectively, by taking sources from medical records for the years 2020-2021. Results: Of the 47 patient samples, the most cases were male patients as many as 27 patients (57%) with the age of 11 years as many as 11 patients (23%) with a length of stay of less than 7 days as many as 45 patients (96%). Based on the pattern of treatment, the most widely used therapy was the rehydration group (RL) 28 patients (60%). In the case of drug interactions occurred as many as 2 cases (3%). Conclusion: In this study show that there are cases of drug interactions.

Analysis of drug interactions in patients with heart disease: An experience report

Cardiopathic patients routinely use multiple medications. This polypharmacy, although an important strategy for the control of comorbidities, can lead to numerous drug interactions, in addition to results of altered magnitude and specificity¹. These interactions can be beneficial and expected, increasing treatment effectiveness, but they can also be undesirable, causing the opposite effect to the desired one.

2-Hydroxypropyl-β-cyclodextrin (HPβCD) as a Potential Therapeutic Agent for Breast Cancer.

Cholesterol accumulation is documented in various malignancies including breast cancer. Consequently, depleting cholesterol in cancer cells can serve as a viable treatment strategy. We identified the potency of 2-hydroxypropyl-β-cyclodextrin (HPβCD), a cholesterol-depletor in vitro against two breast cancer cell lines: MCF-7 (Oestrogen-receptor positive, ER+) and MDA-MB-231 (Triple negative breast cancer (TNBC)). The results were then compared against two non-cancerous cell lines using cytotoxic-, apoptosis-, and cholesterol-based assays. Treatment with HPβCD showed preferential and significant cytotoxic potential in cancer cells, inducing apoptosis in both cancer cell lines (p < 0.001). This was mediated due to significant depletion of cholesterol (p < 0.001). We further tested HPβCD in a MF-1 mice (n = 14) xenograft model and obtained 73.9%, 94% and 100% reduction in tumour size for late-, intermediate-, and early-stage TNBC, respectively. We also detected molecular-level perturbations in the expression patterns of several genes linked to breast cancer and cholesterol signalling pathways using RT2-PCR arrays and have identified SFRP1 as a direct binding partner to HPβCD through SPR drug interaction analysis. This work unravels mechanistic insights into HPβCD-induced cholesterol depletion, which leads to intrinsic apoptosis induction. Results from this study potentiate employing cholesterol depletion as a promising unconventional anticancer therapeutic strategy, which warrants future clinical investigations.