Cancer Genetics and Clinical Research
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Conflicts of Interest
References
- Weinberg, R.A. Oncogenes, antioncogenes, and the molecular bases of multistep carcinogenesis. Cancer Res. 1989, 49, 3713–3721. [Google Scholar]
- Wishart, D. Metabolomics and the Multi-Omics View of Cancer. Metabolites 2022, 12, 154. [Google Scholar] [CrossRef]
- Golub, T.R.; Slonim, D.K.; Tamayo, P.; Huard, C.; Gaasenbeek, M.; Mesirov, J.P.; Coller, H.; Loh, M.L.; Downing, J.R.; Caligiuri, M.A.; et al. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 1999, 286, 531–537. [Google Scholar] [CrossRef] [Green Version]
- Bignell, G.R.; Huang, J.; Greshock, J.; Watt, S.; Butler, A.; West, S.; Grigorova, M.; Jones, K.W.; Wei, W.; Stratton, M.R.; et al. High-resolution analysis of DNA copy number using oligonucleotide microarrays. Genome Res. 2004, 14, 287–295. [Google Scholar] [CrossRef] [Green Version]
- Sanger, F.; Nicklen, S.; Coulson, A.R. DNA sequencing with chain-terminating inhibitors. Proc. Natl. Acad. Sci. USA 1977, 74, 5463–5467. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mardis, E.R. A decade’s perspective on DNA sequencing technology. Nature 2011, 470, 198–203. [Google Scholar] [CrossRef] [PubMed]
- Metzker, M.L. Sequencing technologies—The next generation. Nat. Rev. Genet. 2010, 11, 31–46. [Google Scholar] [CrossRef] [Green Version]
- Ledergerber, C.; Dessimoz, C. Base-calling for next-generation sequencing platforms. Brief. Bioinform. 2011, 12, 489–497. [Google Scholar] [CrossRef] [Green Version]
- Belkadi, A.; Bolze, A.; Itan, Y.; Cobat, A.; Vincent, Q.B.; Antipenko, A.; Shang, L.; Boisson, B.; Casanova, J.L.; Abel, L. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc. Natl. Acad. Sci. USA 2015, 112, 5473–5478. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stratton, M.R.; Campbell, P.J.; Futreal, P.A. The cancer genome. Nature 2009, 458, 719–724. [Google Scholar] [CrossRef] [Green Version]
- Ishino, Y.; Shinagawa, H.; Makino, K.; Amemura, M.; Nakata, A. Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. J. Bacteriol. 1987, 169, 5429–5433. [Google Scholar] [CrossRef]
- Mojica, F.J.; Díez-Villaseñor, C.; García-Martínez, J.; Soria, E. Intervening sequences of regularly spaced prokaryotic repeats derive from foreign genetic elements. J. Mol. Evol. 2005, 60, 174–182. [Google Scholar] [CrossRef] [PubMed]
- Vaghari-Tabari, M.; Hassanpour, P.; Sadeghsoltani, F.; Malakoti, F.; Alemi, F.; Qujeq, D.; Asemi, Z.; Yousefi, B. CRISPR/Cas9 gene editing: A new approach for overcoming drug resistance in cancer. Cell. Mol. Biol. Lett. 2022, 27, 49. [Google Scholar] [CrossRef]
- Inamura, K.; Hamada, T.; Bullman, S.; Ugai, T.; Yachida, S.; Ogino, S. Cancer as microenvironmental, systemic and environmental diseases: Opportunity for transdisciplinary microbiomics science. Gut 2022, 71, 2107–2122. [Google Scholar] [CrossRef] [PubMed]
- Niedzwiecki, M.M.; Walker, D.I.; Vermeulen, R.; Chadeau-Hyam, M.; Jones, D.P.; Miller, G.W. The Exposome: Molecules to Populations. Annu. Rev. Pharmacol. Toxicol. 2019, 59, 107–127. [Google Scholar] [CrossRef] [PubMed]
- Gonzalez-Covarrubias, V.; Martínez-Martínez, E.; Del Bosque-Plata, L. The Potential of Metabolomics in Biomedical Applications. Metabolites 2022, 12, 194. [Google Scholar] [CrossRef] [PubMed]
- Warburg, O.; Wind, F.; Negelein, E. The metabolism of tumors in the body. J. Gen. Physiol. 1927, 8, 519–530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wishart, D.S.; Tzur, D.; Knox, C.; Eisner, R.; Guo, A.C.; Young, N.; Cheng, D.; Jewell, K.; Arndt, D.; Sawhney, S.; et al. HMDB: The Human Metabolome Database. Nucleic Acids Res. 2007, 35, D521–D526. [Google Scholar] [CrossRef] [PubMed]
- Wishart, D.S.; Guo, A.; Oler, E.; Wang, F.; Anjum, A.; Peters, H.; Dizon, R.; Sayeeda, Z.; Tian, S.; Lee, B.L.; et al. HMDB 5.0: The Human Metabolome Database for 2022. Nucleic Acids Res. 2022, 50, D622–D631. [Google Scholar] [CrossRef] [PubMed]
- Gao, S.Q.; Zhao, J.H.; Guan, Y.; Tang, Y.S.; Li, Y.; Liu, L.Y. Mass spectrometry imaging technology in metabolomics: A systematic review. Biomed. Chromatogr. 2022, e5494. [Google Scholar] [CrossRef]
- Nascentes Melo, L.M.; Lesner, N.P.; Sabatier, M.; Ubellacker, J.M.; Tasdogan, A. Emerging metabolomic tools to study cancer metastasis. Trends Cancer 2022, S2405-8033, 00156-X. [Google Scholar] [CrossRef] [PubMed]
- Wishart, D.S.; Cheng, L.L.; Copié, V.; Edison, A.S.; Eghbalnia, H.R.; Hoch, J.C.; Gouveia, G.J.; Pathmasiri, W.; Powers, R.; Schock, T.B.; et al. NMR and Metabolomics-A Roadmap for the Future. Metabolites 2022, 12, 678. [Google Scholar] [CrossRef] [PubMed]
- Foulkes, W.D.; Knoppers, B.M.; Turnbull, C. Population genetic testing for cancer susceptibility: Founder mutations to genomes. Nat. Rev. Clin. Oncol. 2016, 13, 41–54. [Google Scholar] [CrossRef] [PubMed]
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Allegra, S. Cancer Genetics and Clinical Research. J. Pers. Med. 2022, 12, 1649. https://doi.org/10.3390/jpm12101649
Allegra S. Cancer Genetics and Clinical Research. Journal of Personalized Medicine. 2022; 12(10):1649. https://doi.org/10.3390/jpm12101649
Chicago/Turabian StyleAllegra, Sarah. 2022. "Cancer Genetics and Clinical Research" Journal of Personalized Medicine 12, no. 10: 1649. https://doi.org/10.3390/jpm12101649
APA StyleAllegra, S. (2022). Cancer Genetics and Clinical Research. Journal of Personalized Medicine, 12(10), 1649. https://doi.org/10.3390/jpm12101649