Clinical Significance and Potential Molecular Mechanisms of Angiotensin-Converting Enzyme 2 in Colorectal Cancer
Bibliographic record
Abstract
Background: Angiotensin-converting enzyme 2 (ACE2) exhibits tumor-suppressive potential in cancers, but its role in colorectal cancer (CRC) is unclear. The aim of the study was to investigate ACE2 expression, clinical significance, and immune microenvironment associations in CRC. Methods: A multidimensional approach was taken using single-cell RNA sequencing and spatial transcriptomics to analyze ACE2 expression in CRC cells. High-throughput data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) (2,275 CRC and 1,269 adjacent tissues) were used to assess mRNA levels. Immunohistochemistry was performed to examine ACE2 protein expression in 66 CRC and 75 adjacent tissues. Molecular testing assessed associations with Kirsten rat sarcoma viral oncogene homolog (KRAS), neuroblastoma RAS viral oncogene homolog (NRAS), and B-Raf proto-oncogene, serine/threonine kinase (BRAF) mutations. Immune infiltration was analyzed using single-sample gene set enrichment analysis (ssGSEA), focusing on 24 immune cell types, CD8+ T cells, and programmed death ligand 1 (PD-L1) correlations. Results: ACE2 was highly expressed in malignant cells and Ki-67-activated regions. mRNA and protein levels were upregulated in CRC (standardized mean difference (SMD) = 0.321, area under the curve (AUC) = 0.844). High ACE2 exhibited significant associations with nerve invasion, lower expression in mucinous adenocarcinomas, and NRAS (Q61R/L/H/K) mutations. ACE2 negatively showed an inverse correlation with CD8+ T-cell infiltration (r = -0.186, P < 0.001) and PD-L1 expression (r = -0.282, P = 0.022). Conclusions: The upregulation of ACE2 is associated with nerve invasion, pathological type, and an immunosuppressive microenvironment with reduced CD8+ T-cell infiltration and PD-L1 expression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".