Development, Characterization, and Evaluation of SLN-Loaded Thermoresponsive Hydrogel System of Topotecan as Biological Macromolecule for Colorectal Delivery

BACKGROUND

Chemotherapeutic drugs cause severe toxicities if administered unprotected, without proper targeting, and controlled release. In this study, we developed topotecan- (TPT-) loaded solid lipid nanoparticles (SLNs) for their chemotherapeutic effect against colorectal cancer. The TPT-SLNs were further incorporated into a thermoresponsive hydrogel system (TRHS) (TPT-SLNs-TRHS) to ensure control release and reduce toxicity of the drug. Microemulsion technique and cold method were, respectively, used to develop TPT-SLNs and TPT-SLNs-TRHS. Particle size, polydispersive index (PDI), and incorporation efficiency (IE) of the TPT-SLNs were determined. Similarly, gelation time, gel strength, and bioadhesive force studies of the TPT-SLNs-TRHS were performed. Additionally, in vitro release and pharmacokinetic and antitumour evaluations of the formulation were done.

RESULTS

TPT-SLNs have uniformly distributed particles with mean size in nanorange (174 nm) and IE of ~90%. TPT-SLNs-TRHS demonstrated suitable gelation properties upon administration into the rat's rectum. Moreover, drug release was exhibited in a control manner over an extended period of time for the incorporated TPT. Pharmacokinetic studies showed enhanced bioavailability of the TPT with improved plasma concentration and AUC. Further, it showed significantly enhanced antitumour effect in tumour-bearing mice as compared to the test formulations.

CONCLUSION

It can be concluded that SLNs incorporated in TRHS could be a potential source of the antitumour drug delivery with better control of the drug release and no toxicity.

Polyaspartic acid-anchored mesoporous silica nanoparticles for pH-responsive doxorubicin release

Background

Nanotechnology-based drug delivery systems exhibit promising therapeutic efficacy in cancer chemotherapy. However, ideal nano drug carriers are supposed to be sufficiently internalized into cancer cells and then release therapeutic cargoes in response to certain intracellular stimuli, which has never been an easy task to achieve.

Objective

This study is to design mesoporous silica nanoparticles (MSNs)-based pH-responsive nano drug delivery system that is effectively internalized into cancer cells and then release drug in response to lysosomal/endosomal acidified environment.

Methods

We synthesized MSNs by sol-gel method. Doxorubicin (DOX) was encapsulated into the pores as a model drug. Polyaspartic acid (PAsA) was anchored on the surface of mesoporous MSNs (P-MSNs) as a gatekeeper via amide linkage and endowed MSNs with positive charge.

Results

In vitro release analysis demonstrated enhanced DOX release from DOX-loaded PAsA-anchored MSNs (DOX@P-MSNs) under endosomal/lysosomal acidic pH condition. Moreover, more DOX@P-MSNs were internalized into HepG2 cells than DOX-loaded MSNs (DOX@MSNs) and free DOX revealed by flow cytometry. Likewise, confocal microscopic images revealed that DOX@P-MSNs effectively released DOX and translocated to the nucleus. Much stronger cytotoxicity of DOX@P-MSNs against HepG2 cells was observed compared with DOX@MSNs and free DOX.

Conclusion

DOX@P-MSNs were successfully fabricated and achieved pH-responsive DOX release. We anticipated this nanotherapeutics might be suitable contenders for future in vivo cancer chemotherapeutic applications.

Cellulose conjugated FITC-labelled mesoporous silica nanoparticles: intracellular accumulation and stimuli responsive doxorubicin release

Herein, we design novel cellulose conjugated mesoporous silica nanoparticle (CLS-MSP) based nanotherapeutics for stimuli responsive intracellular doxorubicin (DOX) delivery. DOX molecules are entrapped in pores of the fabricated mesoporous silica nanoparticles (MSPs) while cellulose is used as an encapsulating material through esterification on the outlet of the pores of the MSPs to avoid premature DOX release under physiological conditions. In in vitro studies, stimuli responsive DOX release is successfully achieved from DOX loaded cellulose conjugated mesoporous silica nanoparticles (DOX/CLS-MSPs) by pH and cellulase triggers. Intracellular accumulation of DOX/CLS-MSPs in human liver cancer cells (HepG2 cells) is investigated through confocal microscope magnification. Cell viability of HepG2 cells is determined as the percentage of the cells incubated with DOX/CLS-MSPs compared with that of non-incubated cells through an MTT assay.

Objective Spectral-Spatial Analysis of Random Periareolar Fine Needle Aspiration of Women at High Risk for Contralateral Breast Cancer

Background: Random periareolar fine needle aspiration (RPFNA) cytology coupled with the Gail risk model has been used to predict the short-term risk of breast cancer in high risk women. The cytomorphologic features of atypical epithelial cells obtained by RPFNA can be subtle and result in inter-observer diagnostic variability and decreased sensitivity. Spectral-spatial analysis (SSA) is a method for objective image analysis that uses both color and spatial information to classify features into user-defined groups. We use SSA to classify cell clusters from RPFNA specimens into objective categories and compare that result to the cytopathology interpretation, which is the current standard.Design:Cell clusters on Papanicolau stained cytology Thin Prep slides from 7 benign and 7 malignant (14 total) breast RPFNA specimen were used to generate image stacks with the CRI Nuance platform. The specimens were processed and stained in three separate cytopathology laboratories. To build the algorithmic model, image stacks were analyzed using a neural network-based artificial intelligence system now distributed commercially as the Inform system. We manually painted green and red indicating feature (malignant) versus non-feature/background (benign) cells, respectively. A diagnostic algorithmic solution was created to stratify the new images as percent pixels correctly assigned as “malignant”. The solution was tested against cell clusters from 53 high-risk RPFNA specimen stratified by an expert pathologist (CZ) into the 5 categories of benign, epithelial hyperplasia, borderline, atypical and malignant. The specimens were collected from the contra lateral breast of patients with mastectomies for invasive carcinoma. Although 14 of the 67 cases were reused, no cellular clusters used in the training set were included in the validation set. The cytopathologist diagnosis was used as the gold standard and binarized to designate malignant cases as 1 and benign 0. These were compared to the green pixel (malignant) percentage in each case processed by INform.Results: The SSA algorithm classified all 7 malignant cases concordantly with the pathologist. The remaining 60 cases were classified as benign. The ROC curve generated from the cases had an AUC of 0.974 and an accuracy of 79.1%. The sensitivity was 100% and the specificity 76.7%.Conclusions: Spectral-spatial analysis can objectively classify benign and malignant cell clusters in excellent concordance to an expert pathologist. The epithelial hyperplasia, borderline, and atypical categories were all classified as benign by this solution representing a weakness in the solution. However, since these classes are not definitive with respect to biological behavior, the algorithm was binarized as above. In the future, algorithms will be based on biologically proven classes toward the goal of more definitive classification. A mature version of this technology could allow much broader usage of RPFNA since it would no longer be solely dependent on expert cytopathology interpretation.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6001.

A self-consistent transport model for molecular conduction based on extended Hückel theory with full three-dimensional electrostatics

We present a transport model for molecular conduction involving an extended Hückel theoretical treatment of the molecular chemistry combined with a nonequilibrium Green's function treatment of quantum transport. The self-consistent potential is approximated by CNDO (complete neglect of differential overlap) method and the electrostatic effects of metallic leads (bias and image charges) are included through a three-dimensional finite element method. This allows us to capture spatial details of the electrostatic potential profile, including effects of charging, screening, and complicated electrode configurations employing only a single adjustable parameter to locate the Fermi energy. As this model is based on semiempirical methods it is computationally inexpensive and flexible compared to ab initio models, yet at the same time it is able to capture salient qualitative features as well as several relevant quantitative details of transport. We apply our model to investigate recent experimental data on alkane dithiol molecules obtained in a nanopore setup. We also present a comparison study of single molecule transistors and identify electronic properties that control their performance.