Abstract 521: c-MYC as a differentiating marker between angiosarcoma and atypical vascular lesion
Bibliographic record
Abstract
Abstract Introduction: Angiosarcoma is a rare, aggressive malignancy that accounts for less than 1% of all sarcomas, characterized by a dismal 5 year survival of 20-30% at best. In striking contrast, atypical vascular lesion (AVL), which typically occurs secondary to radiation, follows for the most part, a benign course. However, debate rages over the true nature of AVL with reports describing both benign and malignant behavior. Further compounding the issue is the fact that overlapping histological features make the important differentiation between AVL and angiosarcoma difficult, especially on limited biopsy specimens. There have been a number of recent studies of c-MYC expression in vascular tumors in relation to this question, yielding varied results. Objectives: This pilot study aimed to investigate c-MYC expression in atypical vascular lesions and angiosarcomas (primary and secondary) to evaluate the clinical utility of c-MYC testing as an adjunct to the histological diagnosis. Methods: A retrospective search for biopsy, resection specimens and internal consult cases with diagnosis of angiosarcoma and/or atypical vascular lesion from January 2008- February 2014 was performed. A total of 32 cases (including controls) obtained after review were stained by dual colour c-MYC copy number probe set. The expression of c-MYC was read by two independent evaluators and final data was collated along with histology findings, follow-up and survival data. Results: c-MYC amplification was found to be a major differentiating factor (p value: 0.00002, 68% sensitivity, 96% specificity) between AVL and angiosarcoma(median c-MYC expression 1.0 vs. 12.14, 95% confidence interval: 0.8-1.9 vs. 9.2-22.3 respectively). The amplification levels of primary (median c-MYC expression:10.9, 95% confidence interval: 3.8-16.6) and secondary angiosarcoma (median c-MYC expression:13.2, 95% confidence interval: 9.0-25.5) were statistically not found to be significantly different (p = 0.07). Although no correlation was found between level of c-MYC amplification and outcome, the study was underpowered to accurately evaluate this relation. Conclusion: Amplification of c-MYC can be used as a reliable ancillary test to differentiate between diagnostically challenging cases of angiosarcoma and AVL. Citation Format: Ipshita Kak, Bekim Sadikovic, Guillaume Pare, Tom Corbett, Snezana Popovic. c-MYC as a differentiating marker between angiosarcoma and atypical vascular lesion. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 521.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".