Advances in multi-omics datasets and analytical methods have revolutionized cancer research, offering a comprehensive, pan-cancer perspective. Pan-cancer studies identify shared mechanisms and unique traits across different cancer types, which are reshaping diagnostic and treatment strategies. However, continued innovation is required to refine these approaches and deepen our understanding of cancer biology and medicine. This review summarized key findings from pan-cancer research and  explored their potential to drive future advancements in oncology.

A major goal of cancer biology is to understand the mechanisms driven by somatically acquired mutations. Two distinct methodologies-one analyzing mutation clustering within protein sequences and 3D structures, the other leveraging protein-protein interaction network topology-offer complementary strengths. We present NetFlow3D, a unified, end-to-end 3D structurally-informed protein interaction network propagation framework that maps the multiscale mechanistic effects of mutations. Built upon the Human Protein Structurome, which incorporates the 3D structures of every protein and the binding interfaces of all known protein interactions, NetFlow3D integrates atomic, residue, protein and network-level information: It clusters mutations on 3D protein structures to identify driver mutations and propagates their impacts anisotropically across the protein interaction network, guided by the involved interaction interfaces, to reveal systems-level impacts. Applied to 33 cancer types, NetFlow3D identifies 2 times more 3D clusters and incorporates 8 times more proteins in significantly interconnected network modules compared to traditional methods.

Non-coding mutations in the TERT promoter (TERTp), typically at one of two bases -124 and -146 bp upstream of the start codon, are among the most prevalent driver mutations in human cancer. Several additional recurrent TERTp mutations have been reported but their functions and origins remain largely unexplained. Here, we show that atypical TERTp mutations arise secondary to canonical TERTp mutations in a two-step process. Canonical TERTp mutations create de novo binding sites for ETS family transcription factors that induce favourable conditions for DNA damage formation by UV light, thus creating a hotspot effect but only after a first mutational hit. In agreement, atypical TERTp mutations co-occur with canonical driver mutations in large cancer cohorts and arise subclonally specifically on the TERTp driver mutant chromosome homolog of melanoma cells treated with UV light in vitro. Our study gives an in-depth view of TERTp mutations in cancer and provides a mechanistic explanation for atypical TERTp mutations.

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.

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.

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.

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.

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.

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.

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.

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.

A major goal of cancer biology is to understand the mechanisms underlying tumorigenesis driven by somatically acquired mutations. Two distinct types of computational methodologies have emerged: one focuses on analyzing clustering of mutations within protein sequences and 3D structures, while the other characterizes mutations by leveraging the topology of protein-protein interaction network. Their insights are largely non-overlapping, offering complementary strengths. Here, we established a unified, end-to-end 3D structurally-informed protein interaction network propagation framework, NetFlow3D, that systematically maps the multiscale mechanistic effects of somatic mutations in cancer. The establishment of NetFlow3D hinges upon the Human Protein Structurome, a comprehensive repository we compiled that incorporates the 3D structures of every single protein as well as the binding interfaces of all known protein interactions in humans. NetFlow3D leverages the Structurome to integrate information across atomic, residue, protein and network levels: It conducts 3D clustering of mutations across atomic and residue levels on protein structures to identify potential driver mutations. It then anisotropically propagates their impacts across the protein interaction network, with propagation guided by the specific 3D structural interfaces involved, to identify significantly interconnected network "modules", thereby uncovering key biological processes underlying disease etiology. Applied to 1,038,899 somatic protein-altering mutations in 9,946 TCGA tumors across 33 cancer types, NetFlow3D identified 1,4444 significant 3D clusters throughout the Human Protein Structurome, of which ~55% would not have been found if using only experimentally-determined structures. It then identified 26 significantly interconnected modules that encompass ~8-fold more proteins than applying standard network analyses. NetFlow3D and our pan-cancer results can be accessed from http://netflow3d.yulab.org.

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.

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

The TERT gene encodes the reverse transcriptase subunit of telomerase and is normally transcriptionally suppressed in differentiated human cells but reactivated in cancers where its expression is frequently associated with poor survival prognosis. Here we experimentally assessed the RNA sequencing expression patterns associated with TERT transcription in 1039 human cancer samples of 27 tumor types. We observed a bimodal distribution of TERT expression where ∼27% of cancer samples did not express TERT and the rest showed a bell-shaped distribution. Expression of TERT strongly correlated with 1443 human genes including 103 encoding transcriptional factor proteins. Comparison of TERT- positive and negative cancers showed the differential activation of 496 genes and 1975 molecular pathways. Therein, 32/38 (84%) of DNA repair pathways were hyperactivated in TERT+ cancers which was also connected with accelerated replication, transcription, translation, and cell cycle progression. In contrast, the level of 40 positive cell cycle regulator proteins and a set of epithelial-to-mesenchymal transition pathways was specific for the TERT- group suggesting different proliferation strategies for both groups of cancer. Our pilot study showed that the TERT+ group had ∼13% of cancers with C228T or C250T mutated TERT promoter. However, the presence of promoter mutations was not associated with greater TERT expression compared with other TERT+ cancers, suggesting parallel mechanisms of its transcriptional activation in cancers. In addition, we detected a decreased expression of L1 retrotransposons in the TERT+ group, and further decreased L1 expression in promoter mutated TERT+ cancers. TERT expression was correlated with 17 genes encoding molecular targets of cancer therapeutics and may relate to differential survival patterns of TERT- positive and negative cancers.

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.

The biological underpinnings of therapeutic resistance to immune checkpoint inhibitors (ICI) in adolescent and young adult (AYA) melanoma patients are incompletely understood. Here, we characterize the immunogenomic profile and spatial architecture of the tumor microenvironment (TME) in AYA (aged ≤ 30 years) and older adult (aged 31-84 years) patients with melanoma, to determine the AYA-specific features associated with ICI treatment outcomes. We identify two ICI-resistant spatiotypes in AYA patients with melanoma showing stroma-infiltrating lymphocytes (SILs) that are distinct from the adult TME. The SILhigh subtype was enriched in regulatory T cells in the peritumoral space and showed upregulated expression of immune checkpoint molecules, while the SILlow subtype showed a lack of immune activation. We establish a young immunosuppressive melanoma score that can predict ICI responsiveness in AYA patients and propose personalized therapeutic strategies for the ICI-resistant subgroups. These findings highlight the distinct immunogenomic profile of AYA patients, and individualized TME features in ICI-resistant AYA melanoma that require patient-specific treatment strategies.

Diphthamide, a complex modification on eukaryotic translation elongation factor 2 (eEF2), assures reading-frame fidelity during translation. Diphthamide and enzymes for its synthesis are conserved in eukaryotes and archaea. Originally identified as target for diphtheria toxin (DT) in humans, its clinical relevance now proves to be broader than the link to pathogenic bacteria. Diphthamide synthesis enzymes (DPH1 and DPH3) are associated with cancer, and DPH gene mutations can cause diphthamide deficiency syndrome (DDS). Finally, new analyses provide evidence that diphthamide may restrict propagation of viruses including SARS-CoV-2 and HIV-1, and that DPH enzymes are targeted by viruses for degradation to overcome this restriction. This review describes how diphthamide is synthesized and functions in translation, and covers its clinical relevance in human development, cancer, and infectious diseases.

Tumours can arise from thyroid follicular cells if they acquire driver mutations that constitutively activate the MAPK signalling pathway. In addition, a limited set of additional mutations in key genes drive tumour progression towards more aggressive and less differentiated disease. Unprecedented insights into thyroid tumour biology have come from the breadth of thyroid tumour sequencing data from patients and the wide range of mutation-specific mechanisms identified in experimental models, in combination with the genomic simplicity of thyroid cancers. This knowledge is gradually being translated into refined strategies to stratify, manage and treat patients with thyroid cancer. This Review summarizes the biological underpinnings of the genetic alterations involved in thyroid cancer initiation and progression. We also provide a rationale for and discuss specific examples of how to implement genomic information to inform both recommended and investigational approaches to improve thyroid cancer prognosis, redifferentiation strategies and targeted therapies.

Activation of dominant oncogenes by small or structural genomic alterations is a common driver mechanism in many cancers. Silencing of such dominantly activated oncogenic alleles, thus, is a promising strategy to treat cancer. Recently, allele-specific epigenome editing (ASEE) has been described as a means to reduce transcription of genes in an allele-specific manner. In cancer, specificity to an oncogenic allele can be reached by either targeting directly a pathogenic single-nucleotide variant or a polymorphic single-nucleotide variant linked to the oncogenic allele. To investigate the potential of ASEE in cancer, we here explored this approach by targeting variants at the TERT promoter region. The TERT promoter region has been described as one of the most frequently mutated non-coding cancer drivers.

Sequencing of the TERT promoter in cancer cell lines showed 53% (41/77) to contain at least one heterozygous sequence variant allowing allele distinction. We chose the hepatoblastoma cell line Hep-G2 and the lung cancer cell line A-549 for this proof-of-principle study, as they contained two different kinds of variants, namely the activating mutation C228T in the TERT core promoter and the common SNP rs2853669 in the THOR region, respectively. These variants were targeted in an allele-specific manner using sgRNA-guided dCas9-DNMT3A-3L complexes. In both cell lines, we successfully introduced DNA methylation specifically to the on-target allele of the TERT promoter with limited background methylation on the off-target allele or an off-target locus (VEGFA), respectively. We observed a maximum CpG methylation gain of 39% and 76% on the target allele when targeting the activating mutation and the common SNP, respectively. The epigenome editing translated into reduced TERT RNA expression in Hep-G2.

We applied an ASEE-mediated approach to silence TERT allele specifically. Our results show that the concept of dominant oncogene inactivation by allele-specific epigenome editing can be successfully translated into cancer models. This new strategy may have important advantages in comparison with existing therapeutic approaches, e.g., targeting telomerase, especially with regard to reducing adverse side effects.

Telomerase activity and telomere elongation are essential conditions for the unlimited proliferation of neoplastic cells. Point mutations in the core promoter region of the telomerase reverse transcriptase (TERT) gene have been found to occur at high frequencies in several tumour types and considered a primary cause of telomerase reactivation in cancer cells. These mutations promote TERT gene expression by multiple mechanisms, including the generation of novel binding sites for nuclear transcription factors, displacement of negative regulators from DNA G-quadruplexes, recruitment of epigenetic activators and disruption of long-range interactions between TERT locus and telomeres. Furthermore, TERT promoter mutations cooperate with TPP1 promoter nucleotide changes to lengthen telomeres and with mutated BRAF and FGFR3 oncoproteins to enhance oncogenic signalling in cancer cells. TERT promoter mutations have been recognized as an early marker of tumour development or a major indicator of poor outcome and reduced patients survival in several cancer types. In this review, we summarize recent findings on the role of TERT promoter mutations, telomerase expression and telomeres elongation in cancer development, their clinical significance and therapeutic opportunities.

Mutations in the promoter of the telomerase reverse transcriptase (TERT) gene are the paradigm of a cross-cancer alteration in a noncoding region. TERT promoter mutations (TPM) are biomarkers of poor prognosis in cancer, including thyroid tumors. TPMs enhance TERT transcription, which is otherwise silenced in adult tissues, thus reactivating a bona fide oncoprotein. To study TERT deregulation and its downstream consequences, we generated a Tert mutant promoter mouse model via CRISPR/Cas9 engineering of the murine equivalent locus (Tert-123C>T) and crossed it with thyroid-specific BrafV600E-mutant mice. We also employed an alternative model of Tert overexpression (K5-Tert). Whereas all BrafV600E animals developed well-differentiated papillary thyroid tumors, 29% and 36% of BrafV600E+Tert-123C>T and BrafV600E+K5-Tert mice progressed to poorly differentiated cancers at week 20, respectively. Tert-upregulated tumors showed increased mitosis and necrosis in areas of solid growth, and older animals displayed anaplastic-like features, that is, spindle cells and macrophage infiltration. Murine TPM increased Tert transcription in vitro and in vivo, but temporal and intratumoral heterogeneity was observed. RNA-sequencing of thyroid tumor cells showed that processes other than the canonical Tert-mediated telomere maintenance role operate in these specimens. Pathway analysis showed that MAPK and PI3K/AKT signaling, as well as processes not previously associated with this tumor etiology, involving cytokine, and chemokine signaling, were overactivated. These models constitute useful preclinical tools to understand the cell-autonomous and microenvironment-related consequences of Tert-mediated progression in advanced thyroid cancers and other aggressive tumors carrying TPMs.

Telomerase-driven cancer progression activates pathways that can be dissected and perhaps therapeutically exploited.

Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data.

The PIP3/PI3K network is a central regulator of metabolism and is frequently activated in cancer, commonly by loss of the PIP3/PI(3,4)P2 phosphatase, PTEN. Despite huge research investment, the drivers of the PI3K network in normal tissues and how they adapt to overactivation are unclear. We find that in healthy mouse prostate PI3K activity is driven by RTK/IRS signaling and constrained by pathway feedback. In the absence of PTEN, the network is dramatically remodeled. A poorly understood YXXM- and PIP3/PI(3,4)P2-binding PH domain-containing adaptor, PLEKHS1, became the dominant activator and was required to sustain PIP3, AKT phosphorylation, and growth in PTEN-null prostate. This was because PLEKHS1 evaded pathway-feedback and experienced enhanced PI3K- and Src-family kinase-dependent phosphorylation of Y258XXM, eliciting PI3K activation. hPLEKHS1 mRNA and activating Y419 phosphorylation of hSrc correlated with PI3K pathway activity in human prostate cancers. We propose that in PTEN-null cells receptor-independent, Src-dependent tyrosine phosphorylation of PLEKHS1 creates positive feedback that escapes homeostasis, drives PIP3 signaling, and supports tumor progression.

Differentiated thyroid cancers (DTCs) are primarily initiated by mutations that activate the MAPK signaling cascade, typically at BRAF or RAS oncoproteins. DTCs can evolve to more aggressive forms, specifically, poorly differentiated (PDTC) and anaplastic thyroid cancers (ATC), by acquiring additional genetic alterations which deregulate key pathways. In this review, we focused on bona fide mutations involved in thyroid cancer progression for which consistent mechanistic data exist. Here we summarized the relevant literature, spanning approximately 2 decades, highlighting genetic alterations that are unquestionably enriched in PDTC/ATC. We describe the relevant functional data obtained in multiple in vitro and in vivo thyroid cancer models employed to study genetic alterations in the following genes and functional groups: TP53, effectors of the PI3K/AKT pathway, TERT promoter, members of the SWI/SNF chromatin remodeling complex, NF2, and EIF1AX. In addition, we briefly discuss other genetic alterations that are selected in aggressive thyroid tumors but for which mechanistic data is still either limited or nonexistent. Overall, we argue for the importance conveyed by preclinical studies for the clinical translation of genomic knowledge of thyroid cancers.

Non-coding variants in the human genome significantly influence human traits and complex diseases via their regulation and modification effects. Hence, an increasing number of computational methods are developed to predict the effects of variants in human non-coding sequences. However, it is difficult for inexperienced users to select appropriate computational methods from dozens of available methods. To solve this issue, we assessed 12 performance metrics of 24 methods on four independent non-coding variant benchmark datasets: (1) rare germline variants from clinical relevant sequence variants (ClinVar), (2) rare somatic variants from Catalogue Of Somatic Mutations In Cancer (COSMIC), (3) common regulatory variants from curated expression quantitative trait locus (eQTL) data, and (4) disease-associated common variants from curated genome-wide association studies (GWAS). All 24 tested methods performed differently under various conditions, indicating varying strengths and weaknesses under different scenarios. Importantly, the performance of existing methods was acceptable for rare germline variants from ClinVar with the area under the receiver operating characteristic curve (AUROC) of 0.4481-0.8033 and poor for rare somatic variants from COSMIC (AUROC = 0.4984-0.7131), common regulatory variants from curated eQTL data (AUROC = 0.4837-0.6472), and disease-associated common variants from curated GWAS (AUROC = 0.4766-0.5188). We also compared the prediction performance of 24 methods for non-coding de novo mutations in autism spectrum disorder, and found that the combined annotation-dependent depletion (CADD) and context-dependent tolerance score (CDTS) methods showed better performance. Summarily, we assessed the performance of 24 computational methods under diverse scenarios, providing preliminary advice for proper tool selection and guiding the development of new techniques in interpreting non-coding variants.

Thyroid cancers are often initiated by the acquisition of a BRAFV600E mutation. BRAFV600E-driven thyroid tumors display a wide range of behaviors, from the slow-growing papillary carcinomas to the highly aggressive anaplastic. Mutations in the promoter of TERT (telomerase reverse transcriptase) gene were discovered a decade ago and identified as prevalent events in thyroid cancers. Multiple studies showed that TERT promoter mutations, particularly when co-occurring with BRAFV600E, are markers of poor prognosis across thyroid cancer subtypes, and can be implemented for routine clinical stratification. Mechanistically, TERT promoter mutations reactivate telomerase expression via the differential recruitment of transcriptional complexes. Re-expression of TERT impacts tumor biology, plausibly via both the well-known function of telomerase maintaining telomeres and by affecting other cancer-relevant processes.

Decades ago, it was shown that proteins binding to DNA can quantitatively alter the formation of DNA damage by UV light. This established the principle of UV footprinting for non-intrusive study of protein-DNA contacts in living cells, albeit at limited scale and precision. Here, we perform deep base-resolution quantification of the principal UV damage lesion, the cyclobutane pyrimidine dimer (CPD), at select human promoter regions using targeted CPD sequencing. Several transcription factors exhibited distinctive and repeatable damage signatures indicative of site occupancy, involving strong (up to 17-fold) position-specific elevations and reductions in CPD formation frequency relative to naked DNA. Positive damage modulation at some ETS transcription factor binding sites coincided at base level with melanoma somatic mutation hotspots. Our work provides proof of concept for the study of protein-DNA interactions at individual loci using light and sequencing, and reveals widespread and potent modulation of UV damage in regulatory regions.

Sequencing of melanomas has identified hundreds of recurrent mutations in both coding and non-coding DNA. These include a number of well-characterized oncogenic driver mutations, such as coding mutations in the BRAF and NRAS oncogenes, and non-coding mutations in the promoter of telomerase reverse transcriptase (TERT). However, the molecular etiology and significance of most of these mutations is unknown. Here, we use a new method known as CPD-capture-seq to map UV-induced cyclobutane pyrimidine dimers (CPDs) with high sequencing depth and single nucleotide resolution at sites of recurrent mutations in melanoma. Our data reveal that many previously identified drivers and other recurrent mutations in melanoma occur at CPD hotspots in UV-irradiated melanocytes, often associated with an overlapping binding site of an E26 transformation-specific (ETS) transcription factor. In contrast, recurrent mutations in the promoters of a number of known or suspected cancer genes are not associated with elevated CPD levels. Our data indicate that a subset of recurrent protein-coding mutations are also likely caused by ETS-induced CPD hotspots. This analysis indicates that ETS proteins profoundly shape the mutation landscape of melanoma and reveals a method for distinguishing potential driver mutations from passenger mutations whose recurrence is due to elevated UV damage.

Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare malignancy originating from the periprosthetic capsule of a textured, most often macrotextured, breast implant. Identified in women whose indications for breast implants can be either aesthetic or reconstructive, the genomic underpinnings of this disease are only beginning to be elucidated.

The aim of this study was to evaluate the exomes, and in some cases the entire genome, of patients with BIA-ALCL. Specific attention was paid to copy number alterations, chromosomal translocations, and other genomic abnormalities overrepresented in patients with BIA-ALCL.

Whole-exome sequencing was performed on 6 patients, and whole-genome sequencing on 3 patients, with the Illumina NovaSeq 6000 sequencer. Data were analyzed with the Illumina DRAGEN Bio-IT Platform and the ChromoSeq pipeline. The Pathseq Genome Analysis Toolkit pipeline was used to detect the presence of microbial genomes in the sequenced samples.

Two cases with STAT3 mutations and 2 cases with NRAS mutations were noted. A critically deleted 7-Mb region was identified at the 11q22.3 region of chromosome 11, and multiple nonrecurrent chromosomal rearrangements were identified by whole-genome sequencing. Recurrent gene-level rearrangements, however, were not identified. None of the samples showed evidence of potential microbial pathogens.

Although no recurrent mutations were identified, this study identified mutations in genes not previously reported with BIA-ALCL or other forms of ALCL. Furthermore, not previously reported with BIA-ALCL, 11q22.3 deletions were consistent across whole-genome sequencing cases and present in some exomes.

Mutations in the promoter of the telomerase reverse transcriptase ( TERT ) gene are the paradigm of a cross-cancer alteration in a non-coding region. TERT promoter mutations (TPMs) are biomarkers of poor prognosis in several tumors, including thyroid cancers. TPMs enhance TERT transcription, which is otherwise silenced in adult tissues, thus reactivating a bona fide oncoprotein. To study TERT deregulation and its downstream consequences, we generated a Tert mutant promoter mouse model via CRISPR/Cas9 engineering of the murine equivalent locus (Tert -123C>T ) and crossed it with thyroid-specific Braf V600E -mutant mice. We also employed an alternative model of Tert overexpression (K5-Tert). Whereas all Braf V600E animals developed well-differentiated papillary thyroid tumors, 29% and 36% of Braf V600E +Tert -123C>T and Braf V600E +K5-Tert mice progressed to poorly differentiated thyroid cancers at week 20, respectively. Braf+Tert tumors showed increased mitosis and necrosis in areas of solid growth, and older animals from these cohorts displayed anaplastic-like features, i.e., spindle cells and macrophage infiltration. Murine Tert promoter mutation increased Tert transcription in vitro and in vivo , but temporal and intra-tumoral heterogeneity was observed. RNA-sequencing of thyroid tumor cells showed that processes other than the canonical Tert-mediated telomere maintenance role operate in these specimens. Pathway analysis showed that MAPK and PI3K/AKT signaling, as well as processes not previously associated with this tumor etiology, involving cytokine and chemokine signaling, were overactivated. Braf+Tert animals remained responsive to MAPK pathway inhibitors. These models constitute useful pre-clinical tools to understand the cell-autonomous and microenvironment-related consequences of Tert-mediated progression in advanced thyroid cancers and other aggressive tumors carrying TPMs.

Thyroid cancer is the most common malignancy of the endocrine system, and its incidence has been steadily increasing. Advances in sequencing have allowed analysis of the entire cancer genome, and has provided new information on the genetic lesions and modifications responsible for the onset, progression, dedifferentiation and metastasis of thyroid carcinomas. Moreover, integrated genomics has advanced our understanding of the development of cancer and its behavior, and has facilitated the identification of new genetic mutations and molecular pathways. The functional analysis of epigenetic modifications, such as DNA methylation, histone acetylation and non-coding RNAs, have contributed to define new regulatory mechanisms that control cell malignancy in thyroid cancer, especially aggressive forms. Here we review the most recent advances in genomics and epigenomics of thyroid cancer, which have resulted in a new classification and interpretation of the initiation and progression of thyroid tumors, providing new tools and opportunities for further investigation and for the clinical development of new treatment strategies.

Telomerase reverse transcriptase (TERT) promoter mutations are one of the most common mutations responsible for the development of hepatocellular carcinoma (HCC). Noncoding RNAs (ncRNAs) play a regulatory role in different cancers through the long noncoding RNA (lncRNA)/circular RNA (circRNA)-microRNA (miRNA)-mRNA axis. The aim of the study was to explore the influence of TERT promoter mutations on the ncRNA regulatory network in HCC.

Four tumor samples with a wildtype TERT promoter and four tumor samples with TERT promoter mutations (sequencing cohort) were collected from HCC patients for high-throughput next-generation sequencing. Selected ncRNAs and mRNAs were validated by qPCR in 15 HCC tumors with a wildtype TERT promoter and seven HCC tumors with TERT promoter mutations (validation cohort, including the sequencing cohort).

In the mutant TERT promoter group, 536 lncRNAs, 21 circRNAs, 41 miRNAs, and 266 mRNAs were significantly up-regulated, while 1745 lncRNAs, 23 circRNAs, 32 miRNAs, and 1117 mRNAs were significantly down-regulated (P < 0.05) compared with the findings in wildtype group. AL360169.3-201, LINC02672-203, hsa_circ_0021412, hsa-miR-29b-1-5p, hsa-miR-4699-5p, hsa-miR-199a-5p, REG3A, SFRP5, and GSTM1 were verified at the RNA expression level to validate the sequencing results. A differentially expressed lncRNA/circRNA-miRNA-mRNA network was constructed to explore the effects of TERT promoter mutations on ncRNA regulation. Two ncRNA regulatory axes associated with TERT promoter mutations (hsa_circ_0003154/hsa_circ_0008952/IGLL5-AS1/LINC576/LINC575-hsa-miR-1260b -CLPTM1L/GSTM1 and hsa_circ_0031584/LINC2101-hsa-miR-214-3p-CD151) had carcinogenic potential.

This study provides novel insights into the role of TERT promoter mutations on ncRNAs regulatory network in HCC progression.

Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

Cancer gene discovery is reliant on distinguishing driver mutations from a multitude of passenger mutations in tumour genomes. While driver genes may be revealed based on excess mutation recurrence or clustering, there is a need for orthogonal principles. Here, we take advantage of the fact that non-cancer genes, containing only passenger mutations under neutral selection, exhibit a likelihood of mutagenesis in a given tumour determined by the tumour's mutational signature and burden. This relationship can be disrupted by positive selection, leading to a difference in the distribution of mutated cases across a cohort for driver and passenger genes. We apply this principle to detect cancer drivers independently of recurrence in large pan-cancer cohorts, and show that our method (SEISMIC) performs comparably to traditional approaches and can provide resistance to known confounding mutational phenomena. Being based on a different principle, the approach provides a much-needed complement to existing methods for detecting signals of selection.

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.

Currently, breast cancer appears to be the most widespread cancer in the world and the most common cause of cancer deaths. This specific type of cancer affects women in both developed and developing countries. Prevention and early diagnosis are very important factors for good prognosis. A characteristic feature of cancer cells is the ability of unlimited cell division, which makes them immortal. Telomeres, which are shortened with each cell division in normal cells, are rebuilt in cancer cells by the enzyme telomerase, which is expressed in more than 85% of cancers (up to 100% of adenocarcinomas, including breast cancer). Telomerase may have different functions that are related to telomeres or unrelated. It has been shown that high activity of the enzyme in cancer cells is associated with poor cell sensitivity to therapies. Therefore, telomerase has become a potential target for cancer therapies. The low efficacy of therapies has resulted in the search for new combined and more effective therapeutic methods, including the involvement of telomerase inhibitors and telomerase-targeted immunotherapy.

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.

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.