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Record W4303628916 · doi:10.3390/curroncol29100568

Mutational Landscape of Patients Referred for Elevated Hemoglobin Level

2022· article· en· W4303628916 on OpenAlexaffvenue
Pratibha Bhai, Benjamin Chin‐Yee, Victor Pope, Ian Cheong, Maxim Matyashin, Michael A. Levy, Aidin Foroutan, Alan Stuart, Cyrus C. Hsia, Hanxin Lin, Bekim Sadiković, Ian Chin‐Yee

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineHemoglobinBioinformaticsInternal medicineBiology

Abstract

fetched live from OpenAlex

Background: Since the identification of JAK2 V617F and exon 12 mutations as driver mutations in polycythemia vera (PV) in 2005, molecular testing of these mutations for patients with erythrocytosis has become a routine clinical practice. However, the incidence of myeloid mutations other than the common JAK2 V617F mutation in unselected patients referred for elevated hemoglobin is not well studied. This study aimed to characterize the mutational landscape in a real-world population of patients referred for erythrocytosis using a targeted next-generation sequencing (NGS)-based assay. Method: A total of 529 patients (hemoglobin levels >160 g/L in females or >165 g/L in males) were assessed between January 2018 and May 2021 for genetic variants using the Oncomine Myeloid Research Assay (ThermoFisher Scientific, Waltham, MA, USA) targeting 40 key genes with diagnostic and prognostic implications in hematological conditions (17 full genes and 23 genes with clinically relevant “hotspot” regions) and a panel of 29 fusion driver genes (>600 fusion partners). Results: JAK2 mutations were detected in 10.9% (58/529) of patients, with 57 patients positive for JAK2 V617F, while one patient had a JAK2 exon 12 mutation. Additional mutations were detected in 34.5% (20/58) of JAK2-positive patients: TET2 (11; 19%), DNMT3A (2;3.4%), ASXL1 (2; 3.4%), SRSF2 (2; 3.4%), BCOR (1; 1.7%), TP53 (1; 1.7%), and ZRSR2 (1; 1.7%). Diagnosis of PV was suspected in 2 JAK2-negative patients based on the 2016 World Health Organization (WHO) diagnostic criteria. Notably, one patient carried mutations in the SRSF2 and TET2 genes, and the other patient carried mutations in the SRSF2, IDH2, and ASXL1 genes. Three JAK2-negative patients with elevated hemoglobin who tested positive for BCR/ABL1 fusion were diagnosed with chronic myeloid leukemia (CML) and excluded from further analysis. The remaining 466 JAK2-negative patients were diagnosed with secondary erythrocytosis and mutations were found in 6% (28/466) of these cases. Conclusion: Mutations other than JAK2 mutations were frequently identified in patients referred for erythrocytosis, with mutations in the TET2, DNMT3A, and ASXL1 genes being detected in 34.5% of JAK2-positive PV patients. The presence of additional mutations, such as ASXL1 mutations, in this population has implications for prognosis. Both the incidence and mutation type identified in patients with secondary erythrocytosis likely reflects incidental, age-associated clonal hematopoiesis of indeterminate potential (CHIP).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.368
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2022
Admission routes2
Has abstractyes

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