Through multiomics—combined genomics, transcriptomics, proteomics, digital pathology, and other technologies yet to fully unfold—we can now obtain a complete dynamic vision of cancer,” argue the authors of a recent review article (Marshall et al. The Essentials of Multiomics. 2022; 27(4): 272–284).
They expect that in the near future, the multiomics approach will become routine in tissue testing, where it will generate enormous amounts of data for individual patients. They also anticipate that when this data is analyzed with the help of artificial intelligence, it will “result in improved efficiency and outcomes in our treatment of cancer and other serious illnesses.” Once just a tantalizing possibility, multiomics is now becoming a reality for research and clinical medicine.
However, it still isn’t completely “there.” Some omics technologies lag behind others, and most suffer from the need to integrate the massive amount of data generated. To get a sense of where multiomics stands, we have spoken with several leaders in the field.
They agree that multiomics is already enriching our understanding of health and disease, and that it is just beginning to help us advance drug discovery and precision medicine. While much of biomarker discovery in the last two decades has focused on genomics, more than 80% of disease risk comes from nongenetic factors, according to Mohit Jain, MD, PhD, founder and CEO, Sapient Bioanalytics. “It’s been said that our zip code is.