Proteomic Analysis of Human Breast Cancer MCF-7 Cells to Identify Cellular Targets of the Anticancer Pigment OR3 from Streptomyces coelicolor JUACT03.
Somasekhara DManjunath DammalliVaralakshmi Kilingar NadumanePublished in: Applied biochemistry and biotechnology (2022)
Search for ideal compounds with known pathways of anticancer mechanism is still a priority research focus for cancer, as it continues to be a major health challenge across the globe. Hence, in the present study, anticancer potential of a yellow pigment fraction, OR3, isolated from Streptomyces coelicolor JUACT03 was assessed on the breast cancer cell line MCF-7. TLC-fractionated OR3 pigment was subjected to HPLC and GC-MS analysis for characterization and identification of the bioactive component. MCF-7 cells were treated with IC 50 concentration of OR3 and the molecular alterations were analyzed using mass spectrometry-based quantitative proteomic analysis. Bioinformatics tools such as STRING analysis and Ingenuity Pathway Analysis were performed to analyze proteomics data and to identify dysregulated signaling pathways. As per our obtained data, OR3 treatment decreased cell proliferation and induced apoptotic cell death due to significant dysregulation of protein expressions in MCF-7 cells. Altered expression included the ribosomal, mRNA processing and vesicle-mediated transport proteins as a result of OR3 treatment. Downregulation of MAPK proteins, NFkB, and estradiol signaling was identified in OR3-treated MCF-7 cells. Mainly eIF2, mTOR, and eIF4 signaling pathways were altered in OR3-treated cells. GC-MS data indicated the presence of novel compounds in OR3 fraction. It can be concluded that OR3 exhibits potent anticancer activity on the breast cancer cells mainly through altering the expression and affecting the signaling proteins which are involved in different cell proliferation/apoptotic pathways thereby causing inhibition of cancer cell proliferation, survival and metastasis.
Keyphrases
- induced apoptosis
- cell cycle arrest
- cell proliferation
- breast cancer cells
- cell death
- signaling pathway
- mass spectrometry
- pi k akt
- healthcare
- endoplasmic reticulum stress
- poor prognosis
- oxidative stress
- public health
- electronic health record
- epithelial mesenchymal transition
- risk assessment
- machine learning
- cell cycle
- high performance liquid chromatography
- binding protein
- diabetic rats
- small cell lung cancer
- small molecule
- artificial intelligence
- anti inflammatory
- human health
- squamous cell
- deep learning
- social media
- lymph node metastasis
- bioinformatics analysis
- newly diagnosed