Computational Analysis of Transporter Repertoires as Determinants of Cellular Cancer Drug Response

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Saez-Rodriguez, Julio
dc.contributor.advisor Brehme, Marc
dc.contributor.author Buphamalai, Pisanu
dc.date.accessioned 2016-10-12T11:38:01Z
dc.date.available 2016-10-12T11:38:01Z
dc.date.issued 2016-09-29
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/22818
dc.description.abstract Cancer patient heterogeneities challenge disease management despite advances in targeted therapies. Patient sub-populations are irresponsive to certain treatments with unknown reason or differ in sensitivity, while mutations can cause resistance and patient relapse. Large-scale pharmacogenomic screens of large sets of small molecule libraries against comprehensive panels of human cancer cell lines were performed in order to provide novel predictive biomarkers of cancer drug response in the context of genomic profiles. However, predictive accuracy is still lower than desired. This master's thesis focuses on the roles of membrane transporters in cellular drug response. It has been hypothesised that many drugs act upon their endogenous targets by hitch-hiking on membrane channels. Solute Carriers (SLCs), which represent the second-largest family of membrane proteins in the human genome and the largest class of transporters, are the central focus of this study. About 10\% of the human genome encodes for transport-related functions, while a functional link between transporter and cargo and disease relevance are largely unknown. For systematic identification, the analyses also included more well-known transporter family of ATP-binding cassettes (ABC), which have a widely accepted role in mediating drug resistance. The landscape of expression for both transporter families in cancer tissues were analysed. Matrix factorisation based methods were also employed in integrating multiple genetic data and observe tissue specificity patterns. It was found that differential expression of several transporters are likely to link with tumorigenesis, Moreover, functions of transporters in drug influx and efflux were also computationally hypothesised. Several statistical methods were used and compared, with a list of most potential candidates suggested for experimental validation. The interaction between two transporters were also identified using linear model with regularisation with interaction terms. Both computational and biological challenges and limitations of the project are discussed. en
dc.format.extent 49+6
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Computational Analysis of Transporter Repertoires as Determinants of Cellular Cancer Drug Response en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Perustieteiden korkeakoulu fi
dc.subject.keyword solute carriers (SLC) en
dc.subject.keyword membrane transporters en
dc.subject.keyword drug sensitivity en
dc.subject.keyword interaction learning en
dc.identifier.urn URN:NBN:fi:aalto-201610124918
dc.programme.major Computational and Systems Biology fi
dc.programme.mcode IL3013 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Rousu, Juho
dc.programme Master's Degree Programme in Computational and Systems Biology (euSYSBIO) fi


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