Exploring gastric cancer genetics: A turning point in common variable immunodeficiency
Bibliographic record
Abstract
Background: Gastric cancer (GC) stands as a prominent cause of cancer-related mortality and ranks second among the most frequently diagnosed malignancies in individuals with common variable immunodeficiency (CVID). Objective: We sought to conduct a comprehensive, large-scale genetic analysis to explore the CVID-associated germline variant landscape within gastric adenocarcinoma samples and to seek to delineate the transcriptomic similarities between GC and CVID. Methods: We investigated the presence of CVID-associated germline variants in 1591 GC samples and assessed their impact on tumor mutational load. The progression of GC was evaluated in patients with and without these variants. Transcriptomic similarities were explored by matching differentially expressed genes in GC to healthy gastric tissue with a CVID transcriptomic signature. Results: < .0001); high GC mutational load seems to be linked to immunotherapy response and worse prognosis. Transcriptomic similarities unveiled key genes and pathways implicated in innate immune responses and tumorigenesis. We identified upregulated genes related to oncogene drivers, inflammation, tumor suppression, DNA repair, and downregulated immunomodulatory genes shared between GC and CVID. Conclusions: Our findings contribute to a deeper understanding of potential molecular modulators of GC and shed light on the intricate interplay between immunodeficiency and cancer. This study underscores the clinical relevance of CVID-related variants in influencing GC progression and opens avenues for further exploration into novel therapeutic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".