scholarly journals Best Paper Selection

2019 ◽  
Vol 28 (01) ◽  
pp. 194-194
Keyword(s):  
Myeloid Leukemia ◽  
Human Cancer ◽  
Genomic Data ◽  
Learning Approach ◽  
Convolutional Networks ◽  
Genomic Data Integration ◽  
Phenotype Classification ◽  
Machine Learning Approach ◽  
Acute Myeloid ◽  
Integrative Omics

Lee SI, Celik S, Logsdon BA, Lundberg SM, Martins TJ, Oehler VG, Estey EH, Miller CP, Chien S, Dai J, Saxena A, Blau CA, Becker PS. A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nat Commun 2018 Jan;9(1):42 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5752671/ Mobadersany P, Yousefi S, Amgad M, Gutman DA, Barnholtz-Sloan JS, Velázquez Vega JE, Brat DJ, Cooper LAD. Predicting cancer outcomes from histology and genomics using convolutional networks. Proc Natl Acad Sci U S A 2018;115(13):E2970-E2979 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879673/ Sengupta S, Sun SQ, Huang KL, Oh C, Bailey MH, Varghese R, Wyczalkowski MA, Ning J, Tripathi P, Mc Michael JF, Johnson KJ, Kandoth C, Welch J, Ma C, Wendl MC, Payne SH, Fenyö D, Townsend RR, Dipersio JF, Chen F, Ding L. Integrative omics analyses broaden treatment targets in human cancer. Genome Med 2018 Jul 27;10(1):60 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064051/ Torshizi AD, Petzold LR. Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification. J Am Med Inform Assoc 2018;25(1):99-108 https://academic.oup.com/jamia/article/25/1/99/3826530

scholarly journals A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Su-In Lee ◽  
Safiye Celik ◽  
Benjamin A. Logsdon ◽  
Scott M. Lundberg ◽  
Timothy J. Martins ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Myeloid Leukemia ◽  
Big Data ◽  
Precision Medicine ◽  
Myeloid Leukemia ◽  
Learning Approach ◽  
Machine Learning Approach ◽  
Acute Myeloid

scholarly journals SMPDL3B Predicts Poor Prognosis and Contributes to Development of Acute Myeloid Leukemia

2021 ◽  
Vol 8 ◽  
Author(s):  
Huiqing Qu ◽  
Ye Zhu
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Human Cancer ◽  
Negative Regulator ◽  
Poor Overall Survival ◽  
Clinicopathologic Characteristics ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML), characterized by the low cure rate and high relapse, urgently needs novel diagnostic or prognostic biomarkers and potential therapeutic targets. Sphingomyelin Phosphodiesterase Acid Like 3B (SMPDL3B) is a negative regulator of Toll-like receptor signaling that plays important roles in the interface of membrane biology and innate immunity. However, the potential role of SMPDL3B in human cancer, especially in AML, is still unknown.Methods: The expression of SMPDL3B in AML samples was investigated through data collected from Gene Expression Omnibus (GEO). Association between SMPDL3B expression and clinicopathologic characteristics was analyzed with the chi-square test. Survival curves were calculated by the Kaplan–Meier method. Cox univariate and multivariate analyses were used to detect risk factors for overall survival. The biological functions of SMPDL3B in human AML were investigated both in vitro and in vivo.Results: Expression of SMPDL3B mRNA was significantly upregulated in human AML samples and closely correlated to cytogenetics risk and karyotypes. Elevated expression of SMPDL3B was associated with poor overall survival and emerged as an independent predictor for poor overall survival in human AML. Blocked SMPDL3B expression inhibited AML cells growth both in vitro and in vivo via promoting cell apoptosis.Conclusion: Taken together, our results demonstrate that SMPDL3B could be used as an efficient prognostic biomarker and represent a potential therapeutic target for human AML.

Inhibition of Cellular Aminopeptidases as Novel Therapy for AML.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2588-2588
Author(s):  
Christopher Jenkins ◽  
Chris Pepper ◽  
Ken Mills ◽  
Alan Burnett
Keyword(s):  
Acute Myeloid Leukemia ◽  
Cell Lines ◽  
Myeloid Leukemia ◽  
Human Cancer ◽  
Myeloid Cells ◽  
Chemotherapeutic Agents ◽  
Molecular Therapy ◽  
Leukemic Cells ◽  
Therapeutic Window ◽  
Acute Myeloid

Abstract CHR 2797 is one of a new class of enzyme inhibitors with a pleiotropic effect against a number of human cancer cells. It is thought to inhibit the M1 family of metalloenzymes that include aminopeptidases, and is under investigation for the treatment of acute myeloid leukemia. Aminopeptidases catalyse the hydrolysis of the terminal amino acids from short chain polypeptides and they are involved in the continuous cycle of protein formation and degradation in cells. As malignant cells are thought to be more highly dependant on this protein cycling, interrupting this pathway is therefore a potential therapeutic target for novel agents. The effects of the aminopeptidase inhibitor CHR 2797 were investigated in AML cells in-vitro. Leukemic cells and cell lines were treated with CHR 2797 at a range of 0.0002 – 20μM and IC50 values were calculated from the WST-1 proliferation experiments. The AML cell lines HL60, KG1, K562 and U937 had an average IC50 of 1μM with a range between 0.01 and 10μM. Primary diagnostic AML samples (n=40) were analysed and an IC50 range of between 0.01 and >40μM were detected, with a median of 0.8μM. The effects of CHR 2797 were also analysed on normal bone marrow samples (n=10). The IC50 range was between 6.2 and >40μM with a median of 15μM, demonstrating a potential therapeutic window between the treatment of the leukemic cells and toxicity to the normal samples. The level of synergy or antagonism with conventional therapeutic agents was calculated using a combination index. Synergy was demonstrated in 70% of cell samples in combination with ARA-C, and 80% with Velcade. Synergy was also shown in 60% of cells samples with ATRA, even in non-promyelocytic leukemia types. Annexin V and cell cycle analysis confirmed apoptosis after treatment with CHR 2797 in many cases. A degree of differentiation of acute promyelocytic cells to mature myeloid cells was also stimulated with the treatment. The effects of CHR 2797 on cellular aminopeptidases were also measured. CD13 is a cell surface protein which is expressed selectively on myeloid cells and is also classified as an aminopeptidase N. Its activity can be measured by the conversion of the substrate ala-MCA to the protein MCA that can be detected on a fluorometric plate reader. CHR 2797 was demonstrated to reduce CD13 activity in a time and dose responsive manner. The reduction in activity was demonstrated immediately following addition of the drug, and a persistent effect was shown over four days of cell culture. A reduction in CD13 activity was also shown with a concentration of CHR 2797 of under 0.5μM; and with a 10μM dose the activity in many AML samples was reduced by >90%. New treatments are needed for acute myeloid leukemia to improve survival and reduce the toxicity of conventional therapy. This study demonstrates that CHR 2797 might be an effective molecular therapy for AML, either alone or in combination with other chemotherapeutic agents.

scholarly journals Complete characterization of the microRNAome in a patient with acute myeloid leukemia

Blood ◽  
2010 ◽  
Vol 116 (24) ◽  
pp. 5316-5326 ◽  
Author(s):  
Giridharan Ramsingh ◽  
Daniel C. Koboldt ◽  
Maria Trissal ◽  
Katherine B. Chiappinelli ◽  
Todd Wylie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Binding Sites ◽  
Myeloid Leukemia ◽  
Human Cancer ◽  
Complete Characterization ◽  
Small Noncoding Rnas ◽  
Mirna Genes ◽  
Acute Myeloid

Abstract MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression and have been implicated in the pathogenesis of cancer. In this study, we applied next generation sequencing techniques to comprehensively assess miRNA expression, identify genetic variants of miRNA genes, and screen for alterations in miRNA binding sites in a patient with acute myeloid leukemia. RNA sequencing of leukemic myeloblasts or CD34+ cells pooled from healthy donors showed that 472 miRNAs were expressed, including 7 novel miRNAs, some of which displayed differential expression. Sequencing of all known miRNA genes revealed several novel germline polymorphisms but no acquired mutations in the leukemia genome. Analysis of the sequence of the 3′-untranslated regions (UTRs) of all coding genes identified a single somatic mutation in the 3′-UTR of TNFAIP2, a known target of the PML-RARα oncogene. This mutation resulted in translational repression of a reporter gene in a Dicer-dependent fashion. This study represents the first complete characterization of the “miRNAome” in a primary human cancer and suggests that generation of miRNA binding sites in the UTR regions of genes is another potential mechanism by which somatic mutations can affect gene expression.

scholarly journals A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects

Blood ◽  
2009 ◽  
Vol 113 (2) ◽  
pp. 291-298 ◽  
Author(s):  
Bas J. Wouters ◽  
Bob Löwenberg ◽  
Ruud Delwel
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Dna Microarrays ◽  
Human Cancer ◽  
Genome Wide ◽  
Genome Wide Gene Expression ◽  
Acute Myeloid

Abstract The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues

scholarly journals The complexity of interpreting genomic data in patients with acute myeloid leukemia

2016 ◽  
Vol 6 (12) ◽  
pp. e510-e510 ◽  
Author(s):  
A Nazha ◽  
A Zarzour ◽  
K Al-Issa ◽  
T Radivoyevitch ◽  
H E Carraway ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Genomic Data ◽  
Acute Myeloid

scholarly journals diploS/HIC: an updated approach to classifying selective sweeps

2018 ◽  
Author(s):  
Andrew D. Kern ◽  
Daniel R. Schrider
Keyword(s):  
Machine Learning ◽  
Genomic Data ◽  
Difficult Problem ◽  
Small Sample ◽  
Supervised Machine Learning ◽  
Learning Approach ◽  
Selective Sweeps ◽  
Machine Learning Approach ◽  
Small Sample Sizes ◽  
Soft Selective Sweeps

AbstractIdentifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genetic variation surrounding a window of the genome. While S/HIC was shown to be both powerful and precise, the utility of S/HIC was limited by the use of phased genomic data as input. In this report we describe a deep learning variant of our method, diploS/HIC, that uses unphased genotypes to accurately classify genomic windows. diploS/HIC is shown to be quite powerful even at moderate to small sample sizes

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