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147. Garnett, M.J.; Edelman, E.J.; Heidorn, S.J.; Greenman, C.D.; Dastur, A.; Lau, K.W.; Greninger, P.;
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151. Arney, K. Improving brain-cancer therapies through mathematical modelling. Nature 2018, 561, S52–S53.
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152. Barua, D.; Hlavacek, W.S. Modeling the effect of APC truncation on destruction complex function in colorectal
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153. Klinger, B.; Sieber, A.; Fritsche-Guenther, R.; Witzel, F.; Berry, L.; Schumacher, D.; Yan, Y.; Durek, P.;
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154. Kirouac, D.C.; Du, J.Y.; Lahdenranta, J.; Overland, R.; Yarar, D.; Paragas, V.; Pace, E.; McDonagh, C.F.;
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155. Carbo, A.; Bassaganya-Riera, J.; Pedragosa, M.; Viladomiu, M.; Marathe, M.; Eubank, S.; Wendelsdorf, K.;
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during Helicobacter pylori infection. PLoS ONE 2013, 8, e73365. [CrossRef]
156. Zand, R.; Abedi, V.; Hontecillas, R.; Lu, P.; Noorbakhsh-Sabet, N.; Verma, M.; Leber, A.; Tubau-Juni, N.;
Bassaganya-Riera, J. Development of synthetic patient populations and in silico clinical trials. In Accelerated
Path to Cures; Springer International Publishing AG: Basel, Switzerland, 2018; pp. 57–77.
157. Edelman, L.B.; Eddy, J.A.; Price, N.D. In silico models of cancer. Wiley Interdiscip. Rev. Syst. Biol. Med. 2010,
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158. Jerby-Arnon, L.; Shah, P.; Cuoco, M.S.; Rodman, C.; Su, M.-J.; Melms, J.C.; Leeson, R.; Kanodia, A.; Mei, S.;
Lin, J.-R.; et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell
2018, 175, 984–997.e24. [CrossRef][PubMed]
159. Thorsson, V.; Gibbs, D.L.; Brown, S.D.; Wolf, D.; Bortone, D.S.; Ou Yang, T.-H.; Porta-Pardo, E.; Gao, G.F.;
Plaisier, C.L.; Eddy, J.A.; et al. The immune landscape of cancer. Immunity 2018, 48, 812–830.e14. [CrossRef]
[PubMed]
160. Gong, C.; Anders, R.A.; Zhu, Q.; Taube, J.M.; Green, B.; Cheng, W.; Bartelink, I.H.; Vicini, P.; Wang, B.;
Popel, A.S. Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid
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62
142. Figueredo, G.P.; Siebers, P.O.; Owen, M.R.; Reps, J.; Aickelin, U. Comparing stochastic differential equations
and agent-based modelling and simulation for early-stage cancer. PLoS ONE 2014, 9, e95150. [CrossRef]
[PubMed]
143. Yankeelov, T.E.; An, G.; Saut, O.; Luebeck, E.G.; Popel, A.S.; Ribba, B.; Vicini, P.; Zhou, X.; Weis, J.A.; Ye, K.; et al.
Multi-scale modeling in clinical oncology: Opportunities and barriers to success. Ann. Biomed. Eng. 2016, 44,
2626–2641. [CrossRef]
144. Cosgrove, J.; Butler, J.; Alden, K.; Read, M.; Kumar, V.; Cucurull-Sanchez, L.; Timmis, J.; Coles, M.
Agent-based modeling in systems pharmacology. CPT Pharmacometrics Syst. Pharmacol. 2015, 4, 615–629.
[CrossRef]
145. Rieger, T.R.; Allen, R.J.; Bystricky, L.; Chen, Y.; Colopy, G.W.; Cui, Y.; Gonzalez, A.; Liu, Y.; White, R.D.;
Everett, R.A.; et al. Improving the generation and selection of virtual populations in quantitative systems
pharmacology models. Prog. Biophys. Mol. Biol. 2018, 139, 15–22. [CrossRef]
146. Barretina, J.; Caponigro, G.; Stransky, N.; Venkatesan, K.; Margolin, A.A.; Kim, S.; Wilson, C.J.; Lehár, J.;
Kryukov, G.V.; Sonkin, D.; et al. The Cancer Cell Line Encyclopedia enables predictive modelling of
anticancer drug sensitivity. Nature 2012, 483, 603–607. [CrossRef][PubMed]
147. Garnett, M.J.; Edelman, E.J.; Heidorn, S.J.; Greenman, C.D.; Dastur, A.; Lau, K.W.; Greninger, P.;
Thompson, I.R.; Luo, X.; Soares, J.; et al. Systematic identification of genomic markers of drug sensitivity in
cancer cells. Nature 2012, 483, 570–575. [CrossRef][PubMed]
148. Rubio-Perez, C.; Tamborero, D.; Schroeder, M.P.; Antolín, A.A.; Deu-Pons, J.; Perez-Llamas, C.; Mestres, J.;
Gonzalez-Perez, A.; Lopez-Bigas, N. In silico prescription of anticancer drugs to cohorts of 28 tumor types
reveals targeting opportunities. Cancer Cell 2015, 27, 382–396. [CrossRef][PubMed]
149. Anderson, A.R.A.; Maini, P.K. Mathematical oncology. Bull. Math. Biol. 2018, 80, 945–953. [CrossRef]
[PubMed]
150. Sun, X.; Hu, B. Mathematical modeling and computational prediction of cancer drug resistance. Brief. Bioinform.
2017, 19, 1382–1399. [CrossRef]
151. Arney, K. Improving brain-cancer therapies through mathematical modelling. Nature 2018, 561, S52–S53.
[CrossRef][PubMed]
152. Barua, D.; Hlavacek, W.S. Modeling the effect of APC truncation on destruction complex function in colorectal
cancer cells. PLoS Comput. Biol. 2013, 9, e1003217. [CrossRef]
153. Klinger, B.; Sieber, A.; Fritsche-Guenther, R.; Witzel, F.; Berry, L.; Schumacher, D.; Yan, Y.; Durek, P.;
Merchant, M.; Schafer, R.; et al. Network quantification of EGFR signaling unveils potential for targeted
combination therapy. Mol. Syst. Biol. 2014, 9, 673. [CrossRef]
154. Kirouac, D.C.; Du, J.Y.; Lahdenranta, J.; Overland, R.; Yarar, D.; Paragas, V.; Pace, E.; McDonagh, C.F.;
Nielsen, U.B.; Onsum, M.D. Computational modeling of ERBB2-amplified breast cancer identifies combined
ErbB2/3 blockade as superior to the combination of MEK and AKT inhibitors (Science Signaling 6:288 (ra68)).
Sci. Signal. 2014, 7, er5.
155. Carbo, A.; Bassaganya-Riera, J.; Pedragosa, M.; Viladomiu, M.; Marathe, M.; Eubank, S.; Wendelsdorf, K.;
Bisset, K.; Hoops, S.; Deng, X.; et al. Predictive computational modeling of the mucosal immune responses
during Helicobacter pylori infection. PLoS ONE 2013, 8, e73365. [CrossRef]
156. Zand, R.; Abedi, V.; Hontecillas, R.; Lu, P.; Noorbakhsh-Sabet, N.; Verma, M.; Leber, A.; Tubau-Juni, N.;
Bassaganya-Riera, J. Development of synthetic patient populations and in silico clinical trials. In Accelerated
Path to Cures; Springer International Publishing AG: Basel, Switzerland, 2018; pp. 57–77.
157. Edelman, L.B.; Eddy, J.A.; Price, N.D. In silico models of cancer. Wiley Interdiscip. Rev. Syst. Biol. Med. 2010,
2, 438–459. [CrossRef][PubMed]
158. Jerby-Arnon, L.; Shah, P.; Cuoco, M.S.; Rodman, C.; Su, M.-J.; Melms, J.C.; Leeson, R.; Kanodia, A.; Mei, S.;
Lin, J.-R.; et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell
2018, 175, 984–997.e24. [CrossRef][PubMed]
159. Thorsson, V.; Gibbs, D.L.; Brown, S.D.; Wolf, D.; Bortone, D.S.; Ou Yang, T.-H.; Porta-Pardo, E.; Gao, G.F.;
Plaisier, C.L.; Eddy, J.A.; et al. The immune landscape of cancer. Immunity 2018, 48, 812–830.e14. [CrossRef]
[PubMed]
160. Gong, C.; Anders, R.A.; Zhu, Q.; Taube, J.M.; Green, B.; Cheng, W.; Bartelink, I.H.; Vicini, P.; Wang, B.;
Popel, A.S. Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid
Tumors. Front Oncol. 2018, 8, 649. [CrossRef]
62