Title |
Next Generation Sequencing of Acute Myeloid Leukemia: Influencing Prognosis
|
---|---|
Published in |
BMC Genomics, January 2015
|
DOI | 10.1186/1471-2164-16-s1-s5 |
Pubmed ID | |
Authors |
Asad Muhammad Ilyas, Sultan Ahmad, Muhammad Faheem, Muhammad Imran Naseer, Taha A Kumosani, Muhammad Hussain Al-Qahtani, Mamdooh Gari, Farid Ahmed |
Abstract |
Acute myeloid leukemia (AML) is a clonal disorder of the blood forming cells characterized by accumulation of immature blast cells in the bone marrow and peripheral blood. Being a heterogeneous disease, AML has been the subject of numerous studies that focus on unraveling the clinical, cellular and molecular variations with the aim to better understand and treat the disease. Cytogenetic-risk stratification of AML is well established and commonly used by clinicians in therapeutic management of cases with chromosomal abnormalities. Successive inclusion of novel molecular abnormalities has substantially modified the classification and understanding of AML in the past decade. With the advent of next generation sequencing (NGS) technologies the discovery of novel molecular abnormalities has accelerated. NGS has been successfully used in several studies and has provided an unprecedented overview of molecular aberrations as well as the underlying clonal evolution in AML. The extended spectrum of abnormalities discovered by NGS is currently under extensive validation for their prognostic and therapeutic values. In this review we highlight the recent advances in the understanding of AML in the NGS era. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 47% |
Unknown | 8 | 53% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 47% |
Practitioners (doctors, other healthcare professionals) | 5 | 33% |
Scientists | 2 | 13% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
India | 1 | <1% |
Canada | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 180 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 32 | 17% |
Student > Ph. D. Student | 27 | 15% |
Student > Bachelor | 27 | 15% |
Student > Master | 22 | 12% |
Other | 14 | 8% |
Other | 21 | 11% |
Unknown | 41 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 50 | 27% |
Medicine and Dentistry | 37 | 20% |
Agricultural and Biological Sciences | 27 | 15% |
Computer Science | 3 | 2% |
Nursing and Health Professions | 3 | 2% |
Other | 19 | 10% |
Unknown | 45 | 24% |