Evidence map›Paper›PMID 27485109›Full record

ArticleBMC cancer2016

In chronic myeloid leukemia patients on second-line tyrosine kinase inhibitor therapy, deep sequencing of BCR-ABL1 at the time of warning may allow sensitive detection of emerging drug-resistant mutants.

Simona Soverini, Caterina De Benedittis, Fausto Castagnetti, Gabriele Gugliotta, Manuela Mancini, Luana Bavaro, Katerina Machova Polakova, Jana Linhartova, Alessandra Iurlo, Domenico Russo and 6 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04965649 (Search for an Association Between the Innate CD8+ T Cell Population and the Evolution of TKI), which is not on this map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.7field-weighted citation impact, top 9% 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.

NCT04965649 completednot on this mapstarted 2021, after this paper: background citation

Search for an Association Between the Innate CD8+ T Cell Population and the Evolution of TKI (Tyrosine Kinase Inhibitor) Resistance Mutations in Phi+ Hematological Malignancies.

TypeobservationalSponsorCentre Hospitalier Universitaire de NīmesRan2021 to 2026Enrolled30ConditionsLeukemia, Myelogenous Leukemia, Chronic Leukemia, BCR-ABL Positive Acute Myeloid LeukemiaArmsPhenotyping of total and innate CD8+T cells by flow cytometry
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 29 citations in OpenAlex.

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  3. A customized mass array panel forJournal of mass spectrometry and advances in the clinical lab · 2023
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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

16 authors at 6 institutions in 2 countries.

Simona SoveriniHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy. simona.soverini@unibo.it.
Caterina De BenedittisHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Fausto CastagnettiHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Gabriele GugliottaHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Manuela ManciniHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Luana BavaroHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Katerina Machova PolakovaInstitute of Hematology and Blood Transfusion, Prague, Czech Republic.
Jana LinhartovaInstitute of Hematology and Blood Transfusion, Prague, Czech Republic.
Alessandra IurloDivision of Haematology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Domenico RussoUnit of Blood Disease and Stem Cell Transplantation, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
Fabrizio PaneDepartment of Biochemistry and Medical Biotechnologies, University of Naples Federico II, Naples, Italy.
Giuseppe SaglioDepartment of Clinical and Biological Sciences "S. Luigi Gonzaga" Hospital, University of Turin, Orbassano, Italy.
Gianantonio RostiHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Michele CavoHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Michele BaccaraniHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Giovanni MartinelliHematology "L. e A. Seràgnoli", Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
University of Bologna · ITInstitute of Haematology and Blood Transfusion · CZFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITUniversity of Brescia · ITUniversity of Naples Federico II · ITUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImatinib-resistant chronic myeloid leukemia (CML) patients receiving second-line tyrosine kinase inhibitor (TKI) therapy with dasatinib or nilotinib have a higher risk of disease relapse and progression and not infrequently BCR-ABL1 kinase domain (KD) mutations are implicated in therapeutic failure. In this setting, earlier detection of emerging BCR-ABL1 KD mutations would offer greater chances of efficacy for subsequent salvage therapy and limit the biological consequences of full BCR-ABL1 kinase reactivation. Taking advantage of an already set up and validated next-generation deep amplicon sequencing (DS) assay, we aimed to assess whether DS may allow a larger window of detection of emerging BCR-ABL1 KD mutants predicting for an impending relapse.

methodsa total of 125 longitudinal samples from 51 CML patients who had acquired dasatinib- or nilotinib-resistant mutations during second-line therapy were analyzed by DS from the time of failure and mutation detection by conventional sequencing backwards. BCR-ABL1/ABL1%(IS) transcript levels were used to define whether the patient had 'optimal response', 'warning' or 'failure' at the time of first mutation detection by DS.

resultsDS was able to backtrack dasatinib- or nilotinib-resistant mutations to the previous sample(s) in 23/51 (45 %) pts. Median mutation burden at the time of first detection by DS was 5.5 % (range, 1.5-17.5 %); median interval between detection by DS and detection by conventional sequencing was 3 months (range, 1-9 months). In 5 cases, the mutations were detectable at baseline. In the remaining cases, response level at the time mutations were first detected by DS could be defined as 'Warning' (according to the 2013 ELN definitions of response to 2nd-line therapy) in 13 cases, as 'Optimal response' in one case, as 'Failure' in 4 cases. No dasatinib- or nilotinib-resistant mutations were detected by DS in 15 randomly selected patients with 'warning' at various timepoints, that later turned into optimal responders with no treatment changes.

conclusionsDS enables a larger window of detection of emerging BCR-ABL1 KD mutations predicting for an impending relapse. A 'Warning' response may represent a rational trigger, besides 'Failure', for DS-based mutation screening in CML patients undergoing second-line TKI therapy.

Indexed as

Drug Resistance, NeoplasmFusion Proteins, bcr-ablHigh-Throughput Nucleotide SequencingHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositivePharmacogenomic VariantsPolymorphism, Single NucleotideProtein Kinase InhibitorsSequence Analysis, DNABCR-ABL1 fusion protein, humanFusion Proteins, bcr-ablProtein Kinase InhibitorsBCR-ABL1Chronic myeloid leukemiaDeep sequencingTyrosine kinase inhibitorsWarning

Identifiers

PMID27485109
PMCPMC4970247
OpenAlexW2482413243

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Registered trials

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.