PMID- 36230609
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20240417
IS  - 2072-6694 (Print)
IS  - 2072-6694 (Electronic)
IS  - 2072-6694 (Linking)
VI  - 14
IP  - 19
DP  - 2022 Sep 26
TI  - Cross-Domain Text Mining to Predict Adverse Events from Tyrosine Kinase 
      Inhibitors for Chronic Myeloid Leukemia.
LID - 10.3390/cancers14194686 [doi]
LID - 4686
AB  - Tyrosine kinase inhibitors (TKIs) are prescribed for chronic myeloid leukemia 
      (CML) and some other cancers. The objective was to predict and rank TKI-related 
      adverse events (AEs), including under-reported or preclinical AEs, using novel 
      text mining. First, k-means clustering of 2575 clinical CML TKI abstracts 
      separated TKIs by significant (p < 0.05) AE type: gastrointestinal (bosutinib); 
      edema (imatinib); pulmonary (dasatinib); diabetes (nilotinib); cardiovascular 
      (ponatinib). Next, we propose a novel cross-domain text mining method utilizing a 
      knowledge graph, link prediction, and hub node network analysis to predict new 
      relationships. Cross-domain text mining of 30+ million articles via SemNet 
      predicted and ranked known and novel TKI AEs. Three physiology-based tiers were 
      formed using unsupervised rank aggregation feature importance. Tier 1 ranked in 
      the top 1%: hematology (anemia, neutropenia, thrombocytopenia, hypocellular 
      marrow); glucose (diabetes, insulin resistance, metabolic syndrome); iron 
      (deficiency, overload, metabolism), cardiovascular (hypertension, heart failure, 
      vascular dilation); thyroid (hypothyroidism, hyperthyroidism, parathyroid). Tier 
      2 ranked in the top 5%: inflammation (chronic inflammatory disorder, autoimmune, 
      periodontitis); kidney (glomerulonephritis, glomerulopathy, toxic nephropathy). 
      Tier 3 ranked in the top 10%: gastrointestinal (bowel regulation, hepatitis, 
      pancreatitis); neuromuscular (autonomia, neuropathy, muscle pain); others 
      (secondary cancers, vitamin deficiency, edema). Results suggest proactive TKI 
      patient AE surveillance levels: regular surveillance for tier 1, infrequent 
      surveillance for tier 2, and symptom-based surveillance for tier 3.
FAU - Mehra, Nidhi
AU  - Mehra N
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
FAU - Varmeziar, Armon
AU  - Varmeziar A
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
FAU - Chen, Xinyu
AU  - Chen X
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
FAU - Kronick, Olivia
AU  - Kronick O
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
FAU - Fisher, Rachel
AU  - Fisher R
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
FAU - Kota, Vamsi
AU  - Kota V
AUID- ORCID: 0000-0002-5290-9289
AD  - Division of Hematology and Oncology, Georgia Cancer Center, Augusta University, 
      Augusta, GA 30912, USA.
FAU - Mitchell, Cassie S
AU  - Mitchell CS
AD  - Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia 
      Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, 
      USA.
AD  - Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA 30332, 
      USA.
LA  - eng
GR  - R21 CA232249/CA/NCI NIH HHS/United States
GR  - R21CA232249/NH/NIH HHS/United States
PT  - Journal Article
DEP - 20220926
PL  - Switzerland
TA  - Cancers (Basel)
JT  - Cancers
JID - 101526829
PMC - PMC9563938
OTO - NOTNLM
OT  - BCR ABL
OT  - adverse event
OT  - chronic myeloid leukemia
OT  - heterogeneous information network
OT  - machine learning
OT  - natural language processing
OT  - side effect
OT  - toxicity
OT  - tyrosine kinase inhibitor
COIS- The authors declare no conflict of interest. The funders had no role in the 
      design of the study; in the collection, analyses, or interpretation of data; in 
      the writing of the manuscript, or in the decision to publish the results.
EDAT- 2022/10/15 06:00
MHDA- 2022/10/15 06:01
PMCR- 2022/09/26
CRDT- 2022/10/14 01:51
PHST- 2022/07/26 00:00 [received]
PHST- 2022/09/04 00:00 [revised]
PHST- 2022/09/23 00:00 [accepted]
PHST- 2022/10/14 01:51 [entrez]
PHST- 2022/10/15 06:00 [pubmed]
PHST- 2022/10/15 06:01 [medline]
PHST- 2022/09/26 00:00 [pmc-release]
AID - cancers14194686 [pii]
AID - cancers-14-04686 [pii]
AID - 10.3390/cancers14194686 [doi]
PST - epublish
SO  - Cancers (Basel). 2022 Sep 26;14(19):4686. doi: 10.3390/cancers14194686.