To uncover features of PDAC cells that support liver metastasis formation, we utilised available data from the Broad Institute’s DepMap database on human cancer cell line encyclopedia (CCLE) cell lines . Recently, data on the metastatic potential of CCLE cell lines to bone, brain, kidney, lung and liver in immunocompromised mice was reported, including 33 pancreatic cancer cell lines  (Fig. 1A). The metastatic potential of PDAC lines to the liver was fairly diverse as has been reported previously (Fig. 1B). Interestingly, whilst liver metastatic potential correlated with overall metastatic potential (Fig.S1A), there were several examples of lines that metastasised poorly to the liver compared to other organs (e.g. ASPC1, CFPAC1, YAPC; grey bars in Fig. 1B). In order to identify features of “liver tropic” cell lines (i.e. lines that metastasise well to the liver), lines were split into 2 groups, identified as “liver tropic” or “liver atropic” (orange and blue in Fig. 1B respectively). We then utilised existing transcriptional (RNAseq), genetic (SNP, CNV) and CRISPR screen data from DepMap in order to identify differences between these two groups.
We started by analysing RNA sequencing data of cell lines in vitro (Fig. 1C-E). As gene-level variability between different cell lines is large, gene set-based approaches provide a way of identifying changes in broad transcriptional programs between conditions. Gene set variation analysis (GSVA) using the hallmark gene sets uncovered several differences between liver tropic and atropic lines (Fig. 1C). We were particularly struck by the strong enrichment in MYC targets (MYC targets V1: logFC = 0.38, p = 0.02; MYC targets V2: logFC = 0.47, p = 0.02) and downregulation of interferon response pathways (Interferon alpha response: logFC=-0.39, p = 0.02; Interferon gamma response: logFC=-0.33, p = 0.02) . This transcriptional profile was confirmed using the VIPER analysis package to estimate transcription factor (TF) activity based on the sequencing data (Fig. 1D) . Liver tropic cell lines were characterised by increased activity of transcription factors MYC (logFC = 3.18, p = 0.04) and E2F2/4, and a strong downregulation of STAT1/2 (STAT1: logFC=-2.8, p = 0.04; STAT2: logFC=-0.37, p = 0.04) – key TFs in the interferon response pathway  whose promoters were recently shown to be bound by repressive MYC complexes (Muthalagu et al. 2020). Looking at the gene set activities of individual cell lines, we noticed that the majority of liver tropic lines had high MYC and low interferon response activities (Fig. 1E). Interestingly, several cell lines identified previously as being highly metastatic but not to the liver (YAPC, CFPAC1, BXPC3) had the opposite signature to liver tropic lines (see black boxes). To confirm that this profile was liver-specific and not indicative of general metastatic potential, we conducted a similar analysis looking for signatures enriched in brain-metastatic lines (Fig.S1B). Transcriptional signatures in this case were very different. Finally, we classified the cell lines according to two published systems used for molecular subtyping of clinical samples but found no clear association for a particular subtype (Fig.S1C). Thus, cells exhibiting a MYChigh/INFlow transcriptional signature have a specific advantage in colonising the liver (Fig. 1F).
Previous studies have shown that genetic duplications of MYC occur preferentially in liver metastatic clones over primary PDAC tumors . To ask if increased MYC activity had a genetic basis in our analysis, we performed linear regression analysis on single nucleotide polymorphism (SNP), gene- and cytoband-level copy number variation (CNV) data from PDAC cell lines (Fig. 1G). Although a number of potential correlations were found, no SNPs or CNVs in the MYC gene or gene locus were associated with liver tropism, suggesting that the enhanced MYC activity of these cell lines does not have a genetic origin. Finally, analysis of CRISPR KO dependency data identified two genes, EFR3A and TMRT12, which were specifically associated with liver metastatic potential over other organ sites (Fig. 1H, I and S1D). Liver metastatic cells were particularly insensitive to EFR3A KO compared to other PDAC cells. EFR3A has recently been identified as a driver of KRAS signalling in PDAC cells  and suggests that liver metastatic cells may be less reliant on KRAS, supported by the downregulation of the “HALLMARK_KRAS_SIGNALLING_UP” gene set in Fig. 1C. TMRT12 is a tRNA methyltransferase whose silencing is associated with ribosome frame shift events that could impair MYC-driven cell division . Taken together, these data further support the dependence of liver metastatic PDAC cells on MYC activity but do not find evidence that this is related directly to genetic alterations in MYC.
To look for additional evidence for a MYChigh/INFlow transcriptional signature in PDAC liver metastases, we looked to published data of human patient samples. In 2015 Moffitt et al. published a cohort of 187 PDAC samples including 25 liver, 11 lung, 9 lymph metastases, and 145 primary tumors (Fig. 2A) . GSVA analysis of metastasis samples over primary tissue confirmed a MYChigh/INFlow transcriptional signature in liver metastases (Fig. 2B; MYC targets v2: logFC = 0.23, p < 0.001; Interferon alpha response: logFC=-0.31, p < 0.001; Interferon gamma response: logFC=-0.30, p < 0.001). Interestingly, this signature was much less pronounced and non-significant in lung or lymph metastases, supporting the idea of a liver-specific feature of PDAC cells. Further illustrating this, hierarchical clustering of samples using genes from MYC target and Interferon response gene sets showed that liver metastasis samples largely grouped together and were characterised by strong MYC target and low Interferon expression (Fig. 2C). Samples from primary tumor and other metastatic sites were more evenly distributed across this clustering. In agreement with the CCLE cell line data, samples in this region did not appear to be overrepresented in a particular PDAC or stromal subtype (Fig. 2C, top panel).
A limitation of bulk sequencing data is a difficulty in discerning which cell populations contribute to molecular signatures. To look for evidence for a MYChigh/INFlow in PDAC cells of liver metastases, we utilised a recent single cell RNA sequencing (scRNAseq) dataset that contained 14,926 cells from 10 primary PDAC and 5 liver metastatic samples (Fig. 3A) . PDAC cells were identified from samples based on scoring of a “epithelial tumor cell” (ETC) gene set identified by the authors (Fig.S2A; Supp Table 1), isolating 9888 tumor cells (6313 from liver metastases, 3575 from primary tumors). Interestingly, t-distributed stochastic neighbor embedding (tSNE) plots of ETCs showed primary tumor samples from all patients clustered together, whereas liver metastases from different patients formed distinct clusters (Fig. 3B, S2B). Gene set enrichment analysis (GSEA) of individual patient metastases revealed a MYChigh/INFlow transcriptional signature in 4/5 liver samples compared to grouped primary tumor cells (Fig. 3C). Plots of individual genes showed that genes including members of the major histocompatibility complex (HLA-DRB1) and interferon response factors (IRF3) were broadly expressed in primary tumor compared to liver metastases (Fig. 3D, S2C-E). In comparison, key MYC targets such as RPS3 were enriched in liver samples. To further validate this, TF activities were estimated for all cells and compared between all liver metastases and primary tumor samples (Fig. 3E). Interestingly, MYC was the most strongly upregulated TF in liver metastases (LogFC = 1.85, p < 0.001). In comparison, key interferon TFs RFXAP (LogFC=-1.69, FDR < 0.001), STAT1 (LogFC=-0.87, p < 0.001) and STAT2 (LogFC=-0.66, p < 0.001) were all downregulated.
scRNAseq data enables us to ask whether or not MYC and Inteferon response pathways are negatively correlated within individual cells. To test this, VIPER TF estimates of MYC, STAT1 and STAT2 activity were calculated for PDAC cells in liver metastases and primary tumor samples. Activity of STAT TFs were highly correlated (Fig.S2F), whereas MYC activity was negatively correlated with STAT1 expression (Fig. 3F). Taken together, these analyses provide support from clinical samples that the MYChigh/INFlow transcriptional signature is a consistent feature of PDAC cells that have metastasised to the liver. MYC activity suppressing interferon signalling in PDAC cells was recently reported in primary tumors in the KMC (Lsl-KrasG12D;Pdx1CreER;Rosa26DM − lsl−MYC) mouse model of PDAC, driven by activated KRASG12D combined with conditionally expressed MYC driven from the Rosa26 locus . To evidence this relationship, we conducted in vitro experiments using the liver-tropic cell line PSN1 from the DepMap study. Inhibition of ERK1/2 activity leads to rapid loss of MYC protein expression as has been reported previously (Fig. 4A) . To see if loss of MYC altered expression of interferon response genes, qPCR of PSN1 cells was conducted with samples treated with 100nM trametinib (Fig. 4B). Trametinib treatment led to ~ 4 fold change (FC) in interferon regulators, IRF5 (FC = 3.47, p = 0.07), IRF7 (FC = 3.1, p = 0.03) and IFNB1 (FC = 3.2, p = 0.37), whilst MYC expression was drastically reduced (FC = 0.04, p < 0.001). Thus, loss of MYC expression correlates with increased interferon regulatory gene expression.