Abstract 115: KIR haplotype polymorphism determines innate susceptibility/resistance to childhood leukemia
Bibliographic record
Abstract
Abstract Background: The Killer-cell Immunoglobulin-like Receptor (KIR) genes encode receptors that are expressed on the surface of Natural Killer (NK) cells and a subset of T cells. The receptors regulate functional activities of these immune cells in the body. There exist seventeen distinct KIR genes in humans of which nine encode inhibitory, and six encode activating receptors, while two are pseudo genes. KIR haplotypes show extensive variability with respect to their repertoire of activating KIR genes. Humans may have none or up to six different activating KIR genes. The acquisition of these genes is believed to decrease activation threshold of NK cells in humans, and provide resistance to malignancy. Hypothesis: We hypothesized that the acquisition of activating KIR genes by an individual may protect him/her from childhood leukemia. Methods: We used the candidate gene approach. In a case-control study, we determined the presence or absence of different activating KIR genes using gene-specific primer pairs. The frequencies of each gene were compared between cases and controls using Chi2 test and multivariate logistic regression. Results: Our results show for the first time that the inheritance of activating KIR genes is associated with increased resistance to childhood leukemia (both B-ALL and T-ALL; in adjusted analysis p-values being as low as 1.14x10-7). Interestingly, this resistance increased as the number of activating KIR genes increased in the genome of the individual. Furthermore, we found that that this resistance/susceptibility is differentially modulated by co-inheritance of different inhibitory KIR-MHC class I gene pairs. Conclusions: The inheritance of activating KIR gene-containing haplotypes confers innate resistance to childhood leukemia. These receptors may serve as novel target molecules for therapeutic interventions in childhood leukemia. The study was supported by a research grant (≠2010-700554) from the Canadian Cancer Society Research Institute (CCSRI). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 115. doi:1538-7445.AM2012-115
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".