Genetic and functional analyses implicate the NUDT11, HNF1B, and SLC22A3 genes in prostate cancer pathogenesis

Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus

Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1-NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.

A Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis

The aim of fine mapping is to identify genetic variants causally contributing to complex traits or diseases. Existing fine-mapping methods employ Bayesian discrete mixture priors and depend on a pre-specified maximum number of causal variants, which may lead to sub-optimal solutions. In this work, we propose a Bayesian fine-mapping method called h2-D2, utilizing a continuous global-local shrinkage prior. We also present an approach to define credible sets of causal variants in continuous prior settings. Simulation studies demonstrate that h2-D2 outperforms current state-of-the-art fine-mapping methods such as SuSiE and FINEMAP in accurately identifying causal variants and estimating their effect sizes. We further applied h2-D2 to prostate cancer analysis and discovered some previously unknown causal variants. In addition, we inferred 369 target genes associated with the detected causal variants and several pathways that were significantly over-represented by these genes, shedding light on their potential roles in prostate cancer development and progression.

Distributed eQTL analysis with auxiliary information

Expression quantitative trait locus (eQTL) analysis is a useful tool to identify genetic loci that are associated with gene expression levels. Large collaborative efforts such as the Genotype-Tissue Expression (GTEx) project provide valuable resources for eQTL analysis in different tissues. Most existing methods, however, either focus on one tissue at a time, or analyze multiple tissues to identify eQTLs jointly present in multiple tissues. There is a lack of powerful methods to identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. In this paper, we propose a novel statistical framework to improve the eQTL detection efficacy in the tissue of interest with auxiliary information from other tissues. This framework can enhance the power of the hypothesis test for eQTL effects by incorporating shared and specific effects from multiple tissues into the test statistics. We also devise data-driven and distributed computing approaches for efficient implementation of eQTL detection when the number of tissues is large. Numerical studies in simulation demonstrate the efficacy of the proposed method, and the real data analysis of the GTEx example provides novel insights into eQTL findings in different tissues.

Genetic preservation of SLC22A3 in the Admixed and Xhosa populations living in the Western Cape

BACKGROUND

Amphiphilic solute facilitator organic cation transporters mediate the movement of various endogenous and exogenous organic cations, including crucial drugs like metformin, oxaliplatin, and lamivudine. These transporters are now seen as a potential explanation for inter-individual differences in drug effectiveness, contributing to 15-30% of such variability due to genetic factors.The aim of this study was to determine the baseline minor allele frequency distribution of 18 known coding SNPs in the SLC22A3 gene of 278 Cape Admixed (130) and Xhosa (148) individuals residing in Cape Town, South Africa.

METHODS

A convenience sampling method was used for sample collection. DNA extraction and subsequent amplification of target sites was carried out according to standard established methodologies. All genotyping was performed using the SNaPshot™ mini-seuqencing platform.

RESULTS

This study found no genetic polymorphisms in the coding region of the SLC22A3 gene of both the Xhosa and Cape Admixed individuals investigated.

CONCLUSION

This study has shown that SLC22A3 coding SNPs observed in other populations are absent in the sample of both Cape Admixed and Xhosa individuals studied. The lack of protein sequence variation was consistent with other studies and may reflect the significant physiological role of human organic cation transporter 3 in maintaining cellular and organismal homeostasis.

Expression pattern, tumor immune landscape, and prognostic value of N7‑methylguanosine regulators in bladder urothelial carcinoma

N7-Methylguanosine (m7G) modification is important in post-transcriptional regulation. dysregulation of m7G RNA modification has been reported to be markedly associated with cancer. However, its importance in bladder urothelial carcinoma (BLCA) remains poorly characterized. The present study systematically analyzed mRNA gene expression data and clinical information from The Cancer Genome Atlas and further constructed robust risk signatures for the four regulators of m7G RNA modification (nudix hydrolase 11, gem nuclear organelle-associated protein 5, eukaryotic translation initiation factor 3 subunit D and cytoplasmic FMR1 interacting protein 1). The differential expression and cell function of m7G-related genes in bladder cancer cells were verified by reverse transcription-quantitative PCR, Cell Counting Kit-8 and colony formation assays. The four-gene-based model could accurately predict the prognosis of BLCA. Nomogram-based clinical decisions had a higher net benefit compared with that of individual predictors. Through immune infiltration analysis, it was found that immune cell infiltration affected the prognosis of patients with BLCA. Finally, the present study identified potential therapeutics that differ between high and low-risk groups based on four genes. In summary, the current findings revealed an essential role for m7G RNA modification regulators in BLCA, and developed risk signatures as promising prognostic markers in patients with BLCA.

SLC22A3 methylation-mediated gene silencing predicts adverse prognosis in acute myeloid leukemia

BACKGROUND

We screened out several hypermethylated solute carrier (SLC) family genes in acute myeloid leukemia by reduced representation bisulfite sequencing. SLC22A3 encodes an organic cation transport protein, which is critical for drug transportation and cellular detoxification. SLC22A3 is significantly downregulated and associated with tumor progression and worse prognosis in a variety of solid tumors. However, there are no data available regarding the role of SLC22 in AML. This study aimed to explore the regulatory mechanism of DNA methylation on SLC22A3 expression, as well as its clinical significance in AML prognosis.

RESULTS

SLC22A3 was identified as the sole prognosis-associated gene among SLCs based on TCGA and Beat AML databases. Bone marrow mononuclear cells (BMMNCs) from AML, MDS patients, and healthy donors were enrolled in this study. SLC22A3 methylation was significantly increased in AML compared with controls and MDS patients; meanwhile, the expression level of SLC22A3 was decreased. SLC22A3 hypermethylation presented an obvious association with some specific clinical characteristics and affected the survival time of AML patients as an independent risk indicator. SLC22A3 expression changed regularly as the disease complete remissions and relapses. Demethylation drug 5-aza-2'-deoxycytidine (DAC) activated transcription and increased mRNA expression of SLC22A3 in leukemia cell lines and AML fresh BMMNCs. Knockdown of SLC22A3 in leukemia cells enhanced cell proliferation and suppressed cell apoptosis. Data from public programs were used for auxiliary screening of probable molecular mechanisms of SLC22A3 in the antileukemia effect.

CONCLUSIONS

Our results showed that increased methylation and decreased expression of SLC22A3 may be indicators of poor prognosis in AML. Methylation-silenced SLC22A3 expression may have potential guiding significance on antileukemia effect of DAC.

Prostate Cancer Transcriptomic Regulation by the Interplay of Germline Risk Alleles, Somatic Mutations, and 3D Genomic Architecture

Prostate cancer is one of the most heritable human cancers. Genome-wide association studies have identified at least 185 prostate cancer germline risk alleles, most noncoding. We used integrative three-dimensional (3D) spatial genomics to identify the chromatin interaction targets of 45 prostate cancer risk alleles, 31 of which were associated with the transcriptional regulation of target genes in 565 localized prostate tumors. To supplement these 31, we verified transcriptional targets for 56 additional risk alleles using linear proximity and linkage disequilibrium analysis in localized prostate tumors. Some individual risk alleles influenced multiple target genes; others specifically influenced only distal genes while leaving proximal ones unaffected. Several risk alleles exhibited widespread germline-somatic interactions in transcriptional regulation, having different effects in tumors with loss of PTEN or RB1 relative to those without. These data clarify functional prostate cancer risk alleles in large linkage blocks and outline a strategy to model multidimensional transcriptional regulation.

SIGNIFICANCE

Many prostate cancer germline risk alleles are enriched in the noncoding regions of the genome and are hypothesized to regulate transcription. We present a 3D genomics framework to unravel risk SNP function and describe the widespread germline-somatic interplay in transcription control. This article is highlighted in the In This Issue feature, p. 2711.

A Novel m7G-Related Genes-Based Signature with Prognostic Value and Predictive Ability to Select Patients Responsive to Personalized Treatment Strategies in Bladder Cancer

Although N7-methylguanosine (m7G) modification serves as a tumor promoter in bladder cancer (BLCA), the comprehensive role of m7G-related characterization in BLCA remains unclear. In this study, we systematically evaluated the m7G-related clusters of 760 BLCA patients through consensus unsupervised clustering analysis. Next, we investigated the underlying m7G-related genes among these m7G-related clusters. Univariate Cox and LASSO regressions were used for screening out prognostic genes and for reducing the dimension, respectively. Finally, we developed a novel m7G-related scoring system via the GSVA algorithm. The correlation between tumor microenvironment, prediction of personalized therapies and this m7G-related signature was gradually revealed. We first identified three m7G-related clusters and 1108 differentially expressed genes relevant to the three clusters. Based on the profile of 1108 genes, we divided BLCA patients into two clusters, which were quantified by our established m7G-related scoring system. Patients with higher m7G-related scores tended to have a better OS and more chances to benefit from immunotherapy. A significantly negative connection between sensitivity to classic chemotherapeutic drugs and m7G-related signature was uncovered. In summary, our data show that m7G-related characterization of BLCA patients can be of value for prognostic stratification and for patient-oriented therapeutic options, designing personalized treatment strategies in the preclinical setting.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

Molecular characterization, clinical relevance and immune feature of m7G regulator genes across 33 cancer types

Over 170 RNA modifications have been identified after transcriptions, involving in regulation of RNA splicing, processing, translation and decay. Growing evidence has unmasked the crucial role of N6-methyladenosine (m6A) in cancer development and progression, while, as a relative newly found RNA modification, N7-methylguanosine (m7G) is also certified to participate in tumorigenesis via different catalytic machinery from that of m6A. However, system analysis on m7G RNA modification-related regulator genes is lack. In this study, we first investigated the genetic alteration of m7G related regulator genes in 33 cancers, and found mRNA expression levels of most regulator genes were positively correlated with copy number variation (CNV) and negatively correlated with methylation in most cancers. We built a m7G RNA modification model based on the enrichment of the regulator gene scores to evaluate the m7G modification levels in 33 cancers, and investigated the connections of m7G scores to clinical outcomes. Furthermore, we paid close attention to the role of m7G in immunology due to the widely used immune checkpoint blockade therapy. Our results showed the higher m7G scores related to immunosuppression of tumor cells. Further confirmation with phase 3 clinical data with application of anti-PDL1/PDL indicated the impact of m7G modification level on immunotherapy effect. Relevance of m7G regulator genes and drug sensitivity was also evaluated to provide a better treatment choice when treating cancers. In summary, our study uncovered the profile of m7G RNA modification through various cancers, and figured out the connection of m7G modification levels with therapeutical outcomes, providing potential better options of cancer treatment.

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma.

XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.

Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas

Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.

An Ovarian Cancer Susceptible Gene Prediction Method Based on Deep Learning Methods

Ovarian cancer (OC) is one of the most fatal diseases among women all around the world. It is highly lethal because it is usually diagnosed at an advanced stage which may reduce the survival rate greatly. Even though most of the patients are treated timely and effectively, the survival rate is still low due to the high recurrence rate of OC. With a large number of genome-wide association analysis (GWAS)-discovered risk regions of OC, expression quantitative trait locus (eQTL) analyses can explore candidate susceptible genes based on these risk loci. However, a large number of OC-related genes remain unknown. In this study, we proposed a novel gene prediction method based on different omics data and deep learning methods to identify OC causal genes. We first employed graph attention network (GAT) to obtain a compact gene feature representation, then a deep neural network (DNN) is utilized to predict OC-related genes. As a result, our model achieved a high AUC of 0.761 and AUPR of 0.788, which proved the accuracy and effectiveness of our proposed method. At last, we conducted a gene-set enrichment analysis to further explore the mechanism of OC. Finally, we predicted 245 novel OC causal genes and 10 top related KEGG pathways.

Genetic risk factors for colorectal cancer in multiethnic Indonesians

Colorectal cancer is a common cancer in Indonesia, yet it has been understudied in this resource-constrained setting. We conducted a genome-wide association study focused on evaluation and preliminary discovery of colorectal cancer risk factors in Indonesians. We administered detailed questionnaires and collecting blood samples from 162 colorectal cancer cases throughout Makassar, Indonesia. We also established a control set of 193 healthy individuals frequency matched by age, sex, and ethnicity. A genome-wide association analysis was performed on 84 cases and 89 controls passing quality control. We evaluated known colorectal cancer genetic variants using logistic regression and established a genome-wide polygenic risk model using a Bayesian variable selection technique. We replicate associations for rs9497673, rs6936461 and rs7758229 on chromosome 6; rs11255841 on chromosome 10; and rs4779584, rs11632715, and rs73376930 on chromosome 15. Polygenic modeling identified 10 SNP associated with colorectal cancer risk. This work helps characterize the relationship between variants in the SCL22A3, SCG5, GREM1, and STXBP5-AS1 genes and colorectal cancer in a diverse Indonesian population. With further biobanking and international research collaborations, variants specific to colorectal cancer risk in Indonesians will be identified.

Insights into the etiology and physiopathology of MODY5/HNF1B pancreatic phenotype with a mouse model of the human disease

Maturity-onset diabetes of the young type 5 (MODY5) is due to heterozygous mutations or deletion of HNF1B. No mouse models are currently available to recapitulate the human MODY5 disease. Here, we investigate the pancreatic phenotype of a unique MODY5 mouse model generated by heterozygous insertion of a human HNF1B splicing mutation at the intron-2 splice donor site in the mouse genome. This Hnf1bsp2/+ model generated with targeted mutation of Hnf1b mimicking the c.544+1G>T (T) mutation identified in humans, results in alternative transcripts and a 38% decrease of native Hnf1b transcript levels. As a clinical feature of MODY5 patients, the hypomorphic mouse model Hnf1bsp2/+ displays glucose intolerance. Whereas Hnf1bsp2/+ isolated islets showed no altered insulin secretion, we found a 65% decrease in pancreatic insulin content associated with a 30% decrease in total large islet volume and a 20% decrease in total β-cell volume. These defects were associated with a 30% decrease in expression of the pro-endocrine gene Neurog3 that we previously identified as a direct target of Hnf1b, showing a developmental etiology. As another clinical feature of MODY5 patients, the Hnf1bsp2/+ pancreases display exocrine dysfunction with hypoplasia. We observed chronic pancreatitis with loss of acinar cells, acinar-to-ductal metaplasia, and lipomatosis, with upregulation of signaling pathways and impaired acinar cell regeneration. This was associated with ductal cell deficiency characterized by shortened primary cilia. Importantly, the Hnf1bsp2/+ mouse model reproduces the pancreatic features of the human MODY5/HNF1B disease, providing a unique in vivo tool for molecular studies of the endocrine and exocrine defects and to advance basic and translational research. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

A Large-Scale Association Study Detects Novel Rare Variants, Risk Genes, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility

To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th-60th percentile OR = 2.62, P = 2.55 × 10-191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits. SIGNIFICANCE: This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637.

Validation of prostate cancer risk variants rs10993994 and rs7098889 by CRISPR/Cas9 mediated genome editing

GWAS have identified numerous SNPs associated with prostate cancer risk. One such SNP is rs10993994. It is located in the β-microseminoprotein (MSMB) promoter region, mediates MSMB prostate secretion levels, and is linked to mRNA expression changes in both MSMB and the adjacent gene NCOA4. In addition, our previous work showed a second SNP, rs7098889, is in positive linkage disequilibrium with rs10993994 and associated with MSMB expression independent of rs10993994. Here, we generate a series of clones with single alleles removed by double guide RNA (gRNA) mediated CRISPR/Cas9 deletions, through which we demonstrate that each of these SNPs independently and greatly alters MSMB expression in an allele-specific manner. We further show that these SNPs have no substantial effect on the expression of NCOA4. These data demonstrate that a single SNP can have a large effect on gene expression and illustrate the importance of functional validation studies to deconvolute observed correlations. The method we have developed is generally applicable to test any SNP for which a relevant heterozygous cell line is available. AUTHOR SUMMARY: In pursuing the underlying biological mechanism of prostate cancer pathogenesis, scientists utilized the existence of common single nucleotide polymorphisms (SNPs) in the human genome as genetic markers to perform large scale genome wide association studies (GWAS) and have so far identified more than a hundred prostate cancer risk variants. Such variants provide an unbiased and systematic new venue to study the disease mechanism, and the next big challenge is to translate these genetic associations to the causal role of altered gene function in oncogenesis. The majority of these variants are waiting to be studied and lots of them may act in oncogenesis through gene expression regulation. To prove the concept, we took rs10993994 and its linked rs7098889 as an example and engineered single cell clones by allelic-specific CRISPR/Cas9 deletion to separate the effect of each allele. We observed that a single nucleotide difference would lead to surprisingly high level of MSMB gene expression change in a gene specific and cell-type specific manner. Our study strongly supports the notion that differential level of gene expression caused by risk variants and their associated genetic locus play a major role in oncogenesis and also highlights the importance of studying the function of MSMB encoded β-MSP in prostate cancer pathogenesis.

Application of Single-Cell Sequencing to Immunotherapy

Cancer is a highly complex and heterogeneous disease and immunotherapy has shown promise as a therapeutic approach. The increased resolution afforded by single-cell analysis offers the hope of finding and characterizing previously underappreciated populations of cells that could prove useful in understanding cancer progression and treatment. Urologic and prostate cancers are inherently heterogeneous diseases, and the potential for single-cell analysis to help understand and develop immunotherapeutic approaches to treat these diseases is very exciting. In this review, we view cancer immunotherapy through a single-cell lens and discuss the state-of-the-art technologies that enable advances in this field.

HNF1B, EZH2 and ECI2 in prostate carcinoma. Molecular, immunohistochemical and clinico-pathological study

Hepatocyte nuclear factor 1 beta (HNF1B) is a tissue specific transcription factor, which seems to play an important role in the carcinogenesis of several tumors. In our study we focused on analyzing HNF1B in prostate carcinoma (PC) and adenomyomatous hyperplasia (AH), as well as its possible relation to the upstream gene EZH2 and downstream gene ECI2. The results of our study showed that on an immunohistochemical level, the expression of HNF1B was low in PC, did not differ between PC and AH, and did not correlate with any clinical outcomes. In PC, mutations of HNF1B gene were rare, but the methylation of its promotor was a common finding and was positively correlated with Gleason score and stage. The relationship between HNF1B and EZH2/ECI2 was equivocal, but EZH2 and ECI2 were positively correlated on both mRNA and protein level. The expression of EZH2 was associated with poor prognosis. ECI2 did not correlate with any clinical outcomes. Our results support the oncosuppressive role of HNF1B in PC, which may be silenced by promotor methylation and other mechanisms, but not by gene mutation. The high expression of EZH2 (especially) and ECI2 in PC seems to be a potential therapeutic target.

Mapping Tumor-Specific Expression QTLs in Impure Tumor Samples

The study of gene expression quantitative trait loci (eQTL) is an effective approach to illuminate the functional roles of genetic variants. Computational methods have been developed for eQTL mapping using gene expression data from microarray or RNA-seq technology. Application of these methods for eQTL mapping in tumor tissues is problematic because tumor tissues are composed of both tumor and infiltrating normal cells (e.g. immune cells) and eQTL effects may vary between tumor and infiltrating normal cells. To address this challenge, we have developed a new method for eQTL mapping using RNA-seq data from tumor samples. Our method separately estimates the eQTL effects in tumor and infiltrating normal cells using both total expression and allele-specific expression (ASE). We demonstrate that our method controls type I error rate and has higher power than some alternative approaches. We applied our method to study RNA-seq data from The Cancer Genome Atlas and illustrated the similarities and differences of eQTL effects in tumor and normal cells.

Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB

How genome-wide association studies-identified single-nucleotide polymorphisms (SNPs) affect remote genes remains unknown. Expression quantitative trait locus (eQTL) association meta-analysis on 496 prostate tumor and 602 normal prostate samples with 117 SNPs revealed novel cis-eQTLs and trans-eQTLs. Mediation testing and colocalization analysis demonstrate that MSMB is a cis-acting mediator for SNHG11 (P < 0.01). Removing rs10993994 in LNCaP cell lines by CRISPR/Cas9 editing shows that the C-allele corresponds with an over 100-fold increase in MSMB expression and 5-fold increase in SNHG11 compared with the T-allele. Colocalization analysis confirmed that the same set of SNPs associated with MSMB expression is associated with SNHG11 expression (posterior probability of shared variants is 66.6% in tumor and 91.4% in benign). These analyses further demonstrate variants driving MSMB expression differ in tumor and normal, suggesting regulatory network rewiring during tumorigenesis.

Risk SNP-Mediated Enhancer-Promoter Interaction Drives Colorectal Cancer through Both FADS2 and AP002754.2

Although genome-wide association studies (GWAS) have identified more than 100 colorectal cancer risk loci, most of the biological mechanisms associated with these loci remain unclear. Here we first performed a comprehensive expression quantitative trait loci analysis in colorectal cancer tissues adjusted for multiple confounders to test the determinants of germline variants in established GWAS susceptibility loci on mRNA and long noncoding RNA (lncRNA) expression. Combining integrative functional genomic/epigenomic analyses and a large-scale population study consisting of 6,024 cases and 10,022 controls, we then prioritized rs174575 with a C>G change as a potential causal candidate for colorectal cancer at 11q12.2, as its G allele was associated with an increased risk of colorectal cancer (OR = 1.26; 95% confidence interval = 1.17-1.36; P = 2.57 × 10^-9). rs174575 acted as an allele-specific enhancer to distally facilitate expression of both FADS2 and lncRNA AP002754.2 via long-range enhancer-promoter interaction loops, which were mediated by E2F1. AP002754.2 further activated a transcriptional activator that upregulated FADS2 expression. FADS2, in turn, was overexpressed in colorectal cancer tumor tissues and functioned as a potential oncogene that facilitated colorectal cancer cell proliferation and xenograft growth in vitro and in vivo by increasing the metabolism of PGE2, an oncogenic molecule involved in colorectal cancer tumorigenesis. Our findings represent a novel mechanism by which a noncoding variant can facilitate long-range genome interactions to modulate the expression of multiple genes including not only mRNA, but also lncRNA, which provides new insights into the understanding of colorectal cancer etiology. SIGNIFICANCE: This study provides an oncogenic regulatory circuit among several oncogenes including E2F1, FADS2, and AP002754.2 underlying the association of rs174575 with colorectal cancer risk, which is driven by long-range enhancer-promoter interaction loops. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/9/1804/F1.large.jpg.

DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs

Genome-wide association studies have identified more than 100 SNPs that increase the risk of prostate cancer (PrCa). We identify and compare expression quantitative trait loci (eQTLs) and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The role of DNA methylation in eQTL regulation of gene expression was investigated by data triangulation using several causal inference approaches, including a proposed adaptation of the Causal Inference Test (CIT) for causal direction. Comparing eQTLs between tumors and benign samples, we show that 98 of the 147 risk SNPs were identified as eQTLs in the tumor-adjacent benign samples, and almost all 34 eQTL identified in tumor sets were also eQTLs in the benign samples. Three lines of results support the causal role of DNA methylation. First, nearly 100 of the 147 risk SNPs were identified as meQTLs in one tumor set, and almost all eQTLs in tumors were meQTLs. Second, the loss of eQTLs in tumors relative to benign samples was associated with altered DNA methylation. Third, among risk SNPs identified as both eQTLs and meQTLs, mediation analyses suggest that over two-thirds have evidence of a causal role for DNA methylation, mostly mediating genetic influence on gene expression. In summary, we provide a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PrCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in tumor genome. Finally, our mediation analyses illuminate the likely intermediary role of CpG methylation in eQTL regulation of gene expression.

Integrating germline and somatic genetics to identify genes associated with lung cancer

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.

Upregulated OCT3 has the potential to improve the survival of colorectal cancer patients treated with (m)FOLFOX6 adjuvant chemotherapy

PURPOSE

To investigate the influence of organic cation transporter 3 (OCT3) expression on the effect of the combination regimen of 5-fluorouracil, folinic acid and oxaliplatin ((m)FOLFOX6) in colorectal cancer (CRC) patients.

METHODS

This is a retrospective study conducted at a single centre (Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, China). Patients with stage IIb-IV resectable CRC who were being postoperatively treated with (m)FOLFOX6 as a first-line adjuvant chemotherapy regimen for at least 5 cycles and had resected primary tumour samples available were eligible for the study. Patients who preoperatively received chemotherapy and/or radiotherapy or were treated with targeted drugs or other anticancer drugs were excluded from the study. Immunohistochemical staining and digital image analysis were used to assess OCT3 expression in tumour samples. According to OCT3 expression level, the receiver operating characteristic curve (ROC curve) was used to divide the patients into two groups. Cox proportional risk regression was performed with the forward LR (forward stepwise regression based on maximum likelihood estimation) method using SPSS17.0 software. The primary endpoint was the 2-year progression-free survival.

RESULTS

In total, 57 patients were included between 2014 and 2016 according to the inclusion and exclusion criteria (22 had low OCT3 expression, and 35 had high OCT3 expression). The mean age was 55.7 (30-74) years, and 37 of the total patients were male. According to TNM stage, 5 patients had stage IV disease, 44 patients had stage III disease, and 8 patients had stage II disease. Through Cox regression analysis, we found that among patients receiving the (m)FOLFOX6 regimen, those with higher OCT3 expression had a higher two-year progression-free survival rate than those with lower OCT3 expression (P = 0.038). The hazard ratio of patients with high OCT3 expression compared with patients with low OCT3 expression was 0.247. Besides, it was found that the age of patients was negatively correlated with expression level of OCT3, which can explain why patients over 70 years do not benefit from oxaliplatin-containing chemotherapy.

CONCLUSIONS

High OCT3 expression in CRC tissues may be a protective factor for CRC patients treated with (m)FOLFOX6.

Identifying Putative Susceptibility Genes and Evaluating Their Associations with Somatic Mutations in Human Cancers

Genome-wide association studies (GWASs) have identified hundreds of genetic risk variants for human cancers. However, target genes for the majority of risk loci remain largely unexplored. It is also unclear whether GWAS risk-loci-associated genes contribute to mutational signatures and tumor mutational burden (TMB) in cancer tissues. We systematically conducted cis-expression quantitative trait loci (cis-eQTL) analyses for 294 GWAS-identified variants for six major types of cancer-colorectal, lung, ovary, prostate, pancreas, and melanoma-by using transcriptome data from the Genotype-Tissue Expression (GTEx) Project, the Cancer Genome Atlas (TCGA), and other public data sources. By using integrative analysis strategies, we identified 270 candidate target genes, including 99 with previously unreported associations, for six cancer types. By analyzing functional genomic data, our results indicate that 180 genes (66.7% of 270) had evidence of cis-regulation by putative functional variants via proximal promoter or distal enhancer-promoter interactions. Together with our previously reported associations for breast cancer risk, our results show that 24 genes are shared by at least two cancer types, including four genes for both breast and ovarian cancer. By integrating mutation data from TCGA, we found that expression levels of 33 and 66 putative susceptibility genes were associated with specific mutational signatures and TMB of cancer-driver genes, respectively, at a Bonferroni-corrected p < 0.05. Together, these findings provide further insight into our understanding of how genetic risk variants might contribute to carcinogenesis through the regulation of susceptibility genes that are related to the biogenesis of somatic mutations.

Circular RNAs are differentially expressed in prostate cancer and are potentially associated with resistance to enzalutamide

Most forms of castration-resistant prostate cancer (CRPC) are dependent on the androgen receptor (AR) for survival. While, enzalutamide provides a substantial survival benefit, it is not curative and many patients develop resistance to therapy. Although not yet fully understood, resistance can develop through a number of mechanisms, such as AR copy number gain, the generation of splice variants such as AR-V7 and mutations within the ligand binding domain (LBD) of the AR. circular RNAs (circRNAs) are a novel type of non-coding RNA, which can regulate the function of miRNA, and may play a key role in the development of drug resistance. circRNAs are highly resistant to degradation, are detectable in plasma and, therefore may serve a role as clinical biomarkers. In this study, AR-V7 expression was assessed in an isogenic model of enzalutamide resistance. The model consisted of age matched control cells and two sub-line clones displaying varied resistance to enzalutamide. circRNA profiling was performed on the panel using a high throughout microarray assay. Bioinformatic analysis identified a number of differentially expressed circRNAs and predicted five miRNA binding sites for each circRNA. miRNAs were stratified based on known associations with prostate cancer, and targets were validated using qPCR. Overall, circRNAs were more often down regulated in resistant cell lines compared with control (588 vs. 278). Of particular interest was hsa_circ_0004870, which was down-regulated in enzalutamide resistant cells (p ≤ 0.05, vs. sensitive cells), decreased in cells that highly express AR (p ≤ 0.01, vs. AR negative), and decreased in malignant cells (p ≤ 0.01, vs. benign). The associated parental gene was identified as RBM39, a member of the U2AF65 family of proteins. Both genes were down-regulated in resistant cells (p < 0.05, vs. sensitive cells). This is one of the first studies to profile and demonstrate discrete circRNA expression patterns in an enzalutamide resistant cell line model of prostate cancer. Our data suggests that hsa_circ_0004870, through RBM39, may play a critical role in the development of enzalutamide resistance in CRPC.

Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms

Here we train cis-regulatory models of prostate tissue gene expression and impute expression transcriptome-wide for 233,955 European ancestry men (14,616 prostate cancer (PrCa) cases, 219,339 controls) from two large cohorts. Among 12,014 genes evaluated in the UK Biobank, we identify 38 associated with PrCa, many replicating in the Kaiser Permanente RPGEH. We report the association of elevated TMPRSS2 expression with increased PrCa risk (independent of a previously-reported risk variant) and with increased tumoral expression of the TMPRSS2:ERG fusion-oncogene in The Cancer Genome Atlas, suggesting a novel germline-somatic interaction mechanism. Three novel genes, HOXA4, KLK1, and TIMM23, additionally replicate in the RPGEH cohort. Furthermore, 4 genes, MSMB, NCOA4, PCAT1, and PPP1R14A, are associated with PrCa in a trans-ethnic meta-analysis (N = 9117). Many genes exhibit evidence for allele-specific transcriptional activation by PrCa master-regulators (including androgen receptor) in Position Weight Matrix, Chip-Seq, and Hi-C experimental data, suggesting common regulatory mechanisms for the associated genes.

Pancreatic Ductal Deletion of Hnf1b Disrupts Exocrine Homeostasis, Leads to Pancreatitis, and Facilitates Tumorigenesis

BACKGROUND & AIMS

The exocrine pancreas consists of acinar cells that produce digestive enzymes transported to the intestine through a branched ductal epithelium. Chronic pancreatitis is characterized by progressive inflammation, fibrosis, and loss of acinar tissue. These changes of the exocrine tissue are risk factors for pancreatic cancer. The cause of chronic pancreatitis cannot be identified in one quarter of patients. Here, we investigated how duct dysfunction could contribute to pancreatitis development.

METHODS

The transcription factor Hnf1b, first expressed in pancreatic progenitors, is strictly restricted to ductal cells from late embryogenesis. We previously showed that Hnf1b is crucial for pancreas morphogenesis but its postnatal role still remains unelucidated. To investigate the role of pancreatic ducts in exocrine homeostasis, we inactivated the Hnf1b gene in vivo in mouse ductal cells.

RESULTS

We uncovered that postnatal Hnf1b inactivation in pancreatic ducts leads to chronic pancreatitis in adults. Hnf1bΔ^duct mutants show dilatation of ducts, loss of acinar cells, acinar-to-ductal metaplasia, and lipomatosis. We deciphered the early events involved, with down-regulation of cystic disease-associated genes, loss of primary cilia, up-regulation of signaling pathways, especially the Yap pathway, which is involved in acinar-to-ductal metaplasia. Remarkably, Hnf1bΔ^duct mutants developed pancreatic intraepithelial neoplasia and promote pancreatic intraepithelial neoplasia progression in concert with KRAS. We further showed that adult Hnf1b inactivation in pancreatic ducts is associated with impaired regeneration after injury, with persistent metaplasia and initiation of neoplasia.

CONCLUSIONS

Loss of Hnf1b in ductal cells leads to chronic pancreatitis and neoplasia. This study shows that Hnf1b deficiency may contribute to diseases of the exocrine pancreas and gains further insight into the etiology of pancreatitis and tumorigenesis.

Oncogenic PITX2 facilitates tumor cell drug resistance by inverse regulation of hOCT3/SLC22A3 and ABC drug transporters in colon and kidney cancers

Oncogenic pituitary homeobox 2 (PITX2), a de facto master regulator of developmental organ asymmetry, previously upregulated multidrug resistance (MDR) P-glycoprotein ABCB1 in A498 renal cell carcinoma (RCC) cells. The role of PITX2 isoforms in MDR cancers was investigated. Data mining correlated elevated PITX2 in >30% of cancers analyzed, maximally in colon (4.4-fold), confirmed in co-immunostaining of colon and renal cancer microarrays wherein ABCB1 concomitantly increased in RCC. Drug-resistant colorectal adenocarcinoma Colo320DM cells exhibited increased nuclear PITX2 (40-fold), PITX2 promoter activity (27-fold) and ABCB1 (8000-fold) compared to drug-sensitive Colo205. ABCB1 inhibitor PSC833/valspodar or PITX2 siRNA reversed doxorubicin resistance. Nuclei from Colo320DM and A498 cells harbored PITX2A/B1 and PITX2A/B1/B2/Cα/Cβ, respectively. ChIP-qPCR evidenced PITX2 promoter binding in drug exporters ABCB1, ABCC1, ABCG2 and importer hOCT3/SLC22A3. In A498, 786-O, Caki-1, Colo320DM, and Caco2 cells, PITX2 siRNA diminished exporters, increased hOCT3/SLC22A3 expression and activity, and reverted vincristine resistance. Heterologous PITX2 expression induced ABCB1, repressed hOCT3/SLC22A3, enhanced vincristine resistance and diminished proliferation inhibition wherein PITX2A and PITX2C were most effective. Furthermore, PITX2 activity and MDR depended on phosphorylation by GSK3 in A498 cells. Conclusively, oncogenic PITX2 limits sensitizing drug uptake and potentiates cytoprotective drug efflux, contributing to MDR phenotype.

Post-GWAS in prostate cancer: from genetic association to biological contribution

Genome-wide association studies (GWAS) have been successful in deciphering the genetic component of predisposition to many human complex diseases including prostate cancer. Germline variants identified by GWAS progressively unravelled the substantial knowledge gap concerning prostate cancer heritability. With the beginning of the post-GWAS era, more and more studies reveal that, in addition to their value as risk markers, germline variants can exert active roles in prostate oncogenesis. Consequently, current research efforts focus on exploring the biological mechanisms underlying specific susceptibility loci known as causal variants by applying novel and precise analytical methods to available GWAS data. Results obtained from these post-GWAS analyses have highlighted the potential of exploiting prostate cancer risk-associated germline variants to identify new gene networks and signalling pathways involved in prostate tumorigenesis. In this Review, we describe the molecular basis of several important prostate cancer-causal variants with an emphasis on using post-GWAS analysis to gain insight into cancer aetiology. In addition to discussing the current status of post-GWAS studies, we also summarize the main molecular mechanisms of potential causal variants at prostate cancer risk loci and explore the major challenges in moving from association to functional studies and their implication in clinical translation.

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.

Epigenetic alterations of a novel antioxidant gene SLC22A3 predispose susceptible individuals to increased risk of esophageal cancer

Esophageal squamous cell carcinoma (ESCC) occurs with the highest frequency in China, especially in the high-risk Northern Chinese. Recent studies have reported that SLC22A3 is significantly downregulated in non-tumor (NT) esophageal tissues from familial ESCC patients compared with those from sporadic ESCC. However, the mechanism of how SLC22A3 regulates familial ESCC remains unknown. In this study, post hoc genome-wide association studies (GWAS) in 496 cases with a family history of upper gastrointestinal tract cancers and 1056 controls were performed and the results revealed that SLC22A3 is a novel susceptibility gene for familial ESCC. Reduced expression of SLC22A3 in NT esophageal tissues from familial ESCC patients significantly correlates with its promoter hypermethylation. Moreover, case-control study of Chinese descendants from different risk areas of China revealed that the methylation of the SLC22A3 gene in peripheral blood leukocyte (PBL) DNA samples could be a risk factor for developing ESCC in this high-risk population. Functional studies showed that SLC22A3 is a novel antioxidant gene, and deregulation of SLC22A3 facilitates heat stress-induced oxidative DNA damage and formation of γ-H2AX foci in normal esophageal epithelial cells. Collectively, we show that epigenetic alterations of SLC22A3 predispose susceptible individuals to increased risk of esophageal cancer.

Cumulative evidence for relationships between multiple variants of HNF1B and the risk of prostate and endometrial cancers

Background

To provide a synopsis of the current understanding of the association between variants of HNF1B and cancer susceptibility, we conducted a comprehensive research synopsis and meta-analysis to evaluate associations between HNF1B variants and prostate and endometrial cancers.

Results

Eighteen studies totaling 34,937 patients and 55,969 controls were eligible for this meta-analysis. Four variants showed a significant association with the risk of individual cancer. Strong significant associations were found between rs4430796 A and the risk of both prostate cancer (OR = 1.247, p = 2.21 × 10^− 77) and endometrial cancer (OR = 1.217, p = 8.98 × 10^− 16); the AA, AG genotypes also showed strong significant associations with the risk of prostate cancer (OR1 = 1.517, p = 4.46 × 10^− 22; OR2 = 1.180, p = 0.002). There was a strong significant association between rs7501939 G and the risk of prostate cancer (OR = 1.201, p = 9.31 × 10^− 31). Strong significant association was found between rs11649743 G (OR = 1.138, p = 1.08 × 10^− 12), rs3760511 C (OR = 1.214, p = 1.57 × 10^− 19) and the prostate cancer risk;the GG, AG genotypes of rs11649743 also showed strong significant associations with the risk of prostate cancer (OR1 = 1.496, p = 3.32 × 10^− 6; OR2 = 1.276, p = 7.82 × 10^− 6). All the cumulative epidemiological evidence of associations was graded as strong.

Conclusions

Our study summarizes the evidence and helps to reveal that common variants of HNF1B are associated with risk of prostate and endometrial cancer.

Genetic Heterogeneity of SLC22 Family of Transporters in Drug Disposition

An important aspect of modern medicine is its orientation to achieve more personalized pharmacological treatments. In this context, transporters involved in drug disposition have gained well-justified attention. Owing to its broad spectrum of substrate specificity, including endogenous compounds and xenobiotics, and its strategical expression in organs accounting for drug disposition, such as intestine, liver and kidney, the SLC22 family of transporters plays an important role in physiology, pharmacology and toxicology. Among these carriers are plasma membrane transporters for organic cations (OCTs) and anions (OATs) with a marked overlap in substrate specificity. These two major clades of SLC22 proteins share a similar membrane topology but differ in their degree of genetic variability. Members of the OCT subfamily are highly polymorphic, whereas OATs have a lower number of genetic variants. Regarding drug disposition, changes in the activity of these variants affect intestinal absorption and target tissue uptake, but more frequently they modify plasma levels due to enhanced or reduced clearance by the liver and secretion by the kidney. The consequences of these changes in transport-associated function markedly affect the effectiveness and toxicity of the treatment in patients carrying the mutation. In solid tumors, changes in the expression of these transporters and the existence of genetic variants substantially determine the response to anticancer drugs. Moreover, chemoresistance usually evolves in response to pharmacological and radiological treatment. Future personalized medicine will require monitoring these changes in a dynamic way to adapt the treatment to the weaknesses shown by each tumor at each stage in each patient.

Systematic identification of functionally relevant risk alleles to stratify aggressive versus indolent prostate cancer

Novel approaches for classification, including molecular features, are needed to direct therapy for men with low-grade prostate cancer (PCa), especially men on active surveillance. Risk alleles identified from genome-wide association studies (GWAS) could improve prognostication. Those risk alleles that coincided with genes and somatic copy number aberrations associated with progression of PCa were selected as the most relevant for prognostication.

In a systematic literature review, a total of 698 studies were collated. Fifty-three unique SNPs residing in 29 genomic regions, including 8q24, 10q11 and 19q13, were associated with PCa progression. Functional studies implicated 21 of these single nucleotide polymorphisms (SNPs) as modulating the expression of genes in the androgen receptor pathway and several other oncogenes. In particular, 8q24, encompassing MYC, harbours a high density of SNPs conferring unfavourable pathological characteristics in low-grade PCa, while a copy number gain of MYC in low-grade PCa was associated with prostate-specific antigen recurrence after radical prostatectomy.

By combining GWAS data with gene expression and structural rearrangements, risk alleles were identified that could provide a new basis for developing a prognostication tool to guide therapy for men with early prostate cancer.

Profile of common prostate cancer risk variants in an unscreened Romanian population

To find sequence variants affecting prostate cancer (PCA) susceptibility in an unscreened Romanian population we use a genome‐wide association study (GWAS). The study population included 990 unrelated pathologically confirmed PCA cases and 1034 male controls. DNA was genotyped using Illumina SNP arrays, and 24.295.558 variants were imputed using the 1000 Genomes data set. An association test was performed between the imputed markers and PCA. A systematic literature review for variants associated with PCA risk identified 115 unique variants that were tested in the Romanian sample set. Thirty of the previously reported SNPs replicated (P‐value < 0.05), with the strongest associations observed at: 8q24.21, 11q13.3, 6q25.3, 5p15.33, 22q13.2, 17q12 and 3q13.2. The replicated variants showing the most significant association in Romania are rs1016343 at 8q24.21 (P = 2.2 × 10⁻⁴), rs7929962 at 11q13.3 (P = 2.7 × 10⁻⁴) and rs9364554 at 6q25.2 (P = 4.7 × 10⁻⁴). None of the variants tested in the Romanian GWAS reached genome‐wide significance (P‐value <5 × 10⁻⁸) but 807 markers had P‐values <1 × 10⁻⁴. Here, we report the results of the first GWAS of PCA performed in a Romanian population. Our study provides evidence that a substantial fraction of previously validated PCA variants associate with risk in this unscreened Romanian population.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Oesophageal cancer: RNA editing of SLC22A3 mRNAs: causative relevance to familial ESCC?

A new study reveals an involvement of SLC22A3 in the development of familial oesophageal squamous cell carcinoma (ESCC). Reduced expression of SLC22A3 is detected not only in ESCC tumours but also in non-tumour tissues of patients with familial ESCC. Interestingly, adenosine-to-inosine editing of SLC22A3 mRNA is proposed to drive early tumour invasion and metastasis, by inhibiting SLC22A3 expression.

Comparison of miRNA and gene expression profiles between metastatic and primary prostate cancer

The present study aimed to identify the regulatory mechanisms associated with the metastasis of prostate cancer (PC). The microRNA (miRNA/miR) microarray dataset GSE21036 and gene transcript dataset GSE21034 were downloaded from the Gene Expression Omnibus database. Following pre-processing, differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between samples from patients with primary prostate cancer (PPC) and metastatic prostate cancer (MPC) with |log₂ fold change (FC)| >1 and a false discovery rate <0.05 were selected using the Linear Models for Microarray and RNA-seq Data 4 package of R. Next, a DEM-DEG regulatory network was constructed by downloading miRNA-DEG pairs from the miRNA.org database. Finally, functional annotation of each DEM-DEG module was performed using the Database for Annotation, Visualization and Integrated Discovery based on the Gene Ontology database. The upregulated miRNAs, including miR-144, miR-494 and miR-181a, exhibited a higher degree of connections compared with other nodes, including in the DEM-DEG regulatory network, and regulated a number of downregulated DEGs. According to the functional annotation of the DEM-DEG modules, miR-144 and its targeted DEGs enriched the highest number of biological process terms (36 terms), followed by miR-494 (24 terms), miR-30d (18 terms), miR-181a (15 terms), hsa-miR-196a (8 terms), miR-708 (7 terms) and miR-486-5p (2 terms). Therefore, these miRNAs may serve roles in the metastasis of PC cells via downregulation of their corresponding target DEGs.

RNA editing of SLC22A3 drives early tumor invasion and metastasis in familial esophageal cancer

Like many complex human diseases, esophageal squamous cell carcinoma (ESCC) is known to cluster in families. Familial ESCC cases often show early onset and worse prognosis than the sporadic cases. However, the molecular genetic basis underlying the development of familial ESCC is mostly unknown. We reported that SLC22A3 is significantly down-regulated in nontumor esophageal tissues from patients with familial ESCC compared with tissues from patients with sporadic ESCCs. A-to-I RNA editing of the SLC22A3 gene results in its reduced expression in the nontumor esophageal tissues of familial ESCCs and is significantly correlated with lymph node metastasis. The RNA-editing enzyme ADAR2, a familial ESCC susceptibility gene identified by our post hoc genome-wide association study, is positively correlated with the editing level of SLC22A3 Moreover, functional studies showed that SLC22A3 is a metastasis suppressor in ESCC, and deregulation of SLC22A3 facilitates cell invasion and filopodia formation by reducing its direct association with α-actinin-4 (ACTN4), leading to the increased actin-binding activity of ACTN4 in normal esophageal cells. Collectively, we now show that A-to-I RNA editing of SLC22A3 contributes to the early development and progression of familial esophageal cancer in high-risk individuals.

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

OBJECTIVES

The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management.

METHODS

We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included.

RESULTS

Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies.

CONCLUSIONS

The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.

Autoantibody biomarkers for the detection of serous ovarian cancer

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer.

METHODS

To detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n=30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n=30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n=63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed.

RESULTS

We identified 11-TAAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity.

CONCLUSION

These are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts.

Three-dimensional culture system identifies a new mode of cetuximab resistance and disease-relevant genes in colorectal cancer

We previously reported that single cells from a human colorectal cancer (CRC) cell line (HCA-7) formed either hollow single-layered polarized cysts or solid spiky masses when plated in 3D in type-I collagen. To begin in-depth analyses into whether clonal cysts and spiky masses possessed divergent properties, individual colonies of each morphology were isolated and expanded. The lines thus derived faithfully retained their parental cystic and spiky morphologies and were termed CC (cystic) and SC (spiky), respectively. Although both CC and SC expressed EGF receptor (EGFR), the EGFR-neutralizing monoclonal antibody, cetuximab, strongly inhibited growth of CC, whereas SC was resistant to growth inhibition, and this was coupled to increased tyrosine phosphorylation of MET and RON. Addition of the dual MET/RON tyrosine kinase inhibitor, crizotinib, restored cetuximab sensitivity in SC. To further characterize these two lines, we performed comprehensive genomic and transcriptomic analysis of CC and SC in 3D. One of the most up-regulated genes in CC was the tumor suppressor 15-PGDH/HPGD, and the most up-regulated gene in SC was versican (VCAN) in 3D and xenografts. Analysis of a CRC tissue microarray showed that epithelial, but not stromal, VCAN staining strongly correlated with reduced survival, and combined epithelial VCAN and absent HPGD staining portended a poorer prognosis. Thus, with this 3D system, we have identified a mode of cetuximab resistance and a potential prognostic marker in CRC. As such, this represents a potentially powerful system to identify additional therapeutic strategies and disease-relevant genes in CRC and possibly other solid tumors.

HNF1B, TSPAN8 and NOTCH2 gene polymorphisms in women with gestational diabetes

PURPOSE

To investigate genes involved in pancreatic beta cell function, insulin production and glucose metabolism that may predispose to gestational diabetes mellitus (GDM).

METHODS

The study group consisted of 204 women with GDM and 207 women with normal glucose tolerance (NGT). The following polymorphisms were genotyped for each patient: HNF1B rs4430796, TSPAN8 rs7961581 and NOTCH2 rs10923931. A p value of <.05 was considered to indicate a statistically significant result.

RESULTS

There was a statistically significant increase in the frequency of HNF1B rs4430796 G allele among pregnant women with GDM (GG+AG versus AA, OR: 1.55, 95% CI: 1.01-2.36, p = .042; G versus A, OR: 1.39, 95% CI: 1.06-1.83, p = .018), whereas there were no statistically significant differences in the distributions of TSPAN8 rs7961581 and NOTCH2 rs10923931 genotypes and alleles between women with GDM and healthy pregnant women. In the multivariate logistic regression analysis, older age, higher BMI before pregnancy and a higher number of HNF1B rs4430796 G alleles were independent significant predictors of a higher risk of GDM.

CONCLUSIONS

The results of this study suggest that the HNF1B gene rs4430796 G allele may be associated with increased risk of GDM.

A spatiotemporal hypothesis for the regulation, role, and targeting of AMPK in prostate cancer

The 5'-AMP-activated protein kinase (AMPK) is a master regulator of cellular homeostasis. Despite AMPK's known function in physiology, its role in pathological processes such as prostate cancer is enigmatic. However, emerging evidence is now beginning to decode the paradoxical role of AMPK in cancer and, therefore, inform clinicians if - and how - AMPK could be therapeutically targeted. Spatiotemporal regulation of AMPK complexes could be one of the mechanisms that governs this kinase's role in cancer. We hypothesize that different upstream stimuli will activate select subcellular AMPK complexes. This hypothesis is supported by the distinct subcellular locations of the various AMPK subunits. Each of these unique AMPK complexes regulates discrete downstream processes that can be tumour suppressive or oncogenic. AMPK's final biological output is then determined by the weighted net function of these downstream signalling events, influenced by additional prostate-specific signalling.

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers

BACKGROUND

Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits.

METHODS

The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background.

RESULTS

The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis.

CONCLUSIONS

Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.

IMPACT

Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.