Literature DB >> 31575857

A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1.

Nikhil Patkar1, Anam Fatima Shaikh2, Chinmayee Kakirde2, Shrinidhi Nathany2, Hridya Ramesh2, Prasanna Bhanshe2, Swapnali Joshi2, Shruti Chaudhary2, Sadhana Kannan3, Syed Hasan Khizer4, Gaurav Chatterjee2, Prashant Tembhare2, Dhanalaxmi Shetty5, Anant Gokarn4, Sachin Punatkar4, Avinash Bonda4, Lingaraj Nayak4, Hasmukh Jain4, Navin Khattry4, Bhausaheb Bagal4, Manju Sengar4, Sumeet Gujral2, Papagudi Subramanian2.   

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Year:  2019        PMID： 31575857      PMCID： PMC6773777          DOI： 10.1038/s41408-019-0244-2

Source DB:  PubMed          Journal:  Blood Cancer J        ISSN： 2044-5385            Impact factor:   11.037


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  18 in total

1.  Coexisting and cooperating mutations in NPM1-mutated acute myeloid leukemia.

Authors:  Jay L Patel; Jonathan A Schumacher; Kimberly Frizzell; Shelly Sorrells; Wei Shen; Adam Clayton; Rakhi Jattani; Todd W Kelley
Journal:  Leuk Res       Date:  2017-01-23       Impact factor: 3.156

2.  NPM1 mutant variant allele frequency correlates with leukemia burden but does not provide prognostic information in NPM1-mutated acute myeloid leukemia.

Authors:  Hussein A Abbas; Farhad Ravandi; Sanam Loghavi; Keyur P Patel; Gautam Borthakur; Tapan M Kadia; Elias Jabbour; Koichi Takahashi; Jorge Cortes; Ghayas C Issa; Marina Konopleva; Hagop M Kantarjian; Nicholas J Short
Journal:  Am J Hematol       Date:  2019-03-18       Impact factor: 10.047

3.  Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variation.

Authors:  Joseph B Hiatt; Colin C Pritchard; Stephen J Salipante; Brian J O'Roak; Jay Shendure
Journal:  Genome Res       Date:  2013-02-04       Impact factor: 9.043

Review 4.  Age-related clonal hematopoiesis.

Authors:  Liran I Shlush
Journal:  Blood       Date:  2017-11-15       Impact factor: 22.113

5.  Prevalence and prognostic impact of NPM1 mutations in 1485 adult patients with acute myeloid leukemia (AML).

Authors:  Christian Thiede; Sina Koch; Eva Creutzig; Christine Steudel; Thomas Illmer; Markus Schaich; Gerhard Ehninger
Journal:  Blood       Date:  2006-02-02       Impact factor: 22.113

6.  The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia.

Authors:  Rosemary E Gale; Claire Green; Christopher Allen; Adam J Mead; Alan K Burnett; Robert K Hills; David C Linch
Journal:  Blood       Date:  2007-10-23       Impact factor: 22.113

7.  Molecular subtypes of NPM1 mutations have different clinical profiles, specific patterns of accompanying molecular mutations and varying outcomes in intermediate risk acute myeloid leukemia.

Authors:  Tamara Alpermann; Susanne Schnittger; Christiane Eder; Frank Dicker; Manja Meggendorfer; Wolfgang Kern; Christoph Schmid; Carlo Aul; Peter Staib; Clemens-Martin Wendtner; Norbert Schmitz; Claudia Haferlach; Torsten Haferlach
Journal:  Haematologica       Date:  2015-10-15       Impact factor: 11.047

8.  IDH1 and IDH2 mutations are frequent genetic alterations in acute myeloid leukemia and confer adverse prognosis in cytogenetically normal acute myeloid leukemia with NPM1 mutation without FLT3 internal tandem duplication.

Authors:  Peter Paschka; Richard F Schlenk; Verena I Gaidzik; Marianne Habdank; Jan Krönke; Lars Bullinger; Daniela Späth; Sabine Kayser; Manuela Zucknick; Katharina Götze; Heinz-A Horst; Ulrich Germing; Hartmut Döhner; Konstanze Döhner
Journal:  J Clin Oncol       Date:  2010-06-21       Impact factor: 50.717

9.  The NPM1 mutation type has no impact on survival in cytogenetically normal AML.

Authors:  Friederike Pastore; Philipp A Greif; Stephanie Schneider; Bianka Ksienzyk; Gudrun Mellert; Evelyn Zellmeier; Jan Braess; Cristina M Sauerland; Achim Heinecke; Utz Krug; Wolfgang E Berdel; Thomas Buechner; Bernhard Woermann; Wolfgang Hiddemann; Karsten Spiekermann
Journal:  PLoS One       Date:  2014-10-09       Impact factor: 3.240

10.  The combination of NPM1, DNMT3A, and IDH1/2 mutations leads to inferior overall survival in AML.

Authors:  Jennifer B Dunlap; Jessica Leonard; Mara Rosenberg; Rachel Cook; Richard Press; Guang Fan; Philipp W Raess; Brian J Druker; Elie Traer
Journal:  Am J Hematol       Date:  2019-06-21       Impact factor: 13.265
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  5 in total

Review 1.  Application of machine learning in the management of acute myeloid leukemia: current practice and future prospects.

Authors:  Jan-Niklas Eckardt; Martin Bornhäuser; Karsten Wendt; Jan Moritz Middeke
Journal:  Blood Adv       Date:  2020-12-08

2.  Clinical impact of panel-based error-corrected next generation sequencing versus flow cytometry to detect measurable residual disease (MRD) in acute myeloid leukemia (AML).

Authors:  Nikhil Patkar; Chinmayee Kakirde; Anam Fatima Shaikh; Rakhi Salve; Prasanna Bhanshe; Gaurav Chatterjee; Sweta Rajpal; Swapnali Joshi; Shruti Chaudhary; Rohan Kodgule; Sitaram Ghoghale; Nilesh Deshpande; Dhanalaxmi Shetty; Syed Hasan Khizer; Hasmukh Jain; Bhausaheb Bagal; Hari Menon; Navin Khattry; Manju Sengar; Prashant Tembhare; Papagudi Subramanian; Sumeet Gujral
Journal:  Leukemia       Date:  2021-02-08       Impact factor: 12.883

3.  Personalized Survival Prediction of Patients With Acute Myeloblastic Leukemia Using Gene Expression Profiling.

Authors:  Adrián Mosquera Orgueira; Andrés Peleteiro Raíndo; Miguel Cid López; José Ángel Díaz Arias; Marta Sonia González Pérez; Beatriz Antelo Rodríguez; Natalia Alonso Vence; Laura Bao Pérez; Roi Ferreiro Ferro; Manuel Albors Ferreiro; Aitor Abuín Blanco; Emilia Fontanes Trabazo; Claudio Cerchione; Giovanni Martinnelli; Pau Montesinos Fernández; Manuel Mateo Pérez Encinas; José Luis Bello López
Journal:  Front Oncol       Date:  2021-03-29       Impact factor: 6.244

4.  Machine learning derived genomics driven prognostication for acute myeloid leukemia with RUNX1-RUNX1T1.

Authors:  Anam Fatima Shaikh; Chinmayee Kakirde; Chetan Dhamne; Prasanna Bhanshe; Swapnali Joshi; Shruti Chaudhary; Gaurav Chatterjee; Prashant Tembhare; Maya Prasad; Nirmalya Roy Moulik; Anant Gokarn; Avinash Bonda; Lingaraj Nayak; Sachin Punatkar; Hasmukh Jain; Bhausaheb Bagal; Dhanalaxmi Shetty; Manju Sengar; Gaurav Narula; Navin Khattry; Shripad Banavali; Sumeet Gujral; Subramanian P G; Nikhil Patkar
Journal:  Leuk Lymphoma       Date:  2020-08-05

Review 5.  How artificial intelligence might disrupt diagnostics in hematology in the near future.

Authors:  Wencke Walter; Claudia Haferlach; Niroshan Nadarajah; Ines Schmidts; Constanze Kühn; Wolfgang Kern; Torsten Haferlach
Journal:  Oncogene       Date:  2021-06-08       Impact factor: 9.867
  5 in total

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