Treatment-driven evolution of metastatic prostate cancer: A circulating tumor DNA analysis
Sipola, Joonatan (2020)
2020
Bioteknologian tutkinto-ohjelma, luonnontieteiden kandidaatin tutkinto - Degree Programme in Biotechnology, Bachelor of Science
Lääketieteen ja terveysteknologian tiedekunta - Faculty of Medicine and Health Technology
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Hyväksymispäivämäärä
2020-05-12
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202004284252
https://urn.fi/URN:NBN:fi:tuni-202004284252
Tiivistelmä
Metastatic castration resistant prostate cancer (mCRPC) accounts for 8th most deaths of all cancers annually. Many kinds of methods are used in treatment of mCRPC, none of which are shown to do more than prolong the inevitable. The ways in which mCRPC achieves resistance to these treatments are still largely not understood. Understanding these are crucial in order to choose the best treatment for each patient and develop better treatments.
The lack of quality data representing the changes caused by a specific treatment is an essential hindrance in studying mCRPC. This is due to traditional tissue biopsies being often not feasible and biased in terms of intra- and inter-metastasis heterogeneity. Liquid biopsy, being easily feasible and containing cell free DNA, is an alternative for traditional tissue biopsy, but it comes with challenges of its own.
In this thesis I studied the differences in mCRPC clonal evolution resulting from resistances to cabazitaxel and androgen receptor pathway inhibitors. Clonal shifts were called comparing relative mutation allele fractions between samples. While cell free DNA samples are a great alternative to tissue biopsies in terms of sample availability, the algorithm utilized here is designed to be robust to typical challenges associated with cell free DNA, being almost completely independent of circulating tumor DNA fraction estimation. 171 plasma cell free DNA samples were collected before and after treatments and sequenced using a custom panel targeting 73 known cancer related genes.
Despite the very different mechanism of action of the treatments, clonal shifts in cell populations were detected equally often in the chosen gene pool. No significant differences were found between the treatments with clonal shift being called roughly 50% of the time for both. More comprehensive and detailed datasets and analyses are needed for understanding the biology behind resistance to different mCRPC treatments.
The lack of quality data representing the changes caused by a specific treatment is an essential hindrance in studying mCRPC. This is due to traditional tissue biopsies being often not feasible and biased in terms of intra- and inter-metastasis heterogeneity. Liquid biopsy, being easily feasible and containing cell free DNA, is an alternative for traditional tissue biopsy, but it comes with challenges of its own.
In this thesis I studied the differences in mCRPC clonal evolution resulting from resistances to cabazitaxel and androgen receptor pathway inhibitors. Clonal shifts were called comparing relative mutation allele fractions between samples. While cell free DNA samples are a great alternative to tissue biopsies in terms of sample availability, the algorithm utilized here is designed to be robust to typical challenges associated with cell free DNA, being almost completely independent of circulating tumor DNA fraction estimation. 171 plasma cell free DNA samples were collected before and after treatments and sequenced using a custom panel targeting 73 known cancer related genes.
Despite the very different mechanism of action of the treatments, clonal shifts in cell populations were detected equally often in the chosen gene pool. No significant differences were found between the treatments with clonal shift being called roughly 50% of the time for both. More comprehensive and detailed datasets and analyses are needed for understanding the biology behind resistance to different mCRPC treatments.
Kokoelmat
- Kandidaatintutkielmat [8997]