RB1 Status in Triple Negative Breast Cancer Cells Dictates Response to Radiation Treatment and Selective Therapeutic Drugs
Bibliographic record
Abstract
Triple negative breast cancer (TNBC) includes basal-like and claudin-low subtypes for which only chemotherapy and radiation therapy are currently available. The retinoblastoma (RB1) tumor suppressor is frequently lost in human TNBC. Knockdown of RB1 in luminal BC cells was shown to affect response to endocrine, radiation and several antineoplastic drugs. However, the effect of RB1 status on radiation and chemo-sensitivity in TNBC cells and whether RB1 status affects response to divergent or specific treatment are unknown. Using multiple basal-like and claudin-low cell lines, we hereby demonstrate that RB-negative TNBC cell lines are highly sensitive to gamma-irradiation, and moderately more sensitive to doxorubicin and methotrexate compared to RB-positive TNBC cell lines. In contrast, RB1 status did not affect sensitivity of TNBC cells to multiple other drugs including cisplatin (CDDP), 5-fluorouracil, idarubicin, epirubicin, PRIMA-1(met), fludarabine and PD-0332991, some of which are used to treat TNBC patients. Moreover, a non-biased screen of ∼3400 compounds, including FDA-approved drugs, revealed similar sensitivity of RB-proficient and -deficient TNBC cells. Finally, ESA(+)/CD24(-/low)/CD44(+) cancer stem cells from RB-negative TNBC lines were consistently more sensitive to gamma-irradiation than RB-positive lines, whereas the effect of chemotherapy on the cancer stem cell fraction varied irrespective of RB1 expression. Our results suggest that patients carrying RB-deficient TNBCs would benefit from gamma-irradiation as well as doxorubicin and methotrexate therapy, but not necessarily from many other anti-neoplastic drugs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".