Role of non-coding sequence variants in cancer

The reference epigenome and regulatory chromatin landscape of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a frequent hematological neoplasm in which underlying epigenetic alterations are only partially understood. Here, we analyze the reference epigenome of seven primary CLLs and the regulatory chromatin landscape of 107 primary cases in the context of normal B cell differentiation. We identify that the CLL chromatin landscape is largely influenced by distinct dynamics during normal B cell maturation. Beyond this, we define extensive catalogues of regulatory elements de novo reprogrammed in CLL as a whole and in its major clinico-biological subtypes classified by IGHV somatic hypermutation levels. We uncover that IGHV-unmutated CLLs harbor more active and open chromatin than IGHV-mutated cases. Furthermore, we show that de novo active regions in CLL are enriched for NFAT, FOX and TCF/LEF transcription factor family binding sites. Although most genetic alterations are not associated with consistent epigenetic profiles, CLLs with MYD88 mutations and trisomy 12 show distinct chromatin configurations. Furthermore, we observe that non-coding mutations in IGHV-mutated CLLs are enriched in H3K27ac-associated regulatory elements outside accessible chromatin. Overall, this study provides an integrative portrait of the CLL epigenome, identifies extensive networks of altered regulatory elements and sheds light on the relationship between the genetic and epigenetic architecture of the disease.

Non-coding RNAs: the riddle of the transcriptome and their perspectives in cancer

Non-coding RNAs (ncRNAs) constitute a heterogeneous group of RNA molecules in terms of biogenesis, biological function as well as length and structure. These biological molecules have gained attention recently as a potentially crucial layer of tumor cell progression or regulation. ncRNAs are expressed in a broad spectrum of tumors, and they play an important role not only in maintaining but also in promoting cancer development and progression. Recent discoveries have revealed that ncRNAs may act as key signal transduction mediators in tumor signaling pathways by interacting with RNA or proteins. These results reinforce the hypothesis, that ncRNAs constitute therapeutic targets, and point out their clinical potential as stratification markers. The major purpose of this review is to mention the emergence of the importance of ncRNAs, as molecules which are correlated with cancer, and to discuss their clinical implicit as prognostic diagnostic indicators, biomarkers, and therapeutic targets.

Cancer driver mutation prediction through Bayesian integration of multi-omic data

Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel Bayesian hierarchical modeling approach, named rDriver can achieve enhanced prediction accuracy by identifying mutations that not only have high functional impact scores but also are associated with systemic variation in gene expression levels. In examining 3,080 tumor samples from 8 cancer types in The Cancer Genome Atlas, rDriver predicted 1,389 driver mutations. Compared with existing tools, rDriver identified more low frequency mutations associated with lineage specific functional properties, timing of occurrence and patient survival. Evaluation of rDriver predictions using engineered cell-line models resulted in a positive predictive value of 0.94 in PIK3CA genes. Our study highlights the importance of integrating multi-omic data in predicting cancer driver mutations and provides a statistically rigorous solution for cancer target discovery and development.

Prediction and identification of transcriptional regulatory elements at the lung cancer-specific DKK1 locus

The glycoprotein dickkopf 1 (DKK1) is highly expressed in lung cancer cell lines and tissues. Our previous study demonstrated that DKK1 promoter activity is low in lung cancer cell lines. This may be because it lacks the necessary transcriptional regulatory elements (TREs) required for higher activity levels. However, it is difficult to computationally predict functionally significant TREs, as TREs from different locations can affect large segments of distant DNA. The Encyclopedia of DNA Elements project features multiple integrated technologies and approaches for the discovery and definition of functional elements, including enhancer elements and enhancer-blocking insulators. In the present study, DNase I hypersensitive sites and histone modifications of DKK1 were investigated in the A549 lung cancer cell line using the UCSC Genome Browser. A set of cis-acting enhancer elements were identified by a dual-luciferase reporter gene assay system to increase activity of the DKK1 promoter with lung cancer specificity. To the best of our knowledge, these data provide the first insight into the role of the DKK1 locus in lung cancer, and confirm the contribution of intronic cis-acting elements to the regulation of DKK1 expression, providing a new insight into gene regulation in lung cancer, which could inform the development of targeted therapy.

FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications

We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources).

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

Genetic testing for hereditary prostate cancer: Current status and limitations

A significant proportion of prostate cancer diagnoses may be associated with a strong hereditary component. Men who have multiple single-gene polymorphisms and a family history of prostate cancer have a significantly greater risk of developing prostate cancer. Numerous single-gene alterations have been confirmed to increase the risk of prostate cancer. These include breast cancer genes 1 and 2 (BRCA1 and BRCA2, respectively), mutL homolog 1 (MLH1), mutS homologs 2 and 6 (MSH2 and MSH6, respectively), postmeiotic segregation increased 2 (PMS2), homeobox B13 (HOXB13), checkpoint kinase 2 (CHEK2), nibrin (NBN), BRCA1-interacting protein C-terminal helicase 1 (BRIP1), and ataxia telangiectasia mutated (ATM). Currently, there are no uniform guidelines on the definition of hereditary prostate cancer and genetic testing. With the advent of next-generation sequencing, which is capable of testing multiple genes simultaneously, and the approval of olaparib for BRCA1/BRCA2 or ATM-mutated, metastatic, castrate-resistant prostate cancer, it is being recognized that the results of genetic testing have an impact on therapeutic strategies. In this review, the authors examine the role of genetic counseling and testing, the challenges of insurance coverage for testing, the available germline and somatic testing panels, and the complexity of each testing method and its implications. Cancer 2018. © 2018 American Cancer Society.

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These “somatic eQTLs” (expression Quantitative Trait Loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines, and that increasing DAAM1 expression leads to invasive cell migration. Collectively the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.

Long Noncoding RNA in Cancer: Wiring Signaling Circuitry

Long noncoding RNAs (lncRNAs), which are encoded by a vast less explored region of the human genome, may hold missing drivers of cancer and have gained attention recently as a potentially crucial layer of cancer cell regulation. lncRNAs are aberrantly expressed in a broad spectrum of cancers, and they play key roles in promoting and maintaining tumor initiation and progression, demonstrating their clinical potential as biomarkers and therapeutic targets. Recent discoveries have revealed that lncRNAs act as key signal transduction mediators in cancer signaling pathways by interacting with proteins, RNA, and lipids. Here, we review the mechanisms by which lncRNAs regulate cellular responses to extracellular signals and discuss their clinical potential as diagnostic indicators, stratification markers, and therapeutic targets of combinatorial treatments.

Clinically actionable mutation profiles in patients with cancer identified by whole-genome sequencing

Next-generation sequencing (NGS) efforts have established catalogs of mutations relevant to cancer development. However, the clinical utility of this information remains largely unexplored. Here, we present the results of the first eight patients recruited into a clinical whole-genome sequencing (WGS) program in the United Kingdom. We performed PCR-free WGS of fresh frozen tumors and germline DNA at 75× and 30×, respectively, using the HiSeq2500 HTv4. Subtracted tumor VCFs and paired germlines were subjected to comprehensive analysis of coding and noncoding regions, integration of germline with somatically acquired variants, and global mutation signatures and pathway analyses. Results were classified into tiers and presented to a multidisciplinary tumor board. WGS results helped to clarify an uncertain histopathological diagnosis in one case, led to informed or supported prognosis in two cases, leading to de-escalation of therapy in one, and indicated potential treatments in all eight. Overall 26 different tier 1 potentially clinically actionable findings were identified using WGS compared with six SNVs/indels using routine targeted NGS. These initial results demonstrate the potential of WGS to inform future diagnosis, prognosis, and treatment choice in cancer and justify the systematic evaluation of the clinical utility of WGS in larger cohorts of patients with cancer.

Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs, TPT1 and LCP1 Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that change TPT1 and LCP1 RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependent TPT1 and LCP1 mRNA structures were on their environments. We performed SHAPE-MaP on TPT1 and LCP1 mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.

Long noncoding RNAs: Undeciphered cellular codes encrypting keys of colorectal cancer pathogenesis

Long noncoding RNAs are non-protein coding transcripts longer than 200 nucleotides in length. By the advance in genetic and bioinformatic technologies, the new genomic landscape including noncoding transcripts has been revealed. Despite their non-capacity to be translated into proteins, lncRNAs have a versatile functions through various mechanisms interacting with other cellular molecules including DNA, protein, and RNA. Recent research interest and endeavor have identified the functional role of lncRNAs in various diseases including cancer. Colorectal cancer (CRC) is not only one of the most frequent cancer but also one of the cancer types with remarkable achievements in lncRNA research. Of the numerous notable lncRNAs identified and characterized in CRC, we will focus on key lncRNAs with the high potential as CRC-specific biomarkers in this review.

An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes

Background

Sequence variations in coding and non-coding regions of the genome can affect gene expression and signalling pathways, which in turn may influence disease outcome.

Methods

In this study, we integrated somatic mutations, gene expression and clinical data from 930 breast cancer patients included in the TCGA database. Genes associated with single mutations in molecular breast cancer subtypes were identified by the Mann-Whitney U-test and their prognostic value was evaluated by Kaplan-Meier and Cox regression analyses. Results were confirmed using gene expression profiles from the Metabric data set (n = 1988) and whole-genome sequencing data from the TCGA cohort (n = 117).

Results

The overall mutation rate in coding and non-coding regions were significantly higher in ER-negative/HER2-negative tumours (P = 2.8E–03 and P = 2.4E–07, respectively). Recurrent sequence variations were identified in non-coding regulatory regions of several cancer-associated genes, including NBPF1, PIK3CA and TP53. After multivariate regression analysis, gene signatures associated with three coding mutations (CDH1, MAP3K1 and TP53) and two non-coding variants (CRTC3 and STAG2) in cancer-related genes predicted prognosis in ER-positive/HER2-negative tumours.

Conclusions

These findings demonstrate that sequence alterations influence gene expression and oncogenic pathways, possibly affecting the outcome of breast cancer patients. Our data provide potential opportunities to identify non-coding variations with functional and clinical relevance in breast cancer.

Dissection and function of autoimmunity-associated TNFAIP3 (A20) gene enhancers in humanized mouse models

Enhancers regulate gene expression and have been linked with disease pathogenesis. Little is known about enhancers that regulate human disease-associated genes in primary cells relevant for pathogenesis. Here we use BAC transgenics and genome editing to dissect, in vivo and in primary immune cells, enhancers that regulate human TNFAIP3, which encodes A20 and is linked with autoimmune diseases. A20 expression is dependent on a topologically associating subdomain (sub-TAD) that harbors four enhancers, while another >20 enhancers in the A20 locus are redundant. This sub-TAD contains cell- and activation-specific enhancers, including an enhancer (termed TT>A) harboring a proposed causal SLE-associated SNV. Deletion of the sub-TAD or the TT>A enhancer results in enhanced inflammatory responses, autoantibody production, and inflammatory arthritis, thus establishing functional importance in vivo and linking enhancers with a specific disease phenotype. These findings provide insights into enhancers that regulate human A20 expression to prevent inflammatory pathology and autoimmunity.

The human TNFAIP3 gene, which encodes for A20, is associated with autoimmune diseases. Here, the authors use BAC transgenics combined with CRISPR- and recombineering-mediated genome editing to dissect in vivo and in primary immune cells, the role of enhancers regulating TNFAIP3.

Investigation of single and synergic effects of NLRC5 and PD-L1 variants on the risk of colorectal cancer

Constitutive activation of interferon signaling pathways has been reported in colorectal cancer (CRC), leading to a strong CD8+ T cell response through stimulation of NLRC5 expression. Primed CD8+ T cell expansion, however, may be negatively regulated by PD-L1 expression. Additionally, aberrant PD-L1 expression enables cancer cells to escape the immune attack. Our study aimed to select potential regulatory variants in the NLRC5 and PD-L1 genes by using several online in silico tools, such as UCSC browser, HaploReg, Regulome DB, Gtex Portal, microRNA and transcription factor binding site prediction tools and to investigate their influence on CRC risk in a Czech cohort of 1424 CRC patients and 1114 healthy controls. Logistic regression analysis adjusted for age and gender reported a moderate association between rectal cancer risk and two NLRC5 SNPs, rs1684575 T>G (OR: 1.60, 95% CI: 1.13-2.27, recessive model) and rs3751710 (OR: 0.70, 95% CI: 0.51-0.96, dominant model). Given that a combination of genetic variants, rather than a single polymorphism, may explain better the genetic etiology of CRC, we studied the interplay between the variants within NLRC5, PD-L1 and the previously genotyped IFNGR1 and IFNGR2 variants, to evaluate their involvement in the risk of CRC development. Overall we obtained 18 pair-wise interactions within and between the NLRC5 ad PD-L1 genes and 6 more when IFNGR variants were added. Thirteen out of the 24 interactions were below the threshold for the FDR calculated and controlled at an arbitrary level q*<0.10. Furthermore, the interaction IFNGR2 rs1059293 C>T-NLRC5 rs289747 G>A (P<0.0001) remained statistically significant even after Bonferroni correction. Our data suggest that not only a single genetic variant but also an interaction between two or more variants within genes involved in immune regulation may play important roles in the onset of CRC, providing therefore novel biological information, which could eventually improve CRC risk management but also PD-1-based immunotherapy in CRC.

Identification of Single Nucleotide Non-coding Driver Mutations in Cancer

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.

The role of long noncoding RNAs in cancer: the dark matter matters

Sequencing technology has facilitated a new era of cancer research, especially in cancer genomics. Using next-generation sequencing, thousands of long noncoding RNAs (lncRNAs) have been identified as abnormally altered in the cancer genome or differentially expressed in tumor tissues. These lncRNAs are associated with imbalanced gene regulation and aberrant biological processes that contribute to malignant transformation. The functions and therapeutic potential of cancer-related lncRNAs have attracted considerable interest in the past few years. Although few lncRNAs have been well-characterized, researchers have recently made impressive progress in understanding lncRNAs and their novel functions, such as regulation of gene expression, metabolism and DNA repair. These latest findings reinforce the crucial roles of lncRNAs in cancer initiation and development, as well as their possible clinical applications.

Exploiting non-canonical translation to identify new targets for T cell-based cancer immunotherapy

Cryptic MHC I-associated peptides (MAPs) are produced via two mechanisms: translation of protein-coding genes in non-canonical reading frames and translation of allegedly non-coding sequences. In general, cryptic MAPs are coded by relatively short open reading frames whose translation can be regulated at the level of initiation, elongation or termination. In contrast to conventional MAPs, the processing of cryptic MAPs is frequently proteasome independent. The existence of cryptic MAPs derived from allegedly non-coding regions enlarges the scope of CD8 T cell immunosurveillance from a mere ~2% to as much as ~75% of the human genome. Considering that 99% of cancer-specific mutations are located in those allegedly non-coding regions, cryptic MAPs could furthermore represent a particularly rich source of tumor-specific antigens. However, extensive proteogenomic analyses will be required to determine the breath as well as the temporal and spatial plasticity of the cryptic MAP repertoire in normal and neoplastic cells.

lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs), which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA )RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC) method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes) that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.

A transatlantic perspective on the integration of immuno-oncology prognostic and predictive biomarkers in innovative clinical trial design

Immuno-therapeutics aim to activate the body's own immune system against cancer and are one of the most promising cancer treatment strategies, but currently limited by a variable response rate. Biomarkers may help to distinguish those patients most likely to respond to therapy; they may also help guide clinical decision making for combination therapies, dosing schedules, and determining progression versus relapse. However, there is a need to confirm such biomarkers in preferably prospective clinical trials before they can be used in practice. Accordingly, it is essential that clinical trials for immuno-therapeutics incorporate biomarkers. Here, focusing on the specific setting of immune therapies, we discuss both the scientific and logistical hurdles to identifying potential biomarkers and testing them in clinical trials.

Breakthroughs in modern cancer therapy and elusive cardiotoxicity: Critical research-practice gaps, challenges, and insights

To date, five cancer treatment modalities have been defined. The three traditional modalities of cancer treatment are surgery, radiotherapy, and conventional chemotherapy, and the two modern modalities include molecularly targeted therapy (the fourth modality) and immunotherapy (the fifth modality). The cardiotoxicity associated with conventional chemotherapy and radiotherapy is well known. Similar adverse cardiac events are resurging with the fourth modality. Aside from the conventional and newer targeted agents, even the most newly developed, immune-based therapeutic modalities of anticancer treatment (the fifth modality), e.g., immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapy, have unfortunately led to potentially lethal cardiotoxicity in patients. Cardiac complications represent unresolved and potentially life-threatening conditions in cancer survivors, while effective clinical management remains quite challenging. As a consequence, morbidity and mortality related to cardiac complications now threaten to offset some favorable benefits of modern cancer treatments in cancer-related survival, regardless of the oncologic prognosis. This review focuses on identifying critical research-practice gaps, addressing real-world challenges and pinpointing real-time insights in general terms under the context of clinical cardiotoxicity induced by the fourth and fifth modalities of cancer treatment. The information ranges from basic science to clinical management in the field of cardio-oncology and crosses the interface between oncology and onco-pharmacology. The complexity of the ongoing clinical problem is addressed at different levels. A better understanding of these research-practice gaps may advance research initiatives on the development of mechanism-based diagnoses and treatments for the effective clinical management of cardiotoxicity.

Principles and methods of in-silico prioritization of non-coding regulatory variants

Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.

Functional analysis of a CDKN2A 5'UTR germline variant associated with pancreatic cancer development

CDKN2A coding region germline variants are associated with pancreatic adenocarcinoma (PC) susceptibility. Recently, we described functional germline 5’UTR CDKN2A variants from melanoma patients affecting the post-transcriptional regulation of p16^INK4a mRNA that is dependent, at least in part, on an Internal Ribosome Entry Site (IRES) in the 5’UTR region. Here we describe a 5’UTR c.-201_-198delinsCTTT CDKN2A variant (frequency 0.0028 based on 350 PC patients), which seems to be private to PC, since it has never been found in public databases nor in thousands of melanoma patients tested. Functional analyses confirmed IRES activity of the 5’UTR in BX-PC3 PC cells and revealed a functional impact of the identified variant. Using gene reporter assays we observed reduced translation potential in cells treated with the mTOR inhibitor Torin1, a condition that favors the assessment of IRES activity. At the endogenous gene level we quantified allelic imbalance among polysome-associated mRNAs using a patient-derived cell line heterozygous for the c.-201_-198delinsCTTT. Overall, we conclude that this very rare private variant can be considered a potential mutation, specifically associated with PC. Our data indicate that sequencing of the entire 5'UTR of CDKN2A should be included in routine screening of PC cases with suspected inherited susceptibility.

Predicting cancer type from tumour DNA signatures

Background

Establishing the cancer type and site of origin is important in determining the most appropriate course of treatment for cancer patients. Patients with cancer of unknown primary, where the site of origin cannot be established from an examination of the metastatic cancer cells, typically have poor survival. Here, we evaluate the potential and limitations of utilising gene alteration data from tumour DNA to identify cancer types.

Methods

Using sequenced tumour DNA downloaded via the cBioPortal for Cancer Genomics, we collected the presence or absence of calls for gene alterations for 6640 tumour samples spanning 28 cancer types, as predictive features. We employed three machine-learning techniques, namely linear support vector machines with recursive feature selection, L₁-regularised logistic regression and random forest, to select a small subset of gene alterations that are most informative for cancer-type prediction. We then evaluated the predictive performance of the models in a comparative manner.

Results

We found the linear support vector machine to be the most predictive model of cancer type from gene alterations. Using only 100 somatic point-mutated genes for prediction, we achieved an overall accuracy of 49.4±0.4 % (95 % confidence interval). We observed a marked increase in the accuracy when copy number alterations are included as predictors. With a combination of somatic point mutations and copy number alterations, a mere 50 genes are enough to yield an overall accuracy of 77.7±0.3 %.

Conclusions

A general cancer diagnostic tool that utilises either only somatic point mutations or only copy number alterations is not sufficient for distinguishing a broad range of cancer types. The combination of both gene alteration types can dramatically improve the performance.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0493-2) contains supplementary material, which is available to authorized users.

Functional germline variants as potential co-oncogenes

Germline variants that affect the expression or function of proteins contribute to phenotypic variation in humans and likely determine individual characteristics and susceptibility to diseases including cancer. A number of high penetrance germline variants that increase cancer risk have been identified and studied, but germline functional polymorphisms are not typically considered in the context of cancer biology, where the focus is primarily on somatic mutations. Yet, there is evidence from familial cancers indicating that specific cancer subtypes tend to arise in carriers of high-risk germline variants (e.g., triple negative breast cancers in mutated BRCA carriers), which suggests that pre-existing germline variants may determine which complementary somatic driver mutations are needed to drive tumorigenesis. Recent genome sequencing studies of large breast cancer cohorts reported only a handful of highly recurrent driver mutations, suggesting that different oncogenic events drive individual cancers. Here, we propose that germline polymorphisms can function as oncogenic modifiers, or co-oncogenes, and these determine what complementary subsequent somatic events are required for full malignant transformation. Therefore, we propose that germline aberrations should be considered together with somatic mutations to determine what genes drive cancer and how they may be targeted.

The functions and unique features of long intergenic non-coding RNA

Long intergenic non-coding RNA (lincRNA) genes have diverse features that distinguish them from mRNA-encoding genes and exercise functions such as remodelling chromatin and genome architecture, RNA stabilization and transcription regulation, including enhancer-associated activity. Some genes currently annotated as encoding lincRNAs include small open reading frames (smORFs) and encode functional peptides and thus may be more properly classified as coding RNAs. lincRNAs may broadly serve to fine-tune the expression of neighbouring genes with remarkable tissue specificity through a diversity of mechanisms, highlighting our rapidly evolving understanding of the non-coding genome.

An exome sequencing based approach for genome-wide association studies in the dog

Genome-wide association studies (GWAS) are widely used to identify loci associated with phenotypic traits in the domestic dog that has emerged as a model for Mendelian and complex traits. However, a disadvantage of GWAS is that it always requires subsequent fine-mapping or sequencing to pinpoint causal mutations. Here, we performed whole exome sequencing (WES) and canine high-density (cHD) SNP genotyping of 28 dogs from 3 breeds to compare the SNP and linkage disequilibrium characteristics together with the power and mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS. Using simulated phenotypes, we showed that EG-GWAS has a higher power than cHD to detect associations within target regions and less power outside target regions, with power being influenced further by sample size and SNP density. We analyzed two real phenotypes (hair length and furnishing), that are fixed in certain breeds to characterize mapping precision of the known causal mutations. EG-GWAS identified the associated exonic and 3'UTR variants within the FGF5 and RSPO2 genes, respectively, with only a few samples per breed. In conclusion, we demonstrated that EG-GWAS can identify loci associated with Mendelian phenotypes both within and across breeds.

Profile of the breast cancer susceptibility marker rs4245739 identifies a role for miRNAs

OBJECTIVE

To determine the influence of the single nucleotide polymorphism (SNP) rs4245739 on the binding and expression of microRNAs and subsequent MDM4 expression and the correlation of these factors with clinical determinants of ER-negative breast cancers.

METHODS

FindTar and miRanda were used to detect the manner in which potential microRNAs are affected by the SNP rs4245739-flanking sequence. RNA sequencing data for ER-negative breast cancer from The Cancer Genome Atlas (TCGA) were used to compare the expression of miR-184, miR-191, miR-193a, miR-378, and MDM4 in different rs4245739 genotypes.

RESULTS

Comparison of ER-negative cancer patients with and without the expression of miR-191 as well as profile microRNAs (miR-184, miR-191, miR-193a and miR-378 altogether) can differentiate the expression of MDM4 among different rs4245739 genotypes. Although simple genotyping alone did not reveal significant clinical relationships, the combination of genotyping and microRNA profiles was able to significantly differentiate individuals with larger tumor size and lower number of involved lymph nodes (P < 0.05) in the risk group (A allele).

CONCLUSIONS

We present two novel methods to analyze SNPs within 3'UTRs that use: (i) a single miRNA marker expression and (ii) an expression profile of miRNAs predicted to bind to the SNP region. We demonstrate that the application of these two methods, in particular the miRNA profile approach, permits detection of new molecular and clinical features related to the rs4245739 variant in ER-negative breast cancer.

A genome-wide interactome of DNA-associated proteins in the human liver

Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions.

Crosstalk between the Notch signaling pathway and non-coding RNAs in gastrointestinal cancers

The Notch signaling pathway is one of the main signaling pathways that mediates direct contact between cells, and is essential for normal development. It regulates various cellular processes, including cell proliferation, apoptosis, migration, invasion, angiogenesis and metastasis. It additionally serves an important function in tumor progression. Non-coding RNAs mainly include small microRNAs, long non-coding RNAs and circular RNAs. At present, a large body of literature supports the biological significance of non-coding RNAs in tumor progression. It is also becoming increasingly evident that cross-talk exists between Notch signaling and non-coding RNAs. The present review summarizes the current knowledge of Notch-mediated gastrointestinal cancer cell processes, and the effect of the crosstalk between the three major types of non-coding RNAs and the Notch signaling pathway on the fate of gastrointestinal cancer cells.

A method to reduce ancestry related germline false positives in tumor only somatic variant calling

BACKGROUND

Significant clinical and research applications are driving large scale adoption of individualized tumor sequencing in cancer in order to identify tumors-specific mutations. When a matched germline sample is available, somatic mutations may be identified using comparative callers. However, matched germline samples are frequently not available such as with archival tissues, which makes it difficult to distinguish somatic from germline variants. While population databases may be used to filter out known germline variants, recent studies have shown private germline variants result in an inflated false positive rate in unmatched tumor samples, and the number germline false positives in an individual may be related to ancestry.

METHODS

First, we examined the relationship between the germline false positives and ancestry. Then we developed and implemented a tumor only caller (LumosVar) that leverages differences in allelic frequency between somatic and germline variants in impure tumors. We used simulated data to systematically examine how copy number alterations, tumor purity, and sequencing depth should affect the sensitivity of our caller. Finally, we evaluated the caller on real data.

RESULTS

We find the germline false-positive rate is significantly higher for individuals of non-European Ancestry largely due to the limited diversity in public polymorphism databases and due to population-specific characteristics such as admixture or recent expansions. Our Bayesian tumor only caller (LumosVar) is able to greatly reduce false positives from private germline variants, and our sensitivity is similar to predictions based on simulated data.

CONCLUSIONS

Taken together, our results suggest that studies of individuals of non-European ancestry would most benefit from our approach. However, high sensitivity requires sufficiently impure tumors and adequate sequencing depth. Even in impure tumors, there are copy number alterations that result in germline and somatic variants having similar allele frequencies, limiting the sensitivity of the approach. We believe our approach could greatly improve the analysis of archival samples in a research setting where the normal is not available.

MicroRNA-335-5p is a potential suppressor of metastasis and invasion in gastric cancer

Background

Multiple aberrant microRNA expression has been reported in gastric cancer. Among them, microRNA-335-5p (miR-335), a microRNA regulated by DNA methylation, has been reported to possess both tumor suppressor and tumor promoter activities.

Results

Herein, we show that miR-335 levels are reduced in gastric cancer and significantly associate with lymph node metastasis, depth of tumor invasion, and ultimately poor patient survival in a cohort of Amerindian/Hispanic patients. In two gastric cancer cell lines AGS and, Hs 746T the exogenous miR-335 decreases migration, invasion, viability, and anchorage-independent cell growth capacities. Performing a PCR array on cells transfected with miR-335, 19 (30.6%) out of 62 genes involved in metastasis and tumor invasion showed decreased transcription levels. Network enrichment analysis narrowed these genes to nine (PLAUR, CDH11, COL4A2, CTGF, CTSK, MMP7, PDGFA, TIMP1, and TIMP2). Elevated levels of PLAUR, a validated target gene, and CDH11 were confirmed in tumors with low expression of miR-335. The 3′UTR of CDH11 was identified to be directly targeted by miR-335. Downregulation of miR-335 was also demonstrated in plasma samples from gastric cancer patients and inversely correlated with DNA methylation of promoter region (Z = 1.96, p = 0.029). DNA methylation, evaluated by methylation-specific PCR assay, was found in plasma from 23 (56.1%) out of 41 gastric cancer patients but in only 9 (30%) out of 30 healthy donors (p = 0.029, Pearson’s correlation). Taken in consideration, our results of the association with depth of invasion, lymph node metastasis, and poor prognosis together with functional assays on cell migration, invasion, and tumorigenicity are in accordance with the downregulation of miR-335 in gastric cancer.

Conclusions

Comprehensive evaluation of metastasis and invasion pathway identified a subset of associated genes and confirmed PLAUR and CDH11, both targets of miR-335, to be overexpressed in gastric cancer tissues. DNA methylation of miR-335 may be a promissory strategy for non-invasive approach to gastric cancer.

Electronic supplementary material

The online version of this article (10.1186/s13148-017-0413-8) contains supplementary material, which is available to authorized users.

CRISPR Genome Engineering for Human Pluripotent Stem Cell Research

The emergence of targeted and efficient genome editing technologies, such as repurposed bacterial programmable nucleases (e.g., CRISPR-Cas systems), has abetted the development of cell engineering approaches. Lessons learned from the development of RNA-interference (RNA-i) therapies can spur the translation of genome editing, such as those enabling the translation of human pluripotent stem cell engineering. In this review, we discuss the opportunities and the challenges of repurposing bacterial nucleases for genome editing, while appreciating their roles, primarily at the epigenomic granularity. First, we discuss the evolution of high-precision, genome editing technologies, highlighting CRISPR-Cas9. They exist in the form of programmable nucleases, engineered with sequence-specific localizing domains, and with the ability to revolutionize human stem cell technologies through precision targeting with greater on-target activities. Next, we highlight the major challenges that need to be met prior to bench-to-bedside translation, often learning from the path-to-clinic of complementary technologies, such as RNA-i. Finally, we suggest potential bioinformatics developments and CRISPR delivery vehicles that can be deployed to circumvent some of the challenges confronting genome editing technologies en route to the clinic.

Genome-scale identification of microRNA-related SNPs associated with risk of head and neck squamous cell carcinoma

Polymorphisms in microRNAs and their target sites can disrupt microRNA-dependent gene regulation, and have been associated with cancer susceptibility. However, genome-scale analyses of microRNA-related genetic variation in cancer are lacking. We tested the associations of ~40 000 common [minor allele frequency (MAF) ≥5%], microRNA-related single nucleotide polymorphisms (miR-SNPs), with risk of head and neck squamous cell carcinoma (HNSCC) in a discovery population, and validated selected loci in an independent population among a total of 2198 cases and 2180 controls. Joint analyses across the discovery and validation populations revealed six novel miR-SNP associations with risk of HNSCC. An upstream variant of MIR548H4 (rs7834169), replicated its association with overall HNSCC risk as well as risk of oral cavity cancer. Four other variants were specifically associated with oral cavity cancer risk (rs16914640, rs1134367, rs7306991 and rs1373756). 3'UTR variant of HADH, rs221347 and rs4975616, located within known cancer risk locus 5p15.33, were specific to risk of laryngeal cancer. High confidence predicted microRNA binding sites were identified for CLEC2D, LOC37443, KDM8 and HADH overlapping rs16914640, rs7306991, rs1134367 and rs221347, respectively. Furthermore, we identified several microRNA interactions with KDM8 and HADH predicted to be disrupted by genetic variation at rs1134367 and rs221347. These results suggest microRNA-related genetic variation may contribute to the genetic susceptibility of HNSCC, and that more powerful evaluation of this class of genetic variation and their relationship with cancer risk is warranted.

APOBEC signature mutation generates an oncogenic enhancer that drives LMO1 expression in T-ALL

Oncogenic driver mutations are those that provide a proliferative or survival advantage to neoplastic cells, resulting in clonal selection. Although most cancer-causing mutations have been detected in the protein-coding regions of the cancer genome; driver mutations have recently also been discovered within noncoding genomic sequences. Thus, a current challenge is to gain precise understanding of how these unique genomic elements function in cancer pathogenesis, while clarifying mechanisms of gene regulation and identifying new targets for therapeutic intervention. Here we report a C-to-T single nucleotide transition that occurs as a somatic mutation in noncoding sequences 4 kb upstream of the transcriptional start site of the LMO1 oncogene in primary samples from patients with T-cell acute lymphoblastic leukaemia. This single nucleotide alteration conforms to an APOBEC-like cytidine deaminase mutational signature, and generates a new binding site for the MYB transcription factor, leading to the formation of an aberrant transcriptional enhancer complex that drives high levels of expression of the LMO1 oncogene. Since APOBEC-signature mutations are common in a broad spectrum of human cancers, we suggest that noncoding nucleotide transitions such as the one described here may activate potent oncogenic enhancers not only in T-lymphoid cells but in other cell lineages as well.

Genetic susceptibility in childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy and a leading cause of death due to disease in children. The genetic basis of ALL susceptibility has been supported by its association with certain congenital disorders and, more recently, by several genome-wide association studies (GWAS). These GWAS identified common variants in ARID5B, IKZF1, CEBPE, CDKN2A, PIP4K2A, LHPP and ELK3 influencing ALL risk. However, the risk variants of these SNPs were not validated in all populations, suggesting that some of the loci could be population specific. On the other hand, the currently identified risk SNPs in these genes only account for 19% of the additive heritable risk. This estimation indicates that additional susceptibility variants could be discovered. In this review, we will provide an overview of the most important findings carried out in genetic susceptibility of childhood ALL in all GWAS and subsequent studies and we will also point to future directions that could be explored in the near future.

Functional assessment of CTCF sites at cytokine-sensing mammary enhancers using CRISPR/Cas9 gene editing in mice

The zinc finger protein CTCF has been invoked in establishing boundaries between genes, thereby controlling spatial and temporal enhancer activities. However, there is limited genetic evidence to support the concept that these boundaries restrict the search space of enhancers. We have addressed this question in the casein locus containing five mammary and two non-mammary genes under the control of at least seven putative enhancers. We have identified two CTCF binding sites flanking the locus and two associated with a super-enhancer. Individual deletion of these sites from the mouse genome did not alter expression of any of the genes. However, deletion of the border CTCF site separating the Csn1s1 mammary enhancer from neighboring genes resulted in the activation of Sult1d1 at a distance of more than 95 kb but not the more proximal and silent Sult1e1 gene. Loss of this CTCF site led to de novo interactions between the Sult1d1 promoter and several enhancers in the casein locus. Our study demonstrates that only one out of the four CTCF sites in the casein locus had a measurable in vivo activity. Studies on additional loci are needed to determine the biological role of CTCF sites associated with enhancers.

Identification of breast cancer associated variants that modulate transcription factor binding

Genome-wide association studies (GWAS) have discovered thousands loci associated with disease risk and quantitative traits, yet most of the variants responsible for risk remain uncharacterized. The majority of GWAS-identified loci are enriched for non-coding single-nucleotide polymorphisms (SNPs) and defining the molecular mechanism of risk is challenging. Many non-coding causal SNPs are hypothesized to alter transcription factor (TF) binding sites as the mechanism by which they affect organismal phenotypes. We employed an integrative genomics approach to identify candidate TF binding motifs that confer breast cancer-specific phenotypes identified by GWAS. We performed de novo motif analysis of regulatory elements, analyzed evolutionary conservation of identified motifs, and assayed TF footprinting data to identify sequence elements that recruit TFs and maintain chromatin landscape in breast cancer-relevant tissue and cell lines. We identified candidate causal SNPs that are predicted to alter TF binding within breast cancer-relevant regulatory regions that are in strong linkage disequilibrium with significantly associated GWAS SNPs. We confirm that the TFs bind with predicted allele-specific preferences using CTCF ChIP-seq data. We used The Cancer Genome Atlas breast cancer patient data to identify ANKLE1 and ZNF404 as the target genes of candidate TF binding site SNPs in the 19p13.11 and 19q13.31 GWAS-identified loci. These SNPs are associated with the expression of ZNF404 and ANKLE1 in breast tissue. This integrative analysis pipeline is a general framework to identify candidate causal variants within regulatory regions and TF binding sites that confer phenotypic variation and disease risk.

Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying "personal" gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genomes of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers. μ-cisTarget is available from http://mucistarget.aertslab.org .

Genetic polymorphisms of lncRNA-p53 regulatory network genes are associated with concurrent chemoradiotherapy toxicities and efficacy in nasopharyngeal carcinoma patients

The relevance of the transcription factor p53 in cancer is inarguable, and numerous lncRNAs are involved in the p53 regulatory network as either regulators or effectors, triggering a transcriptional response that causes either cell arrest or apoptosis following DNA damage in a p53-dependent manner. Despite the fact that the therapeutic response is improved in NPC, heterogeneity among people remains with regard to the susceptibility of adverse effects and the efficacy of treatments. Therefore, we analysed eight potentially functional SNPs of five genes in the lncRNA-p53 regulatory network in a discovery cohort of 505 NPC patients. By performing multivariate logistic regression, the impact of genetic variations on the efficacy and risk of CRT-induced toxicities was investigated. The most dramatic finding was that the MEG3 rs10132552 CC genotype had a greater than three-fold increased risk of developing grade 3-4 anaemia (OR = 3.001, 95%CI = 1.355-6.646, P = 0.007). Furthermore, the rs10132552 CT genotype had a better response to treatment (OR = 0.261, 95%CI = 0.089-0.770, P = 0.015). Individuals carrying LINC-ROR rs2027701 with one or two variant alleles had significant associations with a reduced risk of neutropaenia (OR = 0.503, 95%CI = 0.303-0.835, P = 0.008). In conclusion, our results suggested that genetic polymorphisms of the lncRNA-p53 regulatory network could play a potential role in reducing treatment-related toxicities and improving outcomes for NPC patients.

Integrative whole-genome sequence analysis reveals roles of regulatory mutations in BCL6 and BCL2 in follicular lymphoma

The contribution of mutations in regulatory regions to tumorigenesis has been the subject of many recent studies. We propose a new framework for integrative analysis of genome-wide sequencing data by considering diverse genetic information. This approach is applied to study follicular lymphoma (FL), a disease for which little is known about the contribution of regulatory gene mutations. Results from a test FL cohort revealed three novel highly recurrent regulatory mutation blocks near important genes implicated in FL, BCL6 and BCL2. Similar findings were detected in a validation FL cohort. We also found transcription factors (TF) whose binding may be disturbed by these mutations in FL: disruption of FOX TF family near the BCL6 promoter may result in reduced BCL6 expression, which then increases BCL2 expression over that caused by BCL2 gene translocation. Knockdown experiments of two TF hits (FOXD2 or FOXD3) were performed in human B lymphocytes verifying that they modulate BCL6/BCL2 according to the computationally predicted effects of the SNVs on TF binding. Overall, our proposed integrative analysis facilitates non-coding driver identification and the new findings may enhance the understanding of FL.

Polymorphisms in Non-coding RNA Genes and Their Targets Sites as Risk Factors of Sporadic Colorectal Cancer

Colorectal cancer (CRC) is a complex disease that develops as a consequence of both genetic and environmental risk factors in interplay with epigenetic mechanisms, such as microRNAs (miRNAs). CRC cases are predominantly sporadic in which the disease develops with no apparent hereditary syndrome. The last decade has seen the progress of genome-wide association studies (GWAS) that allowed the discovery of several genetic regions and variants associated with weak effects on sporadic CRC. Collectively these variants may enable a more accurate prediction of an individual's risk to the disease and its prognosis. However, the number of variants contributing to CRC is still not fully explored.SNPs in genes encoding the miRNA sequence or in 3'UTR regions of the corresponding binding sites may affect miRNA transcription, miRNA processing, and/or the fidelity of the miRNA-mRNA interaction. These variants could plausibly impact miRNA expression and target mRNA translation into proteins critical for cellular integrity, differentiation, and proliferation.In the present chapter, we describe the different aspects of variations related to miRNAs and other non-coding RNAs (ncRNAs) and evidence from studies investigating these candidate genetic alterations in support to their role in CRC development and progression.

Inherited determinants of early recurrent somatic mutations in prostate cancer

Prostate cancer is a highly heritable molecularly and clinically heterogeneous disease. To discover germline events involved in prostate cancer predisposition, we develop a computational approach to nominate heritable facilitators of somatic genomic events in the context of the androgen receptor signaling. Here, we use a ranking score and benign prostate transcriptomes to identify a non-coding polymorphic regulatory element at 7p14.3 that associates with DNA repair and hormone-regulated transcript levels and with an early recurrent prostate cancer-specific somatic mutation in the Speckle-Type POZ protein (SPOP) gene. The locus shows allele-specific activity that is concomitantly modulated by androgen receptor and by CCAAT/enhancer-binding protein (C/EBP) beta (CEBPB). Deletion of this locus via CRISPR-Cas9 leads to deregulation of the genes predicted to interact with the 7p14.3 locus by Hi-C chromosome conformation capture data. This study suggests that a polymorphism at 7p14.3 may predispose to SPOP mutant prostate cancer subclass through a hormone-dependent DNA damage response.

Prostate cancer is a heterogeneous disease, and many cases show somatic mutations of SPOP. Here, the authors show that a non-coding polymorphic regulatory element at 7p14.3 may predispose to SPOP mutant prostate cancer subclass through a hormone dependent DNA damage response.

Transcriptomics technologies

Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organism's genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organism's biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.