Quinacrine causes apoptosis in human cancer cell lines through caspase-mediated pathway and regulation of small-GTPase.

J Biosci

CMBL, Department of Biological Sciences, BITS Pilani K K Birla, Goa Campus, Zuarinagar 403 726, India.

Published: November 2020

Quinacrine (QC), an FDA-approved anti-malarial drug, has shown to have anticancer activities. Due to its 'shotgun' nature, QC has become an inevitable candidate for combination chemotherapy. There is lack of study of the molecular interplay between colorectal cancer (CRC) microenvironment and its metastasis. In this study, we focused on the differential anti-cancerous effect of QC on two different human cancer cell lines, HCT 116 and INT 407. Results suggest that cytotoxicity increased in both the cell lines with an increase in QC concentration. The expression patterns of small-GTPases and caspases were altered significantly in QC-treated cells compared to non-treated cells. HSP70 and p53 showed comparable differences in the expression pattern. The wound-healing assay showed an increase in the denuded zone, with an increase in the concentration of QC. The formation of apoptotic nuclei increased with a rise in the concentration of QC in both the cell lines. The decrease and increase in caspase 9 and caspase 3 expression respectively were studied, confirming apoptosis by the extrinsic pathway.

Download full-text PDF

Source

Publication Analysis

Top Keywords

cell lines
16
human cancer
8
cancer cell
8
increase concentration
8
quinacrine apoptosis
4
apoptosis human
4
cell
4
lines
4
lines caspase-mediated
4
caspase-mediated pathway
4

Similar Publications

Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.

View Article and Find Full Text PDF

Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.

View Article and Find Full Text PDF

Metabolic reprogramming induced by PSMA4 overexpression facilitates bortezomib resistance in multiple myeloma.

Ann Hematol

January 2025

Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.

Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.

View Article and Find Full Text PDF

Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.

View Article and Find Full Text PDF

Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!