Open Access
Issue
BIO Web Conf.
Volume 233, 2026
9th International Conference on Advances in Biosciences and Biotechnology: Emerging Innovations in Biomedical and Bioengineering Sciences (ICABB 2026)
Article Number 01016
Number of page(s) 17
Section Biomedical and Health Innovations
DOI https://doi.org/10.1051/bioconf/202623301016
Published online 23 April 2026
  • Filho, A.M., Laversanne, M., Ferlay, J., Colombet, M., Pineros, M., Znaor, A. and Bray, F. (2025). The GLOBOCAN 2022 cancer estimates: Data sources, methods, and a snapshot of the cancer burden worldwide. International Journal of Cancer, 156(7), 1336–1346. [Google Scholar]
  • Zhang, R., Siu, M.K., Ngan, H.Y. and Chan, K.K. (2022). Molecular biomarkers for the early detection of ovarian cancer. International Journal of Molecular Sciences, 23(19), 12041. [Google Scholar]
  • Sudo, T. (2012). Molecular-targeted therapies for ovarian cancer: Prospects for the future. International Journal of Clinical Oncology, 17, 424–429. [Google Scholar]
  • Ohshima, K. and Morii, E. (2021). Metabolic reprogramming of cancer cells during tumor progression and metastasis. Metabolites, 11(1), 28. [Google Scholar]
  • Mir, R., Javid, J., Ullah, M.F., Alrdahe, S., Altedlawi, I.A., Mustafa, S.K. and Tayeb, F.J. (2025). Metabolic reprogramming and functional crosstalk within the tumor microenvironment (TME) and a multi-omics anticancer approach. Medical Oncology, 42(9), 373. [Google Scholar]
  • Emmings, E., Mullany, S., Chang, Z., Landen Jr, C.N., Linder, S. and Bazzaro, M. (2019). Targeting mitochondria for treatment of chemoresistant ovarian cancer. International Journal of Molecular Sciences, 20(1), 229. [Google Scholar]
  • Roth, K.G., Mambetsariev, I., Kulkarni, P. and Salgia, R. (2020). The mitochondrion as an emerging therapeutic target in cancer. Trends in Molecular Medicine, 26(1), 119–134. [Google Scholar]
  • Koc, Z.C., Sollars, V.E., Bou Zgheib, N., Rankin, G.O. and Koc, E.C. (2023). Evaluation of mitochondrial biogenesis and ROS generation in high-grade serous ovarian cancer. Frontiers in Oncology, 13, 1129352. [Google Scholar]
  • Tomar, M.S., Kumar, A. and Shrivastava, A. (2024). Mitochondrial metabolism as a dynamic regulatory hub to malignant transformation and anti-cancer drug resistance. Biochemical and Biophysical Research Communications, 694, 149382. [Google Scholar]
  • Sokolov, D. and Sullivan, L.B. (2025). Mitochondria, OXPHOS, and cancer progression: A modular view. Annual Review of Cancer Biology, 10. [Google Scholar]
  • Edgar, R., Domrachev, M. and Lash, A.E. (2002). Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Research, 30(1), 207–210. [Google Scholar]
  • Milacic, M., Beavers, D., Conley, P., Gong, C., Gillespie, M., Griss, J., Haw, R., Jassal, B., Matthews, L., May, B., Petryszak, R., Ragueneau, E., Rothfels, K., Sevilla, C., Shamovsky, V., Stephan, R., Tiwari, K., Varusai, T., Weiser, J., Wright, A., Wu, G., Stein, L., Hermjakob, H. and D’Eustachio, P. (2024). The Reactome pathway knowledgebase 2024. Nucleic Acids Research. [Google Scholar]
  • Kanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. and Ishiguro-Watanabe, M. (2025). KEGG: Biological systems database as a model of the real world. Nucleic Acids Research, 53, D672–D677. [Google Scholar]
  • Szklarczyk, D., Nastou, K., Koutrouli, M., Kirsch, R., Mehryary, F., Hachilif, R., Hu, D., Peluso, M.E., Huang, Q., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J. and von Mering, C. (2025). The STRING database in 2025: protein networks with directionality of regulation. Nucleic Acids Research, 53(D1), D730–D737. [Google Scholar]
  • Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. and Ideker, T. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498–2504. [Google Scholar]
  • Reim and, J., Kull, M., Peterson, H., Hansen, J. and Vilo, J. (2007). g: Profiler—A web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Research, 35(Web Server issue), W193. [Google Scholar]
  • Sherman, B.T., Hao, M., Qiu, J., Jiao, X., Baseler, M.W., Lane, H.C., Imamichi, T. and Chang, W. (2022). DAVID: A web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research, 50(W1), W216–W221. [Google Scholar]
  • Ge, S.X., Jung, D. and Yao, R. (2020). ShinyGO: A graphical gene-set enrichment tool for animals and plants. Bioinformatics, 36(8), 2628–2629. [Google Scholar]
  • Hirst, J. (2013). Mitochondrial complex I. Annual Review of Biochemistry, 82(1), 551–575. [Google Scholar]
  • Sazanov, L.A. (2015). A giant molecular proton pump: Structure and mechanism of respiratory complex I. Nature Reviews Molecular Cell Biology, 16(6), 375–388. [Google Scholar]
  • Vinothkumar, K.R., Zhu, J. and Hirst, J. (2014). Architecture of mammalian respiratory complex I. Nature, 515(7525), 80–84. [Google Scholar]
  • Rutter, J., Winge, D.R. and Schiffman, J.D. (2010). Succinate dehydrogenase—Assembly, regulation and role in human disease. Mitochondrion, 10(4), 393–401. [Google Scholar]
  • Briere, J.J., Favier, J., Ghouzzi, V.E., Djouadi, F., Benit, P., Gimenez, A.P. and Rustin, P (2005). Succinate dehydrogenase deficiency in human. Cellular and Molecular Life Sciences, 62(19), 2317–2324. [Google Scholar]
  • Yu, C.A., Xia, D., Kim, H., Deisenhofer, J., Zhang, L., Kachurin, A.M. and Yu, L. (1998). Structural basis of functions of the mitochondrial cytochrome bc1 complex. Biochimica et Biophysica Acta - Bioenergetics, 1365(1-2), 151–158. [Google Scholar]
  • Chen, Q., Vazquez, E.J., Moghaddas, S., Hoppel, C.L. and Lesnefsky, E.J. (2003). Production of reactive oxygen species by mitochondria: Central role of complex III. Journal of Biological Chemistry, 278(38), 3602736031. [Google Scholar]
  • Liberti, M.V. and Locasale, J.W. (2016). The Warburg effect: How does it benefit cancer cells? Trends in Biochemical Sciences, 41(3), 211–218. [Google Scholar]
  • Sirover, M.A. (2011). On the functional diversity of glyceraldehyde-3-phosphate dehydrogenase: Biochemical mechanisms and regulatory control. Biochimica et Biophysica Acta - General Subjects, 1810(8), 741–751. [Google Scholar]
  • Sorgato, M.C., Lippe, G., Seren, S. and Ferguson, S.J. (1985). Partial uncoupling or inhibition of electron transport rate have equivalent effects on the relationship between the rate of ATP synthesis and proton-motive force in submitochondrial particles. FEBS Letters, 181(2), 323–327. [Google Scholar]
  • Bagkos, G., Koufopoulos, K. and Piperi, C. (2014). ATP synthesis revisited: New avenues for the management of mitochondrial diseases. Current Pharmaceutical Design, 20(28), 4570–4579. [Google Scholar]
  • Xu, X.M. and Møller, S.G. (2011). Iron-sulfur clusters: Biogenesis, molecular mechanisms, and their functional significance. Antioxidants & Redox Signaling, 15(1), 271–307. [Google Scholar]
  • Stiban, J., So, M. and Kaguni, L.S. (2016). Iron-sulfur clusters in mitochondrial metabolism: Multifaceted roles of a simple cofactor. Biochemistry (Moscow), 81(10), 1066–1080. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.