Combined Effect of Parthenolide and Various Anti-cancer Drugs or Anticancer Candidate Substances on Malignant Cells in vitro and in vivo

2014 ◽  
Vol 14 (3) ◽  
pp. 222-228 ◽  
Author(s):  
Anna Wyrebska ◽  
Katarzyna Gach ◽  
Anna Janecka
Keyword(s):  
Combined Effect ◽  
Malignant Cells ◽  
Cancer Drugs ◽  
Anti Cancer

Chalcone-Coumarin Derivatives as Potential Anti-Cancer Drugs: An in vitro and in vivo Investigation

2013 ◽  
Vol 14 (7) ◽  
pp. 963-974 ◽  
Author(s):  
Vincent Jamier ◽  
Wioleta Marut ◽  
Sergio Valente ◽  
Christiane Chereau ◽  
Sandrine Chouzenoux ◽  
...  
Keyword(s):  
Coumarin Derivatives ◽  
Cancer Drugs ◽  
Anti Cancer

scholarly journals Coherent Raman Scattering Microscopy in Oncology Pharmacokinetic Research

2021 ◽  
Vol 12 ◽  
Author(s):  
Junjie Zeng ◽  
Wenying Zhao ◽  
Shuhua Yue
Keyword(s):  
Raman Scattering ◽  
High Speed ◽  
Cancer Drug ◽  
Cancer Drugs ◽  
High Speed Imaging ◽  
Coherent Raman Scattering ◽  
Anti Cancer ◽  
Coherent Raman

The high attrition rates of anti-cancer drugs during clinical development remains a bottleneck problem in pharmaceutical industry. This is partially due to the lack of quantitative, selective, and rapid readouts of anti-cancer drug activity in situ with high resolution. Although fluorescence microscopy has been commonly used in oncology pharmacological research, fluorescent labels are often too large in size for small drug molecules, and thus may disturb the function or metabolism of these molecules. Such challenge can be overcome by coherent Raman scattering microscopy, which is capable of chemically selective, highly sensitive, high spatial resolution, and high-speed imaging, without the need of any labeling. Coherent Raman scattering microscopy has tremendously improved the understanding of pharmaceutical materials in the solid state, pharmacokinetics of anti-cancer drugs and nanocarriers in vitro and in vivo. This review focuses on the latest applications of coherent Raman scattering microscopy as a new emerging platform to facilitate oncology pharmacokinetic research.

scholarly journals pH-Sensitive Ratiometric Fluorescent Probe for Evaluation of Tumor Treatments

Materials ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1632
Author(s):  
Peisen Zhang ◽  
Junli Meng ◽  
Yingying Li ◽  
Zihua Wang ◽  
Yi Hou
Keyword(s):  
Ph Sensitive ◽  
Fluorescent Imaging ◽  
Tat Peptide ◽  
Cancer Drugs ◽  
Ph Response ◽  
In Vivo Experiments ◽  
Anti Cancer ◽  
Amidation Reaction

Determining therapeutic efficacy is critical for tumor precision theranostics. In order to monitor the efficacy of anti-cancer drugs (e.g., Paclitaxel), a pH-sensitive ratiometric fluorescent imaging probe was constructed. The pH-sensitive ratiometric fluorescent dye ANNA was covalently coupled to the N-terminal of the cell-penetrating TAT peptide through an amidation reaction (TAT-ANNA). The in vitro cellular experiments determined that the TAT-ANNA probe could penetrate the cell membrane and image the intracellular pH in real time. The in vivo experiments were then carried out, and the ratiometric pH response to the state of the tumor was recorded immediately after medication. The TAT-ANNA probe was successfully used to monitor the pharmacodynamics of anti-cancer drugs in vivo.

Potentiation of the Anti-Proliferative Effects of Anti-Cancer Drugs by Octreotide in vitro and in vivo

Digestion ◽  
1996 ◽  
Vol 57 (1) ◽  
pp. 22-28 ◽  
Author(s):  
G. Weckbecker ◽  
F. Raulf ◽  
L. Tolcsvai ◽  
C. Bruns
Keyword(s):  
Cancer Drugs ◽  
Anti Cancer

Intracellular concentrations of anti cancer drugs in leukemic cells in vitro vs in vivo

1990 ◽  
Vol 25 (4) ◽  
pp. 252-256 ◽  
Author(s):  
B. Sundman-Engberg ◽  
U. Tidefelt ◽  
J. Liliemark ◽  
C. Paul
Keyword(s):  
Leukemic Cells ◽  
Cancer Drugs ◽  
Anti Cancer ◽  
Intracellular Concentrations

scholarly journals A nanoformulation of siRNA and its role in cancer therapy: In vitro and in vivo evaluation

2013 ◽  
Vol 18 (1) ◽  
Author(s):  
Hitesh Jagani ◽  
Josyula Rao ◽  
Vasanth Palanimuthu ◽  
Raghu Hariharapura ◽  
Sagar Gang
Keyword(s):  
Chitosan Nanoparticles ◽  
Cancer Drugs ◽  
Neoplastic Cells ◽  
In Vivo Evaluation ◽  
Anti Cancer ◽  
Effective Delivery ◽  
Interfering Rna ◽  
Cancerous Cells

AbstractOverexpression of anti-apoptotic Bcl-2 is often observed in a wide variety of human cancers. It prevents the induction of apoptosis in neoplastic cells and contributes to resistance to chemotherapy. RNA interference has emerged as an efficient and selective technique for gene silencing. The potential to use small interfering RNA (siRNA) as a therapeutic agent for the treatment of cancer has elicited a great deal of interest. However, insufficient cellular uptake and poor stability have limited its therapeutic applications. The purpose of this study was to prepare chitosan nanoparticles via ionic gelation of chitosan by tripolyphosphate for effective delivery of siRNA to silence the anti-apoptotic Bcl-2 gene in neoplastic cells. Chitosan nanoparticles loaded with siRNA were in the size range 190 to 340 nm with a polydispersive index ranging from 0.04 to 0.2. They were able to completely bind with siRNA, provide protection against nuclease degradation, and enhance the transfection. Cell culture studies revealed that nanoparticles with entrapped siRNA could efficiently silence the antiapoptotic Bcl-2 gene. Studies on Swiss albino mice showed that siRNA could be effectively delivered through nanoparticles. There was significant decrease in the tumor volume. Blocking the expression of anti-apoptotic Bcl-2 can enhance the sensitivity of cancerous cells to anti-cancer drugs and the apoptosis rate. Therefore, nanoformulations with siRNA can be promoted as an adjuvant therapy in combination with anti-cancer drugs.

Bioinformatics Approaches for Anti-cancer Drug Discovery

2019 ◽  
Vol 21 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Kening Li ◽  
Yuxin Du ◽  
Lu Li ◽  
Dong-Qing Wei
Keyword(s):  
Drug Discovery ◽  
Cancer Therapy ◽  
Biological Network ◽  
Computational Prediction ◽  
Cancer Drug ◽  
Cancer Drugs ◽  
Cancer Drug Discovery ◽  
Anti Cancer

Drug discovery is important in cancer therapy and precision medicines. Traditional approaches of drug discovery are mainly based on in vivo animal experiments and in vitro drug screening, but these methods are usually expensive and laborious. In the last decade, omics data explosion provides an opportunity for computational prediction of anti-cancer drugs, improving the efficiency of drug discovery. High-throughput transcriptome data were widely used in biomarkers’ identification and drug prediction by integrating with drug-response data. Moreover, biological network theory and methodology were also successfully applied to the anti-cancer drug discovery, such as studies based on protein-protein interaction network, drug-target network and disease-gene network. In this review, we summarized and discussed the bioinformatics approaches for predicting anti-cancer drugs and drug combinations based on the multi-omic data, including transcriptomics, toxicogenomics, functional genomics and biological network. We believe that the general overview of available databases and current computational methods will be helpful for the development of novel cancer therapy strategies.

scholarly journals Dissecting intratumor heterogeneity of nodal B cell lymphomas on the transcriptional, genetic, and drug response level

2019 ◽  
Author(s):  
Tobias Roider ◽  
Julian Seufert ◽  
Alexey Uvarovskii ◽  
Felix Frauhammer ◽  
Marie Bordas ◽  
...  
Keyword(s):  
B Cell ◽  
Drug Response ◽  
Ex Vivo ◽  
T Cell Subsets ◽  
Intratumor Heterogeneity ◽  
Malignant Cells ◽  
Cancer Drugs ◽  
Response Level ◽  
Anti Cancer

AbstractTumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer drugs, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

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