Identifying shared transcriptional risk patterns between atherosclerosis and cancer
Richard A. Baylis,
Hua Gao,
Fudi Wang,
Caitlin F. Bell,
Lingfeng Luo,
Johan L.M. Björkegren,
Nicholas J. Leeper
Affiliations
Richard A. Baylis
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford, CA, USA; Department of Medicine, Division of Cardiology, University of California, San Francisco, CA, USA; Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
Hua Gao
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford, CA, USA
Fudi Wang
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford, CA, USA
Caitlin F. Bell
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
Lingfeng Luo
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford, CA, USA
Johan L.M. Björkegren
Department of Medicine, Karolinska Institute, Huddinge, Sweden; Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Nicholas J. Leeper
Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford, CA, USA; Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Corresponding author
Summary: Cancer and cardiovascular disease (CVD) are the leading causes of death worldwide. Numerous overlapping pathophysiologic mechanisms have been hypothesized to drive the development of both diseases. Further investigation of these common pathways could allow for the identification of mutually detrimental processes and therapeutic targeting to derive mutual benefit. In this study, we intersect transcriptomic datasets correlated with disease severity or patient outcomes for both cancer and atherosclerotic CVD. These analyses confirmed numerous pathways known to underlie both diseases, such as inflammation and hypoxia, but also identified several novel shared pathways. We used these to explore common translational targets by applying the drug prediction software, OCTAD, to identify compounds that simultaneously reverse the gene expression signature for both diseases. These analyses suggest that certain tumor-specific therapeutic approaches may be implemented so that they avoid cardiovascular consequences, and in some cases may even be used to simultaneously target co-prevalent cancer and atherosclerosis.
