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Current Medicinal Chemistry

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ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

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Review Article

Nanoinformatics and Personalized Medicine: An Advanced Cumulative Approach for Cancer Management

Author(s): Fariya Khan, Salman Akhtar* and Mohammad Amjad Kamal

Volume 30, Issue 3, 2023

Published on: 04 November, 2022

Page: [271 - 285] Pages: 15

DOI: 10.2174/0929867329666220610090405

Price: $65

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Abstract

Background: Even though the battle against one of the deadliest diseases, cancer, has advanced remarkably in the last few decades and the survival rate has improved significantly; the search for an ultimate cure remains a utopia. Nanoinformatics, which is bioinformatics coupled with nanotechnology, endows many novel research opportunities in the preclinical and clinical development of personalized nanosized drug carriers in cancer therapy. Personalized nanomedicines serve as a promising treatment option for cancer owing to their noninvasiveness and their novel approach. Explicitly, the field of personalized medicine is expected to have an enormous impact soon because of its many advantages, namely its versatility to adapt a drug to a cohort of patients.

Objective: The current review explains the application of this newly emerging field called nanoinformatics to the field of precision medicine. This review also recapitulates how nanoinformatics could hasten the development of personalized nanomedicine for cancer, which is undoubtedly the need of the hour.

Conclusion: This approach has been facilitated by a humongous impending field named Nanoinformatics. These breakthroughs and advances have provided insight into the future of personalized medicine. Imperatively, they have been enabling landmark research to merge all advances, creating nanosized particles that contain drugs targeting cell surface receptors and other potent molecules designed to kill cancerous cells. Nanoparticle- based medicine has been developing and has become a center of attention in recent years, focusing primely on proficient delivery systems for various chemotherapy drugs.

Keywords: Personalized medicine, oncogenomics, nanomedicine, nanoinformatics, cancer informatics, bioinformatics.

« Previous Next »
[1]
Wu, D.; Rice, C.M.; Wang, X. Cancer bioinformatics: A new approach to systems clinical medicine. BMC Bioinformatics, 2012, 13(1), 71.
[http://dx.doi.org/10.1186/1471-2105-13-71] [PMID: 22549015]
[2]
Maojo, V.; Martin-Sanchez, F.; Kulikowski, C.; Rodriguez-Paton, A.; Fritts, M. Nanoinformatics and DNA-based computing: Catalyzing nanomedicine. Pediatr. Res., 2010, 67(5), 481-489.
[http://dx.doi.org/10.1203/PDR.0b013e3181d6245e] [PMID: 20118825]
[3]
Maojo, V.; Mitchell, J.A.; Frey, L.J. Section 7: Bioinformatics: Bioinformatics linkage of heterogeneous clinical and genomic information in support of personalized medicine. Yearb. Med. Inform., 2007, 16(1), 98-105.
[http://dx.doi.org/10.1055/s-0038-1638533]
[4]
Sadan, T.; Cormode, D. P.; Popovtzer, R. Nanoinformatics revolutionizes personalized cancer therapy. Trends in Cancer, 2018, 4(6), 397-399.
[http://dx.doi.org/10.1016/j.trecan.2018.04.002]
[5]
Kakkar, A.; Traverso, G.; Farokhzad, O.C.; Weissleder, R.; Langer, R. Evolution of macromolecular complexity in drug delivery systems. Nat. Rev. Chem., 2017, 1(8), 0063.
[http://dx.doi.org/10.1038/s41570-017-0063] [PMID: 31286060]
[6]
Wang, W.; Sedykh, A.; Sun, H.; Zhao, L.; Russo, D.P.; Zhou, H.; Yan, B.; Zhu, H. Predicting nano–bio interactions by integrating nanoparticle libraries and quantitative nanostructure activity relationship modeling. ACS Nano, 2017, 11(12), 12641-12649.
[http://dx.doi.org/10.1021/acsnano.7b07093] [PMID: 29149552]
[7]
Shamay, Y.; Shah, J.; Işık, M.; Mizrachi, A.; Leibold, J.; Tschaharganeh, D.F.; Roxbury, D.; Budhathoki-Uprety, J.; Nawaly, K.; Sugarman, J.L.; Baut, E.; Neiman, M.R.; Dacek, M.; Ganesh, K.S.; Johnson, D.C.; Sridharan, R.; Chu, K.L.; Rajasekhar, V.K.; Lowe, S.W.; Chodera, J.D.; Heller, D.A. Quantitative self-assembly prediction yields targeted nanomedicines. Nat. Mater., 2018, 17(4), 361-368.
[http://dx.doi.org/10.1038/s41563-017-0007-z] [PMID: 29403054]
[8]
Xia, X. Position weight matrix, Gibbs sampler, and the associated significance tests in motif characterization and prediction. Scientifica (Cairo), 2012, 2012, 1-15.
[9]
Jeanquartier, F.; Jean-Quartier, C.; Cemernek, D.; Holzinger, A. Integrating open data on cancer in support to tumor growth analysis. International Conference on Information Technology in Bio- and Medical Informatics, 2016, 9832, 49-66.
[http://dx.doi.org/10.1007/978-3-319-43949-5_4]
[10]
Uhlén, M.; Björling, E.; Agaton, C.; Szigyarto, C.A.K.; Amini, B.; Andersen, E.; Andersson, A.; Angelidou, P.; Asplund, A.; Asplund, C.; Berglund, L.; Bergström, K.; Brumer, H.; Cerjan, D.; Ekström, M.; Elobeid, A.; Eriksson, C.; Fagerberg, L.; Falk, R.; Fall, J.; Forsberg, M.; Björklund, M.G.; Gumbel, K.; Halimi, A.; Hallin, I.; Hamsten, C.; Hansson, M.; Hedhammar, M.; Hercules, G.; Kampf, C.; Larsson, K.; Lindskog, M.; Lodewyckx, W.; Lund, J.; Lundeberg, J.; Magnusson, K.; Malm, E.; Nilsson, P.; Ödling, J.; Oksvold, P.; Olsson, I.; Öster, E.; Ottosson, J.; Paavilainen, L.; Persson, A.; Rimini, R.; Rockberg, J.; Runeson, M.; Sivertsson, A.; Sköllermo, A.; Steen, J.; Stenvall, M.; Sterky, F.; Strömberg, S.; Sundberg, M.; Tegel, H.; Tourle, S.; Wahlund, E.; Waldén, A.; Wan, J.; Wernérus, H.; Westberg, J.; Wester, K.; Wrethagen, U.; Xu, L.L.; Hober, S.; Pontén, F. A human protein atlas for normal and cancer tissues based on antibody proteomics. Mol. Cell. Proteomics, 2005, 4(12), 1920-1932.
[11]
Uhlen, M.; Zhang, C.; Lee, S.; Sjostedt, E.; Fagerberg, L.; Bidkhori, G.; Benfeitas, R.; Arif, M.; Liu, Z.; Edfors, F; Sanli, K. A pathology atlas of the human cancer transcriptome. Sci (New York, NY), 2017, 357(6352), eaan2507.
[12]
Locasale, J. W.; Melman, T.; Song, S.; Yang, X.; Swanson, K. D.; Cantley, L. C.; Wong, E. T.; Asara, J. M. Metabolomics of human cerebrospinal fluid identifies signatures of malignant glioma. Mol. Cell. Proteomics, 2012, 11(6), M111.014688.
[http://dx.doi.org/10.1074/mcp.M111.014688]
[13]
McDunn, J.E.; Li, Z.; Adam, K.P.; Neri, B.P.; Wolfert, R.L.; Milburn, M.V.; Lotan, Y.; Wheeler, T.M. Metabolomic signatures of aggressive prostate cancer. Prostate, 2013, 73(14), 1547-1560.
[http://dx.doi.org/10.1002/pros.22704] [PMID: 23824564]
[14]
Farshidfar, F.; Weljie, A.M.; Kopciuk, K.A.; Hilsden, R.; McGregor, S.E.; Buie, W.D.; MacLean, A.; Vogel, H.J.; Bathe, O.F. A validated metabolomic signature for colorectal cancer: Exploration of the clinical value of metabolomics. Br. J. Cancer, 2016, 115(7), 848-857.
[http://dx.doi.org/10.1038/bjc.2016.243] [PMID: 27560555]
[15]
Tritthart, H.A. In vitro test systems in cancer research. ALTEX, 1996, 13(3), 118-124.
[16]
Teicher, B.A. In vivo/ex vivo and in situ assays used in cancer research: A brief review. Toxicol. Pathol., 2009, 37(1), 114-122.
[http://dx.doi.org/10.1177/0192623308329473] [PMID: 19098118]
[17]
Valeska, M.D.; Adisurja, G.P.; Bernard, S.; Wijaya, R.M. The role of bioinformatics in personalized medicine: Your future medical treatment. Cermin Dunia Kedokteran, 2019, 46(12)
[18]
Scholler, P.; Zwier, J.M.; Trinquet, E.; Rondard, P.; Pin, J.P.; Prézeau, L.; Kniazeff, J. Time-resolved Förster resonance energy transfer-based technologies to investigate G protein-coupled receptor machinery: High-throughput screening assays and future development. Prog. Mol. Biol. Transl. Sci., 2013, 113, 275-312.
[http://dx.doi.org/10.1016/B978-0-12-386932-6.00007-7] [PMID: 23244793]
[19]
Koehn, F.E.; Carter, G.T. The evolving role of natural products in drug discovery. Nat. Rev. Drug Discov., 2005, 4(3), 206-220.
[http://dx.doi.org/10.1038/nrd1657] [PMID: 15729362]
[20]
Mirza, A.Z.; Siddiqui, F.A. Nanomedicine and drug delivery: A mini review. Int. Nano Lett., 2014, 4(1), 94.
[http://dx.doi.org/10.1007/s40089-014-0094-7]
[21]
Prada-Gracia, D.; Huerta-Yépez, S.; Moreno-Vargas, L.M. Application of computational methods for anticancer drug discovery, design, and optimization. Bol. Méd. Hosp. Infant. México, 2016, 73(6), 411-423.
[http://dx.doi.org/10.1016/j.bmhimx.2016.10.006] [PMID: 29421286]
[22]
Mustata, G.; Li, M.; Zevola, N.; Bakan, A.; Zhang, L.; Epperly, M.; Greenberger, J.S.; Yu, J.; Bahar, I. Development of small-molecule PUMA inhibitors for mitigating radiation-induced cell death. Curr. Top. Med. Chem., 2011, 11(3), 281-290.
[http://dx.doi.org/10.2174/156802611794072641] [PMID: 21320058]
[23]
Chiang, Y.K.; Kuo, C.C.; Wu, Y.S.; Chen, C.T.; Coumar, M.S.; Wu, J.S.; Hsieh, H.P.; Chang, C.Y.; Jseng, H.Y.; Wu, M.H.; Leou, J.S.; Song, J.S.; Chang, J.Y.; Lyu, P.C.; Chao, Y.S.; Wu, S.Y. Generation of ligand-based pharmacophore model and virtual screening for identification of novel tubulin inhibitors with potent anticancer activity. J. Med. Chem., 2009, 52(14), 4221-4233.
[http://dx.doi.org/10.1021/jm801649y] [PMID: 19507860]
[24]
Noha, S.M.; Atanasov, A.G.; Schuster, D.; Markt, P.; Fakhrudin, N.; Heiss, E.H.; Schrammel, O.; Rollinger, J.M.; Stuppner, H.; Dirsch, V.M.; Wolber, G. Discovery of a novel IKK-β inhibitor by ligand-based virtual screening techniques. Bioorg. Med. Chem. Lett., 2011, 21(1), 577-583.
[http://dx.doi.org/10.1016/j.bmcl.2010.10.051] [PMID: 21078555]
[25]
San Lucas, F.A.; Fowler, J.; Chang, K.; Kopetz, S.; Vilar, E.; Scheet, P. Cancer in silico drug discovery: A systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes. Mol. Cancer Ther., 2014, 13(12), 3230-3240.
[http://dx.doi.org/10.1158/1535-7163.MCT-14-0260] [PMID: 25349306]
[26]
Maojo, V.; Fritts, M.; de la Iglesia, D.; Cachau, R.E.; Garcia-Remesal, M.; Mitchell, J.A.; Kulikowski, C. Nanoinformatics: A new area of research in nanomedicine. Int. J. Nanomedicine, 2012, 7, 3867-3890.
[http://dx.doi.org/10.2147/IJN.S24582] [PMID: 22866003]
[27]
Maojo, V.; Fritts, M.; Martin-Sanchez, F.; De la Iglesia, D.; Cachau, R.E.; Garcia-Remesal, M.; Crespo, J.; Mitchell, J.A.; Anguita, A.; Baker, N.; Barreiro, J.M.; Benitez, S.E.; De la Calle, G.; Facelli, J.C.; Ghazal, P.; Geissbuhler, A.; Gonzalez-Nilo, F.; Graf, N.; Grangeat, P.; Hermosilla, I.; Hussein, R.; Kern, J.; Koch, S.; Legre, Y.; Lopez-Alonso, V.; Lopez-Campos, G.; Milanesi, L.; Moustakis, V.; Munteanu, C.; Otero, P.; Pazos, A.; Perez-Rey, D.; Potamias, G.; Sanz, F.; Kulikowski, C. Nanoinformatics: Developing new computing applications for nanomedicine. Comput. Sci. Eng., 2012, 94(6), 521-539.
[PMID: 22942787]
[28]
Sharma, N.; Sharma, M.; Sajid Jamal, Q.M.; Kamal, M.A.; Akhtar, S. Nanoinformatics and biomolecular nanomodeling: a novel move en route for effective cancer treatment. Environ. Sci. Pollu. Res. 2020, 27(16), 19127-19141.
[29]
National Research Council of the National Academies Committee to Develop a Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. In: A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. National Academies Press; Washington, DC, 2012.
[30]
Baker, N.A.; Fritts, M.; Guccione, S. National Cancer Institute, caBIG® Integrative Cancer Research Nanotechnology Working Group. Nanotechnology Informatics White Paper; US National Institutes of Health: Bethesda, MD, 2009.
[31]
Fornaguera, C.; García-Celma, M. Personalized nanomedicine: A revolution at the nanoscale. J. Pers. Med., 2017, 7(4), 12.
[http://dx.doi.org/10.3390/jpm7040012] [PMID: 29023366]
[32]
Ge, Y.; Li, S.; Wang, S.; Moore, R. Nanomedicine; Nanostruct; Springer: Otawa, ON, Canada, 2014.
[http://dx.doi.org/10.1007/978-1-4614-2140-5]
[33]
Zhang, X.Q.; Xu, X.; Bertrand, N.; Pridgen, E.; Swami, A.; Farokhzad, O.C. Interactions of nanomaterials and biological systems: Implications to personalized nanomedicine. Adv. Drug Deliv. Rev., 2012, 64(13), 1363-1384.
[http://dx.doi.org/10.1016/j.addr.2012.08.005] [PMID: 22917779]
[34]
Bawa, R.; Audette, G.F.; Reese, B.E. Clinical Nanomedicine; CRC Press: Boca Raton, FL, USA, 2016.
[35]
Amado, R.G.; Wolf, M.; Peeters, M.; Van Cutsem, E.; Siena, S.; Freeman, D.J.; Juan, T.; Sikorski, R.; Suggs, S.; Radinsky, R.; Patterson, S.D.; Chang, D.D. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J. Clin. Oncol., 2008, 26(10), 1626-1634.
[http://dx.doi.org/10.1200/JCO.2007.14.7116] [PMID: 18316791]
[36]
Jimeno, A.; Messersmith, W.A.; Hirsch, F.R.; Franklin, W.A.; Eckhardt, S.G. KRAS mutations and sensitivity to epidermal growth factor receptor inhibitors in colorectal cancer: Practical application of patient selection. J. Clin. Oncol., 2009, 27(7), 1130-1136.
[http://dx.doi.org/10.1200/JCO.2008.19.8168] [PMID: 19124802]
[37]
Lièvre, A.; Bachet, J.B.; Boige, V.; Cayre, A.; Le Corre, D.; Buc, E.; Ychou, M.; Bouché, O.; Landi, B.; Louvet, C.; André, T.; Bibeau, F.; Diebold, M.D.; Rougier, P.; Ducreux, M.; Tomasic, G.; Emile, J.F.; Penault-Llorca, F.; Laurent-Puig, P. KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab. J. Clin. Oncol., 2008, 26(3), 374-379.
[http://dx.doi.org/10.1200/JCO.2007.12.5906] [PMID: 18202412]
[38]
Castillo-Fernández, O.; Santibáñez, M.; Bauza, A.; Calderillo, G.; Castro, C.; Herrera, R.; Serrano, A.; Arrieta, O.; Herrera, L.A. Methylenetetrahydrofolate reductase polymorphism (677 C>T) predicts long time to progression in metastatic colon cancer treated with 5-fluorouracil and folinic acid. Arch. Med. Res., 2010, 41(6), 430-435.
[http://dx.doi.org/10.1016/j.arcmed.2010.08.011] [PMID: 21044746]
[39]
Boni, V.; Zarate, R.; Villa, J.C.; Bandrés, E.; Gomez, M.A.; Maiello, E.; Garcia-Foncillas, J.; Aranda, E. Role of primary miRNA polymorphic variants in metastatic colon cancer patients treated with 5-fluorouracil and irinotecan. Pharmacogenomics J., 2011, 11(6), 429-436.
[http://dx.doi.org/10.1038/tpj.2010.58] [PMID: 20585341]
[40]
Audet-Walsh, E.; Bellemare, J.; Nadeau, G.; Lacombe, L.; Fradet, Y.; Fradet, V.; Huang, S.P.; Bao, B.Y.; Douville, P.; Girard, H.; Guillemette, C.; Lévesque, E. SRD5A polymorphisms and biochemical failure after radical prostatectomy. Eur. Urol., 2011, 60(6), 1226-1234.
[http://dx.doi.org/10.1016/j.eururo.2011.06.020] [PMID: 21715084]
[41]
Bachmann, H.S.; Heukamp, L.C.; Schmitz, K.J.; Hilburn, C.F.; Kahl, P.; Buettner, R.; Nückel, H.; Eisenhardt, A.; Rübben, H.; Schmid, K.W.; Siffert, W.; Eggert, A.; Schramm, A.; Schulte, J.H. Regulatory BCL2 promoter polymorphism (−938C>A) is associated with adverse outcome in patients with prostate carcinoma. Int. J. Cancer, 2011, 129(10), 2390-2399.
[http://dx.doi.org/10.1002/ijc.25904] [PMID: 21207420]
[42]
Takahashi, N.; Miura, M.; Scott, S.A.; Kagaya, H.; Kameoka, Y.; Tagawa, H.; Saitoh, H.; Fujishima, N.; Yoshioka, T.; Hirokawa, M.; Sawada, K. Influence of CYP3A5 and drug transporter polymorphisms on imatinib trough concentration and clinical response among patients with chronic phase chronic myeloid leukemia. J. Hum. Genet., 2010, 55(11), 731-737.
[http://dx.doi.org/10.1038/jhg.2010.98] [PMID: 20720558]
[43]
Rosenquist, R.; Rosenwald, A.; Du, M.Q.; Gaidano, G.; Groenen, P.; Wotherspoon, A.; Ghia, P.; Gaulard, P.; Campo, E.; Stamatopoulos, K. Clinical impact of recurrently mutated genes on lymphoma diagnostics: State-of-the-art and beyond. Haematologica, 2016, 101(9), 1002-1009.
[http://dx.doi.org/10.3324/haematol.2015.134510] [PMID: 27582569]
[44]
Jiang, W.; Cai, G.; Hu, P.C.; Wang, Y. Personalized medicine in non-small cell lung cancer: A review from a pharmacogenomics perspective. Acta Pharm. Sin. B, 2018, 8(4), 530-538.
[http://dx.doi.org/10.1016/j.apsb.2018.04.005] [PMID: 30109178]
[45]
Brauch, H.; Jordan, V.C. Targeting of tamoxifen to enhance antitumour action for the treatment and prevention of breast cancer: The ‘personalised’ approach? Eur. J. Cancer, 2009, 45(13), 2274-2283.
[http://dx.doi.org/10.1016/j.ejca.2009.05.032] [PMID: 19592233]
[46]
Hoskins, J.M.; Carey, L.A.; McLeod, H.L. CYP2D6 and tamoxifen: DNA matters in breast cancer. Nat. Rev. Cancer, 2009, 9(8), 576-586.
[http://dx.doi.org/10.1038/nrc2683] [PMID: 19629072]
[47]
Pozdeyev, N.; Gay, L.M.; Sokol, E.S.; Hartmaier, R.; Deaver, K.E.; Davis, S.; French, J.D.; Borre, P.V.; LaBarbera, D.V.; Tan, A.C.; Schweppe, R.E.; Fishbein, L.; Ross, J.S.; Haugen, B.R.; Bowles, D.W. Genetic analysis of 779 advanced differentiated and anaplastic thyroid cancers. Clin. Cancer Res., 2018, 24(13), 3059-3068.
[http://dx.doi.org/10.1158/1078-0432.CCR-18-0373] [PMID: 29615459]
[48]
Lin, J.D.; Chao, T.C. Vascular endothelial growth factor in thyroid cancers. Cancer Biother. Radiopharm., 2005, 20(6), 648-661.
[http://dx.doi.org/10.1089/cbr.2005.20.648] [PMID: 16398617]
[49]
Capp, C.; Wajner, S.M.; Siqueira, D.R.; Brasil, B.A.; Meurer, L.; Maia, A.L. Increased expression of vascular endothelial growth factor and its receptors, VEGFR-1 and VEGFR-2, in medullary thyroid carcinoma. Thyroid, 2010, 20(8), 863-871.
[http://dx.doi.org/10.1089/thy.2009.0417] [PMID: 20615131]
[50]
Agaimy, A.; Terracciano, L.M.; Dirnhofer, S.; Tornillo, L.; Foerster, A.; Hartmann, A.; Bihl, M.P. V600E BRAF mutations are alternative early molecular events in a subset of KIT/PDGFRA wild-type gastrointestinal stromal tumours. J. Clin. Pathol., 2009, 62(7), 613-616.
[http://dx.doi.org/10.1136/jcp.2009.064550] [PMID: 19561230]
[51]
Kim, M.J.; Kim, S.K.; Park, H.J.; Chung, D.H.; Park, H.K.; Lee, J.S.; Kwon, K.H.; Chung, J.H. PDGFRA promoter polymorphisms are associated with the risk of papillary thyroid cancer. Mol. Med. Rep., 2012, 5(5), 1267-1270.
[PMID: 22327316]
[52]
Panneerselvam, S.; Choi, S. Nanoinformatics: Emerging databases and available tools. Int. J. Mol. Sci., 2014, 15(5), 7158-7182.
[http://dx.doi.org/10.3390/ijms15057158] [PMID: 24776761]

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