Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

E Summerbell,W Zhou,L H Boise,K Galior,Y Hou,P Vertino,L Rusnak,A I Marcus,J Konen,L Cooper,A Chen,J Saltz,B Dwivedi,J Kowalski,K Salaita

doi:10.1038/ncomms15078

Abstract

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. SaGA was used on collectively invading 3D cancer cell packs to create purified leader and follower cell lines. The leader cell cultures are phenotypically stable and highly invasive in contrast to follower cultures, which show phenotypic plasticity over time and minimally invade in a sheet-like pattern. Genomic and molecular interrogation reveals an atypical VEGF-based vasculogenesis signalling that facilitates recruitment of follower cells but not for leader cell motility itself, which instead utilizes focal adhesion kinase-fibronectin signalling. While leader cells provide an escape mechanism for followers, follower cells in turn provide leaders with increased growth and survival. These data support a symbiotic model of collective invasion where phenotypically distinct cell types cooperate to promote their escape.

Highlights

Phenotypic heterogeneity is widely observed in cancer cell populations
To probe the biology of a rare and phenotypically heterogeneous cell populations, single cells or subclones need to be isolated based upon user-defined criteria, instead of a random isolation approach; we developed a technique to image live cells within a biologically relevant three dimensional (3D) environment, select a cell or cellular group based upon user-defined criteria, extract the cell(s) and subject the cell(s) to genomic and molecular analyses
We can purify, amplify and systematically dissect the biologies of rare cells. This technique, termed spatiotemporal genomic and cellular analysis (SaGA), was used to dissect the phenotypic heterogeneity of collective cancer cell invasion in a 3D lung cancer model. These data incorporate the first SaGA-derived leader and follower cell lines to reveal that leader cells utilize atypical vasculogenesis signalling machinery by secreting vascular endothelial growth factor (VEGF) to attract follower cells in invasive cell chains

Summary

Introduction

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. To probe the biology of a rare and phenotypically heterogeneous cell populations, single cells or subclones need to be isolated based upon user-defined criteria, instead of a random isolation approach; we developed a technique to image live cells within a biologically relevant three dimensional (3D) environment, select a cell or cellular group based upon user-defined criteria, extract the cell(s) and subject the cell(s) to genomic and molecular analyses. In this way, we can purify, amplify and systematically dissect the biologies of rare cells. These data provide proof of concept that SaGA is a powerful technology for dissecting phenotypic heterogeneity within cancer cell populations

Methods

Results

Conclusion