Cancer is a disease whose initiation, promotion, and evolution are driven by biological mechanisms. There is a wide inter-patient heterogeneity regarding these biological mechanisms, leading to different sensitivities to therapies and outcome. This led to the concept of precision medicine driven by molecular analyses, where molecular portraits of cancer could inform the clinician and patient about which drug should be administered. While this concept has been successful [ 1 Slamon D.J. Leyland-Jones B. Shak S. et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001; 344: 783-792 Crossref PubMed Scopus (9664) Google Scholar , 2 Janne P.A. Yang J.C. Kim D.W. et al. AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer. N Engl J Med. 2015; 372: 1689-1699 Crossref PubMed Scopus (1733) Google Scholar ], we must now address the next set of challenges. Indeed, while genomic and epigenomic alterations have historically been identified as the leading mechanism of cancer growth, recent data suggest that the microenvironment, host biology, and time also influence cancer biology. This introduces a much more complex concept where cancer is viewed as a dynamic system driven by the interplay of multiple biological dimensions. Further improvement in the field of precision oncology should incorporate these dimensions in the molecular portrait of cancers, which will require developing the technologies and mathematical methods to integrate them into a holistic view of patients and their cancer. Such a tool capable of recapitulating the biology of cancer in each patient could be referred to as a Cancer Patient Hologram. To reach these virtual cancers as a long-term vision, we are proposing a bottom-up approach in which multiple teams generate deep knowledge on each component of biology, and then integrate them. This approach has been proposed for building synthetic organs [ 3 Hutchison 3rd, C.A. Chuang R.Y. Noskov V.N. et al. Design and synthesis of a minimal bacterial genome. Science. 2016; 351: aad6253 Crossref PubMed Scopus (861) Google Scholar ]. Bottom-up organization offers the major advantage of being flexible to incorporate new teams, generating intermediate deliverables (biomarkers and drugs), and allowing stepwise improvements of the final product.