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Abstract B066: Elucidating the role of insulin receptor isoform expression in metastatic pancreatic ductal adenocarcinoma

2022· article· en· W4309185717 on OpenAlexaff
Lan Valerie Tao, James T. Topham, Joanna M. Karasinska, Erica S. Tsang, Andrew Metcalfe, Ali Hassan, Dawn Ashforth, Rachel Goodwin, Patricia A. Tang, Oliver F. Bathe, Janessa Laskin, Marco A. Marra, Daniel J. Renouf, David F. Schaeffer

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsVancouver Coastal Health Research InstituteOttawa HospitalSpinal Cord Injury BC
Fundersnot available
KeywordsInsulin receptorInsulinCancer researchBiologyEndocrinologyCancerInternal medicineMedicineInsulin resistance

Abstract

fetched live from OpenAlex

Abstract Introduction: While type 2 diabetes mellitus (T2DM) has been shown to be both a risk factor and consequence of pancreatic ductal adenocarcinoma (PDAC), the bidirectional relationship between T2DM and PDAC remains to be fully understood. Due to spatial proximity of insulin-producing beta cells, PDAC tumor cells are presumably exposed to a highly concentrated insulin microenvironment, which may contribute to the dysregulation of the insulin receptor gene INSR. There are two isoforms of insulin receptor: IR-A and IR-B. IR-A activity has been associated with oncogenic function and is upregulated in several cancer types. This leads to questions regarding the role of INSR and more specifically, how the ratio of the two isoforms may potentiate tumor aggressiveness in PDAC. Results: Using data from whole-genome and RNA sequencing of metastatic PDAC (mPDAC) from both the PanGen (n=70; NCT01855477) and Personalized Oncogenomics (n=22; NCT02155621) trials, we identified somatic copy loss of INSR in 39/92 (42%) patient tumors, with the majority of such cases (35/39; 90%) showing heterozygous copy loss. There was no statistical association between INSR copy status and PDAC transcriptomic subtypes. INSR expression was lower in basal-like versus classical subtype tumors (p=1.1e-4), and INSR expression was further attenuated in basal-like tumors with heterozygous copy loss of INSR (p=0.0041). The ratio of IR-A:IR-B expression was heterogenous across samples, and heightened IR-A:IR-B ratio was significantly (p<0.05) associated with expression of genes linked to the PI3K-Akt signaling axis (CCDC88A, THEM4) and glucose metabolism (HK1, G6PC, PKLR) in basal-like tumors. Interestingly,HK1 and IGF1R were significantly upregulated, independent of IR-A:IR-B ratio, among basal-like (p 9.1e-9 and p=1.4e-5, respectively) compared to classical subtype tumors. Conclusion: These data indicate that heightened IR-A:IR-B ratio is associated with the expression of key pathways converging on PI3K signalling and glucose metabolism in mPDAC, while highlighting that several IR-A:IR-B-associated gene correlations are unique to basal-like tumors. Such findings warrant further investigation of relative INSR isoform expression in mPDAC and pre-clinical models to elucidate the role of the oncogenic isoform, IR-A, in driving tumor aggressiveness in basal-like subtype tumors. Citation Format: Lan V. Tao, James T. Topham, Joanna M. Karasinska, Erica S. Tsang, Andrew Metcalfe, Hassan Ali, Dawn Ashforth, Rachel Goodwin, Patricia A. Tang, Oliver F. Bathe, Janessa Laskin, Marco Marra, Daniel J. Renouf, David F. Schaeffer. Elucidating the role of insulin receptor isoform expression in metastatic pancreatic ductal adenocarcinoma [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 B066.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.079
GPT teacher head0.410
Teacher spread0.331 · 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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Citations1
Published2022
Admission routes1
Has abstractyes

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