Characterizing the <i>KRAS</i> G12C mutation in metastatic colorectal cancer: a population-based cohort and assessment of expression differences in The Cancer Genome Atlas
Bibliographic record
Abstract
Introduction: In metastatic colorectal cancer (mCRC), RAS mutations impart inferior survival and resistance to anti-epidermal growth factor receptor (EGFR) antibodies. KRAS G12C inhibitors have been developed and we evaluated how KRAS G12C differs from other RAS mutations. Patients and Methods: This retrospective review evaluated patients in British Columbia, Canada with mCRC and RAS testing performed between 1 January 2016 and 31 December 2018. Sequencing information from The Cancer Genome Analysis (TCGA) was also obtained and analysed. Results: Age at diagnosis, sex, anatomic location and stage at diagnosis did not differ by RAS mutation type. Progression free survival on first chemotherapy for patients with metastatic KRAS G12C tumours was 11 months. Median overall survival did not differ by RAS mutation type but was worse for both KRAS G12C (27 months) and non-G12C alterations (29 months) than wildtype (43 months) ( p = 0.01). Within the TCGA, there was no differential gene expression between KRAS G12C and other RAS mutations. However, eight genes with copy number differences between the G12C and non-G12C RAS mutant groups were identified after adjusting for multiple comparisons ( FITM2, PDRG1, POFUT1, ERGIC3, EDEM2, PIGU, MANBAL and PXMP4). We also noted that other RAS mutant mCRCs had a higher tumour mutation burden than those with KRAS G12C mutations (median 3.05 vs 2.06 muts/Mb, p = 4.2e–3) and that KRAS G12C/other RAS had differing consensus molecular subtype distribution from wildtype colorectal cancer (CRC) ( p < 0.0001) but not each other ( p = 0.14). Conclusion: KRAS G12C tumours have similar clinical presentation to other RAS mutant tumours, however, are associated with differential copy number alterations.
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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) | 0.001 | 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 | 0.000 |
| 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".