Impact of acute lymphoblastic leukemia induction therapy: findings from metabolomics on non-fasted plasma samples from a biorepository

Introduction Acute lymphoblastic leukemia (ALL) is among the most common cancers in children. With improvements in combination chemotherapy regimens, the overall survival has increased to over 90%. However, the current challenge is to mitigate adverse events resulting from the complex therapy. Sever...

Full description

Saved in:
Bibliographic Details
Published in:Metabolomics Vol. 17; no. 7; p. 64
Main Authors: Saito, Toshie, Wei, Yue, Wen, Li, Srinivasan, Chaitanya, Wolthers, Benjamin O., Tsai, Cheng-Yu, Harris, Marian H., Stevenson, Kristen, Byersdorfer, Craig, Oparaji, Judy-April, Fernandez, Christian, Mukherjee, Amitava, Abu-El-Haija, Maisam, Agnihotri, Sameer, Schmiegelow, Kjeld, Showalter, Megan R., Fogle, Paul W., McCulloch, Scott, Contrepois, Kevin, Silverman, Lewis B., Ding, Ying, Husain, Sohail Z.
Format: Journal Article
Language:English
Published: New York Springer US 01-07-2021
Springer Nature B.V
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Introduction Acute lymphoblastic leukemia (ALL) is among the most common cancers in children. With improvements in combination chemotherapy regimens, the overall survival has increased to over 90%. However, the current challenge is to mitigate adverse events resulting from the complex therapy. Several chemotherapies intercept cancer metabolism, but little is known about their collective role in altering host metabolism. Objectives We profiled the metabolomic changes in plasma of ALL patients initial- and post- induction therapy. Methods We exploited a biorepository of non-fasted plasma samples derived from the Dana Farber Cancer Institute ALL Consortium; these samples were obtained from 50 ALL patients initial- and post-induction therapy. Plasma metabolites and complex lipids were analyzed by high resolution tandem mass spectrometry and differential mobility tandem mass spectrometry. Data were analyzed using a covariate-adjusted regression model with multiplicity adjustment. Pathway enrichment analysis and co-expression network analysis were performed to identify unique clusters of molecules. Results More than 1200 metabolites and complex lipids were identified in the total of global metabolomics and lipidomics platforms. Over 20% of those molecules were significantly altered. In the pathway enrichment analysis, lipids, particularly phosphatidylethanolamines (PEs), were identified. Network analysis indicated that the bioactive fatty acids, docosahexaenoic acid (DHA)-containing (22:6) triacylglycerols (TAGs), were decreased in the post-induction therapy. Conclusion Metabolomic profiling in ALL patients revealed a large number of alterations following induction chemotherapy. In particular, lipid metabolism was substantially altered. The changes in metabolites and complex lipids following induction therapy could provide insight into the adverse events experienced by ALL patients.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Authors contributions TS, YW, LW, YD, and SZH designed the study, analyzed, and interpreted the data, and wrote the manuscript. SZH obtained funding. MHH, KrS, and LBS provided the samples, interpreted the data, and revised the manuscript. KC, BOW, KjS, CYT, CS, CB, JAO, CF, AM, MAEH, and SA participated in intellectual discussions and revised the manuscript. PWF, SM, and MRS acquired and analyzed the data.
Toshie Saito, Yue Wei and Li Wen shared first authors. Ying Ding and Sohail Z. Husain shared senior authors.
ISSN:1573-3882
1573-3890
1573-3890
DOI:10.1007/s11306-021-01814-2