TY - JOUR
T1 - Gut microbiome, big data and machine learning to promote precision medicine for cancer
AU - Cammarota, Giovanni
AU - Ianiro, Gianluca
AU - Ahern, Anna
AU - Carbone, Carmine
AU - Temko, Andriy
AU - Claesson, Marcus J.
AU - Gasbarrini, Antonio
AU - Tortora, Giampaolo
N1 - Publisher Copyright:
© 2020, Springer Nature Limited.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - The gut microbiome has been implicated in cancer in several ways, as specific microbial signatures are known to promote cancer development and influence safety, tolerability and efficacy of therapies. The ‘omics’ technologies used for microbiome analysis continuously evolve and, although much of the research is still at an early stage, large-scale datasets of ever increasing size and complexity are being produced. However, there are varying levels of difficulty in realizing the full potential of these new tools, which limit our ability to critically analyse much of the available data. In this Perspective, we provide a brief overview on the role of gut microbiome in cancer and focus on the need, role and limitations of a machine learning-driven approach to analyse large amounts of complex health-care information in the era of big data. We also discuss the potential application of microbiome-based big data aimed at promoting precision medicine in cancer.
AB - The gut microbiome has been implicated in cancer in several ways, as specific microbial signatures are known to promote cancer development and influence safety, tolerability and efficacy of therapies. The ‘omics’ technologies used for microbiome analysis continuously evolve and, although much of the research is still at an early stage, large-scale datasets of ever increasing size and complexity are being produced. However, there are varying levels of difficulty in realizing the full potential of these new tools, which limit our ability to critically analyse much of the available data. In this Perspective, we provide a brief overview on the role of gut microbiome in cancer and focus on the need, role and limitations of a machine learning-driven approach to analyse large amounts of complex health-care information in the era of big data. We also discuss the potential application of microbiome-based big data aimed at promoting precision medicine in cancer.
UR - https://www.scopus.com/pages/publications/85087714294
U2 - 10.1038/s41575-020-0327-3
DO - 10.1038/s41575-020-0327-3
M3 - Article
C2 - 32647386
AN - SCOPUS:85087714294
SN - 1759-5045
VL - 17
SP - 635
EP - 648
JO - Nature Reviews Gastroenterology and Hepatology
JF - Nature Reviews Gastroenterology and Hepatology
IS - 10
ER -