Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG

Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG Nikolaos Giannareas , Qin Zhang , Xiayun Yang , Yijun Tian , Peng Zhang , Yuehong Yang , Aki Manninen , Liang Wang , Gong-Hong Wei doi: https://doi.org/10.1101/2021.09.02.458755 Nikolaos Giannareas 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Qin Zhang 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xiayun Yang 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yijun Tian 2 Department of Tumor Biology, H. Lee Moffitt Cancer Center and Research Institute , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peng Zhang 3 Fudan University Shanghai Cancer Center & Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University , Shanghai, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yuehong Yang 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Aki Manninen 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Liang Wang 2 Department of Tumor Biology, H. Lee Moffitt Cancer Center and Research Institute , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gong-Hong Wei 1 Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu , Oulu, Finland 3 Fudan University Shanghai Cancer Center & Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University , Shanghai, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: gonghong_wei{at}fudan.edu.cn Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression. Introduction Genome-wide association studies (GWASs) have successfully discovered thousands of risk-associated single nucleotide polymorphism (SNP) loci for cancers of prostate and others. While most SNP associations are cancer-specific, roughly one-third of such genomic loci with SNPs associates with multiple types of cancers, namely pleiotropic loci that may have shared mechanisms or hallmarks across cancers 1 . Due to the complexity of human genome, the vast majority of GWAS-identified SNPs fell within non-coding genomic regions that have been proven to possess regulatory functions in modulating gene expression through diverse mechanisms 2 – 6 . Growing evidence indicate that GWAS loci are often involved in expression quantitative trait locus (eQTL) conferring cancer risk via altering the DNA-binding affinity of critical transcription factors to causal SNP-containing regulatory elements such as enhancers, representing a major driving force of cancerous gene expression program 2 , 5 , 7 . However, it remains challenging to define somatic driver transcription factors, target genes and aberrant biological pathways from GWAS discoveries, thereby depicting the molecular mechanisms of germline–somatic interplay and continuum underlying these cancer risk loci. Prostate cancer (PCa) remains the second most common cancer in men and globally affects millions of individuals. It was estimated that more than 1.41 million men have been diagnosed with PCa and 375,000 PCa-associated deaths occurred worldwide in 2020 8 . PCa has complex etiology and high heritability with the estimated familiar risk at 57% 9 . Therefore, unravelling PCa risk-associated genetic factors and investigating their underlying mechanisms and biological impacts are expected to greatly inform our understanding of PCa pathogenesis, progression, and clinical management. Comprehensive GWAS analyses have been performed in men with PCa across diverse ancestry groups, and these studies have jointly identified 270 susceptibility loci harboring over 400 SNPs that reach genome-wide significance (P ⩽ 5x10 - 8 ) in association with PCa risk and aggressiveness 10 – 13 . Of these PCa risk loci, the 17q12/HNF1B locus variants rs4430796, rs11263763 and rs11651052 have been reproducibly found to be associated with PCa susceptibility 14 – 21 . Moreover, SNPs in the 17q12/HNF1B region have also been reported in association with risk of several other cancer types, including pancreatic 22 , ovarian 23 , 24 , testicular 25 , and endometrial 26 cancers. Yet, the mechanistic effects and underlying biology of the 17q12/HNF1B remain elusive for all of these associated cancer types. HNF1B as a 17q12 locus gene, belongs to HNF1 transcription factor family whose members possess a POU-homeodomain responsible for sequence-specific DNA binding to gene cis-regulatory elements (CRE) 14 , 27 . HNF1B has been reported to play roles in tumorigenesis and is used as a biomarker for clear cell carcinomas of the pancreas 28 , colorectal cancer 29 and endometrial carcinoma 30 , implying that HNF1B is a plausible causative gene for this pleiotropic association. TMPRSS2-ERG is the most frequent somatic fusion event in PCa, involving a chromosomal rearrangement of ERG transcription factor hijacking the 5′ androgen-responsive regulatory region of TMPRSS2 to form a constitutively activated mutant TMPRSS2-ERG fusion protein 31 , 32 . The frequency of ERG fusion is variable among different ethnic groups, showing the highest frequency (>50%) in Caucasians, followed by African American (20%-30% ) and Asian men (<20%) 33 – 36 . Aberrant ERG fusion transcription factor influences various pathways and biological processes such as androgen receptor (AR) signaling, transforming growth factor beta 1 (TGF-β) signaling and cell invasion 37 , 38 . Many previous studies reported that TMPRSS2-ERG fusion status is positively correlated with high Gleason score, poor prognosis and advanced tumor stage 39 – 41 . Studies have shown that knockdown of ERG inhibits cell proliferation, invasion and xenograft tumour growth of TMPRSS2-ERG-positive PCa cell line VCaP 42 while ERG overexpression lead to PCa precursor-like lesions in mice 43 and promoted cell invasion in vitro 42 . In addition, cooperation of prostate-specific expression of ERG and genetic activation of the PI3K/AKT pathway drive PCa progression in mouse models 44 . However, given the high rate of TMPRSS2-ERG genomic translocation in PCa, it remains to be investigated whether and how this somatic fusion is involved in germline risk loci for PCa discovered by GWASs. In this study, employing an unbiased enrichment analysis, we show that the transcription factor genes, such as HNF1B, are greatly enriched nearby known PCa susceptibility loci, implying a hypothesis that an interconnected gene regulatory network by core genes, transcription factors in particular, may explain subtle effects of GWAS-discovered SNPs on complex diseases and traits. We therefore focused on the 17q12/HNF1B locus and sought to identify functional causal variants of this region as well as investigate role of HNF1B in PCa development and progression, which in turn may be an example for functional study of this cross-cancer pleiotropic genetic association in other types of cancers. We show that TMPRSS2-ERG is a transcription regulator mediating mechanistic effects of the 17q12 locus and control the expression of HNF1B, which in turn regulates a set of cell cycle genes implicating PCa predisposition and progression. It was found that HNF1B and TMPRSS2-ERG physically interact with each other, have a remarkable chromatin co-occupancy and cooperatively regulate genes implicated in PCa development. Lastly, we observe that common binding sites for HNF1B and TMPRSS2-ERG can explain more of genetic effects on PCa predisposition than that of their unique binding sites, and present a solid example of HNF1B co-option of TMPRSS2-ERG co-regulate the 17p13.3 PCa risk locus. Results Transcription factor genes including HNF1B are markedly enriched in PCa susceptibility loci Transcription factors direct the chromatin binding to cis-acting regulatory DNA elements (CREs) and play central roles in gene expression networks 45 , 46 . We thereby examined whether the genes encoding transcription factors are more likely to be enriched in PCa susceptibility loci and extract nearby genes of each PCa GWAS variant for a statistical examination. This analysis revealed that transcription factor genes are indeed preferentially to be enriched in PCa risk loci ( P = 2.49 x 10 - 6 , hypergeometric distribution test; Fig. 1a ), including many with poorly characterized causal roles ( Fig. 1b ), except for HOXB13, RFX6, and NKX3-1 that have been shown to be causally linked to PCa susceptibility and tumorigenesis 47 – 50 . Remarkably, the 17q12/HNF1B locus with several independent SNPs has been reproducibly found in association with PCa susceptibility ( Fig. 1b ), and the phenome-wide association analysis (PheWAS) using FinnGen cohort data (n=176,899) observed a specific top-ranked association of the 17q12/HNF1B locus variants with PCa across 2,264 disease endpoints ( Fig. 1c ). Together with other observations describing 17q12/HNF1B in association with multiple types of cancer, this finding prompted us to delve into the molecular and biological mechanisms as well as the clinical implications of this locus, and the regulation of HNF1B in PCa. Download figure Open in new tab Figure 1 Transcription factor genes are highly enriched nearby PCa risk loci and the 17q12 HNF1B is associated with PCa cell growth and tumour progression. ( a ) Transcription factor genes are more likely to be enriched in PCa susceptibility loci. ( b ) Circos visualization of enriched transcription factor genes and relevant PCa risk loci. ( c ) Phenome-wide association analysis (PheWAS) for an unbiased examination of potential associations between the transcription factor gene enriched PCa risk loci and 2,264 disease endpoints in the FinnGen study (n = 176,899). The x-axis represents the associated p-values on −log10 scale, genome-wide significance threshold was defined as p = 5×10 −8 and the y-axis indicates the SNPs of the loci described in b . Note that the 17q12 alleles are prevalent in association with PCa in this unbiased PheWAS assessment. ( d ) Depletion of HNF1B in the PCa cell line V16A through lentivirus-mediated shRNA (short hairpin RNA) interference. n = 3 technical replicates, error bars, s.d., ** P < 0.01, *** P < 0.001. ( e ) HNF1B knockdown reduces PCa cell proliferation. Cell proliferation was examined at indicated time points by XTT colorimetric assay (absorbance at 450 nm). n = 3 technical replicates, error bars, s.d., *** P < 0.001. ( f ) Wound healing assay in the V16A cells infected with lentiviruses expressing shRNAs targeting HNF1B . n = 3 technical replicates, error bars, s.d., *** P < 0.001. ( g ) Genome-wide loss-of-function screen in VCaP identified essential genes including HNF1B and ERG for cell survival. Lower scores indicate higher dependency on the gene for cell viability. AR, HOXB13, FOXA1, and MYC are well-known genes driving PCa cell proliferation and survival whereas expression of the tumor suppressor PTEN does not favor PCa cell growth and survival. ( h, i ) HNF1B is highly expressed in primary prostate tumours ( h ) and metastases ( i ) in comparison to normal prostate gland. P-values were assessed by Mann-Whitney U tests. ( j, k ) The expression levels of HNF1B are increased in high-grade tumours indicated by higher clinical Grade ( j ) and Gleason scores ( k ). In d-f , P -values were evaluated using the two-tailed Student’s t-tests. We first evaluated the expression profiles of HNF1B across 31 cancer types using RNA-seq data of The Cancer Genome Atlas (TCGA) and found that HNF1B was highly expressed in PCa compared to the majority of examined cancers ( Supplementary Fig. 1a ). To test the biological relevance of HNF1B in PCa, we performed a cell proliferation assay and found that VCaP cells harboring siRNAs against HNF1B displayed reduced cell growth compared to cells harboring control siRNA ( Supplementary Fig. 1b ). In line with this observation, downregulation of HNF1B via lentivirus-mediated short hairpin RNA (shRNA) greatly attenuated cell proliferation and migration in the PCa V16A cell line while ectopic expression of HNF1B elevated cellular proliferation of RWPE1 cells ( Fig. 1d-f and Supplementary Fig. 1c ). Moreover, the data from a genome-wide CRISPR mediated loss-of-function screen in the PCa cell line VCaP 51 demonstrated that HNF1B is a top-ranked essential gene for cell survival ( Fig. 1g ), further indicating the importance of HNF1B in PCa cell growth and survival. To investigate the functional and clinical relevance of HNF1B in PCa, we analyzed multiple independent PCa expression profile datasets 52 – 57 . The results showed that HNF1B expression is significantly elevated in primary and metastatic prostate tumours compared to normal prostate gland ( Fig. 1h, i ). Moreover, we observed that the mRNA levels of HNF1B are greatly increased in metastatic PCa samples and in tumors of higher grade, higher Gleason score or serum PSA levels ( Fig. 1j, k and Supplementary Fig. 1d-f ), suggesting a potential function for HNF1B in advanced prostate tumors. Hence, we assessed the correlation of HNF1B mRNA levels with patient survival. The results suggested that patients with higher expression levels of HNF1B bear a trend for increased risk of biochemical recurrence ( Supplementary Fig. 1g ). Together, these findings illustrated a potential role for HNF1B in PCa development and progression, indicating that HNF1B is a plausible causative gene underlying the effects of the 17q12 PCa susceptibility locus variants. The 17q12/HNF1B PCa risk locus harbors a single risk-associated gene and multiple causal variants To identify functional causal variants at HNF1B locus, we screened a total of 13 SNPs highly associated with multiple PCa risk variants at 17q12 using the expression quantitative trait locus (eQTL) data from Wisconsin cohort of 466 prostate normal tissue samples 58 – 60 . We first examined the mRNA levels of different HNF1B isoforms and found that HNF1B isoform 1 is dominantly expressed compared to the other two isoforms in prostate tissues ( Supplementary Fig. 2a ). The eQTL analysis revealed a strong significant association between HNF1B isoform 1 and 11 of the 13 SNPs ( Fig. 2a and Supplementary Fig. 2b-l ). Remarkably, further cis-eQTL in this Wisconsin cohort revealed the strongest association of HNF1B among all genes within one mega-base window with any of these 11 SNPs ( Fig. 2b and Supplementary Table 1 ). We next performed CRISPR/Cas9-mediated genome editing in V16A cell line to delete each of the 13 SNP-containing regions and observed great downregulation of HNF1B in most of mixed clones with knockout (KO) of individual SNP-region ( Fig. 2c ). To test whether the SNPs residing in HNF1B locus have an enhancer variant-like function in regulating HNF1B , we examined six SNP regions based on the above CRISPR/Cas9-mediated KO screening. Each SNP region with two possible alleles was cloned into upstream of HNF1B promoter in luciferase reporter constructs in both orientations. Enhancer report assays in LNCaP cells showed that rs7405696, rs11651052, rs9901746, rs11263763, and rs12453443 regions indicate enhancer-like function to activate luciferase gene transcription compared to the HNF1B promoter. Moreover, a few SNP regions indicated an orientation-dependent effect on the enhancer activity and, in particular, the G alleles of rs7405696 or rs9901746 showed apparently stronger activity than the C alleles of rs7405696 or the allele A of rs9901746 towards HNF1B promoter in regulating its expression ( Fig. 2d ). To further verify CRISPR/Cas9 screen and the enhancer report assays, we perform genomic deletion of those SNP-enhancer regions through CRISPR/Cas9-mediated KO at single cell levels in the PCa 22Rv1 cells. We observed a profound downregulation of HNF1B in every clone in which SNP-enhancer regions were deleted ( Fig. 2e ). These results pointed to HNF1B as a PCa risk-associated gene and defined several potential causal variants that are likely to be involved in the regulation of HNF1B expression at 17q12 locus. Download figure Open in new tab Figure 2 Multiple eQTL SNPs at 17q12 locus are potential causal variants and involved in the regulation of HNF1B expression. ( a ) Eleven of the thirteen SNPs in the HNF1B region were found to have significant eQTL association with HNF1B isoform 1 expressed in prostate glands or tumours. The SNP rs11986220 within the 8q24 region was used as a non-relevant control site for the analysis. HNF1B-001 (NCBI source: NM_000458); HNF1B-003(NCBI source: NM_001165923); HNF1B-004 (NCBI source: NM_001304286). ( b ) The 17q12/HNF1B locus eQTL analysis of genes within 1-Mbp region using the Wisconsin cohort of 466 benign prostate tissues. ( c ) RT-qPCR analysis to determine the mRNA expression levels of HNF1B in V16A cells with partial knockout (KO) of each SNP region or dampened HNF1B via CRISPR/Cas9 genome editing technology. n = 3 technical replicates, error bars, s.d, * P < 0.05, ** P < 0.01, *** P < 0.001, N.S: Non-significant. ( d ) Reporter assays on six SNP regions with different alleles and in both orientations (5‘-3’, 3‘-5’) showing contribution of each region as an enhancer for HNF1B promoter in LNCaP. Prom: Promoter. n = 3 technical replicates, error bars, s.d. * P < 0.05, ** P < 0.01, *** P < 0.001, N.S: Non-significant. ( e ) RT-qPCR analysis of HNF1B expression levels in 22Rv1 cell clones with CRISPR/Cas9-mediated deletion of each SNP region. Two independent clones were isolated for analysis from each KO-population. n = 3 technical replicates, error bars, s.d. ** P < 0.01, *** P < 0.001. In b-d , P values were evaluated using the two-tailed Student’s t tests. Somatic TMPRSS2-ERG fusion as a regulator of the 17q12/HNF1B PCa risk locus To figure out potential transcription factors that are regulating HNF1B via the causal variant containing regions, we performed a genome-wide co-expression analysis of HNF1B in several large clinical PCa datasets. Intriguingly, ERG emerged as the most positively co-expressed gene with HNF1B in TCGA cohort comprised of 497 primary PCa tumours ( Fig. 3a, b and Supplementary Fig. 3a ). ERG was also found as a top-ranking gene showing positive expression correlation with HNF1B in another cohort of 264 PCa tumours ( Supplementary Fig. 3b ). By contrast, ERG exhibited no apparent expression correlation with HNF1B in normal prostate tissues ( Supplementary Fig. 3c-e ), suggesting that this association is specific to human prostate tumorigenesis. As mentioned above, a common somatic genomic rearrangement involves TMPRSS2 and ERG genes that form an androgen signaling-regulated mutant transcription factor, TMPRSS2-ERG 31 , 61 , 62 . We next assessed whether ERG contributes to the regulation of HNF1B expression by using siRNA-mediated knockdown assay in VCaP cells that harbors a TMPRSS2-ERG fusion 31 . This analysis revealed that depletion of TMPRSS2-ERG resulted in decreased mRNA levels of HNF1B ( Fig. 3c ). Download figure Open in new tab Figure 3 ERG is a responsible transcriptional regulator of the 17q12 locus and regulates HNF1B in PCa cells and clinical tissues in a manner dependent on TMPRSS2-ERG fusion status. ( a,b ) Unbiased genome-wide analysis showing ERG as the most co-expressed gene positively correlated with HNF1B in PCa specimens. ( c ) Depletion of ERG results in reduced mRNA levels of HNF1B in TMPRSS2-ERG fusion positive VCaP cell. n = 3 technical replicates, error bars, s.d. *** P < 0.001. ( d ) Genome browser representation of ChIP-seq signals of active enhancer marks and transcription factor ERG at HNF1B regions harboring several potential causal SNPs as indicated. ( e-g ) ChIP-qPCR validation for chromatin enrichment of ERG, H3K4me1, H4K4me2, H3K4me3, and H3K27ac at given SNP regions in VCaP cells treated with 100nM DHT. n = 3 technical replicates, error bars, s.d. * P < 0.05, ** P < 0.01, *** P < 0.001. ( h, i ) Scatter plots showing positive correlations between ERG and HNF1B expression in PCa specimens with TMPRSS2-ERG fusion. ( j-l ). Four SNPs individually had a significant eQTL association with HNF1B expression in TMPRSS2-ERG fusion positive PCa group ( l ) but not in the whole cohort ( j ) or in ERG fusion negative group ( k ). In c, e-g , P -values were evaluated using two-tailed Student’s t-tests. To understand the regulatory mechanisms at HNF1B locus, we explored a large collection of genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) data derived from PCa 63 . We found an enrichment of epigenetic marks (H3K4me1/2 and H3K27ac) for active enhancers and chromatin binding of ERG transcription factor across or nearby multiple potentially causal SNPs within HNF1B locus ( Fig. 3d ). We next performed ChIP assays with antibodies to ERG, histone modifications, or with IgG as controls. Using quantitative PCR (qPCR), we confirmed specific chromatin enrichment of ERG, H3K4me1, H4K4me2, H3K4me3, and H3K27ac at rs12453443, rs7405696, rs718960, rs11263763, and rs11651052 regions, respectively ( Fig. 3e-g and Supplementary Fig. 3f, g ). Given that ERG hijacks the regulatory element of TMPRSS2 gene to form the most frequent ERG fusion in the clinical setting of PCa 31 , we further investigated in various cohorts whether the expression correlation between ERG and HNF1B is dependent on the TMPRSS2-ERG fusion status. These analyses revealed that ERG and HNF1B show apparent co-expression in TMPRSS2-ERG fusion-positive groups of PCa specimens, but not in ERG fusion-negative groups ( Fig. 3h , i and Supplementary Fig. 3h, i ). SNPs are germline inherited while TMPRSS2–ERG fusion is an acquired somatic genomic alteration. Concurrent presence of these germline-somatic features might exert synergistic impact on the target gene HNF1B with a positive eQTL signal in this region. In line with this, we found that none of these 13 SNPs ( Fig. 2a ) had eQTL association with HNF1B in TCGA cohort of PCa patients ( Fig. 3j ). When taking into account of TMPRSS2-ERG fusion status and stratifying patients into TMPRSS2-ERG fusion-positive and negative groups, we observed that the eQTL results from the ERG fusion-negative group are non-significant ( Fig. 3k and Supplementary Fig. 4 ), whereas four SNPs showed significant eQTL signal with HNF1B in the TMPRSS2-ERG fusion-positive PCa tumours ( Fig. 3l and Supplementary Fig. 5 ). Taken together, these results suggest that the effect of these variants on the target gene HNF1B are further orchestrated by the acquired somatic event of TMPRSS2-ERG gene fusion. HNF1B regulates cell cycle progression pathways implicating PCa severity To understand the role of HNF1B in PCa, we performed RNA-seq analysis of differentially expressed genes upon depletion of HNF1B with siRNA control or two different siRNAs against HNF1B in the PCa VCaP cells ( Fig. 4a ). In each experimental group, two biological replicates were included and showed high correlations ( Supplementary Fig. 6a-c ). This RNA-seq analysis identified 207 significantly upregulated and 132 downregulated genes by HNF1B, respectively (DESeq2, P<0.05; Fig. 4b and Supplementary Fig. 6d, e ). To investigate potential functional categories of HNF1B knockdown target genes, we performed gene set enrichment analysis (GSEA) and revealed several cell cycle relevant terms highly enriched in HNF1B upregulated genes ( Fig. 4c, d ), further supporting the above described role of HNF1B in promoting PCa cell proliferation and invasion ( Fig. 1e-g ). To explore the clinical relevance of HNF1B target genes in PCa, we generated a cell cycle or knock-down signature of HNF1B target genes ( see Methods ). We evaluated the clinical significance in multiple independent cohorts and found that HNF1B cell cycle signature score is positively correlated with the cell cycle progression (CCP) scores 64 ( Fig. 4e, f and Supplementary Fig. 6o-u ). Consistently, the HNF1B knock-down signature derived from differentially expressed genes by HNF1B also displays noteworthy positive linear correlation with the CCP scores ( Fig.4g and Supplementary Fig. 7a-h ). We next investigated the clinical relevance of HFN1B cell cycle signature with PCa tumour progression and severity. The results indicated that the HNF1B cell cycle signature score is significantly elevated in the metastatic group than primary PCa and normal prostate glands ( Fig. 4h, i and Supplementary Fig. 7i ). Patients with higher levels of HNF1B cell cycle signature score are strongly associated with PCa severity, including neoplasm status, Gleason score, lymph node metastasis, tumor stage, and biochemical recurrence ( Fig. 4j-m and Supplementary Fig. 7j-m ). In addition, we observed that patient group with higher levels of HNF1B cell cycle signature score are associated with shorter overall survival, elevated biochemical relapse and metastasis risk ( Fig. 4n-p and Supplementary Fig. 7n, o ). To further investigate the clinical importance of HNF1B target genes, we derived HNF1B knockdown upregulated signature, consisting of 207 upregulated genes. We found that patients with higher levels of the score are associated with PCa tumour progression and severity ( Supplementary Fig. 6f-n ). Collectively, these findings indicate a strong association of HNF1B target genes with PCa progression and implicate the role of HNF1B in PCa severity. Download figure Open in new tab Figure 4 HNF1B gene signatures correlate with PCa progression in the clinical setting. ( a ) Depletion of HNF1B in VCaP cells treated with DHT 100nM 72hrs. n = 3 technical replicates, error bars, s.d. *** P < 0.001, two-tailed Student’s t test. ( b ) Heatmap of HNF1B regulated genes measured by RNA-seq (p < 0.05). ( c ) Top-ranked GSEA enriched pathways associated with genes upregulated and downregulated by HNF1B, respectively. Categories were ranked by Normalized Enrichment Score (NES). ( d ) GSEA enrichment plots displaying enrichment of cell-cycle related pathways among HNF1B upregulated genes. ( e,f ) Cell-cycle gene signature based on z-score sum of the 33 cell cycle relevant genes differentially regulated by HNF1B showing strong positive correlations with cell cycle progression (CCP) score in TCGA and SU2C-PCF cohorts, respectively. ( g ) Pearson correlation test displays significant positive linear correlation of HNF1B knock-down signature with CCP score in TCGA cohort. ( h-m ) Higher HNF1B cell cycle signature scores are associated with tumour progression to metastasis ( h-j ), higher Gleason score ( k ), lymph node-positive PCa ( l ), and higher tumour stages (Mann-Whitney U test or Kruskal-Wallis test). ( n-p ) Kaplan-Meier curves depicting the associations between overall survival, biochemical relapse, or metastasis of PCa patients and the HNF1B cell cycle signature scores in three different cohorts. P -value was calculate using log-rank test. ( q ) Differentially expressed genes that are significantly co-expressed with HNF1B are more likely to be co-expressed with TMPRSS2-ERG in TCGA cohort. ( r ) A 25 gene co-expression signature with HNF1B displayed a similar expression pattern as ERG in DKFZ cohort of 118 patients. Download figure Open in new tab Figure 5 HNF1B physically interacts with ERG and co-opts ERG for chromatin co-occupancy and clinical correlation in PCa. ( a ) IP-WB assay displaying endogenous interaction of HNF1B and ERG in VCaP cells treated with 100nM DHT for 24hrs. ( b ) Exogenous interaction of recombinant HNF1B and TMPRSS2-ERG proteins in 293T cells. ( c ) Schematic of the full-length HNF1B (NM_000458) with D-dimerization domain (1-32aa), POU S -POU-specific domain (89-178aa), NLS-nuclear localization signal (229-235aa), POU H - POU homeodomain (236-313aa), and T-transactivation domain (314-557aa). Three recombinant domains tested for ERG interaction: HNF1B-D (1-88aa), HNF1B-POU (89-313aa) and HNF1B-T (314-557aa). aa: amino acids. ( d ) Interaction of HNF1B with ectopically expressed ERG in vitro via POU domain determined by co-IP in 293T cells. ( e ) Over 70% of HNF1B binding sites are co-occupied by ERG. ( f ) Heatmaps of RNA-seq and ChIP-seq signals on the direct target genes of HNF1B and ERG. HNF1B and ERG ChIP-seq signals are plotted for the genes shown, where blue color indicates higher enrichment. ( g ) Chromatin-binding of HNF1B and ERG on the representative genes, TFF1 , RASSF7 , and POLR3F . The chromosome number and position of the peaks are also indicated. ( h,i ) Pearson correlation tests showing strong positive linear correlation between HNF1B & ERG direct target gene signature scores and CCP scores in TCGA and SU2C-PCF cohorts of PCa patients. HNF1B and ERG direct target gene signature based on z-score sum of the 51 differentially upregulated genes by siRNAs against HNF1B also with ERG & HNF1B ChIP-seq coverage. ( j,k ) Kaplan-Meier curves depicting the overall survival of PCa patients in TCGA and SUC2-PCF cohorts. Patient groups were stratified by median levels of HNF1B & ERG direct target gene signature scores. The log rank p-values are denoted in the figures. In a-d , representative experiment of three independent co-immunoprecipitation experiments is shown. Download figure Open in new tab Figure 6 PCa susceptibility alleles are highly enriched in HNF1B and ERG co-occupied chromatin regions. (a) Enrichment analysis of PCa GWAS risk SNPs within ChIP-seq peaks showing an apparent increased likelihood in common chromatin binding sites of HNF1B and ERG. (b) Circos plot overview of PCa risk loci enriched in the HNF1B and ERG common chromatin binding sites. The outer ring is a circular ideograph of the human genome annotated with chromosome numbers. Tag SNPs are positioned in each locus followed by corresponding proxy SNPs with a cutoff R2 >=0.8. The eQTL genes are indicated adjacent to proxy SNPs. (c,d) Kaplan-Meier plots displaying biochemical relapse and metastatic rates of PCa patients in TCGA cohort with an intermediate risk of Gleason score 7. Patient groups were stratified by median z-score sum of the 17 eQTL genes with associated alleles enriched in both HNF1B and ERG chromatin occupied regions. P-value assessed by a log rank test. (e) Heatmap demonstrating the expression profile of the eQTL genes in the clinical specimens. Note that FAM57A, GEMIN4, and VPS53 display a similar expression pattern to HNF1B and ERG in the SU2C/PCF cohort of PCa patients. (f) HNF1B and ERG ChIP-seq signals at the 17p13.3/rs684232 region harboring the eQTL genes VPS53, FAM57A, and GEMIN4. rs684232 alters co-occupancy of HNF1B-ERG heterodimer. Genomic browser tracks and rs684232-surrounding genome sequence PWM matches are displayed. (g) ChIP-qPCR validation of HNF1B and ERG binding at the regions within 17p13.3 in VCaP cells treated with 100nM DHT. (h) ERG knockdown in VCaP cells downregulates mRNA levels of HNF1B, VPS53, FAM57A, and GEMIN4. (i) CRISPR/Cas9-mediated deletion of HNF1B leads to reduced mRNA levels of VPS53, FAM57A, and GEMIN4 in V16A cells. (j,k) Scatter plots displaying positive linear expression correlation between FAM57A and HNF1B or ERG in two independent cohorts of prostate tumours. (l,m) HNF1B or FAM57A expression levels are significantly elevated in TMPRSS2-ERG fusion positive PCa specimens compared to non-ERG-fusion group. In g-i , n = 3 technical replicates, error bars, s.d. *** P < 0.001, two-tailed Student’s t-test. Download figure Open in new tab Figure 7 Effects of the 17p13.3 locus PCa susceptibility alleles on VPS53 , FAM57A and GEMIN4 . ( a ) Luciferase reporter assays showing elevated enhancer activity of the regions with rs2955626, rs684232 and rs461251 for the promoters of VPS53, FAM57A and GEMIN4, respectively. E: Enhancer; P: Promoter; Luc: Luciferase. N = 3 technical replicates, error bars, s.d. * P < 0.05, ** P < 0.01, *** P < 0.001, NS: Non-significant. (b) 3C analysis of chromatin interactions between rs2955626, rs684232 and rs461251 region, and the promoters of FAM57A or GEMIN4 in a 45kb genomic area (chr17:612,242-656,774) at 17p13.3 locus. S1: rs2955626; S2: rs684232 and rs461251. 3C constant fragment colored in red. (c) RT-qPCR analysis of the mRNA levels of VPS53 , FAM57A , and GEMIN4 in mixed clones of V16A cells with CRISPR/Cas9-mediated deletion of rs2955626, rs684232 or rs461251 region. Each group with selected four distinct mixed clones. N = 3 technical replicates, error bars, s.d. * P < 0.05, ** P < 0.01, *** P < 0.001, NS: Non-significant. ( d ) Depletion of VPS53 , FAM57A and GEMIN4 in 22Rv1 through lentivirus-mediated shRNA knockdown. N = 3 technical replicates, error bars, s.d. *** P < 0.001. ( e-g ) Knockdown of VPS53 ( e ), FAM57A ( f ) or GEMIN4 ( g ) reduces PCa cell proliferation, N = 3 technical replicates, error bars, s.d. ** P < 0.01, *** P < 0.001. ( h-j ) Wound healing assay in 22Rv1 cells infected with lentiviruses expressing shRNAs for ( h ) VPS53, ( i ) FAM57A and ( j ) GEMIN4, n = 3 technical replicates, error bars, s.d. ** P < 0.01, *** P < 0.001. ( k ) Model of the germline-somatic interplay at the 17p13.3 locus between TMPRSS2-ERG and HNF1B driving PCa cell growth and tumour severity. ( i ) Androgen signaling implicates the development of TMPRSS2-ERG fusion and stimulates its expression via androgen-responsive TMPRSS2 element. ( ii ) Aberrant TMPRSS2-ERG fusion cooperating with the 17q12 PCa susceptibility locus augments the expression of HNF1B. ( iii ) HNF1B co-opts TMPRSS2-ERG fusion and synergistically regulates a dozen of PCa risk loci ( Figure 6a-b ), including the 17p13.3 PCa susceptibility genes VPS53, FAM57A and GEMIN4, thereby driving PCa cell proliferation and tumour progression and severity. Lower panel summarizes regulatory circuits at the PCa risk locus chr17p13.3 through HNF1B co-option of TMPRSS2-ERG. S1: rs2955626; S2: rs684232 and rs461251. In a-j , P -values were evaluated using two-tailed Student’s t tests. Given that HNF1B is directly regulated by and co-expressed with ERG transcription factor, we examined whether HNF1B targeted genes are also regulated by ERG. Thus, we first performed a co-expression analysis of HNF1B and 339 differentially expressed genes by HNF1B across multiple clinical PCa datasets. We found that the fraction of genes co-expressed with HNF1B was higher, showing significant co-expression with ERG ( Fig. 4q and Supplementary Fig. 7p ). Based on RNA-seq analysis of HNF1B knockdown, we next curated a panel of 25-gene as HNF1B co-expression signature and measured the degree of their expression correlation with ERG in prostate tumours. The results indicated a similar expression pattern for the 25 genes when compared ERG ( Fig. 4r and Supplementary Fig. 7q ), further supporting a functional interplay between the PCa susceptibility gene HNF1B and the PCa-specific somatic ERG fusion transcription factor. HNF1B and ERG display physical interaction, chromatin co-occupancy and cooperative regulation of PCa genes Given that ERG fusion correlates with and regulates HNF1B expression and is a transcriptional mediator of HNF1B locus variants, we next examined whether there HNF1B and ERG may interact physically with each other. To this end we performed co-immunoprecipitation (Co-IP) assays that revealed indeed an interaction between endogenous HNF1B and TMPRSS2-ERG in VCaP cells treated with DHT ( Fig. 5a ). Moreover, our experiments showed protein-protein interaction between ectopically expressed V5-tagged TMPRSS2-ERG and flag-tagged HNF1B ( Fig. 5b and Supplementary Fig. 8a ). We found that ERG interacts with the POU domain of HNF1B protein ( Fig. 5c, d and Supplementary Fig. 8b ). Consistent with the physical cooperation of TMPRSS2-ERG and HNF1B, it was observed that more than 70% (3,632/5,133) of HNF1B genome-wide binding sites were co-occupied by TMPRSS2-ERG ( Fig. 5e ). We next derived a list of 51 genes as the joint target signature of HNF1B and ERG via an integrated analysis of RNA-seq-defined HNF1B upregulated genes and ChIP-seq profiled genomic co-occupancies of HNF1B and ERG ( see Methods ; Fig. 5f ) , and showed chromatin co-binding of HNF1B and ERG at the three representative genes TFF1 , RASSF7 , and POLR3F ( Fig. 5g ). We next examined the correlation of HNF1B/ERG joint target signature with CCP scores and observed a significant positive linear correlation in multiple independent PCa cohorts ( Fig. 5h, i and Supplementary Fig. 8c-f ). Furthermore, patients with higher levels of the signature score is associated with shorter overall survival ( Fig. 5j, k ). Taken together, those results indicate another layer of germline-somatic interplays between HNF1B and TMPRSS2-ERG, including their protein-protein interaction, genome-wide chromatin co-localization and a potential synergistic role for the activation of cis-regulatory elements driving gene expression for PCa progression and prognosis. HNF1B and ERG co-occupied chromatin regions indicate a greater enrichment of germline variants across PCa risk loci including 17p13.3 Given that ERG fusion is a transcriptional regulator of PCa risk locus in the 17q12/HNF1B region and physically interacts and shares chromatin binding sites with HNF1B, we asked whether HNF1B alone or together with ERG exerts the genetic impacts that explain PCa risk associations. Hence, we performed an enrichment analysis of SNPs in high linkage disequilibrium (LD, R 2 > 0.8) with PCa GWAS variants in ERG unique, ERG and HNF1B common as well as HNF1B unique binding sites, respectively. Strikingly, we found that PCa risk SNPs are more likely to be enriched in the common binding sites of TMPRSS2-ERG and HNF1B compared to their unique DNA-binding regions ( Fig. 6a ). We next examined a genotype-gene expression association of these enriched SNPs from three sources of eQTL datasets, including GTEx 65 , PancanQTL 66 and ncRNA-eQTL 67 , and jointly identified 17 eQTL genes (eGenes) for five PCa loci ( Fig. 6b ) . We generated a HNF1B & ERG eGene signature and explored its potential prognostic value in the clinical PCa settings. This analysis showed an elevated risk for biochemical relapse and metastasis in the patient groups with intermediate Gleason score 7 while having higher eGene signature scores ( Fig. 6c, d ) but not in PCa patients with Gleason score 6 or 8 ( Supplementary Fig. 9a-d ), suggesting that this eGene signature may serve as molecular stratifier for PCa patients with intermediate risk disease. We and others have shown that transcription factors can bind to SNP regions, and often regulate SNP-linked eQTL genes which they are co-expressed 4 , 47 , 68 . We thus examined the expression pattern of the 17 eGenes in two independent cohorts of 266 or 118 PCa patients 69 , 70 and found that most of the eGenes indicated high degree of co-expression with HNF1B and ERG, and interestingly, FAM57A together with GEMIN4 and VPS53 at the 17p13.3 PCa risk locus consistently displayed the strongest co-expression with both HNF1B and ERG ( Fig. 6e and Supplementary Fig. 10a ). We then focused on the 17p13.3/rs684232 locus that has been reproducibly reported to be strongly associated with PCa susceptibility 12 , 71 whereas the underlying biology and functional mechanisms remain elusive. In agreement with an enrichment of the 17p13.3 locus variants in HNF1B and TMPRSS2-ERG common binding sites, ChIP-seq profiles in ERG fusion-positive VCaP cells display multiple strong binding peaks of HNF1B and TMPRSS2-ERG at the 17p13.3/rs684232 region ( Fig. 6f ). These chromatin occupancies were further validated through ChIP-qPCR assays ( Fig. 6g ). To examine whether variation at rs684232 directly influenced DNA-binding motifs of any transcription factors, we employed bioinformatics analysis using the enhancer element locator tool 72 and the motif collection of human transcription factors 45 , 73 . This analysis showed that the rs684232/17p13.3 appears to alter the HNF1B-ERG heterodimer (lower panel, Fig. 6f ). Based on these findings, we hypothesized that HNF1B and ERG could functionally influence the expression of 17p13.3 locus genes. We thus performed siRNA-mediated knockdown of ERG in VCaP treated with DHT and CRISPR-Cas9-mediated genomic deletion of HNF1B in the LNCaP-derived castration resistant cell model V16A 74 , and found downregulation of VPS53 , FAM57A and GEMIN4 mRNA levels ( Fig. 6h, i ). Furthermore, through querying multiple clinical PCa datasets, we found a positive expression correlation between FAM57A and ERG or HNF1B in prostate tumours ( Fig. 6j, k ), but not in adjacent normal prostate tissues ( Supplementary Fig. 10b, c ), indicating ERG and HNF1B directed transcriptional reprogramming in PCa development. ERG has been reported to be highly expressed in TMPRSS2-ERG fusion-positive PCa specimens 31 . In line with this, we found that ERG expression levels were significantly higher in ERG fusion-positive group compared to ERG fusion-negative PCa patient group ( Supplementary Fig. 10d, e ). We next examined whether the expression levels of FAM57A and HNF1B are dependent on ERG fusion status in the clinical PCa cohorts. Expectedly, the mRNA levels of HNF1B and FAM57A are greatly higher in ERG fusion-positive groups ( Fig. 6l, m and Supplementary Fig. 10f, g ). Given that a cluster of cis-regulatory elements were reported to regulate elevated expression of TMPRSS2-ERG 75 and that TMPRSS2-ERG bound at a broad H3K27ac-marked super-enhancer region in HNF1B ( Fig. 3d ) while TMPRSS2-ERG together with HNF1B co-occupied at the rs684232/17p13.3 region ( Fig. 6f ), we investigated whether known transcription inhibitors could perturb this transcriptional misregulation circuit that drives the expression of several PCa risk-associated genes. Thus, we treated the PCa cell line V16A with different concentration of BET inhibitor that is known to target a family of BRD proteins highly activated in PCa and playing roles in the control of cell-cycle-associated genes 76 , 77 . The results showed marked reduction of HNF1B , FAM57A , and GEMIN4 expression ( Supplementary Fig. 10h ), indicating a translational potential of converged somatic ERG fusion, germline loci 17p13.3/rs684232 and 17q12/HNF1B in the same clinical setting. Multiple causal variants and causative genes at 17p13.3 implicating PCa susceptibility We next examined an enhancer-like function of the 17p13.3 region harboring the SNPs rs2955626, rs684232 and rs461251 for PCa susceptibility genes VPS53 , FAM57A and GEMIN4 . Hence, we proceeded to test whether these SNPs could directly alter the promoter activity of VPS53 , FAM57A and GEMIN4 , respectively. We inserted the SNP-containing regions into the upstream of VPS53 , FAM57A or GEMIN4 promoter in pGL4.10-basic vector, except for rs2955626 already within the promoter region of VPS53 , and performed enhancer reporter assays in VCaP cells with ETH and DHT treatment. The results showed that SNP-containing regions possess an enhancer activity towards VPS53 , FAM57A and GEMIN4 . Notably, the rs684232 and rs461251-containing regions have an increased enhancer activity when VCaP cells were treated with DHT compared to that of ETH treatment ( Fig. 7a ). To investigate whether there are direct chromatin interactions between rs2955626/rs684232/rs461251-containing enhancer and proximal regulatory regions of VPS53 , FAM57A and GEMIN4 , we performed quantitative chromosome conformation capture assays (3C-qPCR) 78 with the restriction enzyme HindIII. The constant fragment was designed between the two binding sites of HNF1B and ERG with the SNPs rs2955626, rs684232 and rs461251 ( Fig. 7b ). We determined its interaction with HindIII-digested chromatin fragments in a 45-kb region covering VPS53 , FAM57A and GEMIN4 promoter regions in VCaP cells with ETH or DHT treatment and the lung cancer cell line A549. The results showed that the SNP regions have higher crosslinking frequencies with FAM57A in DHT-treated VCaP compared to ETH-treated VCaP or lung cancer cells A549, suggesting an apparent impact on the observed interactions between the SNP enhancers and FAM57A upon androgen stimulation ( Fig. 7b ). To further verify if rs2955626, rs684232 and rs461251 are directly involved in the regulation of VPS53 , FAM57A and GEMIN4 , we applied the CRISPR/Cas9 genome editing approach in PCa cell line V16A and obtained four independent mixed cell clones with partial depletion of each SNP enhancer region at 17p13.3. The results showed reduced transcriptional levels of VPS53 , FAM57A and GEMIN4 upon deletion of the regulatory region harboring rs2955626, rs684232 or rs461251 compared to the parental V16A line ( Fig. 7c ), suggesting a causal function of rs2955626, rs684232 and rs461251 for the expression of VPS53 , FAM57A and GEMIN4 . Finally, to test the biological relevance of the 17p13.3 locus genes, we pursued tumour cellular assays to demonstrate the effect of VPS53, FAM57A and GEMIN4 on PCa cellular phenotypes. The PCa 22Rv1 cells harboring shRNAs against VPS53 , FAM57A or GEMIN4 showed markedly attenuated cell growth and viability in comparison with cells harboring control shRNA in the proliferation assays ( Fig. 7d-g ). Consistent results were obtained via a real-time monitoring of wound-healing assays, indicating that 22Rv1 cells harboring gene-specific shRNAs showed decreased wound closure rates ( Fig. 7h-j ). Collectively, these results support a mechanistic model of multiple causal variants and causative genes implicating PCa susceptibility and tumour cellular transformation at this 17p13.3 locus. Discussion In this study, we revealed an extensive germline-somatic interaction implicating susceptibility and development of PCa through the oncogenic regulatory circuits, consisting of the most frequent PCa-specific somatic genomic alteration TMPRSS2-ERG, and several germline PCa risk locus genes such as HNF1B at 17q12 and VPS53-FAM57A-GEMIN4 at 17p13.3 ( Fig. 7k ). Our findings demonstrated not only multiple potential causal SNPs and risk CREs within 17q12/HNF1B locus, and the responsibility of TMPRSS2-ERG fusion for transforming molecular and biological effects of 17q12 and regulating HNF1B expression, but also mapped genome-wide binding sites of HNF1B and defined its high rate of chromatin co-occupancy with TMPRSS2-ERG that can explain more of genetic associations discovered by GWASs in PCa. Given that the 17q12/HNF1B has been reported as a cross-cancer pleiotropic genetic risk locus 14 – 26 , our work revealed a better understanding of its underlying causation and biological mechanisms implicating in PCa risk prediction and prognosis, while exhibited as an example for the comprehensive evaluation of this locus contributing to risk association and disease progression in other types of cancers. HNF1B has three isoforms through alternative splicing and has been shown that the two longer isoforms tend to be transcriptional activators, whereas the shortest isoform is a transcriptional repressor 79 . We proved for the first time the relationship between HNF1B isoforms and the 17q12 PCa risk SNPs by which an eQTL analysis indicates a strong association between 11 SNPs and HNF1B isoform 1, the dominant isoform expressed in prostate specimens and other tissues. Moreover, we discovered the role of HNF1B in regulating genes involved in cell cycle progression pathways implicated in PCa progression and clinical severity. Despite the fact that TMPRSS2-ERG has been reported as the most frequent genomic rearrangement in PCa and shown profound roles in PCa initiation and development, our study for the first time reported the association of TMPRSS2-ERG with this cross-cancer locus of 17q12/HNF1B, mechanistically and biologically implicating PCa risk and progression. Our results highlight that the positive correlations of HNF1B expression with the 17q12 SNP genotypes are dependent on ERG fusion status and also showed a physical protein-protein interaction between HNF1B and TMPRSS2-ERG, which in turn co-occupy a large fraction of chromatin regions enriched with various PCa risk-associated non-coding genomic variants, including the SNPs at the 17p13.3 PCa susceptibility locus. Previous studies reported the regulation of VPS53 , FAM57A and GEMIN4 within the 17p13.3 regions through regulatory enhancer region harboring SNPs rs2955626 and rs684232 wherein ERG functions as a transcriptional mediator of those CREs 4 , 80 . Here our observations support those findings and freshly pinpoint the involvement of HNF1B in the regulation of VPS53 , FAM57A and GEMIN4 through a synergistic cooperation with TMPRSS2-ERG where ChIP-seq data showed occupancy of common binding sites in the SNP-surrounding enhancer regions with rs2955626, rs684232 and rs461251. All the SNP regions showed enhancer activity for each gene at 17p13.3 locus but strikingly, we observed an increased enhancer activity on FAM57A proven by CRISPR/Cas9 mediate genome editing, and also by enhancer report assay and quantitative analysis of chromosome conformation capture assays. Finally, we tested the biological relevance of VPS53 , FAM57A and GEMIN4 expression in PCa cells and demonstrated that knockdown of these genes reduces cell growth and migration. Collectively, our results provide mechanistic insight into how the PCa risk locus 17q12/HNF1B contributes to disease severity and progression and reveal a novel germline-somatic interplay between HNF1B and TMPRSS2-ERG with a potential for transcriptional mediating more genetic variance underpinning PCa susceptibility. Methods Cell culture The cell lines used in the work (Supplementary Table 10) are 22Rv1, LNCaP, VCaP, V16A, A549, RWPE1, and 293T, which were originally purchased from the American Type Culture Collection (ATCC). All cell lines were confirmed to be mycoplasma free during our study. The cells were cultured under the conditions of 37°C and 5% CO 2 . VCaP and 293T were grown in DMEM (Invitrogen), LNCaP, 22Rv1 and V16A were grown in RPMI 1640 (Sigma) and A549 was grown in F12-K (Invitrogen). The cell culture media were supplied with a final concentration of 10% fetal bovine serum (Thermo Fisher) and 1% of penicillin and streptomycin (Thermo Fisher). RWPE1 cells were grown in Keratinocyte-Serum Free Medium. Keratinocyte-SFM Kit including epidermal growth factor (EGF) and bovine pituitary extract (BPE) supplements were purchased from Invitrogen (17005-042, Invitrogen). The VCaP cells were cultured in the charcoal-stripped media wherein activating the androgen receptor signaling through a dihydrotestosterone (DHT) treatment with final concentration of 100 nM for 24 h. Plasmids and gene cloning Human cDNA library was used to amplify HNF1B open reading frame (ORF) that was cloned into pLVET-IRES-GFP and pcDNA3.1 vectors. Wild type ERG was also amplified from the same library and cloned into pcDNA3.1. The cDNA of TMPRSS2-ERG fusion was cloned from VCaP into pcDNA3.1. HNF1B-D (domains of full-length HNF1B NM_000458), HNF1B-POU and HNF1B-T of HNF1B sub-domains were cloned into pcDNA3.1, respectively, to express three recombinant proteins for testing protein interaction between HNF1B and TMPRSS2-ERG at domain levels. Primer sequences and relevant cloning methods are shown in Supplementary Table 6. Construction of reporter plasmids Each enhancer or promoter region was amplified from human genomic DNA and cloned into pGL4.10 [luc2] (Promega) containing a SNP (rs718960, rs7405696, rs11651052, rs9901746, rs11263763 or rs12453443) region. Each of these six SNPs was cloned with two different alleles obtained by site-directed mutagenesis. In addition, three SNP (rs2955626 or rs461251 and rs684232) regions were cloned. The enhancers were cloned into the BamHI site (in both orientations), and the promoters of HNF1B, VPS53, FAM57A or GEMIN4 into the EcoRV/HindIII sites of pGL4.10 [luc2] vector, respectively. Both orientations can facilitate testing enhancer activity of SNP-containing regions regardless of the promoter location. The constructs were transient, reversely transfected into LNCaP or VCaP (treated with DHT or ETH) cells with a Renilla Luciferase control plasmid pGL4.75 [hRluc/CMV] (Promega) by using X-treme GENE HP DNA Transfection Reagent (Roche). The experiments were performed on the 96-well white plates with each well containing 100μl medium of 3 x 10 5 LNCaP cells/ml or 9 x 10 5 VCaP cells/ml. After incubation at 5% CO 2 and 37°C for 48 h, the luciferase activity was measured with Dual-Glo Luciferase Assay System (Promega). At least three replicate wells were used per construct and the data were statistically analyzed with a two-tailed Student’s t test. Primer sequences and cloning methods are shown in Supplementary Table 6. Protein blot analysis Cell pellet was resuspended in lysis buffer (600mM Nacl, 1% Triton X-100 in PBS, freshly added 1 x protease inhibitor) and sonicated (Q800R sonicator, Q Sonica). The sample was centrifuged and the supernatant was collected. The amount of protein was measured with Pierce BCA Protein Assay Kit (Thermo Fisher Scientific) based on the manufacturer’s protocol and 30 μg of protein lysate of each sample was separated by electrophoresis in 7.5% or 12% SDS-PAGE gel and transferred into 0.45 μm PVDF transfer membrane using a Semi-Dry transfer cell (Trans-Blot SD, Bio-Rad). After transfer, the membrane was blocked for minimum 30 min at room temperature using blocking buffer (5% nonfat milk in TBST) while gently shaking. The blocked membrane then was incubated with antibody diluted in blocking buffer at 4°C for 16 h with gentle rotation. After incubation, the membrane was washed three times each 10min using TBST. Anti-rabbit IgG or anti-mouse IgG was used as secondary antibody (Thermo Fisher) with 1:5000 dilution into blocking buffer and the incubation took place on a rotor at room temperature for 1 h. Afterwards, the membrane was washed three times each with 15 min using TBST. Finally, the membrane was developed with Lumi-Light Western Blotting Substrate (Merck) or SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific) according to the protocol and exposed with Fujifilm LAS-3000 Imager. For more information about the antibodies see Supplementary Table 5. Ectopic expression via transient transfection 293T cells were used for transient transfection with pcDNA3.1 constructs. Mixer A of pcDNA3.1 construct and P3000 reagent (Invitrogen) was diluted with Opti-MEM. Mixer B of lipofectamine 3000 reagent (Invitrogen) was diluted with Opti-MEM. We mix A and B which were incubated at room temperature for 15 min and added into 70-80% confluent seeded cells. The cells were incubated 24-48 h before harvesting. Co-Immunoprecipitation Co-Immunoprecipitation was performed for examining the endogenous interaction of HNF1B with TMPRSS2-ERG in VCaP with DHT treatment. The ectopic interaction of HNF1B or HNF1B domains with ERG cloned into pcDNA3.1 and transfected in 293T (cloning primers listed in Supplementary Table 6). Cells were harvested and lysed with 0.5ml cold immunoprecipitation buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, 1% Triton X-100, 10% Glycerol, 1 mM EDTA and 1% protease inhibitor cocktail). Keep Cell lysates on ice for 30 min with few vortex periods in between. Sonicate in 4°C water bath for 20 sec. Centrifuge for 30 min at 4°C and supernatant was incubated with 30μl protein-G Magnetic Beads to pre-clear crude cell extract of proteins which can bind non-specifically to the beads at 4°C for 1 h. Keep the supernatant and add 5-8μg of antibody (Supplementary Table 5) with incubation at 4°C overnight. Add 30μl of fresh protein-G Magnetic Beads and incubate at 4°C for 6 h followed by washing five times with Immunoprecipitation buffer. Furthermore, resuspend beads in 30μl of 2 x SDS sample loading buffer and incubate at 95°C for 5 min and finally use the supernatant on SDS-PAGE gel for electrophoresis separation. siRNA transfections Individual set of two siRNAs (Qiagen) against HNF1B or ERG were tested in knockdown efficiency and compared with the siRNA negative-control (Qiagen) by RT-qPCR. For cell proliferation assays, we used the same set of two siRNAs (Qiagen) against HNF1B compared with negative and positive control siRNA (Qiagen). 8 x 10 3 and 8 x 10 5 of VCaP cells were used in reverse transfection for 96-well plate and 6-well plate, respectively. siRNA transfection was performed with HiPerFect Transfection Reagent (Qiagen) with a final concentration of 50nM siRNA (see Supplementary Table 2 for the siRNAs used). RNA isolation and real time quantitative PCR RNeasy Mini Kit (QIAGEN) was applied for RNA isolation and RNase-Free DNase (QIAGEN) was used during the isolation to remove DNA. cDNA was synthesized from 2 μg RNA by either the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems) or the iScript Reverse Transcription Supermix (Bio-Rad). After cDNA synthesis we used SYBR Select Master Mix (Applied Biosystems) and high specificity primers for the quantitative RT-PCR reactions. The results were normalized with beta-actin control and for each gene’s analysis made triplicates. Primers used for RT-qPCR in Supplementary Table 4. CRISPR/Cas9-mediated genome editing analysis CRISPR design tool ( http://crispr.mit.edu/ or crispor.tefor.net) was used to prepare the pair of oligos (sgRNA-top and sgRNA-bottom) attached in Supplementary Table 4. Most of the experiment was performed according to the previous protocol 81 . For annealing process 1μl sgRNA-top (100μM) and 1μl sgRNA-bottom (100μM) were mixed with 1 x T4 ligation buffer, 1μl T4 PNK and 6μl ddH 2 O. The oligos were phosphorylated and annealed in a thermocycler at 37 °C for 30 min followed with 95 °C for 5 min; ramp down to 25 °C with 5°C/min. Then, the annealed oligos were inserted into pSpCas9 (BB)-2A-Puro and the plasmids were transfected in 22Rv1 and V16A cells with 70-80% confluency. 0.6μg of total amount of Cas9 plasmids designed for the same SNP region, with 1:1 ratio or 1:1:1:1 ratio, which added into cells by using Lipofectamine 3000 in 24-well plate according to the protocol. Medium was changed after 24 h and replaced with medium containing 1μg/ml puromycin (Sigma). Afterwards, the successfully transfected cells were isolated to single cells by dilution or FACS. The single cells were seeded into 96-well plates and after 2-3 weeks the positive clones were examined further by genotyping and RT-qPCR determination of gene expression. Chromatin immunoprecipitation (ChIP) ChIP assay was carried out based mainly on previous study 62 . The cells were cross-linked in a final concentration of 1% formaldehyde in medium for 10 min at room temperature with gently shaking. The final concentration of 125 mM glycine was added to stop the reaction and incubated for minimum 5 min with slight shake. Cells were harvested and the pellet was resuspended in hypotonic lysis buffer (20 mM Tris-Cl, pH 8.0, with 10 mM KCl, 10% glycerol, 2 mM DTT, and freshly added cOmplete protease inhibitor cocktail (Roche)) and incubated up to 1 h on a rotor at 4°C. Afterwards, the pellet was washed twice with cold PBS and resuspended in SDS lysis buffer (50 mM Tris-HCl, pH 8.1, with 0.5% SDS, 10 mM EDTA, and freshly added cOmplete Protease Inhibitor). Sonication (Q800R sonicator, Q Sonica) was performed as far as the chromatin had size 250-500bp. Later, 70 μl of Dynabead protein G (Invitrogen) were washed twice with blocking buffer (0.5% BSA in IP buffer) and incubated with 6-8μg of antibody (examined antibodies in Supplementary Table 5) in 1000 μl of 0.5% BSA in IP buffer (20 mM Tris-HCl, pH8.0, with 2 mM EDTA, 150 mM NaCl, 1% Triton X-100, and freshly added Protease inhibitor cocktail) for 10 h at 4°C on rotor. After incubation the supernatant was removed and the sonicated chromatin lysate (200-250 μg) was diluted in 1.3ml of IP buffer and was added into the beads-antibody complex with incubation at 4°C for at least 12 hrs on rotor. Afterwards, the beads-antibody complex was washed one time with wash buffer I (20 mM Tris-HCl, pH 8.0, with 2 mM EDTA, 0.1%SDS, 1% Triton X-100, and 150 mM NaCl) and once with buffer II (20 mM Tris-HCl pH, 8.0, with 2 mM EDTA, 0.1% SDS, 1% Triton X-100, and 500 mM NaCl), followed by two times of washing with buffer III (10 mM Tris-HCl, pH 8.0, with 1 mM EDTA, 250 mM LiCl, 1% deoxycholate, and 1% NP-40) and two times with buffer IV (10 mM Tris-HCl, pH 8.0, and 1 mM EDTA). 50μl of extraction buffer (10 mM Tris-HCl, pH 8.0, 1 mM EDTA, and 1% SDS) were added to extract from the beads the DNA-protein complex by incubating and shaking at 65°C for 20 min (repeat same step with another 50μl of extraction buffer). Proteinase K with final concentration 1mg/ml and NaCl with final concentration 0.3 M were added into the extracted DNA-protein complex and incubated for 16 h at 65°C in 1000rpm to reverse-crosslink of the protein-DNA interactions. DNA was purified with MinElute PCR Purification Kit (QIAGEN) followed by ChIP-qPCR with primers that targeted DNA binding genome sequences (see Supplementary Table 4). ChIP library was prepared according to manufacturer’s protocol TruSeq Sample Preparation Best Practices and Troubleshooting Guide (Illumina). Finally, the sample were sequenced and analyzed. Quantitative analysis of chromosome conformation capture assay Quantitative analysis of chromosome conformation capture assay (3C-qPCR) was performed as described in the previous protocol 78 . The primers used for these assays are listed in Supplementary Table 4. The cells were trypsinized and resuspended in PBS with 10% FBS. 1 x 10 7 cells were cross-linked in PBS with 10% FBS and 1% formaldehyde for 10 min at room temperature. To stop the crosslinking reaction we added 0.57 ml of 2.5 M glycine (ice cold). The pellets of VCaP with treatment and A549 were resuspended in 5 ml cold lysis buffer and incubate for 13 min on ice. Then we centrifuge at 400g at 4°C and remove the supernatant and keep the pelleted nuclei, which were collected by centrifugation and used for digestion. We continue on digestion step of sample with HindIII restriction enzyme to digest chromatin DNA and the digestion efficiency was verified. The digested nuclear lysate was used in the ligation step. After ligation, for purification of DNA we increased the volume of sample to dilute DTT presented in the sample with 7ml distilled water, 1.5ml of 2 M sodium acetate pH 5.6 and 35ml ethanol. After washing pellet with 70% ethanol and dry the pellet, and resuspended it in 150 μl of 10 mM Tris pH 7.5. DNA was desalted with centrifuge filters (Microcon DNA Fast Flow). For TaqMan qPCR, we used 1 μl of the 3C sample (100ng/μl), 5μl of Quanti tech probe PCR mix (QIAGEN), 1 μl of Taqman probe (1.5 μM), 1μl of Test + Constant primer (5 μM) and 2 μl distilled H 2 O. We performed standard curve of each primer using serial dilution of control template, containing amplified fragments across each of 7 HindIII cut sites and mix them together. Values of intercept and slope from the standard curve were used to evaluate the ligation product using the following equation: Value = 10 (Ct-intercept)/slope. These values were finally normalized to ERCC3 (loading control). Lentiviral constructs, lentivirus production and infection HNF1B was cloned into the lentivirus plasmid pLVET-IRES-GFP for ectopic expression (see Supplementary Table 6). Two set of shRNA constructs in the pLKO.1-puro vector targeting HNF1B, VPS53, FAM57A or GEMIN4 (Merck) were applied for knockdown assays. More information on the shRNA constructs can be found in Supplementary Table 2. Lentiviral constructs were produced with the third-generation packaging system in human embryonic kidney (HEK) 293T cells (ATCC, CRL-11268) which were seeded the previous day into 3.5-cm plate in a 70%–80% confluency. At the day of transfection the medium was replaced with 1ml low glucose DMEM (Invitrogen) containing 10% FBS, 0.1% penicillin-streptomycin. A mix of four plasmids was made in a ratio 1:1:1:3 in a total amount of 10μg (pVSVG-envelope plasmid, pMDLg/pRRE-packaging plasmid, pRSV-Rev-packaging plasmid and lentiviral transfer vector) and diluted in Opti-MEM with Lipofectamine 2000. 24 h later the medium was replaced with 2 ml fresh medium. After that time, the virus-containing medium was collected every 24 h for 3 d and then was centrifuged with 1000rpm for 5 min and the supernatant was filtered with 0.45 μm filter unit place on syringe. Then the sample was collected and frozen with liquid nitrogen before stored at -80 ο C. For virus transduction into the desired cells seeded 24 h before transduction in 3.5cm plate, the final concentration of 8 μg/ml polybrene (Sigma) was added in 1.4ml medium and 0.6ml lentivirus-containing medium. Then the culture medium of target cells was replaced with the above prepared mix and incubate for 24 h at 37°C and 5% CO 2 . In case of puromycin (Sigma) selection construct, after 24 h the medium was replaced with pre-warmed medium, and 48 h after transduction the medium was changed with fresh medium containing puromycin in a final concentration of 2μg/ml. Cells without virus transduction were used as control to determine cell survival status upon puromycin selection. For the GFP expression constructs, 48 h after transduction the cells were sorted positively by fluorescence activated cell sorting (FACS) using BD FACS Aria flow cytometer (BD Biosciences). Cell proliferation assays The experiments were performed on the 96-well plates with each well containing 100μl medium of 2 x 10 3 V16A or 22Rv1 cells and 8 x 10 3 VCaP cells per well, respectively, in an incubation period of 4-6 d with 5% CO 2 and 37°C. The Cell Proliferation Kit II XTT (Sigma) was used according to the manufacturer. At least three replicate wells were prepared per condition and the data were statistically analyzed with a two-tailed Student’s t test. Wound healing assays Cells were seeded into 96-well imageLock plates with the appropriate culture medium that can allow to grow near 100% confluence. Then we used WoundMaker tool to create homogenous scratch wounds and cells were washed twice with PBS. Culture medium was added into each well. The wound areas of each well were imaged every 2 h for max 180 h using Essen BioScience IncuCyte Live-Cell Imaging System. Data acquisition RNA-seq or microarray data were retrieved from public databases including cBioPortal for Cancer Genomics 82 , 83 , Oncomine database 84 and GEO database 85 , 86 . The VCaP ChIP-seq profiling data were obtained from Cistrome Data Browser 63 , 87 . The data used for the eQTL analyses described in this manuscript were obtained from GTEx portal 65 , PancanQTL 66 and ncRNA-eQTL 67 . The FinnGen data used in this research are publicly available to qualified researchers and detailed documentation is provided on the FinnGen study website ( https://www.finngen.fi/ ). Gene expression correlation analysis We performed the co-expression analysis to evaluate the expression correlation between HFN1B, ERG and FAM57A from multiple independent cohorts with benign and cancerous prostate tissues. The co-expression tests were also applied in scenarios considering TMPRSS2-ERG status. Both Pearson’s product-moment correlation and Spearman’s rank correlation rho methods were applied in all linear expression correlation tests. Genes were ranked according to Pearson coefficient value in a descending order to figuring out the gene that is most co-expressed with HNF1B in a genome-wise scale. Survival analysis Survival analysis was applied to assess the impact of HNF1B expression level, different HNF1B signature scores and ERG & HNF1B eGene signature scores on PCa prognosis and survival in multiple independent cohorts. The survival analyses were performed and visualized as Kaplan-Meier plots using R package “Survival” (v. 3.2.3) 89 , 90 . Patients were stratified into two groups according to the median value of HNF1B expression level or HNF1B/ERG joint target signature scores. Function “Surv” was first employed to create the survival models with “time-to-event” and “event status” as input from clinical cohorts. Then HNF1B expression level or signature scores was further followed to fit to the models by function “survfit”. The Cox proportional-hazards model 91 was applied to investigate the hazard ratio for assessing the association between patients’ survival time and gene expression or signature score. Expression Quantitative Trait Loci (eQTL) analysis To evaluate the associations between genotypes of SNPs and HNF1B expression level, we performed the expression quantitative trait loci (eQTL) analysis by R package ‘‘MatrixEQTL’’ version 2.2 92 in Wisconsin and TCGA cohorts 82 , 93 , which comprised of 466 normal and 364 prostate tumor samples, respectively. The eQTL analysis was applied by fitting a linear regression model between the expression and the genotype data, other parameters were left as default (pvOutputThreshold = 0.05, errorCovariance = numeric ()”). The transcriptional profiling in TCGA cohort was assessed by RNA-Seq. The TCGA cohort was genotyped on Affymetrix SNP array 6. RNA-sequencing (RNA-seq) and differential expression analysis Preparation of RNA samples was made with VCaP cells, which were treated with 100 nM DHT, and reversely transfected with two different siRNAs targeting HNF1B and negative siRNA control and incubated for 72 h at 37°C each with two biological replicates. For the RNA sequencing in VCaP cells treated with either negative control siRNAs or siRNAs against HFN1B, raw sequence data were first pre-processed with FastQC to assess read quality. SortMeRna was applied to identify and filter rRNA 94 to limit the rRNA quantity in FastQ files. The filtered data was resubmitted for a QC assessment by FastQC to ensure the validity of the filtering steps. Trimmomatic 95 was employed to process reads for quality trimming and adapter removal with default parameters: TruSeq3-SE.fa:2:30:10 SLIDINGWINDOW: 5:20. A final FastQC run was performed to ensure the success of previous quality control steps. The processed reads were aligned against the human genome assembly hg19 using TopHat2 version 2.1.1 96 with default settings; parameter for library type was set as “fr-firststrand”. HTSeq (htseq-count) was employed to quantitate aligned sequencing reads against gene annotation from UCSC and with parameters “-s reverse, –i gene_id”. Differential expression analysis was performed from read count matrix using Bioconductor package DESeq2 (1.16.1) 97 . Genes with low expressions (< 5 cumulative read count across samples) were filtered out before analysis. A threshold of p value < 0.05 was applied to generate the differentially expressed gene list. Statistical test was applied to control or treatment to ensure high correlations between biological replicates. Data was normalized using method variance Stabilizing Transformation (VST) and the heatmap presenting differentially expressed genes between siRNA Control and siRNAs HNF1B samples was generated using R package “pheatmap” (1.0.12). Gene Set Enrichment Analysis We applied Gene Set Enrichment Analysis (GSEA) to interpret the RNA-Seq results upon knockdown of HNF1B. The pre-ranked gene list was obtained by calculation of data following formula sign (logFC)*-log(p-value), and data were sorted in a descending order. GSEAPreranked test 88 was used to test the enrichment of genes with phenotype in Hallmark gene sets. Parameters were set as follows: Enrichment statistic = “weighted”, Max size (exclude larger sets) = 5000, number of permutations =1000. All other parameters were remained as default. The GSEA enrichment plots were generated using R packages “clusterProfiler” (3.14.3) 98 and “enrichplot” (1.12.0) 99 . Chromatin Immunoprecipitation Sequencing (ChIP-seq) The ChIP-seq library was sequenced to generate 35-76 bp single-end reads. FastQC was applied to assess the quality of raw data and followed by Trimmomatic 95 for quality control. The trimmed reads were mapped into the human genome assembly hg19 using BWA-MEM 100 . HOMER v4.10 101 was employed for peak calling using function “findPeaks.pl” with default parameters. Function “findMotifsGenome.pl” was used to perform motif analysis. Function “annotatePeaks.pl” was used for peak annotation and associate peaks with nearby genes. UCSC tools and IGV tools were used to produce big wiggle and TDF formats for visualization. Bioconductor package ChIPseeker (1.18.0) 102 was applied to perform downstream peak annotation ad motif analysis. Development of the HNF1B/ERG derived signatures The HNF1B cell cycle signature, composed of 33 genes, was derived from the five top enriched cell cycle related pathways via GSEA, then further being intersected with the 207-upregulated genes from the RNA-Seq upon HNF1B knockdown. We defined the differentially expressed genes from the RNA-Seq as HFN1B knockdown signature. For the HNF1B and ERG direct target gene signature, we first converted the 207 upregulated gene symbols to Entrez IDs. Bedtools (v.2.27.1) 103 was used to identify common peaks from HNF1B and ERG ChIP-Seq binding signals. Function “annotatePeaks.pl” from HOMER was applied for annotating HNF1B and ERG common peaks. The 207-upregulated gene list and the gene list from HNF1B and ERG common binding peaks were intersected, and thus resulted in a 51-gene list, defined as HNF1B and ERG direct target gene signature. For the eQTL gene (eGene) signature, we screened 13 proxy SNPs enriched in HNF1B and ERG common binding sites. We then set R2 >=0.8 as a threshold, which resulted in a total eight proxy SNPs with 17 corresponding eQTL genes. We defined these 17 genes as HNF1B and ERG eGene signature. Signature scores were calculated as weighted sums of normalized expression of the genes from the each signature. Statistical analysis and data visualization All statistical analyses were performed using RStudio 104 , 105 (v. 1.2.5033) with R version v. 3.6.3. Statistical analyses were applied across normal prostate, tumor and metastatic tissues from multiple cohorts. Mann-Whitney U test was used for gene expression in clinical cohorts with two groups, while Kruskal-Wallis H test was applied for cohorts having three groups or more. R package “Survival” was applied in all Survival analysis. Statistical analyses for all Kaplan Meier curves were calculated using log-rank test. HNF1B signature scores were calculated from the z-score sum of panels of gene expression levels. For microarray-based expression profiling, we selected gene probes with lowest p values. Circos maps were generated using Circos (v.0.67) 106 . Asterisks indicate the significance level (*p < 0.05; **p < 0.01; ***p < 0.005). P value < 0.05 was considered to be statistically significant. Contributions Conceptualization, G.-H.W.; Methodology, N.G., Q.Z., X.Y., Y.T., P.Z., Y.Y., L.W., and G.- H.W.; Software, Q.Z.; Validation, N.G., X.Y., Y.Y.; Formal analysis, N.G., Q.Z., and G.-H.W.; Investigation, N.G., Q.Z., X.Y., Y.Y., and G.-H.W.; Resources, A.M., L.W., G.-H.W.; Data curation, N.G., Q.Z., G.-H.W.; Writing – original draft, N.G., Q.Z., G.-H.W.; Writing – review & editing, all authors; Visualization, Q.Z., G.-H.W.; Supervision, G.-H.W.; Project administration, Y.Y., A.M., L.W., G.-H.W.; Funding acquisition, G.-H.W. Download figure Open in new tab Figure S1. Association of HNF1B with PCa. (a) Expression profiles of HNF1B across 31 cancer types using The Cancer Genome Atlas (TCGA) RNA-seq data. (b) HNF1B promotes VCaP cell proliferation measured by XTT colorimetric assays. n = 3 technical replicates, error bars, s.d. *** P < 0.001. (c) Ectopic expression of HNF1B promotes RWPE1 cell proliferation measured by XTT colorimetric assays. n = 3 technical replicates, error bars, s.d. *** P < 0.001. ( d-f ) HNF1B expression level is elevated in higher PCa stages of tumours and higher PSA levels, respectively. ( g ) High expression levels of HNF1B are associated with higher risk of biochemical relapse in this cohort of PCa patients. In b , c , P values were assessed using two-tailed Student’s t tests. Download figure Open in new tab Figure S2 An eQTL analysis of the 17q12 locus variants in associations with HNF1B expression. ( a ) HNF1B isoform 1 is dominantly expressed in Wiscousin cohort of 466 prostate specimens. ( b-o ) 11 of the 13 highly associated SNPs were found to have significant eQTL associations with HNF1B isoform 1 in Wiscousin cohort. Download figure Open in new tab Figure S3 ERG is the top-ranking gene showing the highest coexpression correlation with HNF1B in PCa tumours. (a) Pearson correlation displaying ERG as the most co-expressed gene with HNF1B. (b) ERG is the most co-expressed gene with HNF1B in an additional PCa tumour cohort (N=264) of GSE62872. (c-e) ERG shows no significant co-expression with HNF1B in normal prostate glands (N=160). (f,g) ChIP-qPCR determination of chromatin enrichment for ERG, H3K4me1, H4K4me2, H3K27ac, and H3K4me3 at rs11263763 ( f ) and rs11651052 ( g ) enhancers of the 17q12/HNF1B regions in VCaP cells treated with 100nM DHT. n= 3 technical replicates, error bars, s.d. *P < 0.05, ** P < 0.01, *** P < 0.001. (h,i) Expression levels of ERG are not significantly correlated with HNF1B in TMPRSS2-ERG fusion-negative group. Download figure Open in new tab Figure S4 eQTL association with HNF1B in TMPRSS2-ERG fusion-negative group of PCa patients. (a-n) None of the 13 highly associated SNPs in the 17q12/HNF1B locus was found to have significant eQTL association with HNF1B in TMPRSS2-ERG fusion-negative PCa patients of TCGA cohort. Download figure Open in new tab Figure S5 eQTL association with HNF1B in TMPRSS2-ERG fusion-positive group of PCa patients. (a-n) Four of the 13 highly associated SNPs at the 17q12/HNF1B locus were found to have significant eQTL association with HNF1B expression levels in PCa patient group with TMPRSS2-ERG fusion. Download figure Open in new tab Figure S6 Experimental validation of HNF1B target genes and exploration of their clinical relevance. ( a-c ) RPKM expression correlation between two biological replicates of control siRNA, HNF1B siRNA1, or HNF1B siRNA2, respectively. ( d,e ) RT-qPCR validation of HNF1B positively or negatively regulated target genes revealed by RNA-seq profiling. n = 3 technical replicates, error bars, s.d. * P < 0.05, ** P < 0.01, *** P < 0.001. ( f-k ) Correlations between HNF1B knock-down signature and PCa severity status across different independent patient cohorts. HNF1B knock-down signature score were defined as z-score sum of the 207 HNF1B upregulated genes by RNA-seq measurement. The signature was compared between different stages of primary tumour and metastasis, Lymph node, biochemical recurrence status, tumour stage, neoplasm status and Gleason score. P value was calculated using Mann–Whitney U test or Kruskal-Wallis test. ( l-n ) Kaplan-Meier plots showing the overall survival and biochemical relapse of PCa patients from TCGA and SUC2-PCF cohorts. Patients were stratified by median expression levels of the HNF1B knock-down upregulated signature scores. P value was calculate using log-rank test. ( o-u ) HNF1B cell-cycle gene signature scores indicates significant positive Pearson correlation with the Cell Cycle Progression (CCP) score across several independent cohorts of PCa patients. Download figure Open in new tab Figure S7 Characterization of clinical relevance for HNF1B target gene signatures. (a-h) Scatter plots displaying significant positive linear correlation between HNF1B knock-down signature and Cell Cycle Progression scores in eight independent cohorts of PCa patients. HNF1B knock-down signature score was calculated by the z-score sum of the 339 differentially expressed genes upon HNF1B siRNA knockdown followed by RNA-seq profiling. ( i-m ) The HNF1B cell cycle signature score was compared between primary and metastasis tumours, Gleason score, Biochemical recurrence status and primary tumour stage. P values were calculated using Mann-Whitney U test or Kruskal-Wallis test. ( n,o ) Kaplan-Meier plots showing the biochemical relapse, overall survival of PCa patients in TCGA and MSKCC cohorts. Patients were stratified by median z-score sum of HNF1B cell cycle signature score. P value was calculate using log-rank test. ( p ) Differentially expressed genes that are significantly co-expressed with HNF1B indicate increased likelihood to be greatly co-expressed with TMPRSS2-ERG in DKFZ cohort of 118 PCa patients. ( q ) A 25-gene co-expression signature with HNF1B displayed a similar expression pattern with ERG in TCGA cohort of PCa tumours. In d , e , P values were assessed using two-tailed Student’s t tests. Download figure Open in new tab Figure S8 Physical interaction of HNF1B and ERG, and their direct target gene signature in the clinical setting. ( a ) Physical interaction of exogenously expressed recombinant HNF1B and ERG protein in 293T. ( b ) Interaction of recombinant HNF1B protein with exogenous ERG in vitro via the POU domain defined by co-IP with anti-flag antibody in 293T cells. ( c-f ) ) Pearson correlation tests demonstrate significant positive linear correlation between HNF1B&ERG direct target gene signature scores and Cell Cycle Progression signature scores in four independent PCa cohorts. In a,b , representative experimental results of three independent co-immunoprecipitation assessments are shown. Download figure Open in new tab Figure S9 No prognostic values were found for the ERG&HNF1B binding sites enriched PCa risk eQTL gene signature in patient groups with Gleason score 6 or 8. (a-d) Kaplan-Meier curves depicting biochemical relapse and metastatic rates of PCa patients in TCGA cohort with Gleason score 6 or 8. Patients were stratified by median z-score sum of HNF1B&ERG eQTL gene (eGene) signature score. P values were examined by a log rank test. Download figure Open in new tab Figure S10 Associations of the 17P13.3 locus risk genes with HNF1B and TMPRSS2-ERG fusion status in PCa clinical setting. (a) Heatmap displaying the expression levels of the HNF1B and ERG binding sites enriched PCa risk loci of the eQTL genes. Note that FAM57A, GEMIN4 and VPS53 show a similar expression pattern to HNF1B and ERG in the DKFZ cohort of PCa specimens. (b-c) The expression levels of FAM57A and ERG or HNF1B are not significantly correlated in normal prostate glands. (d-g) Expression levels of ERG, HNF1B and FAM57A are significantly elevated in TMPRSS2-ERG fusion-positive PCa specimens compared to TMPRSS2-ERG fusion-negative groups. (h) The mRNA levels of HNF1B, FAM57A and GEMIN4 were downregulated in V16A cells treated with BRD4 antagonist I-BET for 24hrs. n= 3 technical replicates, error bars, s.d., *** P< 0.001, two-tailed Student’s t test. Acknowledgements We want to acknowledge the participants and investigators of the FinnGen study. 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Share Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG Nikolaos Giannareas , Qin Zhang , Xiayun Yang , Yijun Tian , Peng Zhang , Yuehong Yang , Aki Manninen , Liang Wang , Gong-Hong Wei bioRxiv 2021.09.02.458755; doi: https://doi.org/10.1101/2021.09.02.458755 Share This Article: Copy Citation Tools Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG Nikolaos Giannareas , Qin Zhang , Xiayun Yang , Yijun Tian , Peng Zhang , Yuehong Yang , Aki Manninen , Liang Wang , Gong-Hong Wei bioRxiv 2021.09.02.458755; doi: https://doi.org/10.1101/2021.09.02.458755 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Cancer Biology Subject Areas All Articles Animal Behavior and Cognition (7844) Biochemistry (18357) Bioengineering (14524) Bioinformatics (43395) Biophysics (22116) Cancer Biology (19235) Cell Biology (26349) Clinical Trials (138) Developmental Biology (13734) Ecology (20546) Epidemiology (2067) Evolutionary Biology (25009) Genetics (15930) Genomics (23130) Immunology (18324) Microbiology (41626) Molecular Biology (17668) Neuroscience (91511) Paleontology (683) Pathology (2929) Pharmacology and Toxicology (4983) Physiology (7933) Plant Biology (15632) Scientific Communication and Education (2077) Synthetic Biology (4460) Systems Biology (10062) Zoology (2337) window.__CF$cv$params={r:'a255397d195d2858',t:'MTc4NTc1OTA4Mw==',u:'019fc789362b77c281453d05021a407d',ut:'egt2T5e_Zb7GCcuaS9vTcuGtrQ.iMtnOfkE9wm9YBr0-1785759086-1.2.1.1-Wpn5sh3STUUQCoTKf7WlZYvp50_VKHbu9nh38XR8Jo.bfnQvZuFpXo9CIQuOz4n5arTqQ.Al1sQNqgEQwPnHgZTHrw44ZTBEDqU_ezMii4I',i:60};(function(){if(!document.body)return;var s=document.createElement('script');s.src='/cdn-cgi/challenge-platform/scripts/precursor/main.js';document.head.appendChild(s);})();