Characteristic of Uterine Rhabdomyosarcoma by Algorithm of Potential Biomarkers for Uterine Mesenchymal Tumor
Bibliographic record
Abstract
BACKGROUND/AIM: Patients with uterine sarcoma comprise 2-5% of all patients with uterine malignancies; however, the morbidity of uterine sarcoma is low compared with that of other gynecological cancers. For many cases, malignant uterine tumors are diagnosed during follow-up of benign uterine leiomyoma. Of the uterine sarcomas, rhabdomyosarcoma is considered a mixed tumor containing components of epithelial cells and mesenchymal cells. Therefore, the onset of primary uterine rhabdomyosarcoma during follow-up of uterine leiomyoma is extremely rare. Rhabdomyosarcoma is a relatively common malignant tumor in children, but rhabdomyosarcoma in adults is extremely rare, accounting for approximately 3% of all patients with soft tissue sarcoma. Rhabdomyosarcoma in children is highly sensitive to chemotherapy and radiation therapy; however, the response to chemotherapy and radiation therapy in adult rhabdomyosarcoma is low and survival in adult rhabdomyosarcoma with metastatic lesions to other organs is approximately 14 months. We experienced a case of pleomorphic rhabdomyosarcoma during the follow-up of a uterine leiomyoma. MATERIALS AND METHODS: We examined the oncological properties of uterine rhabdomyosarcoma in adults using molecular pathological techniques on tissue excised from patients with uterine leiomyoma. RESULT: A differential diagnosis was made for this case by molecular pathology, which included candidate biomarkers for uterine smooth muscle tumors. The oncological nature of uterine rhabdomyosarcoma was found to be similar to the oncological properties of uterine leiomyosarcoma. However, in uterine rhabdomyosarcoma, LMP2/β1i-positive cells were clearly observed. CONCLUSION: It is expected that establishing a diagnostic and treatment method targeting characteristics of mesenchymal tumor cells will lead to the treatment of malignant tumors with a low risk of recurrence and metastasis.
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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 | 0.002 | 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) | 0.001 | 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".