Research Article
BibTex RIS Cite

Hidradan insana: atavistik kanser modelinin in silico araştırması

Year 2024, Volume: 49 Issue: 4, 863 - 880, 30.12.2024
https://doi.org/10.17826/cumj.1505761

Abstract

Amaç: Kanser, hücresel iş birliğini sağlayan genlerin görevlerini yerine getirememelerinden kaynaklanarak çok hücreli sistemlerin işleyişini bozar. Dikkat çekici bir şekilde, kanser atavistik özellikler gösterir; bu, kanser hücrelerinin geleneksel Darwinci evrimden saparak evrimsel yollarında kendine özgü bir rota izlediklerini gösterir. Bu bağlamda, kanser hücreleri kontrolsüz çoğalma, hücre ölüm mekanizmalarından kaçış ve değişmiş metabolizma gibi hücre büyümesi ve hayatta kalma ile ilgili eski biyolojik programları yansıtan özellikler sergileyebilir. Bu çalışmada bazal metazoan Hydra'da oluşan tümörlerle ilişkili proteinleri ve bunların farklı taksonlar boyunca korunmasını analiz ederek kanserin evrimsel kökenini incelemek amaçlanmıştır.
Gereç ve Yöntem: Bu çalışmada Hydra tümörlerinde protein kodlayan transkriptlerin evrimsel korunma durumunu araştırmak için biyoinformatik yaklaşımlar kullanılmıştır. Bu analizler, hem tek hücreli hem de çok hücreli yaşam formlarını temsil eden türler arasında gerçekleştirilmiştir.
Bulgular: Hydra tümörleriyle ilişkili proteinlerin taksonomik dağılımını inceleyerek, kanserin evrimsel kökenleri seçilen temsilci türler boyunca takip edilmiştir. Hydra tümörlerinde protein kodlayan genlerin çoğunluğunun tek hücreli kökenli olduğu ve insanda kanserle ilişkili olduğu bulunmuştur.
Sonuç: Çalışmada Hydra tümörlerinde ifade edilen genlerin evrimsel süreç boyunca korunumu ortaya çıkarılmıştır. Hydra’nın kanser araştırmalarında model organizma olarak değerlendirilebileceği önerilmektedir.

Ethical Statement

We declare there is no conflict of interest

References

  • Aktipis CA, Nesse RM. Evolutionary foundations for cancer biology. Evol Appl. 2013;6:144-59.
  • Rokas A. The origins of multicellularity and the early history of the genetic toolkit for animal development. Annu Rev Genet. 2008;42:235-51.
  • Grosberg RK, Strathmann RR. The evolution of multicellularity: a minor major transition? Annual Review of Ecology, Evolution and Systematics. 2007;38:621-54.
  • Nedelcu AM. The evolution of multicellularity and cancer: views and paradigms. Biochem Soc Trans. 2020;48:1505-18.
  • Aktipis CA, Boddy AM, Jansen G, Hibner U, Hochberg ME, Maley CC et al. Cancer across the tree of life: cooperation and cheating in multicellularity. Philos Trans R Soc Lond B Biol Sci. 2015;370.
  • Davies PC, Lineweaver CH. Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestors. Phys Biol. 2011;8:015001.
  • Domazet-Loso T, Tautz D. Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa. BMC Biol. 2010;8:66.
  • Lineweaver CH, Bussey KJ, Blackburn AC, Davies PCW. Cancer progression as a sequence of atavistic reversions. Bioessays. 2021;43:e2000305.
  • Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors. Proc Natl Acad Sci U S A. 2017;114:6406-11.
  • Louka A, Takan I, Pavlopoulou A, Georgakilas AG. Bioinformatic approaches to the investigation of the atavistic genes implicated in cancer. Front Biosci (Landmark Ed). 2021;26:279-311.
  • Chen H, Lin F, Xing K, He X. The reverse evolution from multicellularity to unicellularity during carcinogenesis. Nat Commun. 2015;6:6367.
  • Robert J. Comparative study of tumorigenesis and tumor immunity in invertebrates and nonmammalian vertebrates. Dev Comp Immunol. 2010;34:915-25.
  • Squires DF. Neoplasia in a Coral? Science. 1965;148:503-5.
  • Domazet-Loso T, Klimovich A, Anokhin B, Anton-Erxleben F, Hamm MJ, Lange C et al. Naturally occurring tumours in the basal metazoan Hydra. Nat Commun. 2014;5:4222.
  • Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC et al. Database resources of the National Center for Biotechnology Information in 2023. Nucleic Acids Res. 2023;51:D29-D38.
  • Sayers EW, Cavanaugh M, Clark K, Pruitt KD, Sherry ST, Yankie L et al. GenBank 2023 update. Nucleic Acids Res. 2023;51:D141-D44.
  • Xu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L et al. Using clusterProfiler to characterize multiomics data. Nat Protoc. 2024.
  • Yu G: enrichplot: Visualization of Functional Enrichment Result. R package version 1.24.2, 2024.
  • Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403-10.
  • Seal RL, Braschi B, Gray K, Jones TEM, Tweedie S, Haim-Vilmovsky L et al. Genenames.org: the HGNC resources in 2023. Nucleic Acids Res. 2023;51:D1003-09.
  • Simossis VA, Heringa J. PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information. Nucleic Acids Res. 2005;33:W289-94.
  • Tamura K, Stecher G, Kumar S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol. 2021;38:3022-27.
  • Webb B, Sali A. Protein structure modeling with MODELLER. Methods Mol Biol. 2017;1654:39-54.
  • Janson G, Grottesi A, Pietrosanto M, Ausiello G, Guarguaglini G, Paiardini A. Revisiting the "satisfaction of spatial restraints" approach of MODELLER for protein homology modeling. PLoS Comput Biol. 2019;15:e1007219.
  • Kontou PI, Pavlopoulou A, Bagos PG. Methods of analysis and meta-analysis for identifying differentially expressed genes. Methods Mol Biol. 2018;1793:183-210.
  • Zhao H, Wu L, Yan G, Chen Y, Zhou M, Wu Y et al. Inflammation and tumor progression: signaling pathways and targeted intervention. Signal Transduct Target Ther. 2021;6:263.
  • Ben-Baruch A. Tumor Necrosis Factor alpha: Taking a Personalized Road in Cancer Therapy. Front Immunol. 2022;13:903679.
  • Rappaport N, Twik M, Plaschkes I, Nudel R, Iny Stein T, Levitt J et al. MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search. Nucleic Acids Res. 2017;45:D877-D87.
  • De Angelis R, Iezzi S, Bruno T, Corbi N, Di Padova M, Floridi A et al. Functional interaction of the subunit 3 of RNA polymerase II (RPB3) with transcription factor-4 (ATF4). FEBS Lett. 2003;547:15-9.
  • Thiffault I, Wolf NI, Forget D, Guerrero K, Tran LT, Choquet K et al. Recessive mutations in POLR1C cause a leukodystrophy by impairing biogenesis of RNA polymerase III. Nat Commun. 2015;6:7623.
  • Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ. Jalview Version 2--a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189-91.
  • National Cancer Institute. https://www.cancer.gov/news-events/press-releases/2020 (accessed on 7 June 2021) (accessed June 7, 2021.
  • Trigos AS, Pearson RB, Papenfuss AT, Goode DL. How the evolution of multicellularity set the stage for cancer. Br J Cancer. 2018;118:145-52.
  • Domazet-Loso T, Brajkovic J, Tautz D. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends Genet. 2007;23:533-9.
  • Lang BF, O'Kelly C, Nerad T, Gray MW, Burger G. The closest unicellular relatives of animals. Curr Biol. 2002;12:1773-8.
  • King N, Westbrook MJ, Young SL, Kuo A, Abedin M, Chapman J et al. The genome of the choanoflagellate Monosiga brevicollis and the origin of metazoans. Nature. 2008;451:783-8.
  • Harris EH. Chlamydomonas as a model organism. Annu Rev Plant Physiol Plant Mol Biol. 2001;52:363-406.
  • Vanderwaeren L, Dok R, Voordeckers K, Nuyts S, Verstrepen KJ. Saccharomyces cerevisiae as a model system for eukaryotic cell biology, from cell cycle control to dna damage response. Int J Mol Sci. 2022;23.
  • Vyas A, Freitas AV, Ralston ZA, Tang Z. Fission yeast schizosaccharomyces pombe: a unicellular "micromammal" model organism. Curr Protoc. 2021;1:e151.
  • Nagy LG, Varga T, Csernetics Á, Virágh M. Fungi took a unique evolutionary route to multicellularity: Seven key challenges for fungal multicellular life. Fungal Biology Reviews. 2020;34:151-69.
  • Torruella G, de Mendoza A, Grau-Bove X, Anto M, Chaplin MA, del Campo J et al. Phylogenomics reveals convergent evolution of lifestyles in close relatives of animals and fungi. Curr Biol. 2015;25:2404-10.
  • Bertile F, Matallana-Surget S, Tholey A, Cristobal S, Armengaud J. Diversifying the concept of model organisms in the age of -omics. Commun Biol. 2023;6:1062.
  • Yum S, Woo S, Lee A, Won H, Kim J. Hydra, a candidate for an alternative model in environmental genomics. Mol Cell Toxicol. 2014;10:339–46.
  • Cetkovic H, Halasz M, Herak Bosnar M. Sponges: A reservoir of genes implicated in human cancer. Mar Drugs. 2018;16:20

From hydra to human: in silico investigation of the atavistic model of cancer

Year 2024, Volume: 49 Issue: 4, 863 - 880, 30.12.2024
https://doi.org/10.17826/cumj.1505761

Abstract

Purpose: Cancer manifests as a disruption in the regular functioning of multicellular systems, arising from the malfunctioning of genes responsible for cellular cooperation. Notably, cancer exhibits atavistic characteristics, wherein cancer cells diverge from the conventional Darwinian evolution, highlighting a distinctive trajectory in their evolutionary fate. In this context, cancer cells may display traits such as uncontrolled proliferation, evasion of cell death mechanisms and altered metabolism, which could reflect ancient biological programs related to cell growth and survival. The objective of this study was to trace the evolutionary origin of cancer by analyzing tumor-related proteins in the basal metazoan Hydra and their preservation across diverse taxa.
Materials and Methods: Bioinformatic approaches were employed to investigate the conservation status of protein-coding transcripts that are differentially expressed in the tumor-bearing Hydra across species, representing both unicellular and multicellular forms of life.
Results: By examining the taxonomic distribution of the Hydra polyp-related proteins, we have traced the ancient evolutionary roots of cancer through the tree of life. The majority of protein-coding genes were found to be of unicellular origin and associated with cancer.
Conclusion: We suggest conservation of the atavistic in model of cancer the basal tumor-bearing animals, which can be considered as promising and intriguing candidate model organisms in cancer research.

References

  • Aktipis CA, Nesse RM. Evolutionary foundations for cancer biology. Evol Appl. 2013;6:144-59.
  • Rokas A. The origins of multicellularity and the early history of the genetic toolkit for animal development. Annu Rev Genet. 2008;42:235-51.
  • Grosberg RK, Strathmann RR. The evolution of multicellularity: a minor major transition? Annual Review of Ecology, Evolution and Systematics. 2007;38:621-54.
  • Nedelcu AM. The evolution of multicellularity and cancer: views and paradigms. Biochem Soc Trans. 2020;48:1505-18.
  • Aktipis CA, Boddy AM, Jansen G, Hibner U, Hochberg ME, Maley CC et al. Cancer across the tree of life: cooperation and cheating in multicellularity. Philos Trans R Soc Lond B Biol Sci. 2015;370.
  • Davies PC, Lineweaver CH. Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestors. Phys Biol. 2011;8:015001.
  • Domazet-Loso T, Tautz D. Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa. BMC Biol. 2010;8:66.
  • Lineweaver CH, Bussey KJ, Blackburn AC, Davies PCW. Cancer progression as a sequence of atavistic reversions. Bioessays. 2021;43:e2000305.
  • Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors. Proc Natl Acad Sci U S A. 2017;114:6406-11.
  • Louka A, Takan I, Pavlopoulou A, Georgakilas AG. Bioinformatic approaches to the investigation of the atavistic genes implicated in cancer. Front Biosci (Landmark Ed). 2021;26:279-311.
  • Chen H, Lin F, Xing K, He X. The reverse evolution from multicellularity to unicellularity during carcinogenesis. Nat Commun. 2015;6:6367.
  • Robert J. Comparative study of tumorigenesis and tumor immunity in invertebrates and nonmammalian vertebrates. Dev Comp Immunol. 2010;34:915-25.
  • Squires DF. Neoplasia in a Coral? Science. 1965;148:503-5.
  • Domazet-Loso T, Klimovich A, Anokhin B, Anton-Erxleben F, Hamm MJ, Lange C et al. Naturally occurring tumours in the basal metazoan Hydra. Nat Commun. 2014;5:4222.
  • Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC et al. Database resources of the National Center for Biotechnology Information in 2023. Nucleic Acids Res. 2023;51:D29-D38.
  • Sayers EW, Cavanaugh M, Clark K, Pruitt KD, Sherry ST, Yankie L et al. GenBank 2023 update. Nucleic Acids Res. 2023;51:D141-D44.
  • Xu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L et al. Using clusterProfiler to characterize multiomics data. Nat Protoc. 2024.
  • Yu G: enrichplot: Visualization of Functional Enrichment Result. R package version 1.24.2, 2024.
  • Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403-10.
  • Seal RL, Braschi B, Gray K, Jones TEM, Tweedie S, Haim-Vilmovsky L et al. Genenames.org: the HGNC resources in 2023. Nucleic Acids Res. 2023;51:D1003-09.
  • Simossis VA, Heringa J. PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information. Nucleic Acids Res. 2005;33:W289-94.
  • Tamura K, Stecher G, Kumar S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol. 2021;38:3022-27.
  • Webb B, Sali A. Protein structure modeling with MODELLER. Methods Mol Biol. 2017;1654:39-54.
  • Janson G, Grottesi A, Pietrosanto M, Ausiello G, Guarguaglini G, Paiardini A. Revisiting the "satisfaction of spatial restraints" approach of MODELLER for protein homology modeling. PLoS Comput Biol. 2019;15:e1007219.
  • Kontou PI, Pavlopoulou A, Bagos PG. Methods of analysis and meta-analysis for identifying differentially expressed genes. Methods Mol Biol. 2018;1793:183-210.
  • Zhao H, Wu L, Yan G, Chen Y, Zhou M, Wu Y et al. Inflammation and tumor progression: signaling pathways and targeted intervention. Signal Transduct Target Ther. 2021;6:263.
  • Ben-Baruch A. Tumor Necrosis Factor alpha: Taking a Personalized Road in Cancer Therapy. Front Immunol. 2022;13:903679.
  • Rappaport N, Twik M, Plaschkes I, Nudel R, Iny Stein T, Levitt J et al. MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search. Nucleic Acids Res. 2017;45:D877-D87.
  • De Angelis R, Iezzi S, Bruno T, Corbi N, Di Padova M, Floridi A et al. Functional interaction of the subunit 3 of RNA polymerase II (RPB3) with transcription factor-4 (ATF4). FEBS Lett. 2003;547:15-9.
  • Thiffault I, Wolf NI, Forget D, Guerrero K, Tran LT, Choquet K et al. Recessive mutations in POLR1C cause a leukodystrophy by impairing biogenesis of RNA polymerase III. Nat Commun. 2015;6:7623.
  • Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ. Jalview Version 2--a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189-91.
  • National Cancer Institute. https://www.cancer.gov/news-events/press-releases/2020 (accessed on 7 June 2021) (accessed June 7, 2021.
  • Trigos AS, Pearson RB, Papenfuss AT, Goode DL. How the evolution of multicellularity set the stage for cancer. Br J Cancer. 2018;118:145-52.
  • Domazet-Loso T, Brajkovic J, Tautz D. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends Genet. 2007;23:533-9.
  • Lang BF, O'Kelly C, Nerad T, Gray MW, Burger G. The closest unicellular relatives of animals. Curr Biol. 2002;12:1773-8.
  • King N, Westbrook MJ, Young SL, Kuo A, Abedin M, Chapman J et al. The genome of the choanoflagellate Monosiga brevicollis and the origin of metazoans. Nature. 2008;451:783-8.
  • Harris EH. Chlamydomonas as a model organism. Annu Rev Plant Physiol Plant Mol Biol. 2001;52:363-406.
  • Vanderwaeren L, Dok R, Voordeckers K, Nuyts S, Verstrepen KJ. Saccharomyces cerevisiae as a model system for eukaryotic cell biology, from cell cycle control to dna damage response. Int J Mol Sci. 2022;23.
  • Vyas A, Freitas AV, Ralston ZA, Tang Z. Fission yeast schizosaccharomyces pombe: a unicellular "micromammal" model organism. Curr Protoc. 2021;1:e151.
  • Nagy LG, Varga T, Csernetics Á, Virágh M. Fungi took a unique evolutionary route to multicellularity: Seven key challenges for fungal multicellular life. Fungal Biology Reviews. 2020;34:151-69.
  • Torruella G, de Mendoza A, Grau-Bove X, Anto M, Chaplin MA, del Campo J et al. Phylogenomics reveals convergent evolution of lifestyles in close relatives of animals and fungi. Curr Biol. 2015;25:2404-10.
  • Bertile F, Matallana-Surget S, Tholey A, Cristobal S, Armengaud J. Diversifying the concept of model organisms in the age of -omics. Commun Biol. 2023;6:1062.
  • Yum S, Woo S, Lee A, Won H, Kim J. Hydra, a candidate for an alternative model in environmental genomics. Mol Cell Toxicol. 2014;10:339–46.
  • Cetkovic H, Halasz M, Herak Bosnar M. Sponges: A reservoir of genes implicated in human cancer. Mar Drugs. 2018;16:20
There are 44 citations in total.

Details

Primary Language English
Subjects Cancer Cell Biology
Journal Section Research
Authors

Yağmur Kafali 0009-0009-3395-1084

Athanasia Pavlopoulou 0000-0002-0815-3808

Publication Date December 30, 2024
Submission Date June 27, 2024
Acceptance Date October 23, 2024
Published in Issue Year 2024 Volume: 49 Issue: 4

Cite

MLA Kafali, Yağmur and Athanasia Pavlopoulou. “From Hydra to Human: In Silico Investigation of the Atavistic Model of Cancer”. Cukurova Medical Journal, vol. 49, no. 4, 2024, pp. 863-80, doi:10.17826/cumj.1505761.