Evidence map›Paper›PMID 35442720›Full record

ArticleJCO precision oncology2022

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing.

Jeremy Wang, Nickhill Bhakta, Vanessa Ayer Miller, Mahler Revsine, Mark R Litzow, Elisabeth Paietta, Yuri Fedoriw, Kathryn G Roberts, Zhaohui Gu, Charles G Mullighan and 2 more

Abstract read
In one paragraph

Article in JCO precision oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

12 authors.

Jeremy WangDepartment of Genetics, University of North Carolina, Chapel Hill, NC.ORCID 0000-0002-0673-9418
Nickhill BhaktaDepartment of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, TN.ORCID 0000-0001-5282-7833
Vanessa Ayer MillerOffice of Clinical Translational Research, University of North Carolina, Chapel Hill, NC.ORCID 0000-0001-7614-1959
Mahler RevsineDepartment of Biology, University of North Carolina, Chapel Hill, NC.
Mark R LitzowDivision of Hematology and Transplant Center, Mayo Clinic Rochester, Rochester, MN.ORCID 0000-0002-9816-6302
Elisabeth PaiettaDepartment of Oncology, Montefiore Medical Center, Bronx, NY.
Yuri FedoriwDepartment of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC.
Kathryn G RobertsDepartment of Pathology, St Jude Children's Research Hospital, Memphis, TN.
Zhaohui GuDepartment of Computational and Quantitative Medicine & Systems Biology, Beckman Research Institute of City of Hope, Duarte, CA.ORCID 0000-0003-1581-1327
Charles G MullighanDepartment of Pathology, St Jude Children's Research Hospital, Memphis, TN.ORCID 0000-0002-1871-1850
Corbin D JonesDepartment of Biology, University of North Carolina, Chapel Hill, NC.ORCID 0000-0001-7281-7130
Thomas B AlexanderDepartment of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC.ORCID 0000-0002-0484-1574

Funding

Project-006U10CA180820 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer, MITCHELL D. SCHNALL · 2014 to 2026
$167.6M
Viral Vector Technology (VVTSR)P30CA021765 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI CHARLES ROBERTS · 1985 to 2026
$166.9M
ECOG-ACRIN Biospecimen Bank to Support NCTNU24CA196172 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI STANLEY R. HAMILTON, Scott D Jewell · 2015 to 2026
$41.1M
Translating genomic discoveries to improved outcomes for high risk acute leukemiaR35CA197695 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI Charles G Mullighan · 2017 to 2026
$11.4M
Montefiore Academic Community NCORP ProgramUG1CA189859 · NCI · MONTEFIORE MEDICAL CENTER (BRONX, NY) · PI Balazs Halmos, Della Makower · 2014 to 2026
$10.8M
UNC Oncology K12K12CA120780 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WILLIAM Y. KIM · 2007 to 2026
$9.6M
NCI, National Clinical Trials Network Lead Academic Participating Site (LAPS) UG1 (funded extension)UG1CA232760 · NCI · MAYO CLINIC ROCHESTER · PI Judy Caroline Boughey, Aaron Scott Mansfield · 2019 to 2026
$8.5M
Advanced sequencing as a novel diagnostic tool to discover strain-level variation and function of mucosal-adherent bacteria contributing to IBDK01DK119582 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WANG, JEREMY R · 2019 to 2023
$754k
Characterization of novel subtypes in B progenitor acute lymphoblastic leukemiaR00CA241297 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GU, ZHAOHUI · 2020 to 2022
$747k
Characterization of novel subtypes in B progenitor acute lymphoblastic leukemiaK99CA241297 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI GU, ZHAOHUI · 2019 to 2019
$90k
NCI NIH HHS K12 CA120780NCI NIH HHS K99 CA241297NCI NIH HHS P30 CA021765NCI NIH HHS R00 CA241297NCI NIH HHS R35 CA197695NCI NIH HHS U10 CA180820NCI NIH HHS U24 CA196172NCI NIH HHS UG1 CA189859NCI NIH HHS UG1 CA232760NIDDK NIH HHS K01 DK119582
6 · The paper itself

Abstract

purposeMost cases of pediatric acute leukemia occur in low- and middle-income countries, where health centers lack the tools required for accurate diagnosis and disease classification. Recent research shows the robustness of using unbiased short-read RNA sequencing to classify genomic subtypes of acute leukemia. Compared with short-read sequencing, nanopore sequencing has low capital and consumable costs, making it suitable for use in locations with limited health infrastructure. MATERIALS AND

methodsWe show the feasibility of nanopore mRNA sequencing on 134 cryopreserved acute leukemia specimens (26 acute myeloid leukemia [AML], 73 B-lineage acute lymphoblastic leukemia [B-ALL], 34 T-lineage acute lymphoblastic leukemia, and one acute undifferentiated leukemia). Using multiple library preparation approaches, we generated long-read transcripts for each sample. We developed a novel composite classification approach to predict acute leukemia lineage and major B-ALL and AML molecular subtypes directly from gene expression profiles.

resultsWe demonstrate accurate classification of acute leukemia samples into AML, B-ALL, or T-lineage acute lymphoblastic leukemia (96.2% of cases are classifiable with a probability of > 0.8, with 100% accuracy) and further classification into clinically actionable genomic subtypes using shallow RNA nanopore sequencing, with 96.2% accuracy for major AML subtypes and 94.1% accuracy for major B-lineage acute lymphoblastic leukemia subtypes.

conclusionTranscriptional profiling of acute leukemia samples using nanopore technology for diagnostic classification is feasible and accurate, which has the potential to improve the accuracy of cancer diagnosis in low-resource settings.

Indexed as

Leukemia, Myeloid, AcuteNanoporesNanopore SequencingPrecursor Cell Lymphoblastic Leukemia-LymphomaPrecursor T-Cell Lymphoblastic Leukemia-LymphomaAcute DiseaseChildHumansRNA, MessengerRNA, Messenger

Identifiers

PMID35442720
PMCPMC9200386

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.