Using NGS to Understand Metastasis

In the 17th August 2017 edition of journal Nature, Dan Robinson (University of Michigan) and collaborators presented their results on the genomic profile of metastatic cancer as part of a study under the Michigan Oncology Sequencing program. Five hundred metastatic cancer patients underwent whole exome and transcriptome sequencing under an IRB approved protocol. The results provided a first glimpse of the metastatic cancer atlas, identifying genes having the highest prevalence of somatic and germline mutations. While the most common primary tumors in these patients were prostate cancer, breast cancer, and soft tissue sarcomas; liver, lymph node, lungs, and bone were the most prevalent sites of metastases.

Among the genes that have undergone somatic mutations during metastases were tumor suppressors such as TP53, CDKN2A, PTEN, and RB1 or oncogenes such as PIK3CA. Among the germline variants included DNA repair pathway genes BRCA 1/2, MUTYH, and CHEK2. Majority of the gene fusions found in metastaic cancer impacted loss of function or DNA binding. The study discovered, eight novel fusion pairs were identified that were pathogenic in metastatic cancer and included genes such as BRAF, ALK, and NOTCH2

This work is exciting because it builds up on the genome sequencing work done to characterize primary tumors in the NIH funded Cancer Genome Atlas project and will help in understanding the mechanistic changes required to cause the current treatment against primary tumors to become ineffective and the tumor to metastasize. With the cost of DNA sequencing continuing to come down, it has become possible to use NGS platforms to guide treatment of cancer by identifying genetic mutations that could be candidate targets for drugs.

Robinson et al. also make a strong case for performing DNA sequencing throughout the course of cancer progression or treatment as a monitoring tool to determine if the cancer has undergone metastasis and if so to which organ. Being able to sequence the cancer patient in real time would enable identification of current mutations to which cancer drugs are targeted and increase success rates of achieving positive outcomes.

I welcome additional comments and thoughts on opportunities and challenges of using NGS in identifying treatment options for metastatic cancer.