There are significant challenges in developing drug carriers for therapeutic perspective. We have investigated a novel nanocarrier system, based on combining functionalized magnetic nanocomposite with Metal–Organic Frameworks (MOFs). Magnetic nanoparticles modified using biocompatible copolymers may be suitable for delivering hydrophobic drugs, such as cisplatin. Furthermore, compared to polymeric nanocarriers, nanocomposite constructed from zeolitic imidazolate framework-8 (ZIF-8) have demonstrated better drug loading capacity, as well as excellent pH-triggered drug release. Cisplatin-encapsulated Fe3O4@SiO2-ZIF-8@N-Chit-FA has been evaluated to determine the antitumor effects of free cisplatin enhancement in cervical cancer cells. In order to increase the stability of the proposed nanocarrier in aqueous solutions, in addition to the density of functional groups, a nano-chitosan layer was coated on top of the magnetic nanocomposite. It was then added with cisplatin onto the surface of Fe3O4@SiO2-ZIF-8@N-Chit-FA to deliver anticancer treatment that could be targeted using a magnetic field. A mouse isograft model of TC1 cells was used to evaluate the in vivo tumor growth inhibition. In tumor-bearing mice, Fe3O4@SiO2-ZIF-8@N-Chit-FA-cisplatin was injected intraperitoneally, and the targeted delivery was amplified by an external magnet (10 mm by 10 mm, surface field strength 0.4 T) fixed over the tumor site. Based on in vivo results, cisplatin-Loaded Mesoporous Magnetic Nanobiocomposite inhibited the growth of cervical tumors (P < 0.001) through the induction of tumor necrosis (P < 0.05) when compared to cisplatin alone. With the application of an external magnetic field, the drug was demonstrated to be able to induce its effects on specific target areas. In summary, Fe3O4 @ SiO2-ZIF-8 @ N-Chit-FA nanocomposites have the potential to be implemented in targeted nanomedicine to deliver bio-functional molecules.

Introduction: Cervical cancer is the leading cause of cancer-related death in women, so novel therapeutic approaches are needed to improve the effectiveness of current therapies or extend their activity. In recent decades, graphene analogs, such as Mxene, an emerging class of two-dimensional (2D) graphene analogs, have been drawing considerable attention based on their intrinsic physicochemical properties and performance as potential candidates for tumor therapy, particularly for therapeutic purposes. Here we explored the targeted drug delivery in cervical cancer in in vivo model. Mxene-based nanocarriers are not able to be precisely controlled in cancer treatment.Method: To solve this problem, the titanium carbide-magnetic core-shell nanocarrier (Ti3C2-Fe3O4@SiO2-FA) is also developed to provide synergetic anticancer with magnetic controlling ability along with pH-responsive drug release. A xenograft model of the cervix was used to investigate the effects of Cisplatin alone, or in combination with Ti3C2@FA and Ti3C2@ Fe3O4@SiO2-FA, on tumor growth following histological staining for evaluation of necrosis.Result and Discussion: A significant tumor-growth suppression effect is shown when the Ti3C2-Fe3O4@SiO2-FA nanocarrier is magnetically controlled Cisplatin drug release. It reveals a synergistic therapeutic efficacy used in conjunction with pharmaceuticals (p &lt; .001). According to the in vivo study, the Ti3C2@FA@Cisplatin nanocomposite exhibits less tumor growth than the drug alone or Ti3C2@FA@Cisplatin via increasing necrosis effect (p &lt; .001). Through this study, Mxene nanosheets are expanded for biomedical applications, not only through the fabrication of biocompatible magnetic Mxene nanocomposite but also through the development of functionalization strategies that enable the magnetic Ti3C2 nanocomposite to load high levels of Cisplatin for cervical cancer treatment (242.5%). Hence, Ti3C2-Fe3O4@SiO2-FA nanocarriers would be promising candidates to improve cancer treatment efficiency.

The development of carriers for drug delivery faces significant challenges from a therapeutic perspective. The present study presents an innovative nanocarrier based on combination of functionalized magnetic nanocomposite nano‐chitosan and cisplatin. Hydrophobic drugs such as cisplatin could be delivered using magnetic nanoparticles modified with biocompatible copolymers. This study aimed to determine the antitumor effects of free cisplatin enhancement in cervical cancer cells using cisplatin‐encapsulated Fe3O4@SiO2@N‐Chit‐FA. An additional layer of nanochitosan was coated on top of the magnetic nanocomposite to increase its stability in aqueous solutions. Biocompatibility and cytotoxicity of Fe3O4@SiO2@N‐Chit‐FA‐cis complex were evaluated against the cervical cancer animal model in C57BL6 mice. An external magnetic field was used to test the in‐vivo uptake and distribution of Fe3O4@SiO2 @N‐Chit‐FA‐cis in tumor cells. The results showed that the released drug would induce its effects on a specific target area when an external magnetic field was applied, and Fe3O4@SiO2@N‐Chit‐FA‐cis can suppress tumor growth more than cisplatin alone via induction of tumor necrosis. Overall, Fe3O4@SiO2@N‐Chit‐FA nanocomposites hold great potential for use in targeted nanomedicine to deliver bio‐functional molecules.

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Background: Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on the identification of new biomarkers for the early diagnosis of PDAC and prediction of patient survival. Genome-wide RNA and microRNA sequencing were used using bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs) followed by validation in additional cohort of PDAC patients. Methods: genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA) to identify DEGs. We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest, (RF), Max Voting, Adaboost, Gradient boosting machines (GBM) and Extreme Gradient Boosting (XGB) techniques were used and Gradient boosting machines (GBM) were selected with 100 % accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs and a combination of these obtained from machine learning algorithms and survival analysis. Results: Machine learning results showed 23 genes with negative regulation, 5 genes with positive regulation, 7 microRNAs with negative regulation and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of disease. In addition, the survival analysis results showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9 and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Conclusion: Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in pathogenesis of the diseases can be used for detection of patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.