Research Article
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Efficacy of metformin on protein profile in breast tumor cells by assessment in vitro and in silico analysis

Year 2022, Volume: 61 Issue: 2, 215 - 224, 13.06.2022
https://doi.org/10.19161/etd.1126777

Abstract

Aim: This study aimed to uncover the varieties in protein profiles of Met in breast tumor (BT) cells by assessment of in vitro and in silico analysis.


Materials and Methods: Here, the cells obtained from mastectomy patients were cultured, the effective Met-dose was determined as 25 mM through cell viability and BrdU tests. Protein identification in the breast tumor cells was implemented by employing LC-MS/MS technology.

Results: The expression of SSR3, THAP3, FTH1, NEFM, ANP32A, ANP32B, KRT7 proteins was significantly decreased whereas the GARS protein increased in the 25 mM Met group compared to the Non-Met (0 mM) control group. In silico analysis, we analyzed the probable interactions of all these proteins with each other and other proteins, to evaluate the analysis of the larger protein network, and which metabolic pathway proteins are involved in.

Conclusion: The stated proteomics analysis in our study proposes a better understanding of the prognosis of breast cancer and future studies to investigate the effect of metformin in this field on proteomic pathways in other sorts of cancer.

References

  • Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018; 68 (6): 394–424.
  • Lynch SM, Stricker CT, Brown JC, Berardi JM, Vaughn D, Domchek S, et al. Evaluation of a web-based weight loss intervention in overweight cancer survivors aged 50 years and younger. Obes Sci Pract. 2017; 3 (1): 83–94.
  • Lukong KE. Understanding breast cancer--The long and winding road. BBA Clin. 2017; 7: 64–77.
  • Bo me M Meie C K ä en ü l S Ji k SS Meie CR. Lon -term metformin use is associated with decreased risk of breast cancer. Diabetes Care. 2010; 33 (6): 1304–8.
  • Libby G, Donnelly LA, Donnan PT, Alessi DR, Morris AD, Evans JMM. New users of metformin are at low risk of incident cancer: a cohort study among people with type 2 diabetes. Diabetes Care. 2009; 32 (9): 1620–5.
  • Currie CJ, Poole CD, Jenkins-Jones S, Gale EAM, Johnson JA, Morgan CL. Mortality after incident cancer in people with and without type 2 diabetes: impact of metformin on survival. Diabetes Care. 2012; 35 (2): 299–304.
  • Bhalla K, Hwang BJ, Dewi RE, Twaddel W, Goloubeva OG, Wong K-K, et al. Metformin prevents liver tumorigenesis by inhibiting pathways driving hepatic lipogenesis. Cancer Prev Res. 2012; 5 (4): 544–52.
  • Pollak MN. Investigating metformin for cancer prevention and treatment: the end of the beginning. Cancer Discov. 2012;2(9):778–90.
  • Liu B, Fan Z, Edgerton SM, Deng XS, Alimova IN, Lind SE. Cell cycle (Georgetown, Tex.). Cell Cycle. 2009; 8 (13): 2031–40.
  • Faria J, Negalha G, Azevedo A, Martel F. Metformin and breast cancer: molecular targets. J Mammary Gland Biol Neoplasia. 2019; 1–13.
  • Thoreen CC, Sabatini DM. AMPK and p53 help cells through lean times. Cell Metab. 2005; 1 (5): 287–8.
  • Malki A, Youssef A. Antidiabetic drug metformin induces apoptosis in human MCF breast cancer via targeting ERK signaling. Oncol Res Featur Preclin Clin Cancer Ther. 2011; 19 (6): 275–85.
  • Deng X-S, Wang S, Deng A, Liu B, Edgerton SM, Lind SE, et al. Metformin targets Stat3 to inhibit cell growth and induce apoptosis in triple-negative breast cancers. Cell cycle. 2012; 11 (2): 367–76.
  • Najafi M, Cheki M, Rezapoor S, Geraily G, Motevaseli E, Carnovale C, et al. Metformin: Prevention of genomic instability and cancer: A review. Mutat Res Toxicol Environ Mutagen. 2018; 827: 1–8.
  • Besli N Yenmis G T nç emi M Sa a EY Do\ugan S, Solako\uglu S, et al. Metformin suppresses the proliferation and invasion through NF-kB and MMPs in MCF-7 cell line. Turkish J Biochem.
  • Yenmi\cs G, Be\csli N, Sarac EY, Emre FSH, \ SENOL K KANIGÜR G. Me o min p omo es apop osis in primary breast cancer cells by downregulation of cyclin D1 and upregulation of P53 through an AMPK-alpha independent mechanism. Turkish J Med Sci. 2021; 51 (2): 826–34.
  • Yu H, Braun P, Y\ild\ir\im MA, Lemmens I, Venkatesan K, Sahalie J, et al. High-quality binary protein interaction map of the yeast interactome network. Science (80-). 2008; 322 (5898): 104–10.
  • Yenmis G, Sarac EY, Besli N, Soydas T, Tastan C, Kancagi DD, et al. Anti-cancer effect of metformin on the metastasis and invasion of primary breast cancer cells through mediating NF-kB activity. Acta Histochem. 2021; 123 (4): 151709.
  • Consortium TU. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2018; 47 (D1): D506–15.
  • Schaefer MH, Fontaine J-F, Vinayagam A, Porras P, Wanker EE, Andrade-Navarro MA. HIPPIE: Integrating protein interaction networks with experiment based quality scores. PLoS One. 2012; 7 (2): e31826.
  • Chatr-Aryamontri A, Breitkreutz B-J, Heinicke S, Boucher L, Winter A, Stark C, et al. The BioGRID interaction database: 2013 update. Nucleic Acids Res. 2012; 41 (D1): D816--D823.
  • Licata L, Briganti L, Peluso D, Perfetto L, Iannuccelli M, Galeota E, et al. MINT, the molecular interaction database: 2012 update. Nucleic Acids Res. 2011; 40 (D1): D857--D861.
  • Kerrien S, Aranda B, Breuza L, Bridge A, Broackes-Carter F, Chen C, et al. The IntAct molecular interaction database in 2012. Nucleic Acids Res. 2011; 40 (D1): D841--D846.
  • Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic acids research. 2019; 47 (W1): W199-205.
  • Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 2019; 47 (D1): D590--D595.
  • Slenter DN, Kutmon M, Hanspers K, Riutta A, Windsor J, Nunes N, et al. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res. 2018; 46 (D1): D661--D667.
  • Mi H, Dong Q, Muruganujan A, Gaudet P, Lewis S, Thomas PD. PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium. Nucleic Acids Res. 2010; 38 (suppl_1): D204--D210.
  • Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol. 2012; 8 (2): e1002375.
  • Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010; 38 (suppl_2): W214–20.
  • Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein--protein association networks, made broadly accessible. Nucleic Acids Res. 2016; gkw937.
  • Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13 (11): 2498–504.
  • Morris JH, Apeltsin L, Newman AM, Baumbach J, Wittkop T, Su G, et al. clusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC Bioinformatics. 2011; 12 (1): 436.
  • Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res. 2002; 30 (7): 1575–84.
  • Isakovic A, Harhaji L, Stevanovic D, Markovic Z, Sumarac-Dumanovic M, Starcevic V, et al. Dual antiglioma action of metformin: cell cycle arrest and mitochondria-dependent apoptosis. Cell Mol life Sci. 2007; 64 (10): 1290.
  • Liu B, Fan Z, Edgerton SM, Deng X-S, Alimova IN, Lind SE, et al. Metformin induces unique biological and molecular responses in triple negative breast cancer cells. Cell cycle. 2009; 8 (13): 2031–40.
  • U lén M Fa e e L Halls öm BM Lin sko C Oksvol P Ma ino l A e al. Tiss e-based map of the human proteome. Science (80-). 2015; 347 (6220): 1260419.
  • Dorn GW, Kitsis RN. The mitochondrial dynamism-mitophagy-cell death interactome: multiple roles performed by members of a mitochondrial molecular ensemble. Circ Res. 2015; 116 (1): 167–82.
  • Cazzaniga M, Bonanni B. Relationship between metabolic reprogramming and mitochondrial activity in cancer cells. Understanding the anticancer effect of metformin and its clinical implications. Anticancer Res. 2015; 35 (11): 5789–96.
  • Vara-Perez M, Felipe-Abrio B, Agostinis P. Mitophagy in Cancer: A Tale of Adaptation. Cells. 2019; 8 (5): 493.
  • Zimmermann G, Papke B, Ismail S, Vartak N, Chandra A, Hoffmann M, et al. Small molecule inhibition of the KRAS--PDE$δ$ in e a ion impai s on o eni KRAS si nallin . Na e. 2013; 497 (7451): 638–42.
  • Boyle KA, Van Wickle J, Hill RB, Marchese A, Kalyanaraman B, Dwinell MB. Mitochondria-targeted drugs stimulate mitophagy and abrogate colon cancer cell proliferation. J Biol Chem. 2018; 293 (38): 14891–904.
  • Tyanova S, Albrechtsen R, Kronqvist P, Cox J, Mann M, Geiger T. Proteomic maps of breast cancer subtypes. Nat Commun. 2016; 7 (1): 1–11.
  • Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2018; 47 (D1): D607–13.

In vitro ve in silico analizi ile metforminin meme tümörü hücrelerinde protein profili üzerindeki etkinliği

Year 2022, Volume: 61 Issue: 2, 215 - 224, 13.06.2022
https://doi.org/10.19161/etd.1126777

Abstract

Amaç: Bu çalışmada, meme tümörü (BT) hücrelerinde Met'in protein profillerindeki çeşitlerin in vitro ve in siliko analizleri değerlendirilerek ortaya çıkarılması amaçlanmıştır.

Gereç ve Yöntem: Burada mastektomi hastalarından elde edilen hücreler kültürlendi, hücre canlılığı ve BrdU testleri ile etkin Met-doz 25 mM olarak belirlendi. Göğüs tümörü hücrelerinde protein tanımlaması, LC-MS/MS teknolojisi kullanılarak gerçekleştirilmiştir.


Bulgular: Proteomik analiz sonuçlarına göre, Non-Met (0 mM) kontrol grubuna kıyasla 25 mM Met grubunda SSR3, THAP3, FTH1, NEFM, ANP32A, ANP32B, KRT7 proteinlerinin ekspresyonu önemli ölçüde azalırken GARS proteininin ekpresyonu arttı. Silico analizde tüm bu proteinlerin birbirleriyle ve diğer proteinlerle olası etkileşimlerini analiz ederek daha büyük protein ağının analizini ve hangi metabolik yolak proteinlerinin rol oynadığını değerlendirdik.

Sonuç: Çalışmamızda belirtilen proteomik analizler, meme kanserinin prognozunun daha iyi anlaşılmasını ve metforminin diğer kanser türlerinde proteomik yolaklar üzerindeki etkisini araştırmak için gelecekteki çalışmaları önermektedir.

References

  • Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018; 68 (6): 394–424.
  • Lynch SM, Stricker CT, Brown JC, Berardi JM, Vaughn D, Domchek S, et al. Evaluation of a web-based weight loss intervention in overweight cancer survivors aged 50 years and younger. Obes Sci Pract. 2017; 3 (1): 83–94.
  • Lukong KE. Understanding breast cancer--The long and winding road. BBA Clin. 2017; 7: 64–77.
  • Bo me M Meie C K ä en ü l S Ji k SS Meie CR. Lon -term metformin use is associated with decreased risk of breast cancer. Diabetes Care. 2010; 33 (6): 1304–8.
  • Libby G, Donnelly LA, Donnan PT, Alessi DR, Morris AD, Evans JMM. New users of metformin are at low risk of incident cancer: a cohort study among people with type 2 diabetes. Diabetes Care. 2009; 32 (9): 1620–5.
  • Currie CJ, Poole CD, Jenkins-Jones S, Gale EAM, Johnson JA, Morgan CL. Mortality after incident cancer in people with and without type 2 diabetes: impact of metformin on survival. Diabetes Care. 2012; 35 (2): 299–304.
  • Bhalla K, Hwang BJ, Dewi RE, Twaddel W, Goloubeva OG, Wong K-K, et al. Metformin prevents liver tumorigenesis by inhibiting pathways driving hepatic lipogenesis. Cancer Prev Res. 2012; 5 (4): 544–52.
  • Pollak MN. Investigating metformin for cancer prevention and treatment: the end of the beginning. Cancer Discov. 2012;2(9):778–90.
  • Liu B, Fan Z, Edgerton SM, Deng XS, Alimova IN, Lind SE. Cell cycle (Georgetown, Tex.). Cell Cycle. 2009; 8 (13): 2031–40.
  • Faria J, Negalha G, Azevedo A, Martel F. Metformin and breast cancer: molecular targets. J Mammary Gland Biol Neoplasia. 2019; 1–13.
  • Thoreen CC, Sabatini DM. AMPK and p53 help cells through lean times. Cell Metab. 2005; 1 (5): 287–8.
  • Malki A, Youssef A. Antidiabetic drug metformin induces apoptosis in human MCF breast cancer via targeting ERK signaling. Oncol Res Featur Preclin Clin Cancer Ther. 2011; 19 (6): 275–85.
  • Deng X-S, Wang S, Deng A, Liu B, Edgerton SM, Lind SE, et al. Metformin targets Stat3 to inhibit cell growth and induce apoptosis in triple-negative breast cancers. Cell cycle. 2012; 11 (2): 367–76.
  • Najafi M, Cheki M, Rezapoor S, Geraily G, Motevaseli E, Carnovale C, et al. Metformin: Prevention of genomic instability and cancer: A review. Mutat Res Toxicol Environ Mutagen. 2018; 827: 1–8.
  • Besli N Yenmis G T nç emi M Sa a EY Do\ugan S, Solako\uglu S, et al. Metformin suppresses the proliferation and invasion through NF-kB and MMPs in MCF-7 cell line. Turkish J Biochem.
  • Yenmi\cs G, Be\csli N, Sarac EY, Emre FSH, \ SENOL K KANIGÜR G. Me o min p omo es apop osis in primary breast cancer cells by downregulation of cyclin D1 and upregulation of P53 through an AMPK-alpha independent mechanism. Turkish J Med Sci. 2021; 51 (2): 826–34.
  • Yu H, Braun P, Y\ild\ir\im MA, Lemmens I, Venkatesan K, Sahalie J, et al. High-quality binary protein interaction map of the yeast interactome network. Science (80-). 2008; 322 (5898): 104–10.
  • Yenmis G, Sarac EY, Besli N, Soydas T, Tastan C, Kancagi DD, et al. Anti-cancer effect of metformin on the metastasis and invasion of primary breast cancer cells through mediating NF-kB activity. Acta Histochem. 2021; 123 (4): 151709.
  • Consortium TU. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2018; 47 (D1): D506–15.
  • Schaefer MH, Fontaine J-F, Vinayagam A, Porras P, Wanker EE, Andrade-Navarro MA. HIPPIE: Integrating protein interaction networks with experiment based quality scores. PLoS One. 2012; 7 (2): e31826.
  • Chatr-Aryamontri A, Breitkreutz B-J, Heinicke S, Boucher L, Winter A, Stark C, et al. The BioGRID interaction database: 2013 update. Nucleic Acids Res. 2012; 41 (D1): D816--D823.
  • Licata L, Briganti L, Peluso D, Perfetto L, Iannuccelli M, Galeota E, et al. MINT, the molecular interaction database: 2012 update. Nucleic Acids Res. 2011; 40 (D1): D857--D861.
  • Kerrien S, Aranda B, Breuza L, Bridge A, Broackes-Carter F, Chen C, et al. The IntAct molecular interaction database in 2012. Nucleic Acids Res. 2011; 40 (D1): D841--D846.
  • Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic acids research. 2019; 47 (W1): W199-205.
  • Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 2019; 47 (D1): D590--D595.
  • Slenter DN, Kutmon M, Hanspers K, Riutta A, Windsor J, Nunes N, et al. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res. 2018; 46 (D1): D661--D667.
  • Mi H, Dong Q, Muruganujan A, Gaudet P, Lewis S, Thomas PD. PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium. Nucleic Acids Res. 2010; 38 (suppl_1): D204--D210.
  • Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol. 2012; 8 (2): e1002375.
  • Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010; 38 (suppl_2): W214–20.
  • Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein--protein association networks, made broadly accessible. Nucleic Acids Res. 2016; gkw937.
  • Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13 (11): 2498–504.
  • Morris JH, Apeltsin L, Newman AM, Baumbach J, Wittkop T, Su G, et al. clusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC Bioinformatics. 2011; 12 (1): 436.
  • Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res. 2002; 30 (7): 1575–84.
  • Isakovic A, Harhaji L, Stevanovic D, Markovic Z, Sumarac-Dumanovic M, Starcevic V, et al. Dual antiglioma action of metformin: cell cycle arrest and mitochondria-dependent apoptosis. Cell Mol life Sci. 2007; 64 (10): 1290.
  • Liu B, Fan Z, Edgerton SM, Deng X-S, Alimova IN, Lind SE, et al. Metformin induces unique biological and molecular responses in triple negative breast cancer cells. Cell cycle. 2009; 8 (13): 2031–40.
  • U lén M Fa e e L Halls öm BM Lin sko C Oksvol P Ma ino l A e al. Tiss e-based map of the human proteome. Science (80-). 2015; 347 (6220): 1260419.
  • Dorn GW, Kitsis RN. The mitochondrial dynamism-mitophagy-cell death interactome: multiple roles performed by members of a mitochondrial molecular ensemble. Circ Res. 2015; 116 (1): 167–82.
  • Cazzaniga M, Bonanni B. Relationship between metabolic reprogramming and mitochondrial activity in cancer cells. Understanding the anticancer effect of metformin and its clinical implications. Anticancer Res. 2015; 35 (11): 5789–96.
  • Vara-Perez M, Felipe-Abrio B, Agostinis P. Mitophagy in Cancer: A Tale of Adaptation. Cells. 2019; 8 (5): 493.
  • Zimmermann G, Papke B, Ismail S, Vartak N, Chandra A, Hoffmann M, et al. Small molecule inhibition of the KRAS--PDE$δ$ in e a ion impai s on o eni KRAS si nallin . Na e. 2013; 497 (7451): 638–42.
  • Boyle KA, Van Wickle J, Hill RB, Marchese A, Kalyanaraman B, Dwinell MB. Mitochondria-targeted drugs stimulate mitophagy and abrogate colon cancer cell proliferation. J Biol Chem. 2018; 293 (38): 14891–904.
  • Tyanova S, Albrechtsen R, Kronqvist P, Cox J, Mann M, Geiger T. Proteomic maps of breast cancer subtypes. Nat Commun. 2016; 7 (1): 1–11.
  • Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2018; 47 (D1): D607–13.
There are 43 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Research Articles
Authors

Güven Yenmiş 0000-0002-6688-9725

Nail Beşli 0000-0002-6174-915X

Publication Date June 13, 2022
Submission Date September 2, 2021
Published in Issue Year 2022Volume: 61 Issue: 2

Cite

Vancouver Yenmiş G, Beşli N. Efficacy of metformin on protein profile in breast tumor cells by assessment in vitro and in silico analysis. EJM. 2022;61(2):215-24.