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Record W2270816365 · doi:10.18632/oncotarget.7235

Activation of the PD-1/PD-L1 immune checkpoint confers tumor cell chemoresistance associated with increased metastasis

2016· article· en· W2270816365 on OpenAlexafffundabout
Madison Black, Ivraym B. Barsoum, Peter Truesdell, Tiziana Cotechini, Shannyn K. Macdonald-Goodfellow, Margaret G. Petroff, D. Robert Siemens, Madhuri Koti, Andrew W. Craig, Charles H. Graham

Bibliographic record

VenueOncotarget · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsCancer researchImmune systemMetastasisPD-L1Immune checkpointMedicineProstate cancerDocetaxelImmunotherapyCytotoxic T cellCancerCancer cellDoxorubicinMetastatic breast cancerProgrammed cell deathImmunologyApoptosisBreast cancerChemotherapyBiologyInternal medicineIn vitro

Abstract

fetched live from OpenAlex

// Madison Black 1 , Ivraym B. Barsoum 1,2 , Peter Truesdell 1,4 , Tiziana Cotechini 1 , Shannyn K. Macdonald-Goodfellow 1 , Margaret Petroff 3 , D. Robert Siemens 1,2 , Madhuri Koti 1,4 , Andrew W.B. Craig 1,4 and Charles H. Graham 1,2,4 1 Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, Ontario, Canada 2 Department of Urology, Queen’s University, Kingston, Ontario, Canada 3 Department of Pathobiology and Diagnostic Investigation, Michigan State University, East Lansing, Michigan, USA 4 Cancer Biology and Genetics, Queen’s Cancer Research Institute, Kingston, Ontario, Canada Correspondence to: Charles H. Graham, email: // Keywords : PD-1, PD-L1, chemoresistance, immune escape, metastasis Received : December 04, 2015 Accepted : January 25, 2016 Published : February 07, 2016 Abstract The ability of tumor cells to avoid immune destruction (immune escape) as well as their acquired resistance to anti-cancer drugs constitute important barriers to the successful management of cancer. Interaction between the Programmed Death Ligand 1 (PD-L1) on the surface of tumor cells with the Programmed Death-1 (PD-1) receptor on cytotoxic T lymphocytes leads to inactivation of these immune effectors and, consequently, immune escape. Here we show that the PD-1/PD-L1 axis also leads to tumor cell resistance to conventional chemotherapeutic agents. Using a panel of PD-L1-expressing human and mouse breast and prostate cancer cell lines, we found that incubation of breast and prostate cancer cells in the presence of purified recombinant PD-1 resulted in resistance to doxorubicin and docetaxel as determined using clonogenic survival assays. Co-culture with PD-1-expressing Jurkat T cells also promoted chemoresistance and this was prevented by antibody blockade of either PD-L1 or PD-1 or by silencing of the PD-L1 gene. Moreover, inhibition of the PD-1/PD-L1 axis using anti-PD-1 antibody enhanced doxorubicin chemotherapy to inhibit metastasis in a syngeneic mammary orthotopic mouse model of metastatic breast cancer. To further investigate the mechanism of tumor cell survival advantage upon PD-L1 ligation, we show that exposure to rPD-1 promoted ERK and mTOR growth and survival pathways leading to increased cell proliferation. Overall, the findings of this study indicate that combinations of chemotherapy and immune checkpoint blockade may limit chemoresistance and progression to metastatic disease.

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 score0.004
Threshold uncertainty score0.012

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.226
Teacher spread0.215 · 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

Citations184
Published2016
Admission routes3
Has abstractyes

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