Osteopontin Level and Promoter Polymorphism in Patients with Metastatic Breast Cancer
Bibliographic record
Abstract
Background: Cancer initiation typically occurs when a proto-oncogene’s coding region undergoes mutation, resulting in uncontrollable cell growth and division, or when a tumour suppressor gene’s coding region is affected by a mutation that inhibits activity of the resulting gene product. The pathophysiologic result is, respectively, exaggerated cell-cycle growth or deficient programmed cell death. Osteopontin (opn) is an integrin-binding phosphoprotein that is expressed on the surface of normal cells. Osteopontin has a major role in diverse tumour components, especially those implicated in invasion and metastasis. In the present study, we aimed to illustrate the value of opn as a possible contributor in breast cancer (bca). Methods: This prospective study included 115 patients newly diagnosed with bca and distant metastasis who were recruited from the Oncology Center, Mansoura University, and the Department of Clinical Oncology and Nuclear Medicine, Mansoura University Hospital, Egypt. The patients recruited had been diagnosed with disseminated visceral metastasis (visceral crisis), with or without bone metastasis; patients with cranial metastasis were excluded from the study. All patients received first-line chemotherapy with docetaxel 75 mg/m2 plus cisplatin 75 mg/m2 or carboplatin 6 auc (area under the curve) on day 1 every 21 days for a maximum of 6 cycles or till development of toxicity. Trastuzumab (in cases of her2-positive disease) was given whenever possible (if government assistance or personal finances permitted). Serum levels of opn were assessed by enzyme-linked immunosorbent assay (elisa) before treatment was started. A group of 30 matched healthy women whose median serum opn level was 15 ng/dL were included, and that level was therefore defined as the cut-off value. In addition, opn gene mutation was determined by polymerase chain reaction (pcr). Correlations of pretreatment serum opn and opn gene mutation with various patient clinicopathologic variables, response to the treatment, progression-free survival (pfs), and overall survival (os) were assessed. Results: Mean serum opn was highest in her2-amplified bca (64.4 ± 42.3 ng/dL), and then in triple-negative bca (55.9 ± 34.7 ng/dL), followed by the luminal B and A subtypes (38.4 ± 33.1 ng/dL and 36.3 ± 32.2 ng/dL respectively, p = 0.017). Testing by pcr revealed that opn gene mutation was highest in triple-negative bca (85% opn mutant vs. 15% non-mutant), and then in her2-overexpressed bca (80% opn mutant vs. 20% non-mutant), followed by luminal B bca (61.9% opn mutant vs. 38.1% non-mutant); the least expression was detected in luminal A bca (57.9% opn mutant vs. 42.1% non-mutant). Interestingly, patients with high serum opn and opn gene mutation experienced both poor pfs (median: 12 months vs. 14 months; p = 0.001) and poor os (median: 14 months vs. 18 months; p = 0.001). Moreover, participants with opn gene mutation experienced a poor response: of those with progressive disease, 74% had opn mutation and 26% had unmutated opn (p = 0.04). Additionally, high pretreatment serum opn was correlated with poor treatment response: 49.1 ± 33.8 ng/dL in patients with progressive disease and 35.5 ± 34.3 ng/dL in those who achieved a complete response, a partial response, or stable disease (p = 0.05). Strong concordance was found between high serum opn and opn gene mutation in 69 tumours (79.3%), and strong concordance was detected between normal or low serum opn and non-mutant opn in 28 tumours (60.8%). Conclusions: The current prospective work helps to highlight opn as a valid prognostic biomarker for patients with metastatic bca and reveals that high pretreatment serum opn and opn gene mutation are both strongly linked with poor response and survival. Concordance between elisa and pcr results indicates that either method can be used for the evaluation of opn. Increased opn gene mutation in triple-negative bca could assist in tailoring the treatment response in this very aggressive tumour subtype and could be considered a targetable molecule in future studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".