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Whole Exome Sequencing Analysis in AML with Normal Karyotype Not Harboring FLT3/ITD Mutation Reveals Novel Genetic Alterations.

2012· article· en· W2550415955 on OpenAlexaff
Il-Kwon Lee, Namshin Kim, Yeo‐Kyeoung Kim, Dennis Dong Hwan Kim, Quang M. Trinh, Mark D. Minden, Chul Won Jung, Jun‐Ho Jang, Hee‐Je Kim, Joon Ho Moon, Sang Kyun Sohn, Jong-Ho Won, Sung‐Hyun Kim, Jungwon Huh, Nan Young Kim, Yu Li, Yun Gyeong Lee, Sung-Hoon Chung, Jae‐Sook Ahn, Deok‐Hwan Yang, Je‐Jung Lee, Hyeoung‐Joon Kim

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsSanger sequencingBiologyGeneticsMutationExome sequencingMissense mutationdbSNPGermline mutationGeneCancer researchGenotype

Abstract

fetched live from OpenAlex

Abstract Abstract 2593 Background: NK-AML represents genetically heterogeneous group of disease. However genetic lesions affecting treatment outcome in patients with NK-AML are relatively unknown. Methods: The discovery cohort consists of 67 NK-AML patients in complete remission (median age: 49.2, ranges: 19–70) without FLT-3 mutations. Genomic DNA was extracted from enriched AML cells at diagnosis or control specimens obtained after complete remission. Whole exomes were captured using Agilent SureSelect and sequencing were performed by HiSeq2000 with 41∼89× coverage. Bioinformatics analysis and identification of somatic mutation has been done by series of software such as BWA, Picard, GATK, VarScan 2, and custom-made scripts. All the data has been re-checked by manual inspection. Validation has been done independent set of cohort (358 NK-AML patients, median age: 51, ranges: 15–85) with Sanger sequencing on highly mutated target sites. Results: Filtering against dbSNP and COSMIC database generated 485 genes with somatic and structural variations. Among them, 41 genes were detected in more than two patients. In addition to well-known 28 mutations, 13 novel mutations with different frequencies were identified including genes responsible for structural maintenance of chromosome (SMC1A, 6.0%) and tumor suppressor function (FAT1, 6.0%). Most common type of mutation was missense mutation (70.8%), and substantial fraction of mutation was splicing site mutations (3.8%). The hematological system development and hematologic function were most highly enriched by the Ingenuity Pathway Analysis (IPA) as expected. CIRCOS plot analysis showed similar co-occurring pattern of recurrent mutations with previous reports. Hierarchical clustering analysis divided into four different groups according to the number of harboring mutations. In network analysis four distinct subgroups were observed ranging 21 to 3 gene network. Conclusion: Using whole exome sequencing approach, a catalog of recurrent mutations was successfully defined in the patients with NK-AML without FLT3/ITD mutation. This candidate list of novel mutations should be tested further for therapeutic target and prognostic marker in the patients with NK-AML. Disclosures: No relevant conflicts of interest to declare.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.028
GPT teacher head0.283
Teacher spread0.256 · 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 designBench or experimental
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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Citations0
Published2012
Admission routes1
Has abstractyes

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