Predisposition to Myelodysplastic Syndrome with Deletion 5q Is Associated with TP53 Codon 72 Genotype
Bibliographic record
Abstract
Abstract Abstract 612 Background: Chromosome 5q deletion (del5q) is the most common cytogenetic abnormality in myelodysplastic syndrome (MDS). Although haplodeficiency of several genes may contribute to the disease phenotype, allelic deletion of the ribosomal protein S14 (RPS14) gene is a key effector of the hypoplastic anemia. Disruption of ribosome assembly arising from RPS14 deletion leads to nucleolar stress that triggers p53 activation. In a murine model of the human 5q- syndrome, TP53 inactivation was alone sufficient to rescue the hematologic phenotype, indicating that the molecular pathogenesis of del(5q) MDS is p53-dependent. The tumor suppressor TP53 gene is a key regulator of stem cell homeostasis and senescence. A well described single nucleotide polymorphism (SNP) located at codon 72 in the proline-rich, pro-apoptotic domain of TP53 has been linked to cancer and mutagen susceptibility, and treatment outcome. Substitution of a cytosine (‘C’ allele) for the more common guanine (‘G’ allele) results in translation of a proline rather than arginine residue at position 72, with diminished apoptotic potential. Given the pathogenetic role of p53 in del(5q) MDS, we hypothesized that homozygosity for the ‘C’ allele may be associated with disease predisposition. Methods: Bone marrow and blood samples were investigated from 118 del(5q) MDS patients, 102 non-del(5q) MDS patients, and 98 healthy controls. Genomic DNA was extracted and codon 72 of the TP53 gene was amplified by PCR. Forward and reverse Sanger sequencing was performed to determine genotype. Relationship to disease specific features at diagnosis including cytogenetic risk category, IPSS score, blast percentage, and age were investigated as well as the relationship to response to lenalidomide and AML transformation using SAS software (Version 9.2, SAS Institute Inc., Cary, NC, USA). Results: Genotype distribution significantly differed between del(5q) MDS patients (18% CC, 47% CG, and 35% GG), non-del(5q) MDS patients (9% CC, 58% CG, and 33% GG),and healthy controls (7% CC, 43% CG, and 50% GG) (p=0.01). The frequency of the homozygous CC genotype was >2x greater in del(5q) MDS (18%) compared to both non-del(5q) MDS (9%) and healthy controls (7%) (p=0.05). There was no significant frequency difference between non-del(5q) and healthy controls. Del(5q) MDS patients were >6 times more likely to carry the CC genotype vs. GG when compared to healthy controls [odds ratio (OR)=6.71, 95% CI: 1.56 to 28.86], whereas non-del(5q) patients were >3 times more likely to carry the CC genotype vs. GG when compared to healthy controls (OR=3.87, 95% CI: 0.66 to 22.71). The corresponding ‘C’ allele frequency was significantly greater among del(5q) MDS patients (41.7%) compared to healthy controls (28.6%) (p=0.006), and approached significance in non-del(5q) patients (37.8%) versus controls (p=0.06). There was no association between TP53 R72P genotype and cytogenetic risk group in either del(5q) (p=0.67) or non-del(5q) MDS patients (p= 0.60), IPSS (del5q, p=0.29; non-del5q, p=0.89), or response to lenalidomide (del5q, p=0.57; non-del5q p=0.89). Mean age at diagnosis was significantly (p=0.04) lower in del(5q) MDS (67.4 years; SD=11.1 years) compared to non-del(5q) MDS patients (70.8 years; SD=9.1years), although significant differences in age according to TP53 R72P genotype were not apparent in either MDS cytogenetic group (del5q, p=0.99; non-del5q, p=0.89). Conclusion: Our findings indicate that the TP53 R72P homozygous CC genotype occurs with significantly greater frequency in del(5q) MDS compared to both non-del(5q) MDS patients and healthy controls, suggesting that this polymorphism may play a key role in the pathogenesis of and predisposition to del(5q) MDS. Disclosures: Kurtin: Celgene: Honoraria. Maciejewski:Celgene: Research Funding; Eisai: Research Funding; Alexion: Consultancy. Nevill:Celgene: Honoraria. Karsan:Celgene: Research Funding. List:Celgene: Research Funding.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".