A siRNA screen identifies RAD21 , EIF3H , CHRAC1 and TANC2 as driver genes within the 8q23, 8q24.3 and 17q23 amplicons in breast cancer with effects on cell growth, survival and transformation
Bibliographic record
Abstract
RNA interference has boosted the field of functional genomics, by making it possible to carry out 'loss-of-function' screens in cultured cells. Here, we performed a small interfering RNA screening, in three breast cancer cell lines, for 101 candidate driver genes overexpressed in amplified breast tumors and belonging to eight amplicons on chromosomes 8q and 17q, investigating their role in cell survival/proliferation. This screening identified eight driver genes that were amplified, overexpressed and critical for breast tumor cell proliferation or survival. They included the well-described oncogenic driver genes for the 17q12 amplicon, ERBB2 and GRB7. Four of six other candidate driver genes-RAD21 and EIF3H, both on chromosome 8q23, CHRAC1 on chromosome 8q24.3 and TANC2 on chromosome 17q23-were confirmed to be driver genes regulating the proliferation/survival of clonogenic breast cancer cells presenting an amplification of the corresponding region. Indeed, knockdown of the expression of these genes decreased cell viability, through both cell cycle arrest and apoptosis induction, and inhibited the formation of colonies in anchorage-independent conditions, in soft agar. Strategies for inhibiting the expression of these genes or the function of the proteins they encode are therefore of potential value for the treatment of breast cancers presenting amplifications of the corresponding genomic region.
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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 | 0.000 | 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) | 0.002 | 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 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".