Background:It has been recognized that as a prostate cancer (PCa) metastasizes to bone, it begins to express bone-specific proteins such as osteopontin, bone sialoprotein, and osteocalcin. This process is known as osteomimicry. Liver metastases (LM) are associated with the poorest clinical outcomes and affect 25% of PCa patients at autopsy. We hypothesized that PCa that metastasize to the liver express liver-specific genes prior to liver metastasis – a process we have named “hepatomimicry”.

Methods:We have curated two lists of putative liver genes in PCa, a proof-of-concept set of liver-relevant genes in the Tempus xT assay (23 genes) and 300 putative genes from GTEX with specifically high liver expression. To test these gene sets, we have collected RNA-seq data from over 3000 PCa samples, including the PCa transcription atlas (n = 2115), West Coast/SU2C Dream Team (n = 210), neuroendocrine PCa from cBioPortal (n = 49), and TEMPUS RNA-seq data generated for Cedars-Sinai (n = 88). In each dataset, for the 23 hepatomimicry genes, we used recursive feature elimination and a t-test to discriminate between PCa LM and non-liver visceral metastases. In datasets with count-level data, we performed differential gene expression analysis with DeSeq2 and gene set enrichment analysis (GSEA) on identified differentially expressed genes. We have also analyzed two single cell (SC) RNA-seq datasets from PCa including liver metastases (SCP1244, 1 LM and GSE210358, 5 LMs), planning to isolate tumor cells from different metastatic locations and compare their gene expression.

Results:In three different datasets, MAT1A, ELF3, and WEE1 were found to be either optimal genes for discriminating between these two groups or significantly different by t-test and were more highly expressed in LM. However, SCRNA-seq showed these genes have modest expression in the specific tumor cells of LM. 437 genes were upregulated in liver metastases (FDR q-value < 0.05, log2 fold change > 1). Subsequent GSEA found that liver-specific gene sets are highly enriched in the genes upregulated in LM.

Conclusions:The initial results indicate that a three-gene subpanel of our initial set have predictive power for LM against other visceral metastases in PCa, but subsequent results indicated other genes from GTEX may be more effective biomarkers. While hepatocyte infiltration may impact the characterization of these samples by yielding a strong signal for liver-specific gene expression signature, confirmation of this finding remains important. Ongoing work is directed at confirming this signature in SCRNA-seq from PCa LM. Our work may be adaptable to developing diagnostic technologies such as liquid biopsies that may enhance the identification of patients who may have occult LM or that may develop LM as part of their natural history so that interventions may be enacted in a more timely manner.

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