Abstract 2215: Detection of novel markers of transitional cell carcinoma of the ovary, the TCC-like variant of high grade serous carcinoma, using proteomics and immunohistochemistry
Bibliographic record
Abstract
Abstract Background: The current WHO classification does not separate transitional carcinoma of the ovary (TCCO) from conventional high grade serous carcinoma of the ovary (HGSC). TCCO has a better prognosis, possibly due to better chemosensitivity or less infiltrative growth pattern. The available immunohistochemical (IHC) markers do not differentiate between the two subtypes. Therefore, we sought to compare the proteomic profiles of conventional HGSC and TCCO to identify surrogate biomarkers of good prognosis from TCCO that could identify conventional HGSC tumors with a better prognosis. Design: Full proteome analysis of 12 cases of TCCO and 12 cases of HGSC was performed using SP3-clinical proteomics, run on an ThermoFisher Orbitrap Fusion. For validation, tissue microarrays of TCCO (n=89) and HGSC (n=237) were immunostained with antibodies against proteins found to be enriched in TCCO. All cases and immunostains were scored by a gynecologic pathologist. Univariate analysis was performed comparing IHC expression in TCCO vs. HGSC. Results: We identified 1220 proteins that were significantly enriched in TCCO over HGSC. Claudin 4 and Ubiquitin carboxyl-terminal esterase L1 (UCHL1) were selected as potential markers of TCCO-like biology (p=0.0017, 0.0322). By IHC, Claudin 4 (95% confidence interval (CI) 0.171, 0.430) and UCHL1 (95% CI 0.291, 0.550) showed a significantly higher expression in TCCO as compared to HGSC (see table). % of tumors with high immunoreactivity scoresClaudin 4UCHL1Pure TCCO34/59 (58%)26/59 (44%)Mixed TCCO-HGSC, TCCO component14/29 (48%)8/29 (28%)Mixed TCCO-HGSC, HGSC component19/28 (68%)6/28 (21%)Conventional HGSC33/235 (14%)32/237 (14%) Legend: Mixed TCCO: TCCO with minor component of conventional HGSC Conclusion: Proteomic analysis showed differing protein profiles for TCCO and HGSC. By IHC, Claudin 4 and UCHL1 were identified as potential markers for TCC-like differentiation of high-grade serous carcinomas. Further studies will focus on the prognostic significance of these and other markers in larger cohorts of HGSC. This study presents a novel approach at identifying potential diagnostic and prognostic biomarkers as well as therapeutic targets. Citation Format: Basile Tessier-Cloutier, Jamie Magrill, Stefan Kommoss, Blake C. Gilks, David G. Huntsman, Dawn R. Cochrane, Aline Talhouk, Robert Soslow, Gregg B. Morin, Chris J. Hughes, Anthony N. Karnezis, Christine Chow, Angela S. Cheng, Andreas du Bois, Jacobus Pfisterer, Friedrich Kommoss. Detection of novel markers of transitional cell carcinoma of the ovary, the TCC-like variant of high grade serous carcinoma, using proteomics and immunohistochemistry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2215. doi:10.1158/1538-7445.AM2017-2215
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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 | 0.001 | 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".