ARID1A Mutation May Define an Immunologically Active Subgroup in Patients with Microsatellite Stable Colorectal Cancer
Bibliographic record
Abstract
Abstract Purpose: AT-rich interactive domain 1A (ARID1A) is commonly mutated in colorectal cancer, frequently resulting in truncation and loss of protein expression. ARID1A recruits MSH2 for mismatch repair during DNA replication. ARID1A deficiency promotes hypermutability and immune activation in preclinical models, but its role in patients with colorectal cancer is being explored. Experimental Design: The DNA sequencing and gene expression profiling of patients with colorectal cancer were extracted from The Cancer Genome Atlas and MD Anderson Cancer Center databases, with validation utilizing external databases, and correlation between ARID1A and immunologic features. IHC for T-cell markers was performed on a separate cohort of patients. Results: Twenty-eight of 417 patients with microsatellite stable (MSS) colorectal cancer (6.7%) had ARID1A mutation. Among 58 genes most commonly mutated in colorectal cancer, ARID1A mutation had the highest increase with frameshift mutation rates in MSS cases (8-fold, P < 0.001). In MSS, ARID1A mutation was enriched in immune subtype (CMS1) and had a strong correlation with IFNγ expression (Δz score +1.91, P < 0.001). Compared with ARID1A wild-type, statistically significant higher expression for key checkpoint genes (e.g., PD-L1, CTLA4, and PDCD1) and gene sets (e.g., antigen presentation, cytotoxic T-cell function, and immune checkpoints) was observed in mutant cases. This was validated by unsupervised differential expression of genes related to immune response and further confirmed by higher infiltration of T cells in IHC of tumors with ARID1A mutation (P = 0.01). Conclusions: The immunogenicity of ARID1A-mutant cases is likely due to an increased level of neoantigens resulting from increased tumor mutational burden and frameshift mutations. Tumors with ARID1A mutation may be more susceptible to immune therapy–based treatment strategies and should be recognized as a unique molecular subgroup in future immune therapy trials.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".