Current State of "Omics" Biomarkers in Pancreatic Cancer.
biomarker
genomics
glycomics
metabolomics
metagenomics
omics
pancreatic cancer
personalized medicine
proteomics
systems biology
transcriptomics
Journal
Journal of personalized medicine
ISSN: 2075-4426
Titre abrégé: J Pers Med
Pays: Switzerland
ID NLM: 101602269
Informations de publication
Date de publication:
14 Feb 2021
14 Feb 2021
Historique:
received:
22
01
2021
revised:
08
02
2021
accepted:
11
02
2021
entrez:
6
3
2021
pubmed:
7
3
2021
medline:
7
3
2021
Statut:
epublish
Résumé
Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.
Identifiants
pubmed: 33672926
pii: jpm11020127
doi: 10.3390/jpm11020127
pmc: PMC7918884
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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