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Abstract PO-056: Insulin receptor signaling in pancreatic acinar cells contributes to pancreatic cancer development

2021· article· en· W3213350334 on OpenAlexaff
Anni Zhang, Jenny C.C. Yang, Twan J. J. de Winter, David F. Schaeffer, Janel L. Kopp, James D. Johnson

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHyperinsulinemiaEndocrinologyInternal medicinePancreatic Intraepithelial NeoplasiaPancreasPancreatic cancerInsulinInsulin receptorAcinar cellBiologyMedicineCancerInsulin resistance

Abstract

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Abstract Hyperinsulinemia is a cardinal feature shared by both obesity and type 2 diabetes, and is independently associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). We previously showed a ~50% reduction in pancreatic intraepithelial neoplasia (PanIN) pre-cancerous lesions in mice with genetically reduced insulin production. Our single-cell transcriptomic data suggested that many pancreatic cell types could mediate the effects of local hyperinsulinemia on PanIN development. In pancreatic acinar cells from mice with reduced insulin, we found alterations in the PI3K/AKT/mTOR and MAPK/ERK pathways known to be involved in tumorigenesis. Here, we examined whether hyperinsulinemia contributes to PDAC development directly through insulin receptor signaling in KrasG12D expressing pancreatic acinar cells. To test this hypothesis, we generated Ptf1aCreER;LSL-KrasG12D;nTnG mice with an Insrwt/wt (PK-Insrwt/wt), Insrwt/fl (PK-Insrwt/fl), or Insrfl/fl (PK-Insrfl/fl) genotype to reduce insulin receptor signaling by 0%, 50%, or 100% in acinar cells, in both males and females. We fed the mice with high-fat diet (HFD) to induce systemic hyperinsulinemia and tracked body weight, fasting glucose and fasting insulin levels routinely. We euthanized the mice when they were 10 months old and performed blinded histopathological analysis and immunohistochemistry staining of the pancreatic sections to assess the PanIN formation. Loss of insulin receptors from acinar cells did not significantly influence body weight, fasting glucose or fasting insulin levels. Alcian blue staining of mucins contained within low-grade PanINs showed that there was a significant reduction in these pre-cancerous lesions in PK-Insrwt/fl and PK-Insrfl/fl female mice compared to PK-Insrwt/wt mice and the difference was Insr gene dosage-dependent. By performing immunohistochemical staining of CK19, marking duct and duct-like cells, we found there was a significant reduction of CK19+ area in PK-Insrwt/fl and PK-Insrfl/fl mice compared to PK-Insrwt/wt mice, and the reduction was Insr gene dosage-dependent. Finally, we found a significant increase in retention of normal acinar cells in PK-Insrfl/fl mice compared to PK-Insrwt/wt mice, which indicates the mice losing Insr had more wild-type like pancreas. Collectively, these data strongly suggest that insulin receptor signaling in acinar cells is important for the metaplasia formation, but do not exclude a role of Insr on other local or distant cell types. Prophylactic approaches targeting insulin receptor signaling pathways, or hyperinsulinemia itself, may be beneficial in preventing pancreatic cancer. Citation Format: Anni M. Y. Zhang, Jenny C. C. Yang, Twan J. J. de Winter, David F. Schaeffer, Janel L. Kopp, James D. Johnson. Insulin receptor signaling in pancreatic acinar cells contributes to pancreatic cancer development [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-056.

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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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.096
GPT teacher head0.426
Teacher spread0.330 · 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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