Genomic Features of Lung-Recurrent Hormone-Sensitive Prostate Cancer

Pulmonary involvement is rare in metastatic hormone-sensitive prostate cancer (mHSPC) that recurs after treatment for localized disease. Guidelines recommend intensive systemic therapy, similar to patients with liver metastases, but some lung-recurrent mHSPC may have good outcomes. Genomic features of lung metastases may clarify disease aggression, but are poorly understood since lung biopsy is rarely performed. We present a comparative assessment of genomic drivers and heterogeneity in metachronous prostate tumors and lung metastases.

We leveraged a prospective functional imaging study of 208 biochemically recurrent prostate cancers to identify 10 patients with lung-recurrent mHSPC. Histologic diagnosis was attained via thoracic surgery or fine-needle lung biopsy. We retrieved clinical data and performed multiregion sampling of primary tumors and metastases. Targeted and/or whole-exome sequencing was applied to 46 primary and 32 metastatic foci.

Unusually for mHSPC, all patients remained alive despite a median follow-up of 11.5 years. Several patients experienced long-term freedom from systemic treatment. The genomic landscape of lung-recurrent mHSPC was typical of curable prostate cancer with frequent PTEN, SPOP, and chromosome 8p alterations, and there were no deleterious TP53 and DNA damage repair gene mutations that characterize aggressive prostate cancer. Despite a long median time to recurrence (76.8 months), copy number alterations and clonal mutations were highly conserved between metastatic and primary foci, consistent with intrapatient homogeneity and limited genomic evolution.

In this retrospective hypothesis-generating study, we observed indolent genomic etiology in selected lung-recurrent mHSPC, cautioning against grouping these patients together with liver or bone-predominant mHSPC. Although our data do not generalize to all patients with lung metastases, the results encourage prospective efforts to stratify lung-recurrent mHSPC by genomic features.