Telomere-Associated Changes in Nuclear Architecture of Cancer-Associated Macrophage-like Cells in Liquid Biopsies from Melanoma Patients
Bibliographic record
Abstract
During phagocytosis, tumor-associated macrophages (TAMs) can incorporate genetic material from tumor cells. The incorporation of extra genetic material may be responsible for advanced malignant behavior observed in some TAMs, making TAMs potentially important players in cancer progression. More recently, similar cells were described in the blood as cancer-associated macrophage-like cells (CAMLs). CAMLs may be equivalent to TAMs cells in the blood, and they express macrophage markers. However, their origin is still unclear. In a previous study, we showed for the first time the distinct telomere 3D structure of circulating tumor cells (CTCs) in melanoma and other cancers. In the present pilot study, we investigated, comparatively, the 3D telomere structure of CAMLs, CTCs and leucocytes from nine melanoma patients with metastatic cutaneous melanoma stage IV. CTC capture was performed by size-based filtration followed by cytological and immunocytological evaluation. Three-dimensional Quantitative Fluorescent in situ Hybridization was performed to measure differences in five 3D telomere parameters. Telomere parameters, such as number, length, telomere aggregates, nuclear volume, and a/c ratio, were compared among different cellular types (CTCs, CAMLs, and normal leucocytes). Three telomere parameters were significantly different between CAMLs and leucocytes. The combination of two telomere parameters (telomere length against the number of telomeres) resulted in the identification of two CAMLs subpopulations with different levels of genomic instability. Those populations were classified as profile 1 and 2. Profile 2, characterized by a high number of short telomeres, was observed in four of the nine melanoma patients. To our knowledge, this is the first pilot study to investigate 3D telomere parameters as hallmarks of nuclear architecture in CAMLs’ population in comparison to leucocytes from the same patient. Further studies involving a larger patient sample size are necessary to validate these findings and explore their potential prognostic value.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".