Hyaluronic Acid Present in the Tumor Microenvironment Can Negate the Pro-apototic Effect of a Recombinant Fragment of Human Surfactant Protein D on Breast Cancer Cells
Bibliographic record
Abstract
Human surfactant protein D (SP-D) belongs to the family of collectins that is composed of a characteristic amino-terminal collagenous region and a carboxy-terminal C-type lectin domain. Being present at the mucosal surfaces, SP-D acts as a potent innate immune molecule and offers protection against non-self and altered self, such as pathogens, allergens, and tumor. Here, we examined the effect of a recombinant fragment of human SP-D (rfhSP-D) on a range of breast cancer lines. Breast cancer has four molecular subtypes characterized by varied expressions of estrogen (ER), progesterone (PR), and epidermal growth factor (EGF) receptors (HER2). The cell viability of HER2-overexpressing (SKBR3) and triple-positive (BT474) breast cancer cell lines [but not of a triple-negative cell line (BT20)] was reduced following rfhSP-D treatment at 24 h. Upregulation of p21/p27 cell cycle inhibitors and p53 phosphorylation (Ser15) in rfhSP-D-treated BT474 and SKBR3 cell lines signified G2/M cell cycle arrest. Cleaved caspases 9 and 3 were detected in rfhSP-D-treated BT474 and SKBR3 cells, suggesting an involvement of the intrinsic apoptosis pathway. However, rfhSP-D-induced apoptosis was nullified in the presence of hyaluronic acid (HA) whose increased level in breast tumor microenvironment is associated with malignant tumor progression and invasion. rfhSP-D bound to solid-phase HA and promoted tumor cell proliferation. rfhSP-D-treated SKBR3 cells in the presence of HA showed decreased transcriptional levels of p53 when compared to cells treated with rfhSP-D only. Thus, HA appears to negate the anti-tumorigenic properties of rfhSP-D against HER2-overexpressing and triple-positive breast cancer cells.
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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 | 0.000 |
| 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) | 0.001 | 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".