Investigation of antitumor effects of sorafenib and lapatinib alone and in combination on MCF-7 breast cancer cells

Quantum DFT analysis and molecular docking investigation of various potential breast cancer drugs

Breast cancer is among the deadliest cancers worldwide, highlighting the urgent need for effective treatments. This study employs density functional theory (DFT) and molecular docking analyses to evaluate the anti-cancer efficacy and specificity of drug molecules lapatinib, tucatinib, neratinib, anastrozole, and letrozole. DFT analysis provides comprehensive insights into the structural, electronic, optical, and vibrational properties of these drugs, helping to elucidate their molecular stability and reactivity through global reactivity descriptors. Additionally, molecular docking simulations reveal the binding conformations and interaction profiles of these drugs with key breast cancer targets, underscoring their therapeutic potential. Docking results indicate that lapatinib, tucatinib, and neratinib have high binding affinities for HER2, with lapatinib exhibiting the strongest overall binding, particularly with PDK1 (PDB ID: 1UU7), PAK4 (PDB ID: 2X4Z), GSK3 (PDB ID: 1GNG), and HER2 (PDB ID: 2IOK). The stable hydrogen bonding and other interactions observed with lapatinib support its effectiveness in treating HER2-positive breast cancers, tucatinib's selective HER2 binding reduces off-target effects, while neratinib's irreversible binding provides prolonged inhibition, making it useful for overcoming resistance in HER2-positive cases. In contrast, anastrozole and letrozole show lower binding affinities for HER2 and EGFR due to their simpler structures but are potent aromatase inhibitors, making them effective in treating estrogen receptor-positive (ER-positive) breast cancers. In conclusion, DFT and molecular docking studies affirm the suitability of lapatinib, tucatinib, and neratinib for HER2-positive cancers, while anastrozole and letrozole are effective in ER-positive cancers, emphasizing the role of molecular structure and binding affinity in optimizing cancer treatment strategies.

Predicting effective drug combinations for cancer treatment using a graph-based approach

Drug combination therapy, involving the use of two or more drugs, has been widely employed to treat complex diseases such as cancer. It enhances therapeutic efficacy, reduces drug resistance, and minimizes side effects. However, traditional methods to identify effective drug combinations are time-consuming, costly, and less efficient than computational methods. Therefore, developing computational approaches to predict drug combinations has become increasingly important. In this paper, we developed the Random Walk with Restart for Drug Combination (RWRDC) model to predict effective drug combinations for cancer therapy. The RWRDC model offers a quantitative mathematical method for predicting the potential effective drug combinations. Cross-validation results indicate that the RWRDC model outperforms other predictive models, particularly in breast, colorectal, and lung cancer predictions across various performance metrics. We have theoretically proven the convergence of its algorithm and provided an explanation for the algorithm's rationality. A targeted case study on breast cancer further highlights the capability of RWRDC to identify effective drug combinations. These findings highlight our model as a novel and effective tool for discovering potential effective drug combinations, offering new possibilities in therapy. Additionally, the graph-based framework of RWRDC holds potential for predicting drug combinations in other complex diseases, expanding its utility in the medical field.

A prognostic four-gene signature and a therapeutic strategy for hepatocellular carcinoma: Construction and analysis of a circRNA-mediated competing endogenous RNA network

BACKGROUND

Hepatocellular carcinoma (HCC) has a poor long-term prognosis. The competition of circular RNAs (circRNAs) with endogenous RNA is a novel tool for predicting HCC prognosis. Based on the alterations of circRNA regulatory networks, the analysis of gene modules related to HCC is feasible.

METHODS

Multiple expression datasets and RNA element targeting prediction tools were used to construct a circRNA-microRNA-mRNA network in HCC. Gene function, pathway, and protein interaction analyses were performed for the differentially expressed genes (DEGs) in this regulatory network. In the protein-protein interaction network, hub genes were identified and subjected to regression analysis, producing an optimized four-gene signature for prognostic risk stratification in HCC patients. Anti-HCC drugs were excavated by assessing the DEGs between the low- and high-risk groups. A circRNA-microRNA-hub gene subnetwork was constructed, in which three hallmark genes, KIF4A, CCNA2, and PBK, were subjected to functional enrichment analysis.

RESULTS

A four-gene signature (KIF4A, CCNA2, PBK, and ZWINT) that effectively estimated the overall survival and aided in prognostic risk assessment in the The Cancer Genome Atlas (TCGA) cohort and International Cancer Genome Consortium (ICGC) cohort was developed. CDK inhibitors, PI3K inhibitors, HDAC inhibitors, and EGFR inhibitors were predicted as four potential mechanisms of drug action (MOA) in high-risk HCC patients. Subsequent analysis has revealed that PBK, CCNA2, and KIF4A play a crucial role in regulating the tumor microenvironment by promoting immune cell invasion, regulating microsatellite instability (MSI), and exerting an impact on HCC progression.

CONCLUSIONS

The present study highlights the role of the circRNA-related regulatory network, identifies a four-gene prognostic signature and biomarkers, and further identifies novel therapy for HCC.

Co-delivery of lapatinib and 5-fluorouracil transfersomes using transpapillary iontophoresis for breast cancer therapy

Combination chemotherapy, involving the intervention of two or more anti-neoplastic agents has been the cornerstone in breast cancer treatment, owing to the applications it holds in contrast to the mono-therapy approach. This research predominantly focussed on proving the synergy between Lapatinib (LPT) and 5-Fluorouracil (5-FU) and further enhancing its localized permeation via transfersome-loaded delivery and iontophoresis to treat breast tumors. The IC50 values for LPT and 5-FU were found to be 19.38 µg/ml and 5.7 µg/ml respectively and their synergistic effect was proven by the Chou-Talalay assay using CompuSyn software. Furthermore, LPT and 5-FU were encapsulated within transfersomes and administered via the transpapillary route. The drug-loaded carriers were characterized for their particle size, polydispersity index, zeta potential, and entrapment efficiency. The ex vivo rat skin permeation studies indicated that when compared to LPT dispersion and 5-FU solution, drug-loaded transfersomes exhibited better permeability and their transpapillary permeation was enhanced on using iontophoresis. Moreover, both LPT and 5-FU transfersomes were found to be stable for 3 months when stored at a temperature of 5 ± 3 °C. The results indicated that this treatment strategy could be an effective approach in contrast to some of the conventional treatments employed to date.

Comparative anti-proliferative effects of potential HER2 inhibitors on a panel of breast cancer cell lines

BACKGROUND

Breast cancer is one of the most lethal types of cancer in women worldwide. The human epidermal growth factor receptor 2 (HER2) is considered as a validated target in breast cancer therapy. Previously, we have used quantitative structure activity relationship QSAR equations and their associated pharmacophore models to screen for new promising HER2 structurally diverse inhibitory leads which were tested against HER2-overexpressing SKOV3 ovarian cancer cell line.

OBJECTIVE

In this study, we sought to explore the effect of most active ligands against different normal and breast cancer cell lines that represent different breast cancer subtypes with distinguished expression levels in HER2 and HER1.

METHODS

We have tested the promising compounds against SKBR3, MDA-MB-231, MCF7, human fibroblast, and MCF10 cell lines. To understand the inhibitory effects of the active ligands against HER2 over expressed breast cancer cell lines, all inhibitors and the control compound, lapatinib, were docked into the active site of HER2 enzyme performed using Ligand Fit docking engine and PMF scoring function.

RESULTS

Five ligands exhibited promising results with relatively low IC₅₀ values on cells that amplify HER2 and high IC₅₀ on those that do not express such a receptor. The most potent compound (compound 13) showed an IC₅₀ of 0.046 µM. To test their toxicity against normal cells, the active compounds were tested against both normal fibroblast and normal breast cancer cell MCF-10 and relatively high IC₅₀ values were scored. The IC₅₀ values on HER2 over-expressed breast cancer and normal fibroblast cells provided a promising safety index. Docking results showed the highest similarity in the binding site between the most active ligand and the lapatinib.

CONCLUSION

Our pharmacophore model resulted in a high potent ligand that shows high potency against HER2 positive breast cancer and relatively low toxicity towards the normal human cells.

Sorafenib for the treatment of breast cancer

INTRODUCTION

Breast cancer treatment includes many options depending on the tumor clinicopathological profile, which groups breast cancer into various subtypes. Bevacizumab is currently the only drug capable of targeting angiogenesis in breast cancer. Sorafenib has also been studied in combination with other agents. Areas covered: Pharmacological aspects of sorafenib, including results from preclinical studies on breast cancer cells; findings about clinical efficacy and safety in both single-arm and randomized clinical trials; ongoing trials. Expert opinion: Since sorafenib as a single agent has shown limited efficacy in breast cancer, its combination with other drugs is under investigation. Dose reduction is the main challenge when sorafenib is combined with chemotherapy or endocrine therapy. Although randomized phase-II trials on sorafenib plus chemotherapy versus chemotherapy alone have shown potential benefits in progression-free survival, preliminary results from a phase-III study in combination with capecitabine are negative. The definitive results of this trial and results from other ongoing phase-II trials will determine further developments of sorafenib in breast cancer. Although these additional data could help determine the most appropriate dose, drug combination and patient settings, a confirmation of the preliminary negative results reported in the phase-III trial are likely to discourage further use of sorafenib in breast cancer, given its non-negligible toxicity, lack of predicting markers, and the number of more promising drugs for breast cancer.

Recent Advances on Small-Molecule Survivin Inhibitors

Survivin, a member of the inhibitor of apoptosisproteins family, is highly expressed in most human neoplasms, but its expression is very low or undetectable in terminally differentiated normal tissues. Survivin has been shown to inhibit cancer cell apoptosis and promote cell proliferation. The overexpression of survivin closely correlates with tumor progression and drug resistance. Because of its key role in tumor formation and maintenance, survivin is considered as an ideal target for anticancer treatment. However, the development of small-molecule survivin inhibitors has been challenging due to the requirement to disrupt the protein-protein interactions. Currently only a limited number of survivin inhibitors have been developed in recent years, and most of these inhibitors reduce survivin levels by interacting with other biomolecules instead of directly interacting with survivin protein. Despite these challenges, developing potent and selective small-molecule survivin inhibitors will be important in both basic science to better understand survivin biology and in translational research to develop potentially more effective, broad-spectrum anticancer agents. In this review, the functions of survivin and its role in cancer are summarized. Recent developments, challenges, and future direction of small-molecule survivin inhibitors are also discussed in detail.