Abstract 1512: Evolution of large copy number variants in breast cancer through genetic network rewiring
Bibliographic record
Abstract
Abstract Large chromosomal alterations are common in cancer and often show preferential gain or loss across many cancer types indicating their selective advantage. Triple negative breast cancer (TNBC) exhibits complex mutational spectrum without common oncogenic drivers yet displays consistent loss of large chromosomal regions. Here, we characterize selection pressures that maintain a recurrently deleted region of chromosome 4p in TNBC. We used bulk WGS phylogenetic analysis of TNCB PT/PDX panel to show that chr4p deletion is an early event in tumor evolution. We used scRNAseq gene expression and inferred copy number analysis to show that chr4p loss is associated with a proliferative state. This finding was confirmed by a combination of RNA in situ hybridization and immunofluorescence. We then tested the dosage sensitivity of genes residing within this region by individual and dual overexpression in TNBC PDX-derived cell lines and control normal cell line by assessing their effect on cell proliferation. The overexpression of genes within chr4p elicited a strong cell proliferation defect in cancer but not normal cell line models. We also characterized an unknown gene within chr4p region as a novel member of the STRIPAK complex. Genome-wide pooled ORFeome library screens identified a global pattern of background-specific dosage sensitive regions. Our study shows that large chromosomal deletions are maintained due to evolutionary early genetic network rewiring rendering multiple genes within such regions to be dosage sensitive. Ultimately, this work enhances our understanding of genetic events that modulate TNBC. Citation Format: Elena Kuzmin, Jean Monlong, Mathieu Bourgey, Tom Lesluyes, Toby Barker, Genevieve Morin, Dongmei Zou, Michael Schwartz, Yang Yang, Alain Pacis, Constanza Martinez, Hellen Kuasne, Anne-Marie Fortier, Rui Li, Claudia Kleinman, Sidong Huang, Peter van Loo, Jiannis Ragoussis, Guillaume Bourque, Morag Park. Evolution of large copy number variants in breast cancer through genetic network rewiring [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1512.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".