Abstract P3-14-08: Preclinical and clinical evidence about the use of betablockers for the treatment of triple negative breast cancer: A systematic review
Bibliographic record
Abstract
Abstract Introduction Triple negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer (BC) for which very limited therapeutic options are available. Recently, beta-blockers (BB) have been suggested to have favorable effects on the treatment of BC both in preclinical and clinical studies. Objective The aim of this systematic review was to collect evidence from preclinical and clinical studies concerning the scientific evidence for the repurposing of BBs in TNBC treatment. Methods PubMed database was searched for retrieving studies of interest published up to 30/01/2018. All preclinical studies using BC in vitro and in vivo models and assessing the effect of any molecule with sympatholytic or sympathomimetic activity on adrenoceptors were included. Clinical studies concerning BB were considered eligible. Two authors independently reviewed and screened title and abstract of retrieved references. Potentially relevant studies were further assessed through full-texts examination. One author extracted information from preclinical and clinical studies respectively. A second author subsequently reviewed the extracted data. The Newcastle-Ottawa scale was used for the quality assessment of clinical studies. Results A total of 616 study references were initially retrieved. Six additional records were retrieved through snowball search. A total of 62 preclinical studieswere included, of which 46 concerned in vitro and in vivo models of TNBC, i.e. cell cultures and/or animal studies (20 in vitro, 9 in vivo, and 17 in vivo/vitro). In vitro studies showed a high expression of β2 adrenoreceptors in TNBC cell lines. Propranolol, a non-selective β1/β2 antagonist, was reported to significantly decrease proliferation, migration and invasion of TNBC cells. Similar effects were also reported for carvedilol, a selective β2 antagonist and α1 antagonist. In vivo studies reported a reduction of metastasis, angiogenesis and tumor growth in animals exposed to propranolol..Clinical studies, reporting evidence from a total of four distinct retrospective observational cohort studies, showed a beneficial effect of BB in TNBC treatment: e.g. study#1: Overall Survival Hazard Ratio (HR)=0.35 (95%CI 0.12-1.00); study#2: metastasis HR=0.32 (95%CI 0.12–0.90); study3# Progression Free Survival: HR=0.52 (95%CI 0.34–0.79); study #4 Relapse Free Survival: HR=0.69 (95%CI 0.35–1.34). The overall quality of the clinical evidence collected was low. Conclusion: Preclinical evidence collected in this systematic review are in line with the results reported in the four clinical studies retrieved, pointing towards a beneficial effect of BB in the treatment of TNBC. However, given the overall low quality of available evidence, no definite conclusion may be drawn. The execution of large scale interventional clinical studies are warranted to shed light on the efficacy/effectiveness of BB in TNBC treatment. Aknowledgment: This study was supported by Fondazione decima regio “Olga e Raimondo Curri” Citation Format: Spini A, Roberto G, Gini R, Bartolini C, Bazzani L, Donnini S, Crispino S, Ziche M. Preclinical and clinical evidence about the use of betablockers for the treatment of triple negative breast cancer: A systematic review [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-14-08.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".