Abstract P2-09-01: MBC alliance: Coordinating metastatic research from lab bench to clinical trials
Bibliographic record
Abstract
Abstract The Metastatic Breast Cancer (MBC) Alliance[1] consists of non-profit advocacy, funding organizations and industry partners who seek to transform and improve the lives of women and men living with MBC. There is no cure for MBC and metastasis is the cause of virtually all breast cancer deaths. One objective of the Alliance is to understand the MBC research landscape from basic lab research through translational and clinical trials, to epidemiology, quality of life and patient reported outcomes. The MBC Alliance partnered with the International Cancer Research Partnership (ICRP[2]), an alliance of governmental and charitable organizations from the USA, Canada, Europe, Australia and Japan that fund regional, national and international cancer research grants and awards. The ICRP database of member’s funded grants contains >60,000 grants since 2000, from >80 member organizations, totalling over $14 billion USD. Each project is coded to a Common Scientific Outline (CSO), a classification system of broad areas of cancer research. Objective: To review the last ten years of breast cancer research grant funding related to metastasis and clinical trials to identify the most promising molecular targets, pathways and therapeutics in development for MBC. Methods: ICRP partner-funded grants related to MBC were queried from the ICRP database and clinical trials were queried from Clinicaltrials.gov and breastcancertrials.org. We also conducted interviews with 75 experts including advocates, scientists, clinicians, and leaders of professional societies and cooperative groups. The database searches resulted in a pool of 150 open clinical trials for MBC and 17,985 breast cancer-relevant grant awards. Relevant grant awards and clinical trials were then coded with the assistance of keywords and manual review, to one or more, of 6 categories relevant to the hallmarks of cancer (Hanahan & Weinberg[4]) and metastasis (Steeg[5]). Results: The ICRP database contained 2,250 unique awards related to MBC. The awards are predominantly basic research (70%) and translational (24%) and that profile has not changed significantly over a 5-year period 2008-2012. Awards active in 2012/2013 show that the main areas of focus are: i) early steps to invasion (10%) and, ii) metastatic colonization (15%). Data from 130 trials have been assigned to the Hanahan/Weinberg framework: sustaining proliferative signal, resisting cell death, enabling replicative mortality, genome instability and mutation, tumor promoting inflammation, activating invasion and metastasis, avoiding immune destruction, and other categories like cancer stem cells. Within these categories, the molecular targets of the drugs being used in the trial were further subdivided (e.g., PI3, RAF, CDK). Of the trials analyzed, 71 were Ph I or PhI/II, 47 Ph II and 11 Ph III. Conclusion: Using publicly available databases we were able to develop a comprehensive list of molecular targets, pathways and therapeutics for MBC that will enable improved coordination of MBC research. [1] https://www.mbcalliance.org/; [2] https://www.icrpartnership.org/index.cfm; [3] CSO 1.4 (Biology of progression) and keywords associated with metastasis.; [4] Hanahan D and Weinberg RA, Cell 2011;144:646-674.; [5] Steeg PS. Nature Medicine 2006;12(8)895-904. Citation Format: Marc S Hurlbert, Musa Mayer, Stephanie Reffey, Elly Cohen, Susan Colen, Samantha Finstad, Katherine McKenzie, Alison Butt, Ginny Mason, Lynne Davies. MBC alliance: Coordinating metastatic research from lab bench to clinical trials [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-09-01.
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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 | 0.162 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.078 | 0.045 |
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".