Divergent organ-specific isogenic metastatic cell lines identified using multi-omics exhibit differential drug sensitivity

Abstract

Background Monitoring and treating metastatic progression remains a formidable task due, in part, to an inability to monitor specific differential molecular adaptations that allow the cancer to thrive within different tissue types. Hence, to develop optimal treatment strategies for metastatic disease, an important consideration is the divergence of the metastatic cancer growing in visceral organs from the primary tumor. We had previously reported the establishment of isogenic human metastatic breast cancer cell lines that are representative of the common metastatic sites observed in breast cancer patients. Methods Here we have used proteomic, RNAseq, and metabolomic analyses of these isogenic cell lines to systematically identify differences and commonalities in pathway networks and examine the effect on the sensitivity to breast cancer therapeutic agents. Results Proteomic analyses indicated that dissemination of cells from the primary tumor sites to visceral organs resulted in cell lines that adapted to growth at each new site by, in part, acquiring protein pathways characteristic of the organ of growth. RNAseq and metabolomics analyses further confirmed the divergences, which resulted in differential efficacies to commonly used FDA approved chemotherapeutic drugs. This model system has provided data that indicates that organ-specific growth of malignant lesions is a selective adaptation and growth process. Conclusions The insights provided by these analyses indicate that the rationale of targeted treatment of metastatic disease may benefit from a consideration that the biology of metastases has diverged from the primary tumor biology and using primary tumor traits as the basis for treatment may not be ideal to design treatment strategies.

Ways to improve breast cancer patients' management and clinical outcome: The 2020 Assisi Think Tank Meeting

“…In breast cancer research, "omic" technologies have not only enhanced the power of traditional models, but also revolutionized analysis of patient samples, making them an indispensable tool in translational studies. "Omic" studies have provided evidence that evolutionary processes in metastatic progression result in distinct biological entities that diverge greatly from the primary tumour (Winnard et al, 2020).…”