Integrative modeling of intratumoral heterogeneity, plasticity and regulation in nervous system cancers

• The adult brain tumor glioblastoma (GBM) is characterized by short survival and a lack of efficient treatments. Median survival is 15 months from time of diagnosis and the 5-year survival rate is only 7 %. There is an urgent need for more efficient treatment against GBM, but there are many challenges, including the high extent of heterogeneity of GBM. The tumoral heterogeneity of GBM ranges from interpatient to intratumoral. The aim of this thesis has been to address unanswered questions relating to the intratumoral heterogeneity of GBM, with three specific focuses; (1) the organization of GBM cell state transitions (paper I and III), (2) the regulation of cell states and cell state transitions (paper II), and (3) targeted interventions against cell states (paper II and IV).In paper I, we develop an experimental-computational method to measure and quantify cell state transitions. We find that GBM cell states organize hierarchically, with a clear “source state” feeding cells downwards in the hierarchy towards a “sink state” with negative growth rate, but with multi-directional transitions between intermediate states. In paper II, we address the lack of computational methods to identify regulators of intratumoral heterogeneity by developing an algorithm called scRegClust that uses scRNA-seq data to estimate regulatory programs. Through an integrative study of the regulatory landscape of neuro-oncology we find two potential regulators of the macrophage-induced mesenchymal transition in GBM.In paper III, we explore the energy-concept as a way of measuring differentiation potential of single cells, instead of relying on gene markers or gene signatures of stemness. We fit a model called the Ising model from statistical mechanics to scRNA-seq data and show both on synthetic and real data that the estimated Ising energy is a good measure of a cell’s differentiation potential, where high Ising energy indicate a high degree of stemness.Finally, in paper IV, another experimental-computational method is developed to investigate drug-induced effects on both inter- and intratumoral heterogeneity. In summary, the high extent of intratumoral heterogeneity in nervous system cancer is a major caveat for the development of more efficient treatments. In this thesis we have taken a systems biology approach to understand how this heterogeneity is structured and how we can exploit that knowledge for therapeutic purposes. 

Ämnesord

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

Nyckelord

Nervous system cancer

Glioblastoma

Heterogeneity

Plasticity

Mathematical modeling

Oncology

Onkologi

Publikations- och innehållstyp

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