High-Resolution Analysis of Chromosomal Alterations in Adult Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Background: Chromosomal alterations occur frequently in acute lymphoblastic leukemia (ALL), affecting either the chromosome number or structural changes. These alterations can lead to inactivation of tumor suppressor genes and/or activation of oncogenes. The objective of this study was to identify recurrent and/or novel chromosomal alterations in adult ALL using single nucleotide polymorphism (SNP) array analysis. Methods: We studied 41 cases of adult ALL compared with healthy normal controls using SNP array. Results: Our analysis revealed 43 copy number variant regions, of which 44% were amplifications and 56% were deletions . The most common amplifications were on chromosome regions 8p23.1 (71%), 1q44 (66%), 1q23.3 (54%), 11q23.3 (54%), 12p13.33 (54%) and 8q24.21 (51%). On the other hand, the most common deletions were identified on chromosomes 1p31.1 (76%), 3q26.1 (68%), 11p11.12 (63%), 4q12 (59%), 19p13.2 (59%), 7q11.21 (56%), Xp22.33 (54%), 7q11.21 (51%) and 19p13.11 (51%). Conclusions: Amplification of chromosome 8p23.1 and deletion of chromosome 1p31.1 were the most frequently found alterations in this study. These chromosomal regions contain genes such as SPAG11B , DEFB104A , DEFB105A , DEFB107A , DEFB106A and SPAG11A . These potential genes may contribute to leukemogenesis in adult ALL. The cytogenetic and molecular mechanisms underlying these chromosome changes deserve further investigations. J Hematol. 2014;3(3):65-71 doi: http://dx.doi.org/10.14740/jh140w
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".