Genetic Variation and Regulation of MICA Alters Natural Killer Cell-Mediated Immunosurveillance in Early-Onset Colorectal Cancer
Bibliographic record
Abstract
Abstract The incidence of colorectal cancer (CRC) among individuals under age 50, or early-onset CRC (EOCRC), has been rising over the past few decades for unclear reasons, and the etiology of the disease remains largely unknown. Known genetic risk factors do not explain this increase, pointing to possible environmental and as-yet unidentified genetic contributors and their interactions. Previous research linked genetic variation on chromosome 6 to increased CRC risk. This region harbors multiple immune genes, including the gene encoding Major Histocompatibility Complex (MHC) class I polypeptide-related sequence A (MICA). MICA is a polygenic ligand for the Natural Killer Group 2D receptor (NKG2D), a receptor expressed on Natural Killer (NK) cells and other lymphocytes. Given that intra-tumoral NK cell infiltration correlates with favorable CRC outcomes, we hypothesized that germline genetic variation in MICA could influence CRC risk. In a discovery set of 40,125 cases and controls, we show that the minor G allele at Chr6:31373718C>G (hg19) is associated with increased risk for CRC (odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.04 - 1.15, p = 0.0009). The effect is stronger in EOCRC (OR = 1.26, 95% CI 1.08 - 1.44, p = 0.0023) than in those 50 and over (OR = 1.07, 95% CI 1.02 - 1.13; p = 0.012) (Ratio of ORs = 1.32, 95% CI 1.14 - 1.52, p = 0.0002). In an independent validation set of 77,983 cases and controls, the adjusted interaction by age-of-onset was significant at OR = 1.15 (95% CI 1.03 - 1.34, p = 0.0150) with a higher risk in EOCRC. Expression quantitative trait locus analysis in normal colonic epithelia showed that MICA RNA expression decreases linearly with each additional copy of the minor G allele (p = 3.345 × 10e-18). Bulk RNA analysis of the tumor immune microenvironment revealed that tumors from patients with CG or GG genotypes have lower resting and activated NK cell infiltration as compared to tumors from patients with CC genotype. Multiplex immunofluorescence analysis demonstrated that patients with a G allele (i.e. CG or GG genotype, but not CC genotype) have a statistically significant decrease in the number of NK cells in tumor compared to adjacent normal colonic mucosa. Taken together, population-based epidemiologic, molecular, genetic, cellular and immunologic evidence demonstrate that MICA genotype is associated with increased risk of EOCRC and reduced number of NK cells in colorectal tumors, suggesting that patients with a G allele have altered NK cell-mediated immunosurveillance. These novel findings suggest that EOCRC may have a previously unrecognized innate immune-mediated etiology which merits further investigation.
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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) | 0.002 | 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".