TY - JOUR
T1 - Personalized Medicine in Cancer Pain Management
AU - Raad, Mohammad
AU - López, William Omar Contreras
AU - Sharafshah, Alireza
AU - Assefi, Marjan
AU - Lewandrowski, Kai Uwe
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/8
Y1 - 2023/8
N2 - Background: Previous studies have documented pain as an important concern for quality of life (QoL) and one of the most challenging manifestations for cancer patients. Thus, cancer pain management (CPM) plays a key role in treating pain related to cancer. The aim of this systematic review was to investigate CPM, with an emphasis on personalized medicine, and introduce new pharmacogenomics-based procedures for detecting and treating cancer pain patients. Methods: This study systematically reviewed PubMed from 1990 to 2023 using keywords such as cancer, pain, and personalized medicine. A total of 597 publications were found, and after multiple filtering processes, 75 papers were included. In silico analyses were performed using the GeneCards, STRING-MODEL, miRTargetLink2, and PharmGKB databases. Results: The results reveal that recent reports have mainly focused on personalized medicine strategies for CPM, and pharmacogenomics-based data are rapidly being introduced. The literature review of the 75 highly relevant publications, combined with the bioinformatics results, identified a list of 57 evidence-based genes as the primary gene list for further personalized medicine approaches. The most frequently mentioned genes were CYP2D6, COMT, and OPRM1. Moreover, among the 127 variants identified through both the literature review and data mining in the PharmGKB database, 21 variants remain as potential candidates for whole-exome sequencing (WES) analysis. Interestingly, hsa-miR-34a-5p and hsa-miR-146a-5p were suggested as putative circulating biomarkers for cancer pain prognosis and diagnosis. Conclusions: In conclusion, this study highlights personalized medicine as the most promising strategy in CPM, utilizing pharmacogenomics-based approaches to alleviate cancer pain.
AB - Background: Previous studies have documented pain as an important concern for quality of life (QoL) and one of the most challenging manifestations for cancer patients. Thus, cancer pain management (CPM) plays a key role in treating pain related to cancer. The aim of this systematic review was to investigate CPM, with an emphasis on personalized medicine, and introduce new pharmacogenomics-based procedures for detecting and treating cancer pain patients. Methods: This study systematically reviewed PubMed from 1990 to 2023 using keywords such as cancer, pain, and personalized medicine. A total of 597 publications were found, and after multiple filtering processes, 75 papers were included. In silico analyses were performed using the GeneCards, STRING-MODEL, miRTargetLink2, and PharmGKB databases. Results: The results reveal that recent reports have mainly focused on personalized medicine strategies for CPM, and pharmacogenomics-based data are rapidly being introduced. The literature review of the 75 highly relevant publications, combined with the bioinformatics results, identified a list of 57 evidence-based genes as the primary gene list for further personalized medicine approaches. The most frequently mentioned genes were CYP2D6, COMT, and OPRM1. Moreover, among the 127 variants identified through both the literature review and data mining in the PharmGKB database, 21 variants remain as potential candidates for whole-exome sequencing (WES) analysis. Interestingly, hsa-miR-34a-5p and hsa-miR-146a-5p were suggested as putative circulating biomarkers for cancer pain prognosis and diagnosis. Conclusions: In conclusion, this study highlights personalized medicine as the most promising strategy in CPM, utilizing pharmacogenomics-based approaches to alleviate cancer pain.
KW - cancer
KW - cancer pain management
KW - pain
KW - personalized medicine
KW - pharmacogenomics
KW - variant
UR - http://www.scopus.com/inward/record.url?scp=85169010777&partnerID=8YFLogxK
U2 - 10.3390/jpm13081201
DO - 10.3390/jpm13081201
M3 - Articulo en revista no especializada
AN - SCOPUS:85169010777
SN - 2075-4426
VL - 13
JO - Journal of Personalized Medicine
JF - Journal of Personalized Medicine
IS - 8
M1 - 1201
ER -