Identification of neutrophil-derived proteases and angiotensin II as biomarkers of cancer cachexia
Bibliographic record
Abstract
BACKGROUND: Cachexia is a metabolic disorder characterised by muscle wasting, diminished response to anti-cancer treatments and poor quality of life. Our objective was to identify blood-based biomarkers of cachexia in advanced cancer patients. Hence, we characterised the plasma cytokine and blood cell mRNA profiles of patients grouped in three cohorts: patients with cachexia, pre-cachexia (no cachexia but high CRP levels: ⩾ 5 mg l⁻¹) and no cachexia (no cachexia and CRP: < 5 mg l⁻¹). METHODS: A total of 122 newly diagnosed cancer patients with seven cancer types were studied prior to their initial therapy. Plasma levels of 22 cytokines were quantified using the bio-plex technology. mRNAs isolated from whole blood and expression profiles were determined by the chip array technology and Ingenuity Pathway Analysis (IPA) software. RESULTS: In comparison with non-cachectic individuals, both pre-cachectic and cachectic patients showed an increase (⩾ 1.5-folds) in mRNA expression of neutrophil-derived proteases (NDPs) and significantly elevated angiotensin II (Ang II) (P = 0.005 and P = 0.02, respectively), TGFβ1 (P = 0.042 and P < 0.0001, respectively) and CRP (both P < 0.0001) in the plasma. Moreover, cachectic patients displayed a significant increase in IL-6 (P = 0.005), IL-8 (P = 0.001) and absolute neutrophil counts (P = 0.007). CONCLUSIONS: Ang II, TGFβ1, CRP and NDP are blood biomarkers for cancer cachexia. These findings contribute to early diagnosis and prevention of cachexia.
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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".