Recurrent somatic mutations in regulatory regions of human cancer genomes

Role of silent mutations in KRAS -mutant tumors

ABSTRACT

Silent mutations within the RAS  gene have garnered increasing attention for their potential roles in tumorigenesis and therapeutic strategies. Kirsten-RAS ( KRAS ) mutations, predominantly oncogenic, are pivotal drivers in various cancers. While extensive research has elucidated the molecular mechanisms and biological consequences of active KRAS  mutations, the functional significance of silent mutations remains relatively understudied. This review synthesizes current knowledge on KRAS  silent mutations, highlighting their impact on cancer development. Silent mutations, which do not alter protein sequences but can affect RNA stability and translational efficiency, pose intriguing questions regarding their contribution to tumor biology. Understanding these mutations is crucial for comprehensively unraveling KRAS -driven oncogenesis and exploring novel therapeutic avenues. Moreover, investigations into the clinical implications of silent mutations in KRAS -mutant tumors suggest potential diagnostic and therapeutic strategies. Despite being in early stages, research on KRAS  silent mutations holds promise for uncovering novel insights that could inform personalized cancer treatments. In conclusion, this review underscores the evolving landscape of KRAS  silent mutations, advocating for further exploration to bridge fundamental biology with clinical applications in oncology.

Identifying barriers and opportunities to facilitate the uptake of whole genome sequencing in paediatric haematology and oncology practice

BACKGROUND

The clinical utility of whole genome sequencing (WGS) in paediatric cancer has been demonstrated in recent years. WGS has been routinely available in the National Health Service (NHS) England for all children with cancer in England since 2021, but its uptake has been variable geographically. To explore the underlying barriers to routine use of WGS in this population across England and more widely in the United Kingdom (UK) and the Republic of Ireland (ROI), a one-day workshop was held in Cambridge, United Kingdom in October 2022.

METHODS

Following a series of talks, delegates participated in open, round-table discussions to outline local and broader challenges limiting routine WGS for diagnostic work-up for children with cancer in their Principal Treatment Centres (PTCs) and Genomic Laboratory Hubs (GLHs). Within smaller groups, delegates answered structured questions regarding clinical capability, education and training needs, and workforce competence and requirements. Data was recorded, centrally collated, and analysed following the event using thematic analysis.

RESULTS

Sixty participants attended the workshop with broad representation from the 20 PTCs across the UK and ROI and the seven GLHs in England. All healthcare professionals involved in the WGS pathway were represented, including paediatric oncologists, clinical geneticists, clinical scientists, and histopathologists. The main themes highlighted by the group in ensuring equitable access to WGS identified were: lack of knowledge equity between NHS trusts, with a perception of WGS being for research only; and perception of lack of financial support for the clinical process surrounding WGS, including lack of time to take informed consent from patients. The latter also included limited trained staff available for data interpretation, affecting the turnaround time for reporting. Finally, the need for an integrated digital pathway to order, track, and return data to clinicians was highlighted.

CONCLUSION

At the workshop, the general motivation for including WGS in the diagnostic work up for children with cancer was high throughout the UK, however a perceived lack of resources and education opportunities limit the widespread use of this commissioned assay. This workshop has led to some recommendations to increase access to WGS in this population in England and more widely in the devolved national of the UK and the ROI.

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes

BACKGROUND

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored.

METHODS

We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity.

RESULTS

We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers.

CONCLUSIONS

Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Benefits for children with suspected cancer from routine whole-genome sequencing

Clinical whole-genome sequencing (WGS) has been shown to deliver potential benefits to children with cancer and to alter treatment in high-risk patient groups. It remains unknown whether offering WGS to every child with suspected cancer can change patient management. We collected WGS variant calls and clinical and diagnostic information from 281 children (282 tumors) across two English units (n = 152 from a hematology center, n = 130 from a solid tumor center) where WGS had become a routine test. Our key finding was that variants uniquely attributable to WGS changed the management in ~7% (20 out of 282) of cases while providing additional disease-relevant findings, beyond standard-of-care molecular tests, in 108 instances for 83 (29%) cases. Furthermore, WGS faithfully reproduced every standard-of-care molecular test (n = 738) and revealed several previously unknown genomic features of childhood tumors. We show that WGS can be delivered as part of routine clinical care to children with suspected cancer and can change clinical management by delivering unexpected genomic insights. Our experience portrays WGS as a clinically impactful assay for routine practice, providing opportunities for assay consolidation and for delivery of molecularly informed patient care.

Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer

Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.

SIGNIFICANCE

Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.

Using evolutionary constraint to define novel candidate driver genes in medulloblastoma

Current knowledge of cancer genomics remains biased against noncoding mutations. To systematically search for regulatory noncoding mutations, we assessed mutations in conserved positions in the genome under the assumption that these are more likely to be functional than mutations in positions with low conservation. To this end, we use whole-genome sequencing data from the International Cancer Genome Consortium and combined it with evolutionary constraint inferred from 240 mammals, to identify genes enriched in noncoding constraint mutations (NCCMs), mutations likely to be regulatory in nature. We compare medulloblastoma (MB), which is malignant, to pilocytic astrocytoma (PA), a primarily benign tumor, and find highly different NCCM frequencies between the two, in agreement with the fact that malignant cancers tend to have more mutations. In PA, a high NCCM frequency only affects the BRAF locus, which is the most commonly mutated gene in PA. In contrast, in MB, >500 genes have high levels of NCCMs. Intriguingly, several loci with NCCMs in MB are associated with different ages of onset, such as the HOXB cluster in young MB patients. In adult patients, NCCMs occurred in, e.g., the WASF-2/AHDC1/FGR locus. One of these NCCMs led to increased expression of the SRC kinase FGR and augmented responsiveness of MB cells to dasatinib, a SRC kinase inhibitor. Our analysis thus points to different molecular pathways in different patient groups. These newly identified putative candidate driver mutations may aid in patient stratification in MB and could be valuable for future selection of personalized treatment options.

Tumour mutations in long noncoding RNAs enhance cell fitness

Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours. The resulting 54 mutated and positively-selected lncRNAs are significantly enriched for previously-reported cancer genes and a range of clinical and genomic features. A number of these lncRNAs promote tumour cell proliferation when overexpressed in in vitro models. Our results also highlight a dense SNV hotspot in the widely-studied NEAT1 oncogene. To directly evaluate the functional significance of NEAT1 SNVs, we use in cellulo mutagenesis to introduce tumour-like mutations in the gene and observe a significant and reproducible increase in cell fitness, both in vitro and in a mouse model. Mechanistic studies reveal that SNVs remodel the NEAT1 ribonucleoprotein and boost subnuclear paraspeckles. In summary, this work demonstrates the utility of driver analysis for mapping cancer-promoting lncRNAs, and provides experimental evidence that somatic mutations can act through lncRNAs to enhance pathological cancer cell fitness.

m6A-enriched lncRNA LINC00839 promotes tumor progression by enhancing TAF15-mediated transcription of amine oxidase AOC1 in nasopharyngeal carcinoma

Dysregulation of long non-coding RNAs (lncRNAs) contributes to tumorigenesis by modulating specific cancer-related pathways, but the roles of m6A-enriched lncRNAs and underlying mechanisms remain elusive in nasopharyngeal carcinoma (NPC). Here, we reanalyzed the previous genome-wide analysis of lncRNA profiles in 18 pairs of NPC and normal tissues, as well as in 10 paired samples from NPC with or without posttreatment metastases. We discerned that an oncogenic m6A-enriched lncRNA, LINC00839, which was substantially upregulated in NPC and correlated with poor clinical prognosis, promoted NPC growth and metastasis both in vitro and in vivo. Mechanistically, by using RNA pulldown assay combined with mass spectrometry, we found that LINC00839 interacted directly with the transcription factor, TATA-box binding protein associated factor (TAF15). Besides, ChIP and dual-luciferase report assays demonstrated that LINC00839 coordinated the recruitment of TAF15 to the promoter region of amine oxidase copper-containing 1 (AOC1), which encodes a secreted glycoprotein playing vital roles in various cancers, thereby activating AOC1 transcription in trans. In this study, potential effects of AOC1 in NPC progression were first proposed. Moreover, ectopic expression of AOC1 partially rescued the inhibitory effect of downregulation of LINC00839 in NPC. Furthermore, we showed that silencing vir-like m6A methyltransferase-associated (VIRMA) and insulin-like growth factor 2 mRNA-binding proteins 1 (IGF2BP1) attenuated the expression level and RNA stability of LINC00839 in an m6A-dependent manner. Taken together, our study unveils a novel oncogenic VIRMA/IGF2BP1-LINC00839-TAF15-AOC1 axis, and highlights the significance and prognostic value of LINC00839 expression in NPC carcinogenesis.

Genome-wide mapping of somatic mutation rates uncovers drivers of cancer

Identification of cancer driver mutations that confer a proliferative advantage is central to understanding cancer; however, searches have often been limited to protein-coding sequences and specific non-coding elements (for example, promoters) because of the challenge of modeling the highly variable somatic mutation rates observed across tumor genomes. Here we present Dig, a method to search for driver elements and mutations anywhere in the genome. We use deep neural networks to map cancer-specific mutation rates genome-wide at kilobase-scale resolution. These estimates are then refined to search for evidence of driver mutations under positive selection throughout the genome by comparing observed to expected mutation counts. We mapped mutation rates for 37 cancer types and applied these maps to identify putative drivers within intronic cryptic splice regions, 5' untranslated regions and infrequently mutated genes. Our high-resolution mutation rate maps, available for web-based exploration, are a resource to enable driver discovery genome-wide.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Recurrent noncoding somatic and germline WT1 variants converge to disrupt MYB binding in acute promyelocytic leukemia

Genetic alternations can occur at noncoding regions, but how they contribute to cancer pathogenesis is poorly understood. Here, we established a mutational landscape of cis-regulatory regions (CREs) in acute promyelocytic leukemia (APL) based on whole-genome sequencing analysis of paired tumor and germline samples from 24 patients and epigenetic profiling of 16 patients. Mutations occurring in CREs occur preferentially in active enhancers bound by the complex of master transcription factors in APL. Among significantly enriched mutated CREs, we found a recurrently mutated region located within the third intron of WT1, an essential regulator of normal and malignant hematopoiesis. Focusing on noncoding mutations within this WT1 intron, an analysis on 169 APL patients revealed that somatic mutations were clustered into a focal hotspot region, including one site identified as a germline polymorphism contributing to APL risk. Significantly decreased WT1 expression was observed in APL patients bearing somatic and/or germline noncoding WT1 variants. Furthermore, biallelic WT1 inactivation was recurrently found in APL patients with noncoding WT1 variants, which resulted in the complete loss of WT1. The high incidence of biallelic inactivation suggested the tumor suppressor activity of WT1 in APL. Mechanistically, noncoding WT1 variants disrupted MYB binding on chromatin and suppressed the enhancer activity and WT1 expression through destroying the chromatin looping formation. Our study highlights the important role of noncoding variants in the leukemogenesis of APL.

Fyn and Lyn gene polymorphisms impact the risk of thyroid cancer

Thyroid cancer is the most common malignancy of the endocrine glands, and during last couple of decades, its incidence has risen alarmingly, across the globe. Etiology of thyroid cancer is still debatable. There are a few worth mentioning risk factors which contribute to initiation of abnormalities in thyroid gland leading to cancer. Genetic instability is major risk factors in thyroid carcinogenesis. Among the genetic factors, the Src family of genes (Src, Yes1, Fyn and Lyn) have been implicated in many cancers but there is little data regarding the association of these (Src, Yes1, Fyn and Lyn) genes with thyroid carcinogenesis. Fyn and Lyn genes of Src family found engaged in proliferation, migration, invasion, angiogenesis, and metastasis in different cancers. This study was planned to examine the effect of Fyn and Lyn SNPs on thyroid cancer risk in Pakistani population in 500 patients and 500 controls. Three polymorphisms of Fyn gene (rs6916861, rs2182644 and rs12910) and three polymorphisms of Lyn gene (rs2668011, rs45587541 and rs45489500) were analyzed using Tetra-primer ARMS-PCR followed by DNA sequencing. SNP rs6916861 of Fyn gene mutant genotype (CC) showed statistically significant threefold increased risk of thyroid cancer (P < 0.0001). In case of rs2182644 of Fyn gene, mutant genotype (AA) indicated statistically significant 17-fold increased risk of thyroid cancer (P < 0.0001). Statistically significant threefold increased risk of thyroid cancer was observed in genotype AC (P < 0.0001) of Fyn gene polymorphism rs12910. In SNP rs2668011 of Lyn gene, TT genotype showed statistically significant threefold increased risk of thyroid cancer (P < 0.0001). In case of rs45587541 of Lyn gene, GA genotypes showed statistically significant 11-fold increased risk in thyroid cancer (P < 0.0001). Haplotype analysis revealed that AAATAG*, AGACAG*, AGCCAA*, AGCCAG*, CAATAG*, CGCCAG* and CGCCGA* haplotypes of Fyn and Lyn polymorphisms are associated with increased thyroid cancer risk. These results showed that genotypes and allele distribution of Fyn and Lyn are significantly linked with increased thyroid cancer risk and could be genetic adjuster for said disease.

Clinical utility of whole-genome sequencing in precision oncology

Precision diagnostics is one of the two pillars of precision medicine. Sequencing efforts in the past decade have firmly established cancer as a primarily genetically driven disease. This concept is supported by therapeutic successes aimed at particular pathways that are perturbed by specific driver mutations in protein-coding domains and reflected in three recent FDA tissue agnostic cancer drug approvals. In addition, there is increasing evidence from studies that interrogate the entire genome by whole-genome sequencing that acquired global and complex genomic aberrations including those in non-coding regions of the genome might also reflect clinical outcome. After addressing technical, logistical, financial and ethical challenges, national initiatives now aim to introduce clinical whole-genome sequencing into real-world diagnostics as a rational and potentially cost-effective tool for response prediction in cancer and to identify patients who would benefit most from 'expensive' targeted therapies and recruitment into clinical trials. However, so far, this has not been accompanied by a systematic and prospective evaluation of the clinical utility of whole-genome sequencing within clinical trials of uniformly treated patients of defined clinical outcome. This approach would also greatly facilitate novel predictive biomarker discovery and validation, ultimately reducing size and duration of clinical trials and cost of drug development. This manuscript is the third in a series of three to review and critically appraise the potential and challenges of clinical whole-genome sequencing in solid tumors and hematological malignancies.

FOXA1 in prostate cancer

Most prostate cancers initially respond to androgen deprivation therapy (ADT). With the long-term application of ADT, localized prostate cancer will progress to castration-resistant prostate cancer (CRPC), metastatic CRPC (mCRPC), and neuroendocrine prostate cancer (NEPC), and the transcriptional network shifted. Forkhead box protein A1 (FOXA1) may play a key role in this process through multiple mechanisms. To better understand the role of FOXA1 in prostate cancer, we review the interplay among FOXA1-targeted genes, modulators of FOXA1, and FOXA1 with a particular emphasis on androgen receptor (AR) function. Furthermore, we discuss the distinct role of FOXA1 mutations in prostate cancer and clinical significance of FOXA1. We summarize possible regulation pathways of FOXA1 in different stages of prostate cancer. We focus on links between FOXA1 and AR, which may play different roles in various types of prostate cancer. Finally, we discuss FOXA1 mutation and its clinical significance in prostate cancer. FOXA1 regulates the development of prostate cancer through various pathways, and it could be a biomarker for mCRPC and NEPC. Future efforts need to focus on mechanisms underlying mutation of FOXA1 in advanced prostate cancer. We believe that FOXA1 would be a prognostic marker and therapeutic target in prostate cancer.

Notch-dependent DNA cis-regulatory elements and their dose-dependent control of C. elegans stem cell self-renewal

A long-standing biological question is how DNA cis-regulatory elements shape transcriptional patterns during metazoan development. Reporter constructs, cell culture assays and computational modeling have made major contributions to answering this question, but analysis of elements in their natural context is an important complement. Here, we mutate Notch-dependent LAG-1 binding sites (LBSs) in the endogenous Caenorhabditis elegans sygl-1 gene, which encodes a key stem cell regulator, and analyze the consequences on sygl-1 expression (nascent transcripts, mRNA, protein) and stem cell maintenance. Mutation of one LBS in a three-element cluster approximately halved both expression and stem cell pool size, whereas mutation of two LBSs essentially abolished them. Heterozygous LBS mutant clusters provided intermediate values. Our results lead to two major conclusions. First, both LBS number and configuration impact cluster activity: LBSs act additively in trans and synergistically in cis. Second, the SYGL-1 gradient promotes self-renewal above its functional threshold and triggers differentiation below the threshold. Our approach of coupling CRISPR/Cas9 LBS mutations with effects on both molecular and biological readouts establishes a powerful model for in vivo analyses of DNA cis-regulatory elements.

High-resolution mapping demonstrates inhibition of DNA excision repair by transcription factors

DNA base damage arises frequently in living cells and needs to be removed by base excision repair (BER) to prevent mutagenesis and genome instability. Both the formation and repair of base damage occur in chromatin and are conceivably affected by DNA-binding proteins such as transcription factors (TFs). However, to what extent TF binding affects base damage distribution and BER in cells is unclear. Here, we used a genome-wide damage mapping method, N-methylpurine-sequencing (NMP-seq), and characterized alkylation damage distribution and BER at TF binding sites in yeast cells treated with the alkylating agent methyl methanesulfonate (MMS). Our data show that alkylation damage formation was mainly suppressed at the binding sites of yeast TFs ARS binding factor 1 (Abf1) and rDNA enhancer binding protein 1 (Reb1), but individual hotspots with elevated damage levels were also found. Additionally, Abf1 and Reb1 binding strongly inhibits BER in vivo and in vitro, causing slow repair both within the core motif and its adjacent DNA. Repair of ultraviolet (UV) damage by nucleotide excision repair (NER) was also inhibited by TF binding. Interestingly, TF binding inhibits a larger DNA region for NER relative to BER. The observed effects are caused by the TF–DNA interaction, because damage formation and BER can be restored by depletion of Abf1 or Reb1 protein from the nucleus. Thus, our data reveal that TF binding significantly modulates alkylation base damage formation and inhibits repair by the BER pathway. The interplay between base damage formation and BER may play an important role in affecting mutation frequency in gene regulatory regions.

Sequencing of BRCA1/2-alterations using NGS-based technology: annotation as a challenge

In this study, the molecular profile of different BRCA-associated tumor types was assessed with regard to the classification and annotation of detected BRCA1/2 variants. The aim was to establish guidelines in order to facilitate the interpretation of BRCA1/2 alterations in routine diagnostics. Annotation of detected variants was evaluated compared to background mutations found in normal tissue samples and manually reviewed according to distinct online databases. This retrospective study included 48 samples (45 tumors, three non-tumors), which were sequenced with the GeneReader (QIAGEN). Thereof ten samples were additionally analyzed with the Ion S5™ (Thermo Fisher) and 20 samples with the MiSeq™ (Illumina^®) to compare the different NGS devices, as well as the sequencing results and their quality. The analysis showed that the individual NGS platforms detected different numbers of BRCA1/2 alterations in the respective tumor sample. In addition, the GeneReader revealed variability in the detection and classification of pathogenic alterations within the platform itself as well as in comparison with the other platforms or online databases. The study concluded that the Ion S5™ in combination with the Oncomine™ Comprehensive Assay v3 is most recommendable for current and prospective requirements of molecular analysis in routine diagnostics. In addition to the two BRCA1/2 genes, a broad number of other genes (BRCAness genes and genes involved in the repair pathway) is covered by the panel, which may open up new treatment options for patients depending on the respective eligibility criteria.

The renal clear cell carcinoma immune landscape

A comprehensive evaluation of the clear cell renal cell carcinoma (ccRCC) immune landscape was found using 584 RNA-sequencing datasets from The Cancer Genome Atlas (TCGA), we identified 17 key dysregulated immune-associated genes in ccRCC based on association with clinical variables and important immune pathways. Of the numerous findings from our analyses, we found that several of the 17 key dysregulated genes are heavily involved in interleukin and NF-kB signaling and that somatic copy number alteration (SCNA) hotspots may be causally associated with gene dysregulation. More importantly, we also found that key immune-associated genes and pathways are strongly upregulated in ccRCC. Our study may lend novel insights into the clinical implications of immune dysregulation in ccRCC and suggests potential immunotherapeutic targets for further evaluation.

Cancer drivers and clonal dynamics in acute lymphoblastic leukaemia subtypes

To obtain a comprehensive picture of composite genetic driver events and clonal dynamics in subtypes of paediatric acute lymphoblastic leukaemia (ALL) we analysed tumour-normal whole genome sequencing and expression data from 361 newly diagnosed patients. We report the identification of both structural drivers, as well as recurrent non-coding variation in promoters. Additionally we found the transcriptional profile of histone gene cluster 1 and CTCF altered tumours shared hallmarks of hyperdiploid ALL suggesting a 'hyperdiploid like' subtype. ALL subtypes are driven by distinct mutational processes with AID mutagenesis being confined to ETV6-RUNX1 tumours. Subclonality is a ubiquitous feature of ALL, consistent with Darwinian evolution driving selection and expansion of tumours. Driver mutations in B-cell developmental genes (IKZF1, PAX5, ZEB2) tend to be clonal and RAS/RTK mutations subclonal. In addition to identifying new avenues for therapeutic exploitation, this analysis highlights that targeted therapies should take into account composite mutational profile and clonality.

Profiling chromatin accessibility in pediatric acute lymphoblastic leukemia identifies subtype-specific chromatin landscapes and gene regulatory networks

Acute lymphoblastic leukemia (ALL) is a hematopoietic malignancy comprised of molecular subtypes largely characterized by aneuploidy or recurring chromosomal rearrangements. Despite extensive information on the ALL transcriptome and methylome, there is limited understanding of the ALL chromatin landscape. We therefore mapped accessible chromatin in 24 primary ALL cell biospecimens comprising three common molecular subtypes (DUX4/ERG, ETV6-RUNX1 and hyperdiploid) from patients treated at St. Jude Children's Research Hospital. Our findings highlight extensive chromatin reprogramming in ALL, including the identification ALL subtype-specific chromatin landscapes that are additionally modulated by genetic variation. Chromatin accessibility differences between ALL and normal B-cells implicate the activation of B-cell repressed chromatin domains and detail the disruption of normal B-cell development in ALL. Among ALL subtypes, we uncovered roles for basic helix-loop-helix, homeodomain and activator protein 1 transcription factors in promoting subtype-specific chromatin accessibility and distinct gene regulatory networks. In addition to chromatin subtype-specificity, we further identified over 3500 DNA sequence variants that alter the ALL chromatin landscape and contribute to inter-individual variability in chromatin accessibility. Collectively, our data suggest that subtype-specific chromatin landscapes and gene regulatory networks impact ALL biology and contribute to transcriptomic differences among ALL subtypes.

Structural and functional analysis of somatic coding and UTR indels in breast and lung cancer genomes

Insertions and deletions (Indels) represent one of the major variation types in the human genome and have been implicated in diseases including cancer. To study the features of somatic indels in different cancer genomes, we investigated the indels from two large samples of cancer types: invasive breast carcinoma (BRCA) and lung adenocarcinoma (LUAD). Besides mapping somatic indels in both coding and untranslated regions (UTRs) from the cancer whole exome sequences, we investigated the overlap between these indels and transcription factor binding sites (TFBSs), the key elements for regulation of gene expression that have been found in both coding and non-coding sequences. Compared to the germline indels in healthy genomes, somatic indels contain more coding indels with higher than expected frame-shift (FS) indels in cancer genomes. LUAD has a higher ratio of deletions and higher coding and FS indel rates than BRCA. More importantly, these somatic indels in cancer genomes tend to locate in sequences with important functions, which can affect the core secondary structures of proteins and have a bigger overlap with predicted TFBSs in coding regions than the germline indels. The somatic CDS indels are also enriched in highly conserved nucleotides when compared with germline CDS indels.

Comprehensive characterization of somatic variants associated with intronic polyadenylation in human cancers

Somatic single nucleotide variants (SNVs) in cancer genome affect gene expression through various mechanisms depending on their genomic location. While somatic SNVs near canonical splice sites have been reported to cause abnormal splicing of cancer-related genes, whether these SNVs can affect gene expression through other mechanisms remains an open question. Here, we analyzed RNA sequencing and exome data from 4,998 cancer patients covering ten cancer types and identified 152 somatic SNVs near splice sites that were associated with abnormal intronic polyadenylation (IPA). IPA-associated somatic variants favored the localization near the donor splice sites compared to the acceptor splice sites. A proportion of SNV-associated IPA events overlapped with premature cleavage and polyadenylation events triggered by U1 small nuclear ribonucleoproteins (snRNP) inhibition. GC content, intron length and polyadenylation signal were three genomic features that differentiated between SNV-associated IPA and intron retention. Notably, IPA-associated SNVs were enriched in tumor suppressor genes (TSGs), including the well-known TSGs such as PTEN and CDH1 with recurrent SNV-associated IPA events. Minigene assay confirmed that SNVs from PTEN, CDH1, VEGFA, GRHL2, CUL3 and WWC2 could lead to IPA. This work reveals that IPA acts as a novel mechanism explaining the functional consequence of somatic SNVs in human cancer.

Unique somatic variants in DNA from urine exosomes of individuals with bladder cancer

Bladder cancer (BC), a heterogeneous disease characterized by high recurrence rates, is diagnosed and monitored by cystoscopy. Accurate clinical staging based on biopsy remains a challenge, and additional, objective diagnostic tools are needed urgently. We used exosomal DNA (exoDNA) as an analyte to examine cancer-associated mutations and compared the diagnostic utility of exoDNA from urine and serum of individuals with BC. In contrast to urine exosomes from healthy individuals, urine exosomes from individuals with BC contained significant amounts of DNA. Whole-exome sequencing of DNA from matched urine and serum exosomes, bladder tumors, and normal tissue (peripheral blood mononuclear cells) identified exonic and 3' UTR variants in frequently mutated genes in BC, detectable in urine exoDNA and matched tumor samples. Further analyses identified somatic variants in driver genes, unique to urine exoDNA, possibly because of the inherent intra-tumoral heterogeneity of BC, which is not fully represented in random small biopsies. Multiple variants were also found in untranslated portions of the genome, such as microRNA (miRNA)-binding regions of the KRAS gene. Gene network analyses revealed that exoDNA is associated with cancer, inflammation, and immunity in BC exosomes. Our findings show utility of exoDNA as an objective, non-invasive strategy to identify novel biomarkers and targets for BC.

Estimating the predictive power of silent mutations on cancer classification and prognosis

In recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.

Functional annotation of noncoding mutations in cancer

Recurrent regulatory mutations affecting transcription factor binding sites in 2,500 cancer samples.

In a cancer genome, the noncoding sequence contains the vast majority of somatic mutations. While very few are expected to be cancer drivers, those affecting regulatory elements have the potential to have downstream effects on gene regulation that may contribute to cancer progression. To prioritize regulatory mutations, we screened somatic mutations in the Pan-Cancer Analysis of Whole Genomes cohort of 2,515 cancer genomes on individual bases to assess their potential regulatory roles in their respective cancer types. We found a highly significant enrichment of regulatory mutations associated with the deamination signature overlapping a CpG site in the CCAAT/Enhancer Binding Protein β recognition sites in many cancer types. Overall, 5,749 mutated regulatory elements were identified in 1,844 tumor samples from 39 cohorts containing 11,962 candidate regulatory mutations. Our analysis indicated 20 or more regulatory mutations in 5.5% of the samples, and an overall average of six per tumor. Several recurrent elements were identified, and major cancer-related pathways were significantly enriched for genes nearby the mutated regulatory elements. Our results provide a detailed view of the role of regulatory elements in cancer genomes.

Tumor Mutational Burden as a Potential Biomarker for Immunotherapy in Pancreatic Cancer: Systematic Review and Still-Open Questions

Tumor mutational burden (TMB) is a numeric index that expresses the number of mutations per megabase (muts/Mb) harbored by tumor cells in a neoplasm. TMB can be determined using different approaches based on next-generation sequencing. In the case of high values, it indicates a potential response to immunotherapy. In this systematic review, we assessed the potential predictive role of high-TMB in pancreatic ductal adenocarcinoma (PDAC), as well as the histo-molecular features of high-TMB PDAC. High-TMB appeared as a rare but not-negligible molecular feature in PDAC, being present in about 1.1% of cases. This genetic condition was closely associated with mucinous/colloid and medullary histology (p < 0.01). PDAC with high-TMB frequently harbored other actionable alterations, with microsatellite instability/defective mismatch repair as the most common. Immunotherapy has shown promising results in high-TMB PDAC, but the sample size of high-TMB PDAC treated so far is quite small. This study highlights interesting peculiarities of PDAC harboring high-TMB and may represent a reliable starting point for the assessment of TMB in the clinical management of patients affected by pancreatic cancer.

Enhanced C/EBP binding to G·T mismatches facilitates fixation of CpG mutations in cancer and adult stem cells

Somatic mutations in regulatory sites of human stem cells affect cell identity or cause malignant transformation. By mining the human genome for co-occurrence of mutations and transcription factor binding sites, we show that C/EBP binding sites are strongly enriched with [C > T]G mutations in cancer and adult stem cells, which is of special interest because C/EBPs regulate cell fate and differentiation. In vitro protein-DNA binding assay and structural modeling of the CEBPB-DNA complex show that the G·T mismatch in the core CG dinucleotide strongly enhances affinity of the binding site. We conclude that enhanced binding of C/EBPs shields CpG·TpG mismatches from DNA repair, leading to selective accumulation of [C > T]G mutations and consequent deterioration of the binding sites. This mechanism of targeted mutagenesis highlights the effect of a mutational process on certain regulatory sites and reveals the molecular basis of putative regulatory alterations in stem cells.

eNEMAL, an enhancer RNA transcribed from a distal MALAT1 enhancer, promotes NEAT1 long isoform expression

Emerging evidence has shown that active enhancers are abundantly transcribed, generating long non-coding RNAs, called enhancer RNAs (eRNAs). While putative eRNAs are often observed from RNA sequencing, the roles of most eRNAs remain largely unknown. Previously, we identified putative enhancer regions at the MALAT1 locus that form chromatin-chromatin interactions under hypoxia, and one of these enhancers is located about 30 kb downstream of the NEAT1 gene and -20 kb upstream of the MALAT1 gene (MALAT1–20 kb enhancer). Here, we report that a novel eRNA, named eRNA of the NEAT1-MALAT1-Locus (eNEMAL), is transcribed from the MALAT1–20 kb enhancer and conserved in primates. We found that eNEMAL is upregulated in response to hypoxia in multiple breast cancer cell lines, but not in non-tumorigenic MCF10A cells. Overexpression and knockdown of eNEMAL revealed that alteration of eNEMAL level does not affect MALAT1 expression. Instead, we found that eNEMAL upregulates the long isoform of NEAT1 (NEAT1_2) without increasing the total NEAT1 transcript level in MCF7 breast cancer cells, suggesting that eNEMAL has a repressive effect on the 3’-end polyadenylation process required for generating the short isoform of NEAT1 (NEAT1_1). Altogether, we demonstrated that an eRNA transcribed from a MALAT1 enhancer regulates NEAT1 isoform expression, implicating the MALAT1–20 kb enhancer and its transcript eNEMAL in co-regulation of MALAT1 and NEAT1 in response to hypoxia in breast cancer cells.

Transcriptional dysregulation by aberrant enhancer activation and rewiring in cancer

Cell identity is controlled by regulatory elements, such as promoters, enhancers, and insulators, within the genome. These regulatory elements interact in the nucleus and form tissue‐specific chromatin structures. Dysregulation of these elements and their interactions can lead to loss of cell identity and promote the development of diseases such as cancer. Tumor cells acquire aberrantly activated enhancers at oncogenic driver genes through various mechanisms. Small genomic changes such as mutations, insertions, and amplifications can form aberrant enhancers. Genomic rearrangements at the chromosomal level, including translocations and inversions, are also often observed in cancers. These rearrangements can result in repositioning of enhancers to locations near tumor‐type‐specific oncogenes. Chromatin structural changes caused by genomic or epigenomic changes lead to mis‐interaction between enhancers and proto‐oncogenes, ultimately contributing to tumorigenesis through activation of oncogenic signals. Additional epigenomic mechanisms can also cause aberrant enhancer activation, including those associated with overexpression of oncogenic transcription factors and the mutation of transcriptional cofactors. Exogenous viral DNA can also lead to enhancer aberrations. Here, we review the mechanisms underlying aberrant oncogene activation through enhancer activation and rewiring, both of which are caused by genomic or epigenomic alterations in non‐coding regions.

Insight Into Chromatin-Enriched RNA: A Key Chromatin Regulator in Tumors

Chromatin-enriched RNAs (cheRNAs) constitute a special class of long noncoding RNAs (lncRNAs) that are enriched around chromatin and function to activate neighboring or distal gene transcription. Recent studies have shown that cheRNAs affect chromatin structure and gene expression by recruiting chromatin modifiers or acting as bridges between distal enhancers and promoters. The abnormal transcription of cheRNAs plays an important role in the occurrence of many diseases, particularly tumors. The critical effect of cancer stem cells (CSCs) on the formation and development of tumors is well known, but the function of cheRNAs in tumorigenesis, especially in CSC proliferation and stemness maintenance, is not yet fully understood. This review focuses on the mechanisms of cheRNAs in epigenetic regulation and chromatin conformation and discusses the way cheRNAs function in CSCs to deepen the understanding of tumorigenesis and provide novel insight to advance tumor-targeting therapy.

Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis-regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%-20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.

Clonal expansion in non-cancer tissues

Cancer is a clonal disorder derived from a single ancestor cell and its progenies that are positively selected by acquisition of 'driver mutations'. However, the evolution of positively selected clones does not necessarily imply the presence of cancer. On the contrary, it has become clear that expansion of these clones in phenotypically normal or non-cancer tissues is commonly seen in association with ageing and/or in response to environmental insults and chronic inflammation. Recent studies have reported expansion of clones harbouring mutations in cancer driver genes in the blood, skin, oesophagus, bronchus, liver, endometrium and bladder, where the expansion could be so extensive that tissues undergo remodelling of an almost entire tissue. The presence of common cancer driver mutations in normal tissues suggests a strong link to cancer development, providing an opportunity to understand early carcinogenic processes. Nevertheless, some driver mutations are unique to normal tissues or have a mutation frequency that is much higher in normal tissue than in cancer, indicating that the respective clones may not necessarily be destined for evolution to cancer but even negatively selected for carcinogenesis depending on the mutated gene. Moreover, tissues that are remodelled by genetically altered clones might define functionalities of aged tissues or modified inflammatory processes. In this Review, we provide an overview of major findings on clonal expansion in phenotypically normal or non-cancer tissues and discuss their biological significance not only in cancer development but also in ageing and inflammatory diseases.

Enhancer pleiotropy, gene expression, and the architecture of human enhancer-gene interactions

Enhancers are often studied as noncoding regulatory elements that modulate the precise spatiotemporal expression of genes in a highly tissue-specific manner. This paradigm has been challenged by recent evidence of individual enhancers acting in multiple tissues or developmental contexts. However, the frequency of these enhancers with high degrees of “pleiotropy” out of all putative enhancers is not well understood. Consequently, it is unclear how the variation of enhancer pleiotropy corresponds to the variation in expression breadth of target genes. Here, we use multi-tissue chromatin maps from diverse human tissues to investigate the enhancer–gene interaction architecture while accounting for 1) the distribution of enhancer pleiotropy, 2) the variations of regulatory links from enhancers to target genes, and 3) the expression breadth of target genes. We show that most enhancers are tissue-specific and that highly pleiotropy enhancers account for <1% of all putative regulatory sequences in the human genome. Notably, several genomic features are indicative of increasing enhancer pleiotropy, including longer sequence length, greater number of links to genes, increasing abundance and diversity of encoded transcription factor motifs, and stronger evolutionary conservation. Intriguingly, the number of enhancers per gene remains remarkably consistent for all genes (∼14). However, enhancer pleiotropy does not directly translate to the expression breadth of target genes. We further present a series of Gaussian Mixture Models to represent this organization architecture. Consequently, we demonstrate that a modest trend of more pleiotropic enhancers targeting more broadly expressed genes can generate the observed diversity of expression breadths in the human genome.

Cis-regulatory mutations with driver hallmarks in major cancers

Despite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants remains challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, genetic data, and allele-specific gene expression from TCGA, we identified 320 somatic non-coding mutations that affect gene expression in cis (FDR<0.25). These mutations cluster into 47 cis-regulatory elements that modulate expression of their subject genes through diverse molecular mechanisms. We further show that these mutations have hallmark features of non-coding drivers; namely, that they preferentially disrupt transcription factor binding motifs, are associated with a selective advantage, increased oncogene expression and decreased tumor suppressor expression.

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Enrichment of functional non-coding somatic mutations predicts drivers

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Elevated variant allele frequencies are consistent with roles in tumorigenesis

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Putative non-coding drivers disrupt transcription factor binding motifs

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Predicted drivers associate with increased oncogene and decreased TSG expression

Pan-cancer noncoding genomic analysis identifies functional CDC20 promoter mutation hotspots

Noncoding DNA sequences occupy more than 98% of the human genome; however, few cancer noncoding drivers have been identified compared with cancer coding drivers, probably because cancer noncoding drivers have a distinct mutation pattern due to the distinct function of noncoding DNA. Here we performed pan-cancer whole genome mutation analysis to screen for functional noncoding mutations that influence protein factor binding. Recurrent mutations were identified in the promoter of CDC20 gene. These CDC20 promoter hotspot mutations disrupt the binding of ELK4 transcription repressor, lead to the up-regulation of CDC20 transcription. Physiologically ELK4 binds to the unmutated hotspot sites and is involved in DNA damage-induced CDC20 transcriptional repression. Overall, our study not only identifies a detailed mechanism for CDC20 gene deregulation in human cancers but also finds functional noncoding genetic alterations, with implications for the further development of function-based noncoding driver discovery pipelines.

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Pan-cancer noncoding analysis for mutations that influence protein factor binding

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Recurrent mutations were identified in the promoter of CDC20 gene

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Promoter hotspot mutations disrupt ELK4 binding, up-regulate CDC20 transcription

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Promoter hotspot mutation site is involved in DNA damage-induced CDC20 repression

The Implications of ncRNAs in the Development of Human Diseases

The mammalian genome comprehends a small minority of genes that encode for proteins (barely 2% of the total genome in humans) and an immense majority of genes that are transcribed into RNA but not encoded for proteins (ncRNAs). These non-coding genes are intimately related to the expression regulation of protein-coding genes. The ncRNAs subtypes differ in their size, so there are long non-coding genes (lncRNAs) and other smaller ones, like microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs). Due to their important role in the maintenance of cellular functioning, any deregulation of the expression profiles of these ncRNAs can dissemble in the development of different types of diseases. Among them, we can highlight some of high incidence in the population, such as cancer, neurodegenerative, or cardiovascular disorders. In addition, thanks to the enormous advances in the field of medical genomics, these same ncRNAs are starting to be used as possible drugs, approved by the FDA, as an effective treatment for diseases.

Information Theory Can Help Quantify the Potential of New Phenotypes to Originate as Exaptations

Exaptations are adaptive traits that do not originate de novo but from other adaptive traits. They include complex macroscopic traits, such as the middle ear bones of mammals, which originated from reptile jaw bones, but also molecular traits, such as new binding sites of transcriptional regulators. What determines whether a trait originates de novo or as an exaptation is unknown. I here use simple information theoretic concepts to quantify a molecular phenotype’s potential to give rise to new phenotypes. These quantities rely on the amount of genetic information needed to encode a phenotype. I use these quantities to estimate the propensity of new transcription factor binding phenotypes to emerge de novo or exaptively, and do so for 187 mouse transcription factors. I also use them to quantify whether an organism’s viability in one of 10 different chemical environment is likely to arise exaptively. I show that informationally expensive traits are more likely to originate exaptively. Exaptive evolution is only sometimes favored for new transcription factor binding, but it is always favored for the informationally complex metabolic phenotypes I consider. As our ability to genotype evolving populations increases, so will our ability to understand how phenotypes of ever-increasing informational complexity originate in evolution.

NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis

Background

Identifying frequently mutated regions is a key approach to discover DNA elements influencing cancer progression. However, it is challenging to identify these burdened regions due to mutation rate heterogeneity across the genome and across different individuals. Moreover, it is known that this heterogeneity partially stems from genomic confounding factors, such as replication timing and chromatin organization. The increasing availability of cancer whole genome sequences and functional genomics data from the Encyclopedia of DNA Elements (ENCODE) may help address these issues.

Results

We developed a negative binomial regression-based Integrative Method for mutation Burden analysiS (NIMBus). Our approach addresses the over-dispersion of mutation count statistics by (1) using a Gamma–Poisson mixture model to capture the mutation-rate heterogeneity across different individuals and (2) estimating regional background mutation rates by regressing the varying local mutation counts against genomic features extracted from ENCODE. We applied NIMBus to whole-genome cancer sequences from the PanCancer Analysis of Whole Genomes project (PCAWG) and other cohorts. It successfully identified well-known coding and noncoding drivers, such as TP53 and the TERT promoter. To further characterize the burdening of non-coding regions, we used NIMBus to screen transcription factor binding sites in promoter regions that intersect DNase I hypersensitive sites (DHSs). This analysis identified mutational hotspots that potentially disrupt gene regulatory networks in cancer. We also compare this method to other mutation burden analysis methods.

Conclusion

NIMBus is a powerful tool to identify mutational hotspots. The NIMBus software and results are available as an online resource at github.gersteinlab.org/nimbus.

Computational methods for detecting cancer hotspots

Cancer mutations that are recurrently observed among patients are known as hotspots. Hotspots are highly relevant because they are, presumably, likely functional. Known hotspots in BRAF, PIK3CA, TP53, KRAS, IDH1 support this idea. However, hundreds of hotspots have never been validated experimentally. The detection of hotspots nevertheless is challenging because background mutations obscure their statistical and computational identification. Although several algorithms have been applied to identify hotspots, they have not been reviewed before. Thus, in this mini-review, we summarize more than 40 computational methods applied to detect cancer hotspots in coding and non-coding DNA. We first organize the methods in cluster-based, 3D, position-specific, and miscellaneous to provide a general overview. Then, we describe their embed procedures, implementations, variations, and differences. Finally, we discuss some advantages, provide some ideas for future developments, and mention opportunities such as application to viral integrations, translocations, and epigenetics.

Discovery of driver non-coding splice-site-creating mutations in cancer

Non-coding mutations can create splice sites, however the true extent of how such somatic non-coding mutations affect RNA splicing are largely unexplored. Here we use the MiSplice pipeline to analyze 783 cancer cases with WGS data and 9494 cases with WES data, discovering 562 non-coding mutations that lead to splicing alterations. Notably, most of these mutations create new exons. Introns associated with new exon creation are significantly larger than the genome-wide average intron size. We find that some mutation-induced splicing alterations are located in genes important in tumorigenesis (ATRX, BCOR, CDKN2B, MAP3K1, MAP3K4, MDM2, SMAD4, STK11, TP53 etc.), often leading to truncated proteins and affecting gene expression. The pattern emerging from these exon-creating mutations suggests that splice sites created by non-coding mutations interact with pre-existing potential splice sites that originally lacked a suitable splicing pair to induce new exon formation. Our study suggests the importance of investigating biological and clinical consequences of noncoding splice-inducing mutations that were previously neglected by conventional annotation pipelines. MiSplice will be useful for automatically annotating the splicing impact of coding and non-coding mutations in future large-scale analyses.

LncRNAs as tumor cell intrinsic factors that affect cancer immunotherapy

Long noncoding RNAs (lncRNAs) have been found to associate with all major types of malignancies and play important roles in regulating several hallmarks of cancer by interacting with proteins, DNA, and RNA. The possible functions of lncRNAs and their roles in the regulation of tumour growth will be reported and discussed in the present review. In our recent report, based on genetic mice models and a series of systematic analyses, we suggested that lncRNAs also play critical roles in the regulation of antigen presentation in tumour cells and allow tumour cells to escape immune surveillance, which further broadens the scope of understanding lncRNA functions and how they relate to cancer immunotherapy resistance.

Prediction of genome-wide effects of single nucleotide variants on transcription factor binding

Single nucleotide variants (SNVs) located in transcriptional regulatory regions can result in gene expression changes that lead to adaptive or detrimental phenotypic outcomes. Here, we predict gain or loss of binding sites for 741 transcription factors (TFs) across the human genome. We calculated ‘gainability’ and ‘disruptability’ scores for each TF that represent the likelihood of binding sites being created or disrupted, respectively. We found that functional cis-eQTL SNVs are more likely to alter TF binding sites than rare SNVs in the human population. In addition, we show that cancer somatic mutations have different effects on TF binding sites from different TF families on a cancer-type basis. Finally, we discuss the relationship between these results and cancer mutational signatures. Altogether, we provide a blueprint to study the impact of SNVs derived from genetic variation or disease association on TF binding to gene regulatory regions.

An enhanced genetic model of relapsed IGH-translocated multiple myeloma evolutionary dynamics

Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 IGH-translocated tumour-normal newly diagnosed pairs and 24 matched relapsed tumours from the Myeloma XI trial. We identify multiple events as potentially important for survival and therapy-resistance at relapse including driver point mutations (e.g., TET2), translocations (MAP3K14), lengthened telomeres, and increased genomic instability (e.g., 17p deletions). Despite heterogeneous mutational processes contributing to relapsed mutations across MM subtypes, increased AID/APOBEC activity is particularly associated with shorter progression time to relapse, and contributes to higher mutational burden at relapse. In addition, we identify three enhanced major clonal evolution patterns of MM relapse, independent of treatment strategies and molecular karyotypes, questioning the viability of "evolutionary herding" approach in treating drug-resistant MM. Our data show that MM relapse is associated with acquisition of new mutations and clonal selection, and suggest APOBEC enzymes among potential targets for therapy-resistant MM.

Insights into the New Cancer Therapy through Redox Homeostasis and Metabolic Shifts

Modest levels of reactive oxygen species (ROS) are necessary for intracellular signaling, cell division, and enzyme activation. These ROS are later eliminated by the body’s antioxidant defense system. High amounts of ROS cause carcinogenesis by altering the signaling pathways associated with metabolism, proliferation, metastasis, and cell survival. Cancer cells exhibit enhanced ATP production and high ROS levels, which allow them to maintain elevated proliferation through metabolic reprograming. In order to prevent further ROS generation, cancer cells rely on more glycolysis to produce ATP and on the pentose phosphate pathway to provide NADPH. Pro-oxidant therapy can induce more ROS generation beyond the physiologic thresholds in cancer cells. Alternatively, antioxidant therapy can protect normal cells by activating cell survival signaling cascades, such as the nuclear factor erythroid 2-related factor 2 (Nrf2)-Kelch-like ECH-associated protein 1 (Keap1) pathway, in response to radio- and chemotherapeutic drugs. Nrf2 is a key regulator that protects cells from oxidative stress. Under normal conditions, Nrf2 is tightly bound to Keap1 and is ubiquitinated and degraded by the proteasome. However, under oxidative stress, or when treated with Nrf2 activators, Nrf2 is liberated from the Nrf2-Keap1 complex, translocated into the nucleus, and bound to the antioxidant response element in association with other factors. This cascade results in the expression of detoxifying enzymes, including NADH-quinone oxidoreductase 1 (NQO1) and heme oxygenase 1. NQO1 and cytochrome b5 reductase can neutralize ROS in the plasma membrane and induce a high NAD⁺/NADH ratio, which then activates SIRT1 and mitochondrial bioenergetics. NQO1 can also stabilize the tumor suppressor p53. Given their roles in cancer pathogenesis, redox homeostasis and the metabolic shift from glycolysis to oxidative phosphorylation (through activation of Nrf2 and NQO1) seem to be good targets for cancer therapy. Therefore, Nrf2 modulation and NQO1 stimulation could be important therapeutic targets for cancer prevention and treatment.

Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X

We developed cis-X, a computational method for discovering regulatory noncoding variants in cancer by integrating whole-genome and transcriptome sequencing data from a single cancer sample. cis-X first finds aberrantly cis-activated genes that exhibit allele-specific expression accompanied by an elevated outlier expression. It then searches for causal noncoding variants that may introduce aberrant transcription factor binding motifs or enhancer hijacking by structural variations. Analysis of 13 T-lineage acute lymphoblastic leukemias identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by chromatin immunoprecipitation sequencing of a patient-derived xenograft. Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion that removes a CTCF-insulated neighborhood boundary. cis-X may be applied to pediatric and adult solid tumors that are aneuploid and heterogeneous. In contrast to existing approaches, which require large sample cohorts, cis-X enables the discovery of regulatory noncoding variants in individual cancer genomes.

An Overview of Non-coding RNAs and Cardiovascular System

Cardiovascular disease management and timely diagnosis remain a major dilemma. Delineating molecular mechanisms of cardiovascular diseases is opening horizon in the field of molecular medicines and in the development of early diagnostic markers. Non-coding RNAs are the highly functional and vibrant nucleic acids and are known to be involved in the regulation of endothelial cells, vascular and smooth muscles cells, cardiac metabolism, ischemia, inflammation and many processes in cardiovascular system. This chapter is comprehensively focusing on the overview of the non-coding RNAs including their discovery, generation, classification and functional regulation. In addition, overview regarding different non-coding RNAs as long non-coding, siRNAs and miRNAs involvement in the cardiovascular diseases is also addressed. Detailed functional analysis of this vast group of highly regulatory molecules will be promising for shaping future drug discoveries.

Integration of single-cell multi-omics for gene regulatory network inference

The advancement of single-cell sequencing technology in recent years has provided an opportunity to reconstruct gene regulatory networks (GRNs) with the data from thousands of single cells in one sample. This uncovers regulatory interactions in cells and speeds up the discoveries of regulatory mechanisms in diseases and biological processes. Therefore, more methods have been proposed to reconstruct GRNs using single-cell sequencing data. In this review, we introduce technologies for sequencing single-cell genome, transcriptome, and epigenome. At the same time, we present an overview of current GRN reconstruction strategies utilizing different single-cell sequencing data. Bioinformatics tools were grouped by their input data type and mathematical principles for reader's convenience, and the fundamental mathematics inherent in each group will be discussed. Furthermore, the adaptabilities and limitations of these different methods will also be summarized and compared, with the hope to facilitate researchers recognizing the most suitable tools for them.