Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Chemicals and Reagents
2.2. Cells and Cell Culture
2.3. Genetic Manipulations
2.4. Metastatic Take in Mice
2.5. Cell Migration and Invasion
2.6. Cell Numbers
2.7. Metabolic Assays
2.8. Electron Microscopy
2.9. Mitochondrial Abundance and Mitochondrial DNA Content
2.10. Microarray Database Analysis
2.11. Real-Time Quantitative PCR
2.12. Western Blotting
2.13. Immunohistochemistry
2.14. Clinical Database Analysis
2.15. Statistics
3. Results
3.1. Validation of Brain-Seeking Variant Models Derived from Human MDA-MB-231 Triple-Negative Breast Cancer Cells
3.2. Brain-Seeking Variants of MDA-MB-231 Cells Undergo an Oxidative Switch
3.3. Identification of Four Candidate Metabolic Genes That Could Account for the Brain Tropism of Human Breast Cancer Cells
3.4. Cytochrome c Oxidase Subunit 7b in Mitochondrial Complex IV Is a Candidate Protein Supporting the Brain Tropism of Human Breast Cancer Cells
3.5. Cox7b Expression Drives Human Breast Cancer Cell Migration towards Astrocytes
3.6. Cox7b Expression Promotes the Oxidative Phenotype of Human Metastatic Breast Cancer Cells
3.7. Cox7b Expression Is Responsible for the Brain Tropism of Metastatic Human Breast Cancer Cells in Mice
4. Discussion
5. Conclusions
6. Patent
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix A.1. Cell Infection for Constitutive Luciferase and GFP Expression
Appendix A.2. COX7B Gene Silencing
Appendix A.3. Cox7b Overexpression
Appendix A.4. Cell Migration and Invasion
Appendix A.5. Seahorse Oximetry
References
- Weiss, F.; Lauffenburger, D.; Friedl, P. Towards targeting of shared mechanisms of cancer metastasis and therapy resistance. Nat. Rev. Cancer 2022, 22, 157–173. [Google Scholar] [CrossRef] [PubMed]
- Seoane, J.; De Mattos-Arruda, L. Brain metastasis: New opportunities to tackle therapeutic resistance. Mol. Oncol. 2014, 8, 1120–1131. [Google Scholar] [CrossRef] [PubMed]
- Kuksis, M.; Gao, Y.; Tran, W.; Hoey, C.; Kiss, A.; Komorowski, A.S.; Dhaliwal, A.J.; Sahgal, A.; Das, S.; Chan, K.K.; et al. The incidence of brain metastases among patients with metastatic breast cancer: A systematic review and meta-analysis. Neuro. Oncol. 2021, 23, 894–904. [Google Scholar] [CrossRef] [PubMed]
- Dent, R.; Trudeau, M.; Pritchard, K.I.; Hanna, W.M.; Kahn, H.K.; Sawka, C.A.; Lickley, L.A.; Rawlinson, E.; Sun, P.; Narod, S.A. Triple-negative breast cancer: Clinical features and patterns of recurrence. Clin. Cancer. Res. 2007, 13, 4429–4434. [Google Scholar] [CrossRef]
- Hugo, H.S.; Cortes, J.; Cescon, D.W.; Im, S.; Md Yusof, M.; Gallardo, C.; Lipatov, O.; Barrios, C.H.; Perez-Garcia, J.; Iwata, H.; et al. KEYNOTE-355: Final results from a randomized, double-blind phase III study of first-line pembrolizumab + chemotherapy vs placebo + chemotherapy for metastatic TNBC. Annals Oncol. 2021, 32 (Suppl. 5), S1283–S1346. [Google Scholar]
- Gennari, A.; Stockler, M.; Puntoni, M.; Sormani, M.; Nanni, O.; Amadori, D.; Wilcken, N.; D’Amico, M.; DeCensi, A.; Bruzzi, P. Duration of chemotherapy for metastatic breast cancer: A systematic review and meta-analysis of randomized clinical trials. J. Clin. Oncol. 2011, 29, 2144–2149. [Google Scholar] [CrossRef]
- Damsky, W.E.; Rosenbaum, L.E.; Bosenberg, M. Decoding melanoma metastasis. Cancers 2010, 3, 126–163. [Google Scholar] [CrossRef]
- Blecker, D.; Abraham, S.; Furth, E.E.; Kochman, M.L. Melanoma in the gastrointestinal tract. Am. J. Gastroenterol. 1999, 94, 3427–3433. [Google Scholar] [CrossRef]
- Tas, F. Metastatic behavior in melanoma: Timing, pattern, survival, and influencing factors. J. Oncol. 2012, 2012, 647684. [Google Scholar] [CrossRef]
- Lin, N.U.; Claus, E.; Sohl, J.; Razzak, A.R.; Arnaout, A.; Winer, E.P. Sites of distant recurrence and clinical outcomes in patients with metastatic triple-negative breast cancer: High incidence of central nervous system metastases. Cancer 2008, 113, 2638–2645. [Google Scholar] [CrossRef]
- Jin, J.; Gao, Y.; Zhang, J.; Wang, L.; Wang, B.; Cao, J.; Shao, Z.; Wang, Z. Incidence, pattern and prognosis of brain metastases in patients with metastatic triple negative breast cancer. BMC Cancer 2018, 18, 446. [Google Scholar] [CrossRef] [Green Version]
- Patrawala, L.; Calhoun, T.; Schneider-Broussard, R.; Li, H.; Bhatia, B.; Tang, S.; Reilly, J.G.; Chandra, D.; Zhou, J.; Claypool, K.; et al. Highly purified CD44+ prostate cancer cells from xenograft human tumors are enriched in tumorigenic and metastatic progenitor cells. Oncogene 2006, 25, 1696–1708. [Google Scholar] [CrossRef] [PubMed]
- Capeloa, T.; Krzystyniak, J.; d’Hose, D.; Canas Rodriguez, A.; Payen, V.L.; Zampieri, L.X.; Van de Velde, J.A.; Benyahia, Z.; Pranzini, E.; Vazeille, T.; et al. MitoQ inhibits human breast cancer cell migration, invasion and clonogenicity. Cancers 2022, 14, 1516. [Google Scholar] [CrossRef] [PubMed]
- Paget, S. The distribution of secondary growths in cancer of the breast. Cancer Metastasis Rev. 1889, 8, 98–101. [Google Scholar] [CrossRef]
- Ribelles, N.; Santonja, A.; Pajares, B.; Llacer, C.; Alba, E. The seed and soil hypothesis revisited: Current state of knowledge of inherited genes on prognosis in breast cancer. Cancer Treat. Rev. 2014, 40, 293–299. [Google Scholar] [CrossRef] [PubMed]
- Jang, A.; Hill, R.P. An examination of the effects of hypoxia, acidosis, and glucose starvation on the expression of metastasis-associated genes in murine tumor cells. Clin. Exp. Metastasis 1997, 15, 469–483. [Google Scholar] [CrossRef]
- Vaupel, P. The role of hypoxia-induced factors in tumor progression. Oncologist 2004, 9 (Suppl. 5), 10–17. [Google Scholar] [CrossRef]
- Lunt, S.J.; Chaudary, N.; Hill, R.P. The tumor microenvironment and metastatic disease. Clin. Exp. Metastasis 2009, 26, 19–34. [Google Scholar] [CrossRef]
- Gilkes, D.M.; Semenza, G.L.; Wirtz, D. Hypoxia and the extracellular matrix: Drivers of tumour metastasis. Nat. Rev. Cancer 2014, 14, 430–439. [Google Scholar] [CrossRef]
- Rankin, E.B.; Giaccia, A.J. Hypoxic control of metastasis. Science 2016, 352, 175–180. [Google Scholar] [CrossRef]
- Payen, V.L.; Porporato, P.E.; Baselet, B.; Sonveaux, P. Metabolic changes associated with tumor metastasis, part 1: Tumor pH, glycolysis and the pentose phosphate pathway. Cell. Mol. Life Sci. 2016, 73, 1333–1348. [Google Scholar] [CrossRef] [PubMed]
- Porporato, P.E.; Payen, V.L.; Baselet, B.; Sonveaux, P. Metabolic changes associated with tumor metastasis, part 2: Mitochondria, lipid and amino acid metabolism. Cell. Mol. Life Sci. 2016, 73, 1349–1363. [Google Scholar] [CrossRef] [PubMed]
- DeClerck, K.; Elble, R.C. The role of hypoxia and acidosis in promoting metastasis and resistance to chemotherapy. Front. Biosci. 2010, 15, 213–225. [Google Scholar] [CrossRef] [PubMed]
- Pietila, M.; Ivaska, J.; Mani, S.A. Whom to blame for metastasis, the epithelial-mesenchymal transition or the tumor microenvironment? Cancer Lett. 2016, 380, 359–368. [Google Scholar] [CrossRef]
- Klein, C.A. Selection and adaptation during metastatic cancer progression. Nature 2013, 501, 365–372. [Google Scholar] [CrossRef]
- Gupta, G.P.; Massague, J. Cancer metastasis: Building a framework. Cell 2006, 127, 679–695. [Google Scholar] [CrossRef]
- Kaplan, R.N.; Riba, R.D.; Zacharoulis, S.; Bramley, A.H.; Vincent, L.; Costa, C.; MacDonald, D.D.; Jin, D.K.; Shido, K.; Kerns, S.A.; et al. VEGFR1-positive haematopoietic bone marrow progenitors initiate the pre-metastatic niche. Nature 2005, 438, 820–827. [Google Scholar] [CrossRef]
- Peinado, H.; Zhang, H.; Matei, I.R.; Costa-Silva, B.; Hoshino, A.; Rodrigues, G.; Psaila, B.; Kaplan, R.N.; Bromberg, J.F.; Kang, Y.; et al. Pre-metastatic niches: Organ-specific homes for metastases. Nat. Rev. Cancer 2017, 17, 302–317. [Google Scholar] [CrossRef]
- Laubli, H.; Borsig, L. Selectins promote tumor metastasis. Semin. Cancer Biol. 2010, 20, 169–177. [Google Scholar] [CrossRef]
- Sevenich, L.; Bowman, R.L.; Mason, S.D.; Quail, D.F.; Rapaport, F.; Elie, B.T.; Brogi, E.; Brastianos, P.K.; Hahn, W.C.; Holsinger, L.J.; et al. Analysis of tumour- and stroma-supplied proteolytic networks reveals a brain-metastasis-promoting role for cathepsin S. Nat. Cell Biol. 2014, 16, 876–888. [Google Scholar] [CrossRef]
- Porporato, P.E.; Payen, V.L.; Perez-Escuredo, J.; De Saedeleer, C.J.; Danhier, P.; Copetti, T.; Dhup, S.; Tardy, M.; Vazeille, T.; Bouzin, C.; et al. A mitochondrial switch promotes tumor metastasis. Cell Rep. 2014, 8, 754–766. [Google Scholar] [CrossRef] [Green Version]
- Capeloa, T.; Krzystyniak, J.; Canas Rodriguez, A.; Payen, V.L.; Zampieri, L.X.; Pranzini, E.; Derouane, F.; Vazeille, T.; Bouzin, C.; Duhoux, F.P.; et al. MitoQ prevents human breast cancer recurrence and lung metastasis in mice. Cancers 2022, 14, 1488. [Google Scholar] [CrossRef] [PubMed]
- Ishikawa, K.; Takenaga, K.; Akimoto, M.; Koshikawa, N.; Yamaguchi, A.; Imanishi, H.; Nakada, K.; Honma, Y.; Hayashi, J. ROS-generating mitochondrial DNA mutations can regulate tumor cell metastasis. Science 2008, 320, 661–664. [Google Scholar] [CrossRef] [PubMed]
- Yoneda, T.; Williams, P.J.; Hiraga, T.; Niewolna, M.; Nishimura, R. A bone-seeking clone exhibits different biological properties from the MDA-MB-231 parental human breast cancer cells and a brain-seeking clone in vivo and in vitro. J. Bone Miner. Res. 2001, 16, 1486–1495. [Google Scholar] [CrossRef] [PubMed]
- Patel, J.B.; Appaiah, H.N.; Burnett, R.M.; Bhat-Nakshatri, P.; Wang, G.; Mehta, R.; Badve, S.; Thomson, M.J.; Hammond, S.; Steeg, P.; et al. Control of EVI-1 oncogene expression in metastatic breast cancer cells through microRNA miR-22. Oncogene 2011, 30, 1290–1301. [Google Scholar] [CrossRef] [PubMed]
- Burnett, R.M.; Craven, K.E.; Krishnamurthy, P.; Goswami, C.P.; Badve, S.; Crooks, P.; Mathews, W.P.; Bhat-Nakshatri, P.; Nakshatri, H. Organ-specific adaptive signaling pathway activation in metastatic breast cancer cells. Oncotarget 2015, 6, 12682–12696. [Google Scholar] [CrossRef]
- Ran, F.A.; Hsu, P.D.; Wright, J.; Agarwala, V.; Scott, D.A.; Zhang, F. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 2013, 8, 2281–2308. [Google Scholar] [CrossRef]
- Piret, J.P.; Vankoningsloo, S.; Mejia, J.; Noel, F.; Boilan, E.; Lambinon, F.; Zouboulis, C.C.; Masereel, B.; Lucas, S.; Saout, C.; et al. Differential toxicity of copper (II) oxide nanoparticles of similar hydrodynamic diameter on human differentiated intestinal Caco-2 cell monolayers is correlated in part to copper release and shape. Nanotoxicology 2012, 6, 789–803. [Google Scholar] [CrossRef]
- Grasso, D.; Medeiros, H.C.D.; Zampieri, L.X.; Bol, V.; Danhier, P.; van Gisbergen, M.W.; Bouzin, C.; Brusa, D.; Gregoire, V.; Smeets, H.; et al. Fitter mitochondria are associated with radioresistance in human head and neck SQD9 cancer cells. Front. Pharmacol. 2020, 11, 263. [Google Scholar] [CrossRef]
- Li, H.; Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25, 1754–1760. [Google Scholar] [CrossRef]
- Van Hee, V.F.; Perez-Escuredo, J.; Cacace, A.; Copetti, T.; Sonveaux, P. Lactate does not activate NF-kappaB in oxidative tumor cells. Front. Pharmacol. 2015, 6, 228. [Google Scholar] [CrossRef] [Green Version]
- Bankhead, P.; Loughrey, M.B.; Fernandez, J.A.; Dombrowski, Y.; McArt, D.G.; Dunne, P.D.; McQuaid, S.; Gray, R.T.; Murray, L.J.; Coleman, H.G.; et al. QuPath: Open source software for digital pathology image analysis. Sci. Rep. 2017, 7, 16878. [Google Scholar] [CrossRef] [PubMed]
- Gyorffy, B. Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer. Comput. Struct. Biotechnol. J. 2021, 19, 4101–4109. [Google Scholar] [CrossRef] [PubMed]
- Vaz, F.M.; Fouchier, S.W.; Ofman, R.; Sommer, M.; Wanders, R.J. Molecular and biochemical characterization of rat gamma-trimethylaminobutyraldehyde dehydrogenase and evidence for the involvement of human aldehyde dehydrogenase 9 in carnitine biosynthesis. J. Biol. Chem. 2000, 275, 7390–7394. [Google Scholar] [CrossRef] [PubMed]
- Zhao, D.; McCaffery, P.; Ivins, K.J.; Neve, R.L.; Hogan, P.; Chin, W.W.; Drager, U.C. Molecular identification of a major retinoic-acid-synthesizing enzyme, a retinaldehyde-specific dehydrogenase. Eur. J. Biochem. 1996, 240, 15–22. [Google Scholar] [CrossRef]
- Schmidt, C.; Sciacovelli, M.; Frezza, C. Fumarate hydratase in cancer: A multifaceted tumour suppressor. Semin. Cell. Dev. Biol. 2020, 98, 15–25. [Google Scholar] [CrossRef]
- Zhu, J.; Vinothkumar, K.R.; Hirst, J. Structure of mammalian respiratory complex I. Nature 2016, 536, 354–358. [Google Scholar] [CrossRef]
- Kadenbach, B.; Huttemann, M. The subunit composition and function of mammalian cytochrome c oxidase. Mitochondrion 2015, 24, 64–76. [Google Scholar] [CrossRef]
- Tsukihara, T.; Aoyama, H.; Yamashita, E.; Tomizaki, T.; Yamaguchi, H.; Shinzawa-Itoh, K.; Nakashima, R.; Yaono, R.; Yoshikawa, S. The whole structure of the 13-subunit oxidized cytochrome c oxidase at 2.8 A. Science 1996, 272, 1136–1144. [Google Scholar] [CrossRef]
- Nakhjavani, M.; Samarasinghe, R.M.; Shigdar, S. Triple-negative breast cancer brain metastasis: An update on druggable targets, current clinical trials, and future treatment options. Drug Discov. Today 2022, 27, 1298–1314. [Google Scholar] [CrossRef]
- Kadenbach, B.; Jarausch, J.; Hartmann, R.; Merle, P. Separation of mammalian cytochrome c oxidase into 13 polypeptides by a sodium dodecyl sulfate-gel electrophoretic procedure. Anal. Biochem. 1983, 129, 517–521. [Google Scholar] [CrossRef]
- Kuhn-Nentwig, L.; Kadenbach, B. Immunological identification of four different polypeptides in ’subunit VII’ of mammalian cytochrome c oxidase. FEBS Lett. 1984, 172, 189–192. [Google Scholar] [CrossRef]
- Cunatova, K.; Reguera, D.P.; Houstek, J.; Mracek, T.; Pecina, P. Role of cytochrome c oxidase nuclear-encoded subunits in health and disease. Physiol. Res. 2020, 69, 947–965. [Google Scholar] [CrossRef] [PubMed]
- Indrieri, A.; van Rahden, V.A.; Tiranti, V.; Morleo, M.; Iaconis, D.; Tammaro, R.; D’Amato, I.; Conte, I.; Maystadt, I.; Demuth, S.; et al. Mutations in COX7B cause microphthalmia with linear skin lesions, an unconventional mitochondrial disease. Am. J. Hum. Genet. 2012, 91, 942–949. [Google Scholar] [CrossRef] [PubMed]
- Jolly, M.K.; Ware, K.E.; Gilja, S.; Somarelli, J.A.; Levine, H. EMT and MET: Necessary or permissive for metastasis? Mol. Oncol. 2017, 11, 755–769. [Google Scholar] [CrossRef] [PubMed]
- Perez-Escuredo, J.; Van Hee, V.F.; Sboarina, M.; Falces, J.; Payen, V.L.; Pellerin, L.; Sonveaux, P. Monocarboxylate transporters in the brain and in cancer. Biochim. Biophys. Acta. 2016, 1863, 2481–2497. [Google Scholar] [CrossRef]
- Mashimo, T.; Pichumani, K.; Vemireddy, V.; Hatanpaa, K.J.; Singh, D.K.; Sirasanagandla, S.; Nannepaga, S.; Piccirillo, S.G.; Kovacs, Z.; Foong, C.; et al. Acetate is a bioenergetic substrate for human glioblastoma and brain metastases. Cell 2014, 159, 1603–1614. [Google Scholar] [CrossRef]
- Bergers, G.; Fendt, S.M. The metabolism of cancer cells during metastasis. Nat. Rev. Cancer 2021, 21, 162–180. [Google Scholar] [CrossRef]
- Martin, A.M.; Cagney, D.N.; Catalano, P.J.; Warren, L.E.; Bellon, J.R.; Punglia, R.S.; Claus, E.B.; Lee, E.Q.; Wen, P.Y.; Haas-Kogan, D.A.; et al. Brain metastases in newly diagnosed breast cancer: A population-based study. JAMA Oncol. 2017, 3, 1069–1077. [Google Scholar] [CrossRef]
- O’Reilly, D.; Sendi, M.A.; Kelly, C.M. Overview of recent advances in metastatic triple negative breast cancer. World J. Clin. Oncol. 2021, 12, 164–182. [Google Scholar] [CrossRef]
- Wang, C.; Luo, D. The metabolic adaptation mechanism of metastatic organotropism. Exp. Hematol. Oncol 2021, 10, 30. [Google Scholar] [CrossRef] [PubMed]
- Tanaka, N.; Katayama, S.; Reddy, A.; Nishimura, K.; Niwa, N.; Hongo, H.; Ogihara, K.; Kosaka, T.; Mizuno, R.; Kikuchi, E.; et al. Single-cell RNA-seq analysis reveals the platinum resistance gene COX7B and the surrogate marker CD63. Cancer Med. 2018, 7, 6193–6204. [Google Scholar] [CrossRef] [PubMed]
- Cong, L.; Ran, F.A.; Cox, D.; Lin, S.; Barretto, R.; Habib, N.; Hsu, P.D.; Wu, X.; Jiang, W.; Marraffini, L.A.; et al. Multiplex genome engineering using CRISPR/Cas systems. Science 2013, 339, 819–823. [Google Scholar] [CrossRef] [PubMed]
- Chu, V.T.; Weber, T.; Wefers, B.; Wurst, W.; Sander, S.; Rajewsky, K.; Kuhn, R. Increasing the efficiency of homology-directed repair for CRISPR-Cas9-induced precise gene editing in mammalian cells. Nat. Biotechnol. 2015, 33, 543–548. [Google Scholar] [CrossRef]
- Sanjana, N.E.; Shalem, O.; Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 2014, 11, 783–784. [Google Scholar] [CrossRef]
- Engler, C.; Kandzia, R.; Marillonnet, S. A one pot, one step, precision cloning method with high throughput capability. PLoS ONE 2008, 3, e3647. [Google Scholar] [CrossRef] [Green Version]
Gene ID | 231-BR (Brain-Seeking) | ADMD-231 (Adrenal-Glands-Seeking) | BMD-231 (Bone-Seeking) | LMD-231 (Lung-Seeking) | p4 | p5 |
---|---|---|---|---|---|---|
HK21 | 1.622,3 | 1.83 | 1.66 | 1.70 | >0.05 | >0.05 |
ALDH1A3 | 1.18 | 1.53 | 1.43 | 1.48 | <0.05 | >0.05 |
ALDH9A1 | 1.55 | 1.04 | 1.07 | 1.09 | >0.05 | <0.05 |
ALDH3A1 | 1.18 | 1.03 | 1.21 | 1.16 | >0.05 | >0.05 |
PCK2 | 1.08 | −1.43 | −1.21 | −1.33 | <0.05 | <0.05 |
IDH1 | −1.18 | −1.31 | −1.13 | −1.14 | >0.05 | >0.05 |
FH | 1.54 | 1.08 | 1.04 | 1.11 | >0.05 | <0.05 |
MDH2 | −1.10 | −1.19 | −1.17 | −1.27 | >0.05 | >0.05 |
ATP5I | 1.25 | 1.36 | 1.33 | 1.33 | >0.05 | >0.05 |
ATP5G2 | −1.06 | −1.21 | −1.07 | −1.11 | >0.05 | >0.05 |
ATP6V0E2 | 1.62 | 1.43 | 1.41 | 1.34 | >0.05 | >0.05 |
ATP6V1D | 1.69 | 2.45 | 1.83 | 1.96 | >0.05 | >0.05 |
ATP6V0D1 | −1.02 | −1.23 | −1.14 | −1.11 | >0.05 | >0.05 |
ATP6V0D2 | 1.21 | 1.08 | 1.03 | 1.20 | >0.05 | >0.05 |
ATP6V1B1 | 1.25 | −1.09 | −1.07 | 1.03 | <0.05 | <0.05 |
COX17 | −1.47 | −1.46 | −1.50 | −1.52 | >0.05 | >0.05 |
COX7B | 2.02 | 1.06 | −1.06 | −1.20 | <0.05 | <0.05 |
NDUFB7 | 1.45 | 1.54 | 1.27 | 1.21 | >0.05 | >0.05 |
NDUFB8 | −1.43 | 1.46 | 1.45 | 1.54 | <0.05 | <0.05 |
NDUFV3 | 1.10 | 1.51 | 1.42 | 1.37 | >0.05 | >0.05 |
UQCRB | 1.31 | 1.05 | 1.27 | 1.30 | >0.05 | >0.05 |
PGM5 | −1.11 | 6.42 | 4.32 | 4.51 | <0.05 | <0.05 |
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Blackman, M.C.N.M.; Capeloa, T.; Rondeau, J.D.; Zampieri, L.X.; Benyahia, Z.; Van de Velde, J.A.; Fransolet, M.; Daskalopoulos, E.P.; Michiels, C.; Beauloye, C.; et al. Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells. Cancers 2022, 14, 4371. https://doi.org/10.3390/cancers14184371
Blackman MCNM, Capeloa T, Rondeau JD, Zampieri LX, Benyahia Z, Van de Velde JA, Fransolet M, Daskalopoulos EP, Michiels C, Beauloye C, et al. Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells. Cancers. 2022; 14(18):4371. https://doi.org/10.3390/cancers14184371
Chicago/Turabian StyleBlackman, Marine C. N. M., Tania Capeloa, Justin D. Rondeau, Luca X. Zampieri, Zohra Benyahia, Justine A. Van de Velde, Maude Fransolet, Evangelos P. Daskalopoulos, Carine Michiels, Christophe Beauloye, and et al. 2022. "Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells" Cancers 14, no. 18: 4371. https://doi.org/10.3390/cancers14184371
APA StyleBlackman, M. C. N. M., Capeloa, T., Rondeau, J. D., Zampieri, L. X., Benyahia, Z., Van de Velde, J. A., Fransolet, M., Daskalopoulos, E. P., Michiels, C., Beauloye, C., & Sonveaux, P. (2022). Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells. Cancers, 14(18), 4371. https://doi.org/10.3390/cancers14184371