Characterization of Nek9 as a transcriptional regulator of p53-mediated networks involved in cellular arrest and apoptosis
Bibliographic record
Abstract
Oncogenesis is the consequence of the transformation of normal cells into cancerous cells. Cellular kinases are vital enzymes that facilitate the transfer of phosphate groups between two molecules. The disruption of these messengers may lead to genomic instability, resulting in death, or oncogenesis. NEK9, a human kinase, is responsible for mitotic progression and spindle formation. This thesis describes how the dysregulation of NEK9 in human cells alters the expression of tumour-suppressing pathways, disrupting mitotic progression, leading to transformation, cell cycle arrest, and the induction of apoptosis. The overexpression of NEK9 in adenovirus-infected MEF cells was shown to enhance the transformative properties of the virus, suggesting it may possess oncogenic properties. NEK9 was shown to suppress p53 activity independent of adenovirus, suggesting an inherent ability to regulate p53-promoters. The depletion of NEK9 in p53-mutant cells led to the upregulation of tumour-suppressor genes such as PIG3, PUMA, and GADD45α. The expression of proapoptotic and antiapoptotic markers in NEK9-depleted cells were mainly cell-dependent, despite their p53 wild-type status. A kinase-inactive variant (D194N) and RCC1-deletion variant (ΔRCC1) of NEK9 were shown to cause a delay in the S-phase of cells. Cells with prolonged expression of these variants also exhibited signs of apoptosis. Altogether, these findings support the hypothesis that NEK9 acts as a transcriptional regulator to p53-regulated genes responsible for the induction of cell cycle arrest and apoptosis. A high throughput in vivo screen was developed to identify NEK9 substrates. Co-localization between an mCherry-NEK9-LacI fusion protein with a GFP-tagged NEK6 consensus site indicated a positive interaction. However, co-localization was also detected between an mCherry-LacI fusion protein that lacked NEK9 and the GFP-tagged NEK6 consensus sequence, suggesting further optimization of the assay is required. Establishment of NEK9’s binding partners would aid in characterizing it’s involvement in various cellular pathways. Additionally, this thesis set out to map the temporal expression of adenoviral genes during infection of normal human cells. The boundaries of early, intermediate, and late viral gene activation were defined and discussed. Overall, these results detail the transcriptional cycle of adenovirus, by carefully examining the chronological events that occur during infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".