Evidence map›Paper›PMID 42588675›Full record

ArticleCancers2026

Unmasking Additional Mutations: A Single Institution Study in Myeloproliferative Neoplasms.

Parastou Tizro, Eric Vail, Manoj Sapkota, Matthew G Gayhart, Celeste C Eno

Abstract read
In one paragraph

Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Parastou TizroDepartment of Pathology and Laboratory Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA.ORCID 0000-0003-1928-8967
Eric VailDepartment of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, 8723 Alden Drive, SSB-362, Los Angeles, CA 90048, USA.ORCID 0000-0002-6578-178X
Manoj SapkotaDepartment of Horticulture, University of Kentucky, Lexington, KY 40546, USA.ORCID 0000-0002-9987-1193
Matthew G GayhartDepartment of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, 8723 Alden Drive, SSB-362, Los Angeles, CA 90048, USA.ORCID 0009-0000-5701-9173
Celeste C EnoDepartment of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, 8723 Alden Drive, SSB-362, Los Angeles, CA 90048, USA.ORCID 0000-0002-3857-9519

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesMyeloproliferative neoplasms (MPNs) are chronic myeloid malignancies characterized by substantial genetic heterogeneity. Although routine molecular evaluation focuses on canonical driver alterations (

methodsWe retrospectively analyzed 1209 consecutive patients who underwent peripheral blood next-generation sequencing (NGS) for suspected or established MPNs using a comprehensive 75-gene DNA/RNA panel.

resultsCanonical driver alterations were identified in 141 patients, while 1068 were driver-negative. Retrospective analysis demonstrated that 251 patients (21%) harbored at least one additional pathogenic or likely pathogenic mutation that was not routinely reported. Among driver-positive patients, 57 of 141 (40%) carried clinically relevant co-mutations, including high-molecular-risk genes such as

conclusionsThese findings indicate that comprehensive NGS performed at the time of initial evaluation provides clinically relevant genomic information beyond canonical driver mutations, improves disease classification and risk stratification, and may facilitate earlier diagnosis and personalized management of patients with suspected MPNs.

Indexed as

CALRHMRJAK2MPLMPNmutationprognosis

Identifiers

PMID42588675
PMCPMC13465104

What OpenQuestion holds

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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.