Abstract 2632: Identification of PTHrP as a biomarker of short survival & brain metastasis in a tissue microarray retrospective analysis of triple-negative breast cancer
Bibliographic record
Abstract
Abstract Triple-negative breast cancer (TNBC) represents 10-20% of all BC cases, and is characterized by aggressive clinical course, frequent relapse, poor patient outcome, and lack of targeted therapy due to the lack of expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). Identifying TNBC molecular drivers and biomarkers would thus be highly beneficial to develop efficient targeted therapies. The parathyroid hormone-related protein (PTHrP) is known for its role in mammary gland and bone development, in addition to breast cancer progression. The aim of this study is to investigate the role of PTHrP as a potential prognostic biomarker in human TNBC. We assessed PTHrP expression using immunohistochemical analysis of a tissue microarray (TMA) constructed for 523 patients newly diagnosed with TNBC between January 1998 and December 2008 in a single-center series with centralized ER, PR and HER-2 testing and standardized treatment and follow-up. We evaluated the correlation between PTHrP expression and TNBC patients' clinico-pathological features as well as progression and survival outcomes for a subset of 314 patients with available clinical data. We show that PTHrP is overexpressed in 55.2% of TNBC tumors and high PTHrP expression is significantly associated with higher propensity for brain progression compared to other sites of distal progression (p=0.0458). Univariate analysis revealed that high PTHrP expression is significantly associated with decreased overall survival (OS) (p=0.0055), but not with progression-free survival (PFS) (p=0.1270). To further investigate the prognostic value of PTHrP with respect to different TNBC molecular subtypes, we analysed expression of markers known to stratify different TNBC subtypes. Multivariate analysis of PTHrP as an independent prognostic factor of survival with respect to different TNBC molecular subtypes is currently underway. In conclusion, we provide for the first time evidence that increased PTHrP expression is significantly associated with shorter OS and higher propensity of brain progression in patients diagnosed with TNBC. Consequently, stratification of this disease based on PTHrP expression might identify patients with relatively higher risk of aggressive disease with brain progression. Additional studies investigating the role of PTHrP in organ-specific metastasis and using PTHrP-targeting strategies are warranted to improve the therapeutic outcome for patients diagnosed with TNBC. Funding: Alberta Cancer Research Institute (ACRI) grant and Department of Defense (DoD, USA) Award No. W81XWH-15-1-0723 Citation Format: Gloria Assaker, Anne Camirand, Bassam Abdulkarim, Atilla Omeroglu, Jean Deschenes, Leon Van Kempen, Richard Kremer, Siham Sabri. Identification of PTHrP as a biomarker of short survival & brain metastasis in a tissue microarray retrospective analysis of triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2632.
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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".