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Abstract PR016: Investigating vulnerabilities associated with chromosome arm aneuploidy in cancer

2024· article· en· W4399504544 on OpenAlexaboutno aff
Nadja Zhakula-Kostadinova, Sejal Jain, Laura Byron, Alison M. Taylor

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyAneuploidyChromosome instabilityCancer researchCarcinogenesisCancerLung cancerChromosomeMetastasisGeneticsPathologyGeneMedicine

Abstract

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Abstract Aneuploidy – loss or gain of whole chromosomes or chromosome arms, is rare and poorly tolerated in normal cells but occurs in ∼90% of solid tumors; however, the mechanisms through which specific aneuploidies affect cancer development are unclear. Additionally, generating mammalian models of specific chromosome arm alterations is technically difficult, limiting further study. Cancers have tumor, cell, and tissue type-specific patterns of chromosome arm copy-number alterations that influence tumor evolution and sensitivity to anti-cancer therapies. Squamous cell carcinomas (SCCs) affecting lung, head and neck, esophageal, and cervical tissues have been shown to feature conserved early losses and gains of arms 3p and 3q, respectively, and are associated with relatively few oncogenic drivers and treatment options. These aneuploidies are particularly well established in lung SCC and have been shown to promote tumorigenesis, metastasis, and poor prognosis. To study cancer vulnerabilities associated with chromosome 3 arm aneuploidies, we used CRISPR-Cas9 to delete a 3p copy in human immortalized lung epithelial cell lines—the lung SCC cell-of-origin. A subset of clones duplicated a wild type chromosome 3 copy, transitioning to 3q gain and providing us with independent models for chromosome 3 wild type, 3p loss, and 3q gain. Next, we performed a CRISPRi screen and found that 3q gain cells are more sensitive to knockdown of sterol regulatory element-binding factor 1 (SREBF1)—a master regulator of cholesterol and fatty acid biosynthesis, its co-factor SREBP cleavage activating protein (SCAP), and downstream target HMG-CoA reductase (HMGCR)—the rate-limiting enzyme for cholesterol synthesis. 3q gain cells also showed up-regulated fatty acid metabolites, ceramides, triglycerides, and phosphatidylinositols. After performing a chemical screen, 3q gain cells showed reduced proliferation, increased apoptosis, and DNA damage in response to statins (HMGCR inhibitors). Statins have previously been shown to induce tumor-specific apoptosis and reduced cancer risk, although these studies have associated with variable efficacy and underlying mechanisms. We hypothesize that 3q gain is a biomarker of statin response and sensitivity in squamous cancers. We aim to study the mechanism through which aneuploidy alters lipid metabolism and contributes to cancer. Investigating aneuploidy-induced vulnerabilities will help us understand how cancers exploit aneuploidies to promote tumorigenesis and to elucidate novel and specific therapeutic targets for cancers with shared copy-number profiles. Citation Format: Nadja Zhakula-Kostadinova, Sejal Jain, Laura Byron, Matthew L. Meyerson, Alison M. Taylor. Investigating vulnerabilities associated with chromosome arm aneuploidy in cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr PR016.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.024
GPT teacher head0.289
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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