MétaCan
Menu
Back to cohort

Abstract A134: The immunoregulatory enzyme IDO induces resistance to common chemotherapy drugs via base excision repair pathway

2016· article· en· W2407448809 on OpenAlexaff
Saman Maleki Vareki, Di Chen, Christine Di Cresce, Peter J. Ferguson, Mark Vincent, Wei‐Ping Min, Xiufen Zheng, James Koropatnick

Bibliographic record

VenueCancer Immunology Research · 2016
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsCancer researchImmune systemIndoleamine 2,3-dioxygenaseMedicineImmunotherapyCD8ImmunologyBiology

Abstract

fetched live from OpenAlex

Abstract Indoleamine 2,3-dioxygenase-1 (IDO) is an immune-regulatory enzyme expressed by most human tumors. IDO expression by tumor cells and the cells of the tumor microenvironment induces anergy and apoptosis in tumor-infiltrating NK cells, CD4+ and CD8+ T cells. IDO-mediated immune suppression is a major obstacle to successful immunotherapy. IDO levels are correlated with increased metastasis and poor patient outcome in many hematological and solid tumors. There is ample evidence that shows IDO induces resistance to ipilimumab and hinders its effectiveness against melanoma. We have recently shown that IDO induces resistance to the PARP inhibitor olaparib, ionizing radiation, and cisplatin independent of its immune-evading functions. However, our knowledge is limited about tumor cell-autonomous effects of IDO that are independent of its well known roles in regulating and suppressing anti-tumor immune responses. We therefore sought to study the underlying mechanism involved in IDO-mediated drug resistance. IFNγ was used to induce IDO in human lung adenocarcinoma A549 cells. Most cancer cells also express IDO in vivo in response to IFNγ production from immune cells. Clonal populations of A549 cells stably-transfected with anti-IDO shRNA or scrambled control shRNA were used to study IDO effects on drug sensitivity and resistance. We show, for the first time, that IDO mediates human tumor cell resistance to NAD+ inhibitor FK866, base excision repair (BER) inhibitor methoxyamine (MX), folate anti-metabolite pemetrexed, nucleoside analogue gemcitabine, and combined treatment with pemetrexed and MX, in the absence of immune cells. Concurrent knock-down of IDO and thymidylate synthase (TS), a key rate-limiting enzyme in DNA synthesis and repair, sensitizes human lung cancer cells to drugs that are commonly used in clinic, pemetrexed and 5FUdR. Based on the differential response of cancer cells to the different drugs we used in this study, we conclude that BER in IDO-expressing A549 cells plays a major role in inducing resistance to the drugs mentioned above. IDO inhibitors are under clinical trial mostly to improve the immune response towards cancer cells in patients. Our findings underlie the central role that IDO plays in not only suppressing the anti-tumor immune response but also causing resistance to common chemotherapeutics. Debulking the tumor and eradicating the immune-suppressive environment surrounding the tumor by pretreating patients with chemotherapy and radiation before immunotherapy could increase the chance of success for the latter. However, IDO could reduce the effectiveness of the treatment and therefore targeting IDO should be considered in studies that combine conventional chemotherapy with immunotherapy. Citation Format: Saman Maleki Vareki, Chen Di, Christine Di Cresce, Peter J. Ferguson, Mark Vincent, Weiping Min, Xiufen Zheng, James Koropatnick. The immunoregulatory enzyme IDO induces resistance to common chemotherapy drugs via base excision repair pathway. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A134.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.056
GPT teacher head0.348
Teacher spread0.292 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCancer Immunology ResearchSame topicTryptophan and brain disordersFrench-language works237,207