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An Investigation of the Anticancer Mechanism of Caesalpinia sappan L. Extract Against Colorectal Cancer by Integrating a Network Pharmacological Analysis and Experimental Validation

GSE313097 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2025/12/09 Platform GPL19057
Summary
Caesalpinia sappan L. has exhibited various pharmacological effects, yet its anticancer activities against colorectal cancer (CRC) and underlying molecular mechanisms remain unclear. This study investigated the anticancer properties of an ethanol extract of C. sappan L. (CSE) against CRC cells, focusing on the identification of bioactive compounds and their mechanisms of action. A network pharmacology analysis was conducted to identify potential CRC targets and bioactive compounds of CSE, using LC-MS for compound identification. The anticancer effects of CSE were then validated through in vitro and in vivo models of CRC. The network pharmacological approach identified 87 overlapping genes between CSE targets and CRC-related genes, with protein–protein interaction analysis highlighting 33 key target genes. CSE inhibited cell proliferation in human CRC cell lines, including HCT 116, KM12SM, HT-29, and COLO 205, and induced apoptosis via caspase 3/7 activation. Western blot analyses confirmed the modulation of critical signaling pathways, including STAT3, AKT, and mitogen-activated protein kinases. Furthermore, CSE significantly suppressed tumor growth in MC38 CRC-bearing mice. These findings suggest that CSE possesses substantial potential as a natural anticancer agent for CRC treatment, highlighting the need for further exploration in therapeutic development.
Published in
An Investigation of the Anticancer Mechanism of Caesalpinia sappan L. Extract Against Colorectal Cancer by Integrating a Network Pharmacological Analysis and Experimental Validation
Jeong M, Chun J, Park SM et al. · Plants (Basel, Switzerland) 2025 · PMID 39861616 · doi:10.3390/plants14020263
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Also filed as BioProject PRJNA1378257 and SRA study SRP653841. Searching any of these in the dataset finder brings you back here.

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