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Record W4362541389 · doi:10.1158/1538-7445.am2023-3539

Abstract 3539: Indoleamine-2,3-dioxygenase 2 (IDO-2) is expressed in hepatoblastoma cells and associated with metastatic state

2023· article· en· W4362541389 on OpenAlexaff
Lisandro Luques, Ashby Kissoondoyal, Emily De Sousa, Paula R. Quaglietta, David Malkin, Stefano Cairo, Émilie Indersie, Reto M. Baertschiger

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsIndoleamine 2,3-dioxygenaseHepatoblastomaMedicineKynurenineCarcinogenesisMalignancyCancer researchImmune systemInternal medicineCancerImmunologyBiologyTryptophan

Abstract

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Abstract Hepatoblastoma (HB) is the most common pediatric primary liver malignancy and represents about 1% of all pediatric tumors. Incidence of HB has been increasing in the past 10 years. Risk stratification of HB patients is established by the extent of the liver disease, patient age, levels of serum AFP and presence of metastatic disease. Currently, treatment and prognosis of HB patients relies on chemotherapy and complete tumor resection. Unfortunately, patients with high-risk HB (metastatic, unresectable, refractory and recurrent) have dismal prognosis. The molecular mechanisms underlying the aggressiveness and metastatic potential of the tumor have not been elucidated yet. Tryptophan-2,3-dioxygenase (TDO) and indoleamine-2,3-dioxygenase 1 and 2 (IDO 1 and IDO-2) are enzymes in mammals that catabolize tryptophan to kynurenine and its activity has been related with immunoregulation and tumorigenesis. While TDO and IDO-1 have been extensively studied before the discovery of IDO-2, the role of the later in tumorigenesis is still under evaluation. Expression of IDO-2 is normally found in liver, kidney, pancreas, brain and epididymis while a dysregulated expression was reported in different types of cancer. IDO-2 activity was found to affect both the immune cells activation status and also the proliferation, migration and survival of tumor cells both in vitro and in vivo. Despite being expressed in normal liver tissues, IDO-2 expression has never been assessed in HB cells. The aim of this study was to determine if IDO-2 mRNA is expressed in HB cell lines and to determine if this expression is correlated with patient risk classification. By using real-time RT-PCR, we determined the expression of IDO-2 in commercially available HepG2 cells and in three patient derived xenograft (PDX)-derived HB cell lines (HB214, HB279, HB 303) (high risk metastatic, high-risk non metastatic and-low risk, respectively). IDO-2 is expressed in both HepG2 cells and in the 3 PDX-derived cell lines. Data analysis by using linear mixed effects modelling followed by t-tests to examine specific comparisons showed significant differences between cell lines. Expression of IDO-2 in cells from the metastatic tumor (HB214) was significantly higher than in HepG2 and cells from non-metastatic disease (p<0.05). In conclusion, we report here for the first time that IDO-2 is expressed in HB cells. Although further investigation should be conducted in order to understand its specific role in HB, the findings in this work suggest that IDO-2 expression might be related with clinical tumor behavior. Citation Format: Lisandro Luques, Ashby Kissoondoyal, Emily De Sousa, Paula Quaglietta, David Malkin, Stefano Cairo, Emilie Indersie, Reto Baertschiger. Indoleamine-2,3-dioxygenase 2 (IDO-2) is expressed in hepatoblastoma cells and associated with metastatic state. [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 3539.

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: Observational · Consensus signal: none
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
Bibliometrics0.0000.000
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 head0.099
GPT teacher head0.368
Teacher spread0.269 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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