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BIOTEK2021-Bioteknologi for verdiskaping

ERA-NET: Mathematical modeling of TKI effects and immune response to predict patient-specific treatment dynamics in CML

Alternative title: Forbedret matematisk modell for behandling av kronisk myelogen leukemi (KML)

Awarded: NOK 2.1 mill.

The work with the mathematical model is ongoing in the international consortium. The work is not concluded. Clinical and immunological data from the Nordic CML studies have been added to the common database after a data cleansing operation by the immmunology lab in Helsinki including new assays. Data have been used in a mathematical modelling effort bby Hähnel et al Cancer Research 2020 using the consortium data base. The data support a role for a crucial immunological component in explaining patient treatment fate. WE continue aour work with single cell characterization of the immune cells in response and in the setting of treatment discontinuation. In Tromsø, studies of the different protein binding characteristics of CML drugs enable new hypotheses regarding their differing clinical profiles, both as to effect and adverse effects. A survey of all published data has been performed paving way for more studies.

Konsortiet har mottatt data fra Nordisk CML studiegruppes immunologiske prosjekter og integrert dette i en større database Arbeidet fortsetter men har allerede resultert i en matematisk modell som taler sterkt for at immunologiske mekanismer er viktige for hvorvidt pasienter som stopper behandling får tilbakefall eller ei. I vårt bidrag med off-target effekter av ulike KML-hemmere har vi samlet data fra en mengde publikasjoner og andre kilder for å se på interaksjoner av hemmerne på molekyler som er viktige i immunologiske prosesser, men også utenfor tyrosinkinasefamilien. Dette kan gi pekepinn for mekanismer for bivirkninger og forskjeller i immunologiske effkter av hemmerne. .

Our consortium of European CML researchers aims to combine data from multiple clinical studies in which we have good clinical data, but also have studied primitive cell fractions / stem cells or have made characterizations of the immune system. This applies both to the initial treatment course, but also to studies of treatment discontinuation in the patients with excellent clinical response. There is evidence that characteristics of the immunological system, in particular numbers of NK cells and their function plays a role for success in terms of achievement of deep response but also success of discontinuation in terms of relapse-free survival without treatment , i. e. "cure". In a first phase we will combine the available date in a meaningful way and attempt to identify "gaps" in data. If we have relevant biobanked material new assays may be possible for select parameters. In a second phase we will develop several improved mathematical models for prediction of individual response and likelihood of successful discontinuation In a third phase we will try to develop practical tools for individual patient response prediction/ fate.

Funding scheme:

BIOTEK2021-Bioteknologi for verdiskaping