Identifying stromal-epithelial interactions in the mammary gland through genome-wide siRNA screening.
Bibliographic record
Abstract
Abstract Abstract #101 Stromal-epithelial interactions have been implicated in all stages of mammary gland development and malignancy. Although stromal composition is dynamic over time, fibroblasts account for a large proportion of the cellular compartment. The relationship between the fibroblasts and the mammary epithelial cells hitherto remains ill defined. A striking example of the relationship between the two cell types lies in the obligatory requirement for fibroblasts in the Colony Forming Assay (CFC assay). When plated with irradiated fibroblasts, mammary epithelial cells obtained from dissociated normal tissues are able to form colonies containing either all myoepithelial cells, all luminal cells or both. Mixed colonies represent derivation from bipotent progenitor cells, the most primitive detectable cell within the breast lineage hierarchy. The fibroblast dependency exhibited by primitive cells within the CFC assay is mimicked by the 184-hTERT cell line. This is a heterogeneous normal mammary epithelial cell line immortalized through the forced expression of human telomerase. A series of clonal cell lines was derived from the earliest available passage of 184-hTERT cells and 14 unique telomerase integration sites were found amongst the original cells. Interestingly, all of these clonal lines have the propensity to selectively gain chromosome 20 during passaging. Copy number gain of chromosome 20 is associated with poor clinical prognosis in breast cancer and is thought to play a role in oncogenic progression. A genome-wide siRNA screen has been completed targeting the 184-hTERT cells in a modified CFC assay to identify genes that are involved in fibroblast dependant growth. The screen was done in parallel using an early passage diploid 184-hTERT clonal line and a later passage (48,XX,+20,+20) clonal line. Dharmacon's human siGENOME library was used to individually interrogate approximately 22,000 genes found within the NCBI RefSeq database. Effects on fibroblast dependant growth were established through cell counts derived from images collected on GE's InCell Analyzer and segmented using Cell Profiler. 4225 genes showed conservative statistically significant evidence of difference in cell counts using the Bonferroni-Holm multiple comparisons method in both or either of the cell lines. Of these, 534 have an annotated location on the plasma membrane. Receptors to obligatory media components including Insulin, EGF and Transferrin were captured in this dataset. Not all of these genes will be specific to fibroblast dependant growth and thus the cognate ligands to these targets have been identified and are currently being manipulated in the fibroblasts. Modified fibroblasts will be used in the CFC assay to judge effects on mammary progenitor cell growth and will be co-cultured with carcinoma cells to evaluate effects on proliferation. This global assessment of the interactions between normal and malignant epithelial cells with fibroblasts has broad spanning implications ranging from the culturing of mammary progenitor cells to therapeutic target selection. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 101.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".