Evidence map›Paper›PMID 25880391›Full record

ArticleBMC cancer2015

Clonal distribution of BCR-ABL1 mutations and splice isoforms by single-molecule long-read RNA sequencing.

Lucia Cavelier, Adam Ameur, Susana Häggqvist, Ida Höijer, Nicola Cahill, Ulla Olsson-Strömberg, Monica Hermanson

Abstract read
In one paragraph

Article in BMC cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Trial
  2. Long-read RNA sequencing: A transformative technology for exploring transcriptome complexity in human diseases.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
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  11. Article
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  13. C1222C Deletion in Exon 8 ofFrontiers in oncology · 2020
    Article
  14. Review
  15. Article
  16. Long reads: their purpose and place.Human molecular genetics · 2018
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  18. Review
  19. 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

7 authors.

Lucia CavelierDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. lucia.cavelier@igp.uu.se.
Adam AmeurDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. adam.ameur@igp.uu.se.
Susana HäggqvistDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. susana.haggqvist@igp.uu.se.
Ida HöijerDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Ida.hoijer@igp.uu.se.
Nicola CahillDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. nicola.cahill@igp.uu.se.
Ulla Olsson-StrömbergDepartment of Medical Sciences, Haematology, Uppsala University, Uppsala, Sweden. ulla.olsson-stromberg@medsci.uu.se.
Monica HermansonDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. monica.hermanson@igp.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe evolution of mutations in the BCR-ABL1 fusion gene transcript renders CML patients resistant to tyrosine kinase inhibitor (TKI) based therapy. Thus screening for BCR-ABL1 mutations is recommended particularly in patients experiencing poor response to treatment. Herein we describe a novel approach for the detection and surveillance of BCR-ABL1 mutations in CML patients.

methodsTo detect mutations in the BCR-ABL1 transcript we developed an assay based on the Pacific Biosciences (PacBio) sequencing technology, which allows for single-molecule long-read sequencing of BCR-ABL1 fusion transcript molecules. Samples from six patients with poor response to therapy were analyzed both at diagnosis and follow-up. cDNA was generated from total RNA and a 1,6 kb fragment encompassing the BCR-ABL1 transcript was amplified using long range PCR. To estimate the sensitivity of the assay, a serial dilution experiment was performed.

resultsOver 10,000 full-length BCR-ABL1 sequences were obtained for all samples studied. Through the serial dilution analysis, mutations in CML patient samples could be detected down to a level of at least 1%. Notably, the assay was determined to be sufficiently sensitive even in patients harboring a low abundance of BCR-ABL1 levels. The PacBio sequencing successfully identified all mutations seen by standard methods. Importantly, we identified several mutations that escaped detection by the clinical routine analysis. Resistance mutations were found in all but one of the patients. Due to the long reads afforded by PacBio sequencing, compound mutations present in the same molecule were readily distinguished from independent alterations arising in different molecules. Moreover, several transcript isoforms of the BCR-ABL1 transcript were identified in two of the CML patients. Finally, our assay allowed for a quick turn around time allowing samples to be reported upon within 2 days.

conclusionsIn summary the PacBio sequencing assay can be applied to detect BCR-ABL1 resistance mutations in both diagnostic and follow-up CML patient samples using a simple protocol applicable to routine diagnosis. The method besides its sensitivity, gives a complete view of the clonal distribution of mutations, which is of importance when making therapy decisions.

Indexed as

Alternative SplicingMutationSequence Analysis, RNAAdultAgedAllelesClonal EvolutionDrug Resistance, NeoplasmFemaleFusion Proteins, bcr-ablGene Expression Regulation, LeukemicHigh-Throughput Nucleotide SequencingHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositiveMaleMiddle AgedFusion Proteins, bcr-ablProtein Kinase InhibitorsRNA Isoforms

Identifiers

PMID25880391
PMCPMC4335374

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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.