Network pharmacology-based evaluation of natural compounds with paclitaxel for the treatment of metastatic breast cancer

Combination of paclitaxel with rosiglitazone induces synergistic cytotoxic effects in ovarian cancer cells

Ovarian cancer is known to be a challenging disease to detect at an early stage and is a major cause of death among women. The current treatment for ovarian cancer typically involves a combination of surgery and the use of drugs such as platinum-based cytotoxic agents, anti-angiogenic drugs, etc. However, current treatment methods are not always effective in preventing the recurrence of ovarian cancer. As a result, the treatments administered after a relapse need to be more aggressive, leading to increased toxicity and drug resistance. To address this issue, researchers are exploring the potential of combining existing anticancer agents with novel or repurposed drugs to reduce the side effects and improve the effectiveness of treatment. In this study, we have investigated the use of rosiglitazone, a well-known anti-diabetic drug, in combination with the chemotherapeutic drug, paclitaxel for the prevention of ovarian cancer. The study utilized the SKOV-3 ovarian cancer cell line to assess the effects of this combination treatment. The results of the study showed that the combination of paclitaxel with rosiglitazone inhibited cell proliferation at much lower concentrations of paclitaxel as compared to paclitaxel alone. The combined treatment also induced cell cycle arrest at the G2/M phase and increased apoptosis by altering the mitochondrial membrane potential of the cells. Additionally, the combination treatment activated the PPAR-γ pathway and downregulated expression of genes associated with cancer stemness, such as NANOG, OCT4, and EHF. Furthermore, the CAM assay substantiated the anti-angiogenic potential of the synergistic treatment of paclitaxel and rosiglitazone. The findings of the study suggest that repurposing rosiglitazone as an anticancer agent in combination with paclitaxel has immense potential to target cancer cell cycle progression and apoptosis, making it a promising therapeutic approach for sensitizing chemo-resistant population of ovarian cancer cells.

High-throughput screening of ancient forest plant extracts shows cytotoxicity towards triple-negative breast cancer

According to the World Health Organization, women's breast cancer is among the most common cancers with 7.8 million diagnosed cases during 2016-2020 and encompasses 15 % of all female cancer-related mortalities. These mortality events from triple-negative breast cancer are a significant health issue worldwide calling for a continuous search of bioactive compounds for better cancer treatments. Historically, plants are important sources for identifying such new bioactive chemicals for treatments. Here we use high-throughput screening and mass spectrometry analyses of extracts from 100 plant species collected in Chinese ancient forests to detect novel bioactive breast cancer phytochemicals. First, to study the effects on viability of the plant extracts, we used a MTT and CCK-8 cytotoxicity assay employing triple-negative breast cancer (TNBC) MDA-MB-231 and normal epithelial MCF-10A cell lines and cell cycle arrest to estimate apoptosis using flow cytometry for the most potent three speices. Based on these analyses, the final most potent extracts were from the Amur honeysuckle (Lonicera maackii) wood/root bark and Nigaki (Picrasma quassioides) wood/root bark. Then, 5 × 106 MDA-MB-231 cells were injected subcutaneously into the right hind leg of nude mice and a tumour was allowed to grow before treatment for seven days. Subsequently, the four exposed groups received gavage extracts from Amur honeysuckle and Nigaki (Amur honeysuckle wood distilled water, Amur honeysuckle root bark ethanol, Nigaki wood ethanol or Nigaki root bark distilled water/ethanol (1:1) extracts) in phosphate-buffered saline (PBS), while the control group received only PBS. The tumour weight of treated nude mice was reduced significantly by 60.5 % within 2 weeks, while on average killing 70 % of the MDA-MB-231 breast cancer cells after 48 h treatment (MTT test). In addition, screening of target genes using the Swiss Target Prediction, STITCH, STRING and NCBI-gene database showed that the four plant extracts possess desirable activity towards several known breast cancer genes. This reflects that the extracts may kill MBD-MB-231 breast cancer cells. This is the first screening of plant extracts with high efficiency in 2 decades, showing promising results for future development of novel cancer treatments.

Integrated computational screening and liquid biopsy approach to uncover the role of biomarkers for oral cancer lymph node metastasis

Cancer is an abnormal, heterogeneous growth of cells with the ability to invade surrounding tissue and even distant organs. Worldwide, GLOBOCAN had an estimated 18.1 million new cases and 9.6 million death rates of cancer in 2018. Among all cancers, Oral cancer (OC) is the sixth most common cancer worldwide, and the third most common in India, the most frequent type, oral squamous cell carcinoma (OSCC), tends to spread to lymph nodes in advanced stages. Throughout the past few decades, the molecular landscape of OSCC biology has remained unknown despite breakthroughs in our understanding of the genome-scale gene expression pattern of oral cancer particularly in lymph node metastasis. Moreover, due to tissue variability in single-cohort studies, investigations on OSCC gene-expression profiles are scarce or inconsistent. The work provides a comprehensive analysis of changed expression and lays a major focus on employing a liquid biopsy base method to find new therapeutic targets and early prediction biomarkers for lymph node metastasis. Therefore, the current study combined the profile information from GSE9844, GSE30784, GSE3524, and GSE2280 cohorts to screen for differentially expressed genes, and then using gene enrichment analysis and protein-protein interaction network design, identified the possible candidate genes and pathways in lymph node metastatic patients. Additionally, the mRNA expression of discovered genes was assessed using real-time PCR, and the Human Protein Atlas database was utilized to determine the protein levels of hub genes in tumor and normal tissues. Angiogenesis was been investigated using the Chorioallentoic membrane (CAM) angiogenesis test. In a cohort of OSCC patients, fibronectin (FN1), C-X-C Motif Chemokine Ligand 8 (CXCL8), and matrix metallopeptidase 9 (MMP9) were significantly upregulated, corroborating these findings. Our identified significant gene signature showed greater serum exosome effectiveness in early detection and clinically linked with intracellular communication in the establishment of the premetastatic niche. Also, the results of the CAM test reveal that primary OC derived exosomes may have a function in angiogenesis. As a result, our study finds three potential genes that may be used as a possible biomarker for lymph node metastasis early detection and sheds light on the underlying processes of exosomes that cause a premetastatic condition.

Antitumor Effects of Ononin by Modulation of Apoptosis in Non-Small-Cell Lung Cancer through Inhibiting PI3K/Akt/mTOR Pathway

Lung cancer is a leading global cause of cancer-related death in both males and females. Non-small-cell lung cancer (NSCLC) is the most commonly diagnosed cancer type that can be difficult to control with conventional chemotherapeutic and surgical approaches resulting in a poor prognosis. Paclitaxel (PTX) is a commonly used chemotherapeutic drug for NSCLC, which can cause tissue injury in healthy cells and affect the quality of life in patients with cancer. In order to treat NSCLC, alternative medications with minimal or no side effects are highly needed. Ononin is an isoflavone glycoside extracted from Astragali Radix (AR) that has various pharmacological activities. Therefore, this study investigated whether ononin inhibits NSCLC progression and promotes apoptosis synergistically with PTX both in vitro and in vivo. Antitumorigenic properties of ononin were determined by MTT assay, colony formation assay, migratory capacity, and apoptotic marker expression in A549 and HCC827 cells. The combination of ononin with PTX increased the expression of apoptotic markers and ROS generation and inhibited cell proliferation through the PI3K/Akt/mTOR signaling pathways. Furthermore, ononin prevented the translocation of NF-κB from cytosol to the nucleus. Also, we used the xenograft NSCLC mice model to confirm the in vivo antitumorigenic efficacies of ononin by reduction of CD34 and Ki67 expressions. Based on the histological analysis, the cotreatment of PTX and ononin reduced PTX-induced liver and kidney damage. Overall, our findings suggested that the therapeutic index of PTX-based chemotherapy could be improved by reducing toxicity with increasing antitumor capabilities when combined with ononin.

A comprehensive review on recent approaches for cancer drug discovery associated with artificial intelligence

Through the revolutionization of artificial intelligence (AI) technologies in clinical research, significant improvement is observed in diagnosis of cancer. Utilization of these AI technologies, such as machine and deep learning, is imperative for the discovery of novel anticancer drugs and improves existing/ongoing cancer therapeutics. However, building a model for complicated cancers and their types remains a challenge due to lack of effective therapeutics that hinder the establishment of effective computational tools. In this review, we exploit recent approaches and state-of-the-art in implementing AI methods for anticancer drug discovery, and discussed how advances in these applications need to be considered in the current cancer therapeutics. Considering the immense potential of AI, we explore molecular docking and their interactions to recognize metabolic activities that support drug design. Finally, we highlight corresponding strategies in applying machine and deep learning methods to various types of cancer with their pros and cons.