Evidence map›Paper›PMID 29675955›Full record

ArticleBritish journal of haematology2018

Rapid identification of BCR/ABL1-like acute lymphoblastic leukaemia patients using a predictive statistical model based on quantitative real time-polymerase chain reaction: clinical, prognostic and therapeutic implications.

Sabina Chiaretti, Monica Messina, Sara Grammatico, Alfonso Piciocchi, Anna L Fedullo, Filomena Di Giacomo, Nadia Peragine, Valentina Gianfelici, Alessia Lauretti, Rohan Bareja and 11 more

Open access · bronzeAbstract read
In one paragraph

Article in British journal of haematology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors at 6 institutions in 3 countries.

Sabina ChiarettiHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.ORCID 0000-0001-8499-4492
Monica MessinaHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.ORCID 0000-0003-3531-4766
Sara GrammaticoHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Alfonso PiciocchiGIMEMA Data Centre, GIMEMA Foundation, Rome, Italy.
Anna L FedulloHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Filomena Di GiacomoHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Nadia PeragineHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Valentina GianfeliciHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Alessia LaurettiHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Rohan BarejaDepartment of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA.
Maria P MartelliInstitute of Haematology, Centro Ricerche Onco-Ematologiche (CREO), University of Perugia, Perugia, Italy.
Marco VignettiHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Valerio ApicellaHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Antonella VitaleHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Loretta S LiDepartment of Paediatric Haematology/Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Cyril SalekInstitute of Haematology and Blood Transfusion, Prague, Czech Republic.
Olivier ElementoDepartment of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA.
Giorgio InghiramiDepartment of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY, USA.
David M WeinstockDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Anna GuariniDepartment of Molecular Medicine, "Sapienza" University, Rome, Italy.
Robin FoàHaematology, Department of Cellular Biotechnologies and Haematology, "Sapienza" University, Rome, Italy.
Sapienza University of Rome · ITCornell University · USDana-Farber Cancer Institute · USFondazione Gimema Onlus · ITInstitute of Haematology and Blood Transfusion · CZUniversity of Perugia · IT

Funding

CRLF2 signaling in B-cell acute lymphoblastic leukemiaR01CA151898 · NCI · DANA-FARBER CANCER INST · PI WEINSTOCK, DAVID MARC · 2010 to 2019
$3.4M
The identification and validation of mechanisms and biomarkers for relapse in diffuse large B-cell lymphoma (Administrative Supplement)R01CA194547 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI ELEMENTO, OLIVIER, TAM, WAYNE · 2015 to 2019
$2.6M
The Mechanism of DISC FormationR01AA017238 · NIAAA · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI RIEDL, STEFAN J · 2008 to 2012
$2.1M
NCI NIH HHS R01 CA151898NCI NIH HHS R01 CA194547
6 · The paper itself

Abstract

BCR/ABL1-like acute lymphoblastic leukaemia (ALL) is a subgroup of B-lineage acute lymphoblastic leukaemia that occurs within cases without recurrent molecular rearrangements. Gene expression profiling (GEP) can identify these cases but it is expensive and not widely available. Using GEP, we identified 10 genes specifically overexpressed by BCR/ABL1-like ALL cases and used their expression values - assessed by quantitative real time-polymerase chain reaction (Q-RT-PCR) in 26 BCR/ABL1-like and 26 non-BCR/ABL1-like cases to build a statistical "BCR/ABL1-like predictor", for the identification of BCR/ABL1-like cases. By screening 142 B-lineage ALL patients with the "BCR/ABL1-like predictor", we identified 28/142 BCR/ABL1-like patients (19·7%). Overall, BCR/ABL1-like cases were enriched in JAK/STAT mutations (P < 0·001), IKZF1 deletions (P < 0·001) and rearrangements involving cytokine receptors and tyrosine kinases (P = 0·001), thus corroborating the validity of the prediction. Clinically, the BCR/ABL1-like cases identified by the BCR/ABL1-like predictor achieved a lower rate of complete remission (P = 0·014) and a worse event-free survival (P = 0·0009) compared to non-BCR/ABL1-like ALL. Consistently, primary cells from BCR/ABL1-like cases responded in vitro to ponatinib. We propose a simple tool based on Q-RT-PCR and a statistical model that is capable of easily, quickly and reliably identifying BCR/ABL1-like ALL cases at diagnosis.

Indexed as

Fusion Proteins, bcr-ablGene Expression Regulation, LeukemicModels, BiologicalPrecursor Cell Lymphoblastic Leukemia-LymphomaReal-Time Polymerase Chain ReactionAdolescentAdultChildChild, PreschoolDisease-Free SurvivalFemaleHumansInfantInfant, NewbornMalePredictive Value of TestsBCR-ABL1 fusion protein, humanFusion Proteins, bcr-ablAcute lymphoblastic leukaemiaadultsBCR/ABL1-likeprognosistyrosine kinase inhibitors

Identifiers

PMID29675955
PMCPMC5975184
OpenAlexW2800118768

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.