Bibliographic record
Abstract
Metastatic cancer is the leading cause of death in Canada. The personalized medical framework considers each patient’s genetic profile as a background to develop a specific treatment approach. Due to the success of early diagnostics, the mutational landscape of a tumour is mainly based on the sequencing data collected from early resected primary tumours, which do not necessarily reflect the mutational heterogeneity of the metastatic form of the disease and/or local recurrences underestimating tumour adaptational variations, challenging biomarker development and hindering therapeutic strategies of personalized medicine. This study has been designed to define the changes in metastatic potential of a developing tumour highlighting the immunological tumour properties, as one of emerging cancer hallmark. Microarray profiling of two separate paired cell lines of murine lung and prostate carcinomas allowed the detection of IFI44 and IL-33 as possible regulators of immunological properties within tumours. Significant down-regulation of these genes allows cancer cells with high metastatic potential to acquire capabilities to avoid destruction by the immune system via suppression of MHC-I expression. The immune-evasive phenotype allows tumour to obtain biological advantages resulting in the evasion of eradication by the immune system, which is a significant barrier for tumour growth and progression. Further study found that the overexpression of these selected genes reverses the antigen presentation deficiency in murine metastatic lung carcinoma and makes the tumour recognizable to the immune system. A parallel human study demonstrated that the expression of IL-33 is also co-regulated with HLA-I levels in human prostate cancer. Moreover, IL-33 by itself may be used as an immune prognostic biomarker for recurrence and survival in human prostate and kidney renal clear cell carcinomas. This new link in cancer biology allowed for the development a novel immunotherapeutic strategy for cancer-free survival via IL-33/ILC2 axis and the use of adoptively-transferred ILC2s. Testing this strategy on ILC2-deficient animals and animals that received ILC2s via adoptive transfer showed the importance of IL-33 and ILC2s in reducing tumour growth rate and metastatic spread to distal organs. Collectively, this thesis demonstrates a new mechanism for tumour immune escape and suggests a novel immunotherapeutic approach for anti-cancer treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".