The IL-33/ILC2 axis in cancer : regulation, heterogeneity, plasticity, and immune activation during tumour development
Bibliographic record
Abstract
The tumour microenvironment plays a pivotal role in shaping immune responses to cancer, often promoting immune evasion through suppression of antigen presentation and disruption of innate and adaptive immune signaling. This thesis investigates the regulatory mechanisms governing the IL-33/ILC2 axis in solid tumours, integrating bioinformatics, molecular biology, single-cell transcriptomics, and spatial immunology to define their roles in tumour progression and immune modulation. Analysis of The Cancer Genome Atlas prostate adenocarcinoma dataset revealed that low IL-33 expression correlates with genomic instability, suppression of antigen presentation machinery, and immune-depleted tumour states. FOXA1 emerged as a candidate upstream regulator, showing inverse expression correlation with IL-33 and enrichment of hotspot mutations in IL-33-low tumours. Functional assays suggested that FOXA1 indirectly modulates IL-33 expression and APM-related gene networks, potentially through chromatin-level mechanisms or co-factor interactions. We further characterized novel IL-33 splice variants with distinct subcellular localization and functional properties, where some isoforms were more potent in upregulating antigen-presentation-related molecules and others were more effective at stimulating ILC2 activation, suggesting that isoform-specific expression may fine-tune immune activation in the tumour context. To understand the effector populations downstream of IL-33, we conducted single-cell RNA sequencing on lung- and tumour- resident ILC2 during tumour progression, revealing significant heterogeneity including pro-inflammatory, regulatory, T-cell recruitment, and Th1-like transcriptional signatures that shifted dynamically with tumour burden and activation. Multiplex immunofluorescent staining in the TC1 tumour model revealed that IL-33 treatment promoted the accumulation and deeper infiltration of KLRG1⁺ ILC2s into the tumour parenchyma, accompanied by enhanced CD3⁺ T cell distribution. These data support a role for IL-33 in enhancing early immune activation through inflammatory ILC2 expansion and remodeling the TME to facilitate adaptive immune infiltration. Collectively, this work uncovers a complex regulatory network involving FOXA1, IL-33 isoform diversity, and ILC2 heterogeneity that governs tumour-immune interactions and positions ILC2s as critical, context-dependent mediators of anti-tumour immunity while highlighting therapeutic opportunities to exploit the IL-33/ILC2 axis in cancer immunotherapy.
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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 | 0.001 | 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".