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Abstract B031: Loss of GATA6 leads to reduced cell fitness and PDA molecular subtype changes

2022· article· en· W4309185558 on OpenAlexaff
Tristan S.D. Woo, Kena F. Figueroa, Sabrina Ge, Irene Y. Xie, Karen Ng, Pinjiang Cao, Julie M. Wilson, Stephanie Ramotar, Jennifer J. Knox, Grainne M. O’Kane, Steven Gallinger, Faiyaz Notta

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity Health NetworkOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsGATA6BiologyCancer researchGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Background: Pancreatic ductal adenocarcinoma (PDA) is defined by two main transcriptional subtypes, Basal-like & Classical. Classical tumors are more frequent and tend to respond better to chemotherapy with higher expression of genes related to pancreatic lineage development, the epithelial compartment, and adhesion. Conversely, Basal-like tumors are more aggressive, therapy resistant and have higher expression of laminins and keratins. The Classical subtype correlates with GATA6 expression, and ~16% pancreatic tumors show amplification in the transcription factor GATA6 suggesting its importance in the Classical subtype and in tumor survival (Chan-Seng-Yue et al., 2020). The goal of this project is to elucidate the role of GATA6 expression in PDA tumors showing that GATA6 is a key molecular regulator of the Classical subtype influencing tumor growth, maintenance, and phenotype. Methods: Patient derived organoids (PDOs) spanning the spectrum of GATA6 expression were used with CRISPR/Cas9 to establish GATA6 KO lines (n=8). These were then subject to a growth competition assay between cells with and without GATA6 KO and the amount of knockout over time was monitored by Sanger sequencing. Tumor growth curves were generated in a subcutaneous xenograft mouse model over 1.5 months to assess the in vivo growth potential of GATA6 KO cells in a sample with high GATA6 expression. 3’RNA-seq was used to assess gene expression changes in subtype, and GSEA was used to assess pathway enrichment. This was done alongside IHC, capillary Westerns, and flow cytometry to assess changes that GATA6 KO incurs on a functional level. Results: GATA6 KO tended to result in reduced fitness (dropout) in cells when ablated, although the rate and level of dropout varied, suggesting different levels of dependence on GATA6 expression for survival/growth. This was confirmed in vivo when the GATA6 KO failed to grow as robustly as control groups in a sample with high native GATA6 expression. Molecular analysis of all PDO samples showed shifts in expression from Classical to Basal-like. This shift was denoted in changes in subtype score, changes in marker gene expression (i.e., ANXA10 & TP63), and in changes in key pathways associated with each subtype. This shows that GATA6 not only correlates with the Classical subtype but plays a causal role in maintaining it. Even though there was a shift towards Basal-like expression several key characteristics of the subtype were notably absent including enrichment for epithelial to mesenchymal transition, down regulation of MYC and its targets, and the lack of aggressive growth in in vitro and in vivo models (dropout of GATA6 KO cells, low Ki67 expression, and upregulation of apoptosis). This suggests that KO of GATA6 is not sufficient in of itself to cause a true Basal-like phenotype and that instead GATA6 KO might lead to an in-between state that does not quite offer the same growth advantages and may open GATA6 and its pathways to be a potential therapeutic target. Citation Format: Tristan S.D. Woo, Kena F. Figueroa, Sabrina Ge, Irene Xie, Karen Ng, Pinjiang Cao, Julie M. Wilson, Stephanie Ramotar, Jennifer J. Knox, Grainne M. O'Kane, Steven Gallinger, Faiyaz Notta. Loss of GATA6 leads to reduced cell fitness and PDA molecular subtype changes [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B031.

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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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.003

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 head0.048
GPT teacher head0.376
Teacher spread0.328 · 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
Published2022
Admission routes1
Has abstractyes

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