Recent Advances in Diagnostic and Therapeutic Approaches for Breast Cancer: A Comprehensive Review

MultiOmics analysis of metabolic dysregulation and immune features in breast cancer

Metabolic disorders and diminished immune response are hallmark characteristics of tumors. However, limited studies have comprehensively integrated metabolic and immunological factors to evaluate or predict the prognosis of cancer patients. In this study, we utilized 72 metabolic pathway gene sets from the MsigDB database to conduct GSVA, univariate regression, and prognostic analyses on 247 breast cancer samples sourced from the TCGA and GEO databases. Consequently, five metabolic pathways with significant research value were identified. Based on these findings, unsupervised clustering was performed on the breast cancer samples to compare differences in gene expression, clinicopathological features, immune infiltration levels, and prognosis across different clusters. This process led to the identification of nine metabolism-related characteristic genes. Additionally, single-cell sequencing analysis was employed to assess the spatial expression patterns of these characteristic genes, revealing significantly higher expression indices in tumor cells compared to non-tumor cells. Subsequently, machine learning algorithms were applied to reconstruct metabolic risk models for evaluating the prognosis of breast cancer patients. The results indicated that the high metabolic risk group exhibited higher gene mutation scores, a greater proportion of unfavorable clinicopathological parameters, and lower chemokine and immune scores compared to the low-risk group. In conclusion, the metabolic risk model constructed using metabolism-related characteristic genes can accurately distinguish and predict the survival prognosis and immunotherapy outcomes of breast cancer patients, offering novel targets and insights for personalized treatment strategies.

Exploring the antiproliferative and proapoptotic activities of new pyridopyrimidine derivatives and their analogs

This study investigates a series of newly synthesized compounds, including pyridopyrimidine derivatives (9a-g), tricyclic pyridotriazolopyrimidine analogs (18a-d), and dihydropyrimidinones (22a-i), as apoptotic inducers and inhibitors of phosphatidylinositol-3-kinase α (PI3Kα), with potential anticancer activity. An initial in vitro screening of 60 cancer cell lines identified pyridopyrimidine derivatives 9a-g as promising broad-spectrum anticancer agents, with compound 9e demonstrating the strongest inhibitory activity, particularly against T-47D breast cancer cells. Notably, the antitumor potency of compound 9e surpassed that of Pictilisib, inducing G2-M phase cell cycle arrest and initiating apoptosis through the intrinsic apoptotic pathway. Molecular docking studies further indicated that compound 9e binds to PI3Kα in a similar fashion to the co-crystallized ligand. Moreover, compound 9e exhibited favorable drug-like properties, including compliance with Lipinski's rule and Veber's rule, good solubility, acceptable TPSA, and high gastrointestinal absorption reinforcing its potential as a highly effective anticancer agent.

Exploring the anti-cancer properties of Carissa carandas as a multi-targeted approach against breast cancer

The escalating incidence of breast cancer globally presents a formidable challenge within oncology. Our research pursued an examination of the anti-cancer potential of Carissa carandas, a shrub traditionally used for medicinal purposes and known for its composition of vital nutrients and phytochemicals. We employed a network pharmacology strategy combined with molecular docking and molecular dynamics simulations to elucidate the intricate relationships between the phytochemical constituents of C. carandas, critical breast cancer proteins, and associated signaling pathways. The study highlighted a complex network of protein interactions, identifying AKT1, HIF1A, PTGS2, and GSK3B as key nodes within this network. These proteins are engaged by numerous investigated compounds from C. carandas and are fundamental in modulating crucial signaling pathways such as those involving Estrogen, HIF-1, Prolactin, VEGF, and Th17 cell differentiation-each of which plays a recognized role in breast cancer progression, affecting tumor growth, proliferation, and metastatic potential. Our analysis suggests that the phytochemicals in C. carandas may exert anti-cancer activity by synergistically modulating these pathways, highlighting the benefit of multi-targeted therapeutic approaches over single-targeted ones. In summary, through the application of advanced network pharmacology, molecular docking, MD simulations, and MM/PBSA analysis, our study offers a detailed exploration of the potential mechanisms by which C. carandas may exert anti-cancer effects. This sets a foundation for further in-depth experimental and clinical trials to validate these mechanisms and support the advancement of novel plant-derived therapeutic options towards breast cancer, with the possibility of significantly advancing the therapeutic options for this prevalent disease.

Potential Target Metabolites From Gut Microbiota Against Hepatocellular Carcinoma: A Network Pharmacology and Molecular Docking Study

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, posing significant challenges and economic burdens on healthcare systems. Gut microbiota metabolites have shown promise in cancer treatment, but the specific active metabolites and their key targets remain unclear. This study employed a network pharmacology-based approach to identify potent metabolites of gut microbiota and their key targets. Active metabolites produced by gut microbiota were retrieved using the database gutMGene, and targets associated with these metabolites were identified using the Swiss Target Prediction tool. HCC-related targets were obtained from the GeneCards database, and overlapping targets were selected through a Venn diagram tool. An integrated metabolites-target-pathway network was analyzed to identify active inhibitors against HCC, including p-cresol glucuronide, secoisolariciresinol, glycocholic acid, enterodiol, and citric acid. Molecular docking tests were performed to validate the findings and assess the binding affinity of the metabolites with their target proteins. The study identified AKT1, EGFR, ALB, and TNF genes as potential therapeutic targets against hepatic cancer. The metabolites, p-cresol glucuronide, secoisolariciresinol, glycocholic acid, enterodiol, and citric acid, exhibited significant binding affinity with their respective target proteins. The study also revealed multiple signaling pathways and biological processes associated with the metabolites, demonstrating their preventive effect against HCC. This research utilizes a network pharmacology-based approach to identify potent metabolites of gut microbiota and their key targets for the treatment of HCC. The findings were validated through molecular docking tests, providing a foundation for future studies on anti-HCC metabolites and their mechanisms of action. Furthermore, this study offers insights into the development of novel anti-HCC drugs utilizing gut microbiota metabolites.

Intersecting planetary health: Exploring the impacts of environmental stressors on wildlife and human health

This comprehensive review articulates critical insights into the nexus of environmental stressors and their health impacts across diverse species, underscoring significant findings that reveal profound effects on both wildlife and human health systems. Central to our examination is the role of pollutants, climate variables, and pathogens in contributing to complex disease dynamics and physiological disruptions, with particular emphasis on immune and endocrine functions. This research brings to light emerging evidence on the severe implications of environmental pressures on a variety of taxa, including predatory mammals, raptorial birds, seabirds, fish, and humans, which are pivotal as indicators of broader ecosystem health and stability. We delve into the nuanced interplay between environmental degradation and zoonotic diseases, highlighting novel intersections that pose significant risks to biodiversity and human populations. The review critically evaluates current methodologies and advances in understanding the morphological, histopathological, and biochemical responses of these organisms to environmental stressors. We discuss the implications of our findings for conservation strategies, advocating for a more integrated approach that incorporates the dynamics of zoonoses and pollution control. This synthesis not only contributes to the academic discourse but also aims to influence policy by aligning with the Global Goals for Sustainable Development. It underscores the urgent need for sustainable interactions between humans and their environments, which are critical for preserving biodiversity and ensuring global health security. By presenting a detailed analysis of the interdependencies between environmental stressors and biological health, this review highlights significant gaps in current research and provides a foundation for future studies aimed at mitigating these pressing issues. Our study is significant as it proposes integrative and actionable strategies to address the challenges at the intersection of environmental change and public health, marking a crucial step forward in planetary health science.

Network pharmacology-based screening of active constituents of Avicennia marina and their clinical biochemistry related mechanism against breast cancer

Breast cancer is the second major cause of cancer death in women globally. Avicennia marina is a medicinal plant that belongs to the family Acanthaceae and is known as grey or white mangrove. It has antioxidant, antiviral, anticancer, anti-inflammatory, and antibacterial activity in the treatment of various diseases including cancer. The goal of the study is to use a network pharmacology method to identify the potential phenomena of bioactive compounds of A. marina in the treatment of breast cancer and explore clinical biochemistry related aspects. A total of 74 active compounds of A. marina were retrieved from various databases as well as a literature review and collectively 429 targets of these compounds were identified by STITCH and Swiss Target Prediction databases. Breast cancer related 15606 potential targets were retrieved from the GeneCards database. A Venn diagram was drawn to find common key targets. To check the biological functions, the GO enrichment and KEGG pathways analysis of 171 key targets were performed through the DAVID database. To understand the interactions among key targets, Protein-protein interaction (PPI) studies were completed using the STRING database, and the Protein-Protein Interaction (PPI) network, as well as the compound-target-pathway network, was constructed using Cytoscape 3.9.0. Finally, molecular docking analysis of 5 hub genes named tumor protein 53 (TP53), catenin beta 1 (CTNNB1), interleukin 6 (IL6), tumor necrosis factor (TNF), and RAC-alpha serine/threonine protein kinases 1 (AKT1) with the active constituent of A. marina against breast cancer were performed. Additionally, a molecular docking study demonstrates that active drugs have a higher affinity for the target that may be used to decrease breast cancer. The molecular dynamic simulation analysis predicted the very stable behavior of docked complexes with no global structure deviations seen. The MMGBSA further supported strong intermolecular interactions with net energy values as; AKT1_Betulinic_acid (-20.97 kcal/mol), AKT1_Stigmasterol (-44.56 kcal/mol), TNF_Betulinic_acid (-28.68 kcal/mol) and TNF_Stigmastero (-29.47 kcal/mol).Communicated by Ramaswamy H. Sarma.

In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches

Single-point mutations in the Kirsten rat sarcoma (KRAS) viral proto-oncogene are the most common cause of human cancer. In humans, oncogenic KRAS mutations are responsible for about 30% of lung, pancreatic, and colon cancers. One of the predominant mutant KRAS G12D variants is responsible for pancreatic cancer and is an attractive drug target. At the time of writing, no Food and Drug Administration (FDA) approved drugs are available for the KRAS G12D mutant. So, there is a need to develop an effective drug for KRAS G12D. The process of finding new drugs is expensive and time-consuming. On the other hand, in silico drug designing methodologies are cost-effective and less time-consuming. Herein, we employed machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF) for the identification of new inhibitors against the KRAS G12D mutant. A total of 82 hits were predicted as active against the KRAS G12D mutant. The active hits were docked into the active site of the KRAS G12D mutant. Furthermore, to evaluate the stability of the compounds with a good docking score, the top two complexes and the standard complex (MRTX-1133) were subjected to 200 ns MD simulation. The top two hits revealed high stability as compared to the standard compound. The binding energy of the top two hits was good as compared to the standard compound. Our identified hits have the potential to inhibit the KRAS G12D mutation and can help combat cancer. To the best of our knowledge, this is the first study in which machine-learning-based virtual screening, molecular docking, and molecular dynamics simulation were carried out for the identification of new promising inhibitors for the KRAS G12D mutant.

Naphthoquinone Derivatives from Angustimassarina populi CF-097565 Display Anti-Tumour Activity in 3D Cultures of Breast Cancer Cells

Cancer is one of the leading causes of death worldwide, with breast cancer being the second cause of cancer-related mortality among women. Natural Products (NPs) are one of the main sources for drug discovery. During a screening campaign focused on the identification of extracts from Fundación MEDINA's library inhibiting the proliferation of cancer cell lines, a significant bioactivity was observed in extracts from cultures of the fungus Angustimassarina populi CF-097565. Bioassay-guided fractionation of this extract led to the identification and isolation of herbarin (1), 1-hydroxydehydroherbarin (4) plus other three naphthoquinone derivatives of which 3 and 5 are new natural products and 2 is herein described from a natural source for the first time. Four of these compounds (1, 3, 4 and 5) confirmed a specific cytotoxic effect against the human breast cancer cell line MCF-7. To evaluate the therapeutic potential of the compounds isolated, their efficacy was validated in 3D cultures, a cancer model of higher functionality. Additionally, an in-depth study was carried out to test the effect of the compounds in terms of cell mortality, sphere disaggregation, shrinkage, and morphology. The cell profile of the compounds was also compared to that of known cytotoxic compounds with the aim to distinguish the drug mode of action (MoA). The profiles of 1, 3 and 4 showed more biosimilarity between them, different to 5, and even more different to other known cytotoxic agents, suggesting an alternative MoA responsible for their cytotoxicity in 3D cultures.

Integrated virtual screening, molecular modeling and machine learning approaches revealed potential natural inhibitors for epilepsy

Epilepsy, a prevalent chronic disorder of the central nervous system, is typified by recurrent seizures. Present treatments predominantly offer symptomatic relief by managing seizures, yet fall short of influencing epileptogenesis. This study endeavored to identify novel phytochemicals with potential therapeutic efficacy against S100B, an influential protein in epileptogenesis, through an innovative application of machine learning-enabled virtual screening. Our study incorporated the use of multiple machine learning algorithms, including Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naive Bayes (NB), and Random Forest (RF). These algorithms were employed not only for virtual screening but also for essential feature extraction and selection, enhancing our ability to distinguish between active and inactive compounds. Among the tested machine learning algorithms, the RF model outshone the rest, delivering an impressive 93.43 % accuracy on both training and test datasets. This robust RF model was leveraged to sift through the library of 9,000 phytochemicals, culminating in the identification of 180 potential inhibitors of S100B. These 180 active compounds were than docked with the active site of S100B proteins. The results of our study highlighted that the 6-(3,12-dihydroxy-4,10,13-trimethyl-7,11-dioxo-2,3,4,5,6,12,14,15,16,17-decahydro-1H cyclopenta[a] phenanthren -17-yl)-2-methyl-3-methylideneheptanoic acid, rhinacanthin K, thiobinupharidine, scopadulcic acid, and maslinic acid form significant interactions within the binding pocket of S100B, resulting in stable complexes. This underscores their potential role as S100B antagonists, thereby presenting novel therapeutic possibilities for epilepsy management. To sum up, this study's deployment of machine learning in conjunction with virtual screening not only has the potential to unearth new epilepsy therapeutics but also underscores the transformative potential of these advanced computational techniques in streamlining and enhancing drug discovery processes.

Unveiling the multi-target compounds of Rhazya stricta: Discovery and inhibition of novel target genes for the treatment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a prevalent kidney malignancy with a pressing need for innovative therapeutic strategies. In this context, emerging research has focused on exploring the medicinal potential of plants such as Rhazya stricta. Nevertheless, the complex molecular mechanisms underlying its potential therapeutic efficacy remain largely elusive. Our study employed an integrative approach comprising data mining,network pharmacology,tissue cell type analysis, and molecular modelling approaches to identify potent phytochemicals from R. stricta, with potential relevance for ccRCC treatments. Initially, we collected data on R. stricta's phytochemical from public databases. Subsequently, we integrated this information with differentially expressed genes (DEGs) in ccRCC, which were derived from microarray datasets(GSE16441,GSE66270, and GSE76351). We identified potential intersections between R. stricta and ccRCC targets, which enabled us to construct a compound-genes-pathway network using Cytoscape software. This helped illuminate R. stricta's multi-target pharmacological effects on ccRCC. Moreover, tissue cell type analysis added another layer of insight into the cellular specificity of potential therapeutic targets in the kidney. Through further Kaplan-Meier survival analysis, we pinpointed MMP9,ACE,ERBB2, and HSP90AA1 as prospective diagnostic and prognostic biomarkers for ccRCC. Notably, our study underscores the potential of R. stricta derived compounds-namely quebrachamine,corynan-17-ol, stemmadenine,strictanol,rhazinilam, and rhazimolare-to impede ccRCC progression by modulating the activity of MMP9,ACE,ERBB2, and HSP90AA1 genes. Further, molecular docking and dynamic simulations confirmed the plausible binding affinities of these compounds. Despite these promising findings, we recognize the need for comprehensive in vivo and in vitro studies to further investigate the pharmacokinetics and biosafety profiles of these compounds.

Integrated molecular modeling and dynamics approaches revealed potential natural inhibitors of NF-κB transcription factor as breast cancer therapeutics

Breast cancer is a silent killer malady among women and a serious economic burden in health care management. A case of breast cancer is diagnosed among women every 19 s, and every 74 s, a woman dies of breast cancer somewhere in the world. Despite the pop-up of progressive research, advanced treatment approaches, and preventive measures, breast cancer remains amplifying ailment. The nuclear factor kappa B (NF-κB) is a key transcription factor that links inflammation with cancer and is demonstrated as being involved in the tumorigenesis of breast cancer. The NF-κB transcription factor family in mammals consists of five proteins; c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52). The antitumor effect of NF-κB has also been explored in breast cancer, however, the actual treatment for breast cancer is yet to be discovered. This study is attributed to the identification of novel drug targets against breast cancer by targeting c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52) proteins. To identify the putative active compounds, a structure-based 3D pharmacophore model to the protein active site cavity was generated followed by virtual screening, molecular docking, and molecular dynamics (MD) simulation. Initially, a library of 45000 compounds were docked against the target protein and five compounds namely Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 were selected for further analysis. The relative binding affinity of Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 with NF-κB1 (p50), NF-κB2 (p52), RelA (p65), RelB, and c-Rel proteins were -6.8, -8, -7.0, -6.9, and -7.2 kcal/mol, respectively which remained stable throughout the simulations of 200 ns. Furthermore, all of these compounds depict maximum drug-like properties. Therefore, the proposed compounds can be a potential candidate for patients with breast cancer, but, experimental validation is needed to ensure their safety.Communicated by Ramaswamy H. Sarma.

Effects of Tai Chi Chuan training on the QoL and psychological well-being in female patients with breast cancer: a systematic review of randomized controlled trials

Background

Tai Chi Chuan (TCC) may have a positive impact on physical and psychological well-being in breast cancer patients, but the evidence remains limited and inconclusive. This systematic review aims to evaluate the effects of TCC on the quality of life (QoL) and psychological symptoms in women patients with breast cancer.

Methods

This review has been registered on PROSPERO (ID: CRD42019141977). Randomized controlled trials (RCTs) of TCC for breast cancer were searched from eight major English and Chinese databases. All trials included were analyzed in accordance with the Cochrane Handbook. The primary outcomes were QoL, anxiety, and depression in patients with breast cancer. Fatigue, sleep quality, cognitive function, and inflammatory cytokine were the secondary outcomes.

Results

Fifteen RCTs involving a total of 1,156 breast cancer participants were included in this review. The methodological quality of included trials was generally poor. The pooled results suggested that TCC-based exercise could significantly improve QoL [standardized mean difference (SMD)=0.35, 95%CI: 0.15-0.55, I ² = 0, model: fixed, IV], anxiety [weighted mean difference (WMD)=-4.25, 95%CI: -5.88 to -2.63, I ² = 0, model: fixed, IV], and fatigue (SMD=-0.87, 95%CI: -1.50 to -0.24, I ² = 80.9%, model: random, DL) compared other controls, with moderate to low certainty of evidence. The improvement of QoL and fatigue by TCC was also clinically meaningful. However, TCC-based exercise failed to show any between-group differences in depression, sleep quality, cognitive function, and inflammatory cytokine. Post-hoc analysis revealed that TCC-based exercise outperformed the other exercise in improving shoulder function with very low certainty of evidence.

Conclusion

Our findings manifested that TCC-based exercise is helpful for improving the QoL, anxiety, and fatigue in patients with breast cancer within the range of comparisons covered in this study. However, the results must be treated with great caution because of the methodological flaws of included trials. Larger, well-designed, and conducted randomized controlled trials with longer follow-up is warranted in the future to evaluate the important outcomes of TCC for breast cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019141977, identifier, CRD42019141977.

Therapeutic effects of Crataegus monogyna inhibitors against breast cancer

Breast cancer is a silent killer disorder among women and a serious economic burden in healthcare management. Every 19 s, a woman is diagnosed with breast cancer, and every 74 s, a woman worldwide passes away from the disease. Despite the increase in progressive research, advanced treatment approaches, and preventive measures, breast cancer rates continue to increase. This study provides a combination of data mining, network pharmacology, and docking analysis that surely could revolutionize cancer treatment by exploiting prestigious phytochemicals. Crataegus monogyna is a small, rounded deciduous tree with glossy, deeply lobed leaves and flat sprays of cream flowers, followed by dark red berries in autumn. Various studies demonstrated that C. monogyna is therapeutically effective against breast cancer. However, the particular molecular mechanism is still unknown. This study is credited for locating bioactive substances, metabolic pathways, and target genes for breast cancer treatment. According to the current investigation, which examined compound-target genes-pathway networks, it was found that the bioactive compounds of C. monogyna may operate as a viable solution against breast cancer by altering the target genes implicated in the disease pathogenesis. The expression level of target genes was analyzed using GSE36295 microarray data. Docking analysis and molecular dynamic simulation studies further strengthened the current findings by validating the effective activity of the bioactive compounds against putative target genes. In summary, we propose that six key compounds, luteolin, apigenin, quercetin, kaempferol, ursolic acid, and oleanolic acid, contributed to the development of breast cancer by affecting the MMP9 and PPARG proteins. Integration of network pharmacology and bioinformatics revealed C. monogyna's multitarget pharmacological mechanisms against breast cancer. This study provides convincing evidence that C. monogyna might partially alleviate breast cancer and ultimately lays a foundation for further experimental research on the anti-breast cancer activity of C. monogyna.

Integrating Network Pharmacology Approaches to Decipher the Multi-Target Pharmacological Mechanism of Microbial Biosurfactants as Novel Green Antimicrobials against Listeriosis

Listeria monocytogenes (L. monocytogenes) is a serious food-borne pathogen that can cause listeriosis, an illness caused by eating food contaminated with this pathogen. Currently, the treatment or prevention of listeriosis is a global challenge due to the resistance of bacteria against multiple commonly used antibiotics, thus necessitating the development of novel green antimicrobials. Scientists are increasingly interested in microbial surfactants, commonly known as "biosurfactants", due to their antimicrobial properties and eco-friendly nature, which make them an ideal candidate to combat a variety of bacterial infections. Therefore, the present study was designed to use a network pharmacology approach to uncover the active biosurfactants and their potential targets, as well as the signaling pathway(s) involved in listeriosis treatment. In the framework of this study, 15 biosurfactants were screened out for subsequent studies. Among 546 putative targets of biosurfactants and 244 targets of disease, 37 targets were identified as potential targets for treatment of L. monocytogenes infection, and these 37 targets were significantly enriched in a Gene Ontology (GO) analysis, which aims to identify those biological processes, cellular locations, and molecular functions that are impacted in the condition studied. The obtained results revealed several important biological processes, such as positive regulation of MAP kinase activity, protein kinase B signaling, ERK1 and ERK2 cascade, ERBB signaling pathway, positive regulation of protein serine/threonine kinase activity, and regulation of caveolin-mediated endocytosis. Several important KEGG pathways, such as the ERBBB signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, Yersinia infection, Shigellosis, and C-type lectin receptor signaling pathways, were identified. The protein-protein interaction analysis yielded 10 core targets (IL2, MAPK1, EGFR, PTPRC, TNF, ITGB1, IL1B, ERBB2, SRC, and mTOR). Molecular docking was used in the latter part of the study to verify the effectiveness of the active biosurfactants against the potential targets. Lastly, we found that a few highly active biosurfactants, namely lichenysin, iturin, surfactin, rhamnolipid, subtilisin, and polymyxin, had high binding affinities towards IL2, MAPK1, EGFR, PTPRC, TNF, ITGB1, IL1B, ERBB2, SRC, and mTOR, which may act as potential therapeutic targets for listeriosis. Overall, based on the integrated network pharmacology and docking analysis, we found that biosurfactants possess promising anti-listeriosis properties and explored the pharmacological mechanisms behind their effect, laying the groundwork for further research and development.

Recent Advances in Nanomaterials of Group XIV Elements of Periodic Table in Breast Cancer Treatment

Breast cancer is one of the most common malignancies and a leading cause of cancer-related mortality among women worldwide. The elements of group XIV in the periodic table exhibit a wide range of chemical manners. Recently, there have been remarkable developments in the field of nanobiomedical research, especially in the application of engineered nanomaterials in biomedical applications. In this review, we concentrate on the recent investigations on the antiproliferative effects of nanomaterials of the elements of group XIV in the periodic table on breast cancer cells. In this review, the data available on nanomaterials of group XIV for breast cancer treatment has been documented, providing a useful insight into tumor biology and nano-bio interactions to develop more effective nanotherapeutics for cancer patients.

Integrated Pangenome Analysis and Pharmacophore Modeling Revealed Potential Novel Inhibitors against Enterobacter xiangfangensis

Enterobacter xiangfangensis is a novel, multidrug-resistant pathogen belonging to the Enterobacter genus and has the ability to acquire resistance to multiple antibiotic classes. However, there is currently no registered E. xiangfangensis drug on the market that has been shown to be effective. Hence, there is an urgent need to identify novel therapeutic targets and effective treatments for E. xiangfangensis. In the current study, a bacterial pan genome analysis and subtractive proteomics approach was employed to the core proteomes of six strains of E. xiangfangensis using several bioinformatic tools, software, and servers. However, 2611 nonredundant proteins were predicted from the 21,720 core proteins of core proteome. Out of 2611 nonredundant proteins, 372 were obtained from Geptop2.0 as essential proteins. After the subtractive proteomics and subcellular localization analysis, only 133 proteins were found in cytoplasm. All cytoplasmic proteins were examined using BLASTp against the virulence factor database, which classifies 20 therapeutic targets as virulent. Out of these 20, 3 cytoplasmic proteins: ferric iron uptake transcriptional regulator (FUR), UDP-2,3diacylglucosamine diphosphatase (UDP), and lipid-A-disaccharide synthase (lpxB) were chosen as potential drug targets. These drug targets are important for bacterial survival, virulence, and growth and could be used as therapeutic targets. More than 2500 plant chemicals were used to molecularly dock these proteins. Furthermore, the lowest-binding energetic docked compounds were found. The top five hit compounds, Adenine, Mollugin, Xanthohumol C, Sakuranetin, and Toosendanin demonstrated optimum binding against all three target proteins. Furthermore, molecular dynamics simulations and MM/GBSA analyses validated the stability of ligand-protein complexes and revealed that these compounds could serve as potential E. xiangfangensis replication inhibitors. Consequently, this study marks a significant step forward in the creation of new and powerful drugs against E. xiangfangensis. Future studies should validate these targets experimentally to prove their function in E. xiangfangensis survival and virulence.

Integrated System Pharmacology Approaches to Elucidate Multi-Target Mechanism of Solanum surattense against Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant liver tumors with high mortality. Chronic hepatitis B and C viruses, aflatoxins, and alcohol are among the most common causes of hepatocellular carcinoma. The limited reported data and multiple spectra of pathophysiological mechanisms of HCC make it a challenging task and a serious economic burden in health care management. Solanum surattense (S. surattense) is the herbal plant used in many regions of Asia to treat many disorders including various types of cancer. Previous in vitro studies revealed the medicinal importance of S. surattense against hepatocellular carcinoma. However, the exact molecular mechanism of S. surattense against HCC still remains unclear. In vitro and in silico experiments were performed to find the molecular mechanism of S. surattense against HCC. In this study, the network pharmacology approach was used, through which multi-targeted mechanisms of S. surattense were explored against HCC. Active ingredients and potential targets of S. surattense found in HCC were figured out. Furthermore, the molecular docking technique was employed for the validation of the successful activity of bioactive constituents against potential genes of HCC. The present study investigated the active “constituent–target–pathway” networks and determined the tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mammalian target of rapamycin (mTOR), Bcl-2-like protein 1(BCL2L1), estrogen receptor (ER), GTPase HRas, hypoxia-inducible factor 1-alpha (HIF1-α), Harvey Rat sarcoma virus, also known as transforming protein p21 (HRAS), and AKT Serine/Threonine Kinase 1 (AKT1), and found that the genes were influenced by active ingredients of S. surattense. In vitro analysis was also performed to check the anti-cancerous activity of S. surattense on human liver cells. The result showed that S. surattense appeared to act on HCC via modulating different molecular functions, many biological processes, and potential targets implicated in 11 different pathways. Furthermore, molecular docking was employed to validate the successful activity of the active compounds against potential targets. The results showed that quercetin was successfully docked to inhibit the potential targets of HCC. This study indicates that active constituents of S. surattense and their therapeutic targets are responsible for their pharmacological activities and possible molecular mechanisms for treating HCC. Lastly, it is concluded that active compounds of S. surattense act on potential genes along with their influencing pathways to give a network analysis in system pharmacology, which has a vital role in the development and utilization of drugs. The current study lays a framework for further experimental research and widens the clinical usage of S. surattense.

Sodium alginate based drug delivery in management of breast cancer

Among women, breast cancer (B·C.) is a common form of cancer that can strike either developed or developing countries. In addition to pregnancy-related variables, hormone therapy lifestyle factors (e.g., physical inactivity, smoking, and alcohol use) may all influence the progression of B·C. The creation of anti-B·C. medication carriers with better stability, controlled and targeted administration, and the goal of minimizing unwanted effects has taken a lot of time and effort. Naturally generated biopolymers-based pharmaceutical delivery techniques have attracted attention for their potential use in treating B·C. It's been shown that natural polymers can deliver high medication concentrations to the desired place and provide prolonged release of pharmaceuticals useful in treating B.C. Alginate is one of the most commonly used drug carriers for delayed and targeted release. In present review will discuss the utilization of sodium alginate as an carrier of anticancer drug, such as paclitaxel, doxorubicin, tamoxifen, curcumin, and others.

Ang2-Targeted Combination Therapy for Cancer Treatment

Angiopoietin-2 (Ang2), a member of the angiopoietin family, is widely involved in the process of vascular physiology, bone physiology, adipose tissue physiology and the occurrence and development of inflammation, cardiac hypertrophy, rheumatoid, tumor and other diseases under pathological conditions. Proliferation and metastasis of cancer largely depend on angiogenesis. Therefore, anti-angiogenesis has become the target of tumor therapy. Due to the Ang2 plays a key role in promoting angiogenesis and stability in vascular physiology, the imbalance of its expression is an important condition for the occurrence and development of cancer. It has been proved that blocking Ang2 can inhibit the growth, invasion and metastasis of cancer cells. In recent years, research has been constantly supplemented. We focus on the mechanisms that regulate the expression of Ang2 mRNA and protein levels in different cancers, contributing to a better understanding of how Ang2 exerts different effects in different cancers and stages, as well as facilitating more specific targeting of relevant molecules in cancer therapy. At the same time, the importance of Ang2 in cancer growth, metastasis, prognosis and combination therapy is pointed out. And finally, we will discuss the current investigations and future challenges of combining Ang2 inhibition with chemotherapy, immunotherapy, and radiotherapy to increase its efficacy in cancer patients. This review provides a theoretical reference for the development of new targets and effective combination therapy strategies for cancer treatment in the future.

Network Pharmacology and Bioinformatics Approach Reveals the Multi-Target Pharmacological Mechanism of Fumaria indica in the Treatment of Liver Cancer

Liver cancer (LC), a frequently occurring cancer, has become the fourth leading cause of cancer mortality. The small number of reported data and diverse spectra of pathophysiological mechanisms of liver cancer make it a challenging task and a serious economic burden in health care management. Fumaria indica is a herbaceous annual plant used in various regions of Asia to treat a variety of ailments, including liver cancer. Several in vitro investigations have revealed the effectiveness of F. indica in the treatment of liver cancer; however, the exact molecular mechanism is still unrevealed. In this study, the network pharmacology technique was utilized to characterize the mechanism of F. indica on liver cancer. Furthermore, we analyzed the active ingredient-target-pathway network and uncovered that Fumaridine, Lastourvilline, N-feruloyl tyramine, and Cryptopine conclusively contributed to the development of liver cancer by affecting the MTOR, MAPK3, PIK3R1, and EGFR gene. Afterward, molecular docking was used to verify the effective activity of the active ingredients against the prospective targets. The results of molecular docking predicted that several key targets of liver cancer (along with MTOR, EGFR, MAPK3, and PIK3R1) bind stably with the corresponding active ingredient of F. indica. We concluded through network pharmacology methods that multiple biological processes and signaling pathways involved in F. indica exerted a preventing effect in the treatment of liver cancer. The molecular docking results also provide us with sound direction for further experiments. In the framework of this study, network pharmacology integrated with docking analysis revealed that F. indica exerted a promising preventive effect on liver cancer by acting on liver cancer-associated signaling pathways. This enables us to understand the biological mechanism of the anti liver cancer activity of F. indica.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

Integrating Network Pharmacology and Molecular Docking Approaches to Decipher the Multi-Target Pharmacological Mechanism of Abrus precatorius L. Acting on Diabetes

Type 2 diabetes mellitus (T2DM) is a notable health care load that imposes a serious impact on the quality of life of patients. The small amount of reported data and multiple spectra of pathophysiological mechanisms of T2DM make it a challenging task and serious economic burden in health care management. Abrus precatorius L. is a slender, perennial, deciduous, and woody twining plant used in various regions of Asia to treat a variety of ailments, including diabetes mellitus. Various in vitro studies revealed the therapeutic significance of A. precatorius against diabetes. However, the exact molecular mechanism remains unclarified. In the present study, a network pharmacology technique was employed to uncover the active ingredients, their potential targets, and signaling pathways in A. precatorius for the treatment of T2DM. In the framework of this study, we explored the active ingredient-target-pathway network and figured out that abrectorin, abrusin, abrisapogenol J, sophoradiol, cholanoic acid, precatorine, and cycloartenol decisively contributed to the development of T2DM by affecting AKT1, MAPK3, TNFalpha, and MAPK1 genes. Later, molecular docking was employed to validate the successful activity of the active compounds against potential targets. Lastly, we conclude that four highly active constituents, namely, abrusin, abrisapogenol J, precatorine, and cycloartenol, help in improving the body's sensitivity to insulin and regulate the expression of AKT1, MAPK3, TNFalpha, and MAPK1, which may act as potential therapeutic targets of T2DM. Integrated network pharmacology and docking analysis revealed that A. precatorius exerted a promising preventive effect on T2DM by acting on diabetes-associated signaling pathways. This provides a basis to understand the mechanism of the anti-diabetes activity of A. precatorius.

Alloimperatorin activates apoptosis, ferroptosis and oxeiptosis to inhibit the growth and invasion of breast cancer cells in vitro

Breast cancer is the most common malignant tumour in women. Our research on alloimperatorin from Angelica dahurica showed that alloimperatorin inhibited breast cancer cell viability in a concentration- and time-dependent manner; it also showed that apoptosis and ferroptosis inhibitors significantly weakened the anti-survival effect of alloimperatorin. Alloimperatorin clearly induced breast cancer cell apoptosis and increased the activities of Caspase-3, Caspase-8, Caspase-9 and PARP; it also caused significant mitochondrial shrinkage, promoted the accumulation of Fe2+, ROS and MDA, and significantly reduced mRNA and protein expression levels of SLC7A11 and GPX4, indicating that alloimperatorin induces ferroptosis. In addition, alloimperatorin significantly promoted Keap1 expression; although it did not affect the expression of PGAM5 and AIFM1, it significantly reduced the phosphorylation level of AIFM1. After downregulating the expression of Keap1, PGAM5 or AIFM1, the inhibitory effect of alloimperatorin on cell viability was significantly weakened, indicating that alloimperatorin regulates the Keap1/PGAM5/AIFM1 pathway to promote oxeiptosis. Alloimperatorin significantly inhibited the invasion of breast cancer cells, while Keap1 siRNA or GPX4 overexpression vectors significantly enhanced cell invasion and effectively reversed the anti-invasive effect of alloimperatorin. Therefore, alloimperatorin induces breast cancer cell apoptosis, ferroptosis and oxeiptosis, thereby inhibiting cell growth and invasion.

Investigation of Antimicrobial and Cytotoxic Properties and Specification of Silver Nanoparticles (AgNPs) Derived From Cicer arietinum L. Green Leaf Extract

Using biological materials to synthesize metallic nanoparticles has become a frequently preferred method by researchers. This synthesis method is both fast and inexpensive. In this study, an aqueous extract obtained from chickpea (Cicer arietinum L.) (CA) leaves was used in order to synthesize silver nanoparticles (AgNPs). For specification of the synthesized AgNPs, UV-vis spectrophotometer, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction analysis (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), electron dispersive X-ray (EDX), and zeta potential (ZP) analyses data were used. Biologically synthesized AgNPs demonstrated a maximum surface plasmon resonance of 417.47 nm after 3 h. With the powder XRD model, the mean crystallite dimension of nanoparticles was determined as 12.17 mm with a cubic structure. According to the TEM results, the dimensions of the obtained silver nanoparticles were found to be 6.11-9.66 nm. The ZP of the electric charge on the surface of AgNPs was measured as -19.6 mV. The inhibition effect of AgNPs on food pathogen strains and yeast was determined with the minimum inhibition concentration (MIC) method. AgNPs demonstrated highly effective inhibition at low concentrations especially against the growth of B. subtilis (0.0625) and S. aureus (0.125) strains. The cytotoxic effects of silver nanoparticles on cancerous cell lines (CaCo-2, U118, Sk-ov-3) and healthy cell lines (HDF) were revealed. Despite the increase of AgNPs used against cancerous and healthy cell lines, no significant decrease in the percentage of viability was detected.

Advances of Exosomal miRNAs in Breast Cancer Progression and Diagnosis

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death in women worldwide. Although many factors associated with breast cancer have been identified, the definite etiology of breast cancer is still unclear. In addition, early diagnosis of breast cancer remains challenging. Exosomes are membrane-bound nanovesicles secreted by most types of cells and contain a series of biologically important molecules, such as lipids, proteins, and miRNAs, etc. Emerging evidence shows that exosomes can affect the status of cells by transmitting substances and messages among cells and are involved in various physiological and pathological processes. In breast cancer, exosomes play a significant role in breast tumorigenesis and progression through transfer miRNAs which can be potential biomarkers for early diagnosis of breast cancer. This review discusses the potential utility of exosomal miRNAs in breast cancer progression such as tumorigenesis, metastasis, immune regulation and drug resistance, and further in breast cancer diagnosis.

In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pyogenes

Streptococcus pyogenes is a significant pathogen that causes skin and upper respiratory tract infections and non-suppurative complications, such as acute rheumatic fever and post-strep glomerulonephritis. Multidrug resistance has emerged in S. pyogenes strains, making them more dangerous and pathogenic. Hence, it is necessary to identify and develop therapeutic methods that would present novel approaches to S. pyogenes infections. In the current study, a subtractive proteomics approach was employed to core proteomes of four strains of S. pyogenes using several bioinformatic software tools and servers. The core proteome consists of 1324 proteins, and 302 essential proteins were predicted from them. These essential proteins were analyzed using BLASTp against human proteome, and the number of potential targets was reduced to 145. Based on subcellular localization prediction, 46 proteins with cytoplasmic localization were chosen for metabolic pathway analysis. Only two cytoplasmic proteins, i.e., chromosomal replication initiator protein DnaA and two-component response regulator (TCR), were discovered to have the potential to be novel drug target candidates. Three-dimensional (3D) structure prediction of target proteins was carried out via the Swiss Model server. Molecular docking approach was employed to screen the library of 1000 phytochemicals against the interacting residues of the target proteins through the MOE software. Further, the docking studies were validated by running molecular dynamics simulation and highly popular binding free energy approaches of MM-GBSA and MM-PBSA. The findings revealed a promising candidate as a novel target against S. pyogenes infections.

Designing a Multi-Epitope Vaccine against Chlamydia trachomatis by Employing Integrated Core Proteomics, Immuno-Informatics and In Silico Approaches

Chlamydia trachomatis, a Gram-negative bacterium that infects the rectum, urethra, congenital sites, and columnar epithelium of the cervix. It is a major cause of preventable blindness, ectopic pregnancy, and bacterial sexually transmitted infections worldwide. There is currently no licensed multi-epitope vaccination available for this pathogen. This study used core proteomics, immuno-informatics, and subtractive proteomics approaches to identify the best antigenic candidates for the development of a multi-epitope-based vaccine (MEBV). These approaches resulted in six vaccine candidates: Type III secretion system translocon subunit CopD2, SctW family type III secretion system gatekeeper subunit CopN, SycD/LcrH family type III secretion system chaperone Scc2, CT847 family type III secretion system effector, hypothetical protein CTDEC_0668, and CHLPN 76kDa-like protein. A variety of immuno-informatics tools were used to predict B and T cell epitopes from vaccine candidate proteins. An in silico vaccine was developed using carefully selected epitopes (11 CTL, 2 HTL & 10 LBL) and then docked with the MHC molecules (MHC I & MHC II) and human TLR4. The vaccine was coupled with Cholera toxin subunit B (CTB) adjuvant to boost the immune response. Molecular dynamics (MD) simulations, molecular docking, and MMGBSA analysis were carried out to analyze the molecular interactions and binding affinity of MEBV with TLR4 and MHC molecules. To achieve the highest level of vaccine protein expression, the MEBV was cloned and reverse-translated in Escherichia coli. The highest level of expression was achieved, and a CAI score of 0.97 was reported. Further experimental validation of the MEBV is required to prove its efficacy. The vaccine developed will be useful in preventing infections caused by C. trachomatis.