Abstract 4722: Evaluation of the prognostic value of ATG4B expression in different breast cancer subtypes
Bibliographic record
Abstract
Abstract Introduction: Autophagy, a lysosome-mediated degradation and recycling process, functions as an adaptive survival response during various stressful conditions including hypoxia and chemotherapy. The cysteine protease ATG4B, an important component of the autophagy pathway, is becoming a promising therapeutic target, but its value as a prognostic marker in breast cancer has not been investigated yet. Our recent studies established a novel association between ATG4B and HER2 positive breast cancer. Objective: The aim of this study was to investigate the prognostic value of ATG4B in different breast cancer subtypes using a large population-based cohort. Methods/Experimental Design: We evaluated ATG4B cytoplasmic expression by immunohistochemistry on tissue microarrays constructed from a cohort of 2003 breast cancer patients seen at the British Columbia Cancer Agency. For this large, well-characterized cohort detailed clinical information was available, including age, histology, tumor grade, tumor size, lymph node status, type of local and adjuvant systemic therapy, and dates of first recurrence and death. Median follow-up time was 12.4 years. ATG4B expression was scored by two independent observers using a categorized H-score system. Survival analyses were performed using the Kaplan-Meier function and Cox proportional hazards regression models to evaluate the association of ATG4B expression with breast cancer-specific survival, stratified by intrinsic subtype. Results: ATG4B expression was significantly lower in basal-like vs. non-basal (p<0.001), basal vs. HER2 overexpressed (p=0.0029), and triple-negative vs. non-triple-negative (p<0.001) breast cancer subtypes. In HER2 positive breast cancers, high (H-score >200) ATG4B expression was significantly associated with poor overall survival (hazard ratio (HR) =1.90, 95% confidence interval (CI) =1.10 to 3.27, p=0.033), disease specific survival (HR=2.23, CI =1.23 to 4.04, p=0.016), and relapse-free survival (HR=1.92, CI=1.09 to 3.39, p=0.037). However, in Luminal A breast cancers, high (H-score>150) ATG4B expression was strongly associated with improved overall survival (HR=0.71, CI=0.55 to 0.93, p=0.012) and disease-specific survival (HR=0.43, CI=0.26 to 0.67, p=0.00009). Conclusion: High ATG4B expression is a poor prognostic marker in HER2 positive breast cancer, but a favorable prognostic factor in the Luminal A subtype. Validation analyses are planned on a further set of 1989 cases. Citation Format: Svetlana Bortnik, Basile Tessier Cloutier, Jamie Magrill, Samuel Leung, Aline Talhouk, Karen Gelmon, Stephen Yip, Tony NG, Torsten Nielsen, Sharon Gorski. Evaluation of the prognostic value of ATG4B expression in different breast cancer subtypes [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 4722. doi:10.1158/1538-7445.AM2017-4722
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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 | 0.001 | 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) | 0.002 | 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".