Reduction of novel circulating long-chain fatty acids in colorectal cancer patients is independent of tumor burden and correlates with age
Bibliographic record
Abstract
BACKGROUND: Serum levels of novel hydroxy polyunsaturated ultra long-chain fatty acids (hPULCFAs) have been previously shown to be reduced in pre-treatment CRC patients compared to disease-free subjects, independent of disease stage. However, whether reduced levels of hPULCFAs result from the presence of cancer is currently unknown, as is the distribution of hPULCFAs in the general population. The following studies were carried out to assess whether conventional therapy would result in restoration of systemic hPULCFAs in CRC patients, and to investigate the relationship between hPULCFA levels and age. METHODS: Tandem mass spectrometry was used to determine serum levels of the 28 carbon-containing hPULCFA C28H46O4 (CRC-446) in the following cohorts: two independent Japanese CRC populations following surgical tumor removal (n = 86), a North American Caucasian CRC cohort (n = 150) following post-surgery combination chemo/radiation therapy, 990 randomly selected anonymized serum samples from subjects ranging between 11 and 99 years of age, as well as longitudinally collected serum samples from healthy normals (n = 8, up to 90 weeks) and stage IV CRC subjects on combination therapy (n = 12, up to 63 weeks). RESULTS: Serum CRC-446 levels in CRC subjects were significantly lower than controls (mean of 0.297 ± 0.07 ug/ml in controls versus 0.092 ± 0.03 in CRCs, p < 0.001), and were unaffected by surgical tumor removal or by chemo/radiation treatment (p > 0.05 between pre vs post surgery). CRC-446 levels showed a strong inverse association with age (p < E-11) across the randomly-selected cohort of 990 subjects, with no correlation observed in the CRC-positive subjects. Longitudinal intra-subject results, however, showed relatively stable CRC-446 levels over the short term of up to 90 weeks in both disease-free subjects and late-stage CRC patients. CONCLUSIONS: Our findings show that CRC-446 levels are not affected by conventional CRC treatment and inversely correlate with age, which suggest that reduced serum CRC-446 levels likely exist prior to the development of CRC. Extrapolation of the results to a simple screening scenario showed that, compared to fecal blood testing, pre-colonoscopy screening using serum CRC-446 levels would require 80% fewer colonoscopies, would identify risk in subjects under the age of 50, and would result in increased numbers of early cases detected. The precise role these serum metabolites play in the aetiology of cancer development remains to be determined.
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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 | 0.000 | 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 | 0.000 |
| 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".