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Somatic CNVs and LOH in Acute Myelomonocitic Leukemia

2008· article· en· W2557857454 on OpenAlexaboutno aff
Alessandra Romano, Vincenza Barresi, Nicolò Musso, Giuseppe A. Palumbo, Francesco Di Raimondo, D. F. Condorelli

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsCopy-number variationSNP arrayLoss of heterozygosityBiologyGeneticsComparative genomic hybridizationCopy number analysisSingle-nucleotide polymorphismCytogeneticsGene dosageSNP genotypingSNPAlleleGenomeGeneChromosomeGenotypeGene expression

Abstract

fetched live from OpenAlex

Abstract In acute myeloid leukemias (AML) chromosomal aberrations, detectable by conventional cytogenetics or targeted molecular techniques, provide the basis for a classification with prognostic relevance. However, cases with normal cytogenetics and undefined prognosis still constitute the single largest group. Recent advances in genome-wide analysis of submicroscopic DNA segment copy number variations (CNVs) may allow the identification of novel molecular tumor-associated abnormalities in the normal cytogenetics group (somatic CNVs). However, CNVs are also present physiologically in the normal population (germline CNVs) (Redon et al., 2006) and can represent potential predisposition factors in disease. Indeed, CNVs can have dramatic phenotypic consequences as a result of altering gene dosage, disrupting coding sequences, or perturbing long-range gene regulation. We used the last generation of Affymetrix single nucleotide polymorphism (SNP)/CNV microarrays (SNP Array 6.0) containing probes for the detection of CNVs and SNPs, with an inter-marker distance of 680 bases and a resolution power of 100 kb. SNP Array 6.0 Assay kit (Affymetrix, Santa Clara, CA) is able to assess copy number changes (CNVs) at a resolution comparable with data obtained using oligonucleotide-array-comparative genomic hybridization (aCGH) and provides also information on loss of heterozygosity (LOH) of the allelic imbalance and copy number neutral type. In the present communication we report preliminary results of a study aimed to test the ability of such arrays to distinguish tumor-associated somatic CNVs and LOHs from germ-line ones by comparing bone marrow samples from AML patients at diagnosis (>90% blasts) and at the remission phase. So far, 8 M4–M5 FAB subtype AML patients have been studied, 6 females, 2 males (median age 38 years, range 25–51). At diagnosis 4 cases with normal karyotype, 2 cases with trisomies (respectively trisomy 13 in 25% and trisomy 22 in 80% of 20 metaphases), 1 inversion (inv (16) (p13q22)) and 1 balanced translocation (t (6;14) (q27;q23)) were detected by conventional cytogenetic analysis. We obtained arrays with quality control (QC) call rates in excess of 90% in all cases (>95% in 8/13 cases) and MAPD <0.4 (<0.35 in 7/13 arrays), using Genotyping Console Version 2.1 for signal intensity analysis, as recommended by Affymetrix. To obtain copy number and LOH calls we used a predefined reference model file, obtained from 270 healthy individuals (HapMap collection). All samples that were regarded as normal karyotype by chromosomal banding had detectable submicroscopic abnormalities by the SNP/CNV array assay. Results obtained are reported in table 1. We found 13 somatic gains not in overlap with known CNVs deposited in the Toronto Database of Genomic Variants. The only recurrent somatic CNV (2/8 patients) was a gain of 109kb in 7q22.1, where genes MGC57359 and GATS map. Five recurrent germline CNVs have been detected, both at diagnosis and remission samples, which could represent regions determining susceptibility to AML. The trisomy 13 case showed a whole chromosome somatic LOH at chromosome 21. 3/8 patients had an interstitial somatic LOH in 19q13.12 in correspondence with adhesion molecules genes (CEACAM1, MEGF8, PSG 1-6-7, ZNF 526). Finally, we detected an interstitial germline LOH, common to all samples, in 16q22.1, where CBFB (core binding factor beta) gene maps, involved in FAB subtypes evaluated in this study. Although this is an ongoing study, with preliminary results, we think that such genome-wide characterization of sub-microscopic DNA alterations might contribute to the discovery of new markers and target genes, with diagnostic, prognostic or therapeutic relevance. CNV or LOH per sample Normal karyotype Abnormal karyotype median range median range CNV (diagnosis) 38 16–52 79 18–163 ratio gain/loss at diagnosis 7 6–7 15 4–22 CNV (remission) 24 16–32 49 20–167 ratio gain/loss at remission 1 1–2 9 1–20 germline CNV 18 14–21 33 7–77 somatic CNV 16 2–30 51 3–86 LOH (diagnosis) 299 285–314 316 307–317 LOH (remission) 291 285–297 295 282–318 germline LOH 283 278–289 287 287–308 somatic LOH 16 12–19 20 8–30 Table 1

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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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Citations0
Published2008
Admission routes1
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