High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing

Comprehensive mapping of genetic variation at Epromoters reveals pleiotropic association with multiple disease traits

There is growing evidence that a wide range of human diseases and physiological traits are influenced by genetic variation of cis-regulatory elements. We and others have shown that a subset of promoter elements, termed Epromoters, also function as enhancer regulators of distal genes. This opens a paradigm in the study of regulatory variants, as single nucleotide polymorphisms (SNPs) within Epromoters might influence the expression of several (distal) genes at the same time, which could disentangle the identification of disease-associated genes. Here, we built a comprehensive resource of human Epromoters using newly generated and publicly available high-throughput reporter assays. We showed that Epromoters display intrinsic and epigenetic features that distinguish them from typical promoters. By integrating Genome-Wide Association Studies (GWAS), expression Quantitative Trait Loci (eQTLs) and 3D chromatin interactions, we found that regulatory variants at Epromoters are concurrently associated with more disease and physiological traits, as compared with typical promoters. To dissect the regulatory impact of Epromoter variants, we evaluated their impact on regulatory activity by analyzing allelic-specific high-throughput reporter assays and provided reliable examples of pleiotropic Epromoters. In summary, our study represents a comprehensive resource of regulatory variants supporting the pleiotropic role of Epromoters.

PCAT19: the role in cancer pathogenesis and beyond

PCAT19, a long non-coding RNA, has attracted considerable attention due to its diverse roles in various malignancies. This work compiles current research on PCAT19's involvement in cancer pathogenesis and progression. Abnormal expression of PCAT19 has been observed in various cancers, and its correlation with clinical features and prognosis positions it as a promising prognostic biomarker. Additionally, its ability to effectively differentiate between tumor and normal tissues suggests significant diagnostic value. PCAT19 exhibits a dual nature, functioning either as an oncogene or a tumor suppressor, depending on the cancer type. It is implicated in a range of tumor-related activities, including cell proliferation, apoptosis, invasion, migration, metabolism, as well as tumor growth and metastasis. PCAT19 acts as a competing endogenous RNA (ceRNA) or interacts with proteins to regulate critical cancer-related pathways, such as MELK signaling, p53 signaling, and cell cycle pathways. Furthermore, emerging evidence suggests that PCAT19 plays a role in the modulation of neuropathic pain, adding complexity to its functional repertoire. By exploring the molecular mechanisms and pathways associated with PCAT19, we aim to provide a comprehensive understanding of its multifaceted roles in human health and disease, highlighting its potential as a therapeutic target for cancer and pain management.

Linking Iris Cis-Regulatory Variants to Primary Angle-Closure Glaucoma Via Clinical Imaging and Multiomics

Purpose

To elucidate the genetic basis of primary angle-closure glaucoma (PACG) by identifying pathogenic tissue and critical tissue-specific variants.

Methods

The correlations among PACG susceptibility, axial length (AL), and anterior chamber depth (ACD) were evaluated using meta-analyses. Propensity score matching was utilized on 2161 participants from the Handan Eye Study to determine the risk factors independent of ACD and AL for PACG. Subsequently, we employed the assay for transposase-accessible chromatin with sequencing (ATAC-seq) and allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to screen 202 PACG genome-wide association study (GWAS) variants for chromatin accessibility and functional roles.

Results

The meta-analysis found that PACG susceptibility loci are not associated with ACD or AL. However, abnormal iris phenotypes emerged as significant independent risk factors for primary angle-closure disease (PACD), unrelated to ACD and AL. Substantial enrichment of PACG heritability was observed in the open chromatin regions of the human iris. Within the iris-relevant cellular context, 22 out of the 202 PACG GWAS variants could influence enhancer activity. Two variants in the iris open chromatin regions were implicated in the modulation of PLEKHA7 and C10orf53 expression. The downregulation of these two genes affects cytoskeletal organization.

Conclusions

Our findings underscore the importance of the iris in the pathogenesis of PACG and identified iris-specific, enhancer-modulating variants that may influence disease risk. Our approach also provides a generalizable framework for studying ocular diseases from the perspective of enhancer-modulating variants.

Molecular methods in cancer diagnostics: a short review

BACKGROUND

One of the ailments with the greatest fatality rates in the 21st century is cancer. Globally, molecular methods are widely employed to treat cancer-related disorders, and the body of research on this subject is growing yearly. A thorough and critical summary of the data supporting molecular methods for illnesses linked to cancer is required.

OBJECTIVE

In order to guide clinical practice and future research, it is important to examine and summarize the systematic reviews (SRs) that evaluate the efficacy and safety of molecular methods for disorders associated to cancer.

METHODS

We developed a comprehensive search strategy to find relevant articles from electronic databases like PubMed, Google Scholar, Web of Science (WoS), or Scopus. We looked through the literature and determined which diagnostic methods in cancer genetics were particularly reliable. We used phrases like 'cancer genetics', genetic susceptibility, Hereditary cancer, cancer risk assessment, 'cancer diagnostic tools', cancer screening', biomarkers, and molecular diagnostics, reviews and meta-analyses evaluating the efficacy and safety of molecular therapies for cancer-related disorders. Research that only consider treatment modalities that don't necessitate genetic or molecular diagnostics fall under the exclusion criteria.

RESULTS

The results of this comprehensive review clearly demonstrate the transformative impact of molecular methods in the realm of cancer genetics.This review underscores how these technologies have empowered researchers and clinicians to identify and understand key genetic alterations that drive malignancy, ranging from point mutations to structural variations. Such insights are instrumental in pinpointing critical oncogenic drivers and potential therapeutic targets, thus opening the door for methods in precision medicine that can significantly improve patient outcomes.

LIMITATION

The search does not specify a timeframe for publication inclusion, it may have missed recent advancements or changes in the field's landscape of molecular methods for cancer. As a result, it may not have included the most recent developments in the field.

CONCLUSION

After conducting an in-depth study on the molecular methods in cancer genetics, it is evident that these cutting-edge technologies have revolutionized the field of oncology, providing researchers and clinicians with powerful tools to unravel the complexities of cancer at the genetic level. The integration of molecular methods techniques has not only enhanced our understanding of cancer etiology, progression, and treatment response but has also opened new avenues for personalized medicine and targeted therapies, leading to improved patient outcomes.

Methods for Functional Characterization of Genetic Polymorphisms of Non-Coding Regulatory Regions of the Human Genome

Currently, numerous associations between genetic polymorphisms and various diseases have been characterized through the Genome-Wide Association Studies. Majority of the clinically significant polymorphisms are localized in non-coding regions of the genome. While modern bioinformatic resources make it possible to predict molecular mechanisms that explain influence of the non-coding polymorphisms on gene expression, such hypotheses require experimental verification. This review discusses the methods for elucidating molecular mechanisms underlying dependence of the disease pathogenesis on specific genetic variants within the non-coding sequences. A particular focus is on the methods for identification of transcription factors with binding efficiency dependent on polymorphic variations. Despite remarkable progress in bioinformatic resources enabling prediction of the impact of polymorphisms on the disease pathogenesis, there is still the need for experimental approaches to investigate this issue.

Validated Negative Regions (VNRs) in the VISTA Database might be Truncated Forms of Bona Fide Enhancers

The VISTA enhancer database is a valuable resource for evaluating predicted enhancers in humans and mice. In addition to thousands of validated positive regions (VPRs) in the human and mouse genomes, the database also contains similar numbers of validated negative regions (VNRs). It is previously shown that the VPRs are on average half as long as predicted overlapping enhancers that are highly conserved and hypothesize that the VPRs may be truncated forms of long bona fide enhancers. Here, it is shown that like the VPRs, the VNRs also are under strong evolutionary constraints and overlap predicted enhancers in the genomes. The VNRs are also on average half as long as predicted overlapping enhancers that are highly conserved. Moreover, the VNRs and the VPRs display similar cell/tissue-specific modification patterns of key epigenetic marks of active enhancers. Furthermore, the VNRs and the VPRs show similar impact score spectra of in silico mutagenesis. These highly similar properties between the VPRs and the VNRs suggest that like the VPRs, the VNRs may also be truncated forms of long bona fide enhancers.

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.

Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis

The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.

Ultra-Fast Single-Nucleotide-Variation Detection Enabled by Argonaute-Mediated Transistor Platform

"Test-and-go" single-nucleotide variation (SNV) detection within several minutes remains challenging, especially in low-abundance samples, since existing methods face a trade-off between sensitivity and testing speed. Sensitive detection usually relies on complex and time-consuming nucleic acid amplification or sequencing. Here, a graphene field-effect transistor (GFET) platform mediated by Argonaute protein that enables rapid, sensitive, and specific SNV detection is developed. The Argonaute protein provides a nanoscale binding channel to preorganize the DNA probe, accelerating target binding and rapidly recognizing SNVs with single-nucleotide resolution in unamplified tumor-associated microRNA, circulating tumor DNA, virus RNA, and reverse transcribed cDNA when a mismatch occurs in the seed region. An integrated microchip simultaneously detects multiple SNVs in agreement with sequencing results within 5 min, achieving the fastest SNV detection in a "test-and-go" manner without the requirement of nucleic acid extraction, reverse transcription, and amplification.

Human-genome single nucleotide polymorphisms affecting transcription factor binding and their role in pathogenesis

Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association (genome-wide association studies, GWASs) with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which - among transcriptomes of homozygotes and heterozygotes for its various alleles - there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases.

PNA-Pdx: Versatile Peptide Nucleic Acid-Based Detection of Nucleic Acids and SNPs

Monitoring diseases caused by pathogens or by mutations in DNA sequences requires accurate, rapid, and sensitive tools to detect specific nucleic acid sequences. Here, we describe a new peptide nucleic acid (PNA)-based nucleic acid detection toolkit, termed PNA-powered diagnostics (PNA-Pdx). PNA-Pdx employs PNA probes that bind specifically to a target and are then detected in lateral flow assays. This can precisely detect a specific pathogen or genotype genomic sequence. PNA probes can also be designed to invade double-stranded DNAs (dsDNAs) to produce single-stranded DNAs for precise CRISPR-Cas12b-based detection of genomic SNPs without requiring the protospacer-adjacent motif (PAM), as Cas12b requires PAM sequences only for dsDNA targets. PNA-Pdx identified target nucleic acid sequences at concentrations as low as 2 copies/μL and precisely detected the SARS-CoV-2 genome in clinical samples in 40 min. Furthermore, the specific dsDNA invasion by the PNA coupled with CRISPR-Cas12b precisely detected genomic SNPs without PAM restriction. Overall, PNA-Pdx provides a novel toolkit for nucleic acid and SNP detection as well as highlights the benefits of engineering PNA probes for detecting nucleic acids.

Underlying causes for prevalent false positives and false negatives in STARR-seq data

Self-transcribing active regulatory region sequencing (STARR-seq) and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR-seq peaks are located in repressive chromatin and are not functional in the tested cells. While some of the STARR-seq peaks in repressive chromatin might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. Although methods have been proposed to mitigate systematic errors caused by the use of plasmid vectors, the artifacts due to the intrinsic limitations of current STARR-seq methods are still prevalent and the underlying causes are not fully understood. Based on predicted cis-regulatory modules (CRMs) and non-CRMs in the human genome as well as predicted active CRMs and non-active CRMs in a few human cell lines/tissues with STARR-seq data available, we reveal prevalent false positives and false negatives in STARR-seq peaks generated by major variants of STARR-seq methods and possible underlying causes. Our results will help design strategies to improve STARR-seq methods and interpret the results.

Immune checkpoint-related gene polymorphisms are associated with acute myeloid leukemia

BACKGROUND

Chemotherapy is still the standard regimen for treating acute myeloid leukemia (AML) and its disappointing efficacy requires the urgent need for new therapeutic targets. It is well known that immune response plays an increasingly significant role in the pathogenesis of AML.

METHODS

We detected nine single nucleotide polymorphisms (SNPs) in immune checkpoint-related genes, including PD1, LAG3, TIM3, and TIGIT in 285 AML inpatients and 324 healthy controls. SNP genotyping was performed on the MassARRAY platform. Furthermore, we analyzed the relationship between the susceptibility and prognosis of AML and the selected SNPs.

RESULTS

Our results showed that rs2227982 and rs10204525 in PD1 were significantly associated with susceptibility to AML after false discovery rate correction. PD1 rs10204525 also showed a significant correlation with the response to chemotherapy and risk stratification of AML. Importantly, the AA genotype of PD1 (rs2227982) under the recessive model showed a negative impact on AML prognosis independently.

CONCLUSIONS

Our results indicate that PD1 SNPs are important for susceptibility and prognosis in AML, which may provide a new therapeutic target for AML patients.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

KLK2 single-nucleotide polymorphism rs198977 is associated with increased susceptibility and hyperleukocytosis in AML

Introduction: Acute myeloid leukemia (AML) is a heterogeneous myeloid malignancy with abnormal molecular diversity. Tissue kallikrein 2 (KLK2) is a kind of serine protease, and has a close relationship with the occurrence and development of malignant tumors. Single nucleotide polymorphism (SNP) of various genes are associated with susceptibility, treatment and survival of AML. Methods: We investigated the association of KLK2 SNPs rs198977 and rs2664155 with AML. We recruited 284 AML patients and 280 healthy controls from the Han population and genotyping KLK2 SNPs rs198977 and rs2664155 by MassARRAY system. Results: Using clinical data from AML patients and controls, including AML susceptibility, blood count, risk stratification, response to induced chemotherapy and survival, our results showed an increased risk of AML susceptibility with KLK2 rs198977 TT genotype in the recessive model. Regarding white blood cell counts in AML patients, the results showed an increased risk of hyperleukocytosis with the TT genotype of KLK2 rs198977 in a codominant model. Moreover, in the recessive model, AML with KLK2 SNPs rs198977 TT genotype had an increased risk of hyperleukocytosis. No significant correlation was found between KLK2 rs2664155 and AML. Discussion: This study suggests that KLK2 rs198977 may be an important genetic factor in the occurrence of AML and hyperleukocytosis in AML, providing a new perspective for disease progression and new therapeutic targets.

Short tandem repeats are important contributors to silencer elements in T cells

The action of cis-regulatory elements with either activation or repression functions underpins the precise regulation of gene expression during normal development and cell differentiation. Gene activation by the combined activities of promoters and distal enhancers has been extensively studied in normal and pathological contexts. In sharp contrast, gene repression by cis-acting silencers, defined as genetic elements that negatively regulate gene transcription in a position-independent fashion, is less well understood. Here, we repurpose the STARR-seq approach as a novel high-throughput reporter strategy to quantitatively assess silencer activity in mammals. We assessed silencer activity from DNase hypersensitive I sites in a mouse T cell line. Identified silencers were associated with either repressive or active chromatin marks and enriched for binding motifs of known transcriptional repressors. CRISPR-mediated genomic deletions validated the repressive function of distinct silencers involved in the repression of non-T cell genes and genes regulated during T cell differentiation. Finally, we unravel an association of silencer activity with short tandem repeats, highlighting the role of repetitive elements in silencer activity. Our results provide a general strategy for genome-wide identification and characterization of silencer elements.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Challenges and considerations for reproducibility of STARR-seq assays

High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.

Strategies for activity analysis of single nucleotide polymorphisms associated with human diseases

Genome-wide association studies (GWAS) have identified a large number of single nucleotide polymorphism (SNP) sites associated with human diseases. In the annotation of human diseases, especially cancers, SNPs, as an important component of genetic factors, have gained increasing attention. Given that most of the SNPs are located in non-coding regions, the functional verification of these SNPs is a great challenge. The key to functional annotation for risk SNPs is to screen SNPs with regulatory activity from thousands of disease associated-SNPs. In this review, we systematically recapitulate the characteristics and functional roles of SNP sites, discuss three parallel reporter screening strategies in detail based on barcode tag classification, and recommend the common in silico strategies to help supplement the annotation of SNP sites with epigenetic activity analysis, prediction of target genes and trans-acting factors. We hope that this review will contribute to this exuberant research field by providing robust activity analysis strategies that can facilitate the translation of GWAS results into personalized diagnosis and prevention measures for human diseases.

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

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.

Liquid Biopsy in Diagnosis and Prognosis of Non-Metastatic Prostate Cancer

Currently, sensitive and specific methods for the detection and prognosis of early stage PCa are lacking. To establish the diagnosis and further identify an appropriate treatment strategy, prostate specific antigen (PSA) blood test followed by tissue biopsy have to be performed. The combination of tests is justified by the lack of a highly sensitive, specific, and safe single test. Tissue biopsy is specific but invasive and may have severe side effects, and therefore is inappropriate for screening of the disease. At the same time, the PSA blood test, which is conventionally used for PCa screening, has low specificity and may be elevated in the case of noncancerous prostate tumors and inflammatory conditions, including benign prostatic hyperplasia and prostatitis. Thus, diverse techniques of liquid biopsy have been investigated to supplement or replace the existing tests of prostate cancer early diagnosis and prognostics. Here, we provide a review on the advances in diagnosis and prognostics of non-metastatic prostate cancer by means of various biomarkers extracted via liquid biopsy, including circulating tumor cells, exosomal miRNAs, and circulating DNAs.

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients' outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

Extensive germline-somatic interplay contributes to prostate cancer progression through HNF1B co-option of TMPRSS2-ERG

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

Gene Regulatory Identification Based on the Novel Hybrid Time-Delayed Method

Gene regulatory network (GRN) inference with biology data is a difficult and serious issue in the field of system biology. In order to detect the direct associations of GRN more accurately, a novel two-step GRN inference technique based on the time-delayed correlation coefficient (TDCC) and time-delayed complex-valued S-system model (TDCVSS) is proposed. First, a TDCC algorithm is utilized to construct an initial network. Second, a TDCVSS model is utilized to prune the network topology in order to delete false-positive regulatory relationships for each target gene. The complex-valued restricted additive tree and complex-valued differential evolution are proposed to approximate the optimal TDCVSS model. Finally, the overall network could be inferred by integrating the regulations of all target genes. Two real gene expression datasets from E. coli and S. cerevisiae gene networks are utilized to evaluate the performances of our proposed two-step GRN inference algorithm. The results demonstrated that the proposed algorithm could infer GRN more correct than classical methods and time-delayed methods.

Discrimination of Single-Nucleotide Variants Based on an Allele-Specific Hybridization Chain Reaction and Smartphone Detection

Massive DNA testing requires novel technologies to support a sustainable health system. In recent years, DNA superstructures have emerged as alternative probes and transducers. We, herein, report a multiplexed and highly sensitive approach based on an allele-specific hybridization chain reaction (AS-HCR) in the array format to detect single-nucleotide variants. Fast isothermal amplification was developed before activating the HCR process on a chip to work with genomic DNA. The assay principle was demonstrated, and the variables for integrating the AS-HCR process and smartphone-based detection were also studied. The results were compared to a conventional polymerase reaction chain (PCR)-based test. The developed multiplex method enabled higher selectivity against single-base mismatch sequences at concentrations as low as 10³ copies with a limit of detection of 0.7% of the mutant DNA percentage and good reproducibility (relative error: 5% for intra-assay and 17% for interassay). As proof of concept, the AS-HCR method was applied to clinical samples, including human cell cultures and biopsied tissues of cancer patients. Accurate identification of single-nucleotide mutations in KRAS and NRAS genes was validated, considering those obtained from the reference sequencing method. To conclude, AS-HCR is a rapid, simple, accurate, and cost-effective isothermal method that detects clinically relevant genetic variants and has a high potential for point-of-care demands.

Functional noncoding SNPs in human endothelial cells fine-map vascular trait associations

Functional consequences of genetic variation in the noncoding human genome are difficult to ascertain despite demonstrated associations to common, complex disease traits. To elucidate properties of functional noncoding SNPs with effects in human endothelial cells (ECs), we utilized our previous molecular quantitative trait locus (molQTL) analysis for transcription factor binding, chromatin accessibility, and H3K27 acetylation to nominate a set of likely functional noncoding SNPs. Together with information from genome-wide association studies (GWASs) for vascular disease traits, we tested the ability of 34,344 variants to perturb enhancer function in ECs using the highly multiplexed STARR-seq assay. Of these, 5711 variants validated, whose enriched attributes included: (1) mutations to TF binding motifs for ETS or AP-1 that are regulators of the EC state; (2) location in accessible and H3K27ac-marked EC chromatin; and (3) molQTL associations whereby alleles associate with differences in chromatin accessibility and TF binding across genetically diverse ECs. Next, using pro-inflammatory IL1B as an activator of cell state, we observed robust evidence (>50%) of context-specific SNP effects, underscoring the prevalence of noncoding gene-by-environment (GxE) effects. Lastly, using these cumulative data, we fine-mapped vascular disease loci and highlighted evidence suggesting mechanisms by which noncoding SNPs at two loci affect risk for pulse pressure/large artery stroke and abdominal aortic aneurysm through respective effects on transcriptional regulation of POU4F1 and LDAH. Together, we highlight the attributes and context dependence of functional noncoding SNPs and provide new mechanisms underlying vascular disease risk.

CASCADE: high-throughput characterization of regulatory complex binding altered by non-coding variants

Non-coding DNA variants (NCVs) impact gene expression by altering binding sites for regulatory complexes. New high-throughput methods are needed to characterize the impact of NCVs on regulatory complexes. We developed CASCADE (Customizable Approach to Survey Complex Assembly at DNA Elements), an array-based high-throughput method to profile cofactor (COF) recruitment. CASCADE identifies DNA-bound transcription factor-cofactor (TF-COF) complexes in nuclear extracts and quantifies the impact of NCVs on their binding. We demonstrate CASCADE sensitivity in characterizing condition-specific recruitment of COFs p300 and RBBP5 (MLL subunit) to the CXCL10 promoter in lipopolysaccharide (LPS)-stimulated human macrophages and quantify the impact of all possible NCVs. To demonstrate applicability to NCV screens, we profile TF-COF binding to ~1,700 single-nucleotide polymorphism quantitative trait loci (SNP-QTLs) in human macrophages and identify perturbed ETS domain-containing complexes. CASCADE will facilitate high-throughput testing of molecular mechanisms of NCVs for diverse biological applications.

Bray et al. develop CASCADE, a method to profile transcription factor (TF)-cofactor (COF) complexes binding to DNA. They demonstrate the approach by profiling complex binding across the CXCL10 cytokine promoter and to ~1,700 single-nucleotide polymorphisms (SNPs). They anticipate that CASCADE can be applied to diverse biological systems to examine regulatory complex binding to DNA.

Identification of Novel Prognostic Markers Associated With Laryngeal Squamous Cell Carcinoma Using Comprehensive Analysis

Background

Laryngeal squamous cell carcinoma (LSCC) is a leading malignant cancer of the head and neck. Patients with LSCC, in which the cancer has infiltrated and metastasized, have a poor prognosis. Therefore, there is an urgent need to identify more potential targets for drugs and biomarkers for early diagnosis.

Methods

RNA sequence data from LSCC and patients’ clinical traits were obtained from the Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) database. Differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify hub genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, prognostic value analysis, receiver operating characteristic (ROC) curve analysis, gene mutation analysis, tumor-infiltrating immune cell abundance profile estimation, gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) were performed. Single-gene RNA sequencing data were obtained from the GSE150321 dataset. Cell proliferation and viability were confirmed by the CCK-8 assay and real-time PCR.

Results

A total of 701 DEGs, including 329 upregulated and 372 downregulated genes, were screened in the GSE142083 dataset. Using WGCNA, three modules were identified to be closely related to LSCC. After intersecting the DEGs and performing univariate and multivariate Cox analyses, a novel prognostic model based on three genes (SLC35C1, HOXB7, and TEDC2) for LSCC was established. Interfering TEDC2 expression inhibited tumor cell proliferation and migration.

Conclusions

Our results show that SLC35C1, HOXB7, and TEDC2 have the potential to become new therapeutic targets and prognostic biomarkers for LSCC.

CRISPRi links COVID-19 GWAS loci to LZTFL1 and RAVER1

Background

To identify host genetic variants (SNPs) associated with COVID-19 disease severity, a number of genome-wide association studies (GWAS) have been conducted. Since most of the identified variants are located at non-coding regions, such variants are presumed to affect the expression of neighbouring genes, thereby influencing COVID-19 disease severity. However, it remains largely unknown which genes are influenced by such COVID-19 GWAS loci.

Methods

CRISPRi (interference)-mediated gene expression analysis was performed to identify genes functionally regulated by COVID-19 GWAS loci by targeting regions near the loci (SNPs) in lung epithelial cell lines. The expression of CRISPRi-identified genes was investigated using COVID-19-contracted human and monkey lung single-nucleus/cell (sn/sc) RNA-seq datasets.

Findings

CRISPRi analysis indicated that a region near rs11385942 at chromosome 3p21.31 (locus of highest significance with COVID-19 disease severity at intron 5 of LZTFL1) significantly affected the expression of LZTFL1 (P<0.05), an airway cilia regulator. A region near rs74956615 at chromosome 19p13.2 (locus located at the 3’ untranslated exonic region of RAVER1), which is associated with critical illness in COVID-19, affected the expression of RAVER1 (P<0.05), a coactivator of MDA5 (IFIH1), which induces antiviral response genes, including ICAM1. The sn/scRNA-seq datasets indicated that the MDA5/RAVER1-ICAM1 pathway was activated in lung epithelial cells of COVID-19-resistant monkeys but not those of COVID-19-succumbed humans.

Interpretation

Patients with risk alleles of rs11385942 and rs74956615 may be susceptible to critical illness in COVID-19 in part through weakened airway viral clearance via LZTFL1-mediated ciliogenesis and diminished antiviral immune response via the MDA5/RAVER1 pathway, respectively.

Funding

NIH.

Dinucleotide tag-based parallel reporter gene assay method enables efficient identification of regulatory mutations

BACKGROUND

The causal single nucleotide polymorphisms (SNPs) leading to increased cancer predisposition mainly function as gene regulatory elements, the evaluation of which largely relies on the parallel reporter gene assay system. However, the common DNA barcodes used in parallel reporter gene assay systems typically because nucleotide composition bias, and many barcodes must be allocated for each sequence to reduce the bias effect.

MAIN METHODS AND MAJOR RESULTS

Here, a versatile dinucleotide-tag reporter system (DiR) that enables parallel analysis of regulatory elements with minimized bias based on next-generation sequencing is described. The DiR system is more robust than the classical luciferase assay method, particularly for the investigation of moderate-level regulatory elements. The authors applied the DiR-seq assay in the functional evaluation of SNPs with prostate cancer risk and nominated two and six regulatory SNPs in PC-3 and LNCaP cells, respectively.

CONCLUSIONS AND IMPLICATIONS

The DiR system has great potential to advance the functional study of SNPs associated with polygenic disease risks.

Mechanistic insights into genetic susceptibility to prostate cancer

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

Functional Screenings Identify Regulatory Variants Associated with Breast Cancer Susceptibility

Genome-wide association studies (GWAS) have identified more than 2000 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, most of which are located in the non-coding region. However, the causal SNPs functioning as gene regulatory elements still remain largely undisclosed. Here, we applied a Dinucleotide Parallel Reporter sequencing (DiR-seq) assay to evaluate 288 breast cancer risk SNPs in nine different breast cancer cell lines. Further multi-omics analysis with the ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing), DNase-seq (DNase I hypersensitive sites sequencing) and histone modification ChIP-seq (Chromatin Immunoprecipitation sequencing) nominated seven functional SNPs in breast cancer cells. Functional investigations show that rs4808611 affects breast cancer progression by altering the gene expression of NR2F6. For the other site, rs2236007, the alteration promotes the binding of the suppressive transcription factor EGR1 and results in the downregulation of PAX9 expression. The downregulated expression of PAX9 causes cancer malignancies and is associated with the poor prognosis of breast cancer patients. Our findings contribute to defining the functional risk SNPs and the related genes for breast cancer risk prediction.

Parallel Reporter Assays Identify Altered Regulatory Role of rs684232 in Leading to Prostate Cancer Predisposition

Functional characterization of cancer risk-associated single nucleotide polymorphism (SNP) identified by genome-wide association studies (GWAS) has become a big challenge. To identify the regulatory risk SNPs that can lead to transcriptional misregulation, we performed parallel reporter gene assays with both alleles of 213 prostate cancer risk-associated GWAS SNPs in 22Rv1 cells. We disclosed 32 regulatory SNPs that exhibited different regulatory activities with two alleles. For one of the regulatory SNPs, rs684232, we found that the variation altered chromatin binding of transcription factor FOXA1 on the DNA region and led to aberrant gene expression of VPS53, FAM57A, and GEMIN4, which play vital roles in prostate cancer malignancy. Our findings reveal the roles and underlying mechanism of rs684232 in prostate cancer progression and hold great promise in benefiting prostate cancer patients with prognostic prediction and target therapies.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

How Cancer Risk SNPs May Contribute to Prostate Cancer Disparities

Disparities in cancer incidence, prevalence, burden, and outcome exist among specific population groups in the United States. Researchers have identified germline genetic risk single-nucleotide polymorphisms (SNP) that differ by ancestry and may contribute to some of these differences. In this issue of Cancer Research, Han and colleagues found the prostate cancer risk SNP rs4713266 is associated with increased risk of patients with African ancestry. The authors investigated the functional role of the risk SNP, finding that it alters activity of a NEDD9 enhancer and increases NEDD9 expression. The study provides epidemiologic and mechanistic insight into factors that may drive prostate cancer disparities.See related article by Han et al., p. 3766.

A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs

Currently, the detection of the allele asymmetry of gene expression from RNA-seq data or the transcription factor binding from ChIP-seq data is one of the approaches used to identify the functional genetic variants that can affect gene expression (regulatory SNPs or rSNPs). In this study, we searched for rSNPs using the data for human pulmonary arterial endothelial cells (PAECs) available from the Sequence Read Archive (SRA). Allele-asymmetric binding and expression events are analyzed in paired ChIP-seq data for H3K4me3 mark and RNA-seq data obtained for 19 individuals. Two statistical approaches, weighted z-scores and predicted probabilities, were used to improve the efficiency of finding rSNPs. In total, we identified 14,266 rSNPs associated with both allele-specific binding and expression. Among them, 645 rSNPs were associated with GWAS phenotypes; 4746 rSNPs were reported as eQTLs by GTEx, and 11,536 rSNPs were located in 374 candidate transcription factor binding motifs. Additionally, we searched for the rSNPs associated with gene expression using an SRA RNA-seq dataset for 281 clinically annotated human postmortem brain samples and detected eQTLs for 2505 rSNPs. Based on these results, we conducted Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and constructed the protein-protein interaction networks to represent the top-ranked biological processes with a possible contribution to the phenotypic outcome.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Optimized CRISPR/Cas9-mediated single nucleotide mutation in adherent cancer cell lines

CRISPR/Cas9 is an efficient, accurate, and optimizable genome-editing tool. Here, we present a modified CRISPR/Cas9 genome-editing protocol for single nucleotide mutation in adherent cell lines. The protocol was adapted to focus on ease of use and efficiency. The protocol here describes how to generate a single nucleotide mutation in cultured 22Rv1 cells. We have also used the protocol in other adherent cell types. Thus, the protocol can be applied to assessing the effect of non-coding single nucleotide polymorphisms (SNPs) in a variety of cell types.

For complete details on the use and execution of this protocol, please refer to Gao et al. (2018).

•

A detailed protocol for CRISPR/Cas9-mediated single nucleotide editing in cultured cells

•

Protocol to convert an SNP genotype in 22Rv1 cell line

•

Efficient and easy method yields single cell clones with desired genotypes

•

Applicable to the study of SNPs in a variety of adherent cell lines

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.

Recent Discoveries in the Androgen Receptor Pathway in Castration-Resistant Prostate Cancer

The androgen receptor (AR) is the main therapeutic target in advanced prostate cancer, because it regulates the growth and progression of prostate cancer cells. Patients may undergo multiple lines of AR-directed treatments, including androgen-deprivation therapy, AR signaling inhibitors (abiraterone acetate, enzalutamide, apalutamide, or darolutamide), or combinations of these therapies. Yet, tumors inevitably develop resistance to the successive lines of treatment. The diverse mechanisms of resistance include reactivation of the AR and dysregulation of AR cofactors and collaborative transcription factors (TFs). Further elucidating the nexus between the AR and collaborative TFs may reveal new strategies targeting the AR directly or indirectly, such as targeting BET proteins or OCT1. However, appropriate preclinical models will be required to test the efficacy of these approaches. Fortunately, an increasing variety of patient-derived models, such as xenografts and organoids, are being developed for discovery-based research and preclinical drug screening. Here we review the mechanisms of drug resistance in the AR signaling pathway, the intersection with collaborative TFs, and the use of patient-derived models for novel drug discovery.

Immunorelated gene polymorphisms associated with acute myeloid leukemia

Although the pathogenesis of acute myeloid leukemia (AML) is still unknown, accumulating evidence has revealed that immune response plays a vital part in the pathogenesis. Here, we investigated the involvement of 21 single nucleotide polymorphisms (SNPs) of immunorelated genes, including cytokines [interleukin (IL)-2, IL-4, IL-9, IL-12A, IL-22, interferon (IFN-α) and transforming growth factor (TGF)-β1], transcriptional regulatory genes (TBX21, STAT1, STAT3, STAT5B, STAT6, GATA3, FOXP3 and IRF4) and others (IL2RA, IL6R, NFKBIA) in 269 AML in-patients and 200 healthy controls. Furthermore, we analyzed the relationship between the SNPs and clinical characteristics. Immunorelated SNP genotyping was performed on the Sequenom MassARRAY iPLEX platform. All the SNPs in healthy controls were consistent with Hardy-Weinberg equilibrium. All final P-values were adjusted by Bonferroni multiple testing. Our results showed that IL-22 (rs2227491) was significantly associated with the white blood cell (WBC) counts. Signal transducer and activator of transcription 5B (STAT-5B) (rs6503691) showed a close relationship with the recurrent genetic abnormalities in patients with AML. We verified the negatively independent effect of age and risk of cytogenetics on overall survival (OS). More importantly, the GG genotype of IL-12A (rs6887695) showed a negative impact on AML prognosis independently. Furthermore, the relative expression of IL-12 was decreased in GG genotype, no matter under a co-dominant or recessive model. However, no correlation was observed between the SNPs mentioned above and disease susceptibility, risk stratification and survival. Our findings suggest that immunorelated gene polymorphisms are associated with prognosis in AML, which may perform as novel inspection targets for AML patients.

RPL41 sensitizes retinoblastoma cells to chemotherapeutic drugs via ATF4 degradation

Retinoblastoma is the most common intraocular cancer with metastatic potential affecting infants and children. Although chemotherapy is available for retinoblastoma, side effects and drug resistance are frequent. Rpl41, encoding ribosomal protein L41 (RPL41), has been identified as a tumor suppressor gene, and its targeted degradation of activating transcription factor 4 (ATF4) produces an antitumor effect. The goal of the present study is to provide experimental evidence for the clinical application of a small peptide regimen in combination with chemotherapy for the treatment of retinoblastoma and to investigate the mechanism of their combined cytotoxicity. It was observed that treatment with the RPL41 peptide alone decreased the viability, migration, and invasion of retinoblastoma Y79 and Weri-Rb1 cells, in addition to promoting cell apoptosis and cell cycle arrest. Furthermore, RPL41 protein levels showed a significantly decreased trend in retinoblastoma specimens, whereas ATF4 protein levels tended to be increased. Mechanistically, ATF4 degradation as a result of RPL41 peptide treatment was observed in retinoblastoma Y79 and Weri-Rb1 cells. Most important, low-dose administration of the RPL41 peptide significantly enhanced the antitumor effect of carboplatin, and further analysis confirmed their synergistic effect as anti-retinoblastoma therapy, indicating that RPL41 sensitized Y79 and Weri-Rb1 retinoblastoma cells to carboplatin. Thus, our data provide a preclinical rationale for the exploration of the RPL41 peptide as a potential adjuvant to carboplatin treatment in retinoblastoma.

A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs

GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information.

Identification of potential markers for type 2 diabetes mellitus via bioinformatics analysis

Type 2 diabetes mellitus (T2DM) is a multifactorial and multigenetic disease, and its pathogenesis is complex and largely unknown. In the present study, microarray data (GSE201966) of β-cell enriched tissue obtained by laser capture microdissection were downloaded, including 10 control and 10 type 2 diabetic subjects. A comprehensive bioinformatics analysis of microarray data in the context of protein-protein interaction (PPI) networks was employed, combined with subcellular location information to mine the potential candidate genes for T2DM and provide further insight on the possible mechanisms involved. First, differential analysis screened 108 differentially expressed genes. Then, 83 candidate genes were identified in the layered network in the context of PPI via network analysis, which were either directly or indirectly linked to T2DM. Of those genes obtained through literature retrieval analysis, 27 of 83 were involved with the development of T2DM; however, the rest of the 56 genes need to be verified by experiments. The functional analysis of candidate genes involved in a number of biological activities, demonstrated that 46 upregulated candidate genes were involved in ‘inflammatory response’ and ‘lipid metabolic process’, and 37 downregulated candidate genes were involved in ‘positive regulation of cell death’ and ‘positive regulation of cell proliferation’. These candidate genes were also involved in different signaling pathways associated with ‘PI3K/Akt signaling pathway’, ‘Rap1 signaling pathway’, ‘Ras signaling pathway’ and ‘MAPK signaling pathway’, which are highly associated with the development of T2DM. Furthermore, a microRNA (miR)-target gene regulatory network and a transcription factor-target gene regulatory network were constructed based on miRNet and NetworkAnalyst databases, respectively. Notably, hsa-miR-192-5p, hsa-miR-124-5p and hsa-miR-335-5p appeared to be involved in T2DM by potentially regulating the expression of various candidate genes, including procollagen C-endopeptidase enhancer 2, connective tissue growth factor and family with sequence similarity 105, member A, protein phosphatase 1 regulatory inhibitor subunit 1 A and C-C motif chemokine receptor 4. Smad5 and Bcl6, as transcription factors, are regulated by ankyrin repeat domain 23 and transmembrane protein 37, respectively, which might also be used in the molecular diagnosis and targeted therapy of T2DM. Taken together, the results of the present study may offer insight for future genomic-based individualized treatment of T2DM and help determine the underlying molecular mechanisms that lead to T2DM.

CRISPRi-mediated functional analysis of lung disease-associated loci at non-coding regions

Genome-wide association studies have identified lung disease-associated loci; however, the functions of such loci are not well understood in part because the majority of such loci are located at non-coding regions. Hi-C, ChIP-seq and eQTL data predict potential roles (e.g. enhancer) of such loci; however, they do not elucidate the molecular function. To determine whether these loci function as gene-regulatory regions, CRISPR interference (CRISPRi; CRISPR/dCas9-KRAB) has been recently used. Here, we applied CRISPRi along with Hi-C, ChIP-seq and eQTL to determine the functional roles of loci established as highly associated with asthma, cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). Notably, Hi-C, ChIP-seq and eQTL predicted that non-coding regions located at chromosome 19q13 or chromosome 17q21 harboring single-nucleotide polymorphisms (SNPs) linked to asthma/CF/COPD and chromosome 11p15 harboring an SNP linked to IPF interact with nearby genes and function as enhancers; however, CRISPRi indicated that the regions with rs1800469, rs2241712, rs12603332 and rs35705950, but not others, regulate the expression of nearby genes (single or multiple genes). These data indicate that CRISPRi is useful to precisely determine the roles of non-coding regions harboring lung disease-associated loci as to whether they function as gene-regulatory regions at a genomic level.

Identification of Functional Variant Enhancers Associated With Atrial Fibrillation

RATIONALE

Genome-wide association studies have identified a large number of common variants (single-nucleotide polymorphisms) associated with atrial fibrillation (AF). These variants are located mainly in noncoding regions of the genome and likely include variants that modulate the function of transcriptional regulatory elements (REs) such as enhancers. However, the actual REs modulated by variants and the target genes of such REs remain to be identified. Thus, the biological mechanisms by which genetic variation promotes AF has thus far remained largely unexplored.

OBJECTIVE

To identify REs in genome-wide association study loci that are influenced by AF-associated variants.

METHODS AND RESULTS

We screened 2.45 Mbp of human genomic DNA containing 12 strongly AF-associated loci for RE activity using self-transcribing active regulatory region sequencing and a recently generated monoclonal line of conditionally immortalized rat atrial myocytes. We identified 444 potential REs, 55 of which contain AF-associated variants (P<10^-8). Subsequently, using an adaptation of the self-transcribing active regulatory region sequencing approach, we identified 24 variant REs with allele-specific regulatory activity. By mining available chromatin conformation data, the possible target genes of these REs were mapped. To define the physiological function and target genes of such REs, we deleted the orthologue of an RE containing noncoding variants in the Hcn4 (potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 4) locus of the mouse genome. Mice heterozygous for the RE deletion showed bradycardia, sinus node dysfunction, and selective loss of Hcn4 expression.

CONCLUSIONS

We have identified REs at multiple genetic loci for AF and found that loss of an RE at the HCN4 locus results in sinus node dysfunction and reduced gene expression. Our approach can be broadly applied to facilitate the identification of human disease-relevant REs and target genes at cardiovascular genome-wide association studies loci.

Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders

Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.

Single-nucleotide polymorphism rs13426236 contributes to an increased prostate cancer risk via regulating MLPH splicing variant 4

A prostate cancer risk single-nucleotide polymorphism (SNP), rs13426236, is significantly associated with melanophilin (MLPH) expression. To functionally characterize role of the rs13426236 in prostate cancer, we first performed splicing-specific expression quantitative trait loci analysis and refined the significant association of rs13426236 allele G with an increased expression of MLPH splicing transcript variant 4 (V4) (P = 7.61E-5) but not other protein-coding variants (V1-V3) (P > .05). We then performed an allele-specific reporter assay to determine if SNP-containing sequences functioned as an active enhancer. Compared to allele A, allele G of rs13426236 showed significantly higher luciferase activity on the promoter of the splicing transcript V4 (P < .03) but not on the promoter of transcript V1 (P > .05) in two prostate cancer cell lines (DU145 and 22Rv1). Cell transfection assays showed stronger effect of transcript V4 than V1 on promoting cell proliferation, invasion, and antiapoptotic activities. RNA profiling analysis demonstrated that transcript V4 overexpression caused significant expression changes in glycosylation/glycoprotein and metal-binding gene ontology pathways (FDR < 0.01). We also found that both transcripts V4 and V1 were significantly upregulated in prostate adenocarcinoma (P ≤ 2.49E-6) but only transcript V4 upregulation was associated with poor recurrence-free survival (P = .028, hazard ratio = 1.63, 95% confidence interval = 1.05-2.42) in The Cancer Genome Atlas data. This study provides strong evidence showing that prostate cancer risk SNP rs13426236 upregulates expression of MLPH transcript V4, which may function as a candidate oncogene in prostate cancer.