Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts
Susmita Mandal,
Tanishq Tejaswi,
Rohini Janivara,
Syamanthak Srikrishnan,
Pradipti Thakur,
Sarthak Sahoo,
Priyanka Chakraborty,
Sukhwinder Singh Sohal,
Herbert Levine,
Jason T. George,
Mohit Kumar Jolly
Affiliations
Susmita Mandal
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Tanishq Tejaswi
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Rohini Janivara
Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
Syamanthak Srikrishnan
Department of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India
Pradipti Thakur
Department of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India
Sarthak Sahoo
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Priyanka Chakraborty
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Sukhwinder Singh Sohal
Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston 7248, Australia
Herbert Levine
Departments of Physics and Bioengineering, Northeastern University, Boston, MA 02115, USA
Jason T. George
Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
Mohit Kumar Jolly
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics—each derived using a different gene list and algorithm—that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.
