Prognostic significance of microRNA-99a in acute myeloid leukemia patients undergoing allogeneic hematopoietic stem cell transplantation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09

AUTHORS

Zhiheng Cheng, Lei Zhou, Kai Hu, Yifeng Dai, Yifan Pang, Hongmian Zhao, Sun Wu, Tong Qin, Yu Han, Ning Hu, Li Chen, Chao Wang, Yijie Zhang, Depei Wu, Xiaoyan Ke, Jinlong Shi, Lin Fu

ABSTRACT

Overexpression of microRNA-99a (miR-99a) have been associated with adverse prognosis in acute myeloid leukemia (AML). Nevertheless, whether it also predicts poor outcome in post-allogeneic hematopoietic stem cell transplantation (allo-HSCT) AML patients remains unclear. To further elucidate the prognostic value of miR-99a, 74 AML patients with miR-99a expression report who underwent allo-HSCT from The Cancer Genome Atlas database were identified and grouped into either miR-99ahigh or miR-99alow based on their miR-99a expression levels relative to the median. Two groups had similar clinical and molecular characteristics except that miR-99ahigh group had fewer patients of the French-American-British M4 subtype (P = 0.018) and more frequent CEBPA mutations (P = 0.005). Univariate analysis indicated that high miR-99a expression was unfavorable for both event-free survival (EFS) and overall survival (OS; P = 0.029; P = 0.012, respectively). Multivariate analysis suggested that high miR-99a expression was an independent risk factor for both EFS and OS in AML patients who underwent allo-HSCT [hazard ratio (HR) 1.909, 95% confidence interval (CI) 1.043-3.494, P = 0.036 and HR 2.179, 95% CI 1.192-3.982, P = 0.011, respectively]. Our results further proved that high miR-99a expression could predict worse outcome in AML patients, even in those who underwent intensive post-remission therapy such as allo-HCST. More... »

PAGES

1089-1095

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41409-018-0146-0

DOI

http://dx.doi.org/10.1038/s41409-018-0146-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101298920

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29515250


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41409-018-0146-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41409-018-0146-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41409-018-0146-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41409-018-0146-0'


 

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290 https://www.grid.ac/institutes/grid.414252.4 schema:alternateName Chinese PLA General Hospital
291 schema:name Department of Biomedical Engineering, Chinese PLA General Hospital, 100853, Beijing, China
292 Department of Hematology, Chinese PLA General Hospital, 100853, Beijing, China
293 Department of Medical Big Data, Chinese PLA General Hospital, 100853, Beijing, China
294 Translational Medicine Center, Huaihe Hospital of Henan University, 475000, Kaifeng, China
295 rdf:type schema:Organization
296 https://www.grid.ac/institutes/grid.417118.a schema:alternateName William Beaumont Hospital
297 schema:name Department of Medicine, William Beaumont Hospital, 48073, Royal Oak, MI, USA
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299 https://www.grid.ac/institutes/grid.429222.d schema:alternateName First Affiliated Hospital of Soochow University
300 schema:name Department of Hematology, The First Affiliated Hospital of Soochow University, 215006, Suzhou, China
301 rdf:type schema:Organization
302 https://www.grid.ac/institutes/grid.493088.e schema:alternateName First Affiliated Hospital of Xinxiang Medical University
303 schema:name Department of Hematology, The First Affiliated Hospital of Xinxiang Medical University, 453100, Weihui, China
304 rdf:type schema:Organization
 




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