The tumor cell‐derived matrix of lobular breast cancer: a new vulnerability
Bibliographic record
Abstract
Abstract Invasive lobular carcinoma (ILC) of the breast is a very common disease. Despite its prevalence, these tumors are relatively understudied. One reason for this is a relative lack of models for ILC. This challenge was addressed by Brisken and colleagues through development of an intraductal injection‐based xenograft system for the study of ERα + breast cancers, including both ILC and more common invasive ductal carcinoma (IDC; Sflomos et al , 2016). In this issue of EMBO Molecular Medicine, the same group have applied intraductal injection‐based xenografts to identify novel tumor cell‐specific transcriptional signatures in ILC (Sflomos et al , 2021). In doing so they found overexpression of lysyl oxidase‐like 1 (LOXL1) to be both responsible for the frequently seen stiff collagen‐rich extracellular matrix of lobular breast cancer and essential for their robust growth and metastatic dissemination in vivo , thereby identifying a novel therapeutic target.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".