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Discovery and Validation of Cell-Surface Protein Mesothelin (MSLN) As a Novel Therapeutic Target in AML: Results from the COG/NCI Target AML Initiative

2016· article· en· W2979530151 on OpenAlexaff
Katherine Tarlock, Allison Kaeding, Todd A. Alonzo, Michael R. Loken, Rhonda E. Ries, Laura Pardo, Robert B. Gerbing, Jason E. Farrar, Jaime M. Guidry Auvil, Daniela S. Gerhard, Malcolm A. Smith, Tanja M. Davidsen, Pattee Gesuwan, Leandro C. Hermida, Marco A. Marra, Andrew J. Mungall, Karen Mungall, Yussanne Ma, Stuart Zong, William D. Long, Alan S. Gamis, E. Anders Kolb, Soheil Meshinchi

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsBC Cancer AgencyCanada's Michael Smith Genome Sciences Centre
Fundersnot available
KeywordsMesothelinCancer researchBiologyHaematopoiesisCancerStem cellGenetics

Abstract

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Abstract In efforts to discover genes uniquely expressed in childhood AML, we performed transcriptomesequencing (RNA-Seq) in pediatric AML and contrasted the expression signature to that in normal marrow hematopoiesis. This effort led to the discovery of over 200 genes that lack expression in normal hematopoietic cells, but are variably expressed in pediatric AML cells. Mesothelin(MSLN) was discovered to be one of the most highly expressed genes in a subset of childhood AML cases (p<10-15).Mesothelin is a cell-surface protein that is expressed onmesothelial cells ofserosal lining. MSLN is over-expressed on a variety of solid tumors, including lung, pancreatic, and ovarian cancers, and is associated with increased malignant transformation, cellular proliferation, and tumor aggressiveness. Given its cell surface expression, MSLN has emerged as an attractive target for immunotherapeutic interventions in solid tumors in adults. In this study, RNA obtained from diagnostic bone marrow specimens from childhood AML (N=434) and normal marrow (N=20) was subjected to wholetranscriptomesequencing and MSLN expression was quantified and normalized and reported as reads perkilobaseof exon per million reads mapped (RPKM). Similar data was obtained from adult TCGA AML database. Quantitative RT-PCR (qRT-PCR) and multidimensional flowcytometry(MDF) was used for confirmation of the transcript and cell surface protein expression. TARGET AML methylation data was used for correlation with transcript expression. Of the 434 specimens analyzed, MSLN mRNA expression was variably expressed (RPKM range 0-618.8), with expression detected in 119 patients (27%). Confirmatory studies by qRT-PCR on specimens with and without MSLN expression (N=137) showed correlation between RNA-Seqand PCR data. Cell surface MSLN expression was assessed by MDF using a PE-conjugated MSLN antibody (PE-mesoAb) and verified expression of MSLN protein on the leukemic cell surface in every case with MSLN transcript expression (Figure 1A). Evaluation of CD34+/CD38- hematopoietic progenitor cells by PE-mesoAbdemonstrated lack of MSLN expression by MDF. Evaluation of matched diagnostic and relapse specimens from MSLN-expressing patients (n=27) confirmed that MSLN expression was largely stable (R2=0.87), thus substantiating its expression in the major AML clone. Comparison of MSLN expression in pediatric vs. adult AML demonstrated a higher prevalence in pediatric AML (TARGET: 27% vs. TCGA: 11%)(Figure 1B). Evaluation of the clinical and biologic features in MSLN expressing (MSLN+) and non-MSLN expressing (MSLN-) pediatric patients revealed that MSLN expression was rarely observed in patients with normal karyotype (p<0.001) or with the most common somatic mutations of FLT3/ITD, NPM1, CEBPA (p<0.001 in all cases). However, MSLN expression was significantly higher in patients with inv(16), t(8;21) and MLL translocations (p<0.001, p<0.001, and p=0.02 respectively; Figure 1C). Given that a majority of patients with core binding factor (CBF) AML were MSLN+, we evaluated the clinical implications of MSLN expression in this favorable risk cohort. Among CBF patients, MLSN+ patients (n=95) had a relapse risk of 51% vs. 32% in the MSLN- (n=62) cohort (p=0.03; Figure 1D), with a corresponding disease free survival of 46% vs. 64% respectively (p=0.03). We further inquired about the mechanism by which MSLN expression might be regulated. Whole genome sequencing data failed to identify any genomic alterations in MSLN that could result in high expression. Therefore, we interrogated the possibility of epigenetic regulation of MSLN expression. Integration of the expression and methylation profiling cases with matching RNA-Seqand methylation data (N=246) demonstrated thathypomethylationof the MSLN promoter significantly correlated with high MSLN expression, implicating epigenetic regulation in the expression of MSLN in AML. Mesothelin, a therapeutic target in solid tumors, is highly expressed in biologically distinct subsets of childhood AML. High expression on leukemic blasts and lack of expression in normal hematopoiesis makes this antigen an ideal target for therapeutic intervention in AML. As a cell surface protein, this antigen avails itself for immune targeting by antibody drug conjugates, CAR-T cells, and T cell receptor mediated targeting. Figure 1 Mesothelin expression in childhood AML. Figure 1. Mesothelin expression in childhood AML. Disclosures Loken: Hematologics: Employment, Equity Ownership. Pardo:Hematologics, Inc: Employment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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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Citations6
Published2016
Admission routes1
Has abstractyes

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