Evidence map›Paper›PMID 40211380›Full record

ArticleCell communication and signaling : CCS2025

A network-based approach to overcome BCR::ABL1-independent resistance in chronic myeloid leukemia.

Valeria Bica, Veronica Venafra, Giorgia Massacci, Simone Graziosi, Sara Gualdi, Gessica Minnella, Federica Sorà, Patrizia Chiusolo, Maria Elsa Brunetti, Gennaro Napolitano and 6 more

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In one paragraph

Article in Cell communication and signaling : CCS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Valeria Bica *Ph.D. Program in Cellular and Molecular Biology, Department of Biology, University of Rome 'Tor Vergata', Rome, Italy.
Veronica Venafra *Ph.D. Program in Cellular and Molecular Biology, Department of Biology, University of Rome 'Tor Vergata', Rome, Italy.
Giorgia MassacciDepartment of Biology, University of Rome Tor Vergata, Rome, Italy.
Simone GraziosiPh.D. Program in Cellular and Molecular Biology, Department of Biology, University of Rome 'Tor Vergata', Rome, Italy.
Sara GualdiDepartment of Biology and Biotechnologies "C. Darwin", University of Rome La Sapienza, Rome, Italy.
Gessica MinnellaSezione di Ematologia, Dipartimento di Scienze Radiologiche ed Ematologiche, Università Cattolica del Sacro Cuore, Roma, Italy.
Federica SoràSezione di Ematologia, Dipartimento di Scienze Radiologiche ed Ematologiche, Università Cattolica del Sacro Cuore, Roma, Italy.
Patrizia ChiusoloSezione di Ematologia, Dipartimento di Scienze Radiologiche ed Ematologiche, Università Cattolica del Sacro Cuore, Roma, Italy.
Maria Elsa BrunettiTelethon Institute of Genetics and Medicine (TIGEM), Naples, Italy.
Gennaro NapolitanoTelethon Institute of Genetics and Medicine (TIGEM), Naples, Italy.
Massimo BrecciaDepartment of Translational and Precision Medicine, Azienda Policlinico Umberto I, Sapienza University of Rome, Rome, Italy.
Dimitrios MougiakakosHealth campus for Inflammation, Immunity and Infection (GCI3), University of Magdeburg, Magdeburg, Germany.
Martin BöttcherHealth campus for Inflammation, Immunity and Infection (GCI3), University of Magdeburg, Magdeburg, Germany.
Thomas FischerHealth campus for Inflammation, Immunity and Infection (GCI3), University of Magdeburg, Magdeburg, Germany.
Livia PerfettoDepartment of Biology and Biotechnologies "C. Darwin", University of Rome La Sapienza, Rome, Italy. livia.perfetto@uniroma1.it.
Francesca SaccoDepartment of Biology, University of Rome Tor Vergata, Rome, Italy. francesca.sacco@uniroma2.it.

Funding

Associazione Italiana per la Ricerca sul Cancro 21815Associazione Italiana per la Ricerca sul Cancro 28858Ministero dell'Università e della Ricerca E53D23004850006
6 · The paper itself

Abstract

backgroundAbout 40% of relapsed or non-responder tumors exhibit therapeutic resistance in the absence of a clear genetic cause, suggesting a pivotal role of intracellular communication. A deeper understanding of signaling pathways rewiring occurring in resistant cells is crucial to propose alternative effective strategies for cancer patients.

methodsTo achieve this goal, we developed a novel multi-step strategy, which integrates high sensitive mass spectrometry-based phosphoproteomics with network-based analysis. This strategy builds context-specific networks recapitulating the signaling rewiring upon drug treatment in therapy-resistant and sensitive cells.

resultsWe applied this strategy to elucidate the BCR::ABL1-independent mechanisms that drive relapse upon therapy discontinuation in chronic myeloid leukemia (CML) patients. We built a signaling map, detailing - from receptor to key phenotypes - the molecular mechanisms implicated in the control of proliferation, DNA damage response and inflammation of therapy-resistant cells. In-depth analysis of this map uncovered novel therapeutic vulnerabilities. Functional validation in patient-derived leukemic stem cells revealed a crucial role of acquired FLT3-dependency and its underlying molecular mechanism.

conclusionsIn conclusion, our study presents a novel generally applicable strategy and the reposition of FLT3, one of the most frequently mutated drivers of acute leukemia, as a potential therapeutic target for CML relapsed patients.

Indexed as

Drug Resistance, NeoplasmFusion Proteins, bcr-ablLeukemia, Myelogenous, Chronic, BCR-ABL PositiveProto-Oncogene Proteins c-ablCell Line, Tumorfms-Like Tyrosine Kinase 3HumansNeoplastic Stem CellsSignal Transductionfms-Like Tyrosine Kinase 3Fusion Proteins, bcr-ablProto-Oncogene Proteins c-ablBCR:ABL1-independent resistanceChronic myeloid leukemiaComputational strategyDrug repurposingFLT3PhosphoproteomicsSignaling pathways

Identifiers

PMID40211380
PMCPMC11987405

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LicenceCC BY-NC-ND
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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.