Fogarty, Zachary C.

Prostate‐specific membrane antigen (PSMA) is a validated target for molecular diagnostics and targeted radionuclide therapy. Our purpose was to evaluate PSMA expression in hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and hepatic adenoma (HCA); investigate the genetic pathways in HCC associated with PSMA expression; and evaluate HCC detection rate with 68Ga‐PSMA‐11 positron emission tomography (PET). In phase 1, PSMA immunohistochemistry (IHC) on HCC (n = 148), CCA (n = 111), and HCA (n = 78) was scored. In a subset (n = 30), messenger RNA (mRNA) data from the Cancer Genome Atlas HCC RNA sequencing were correlated with PSMA expression. In phase 2, 68Ga‐PSMA‐11 PET was prospectively performed in patients with treatment‐naïve HCC on a digital PET scanner using cyclotron‐produced 68Ga. Uptake was graded qualitatively and semi‐quantitatively using standard metrics. On IHC, PSMA expression was significantly higher in HCC compared with CCA and HCA (P < 0.0001); 91% of HCCs (n = 134) expressed PSMA, which principally localized to tumor‐associated neovasculature. Higher tumor grade was associated with PSMA expression (P = 0.012) but there was no association with tumor size (P = 0.14), fibrosis (P = 0.35), cirrhosis (P = 0.74), hepatitis B virus (P = 0.31), or hepatitis C virus (P = 0.15). Overall survival tended to be longer in patients without versus with PSMA expression (median overall survival: 4.2 vs. 1.9 years; P = 0.273). FGF14 (fibroblast growth factor 14) mRNA expression correlated positively (rho = 0.70; P = 1.70 × 10‐5) and MAD1L1 (Mitotic spindle assembly checkpoint protein MAD1) correlated negatively with PSMA expression (rho = −0.753; P = 1.58 × 10‐6). Of the 190 patients who met the eligibility criteria, 31 patients with 39 HCC lesions completed PET; 64% (n = 25) lesions had pronounced 68Ga‐PSMA‐11 standardized uptake value: SUVmax (median [range] 9.2 [4.9‐28.4]), SUVmean 4.7 (2.4‐12.7), and tumor‐to‐liver background ratio 2 (1.1‐11). Conclusion: Ex vivo expression of PSMA in neovasculature of HCC translates to marked tumor avidity on 68Ga‐PSMA‐11 PET, which suggests that PSMA has the potential as a theranostic target in patients with HCC.

Abstract Background: DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT>TAT and TCG>TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. Methods: Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n=195), The Cancer Genome Atlas (TCGA) OC tumors (n=419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n=84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. Results: In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P=5e-04). These six tumors were hypermutated with a higher tumor mutation load (mean, 54.02 mutations per megabase) compared to non-POLE endometrioid OC cases (mean, 7.69 mutations per megabase; P=5e-04), and had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P=.008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations.Conclusions: From the largest cohort of RNA-seq from endometrioid OC to date (n=53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

Congenital heart diseases (CHDs), including hypoplastic left heart syndrome (HLHS), are genetically complex and poorly understood. Here, a multidisciplinary platform was established to functionally evaluate novel CHD gene candidates, based on whole-genome and iPSC RNA sequencing of a HLHS family-trio. Filtering for rare variants and altered expression in proband iPSCs prioritized 10 candidates. siRNA/RNAi-mediated knockdown in healthy human iPSC-derived cardiomyocytes (hiPSC-CM) and in developing Drosophila and zebrafish hearts revealed that LDL receptor-related protein LRP2 is required for cardiomyocyte proliferation and differentiation. Consistent with hypoplastic heart defects, compared to parents the proband’s iPSC-CMs exhibited reduced proliferation. Interestingly, rare, predicted-damaging LRP2 variants were enriched in a HLHS cohort; however, understanding their contribution to HLHS requires further investigation. Collectively, we have established a multi-species high-throughput platform to rapidly evaluate candidate genes and their interactions during heart development, which are crucial first steps toward deciphering oligogenic underpinnings of CHDs, including hypoplastic left hearts.

Abstract Background: Large genome-wide association studies (GWAS) have identified hundreds of single-nucleotide polymorphisms (SNPs) associated with increased risk of prostate cancer (PRCA). The majority of these risk loci are intergenic and the underlying causal variants are presumed to confer regulatory effects on gene expression. While follow-up eQTL studies have begun to explore putative regulatory targets of PRCA risk SNPs, these have largely focused on protein-coding genes. Recent evidence demonstrates that pri-miRNA transcripts are susceptible to the same cis-acting regulatory effects as other long RNAs, and PRCA risk SNPs may confer systemic impacts on the prostate transcriptome through miRNA expression dysregulation. However, no miRNA transcriptome-wide association studies (TWAS) of PRCA risk have been conducted to date, and the role of miRNA dysregulation in PRCA risk is poorly understood. Methods: We performed a comprehensive miRNA TWAS of PRCA risk using small RNA sequencing and genome-wide genotyping data from N = 441 normal prostate tissue samples from Mayo Clinic along with N = 411 prostate adenocarcinoma (PRAD) tumor samples from the Cancer Genome Atlas (TCGA). Both miRNA expression datasets were uniformly processed separately using the CAP-miRSeq miRNA workflow and trimmed mean of M (TMM) normalization. Expressed mature miRNAs were identified as ≥ 5 reads in &gt;25% of samples. PEER was used to remove known and latent factors on miRNA expression levels, and subsequent analyses were performed on residual values. Genetically regulated expression (GReX) prediction models were trained for all expressed miRNAs with evidence of cis-heritability (P&lt;0.01) in the respective normal and tumor datasets using the FUSION TWAS software. TWAS for PRCA risk was performed with both sets of GReX models using single-SNP summary statistics from the recent PRACTICAL consortium PRCA case-control OncoArray GWAS meta-analysis. Significant TWAS associations were declared at a false discovery rate of 0.05. Results: A total of 615 and 571 distinct expressed miRNAs were identified in the normal and tumor tissue datasets, respectively (overlap: 480). Among these, 98 (16%) normal tissue miRNAs demonstrated significant cis-heritability (median cis-h2 = 0.09, range: 0.04-0.79) for GReX model training. Similar results were obtained from TCGA tumor samples, with 63 (11%) miRNA GReX models successfully trained (median cis-h2 = 0.11, range: 0.05-0.60). Using normal tissue GReX models, we identified three significant TWAS miRNA associations with PRCA risk: over-expression of mir-941 family miRNAs (PTWAS = 3.1E-04) and reduced expression of miR-3617-5p (PTWAS = 1.7E-04) and hsa-miR-16-2-3p (PTWAS = 9.1E-04). The TCGA tumor TWAS also identified a significant association with miR-941 overexpression (PTWAS = 9.7E-04). All associated miRNAs have previously reported oncogenic or tumor-suppressive associations in other cancer types. Conclusions: We identified significant associations with PRCA genetic risk and miRNA expression dysregulation using tumor and normal prostate tissue data. Future work will examine downstream regulatory effects of miRNA dysregulation as well as miRNA-mediated risk mechanisms via competing endogenous RNA relationships. Citation Format: Nicholas B. Larson, Shannon K. McDonnell, Zachary Fogarty, Stephen N. Thibodeau. An miRNA transcriptome-wide association study of prostate cancer risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 54.

AbstractX chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women’s cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10−10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of rl disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.

ABSTRACTX‐chromosome inactivation (XCI) epigenetically silences transcription of an X chromosome in females; patterns of XCI are thought to be aberrant in women's cancers, but are understudied due to statistical challenges. We develop a two‐stage statistical framework to assess skewed XCI and evaluate gene‐level patterns of XCI for an individual sample by integration of RNA sequence, copy number alteration, and genotype data. Our method relies on allele‐specific expression (ASE) to directly measure XCI and does not rely on male samples or paired normal tissue for comparison. We model ASE using a two‐component mixture of beta distributions, allowing estimation for a given sample of the degree of skewness (based on a composite likelihood ratio test) and the posterior probability that a given gene escapes XCI (using a Bayesian beta‐binomial mixture model). To illustrate the utility of our approach, we applied these methods to data from tumors of ovarian cancer patients. Among 99 patients, 45 tumors were informative for analysis and showed evidence of XCI skewed toward a particular parental chromosome. For 397 X‐linked genes, we observed tumor XCI patterns largely consistent with previously identified consensus states based on multiple normal tissue types. However, 37 genes differed in XCI state between ovarian tumors and the consensus state; 17 genes aberrantly escaped XCI in ovarian tumors (including many oncogenes), whereas 20 genes were unexpectedly inactivated in ovarian tumors (including many tumor suppressor genes). These results provide evidence of the importance of XCI in ovarian cancer and demonstrate the utility of our two‐stage analysis.

Abstract Introduction: In females, X-chromosome inactivation (XCI) epigenetically silences transcription of one copy of the X chromosome. Which chromosome is silenced is randomly selected, and is tissue- and cell-specific. While some genes are known to escape XCI under normal conditions, aberrant XCI patterns are thought to occur in female-specific cancers, although the role of XCI in ovarian tumorigenesis and progression is largely unknown. The process of XCI is complex, and integration of gene expression, DNA methylation, and copy number data can inform the XCI status of individual genes and chromosome-wide XCI patterns for individual patients. Methods: We evaluated gene- and chromosome-level patterns of XCI by integrating RNA sequence, copy number alteration, genotype, and DNA methylation data to study XCI escape patterns in tumor samples from 99 ovarian cancer patients. We measured allele-specific expression (ASE) for 397 X-linked genes to identify the active alleles for each tumor. Combining ASE data with knowledge of copy number status, we used a Bayesian beta-binomial mixture model to estimate which genes escaped XCI for each patient, and validated our findings using DNA methylation data. To assess global XCI patterns, we performed cluster analyses on the ASE and methylation data, after adjusting for loss of heterozygosity. We examined the relationship between the clusters and clinical factors, including overall survival and time to recurrence. Results: DNA promoter methylation demonstrated inverse regional correlations with ASE. Cluster analyses using ASE and methylation data demonstrated evidence of two tumor clusters, representing normal XCI and global XCI dysregulation. The dysregulated XCI cluster (N=52) was associated with lower X-inactive specific transcript expression as expected (p&lt;0.01). Patients with XCI dysregulated tumors were higher grade, stage, serous histology and were sub-optimally debulked (p&lt;0.05). These patients also had shorter overall survival time (HR=1.87, p=0.02) and time to recurrence (HR=2.34, p&lt;0.01), although associations were attenuated after covariate adjustment. In 45 tumor samples with sufficient data, we observed escape patterns largely consistent with previous reports of multiple tissue types. When comparing tumor to normal ovarian tissue, eight genes (CXorf23, CXorf36, BRWD3, ELF4, SLITRK4, GABRE, CLCN4, SH3BGRL) showed putative escape in the tumor and two genes (RBBP7, OFD1) showed discrepant tumor inactivation. Conclusions: We identified discrepant gene-level XCI tumor classifications compared to normal tissue and identified a group of patients with chromosome-wide XCI dysregulation associated with worse clinical prognosis. This provides evidence of the role of XCI in ovarian cancer and highlights the need to integrate multiple genomic data types to study XCI. Citation Format: Stacey J. Winham, Nicholas B. Larson, Sebastian M. Armasu, Zachary C. Fogarty, Melissa C. Larson, Kimberly R. Kalli, Kate Lawrenson, Simon Gayther, Brooke L. Fridley, Ellen L. Goode. Integrative analyses of gene expression, DNA methylation, genotype and copy number alterations characterize X-chromosome inactivation in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2420. doi:10.1158/1538-7445.AM2017-2420