Alternative Chemotherapies: Angiotensin-Converting Enzyme Inhibitors Reduce Myeloid-Derived Suppressor Cells to Benefit Older Patients with Colorectal Cancer
Bibliographic record
Abstract
Older individuals are more likely to develop solid cancers, but at the same time are more sensitive to the side effects of chemotherapy. In addition, older adults are more likely to present with chronic diseases (comorbidities) and immunosenescence that may decrease immunosurveillance against cancer. Clinical outcomes for the older patient with cancer are different from the younger patient and require different research and treatment approaches. Thus, alternative therapeutic approaches tailored specifically to the older patients are required. Colorectal cancer (CRC) has a high incidence in older individuals and is the third leading cause of cancer death globally. Anti-hypertensives are used by a large proportion of older patients and some studies have pointed to a positive impact of angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB) on CRC outcomes. As we have previously shown in a mouse model, lung metastases express ACE and contain many infiltrating myeloid-derived suppressor cells (MDSC); particularly high levels of MDSC are also present in the blood of older patients with CRC and other cancers, and are associated with disease severity. In this Commentary, we hypothesize that one mechanism responsible for the positive impact of ACEi or ARB on the outcome of CRC is the modulation of myeloid cells contributing to their maturation to non-suppressive neutrophils/monocytes and diverting them away from retaining an immature MDSC phenotype.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".