Effects of adipocyte-conditioned cell culture media on S1P treatment of human triple-negative breast cancer cells
Bibliographic record
Abstract
Sphingosine-1-phosphate (S1P) is a potent sphingolipid metabolite that regulates a wide range of biological functions such as cell proliferation, cell apoptosis and angiogenesis. Its cellular level is elevated in breast cancer, which, in turn, would promote cancer cell proliferation, survival, growth and metastasis. However, the cellular concentration of S1P is normally in the low nanomolar range, and our previous studies showed that S1P selectively induced apoptosis of breast cancer cells at high concentrations (high nanomolar to low micromolar). Thus, local administration of high-concentration S1P alone or in combination of chemotherapy agents could be used to treat breast cancer. The breast mainly consists of mammary gland and connective tissue stroma (adipose), which are dynamically interacting each other. Thus, in the current study, we evaluated how normal adipocyte-conditioned cell culture media (AD-CM) and cancer-associated adipocyte-conditioned cell culture media (CAA-CM) would affect high-concentration S1P treatment of triple-negative breast cancer (TNBC) cells. Both AD-CM and CAA-CM may suppress the anti-proliferative effect and reduce nuclear alteration/apoptosis caused by high-concentration S1P. This implicates that adipose tissue is likely to be detrimental to local high-concentration S1P treatment of TNBC. Because the interstitial concentration of S1P is about 10 times higher than its cellular level, we undertook a secretome analysis to understand how S1P would affect the secreted protein profile of differentiated SGBS adipocytes. At 100 nM S1P treatment, we identified 36 upregulated and 21 downregulated secretome genes. Most of these genes are involved in multiple biological processes. Further studies are warranted to identify the most important secretome targets of S1P in adipocytes and illustrate the mechanism on how these target proteins affect S1P treatment of TNBC.
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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) | 0.001 | 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 | 0.001 |
| 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".