Evidence map›Paper›PMID 33666652›Full record

ArticleBlood advances2021

Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis.

Sebastiano Rontauroli, Sara Castellano, Paola Guglielmelli, Roberta Zini, Elisa Bianchi, Elena Genovese, Chiara Carretta, Sandra Parenti, Sebastian Fantini, Selene Mallia and 22 more

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Prognostic and Predictive Models in Myelofibrosis.Current hematologic malignancy reports · 2024
    Review
  3. Article
  4. Review
  5. Review
  6. Article
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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

32 authors at 7 institutions in 2 countries.

Sebastiano RontauroliCentre for Regenerative Medicine, Life Sciences Department.
Sara CastellanoCenter for Genome Research.
Paola GuglielmelliCenter for Research and Innovation for Myeloproliferative Neoplasms (CRIMM), Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Roberta ZiniCentre for Regenerative Medicine, Life Sciences Department.
Elisa BianchiCentre for Regenerative Medicine, Life Sciences Department.
Elena GenoveseCentre for Regenerative Medicine, Life Sciences Department.
Chiara CarrettaCentre for Regenerative Medicine, Life Sciences Department.
Sandra ParentiCentre for Regenerative Medicine, Life Sciences Department.
Sebastian FantiniCentre for Regenerative Medicine, Life Sciences Department.
Selene MalliaCentre for Regenerative Medicine, Life Sciences Department.
Lara TavernariCentre for Regenerative Medicine, Life Sciences Department.
Stefano SartiniCentre for Regenerative Medicine, Life Sciences Department.
Margherita MirabileCentre for Regenerative Medicine, Life Sciences Department.
Carmela MannarelliCenter for Research and Innovation for Myeloproliferative Neoplasms (CRIMM), Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Francesca GesulloCenter for Research and Innovation for Myeloproliferative Neoplasms (CRIMM), Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Annalisa PacilliCenter for Research and Innovation for Myeloproliferative Neoplasms (CRIMM), Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Daniela PietraDepartment of Hematology Oncology, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
Elisa RumiDepartment of Hematology Oncology, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
Silvia SalmoiraghiHematology, ASST Papa Giovanni XXIII, Bergamo, Italy.
Barbara MoraDivision of Hematology, Ospedale ASST Sette Laghi, University of Insubria, Varese, Italy.
Laura VillaniCenter for the Study of Myelofibrosis, Foundation IRCCS Policlinico San Matteo, Pavia, Italy; and.
Andrea GrilliDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Vittorio RostiCenter for the Study of Myelofibrosis, Foundation IRCCS Policlinico San Matteo, Pavia, Italy; and.
Giovanni BarosiCenter for the Study of Myelofibrosis, Foundation IRCCS Policlinico San Matteo, Pavia, Italy; and.
Francesco PassamontiDivision of Hematology, Ospedale ASST Sette Laghi, University of Insubria, Varese, Italy.
Alessandro RambaldiHematology, ASST Papa Giovanni XXIII, Bergamo, Italy.
Luca MalcovatiDepartment of Hematology Oncology, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
Mario CazzolaDepartment of Hematology Oncology, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
Silvio BicciatoDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Enrico TagliaficoCenter for Genome Research.
Alessandro M VannucchiCenter for Research and Innovation for Myeloproliferative Neoplasms (CRIMM), Azienda Ospedaliero Universitaria Careggi, Florence, Italy.
Rossella ManfrediniCentre for Regenerative Medicine, Life Sciences Department.
MRC Centre for Regenerative Medicine · GBAzienda Ospedaliero-Universitaria Careggi · ITPoliclinico San Matteo Fondazione · ITUniversity of Modena and Reggio Emilia · ITUniversity of Pavia · ITOspedale Papa Giovanni XXIII · ITUniversity of Insubria · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myelofibrosis (MF) belongs to the family of classic Philadelphia-negative myeloproliferative neoplasms (MPNs). It can be primary myelofibrosis (PMF) or secondary myelofibrosis (SMF) evolving from polycythemia vera (PV) or essential thrombocythemia (ET). Despite the differences, PMF and SMF patients are currently managed in the same way, and prediction of survival is based on the same clinical and genetic features. In the last few years, interest has grown concerning the ability of gene expression profiles (GEPs) to provide valuable prognostic information. Here, we studied the GEPs of granulocytes from 114 patients with MF, using a microarray platform to identify correlations with patient characteristics and outcomes. Cox regression analysis led to the identification of 201 survival-related transcripts characterizing patients who are at high risk for death. High-risk patients identified by this gene signature displayed an inferior overall survival and leukemia-free survival, together with clinical and molecular detrimental features included in contemporary prognostic models, such as the presence of high molecular risk mutations. The high-risk group was enriched in post-PV and post-ET MF and JAK2V617F homozygous patients, whereas pre-PMF was more frequent in the low-risk group. These results demonstrate that GEPs in MF patients correlate with their molecular and clinical features, particularly their survival, and represent the proof of concept that GEPs might provide complementary prognostic information to be applied in clinical decision making.

Indexed as

Myeloproliferative DisordersPolycythemia VeraPrimary MyelofibrosisThrombocythemia, EssentialHumansTranscriptome

Identifiers

PMID33666652
PMCPMC7948267
OpenAlexW3134153489

What OpenQuestion holds

Textmetadata
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Registered trials

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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.