Abstract P4-09-19: Comprehensive multiplatform molecular profiling identifies potentially targetable biomarkers in malignant phyllodes tumors of the breast
Bibliographic record
Abstract
Abstract Introduction: Malignant phyllodes tumors are rare breast malignancies (0.1% of all breast tumors) with limited effective treatment options for recurrent and metastatic disease. Recent trials indicated a potential for anti-angiogenic therapy in soft tissue sarcomas, which led us to investigate these pathways. Materials and Methods: Thirty-five malignant phyllodes tumors (including two cases with matched primary and metastatic tumors) were profiled using gene sequencing (Next-generation and Sanger), gene copy number analysis (in-situ hybridization), whole genome RNA expression, and protein expression (immunohistochemical assay). Results: RNA microarray assay showed consistent over-expression of genes involved in angiogenesis including VEGFA, Angiopoietin2, VCAM1, PDGFRA, PTTG1, and CYP3A5 in all cases analyzed (n=5). No mutations in KDR (VEGFR2) were detected (0/26). EGFR protein overexpression was observed in 25/26 (96%) of cases with amplification of the EGFR gene in 8 cases (33%). EGFR gene mutations were identified in 2 cases (8%) including one case with presumed pathogenic V774M mutation and one case with EGFRvIII mutation. The most common mutations included those of TP53 (50%) and PIK3CA (15%) while other mutations (BRCA1, BRCA2, RET, CDH1, MLH1, ATM) were rare affecting single phyllodes cases. Two cases with matched primary and metastatic cancers harbored the same mutations in both sites (PIK3CA/KRAS and RB1 gene mutations, respectively). Conclusions: Comprehensive multiplatform profiling approach to phyllodes tumors identifies various molecular alterations of which some are potentially actionable. Our data suggests that anti-angiogenic therapy may also be effective in patients with malignant phyllodes tumor. Evaluation of EGFR pathway discovered consistent protein over-expression but rare activating mutations, which necessitates refinement in patient selection targeting these pathways. Citation Format: Gatalica Z, Vranic S, Ghazalpour A, Xiu J, Ocal I, McGill J, Bender R, Discianno E, Sanati S, Reddy S, Pockaj B. Comprehensive multiplatform molecular profiling identifies potentially targetable biomarkers in malignant phyllodes tumors of the breast. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-09-19.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".