Väitös (lääketieteellinen biokemia ja genetiikka): MSc Deepankar Chakroborty
Aika
9.2.2023 klo 14.00 - 18.00
MSc Deepankar Chakroborty esittää väitöskirjansa ”Novel tools for identification of oncogenic driver mutations” julkisesti tarkastettavaksi Turun yliopistossa torstaina 9.2.2023 klo 14 (Turun yliopisto, Biocity, Presidentti-auditorio, Tykistökatu 6, Turku).
Vastaväittäjänä toimii professori René Bernards (Alankomaiden syöpäinstituutti The Netherlands Cancer Institute, Alankomaat) ja kustoksena professori Klaus Elenius (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on lääketieteellinen biokemia ja genetiikka.
Väitöskirja yliopiston julkaisuarkistossa: https://www.utupub.fi/handle/10024/174004 (kopioi linkki selaimeen).
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Tiivistelmä väitöstutkimuksesta:
Genetic alterations contribute to the development and pathogenesis of several human cancers. These mutations accumulate in a cancer tissue over the course of time due to the instability of the cancer genome. Large-scale sequencing efforts have enabled identification of an abundance of these somatic mutations, and the amount of data is constantly increasing due to the improved accessibility of next-generation sequencing technologies. From this multitude of cancer-associated somatic mutations, a large majority are predicted to be inconsequential “passenger” mutations, (i.e., mutations which do not confer a ive growth advantage to the cancer cells); and only a handful have been validated as “driver” mutations (i.e., mutations playing a critical role in the development or maintenance of cancer). These driver mutations also function as predictive markers for survival, therapeutic efficacy, and often make the cancer cells susceptible to therapeutic intervention.
Identification of driver mutations is an integral part of biomarker discovery in cancer research, and my thesis aimed to address this by developing a screening platform and a database. The in vitro Screen for Activating Mutations (iSCREAM) is a high-throughput screening workflow which was established with Epidermal Growth Factor Receptor (EGFR) as a model. The screen was validated by detection of known activating mutations like EGFR L858R. A previously known EGFR variant of unknown significance (VUS), EGFR A702V, was discovered in the screen and was functionally characterized to be an activating mutation. The iSCREAM screening methodology was further used to systematically study ERBB4, another gene in the EGFR family of receptor tyrosine kinases. We detected ERBB4 VUS R687K, and E715K in the screen and identify them as activating mutations. The ERBB4 mutations were characterized for their effect on ERBB4 phosphorylation, their sensitivity to various tyrosine kinase inhibitors, and their tumorigenicity was evaluated with in vivo allografts.
The Database Of Recurrent Mutations (DORM), was prepared by analyzing a public registry of somatic mutations and preparing a catalog of the mutations identified from genome-wide studies to recapitulate the “real-world” frequency of all the recurrent (n 1) somatic mutations. DORM allows limiting the scope of search to 38 tissue types and supports advanced queries using regular expressions. The easy-to-use database and its backend are written to be very responsive and fast in comparison to contemporary public cancer databases.
Taken together, the findings and resources presented in this thesis establish grounds for further studies with other tyrosine kinases and potentially enable diversification into new niches.
Vastaväittäjänä toimii professori René Bernards (Alankomaiden syöpäinstituutti The Netherlands Cancer Institute, Alankomaat) ja kustoksena professori Klaus Elenius (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on lääketieteellinen biokemia ja genetiikka.
Väitöskirja yliopiston julkaisuarkistossa: https://www.utupub.fi/handle/10024/174004 (kopioi linkki selaimeen).
***
Tiivistelmä väitöstutkimuksesta:
Genetic alterations contribute to the development and pathogenesis of several human cancers. These mutations accumulate in a cancer tissue over the course of time due to the instability of the cancer genome. Large-scale sequencing efforts have enabled identification of an abundance of these somatic mutations, and the amount of data is constantly increasing due to the improved accessibility of next-generation sequencing technologies. From this multitude of cancer-associated somatic mutations, a large majority are predicted to be inconsequential “passenger” mutations, (i.e., mutations which do not confer a ive growth advantage to the cancer cells); and only a handful have been validated as “driver” mutations (i.e., mutations playing a critical role in the development or maintenance of cancer). These driver mutations also function as predictive markers for survival, therapeutic efficacy, and often make the cancer cells susceptible to therapeutic intervention.
Identification of driver mutations is an integral part of biomarker discovery in cancer research, and my thesis aimed to address this by developing a screening platform and a database. The in vitro Screen for Activating Mutations (iSCREAM) is a high-throughput screening workflow which was established with Epidermal Growth Factor Receptor (EGFR) as a model. The screen was validated by detection of known activating mutations like EGFR L858R. A previously known EGFR variant of unknown significance (VUS), EGFR A702V, was discovered in the screen and was functionally characterized to be an activating mutation. The iSCREAM screening methodology was further used to systematically study ERBB4, another gene in the EGFR family of receptor tyrosine kinases. We detected ERBB4 VUS R687K, and E715K in the screen and identify them as activating mutations. The ERBB4 mutations were characterized for their effect on ERBB4 phosphorylation, their sensitivity to various tyrosine kinase inhibitors, and their tumorigenicity was evaluated with in vivo allografts.
The Database Of Recurrent Mutations (DORM), was prepared by analyzing a public registry of somatic mutations and preparing a catalog of the mutations identified from genome-wide studies to recapitulate the “real-world” frequency of all the recurrent (n 1) somatic mutations. DORM allows limiting the scope of search to 38 tissue types and supports advanced queries using regular expressions. The easy-to-use database and its backend are written to be very responsive and fast in comparison to contemporary public cancer databases.
Taken together, the findings and resources presented in this thesis establish grounds for further studies with other tyrosine kinases and potentially enable diversification into new niches.