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Transcriptional Landscape of APL Identifies Aberrant Podoplanin Expression As a Defining Feature and Missing Link for the Bleeding Disorder of This Disease

2016· article· en· W2595557001 on OpenAlexaff
Vincent‐Philippe Lavallée, Miriam Marquis, Marie-Ève Bordeleau, Jalila Chagraoui, Tara MacRae, Isabel Boivin, Geneviève Boucher, Patrick Gendron, Sébastien Lemieux, Arnaud Bonnefoy, Georges E. Rivard, Josée Hébert, Guy Sauvageau

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineInstitute for Research in Immunology and CancerLeukemia & Lymphoma Society of CanadaUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsCancer researchPodoplaninGATA1MedicineBiologyImmunologyGeneGene expressionGeneticsLymphatic system

Abstract

fetched live from OpenAlex

Abstract Background:Acute promyelocytic leukemia (APL) is a favorable-risk subgroup of AML characterized by the t(15;17) translocation. The leading cause of early death in APL is uncontrolled bleeding mostly attributed to aberrant expression of tissue factor (F3) and annexin A2 (ANXA2) on leukemic promyelocytes leading to disseminated intravascular coagulation and hyperfibrinolysis, respectively. To prevent or treat such complications, early suspicion of APL and rapid initiation of therapy and supportive measures are critical. Podoplaninor PDPN is a surface glycoprotein expressed in most cell types (http://www.gtexportal.org), but not in blood cells. CLEC-2, the PDPN receptor, is expressed on normal platelets and was found to be necessary for the separation of blood and lymphatic vessels during embryogenesis. PDPN expression (whether endogenous or ectopic) in cell lines induces platelet aggregation, which can be inhibited by chemical tool compounds or by monoclonal antibodies (Chang et al, Oncotarget, 2015, Kato et al, Biochem. Biophys. Res. Commun., 2006). Aims and Methods:We analyzed the transcriptome of 30 APL comprised in the Leucegene 430 AML cohort, aiming to identify clinically useful markers and to better understand the hemostasis-related transcriptomic landscape of this subgroup. Patient cohorts and sorted normal hematopoietic cell populations (n=63) were previously reported (Lavallée et al, Nature Genetics, 2015 and Lavallée et al, Blood, 2016). Comparative analysis of gene expression and mutations were performed as previously described. Results:Our analytical pipeline identified several mutated genes in this cohort, most of which are non-specific and previously identified. CEBPE mutations were the only exception and were specific to APL specimens in this cohort (2/30 vs 0/400, p= 0.005). Most interestingly, we identified PDPN as the single most differentially overexpressed gene in APL (median 2.6 vs 0 RPKM, q = 7 x 10-29, Fig A-B). We also found that PDPN is not expressed in whole blood, bone marrow and in any sorted cell subpopulations from these normal tissues, including promyelocytes (median PDPN expression = 0 RPKM, range 0-0.018). This indicates that platelets are never exposed to PDPN in the adult vasculature and reveals that this gene is ectopically expressed in APL promyelocytes. Accordingly, our hypothesis is that aberrant PDPN expression on leukemic promyelocytes contributes to abnormal platelet aggregation in APL patients. We found that high PDPN expression is associated with lower platelet counts at presentation (18 vs 34 x 1012/L, median PDPN expression ≥ 10 vs < 10 RPKM, p = 0.016, Fig C). Furthermore, a strong inverse correlation was observed between the number of estimated circulating PDPN+ promyelocytes and platelet counts (leukocyte count x [% PDPN+ cells] > 1 x 109/L, Fig C, p=0.007). By incorporating anti-PDPN antibody (clone NC-08, Biolegend) in the EuroFlow protocol, we observed that PDPN expression test was 90% sensitive and 100% specific for APL (n= 48 and 50 APL and non-APL primary AML, respectively). Of note, 5 APL cases considered positive expressed low levels of PDPN. Interestingly, by comparing expression of all coagulation and fibrinolysis genes in APL (n=30) to that of non-APL specimens (n=400), we found that PDPN was the most discriminatory transcript (Fig. A). This result stands in sharp contrast with that found with F3 and ANXA2 which largely overlap in these APL versus non-APL human AML (Fig. A-B). This reinforces the hypothesis that aberrant PDPN expression may be a strong and unappreciated contributor to platelet consumption in APL. Conclusion:I) CEPBE is recurrently mutated in a small subset of APL patients. II) PDPN is the most specific aberrant transcript in this disease and is a new biomarker for APL. Systematic assessment of podoplanin by flow cytometry in newly diagnosed AML could lead to an earlier detection of unsuspected APL cases. III) PDPN expression by leukemic promyelocytes likely contributes to defective primary hemostasis, representing a new mechanism of APL-related bleeding. This provides a strong rationale for evaluating PDPN-CLEC-2 axis inhibitors in this setting. Figure Figure. Disclosures No relevant conflicts of interest to declare.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.016
GPT teacher head0.275
Teacher spread0.258 · 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".

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Citations2
Published2016
Admission routes1
Has abstractyes

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