Methylation Status of SMURF2 and Correlation with Clinical Parameters in Patients with Multiple Myeloma
Bibliographic record
Abstract
Abstract Background–Aim: Multiple myeloma (MM) is an incurable interleukin (IL)-6 dependent plasma-cell malignancy. It has been previously suggested that transforming growth factor-β (TGF-β) is the major inducer of IL-6 secretion by bone marrow stromal cells. The signaling responses to TGF-b are mediated by a heteromeric complex of two types of transmembrane serine threonine kinase receptors at the cell surface and their intracellular substrates, the Smad proteins. The Smurf2 gene (Smad ubiqitiniation regulatory factor 2) encodes a Smad-specific E3 ubiquitin ligase. Smurf2 targets Smad2 and Smad3 for proteasome-dependent degradation and enhances the inhibitory activity of Smad7. In addition to its role in regulating TGF-beta signalling, Smurf2 is up-regulated during replicative senescence in response to telomere shortening and induces senescence when ectopically expressed. Together these properties imply that Smurf2 may have tumour suppressor potential and may be involved in MM pathogenesis, but no studies exist regarding the smurf2 methylation status in human neoplasia. Here we have investigated for the first time the methylation status of Smurf2 in patients with MM. Patients and methods: Bone marrow samples from individuals with multiple myeloma (MM) were obtained at diagnosis and in some cases at disease progression. Genomic DNA was isolated and bisulphite modification was performed using commercially available kits (QIAmp DNA mini kit, Qiagen and EZ DNA methylation kit, Zymo Research respectively). The methylation-specific polymerase chain reaction (MSP) with primers for methylated and unmethylated alleles of the Smurf2 gene promoter was employed to study its methylation status. Control methylated (CpG Genome™ Universal Methylated, Chemicon International) and unmethylated genomic DNAs were included in each experiment. Ten bone marrow samples from individuals with borderline thrombocytopenia, that proved to have no haematological malignancy, served as negative controls. Survival curves were generated using the method of Kaplan-Meier and compared with the log-rank test. Logistic regression analysis was also used to measure the association between gene methylation and the development of advanced disease (DS3II), extramedullary disease, bone disease, anemia (Hb≤10 mg/dl), serum albumin and beta 2 microglobulin levels. Results: We analysed the methylation of SMURF2 in 45 cases of multiple myeloma (MM) (24 male, 21 female, mean age 66.4 years). Using the Durie and Salmon staging system MM patients’ disease stages were as follows: smoldering MM 7/45, IA 9/45, IIA 13/45 patients, IIIA 7/45 patients and IIIB 9/45 patients. No sample from the control population was found methylated. The SMURF2 gene promoter was found to be methylated in 11/45 MM patients (24%). Interesting trends were noted where patients with methylated Smurf2 promoter had an increased risk of death (HR = 1.3; p = 0.68), anemia (OR=2.1, p=0.2) and advanced stage (OR=1.3, p=0.6) and a reduced risk of extramedullary disease (OR 0.2, p=0.2). No association was found between Smurf2 methylation status and bone lytic lesions, serum albumin levels or beta-2 microglobulin levels. Conclusions: To the best of our knowledge, this is the first demonstration of Smurf2 methylation in human neoplasia. Also, interesting associations between Smurf2 methylation and some relevant clinical parameters in patients with MM were suggested by the data. These findings warrant further evaluation in a larger sample of patients in order to enhance our statistical power and better define the prognostic and clinical value of Smurf2 methylation in MM.
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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".