Quantification of Breast Cancer Cell Invasiveness Using a Three-dimensional (3D) Model
Bibliographic record
Abstract
It is now well known that the cellular and tissue microenvironment are critical regulators influencing tumor initiation and progression. Moreover, the extracellular matrix (ECM) has been demonstrated to be a critical regulator of cell behavior in culture and homeostasis in vivo. The current approach of culturing cells on two-dimensional (2D), plastic surfaces results in the disturbance and loss of complex interactions between cells and their microenvironment. Through the use of three-dimensional (3D) culture assays, the conditions for cell-microenvironment interaction are established resembling the in vivo microenvironment. This article provides a detailed methodology to grow breast cancer cells in a 3D basement membrane protein matrix, exemplifying the potential of 3D culture in the assessment of cell invasion into the surrounding environment. In addition, we discuss how these 3D assays have the potential to examine the loss of signaling molecules that regulate epithelial morphology by immunostaining procedures. These studies aid to identify important mechanistic details into the processes regulating invasion, required for the spread of breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".