Myeloid cells in circulation and tumor microenvironment of breast cancer patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pathological conditions including cancers lead to accumulation of a morphological mixture of highly immunosuppressive cells termed as myeloid-derived suppressor cells (MDSC). The lack of conclusive markers to identify human MDSC, due to their heterogeneous nature and close phenotypical and functional proximity with other cell subsets, made it challenging to identify these cells. Nevertheless, expansion of MDSC has been reported in periphery and tumor microenvironment of various cancers. The majority of studies on breast cancers were performed on murine models and hence limited literature is available on the relation of MDSC accumulation with clinical settings in breast cancer patients. The aim of this study was to investigate levels and phenotypes of myeloid cells in peripheral blood (n = 23) and tumor microenvironment of primary breast cancer patients (n = 7), compared with blood from healthy donors (n = 21) and paired non-tumor normal breast tissues from the same patients (n = 7). Using multicolor flow cytometric assays, we found that breast cancer patients had significantly higher levels of tumor-infiltrating myeloid cells, which comprised of granulocytes (P = 0.022) and immature cells that lack the expression of markers for fully differentiated monocytes or granulocytes (P = 0.016). Importantly, this expansion was not reflected in the peripheral blood. The immunosuppressive potential of these cells was confirmed by expression of Arginase 1 (ARG1), which is pivotal for T-cell suppression. These findings are important for developing therapeutic modalities to target mechanisms employed by immunosuppressive cells that generate an immune-permissive environment for the progression of cancer.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it