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- L. B. Almeida, Bilena, et al.
(författare)
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The transcription factor network of E. coli steers global responses to shifts in RNAP concentration
- 2022
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Ingår i: Nucleic Acids Research. - : Oxford University Press. - 0305-1048 .- 1362-4962. ; 50:12, s. 6801-6819
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Tidskriftsartikel (refereegranskat)abstract
- The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene's numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.
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- Hamis, S., et al.
(författare)
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Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems
- 2023
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Ingår i: Journal of Mathematical Biology. - : Springer Nature. - 0303-6812 .- 1432-1416. ; 86:5
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Tidskriftsartikel (refereegranskat)abstract
- Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.
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- Kallio, Heini M.L., et al.
(författare)
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Constitutively active androgen receptor splice variants AR-V3, AR-V7 and AR-V9 are co-expressed in castration-resistant prostate cancer metastases
- 2018
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Ingår i: British Journal of Cancer. - : Springer Science and Business Media LLC. - 0007-0920 .- 1532-1827. ; 119:3, s. 347-356
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Tidskriftsartikel (refereegranskat)abstract
- Background: A significant subset of prostate cancer (PC) patients with a castration-resistant form of the disease (CRPC) show primary resistance to androgen receptor (AR)-targeting drugs developed against CRPC. As one explanation could be the expression of constitutively active androgen receptor splice variants (AR-Vs), our current objectives were to study AR-Vs and other AR aberrations to better understand the emergence of CRPC. Methods: We analysed specimens from different stages of prostate cancer by next-generation sequencing and immunohistochemistry. Results: AR mutations and copy number variations were detected only in CRPC specimens. Genomic structural rearrangements of AR were observed in 5/30 metastatic CRPC patients, but they were not associated with expression of previously known AR-Vs. The predominant AR-Vs detected were AR-V3, AR-V7 and AR-V9, with the expression levels being significantly higher in CRPC cases compared to prostatectomy samples. Out of 25 CRPC metastases that expressed any AR variant, 17 cases harboured expression of all three of these AR-Vs. AR-V7 protein expression was highly heterogeneous and higher in CRPC compared to hormone-naïve tumours. Conclusions: AR-V3, AR-V7 and AR-V9 are co-expressed in CRPC metastases highlighting the fact that inhibiting AR function via regions common to all AR-Vs is likely to provide additional benefit to patients with CRPC.
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