| 1. |
- Wan, Lu Ming, et al.
(author)
-
Heparanase Facilitates PMA-Induced Megakaryocytic Differentiation in K562 Cells via Interleukin 6/STAT3 Pathway
- 2020
-
In: Thrombosis and Haemostasis. - : GEORG THIEME VERLAG KG. - 0340-6245 .- 2567-689X. ; 120:4, s. 647-657
-
Journal article (peer-reviewed)abstract
- Heparanase (HPSE) is an endo-beta-D-glucuronidase that cleaves heparan sulfate and hence participates in remodeling of the extracellular matrix, leading to release of cytokines that are immobilized by binding to heparan sulfate proteoglycans (HSPGs), and consequently activating signaling pathways. This function of HPSE is correlated to its expression level that is normally very low in majority of the tissues. Exceptionally, human platelets express high level of HPSE, suggesting a unique physiological role in this cell. Using K562 cell line, we found a progressive increase of HPSE during the megakaryocytic differentiation. Analysis of a series of megakaryocytic differentiation-related heparin-binding proteins (HBPs) in the cell culture medium revealed an exclusive positive correlation between the level of interleukin 6 (IL-6) and HPSE expression. IL-6 modulated megakaryocytic differentiation through activation of STAT3. Further, we demonstrated that overexpression of HPSE potentiates megakaryocytic differentiation, whereas elimination of HPSE led to a delayed differentiation. This function of HPSE is associated with its activity, as overexpression of inactive HPSE had no effect on IL-6 production and megakaryocytic differentiation. The role of HPSE is further supported by the observation in an umbilical cord blood CD34+ cells megakaryocytic differentiation model. Our data propose a novel role for HPSE in platelets production by a HPSE/IL-6/STAT3 positive feedback loop that specifically regulates megakaryocytes maturation.
|
|
| 2. |
- Sampson, Joshua N., et al.
(author)
-
Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
-
In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
-
Journal article (peer-reviewed)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
|
|
