Creixell, Pau

Cancerceller udviser mange unikke træk, hvoraf ændringer i de cellulære beslutningsprocesser formodentlig hører til blandt de vigtigste. Cancerceller såvel som normale celler integrerer løbende forskellige udefrakommende indtryk til at træffe beslutninger, f.eks. om proliferation eller apoptose. Denne integration hos cancerceller og de deraf afledte beslutninger er distinkt fra den, der observeres hos tilsvarende normale celler. Da cellulære signaleringsnetværk og deres tilhørende tilstande udgør de kredsløb, som styrer cellers adfærd, er det derfor oplagt, at disse netværk ofte vil være fejlregulerede i cancerceller. At udvikle og anvende metoder, som vil være i stand til at forudsige, hvordan mutationer i cancer fører til forandringer i signaleringsnetværk, er en stor udfordring. Men genvinsten er at sådanne metoder vil føre til en bedre forståelse af cancercellers udvikling og lægemiddelresistens og dermed på længere sigt give mulighed for at hjælpe personer, der rammes af cancer. Denne afhandling opsummerer mine bidrag over de seneste år til at løse denne udfordring.Afhandlingen består af seks dele og starter med en kortfattet introduktion til grundlæggende begreber inden for cancer, signaleringsnetværk og humane proteinkinaser (del I). Herefter følger en beskrivelse af metoder til at analysere cancersignaleringsnetværk – herunder metoder udviklet af os – samt et resumé af tre af de artikler, der udgør en del af denne ph.d.-afhandling (del II). I del III illustrerer vi (med en nyligt indsendt artikel), hvordan data fra next-generation sequencing og massespektrometri kan kombineres til at afdække genomspecifikke signaleringsnetværk. I del IV beskriver jeg de to beregningsmetoder, som jeg har udviklet, samt hvordan de kan kombineres til at forudsige hvordan signaleringsnetværk fejlreguleres i cancer. Den følgende del (V) viser anvendeligheden af denne kombinationsmetode ved at identificere en funktionel mutation, som vil kunne føre til resistens mod behandling med cisplatin i en gruppe af ovarian clear cell carcinoma cellelinjer. Del VI er en opsamling af afhandlingens hovedpointer og afsluttes med en diskussion af perspektiverne samt forslag til videre arbejde.Denne afhandling etablerer således en ny fremgangsmåde til at beskrive og forudsige de begivenheder og mekanismer, der ligger til grund for udvikling af cancer, og som – med lidt held – kan hjælpe med til at bygge bro mellem de genotypiske og fænotypiske aspekter af denne udvikling.Amongst the unique features of cancer cells perhaps the most crucial one is the change in the cellular decision-making process. While both non-cancer and cancer cells are constantly integrating different external cues that reach them and computing cellular decisions (e.g. proliferation or apoptosis) based on the integration of these cues; this integration and consequently the cellular decisions taken by cancer cells are arguably very distinct from the decisions that would be expected from non-cancer cells. Since cellular signaling networks and its different states are the computational circuits that determine cellular outcome, it is clear to many that these networks will be highly dysregulated in cancer cells. Thus, developing and applying methods that will be capable of mapping and predicting how cancer mutations translate into signaling network perturbations, which could explain cancer development as well as cancer resistance to treatment, represent not only a huge challenge, but also one with potentially extreme benefit for our understanding of the disease and for patients. This thesis summarizes my efforts during the last years in contributing positively to overcome this challenge.This thesis is divided into six parts. Starting with a brief introduction to the history and some basic concepts of cancer, signaling networks and human protein kinases (part I), we quickly move on to describing existing methods to analyze cancer signaling networks, including methods proposed by us, as well as three of the articles that are part of this PhD thesis (part II). In part III, we illustrate with an article that has been submitted recently, how next-generation sequencing data and mass spectrometry data can be combined to uncover genome-specific signaling networks. In part IV, I describe the two computational methods that I have developed and how they can be integrated with the aim of predicting how signaling networks will be dysregulated in cancer. As a matter of fact, the following part (part V) proves the usefulness of the method by identifying a functional mutation in a group of ovarian clear cell carcinoma cell lines that could cause their resistance to cisplatin treatment. Part VI closes the thesis by summarizing its main points and proposing some future perspectives for the work presented here.All in all, this work establishes a new framework for the prediction of mechanisms underlying cancer development and evolution which, one would hope, should help close the gap between cancer genotype and phenotype

Online Research Database In Technology

Cancer signaling networks and their implications for personalized medicine

http://orbit.dtu.dk/ws/files/74988179/PauCreixellPhDThesis..PDF

Cancer signaling networks and their implications for personalized medicine

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Online Research Database In Technology