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. 2024 Mar 20;25(6):3503.
doi: 10.3390/ijms25063503.

Anti-Cancer Mechanisms of Diarylpentanoid MS17 (1,5-Bis(2-hydroxyphenyl)-1,4-pentadiene-3-one) in Human Colon Cancer Cells: A Proteomics Approach

Kha Wai Hon  1 , Syafiq Asnawi Zainal Abidin  1 , Faridah Abas  2   3 , Iekhsan Othman  1 , Rakesh Naidu  1
Affiliations

Anti-Cancer Mechanisms of Diarylpentanoid MS17 (1,5-Bis(2-hydroxyphenyl)-1,4-pentadiene-3-one) in Human Colon Cancer Cells: A Proteomics Approach

Kha Wai Hon et al. Int J Mol Sci. .

Abstract

Diarylpentanoids are synthesized to overcome curcumin's poor bioavailability and low stability to show enhanced anti-cancer effects. Little is known about the anti-cancer effects of diarylpentanoid MS17 (1,5-bis(2-hydroxyphenyl)-1,4-pentadiene-3-one) in colon cancer cells. This study aimed to elucidate molecular mechanisms and pathways modulated by MS17 in colon cancer based on proteomic profiling of primary SW480 and metastatic SW620 colon cancer cells. Cytotoxicity and apoptotic effects of MS17 were investigated using MTT assay, morphological studies, and Simple Western analysis. Proteomic profiling using LC/MS analysis identified differentially expressed proteins (DEPs) in MS17-treated cells, with further analysis in protein classification, gene ontology enrichment, protein-protein interaction network and Reactome pathway analysis. MS17 had lower EC50 values (SW480: 4.10 µM; SW620: 2.50 µM) than curcumin (SW480: 17.50 µM; SW620: 13.10 µM) with a greater anti-proliferative effect. MS17 treatment of 1× EC50 induced apoptotic changes in the morphology of SW480 and SW620 cells upon 24 h treatment. A total of 24 and 92 DEPs (fold change ≥ 1.50) were identified in SW480 and SW620 cells, respectively, upon MS17 treatment of 2× EC50 for 24 h. Pathway analysis showed that MS17 may induce its anti-cancer effects in both cells via selected DEPs associated with the top enriched molecular pathways. RPL and RPS ribosomal proteins, heat shock proteins (HSPs) and ubiquitin-protein ligases (UBB and UBC) were significantly associated with cellular responses to stress in SW480 and SW620 cells. Our findings suggest that MS17 may facilitate the anti-proliferative and apoptotic activities in primary (SW480) and metastatic (SW620) human colon cancer cells via the cellular responses to stress pathway. Further investigation is essential to determine the alternative apoptotic mechanisms of MS17 that are independent of caspase-3 activity and Bcl-2 protein expression in these cells. MS17 could be a potential anti-cancer agent in primary and metastatic colon cancer cells.

Keywords: anti-proliferation; apoptosis; colon cancer; diarylpentanoid; molecular pathways; proteomics.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Chemical structure of MS17 and curcumin.
Figure 2
Figure 2
Cytotoxicity assays using different concentrations of MS17 treated on (A) SW480 cells and (B) SW620 cells and curcumin on (C) SW480 cells and (D) SW620 cells. All the experiments were performed in triplicate, and results were compared between three independent experiments. Statistically significant differences between the means of values obtained with treated vs. untreated are represented by * for p ≤ 0.05, ** for p ≤ 0.01, and **** for p ≤ 0.0001. Data are presented as means ± SEM.
Figure 3
Figure 3
The anti-proliferative effect of MS17 in (A) SW480 and (B) SW620 cells and curcumin in (C) SW480 and (D) SW620 cells at 24, 48 and 72 h, in which (E) 0.2% of DMSO treatment (vehicle only) in the control wells of both cell lines did not induce anti-proliferative effects. All the experiments were performed in triplicate, and results were compared between three independent experiments. Statistically significant differences between the means of values obtained with treated vs. untreated are represented by * for p ≤ 0.05, ** for p ≤ 0.01, *** for p ≤ 0.001 and **** for p ≤ 0.0001. Data are presented as means ± SEM.
Figure 4
Figure 4
Morphological and quantitative analysis of apoptotic cells by acridine orange–propidium iodide (AO/PI) in SW480 cells upon MS17 treatment for 24, 48 and 72 h. Untreated viable cells emit uniformly green fluorescence (white arrow), while early apoptotic cells emit dense, bright-green fluorescence with membrane blebbing and chromatin condensation (blue arrow). Late apoptotic cells appear bright orange–red with yellow beads (yellow arrow). Necrotic cells showed a red appearance (purple arrow). Magnification 100×.
Figure 5
Figure 5
Morphological and quantitative analysis of apoptotic cells by acridine orange–propidium iodide (AO/PI) in SW620 cells upon MS17 treatment for 24, 48 and 72 h. Untreated viable cells emit uniformly green fluorescence (white arrow), while early apoptotic cells emit dense, bright-green fluorescence with membrane blebbing and chromatin condensation (blue arrow). Late apoptotic cells appear bright orange–red with yellow beads (yellow arrow). Necrotic cells showed a red appearance (purple arrow). Magnification 100×.
Figure 6
Figure 6
Percentage of cell population in (A) SW480 and (B) SW620 cells treated with MS17 for 24, 48, and 72 h. Results are expressed as means ± SEM from three independent experiments and comparison between data sets was performed using ANOVA. Statistically significant differences between the means of values obtained with treated vs. untreated cells are represented by * for p ≤ 0.05, ** for p ≤ 0.01, *** for p ≤ 0.001 and **** for p ≤ 0.0001.
Figure 7
Figure 7
Investigation of relative caspase-3 activity in (A) SW480 and (B) SW620 cells and the Bcl-2 protein expression in (C) SW480 and (D) SW620 cells upon MS17 treatment for 24, 48 and 72 h. The fold change of protein expression in each treatment group was normalized against the untreated control. Results are expressed as means ± SEM from three independent experiments and comparison between data sets was performed using ANOVA.
Figure 8
Figure 8
Percentage (%) of DEPs identified in MS17-treated (A) SW480 and (B) SW620 cells annotated to each statistically enriched GO term for functional categories “Molecular function”, “Cellular component” and “Biological process”. The number above each bar represents the percentage of protein of the respective GO terms, while the asterisks indicate the false-discovery rate (FDR) of each GO term upon multiple correction statistical tests using the Benjamini–Hochberg procedure (** p < 0.01, *** p < 0.001 and **** p < 0.0001).
Figure 9
Figure 9
Protein–protein interaction (PPI) network of all differentially expressed proteins (DEPs) identified in MS17-treated SW480. The nodes represent proteins, wherein the nodes in the same cluster are demonstrated by the same color. The lines connecting the nodes indicate the association between the proteins. The thicker the line, the higher the confidence in the interaction prediction. Dashed lines represent inter-clusters between the highly connected clusters.
Figure 10
Figure 10
Protein–protein interaction (PPI) network of all differentially expressed proteins (DEPs) identified in MS17-treated SW620. The nodes represent proteins, wherein the nodes in the same cluster are demonstrated by the same color. The lines connecting the nodes indicate the association between the proteins. The thicker the line, the higher the confidence in the interaction prediction. Dashed lines represent inter-clusters between the highly connected clusters.
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References

    1. Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F., Bsc M.F.B., Me J.F., Soerjomataram M.I., et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021;71:209–249. doi: 10.3322/caac.21660. - DOI - PubMed
    1. Arnold M., Sierra M.S., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017;66:683–691. doi: 10.1136/gutjnl-2015-310912. - DOI - PubMed
    1. Hassan M.R.A., Ismail I., Suan M.A.M., Ahmad F., Khazim W.K.W., Othman Z., Said R.M., Tan W.L., Rahmah S., Mohammed N.S., et al. Incidence and mortality rates of colorectal cancer in Malaysia. Epidemiol. Health. 2016;38:e2016007. doi: 10.4178/epih.e2016007. - DOI - PMC - PubMed
    1. Ramzi N.H., Chahil J.K., Lye S.H., Munretnam K., Sahadevappa K.I., Velapasamy S., Hashim N.A.N., Cheah S.K., Lim G.C.C., Hussein H., et al. Role of genetic & environment risk factors in the aetiology of colorectal cancer in Malaysia. Indian J. Med. Res. 2014;139:873–882. - PMC - PubMed
    1. Veettil S.K., Lim K.G., Chaiyakunapruk N., Ching S.M., Abu Hassan M.R. Colorectal cancer in Malaysia: Its burden and implications for a multiethnic country. Asian J. Surg. 2017;40:481–489. doi: 10.1016/j.asjsur.2016.07.005. - DOI - PubMed