The Significance of the Stromal Response in Breast Cancer: An Immunohistochemical Study of Myofibroblasts in Primary and Metastatic Breast Cancer.
Bibliographic record
Abstract
BACKGROUND: Gene expression profiling of breast cancer has demonstrated the importance of stromal response in determining the prognosis of invasive breast cancer. The host response to breast cancer is of increasing interest to pathologists and may be a future focus for novel pharmacological treatments. METHODS: This study describes the pattern of distribution of stromal myofibroblasts using immunostains for CD10 and smooth muscle actin (SMA) in 50 primary breast cancers and their matched nodal metastases (68.6% nodes positive and 31.4% nodes negative). The stroma within the tumor (intratumoral) and at the advancing tumor edge (peri-tumoral) was studied in both primary and nodal sites. A simple quantitative scoring system was employed for both immunostains. The correlation between expression of these markers by stromal cells and standard pathological prognostic factors of stage, grade, hormone receptor and Her-2 status was analysed. RESULTS: SMA-positive stromal cells were more abundant in peri-tumoral stroma compared with intratumoral stroma in both primary and metastatic lesions. SMA expression in the lymph node metastases showed a significant correlation with tumor stage. SMA expression in peri-tumoral stroma correlated with Her-2 status. CONCLUSION: The results of this study suggest that myofibroblasts, particularly those expressing SMA, might potentiate the progression of the carcinomatous process especially in nodal metastases. Thus these cells may be a potential therapeutic target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".