Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing

Oncogenic gene fusions in cancer: from biology to therapy

Oncogenic gene fusions occur across a broad range of cancers and are a defining feature of some cancer types. Cancers driven by gene fusion products tend to respond well to targeted therapies, where available; thus, detection of potentially targetable oncogenic fusions is necessary to select optimal treatment. Detection methods include non-sequencing methods, such as fluorescence in situ hybridization and immunohistochemistry, and sequencing methods, such as DNA- and RNA-based next-generation sequencing (NGS). While NGS is an efficient way to analyze multiple genes of interest at once, economic and technical factors may preclude its use in routine care globally, despite several guideline recommendations. The aim of this review is to present a summary of oncogenic gene fusions, with a focus on fusions that affect tyrosine kinase signaling, and to highlight the importance of testing for oncogenic fusions. We present an overview of the identification of oncogenic gene fusions and therapies approved for the treatment of cancers harboring gene fusions, and summarize data regarding treating fusion-positive cancers with no current targeted therapies and clinical studies of fusion-positive cancers. Although treatment options may be limited for patients with rare alterations, healthcare professionals should identify patients most likely to benefit from oncogenic gene fusion testing and initiate the appropriate targeted therapy to achieve optimal treatment outcomes.

Computational Tools for Studying Genome Structural Variation

Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.

Translational and clinical comparison of whole genome and transcriptome to panel sequencing in precision oncology

Precision oncology offers new cancer treatment options, yet sequencing methods vary in type and scope. In this study, we compared whole-exome/whole-genome (WES/WGS) and transcriptome sequencing (TS) with broad panel sequencing by resequencing the same tumor DNA and RNA as well as normal tissue DNA for germline assessment, from 20 patients with rare or advanced tumors, who were originally sequenced by WES/WGS ± TS within the DKFZ/NCT/DKTK MASTER program from 2015 to 2020. Molecular analyses resulted in a median number of 2.5 (gene panel) to 3.5 (WES/WGS ± TS) treatment recommendations per patient. Our results showed that approximately half of the therapy recommendations (TRs) of both sequencing programs were identical, while approximately one-third of the TRs in WES/WGS ± TS relied on biomarkers not covered by the panel. Eight of 10 molecularly informed therapy implementations were supported by the panel, the remaining two were based on biomarkers absent from the panel, highlighting the potential additional clinical benefit of WGS and TS.

LoRA-TV: read depth profile-based clustering of tumor cells in single-cell sequencing

Single-cell sequencing has revolutionized our ability to dissect the heterogeneity within tumor populations. In this study, we present LoRA-TV (Low Rank Approximation with Total Variation), a novel method for clustering tumor cells based on the read depth profiles derived from single-cell sequencing data. Traditional analysis pipelines process read depth profiles of each cell individually. By aggregating shared genomic signatures distributed among individual cells using low-rank optimization and robust smoothing, the proposed method enhances clustering performance. Results from analyses of both simulated and real data demonstrate its effectiveness compared with state-of-the-art alternatives, as supported by improvements in the adjusted Rand index and computational efficiency.

Disentangling oncogenic amplicons in esophageal adenocarcinoma

Esophageal adenocarcinoma is a prominent example of cancer characterized by frequent amplifications in oncogenes. However, the mechanisms leading to amplicons that involve breakage-fusion-bridge cycles and extrachromosomal DNA are poorly understood. Here, we use 710 esophageal adenocarcinoma cases with matched samples and patient-derived organoids to disentangle complex amplicons and their associated mechanisms. Short-read sequencing identifies ERBB2, MYC, MDM2, and HMGA2 as the most frequent oncogenes amplified in extrachromosomal DNAs. We resolve complex extrachromosomal DNA and breakage-fusion-bridge cycles amplicons by integrating of de-novo assemblies and DNA methylation in nine long-read sequenced cases. Complex amplicons shared between precancerous biopsy and late-stage tumor, an enrichment of putative enhancer elements and mobile element insertions are potential drivers of complex amplicons' origin. We find that patient-derived organoids recapitulate extrachromosomal DNA observed in the primary tumors and single-cell DNA sequencing capture extrachromosomal DNA-driven clonal dynamics across passages. Prospectively, long-read and single-cell DNA sequencing technologies can lead to better prediction of clonal evolution in esophageal adenocarcinoma.

Breaking paradigms: Long non-coding RNAs forming gene fusions with potential implications in cancer

Long non-coding RNAs (lncRNAs) are non-coding RNAs longer than 200 nucleotides with dynamic regulatory functions. They interact with a wide range of molecules such as DNA, RNA, and proteins to modulate diverse cellular functions through several mechanisms and, if deregulated, they can lead to cancer development and progression. Recently, it has been described that lncRNAs are susceptible to form gene fusions with mRNAs or other lncRNAs, breaking the paradigm of gene fusions consisting mainly of protein-coding genes. However, their biological significance in the tumor phenotype is still uncertain. Therefore, their recent identification opens a new line of research to study their biological role in tumorigenesis, and their potential as biomarkers with clinical relevance or as therapeutic targets. The present study aimed to review the lncRNA fusions identified so far and to know which of them have been associated with a potential function. We address the current challenges to deepen their study as well as the reasons why they represent a future therapeutic window in cancer.

The reckoning of chromosomal instability: past, present, future

Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.

Haplotype-specific assembly of shattered chromosomes in esophageal adenocarcinomas

The epigenetic landscape of cancer is regulated by many factors, but primarily it derives from the underlying genome sequence. Chromothripsis is a catastrophic localized genome shattering event that drives, and often initiates, cancer evolution. We characterized five esophageal adenocarcinoma organoids with chromothripsis using long-read sequencing and transcriptome and epigenome profiling. Complex structural variation and subclonal variants meant that haplotype-aware de novo methods were required to generate contiguous cancer genome assemblies. Chromosomes were assembled separately and scaffolded using haplotype-resolved Hi-C reads, producing accurate assemblies even with up to 900 structural rearrangements. There were widespread differences between the chromothriptic and wild-type copies of chromosomes in topologically associated domains, chromatin accessibility, histone modifications, and gene expression. Differential epigenome peaks were most enriched within 10 kb of chromothriptic structural variants. Alterations in transcriptome and higher-order chromosome organization frequently occurred near differential epigenetic marks. Overall, chromothripsis reshapes gene regulation, causing coordinated changes in epigenetic landscape, transcription, and chromosome conformation.

On the core segmentation algorithms of copy number variation detection tools

Shotgun sequencing is a high-throughput method used to detect copy number variants (CNVs). Although there are numerous CNV detection tools based on shotgun sequencing, their quality varies significantly, leading to performance discrepancies. Therefore, we conducted a comprehensive analysis of next-generation sequencing-based CNV detection tools over the past decade. Our findings revealed that the majority of mainstream tools employ similar detection rationale: calculates the so-called read depth signal from aligned sequencing reads and then segments the signal by utilizing either circular binary segmentation (CBS) or hidden Markov model (HMM). Hence, we compared the performance of those two core segmentation algorithms in CNV detection, considering varying sequencing depths, segment lengths and complex types of CNVs. To ensure a fair comparison, we designed a parametrical model using mainstream statistical distributions, which allows for pre-excluding bias correction such as guanine-cytosine (GC) content during the preprocessing step. The results indicate the following key points: (1) Under ideal conditions, CBS demonstrates high precision, while HMM exhibits a high recall rate. (2) For practical conditions, HMM is advantageous at lower sequencing depths, while CBS is more competitive in detecting small variant segments compared to HMM. (3) In case involving complex CNVs resembling real sequencing, HMM demonstrates more robustness compared with CBS. (4) When facing large-scale sequencing data, HMM costs less time compared with the CBS, while their memory usage is approximately equal. This can provide an important guidance and reference for researchers to develop new tools for CNV detection.

GASOLINE: detecting germline and somatic structural variants from long-reads data

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30[Formula: see text] sequencing coverage experiments requires 4-5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

Efficient sequencing data compression and FPGA acceleration based on a two-step framework

With the increasing throughput of modern sequencing instruments, the cost of storing and transmitting sequencing data has also increased dramatically. Although many tools have been developed to compress sequencing data, there is still a need to develop a compressor with a higher compression ratio. We present a two-step framework for compressing sequencing data in this paper. The first step is to repack original data into a binary stream, while the second step is to compress the stream with a LZMA encoder. We develop a new strategy to encode the original file into a LZMA highly compressed stream. In addition an FPGA-accelerated of LZMA was implemented to speedup the second step. As a demonstration, we present repaq as a lossless non-reference compressor of FASTQ format files. We introduced a multifile redundancy elimination method, which is very useful for compressing paired-end sequencing data. According to our test results, the compression ratio of repaq is much higher than other FASTQ compressors. For some deep sequencing data, the compression ratio of repaq can be higher than 25, almost four times of Gzip. The framework presented in this paper can also be applied to develop new tools for compressing other sequencing data. The open-source code of repaq is available at: https://github.com/OpenGene/repaq.

Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.

Conversion of specific lncRNAs to biomarkers in exhaled breath condensate samples of patients with advanced stage non-small-cell lung cancer

Objectives: Lung cancer (LC) is one of the most prevalent cancers with the highest fatality rate worldwide. Long noncoding RNAs (lncRNAs) are being considered potential new molecular targets for early diagnosis, follow-up, and individual treatment decisions in LC. Therefore, this study evaluated whether lncRNA expression levels obtained from exhaled breath condensate (EBC) samples play a role in the occurrence of metastasis in the diagnosis and follow-up of patients with advanced lung adenocarcinoma (LA). Methods: A total of 40 patients with advanced primary LA and 20 healthy controls participated in the study. EBC samples were collected from patients (during diagnosis and follow-up) and healthy individuals for molecular analysis. Liquid biopsy samples were also randomly obtained from 10 patients with LA and 10 healthy people. The expression of lncRNA genes, such as MALAT1, HOTAIR, PVT1, NEAT1, ANRIL, and SPRY4-IT1 was analyzed using cfRNA extracted from all clinical samples. Results: In the diagnosis and follow-up of patients with LA, lncRNA HOTAIR (5-fold), PVT1 (7.9-fold), and NEAT1 (12.8-fold), PVT1 (6.8-fold), MALAT1 (8.4-fold) expression levels were significantly higher than those in healthy controls, respectively. Additionally, the distinct lncRNA expression profiles identified in EBC samples imply that decreased ANRIL-NEAT1 and increased ANRIL gene expression levels can be used as biomarkers to predict the development of bone and lung metastases, respectively. Conclusion: EBC is an innovative, easily reproducible approach for predicting the development of metastases, molecular diagnosis, and follow-up of LC. EBC has shown potential in elucidating the molecular structure of LC, monitoring changes, and discovering novel biomarkers.

Preleukemic Fusion Genes Induced via Ionizing Radiation

Although the prevalence of leukemia is increasing, the agents responsible for this increase are not definitely known. While ionizing radiation (IR) was classified as a group one carcinogen by the IARC, the IR-induced cancers, including leukemia, are indistinguishable from those that are caused by other factors, so the risk estimation relies on epidemiological data. Several epidemiological studies on atomic bomb survivors and persons undergoing IR exposure during medical investigations or radiotherapy showed an association between radiation and leukemia. IR is also known to induce chromosomal translocations. Specific chromosomal translocations resulting in preleukemic fusion genes (PFGs) are generally accepted to be the first hit in the onset of many leukemias. Several studies indicated that incidence of PFGs in healthy newborns is up to 100-times higher than childhood leukemia with the same chromosomal aberrations. Because of this fact, it has been suggested that PFGs are not able to induce leukemia alone, but secondary mutations are necessary. PFGs also have to occur in specific cell populations of hematopoetic stem cells with higher leukemogenic potential. In this review, we describe the connection between IR, PFGs, and cancer, focusing on recurrent PFGs where an association with IR has been established.

Identification of hub genes and biological mechanisms underlying the pathogenesis of asthenozoospermia and chronic epididymitis

Objective: Asthenozoospermia (AZS) is one of the most common causes of male fertility, affecting family wellbeing and population growth. Chronic epididymitis (CE) is a common and lingering inflammatory disease in the scrotum. Inflammation in the epididymis has a severe impact on sperm motility. This study aimed to explore the genetic profile and critical pathways involved in the pathological mechanisms of AZS and CE, and discover potential biomarkers. Methods: Genomic datasets of AZS and CE were obtained from the Gene Expression Omnibus (GEO) database, and relevant differentially expressed genes (DEGs) were identified. GO and pathway enrichment analyses, construction of a protein-protein interaction network, and receiver operator characteristic curve analysis were conducted. The expression profile of hub genes was validated in immunohistochemical data and testicular cell data. Immune infiltration, miRNA-hub gene interactions, and gene-disease interactions were explored. The mRNA levels of hub genes were further measured by qRT-PCR. Results: A total of 109 DEGs were identified between the AZS/CE and healthy control groups. Pathways of the immune system, neutrophil degranulation, and interleukin-4 and interleukin-13 signaling were enriched in AZS and CE. Five hub genes (CD300LB, CMKLR1, CCR4, B3GALT5, and CTSK) were selected, and their diagnostic values were validated in AZS, CE, and independent validation sets (area under the curve >0.7). Furthermore, the five-hub gene signature was well characterized in testicular immunohistochemical staining and testicular cells from healthy controls. Immune infiltration analysis showed that infiltration of CD8⁺ cells and T helper cells was significantly related to the expression level of five hub genes. In addition, a miRNA-hub gene network and interaction of other diseases were displayed. The mRNA levels of hub genes (CD300LB, CMKLR1, CCR4, and B3GALT5) were significantly elevated in the patient group. The mRNA level of CTSK also showed a similar trend. Conclusion: Our study uncovered the genetic profile involved in AZS and CE, and elucidated enriched pathways and molecular associations between hub genes and immune infiltration. This finding provides novel insight into the common pathogenesis of both diseases as well as the potential biomarkers for CE-associated AZS.

circPVT1 and PVT1/AKT3 show a role in cell proliferation, apoptosis, and tumor subtype-definition in small cell lung cancer

Small cell lung cancer (SCLC) is treated as a homogeneous disease, although the expression of NEUROD1, ASCL1, POU2F3, and YAP1 identifies distinct molecular subtypes. The MYC oncogene, amplified in SCLC, was recently shown to act as a lineage-specific factor to associate subtypes with histological classes. Indeed, MYC-driven SCLCs show a distinct metabolic profile and drug sensitivity. To disentangle their molecular features, we focused on the co-amplified PVT1, frequently overexpressed and originating circular (circRNA) and chimeric RNAs. We analyzed hsa_circ_0001821 (circPVT1) and PVT1/AKT3 (chimPVT1) as examples of such transcripts, respectively, to unveil their tumorigenic contribution to SCLC. In detail, circPVT1 activated a pro-proliferative and anti-apoptotic program when over-expressed in lung cells, and knockdown of chimPVT1 induced a decrease in cell growth and an increase of apoptosis in SCLC in vitro. Moreover, the investigated PVT1 transcripts underlined a functional connection between MYC and YAP1/POU2F3, suggesting that they contribute to the transcriptional landscape associated with MYC amplification. In conclusion, we have uncovered a functional role of circular and chimeric PVT1 transcripts in SCLC; these entities may prove useful as novel biomarkers in MYC-amplified tumors.

A 67-bp variable duplication in the promoter region of the ADIPOQ is associated with milk traits in Xinjiang brown cattle

Adiponectin, also known as ADIPOQ, is a hormone protein secreted by adipocytes. The ADIPOQ gene is expressed primarily in adipose tissue, and the encoded protein circulates in the bloodstream and has the potential to regulate both animal fat metabolism and hormone production. Our previous work uncovered a 67-bp variable duplication in the promoter region of ADIPOQ, which reduced the basal transcriptional activity of ADIPOQ in the 3T3_L1 cell and also inhibits the ADIPOQ mRNA expression in adipose tissue. Accordingly, the present study aimed to identify the relationship between the 67-bp structural variations in ADIPOQ promoter region and the milk traits of Xinjiang brown cattle (XJBC). The results revealed two genotypes, DD and ID, in the XJBC, and minor allelic frequency (MAF) for the 'I' allele was more than 1%. Moreover, the association analysis revealed that the 67-bp duplication in the promoter region of the ADIPOQ gene was significantly correlated with the 305 days of milk production volume, fat yield, and milk fat percentage in the XJBC (p < 0.05). These results obtained in this study suggested that the identified variable duplication could be considered as the potential genetic marker for improving milk traits of XJBC.

Defining the origin, evolution, and immune composition of SDH-deficient renal cell carcinoma

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma represents a rare subtype of hereditary kidney cancer. Clinical diagnosis can be challenging and there is little evidence to guide systemic therapeutic options. We performed genomic profiling of a cohort of tumors through the analysis of whole genomes, transcriptomes, as well as flow cytometry and immunohistochemistry in order to gain a deeper understanding of their molecular biology. We find neutral evolution after early tumor activation with a lack of secondary driver events. We show that these tumors have epithelial derivation, possibly from the macula densa, a specialized paracrine cell of the renal juxtaglomerular apparatus. They subsequently develop into immune excluded tumors. We provide transcriptomic and protein expression evidence of a highly specific tumor marker, PAPPA2. These translational findings have implications for the diagnosis and treatment for this rare tumor subtype.

Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease

INTRODUCTION

A few copy number variations (CNVs) have been reported for Alzheimer's disease (AD). However, there is a lack of a systematic investigation of CNVs in AD based on whole genome sequencing (WGS) data.

METHODS

We used four methods to identify consensus CNVs from the WGS data of 1,411 individuals and further investigated their functional roles in AD using the matched transcriptomic and clinicopathological data.

RESULTS

We identified 3,012 rare AD-specific CNVs whose residing genes are enriched for cellular glucuronidation and neuron projection pathways. Genes whose mRNA expressions are significantly correlated with common CNVs are involved in major histocompatibility complex class II receptor activity. Integration of CNVs, gene expression, and clinical and pathological traits further pinpoints a key CNV that potentially regulates immune response in AD.

DISCUSSION

We identify CNVs as potential genetic regulators of immune response in AD. The identified CNVs and their downstream gene networks reveal novel pathways and targets for AD.

Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality

BACKGROUND

Prostate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis. To find new prognostic biomarkers to enable earlier intervention and improved outcomes, we performed methylome sequencing of DNA from patients with localised prostate cancer and long-term clinical follow-up.

METHODS

We used whole-genome bisulphite sequencing (WGBS) to comprehensively map and compare DNA methylation of radical prostatectomy tissue between patients with lethal disease (n = 7) and non-lethal (n = 8) disease (median follow-up 19.5 years). Validation of differentially methylated regions (DMRs) was performed in an independent cohort (n = 185, median follow-up 15 years) using targeted multiplex bisulphite sequencing of candidate regions. Survival was assessed via univariable and multivariable analyses including clinicopathological measures (log-rank and Cox regression models).

RESULTS

WGBS data analysis identified cancer-specific methylation patterns including CpG island hypermethylation, and hypomethylation of repetitive elements, with increasing disease risk. We identified 1420 DMRs associated with prostate cancer-specific mortality (PCSM), which showed enrichment for gene sets downregulated in prostate cancer and de novo methylated in cancer. Through comparison with public prostate cancer datasets, we refined the DMRs to develop an 18-gene prognostic panel. Applying this panel to an independent cohort, we found significant associations between PCSM and hypermethylation at EPHB3, PARP6, TBX1, MARCH6 and a regulatory element within CACNA2D4. Strikingly in a multivariable model, inclusion of CACNA2D4 methylation was a better predictor of PCSM versus grade alone (Harrell's C-index: 0.779 vs. 0.684).

CONCLUSIONS

Our study provides detailed methylome maps of non-lethal and lethal prostate cancer and identifies novel genic regions that distinguish these patient groups. Inclusion of our DNA methylation biomarkers with existing clinicopathological measures improves prognostic models of prostate cancer mortality, and holds promise for clinical application.

Diverse mutational landscapes in human lymphocytes

The lymphocyte genome is prone to many threats, including programmed mutation during differentiation1, antigen-driven proliferation and residency in diverse microenvironments. Here, after developing protocols for expansion of single-cell lymphocyte cultures, we sequenced whole genomes from 717 normal naive and memory B and T cells and haematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells, with higher burdens in memory cells than in naive cells, and with T cells accumulating mutations at a higher rate throughout life. Off-target effects of immunological diversification accounted for approximately half of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every on-target IGHV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than in stem cells, with around 15% of deletions being attributable to off-target recombinase-activating gene activity. DNA damage from ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory cells. The mutation burden and signatures of normal B cells were broadly similar to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes that are active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.

Association of Pathway Mutations With Survival in Taiwanese Breast Cancers

Breast cancer is the most common invasive cancer in women worldwide. Next-generation sequencing (NGS) provides a high-resolution profile of cancer genome. Our study ultimately gives the insight for genetic screening to identify the minority of patients with breast cancer with a poor prognosis, who might benefit from the most intensive possible treatment. The detection of mutations can polish the traditional method to detect high-risk patients who experience poor prognosis, recurrence and death early. In total, 147 breast cancer tumors were sequenced with targeted sequencing using a RainDance Cancer Hotspot Panel. The average age of all 147 breast cancer patients in the study was 51.7 years, with a range of 21-77 years. The average sequencing depth was 5,222x (range 2,900x-8,633x), and the coverage was approximately 100%. A total of 235 variants in 43 genes were detected in 147 patients by high-depth Illumina sequencing. A total of 219 single nucleotide variations were found in 42 genes from 147 patients, and 16 indel mutations were found in 13 genes from 84 patients. After filtering with the 1000 Genomes database and for synonymous SNPs, we focused on 54 somatic functional point mutations. The functional point mutations contained 54 missense mutations in 22 genes. Additionally, mutation of genes within the RET, PTEN, CDH1, MAP2K4, NF1, ERBB2, RUNX1, PIK3CA, FGFR3, KIT, KDR, APC, SMO, NOTCH1, and FBXW7 in breast cancer patients were with poor prognosis. Moreover, TP53 and APC mutations were enriched in triple-negative breast cancer. APC mutations were associated with a poor prognosis in human breast cancer (log-rank P<0.001). Our study identified tumor mutation hotspot profiles in Taiwanese breast cancer patients, revealing new targetable gene mutations in Asian breast cancer patients.

Genetic changes associated with relapse in favorable histology Wilms tumor: A Children's Oncology Group AREN03B2 study

Over the last decade, sequencing of primary tumors has clarified the genetic underpinnings of Wilms tumor but has not affected therapy, outcome, or toxicity. We now sharpen our focus on relapse samples from the umbrella AREN03B2 study. We show that over 40% of relapse samples contain mutations in SIX1 or genes of the MYCN network, drivers of progenitor proliferation. Not previously seen in large studies of primary Wilms tumors, DIS3 and TERT are now identified as recurrently mutated. The analysis of primary-relapse tumor pairs suggests that 11p15 loss of heterozygosity (and other copy number changes) and mutations in WT1 and MLLT1 typically occur early, but mutations in SIX1, MYCN, and WTX are late developments in some individuals. Most strikingly, 75% of relapse samples had gain of 1q, providing strong conceptual support for studying circulating tumor DNA in clinical trials to better detect 1q gain earlier and monitor response.

EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps

The Hi-C technique has been shown to be a promising method to detect structural variations (SVs) in human genomes. However, algorithms that can use Hi-C data for a full-range SV detection have been severely lacking. Current methods can only identify interchromosomal translocations and long-range intrachromosomal SVs (>1 Mb) at less-than-optimal resolution. Therefore, we develop EagleC, a framework that combines deep-learning and ensemble-learning strategies to predict a full range of SVs at high resolution. We show that EagleC can uniquely capture a set of fusion genes that are missed by whole-genome sequencing or nanopore. Furthermore, EagleC also effectively captures SVs in other chromatin interaction platforms, such as HiChIP, Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), and capture Hi-C. We apply EagleC in more than 100 cancer cell lines and primary tumors and identify a valuable set of high-quality SVs. Last, we demonstrate that EagleC can be applied to single-cell Hi-C and used to study the SV heterogeneity in primary tumors.

Clonal dynamics of haematopoiesis across the human lifespan

Age-related change in human haematopoiesis causes reduced regenerative capacity1, cytopenias2, immune dysfunction3 and increased risk of blood cancer4-6, but the reason for such abrupt functional decline after 70 years of age remains unclear. Here we sequenced 3,579 genomes from single cell-derived colonies of haematopoietic cells across 10 human subjects from 0 to 81 years of age. Haematopoietic stem cells or multipotent progenitors (HSC/MPPs) accumulated a mean of 17 mutations per year after birth and lost 30 base pairs per year of telomere length. Haematopoiesis in adults less than 65 years of age was massively polyclonal, with high clonal diversity and a stable population of 20,000-200,000 HSC/MPPs contributing evenly to blood production. By contrast, haematopoiesis in individuals aged over 75 showed profoundly decreased clonal diversity. In each of the older subjects, 30-60% of haematopoiesis was accounted for by 12-18 independent clones, each contributing 1-34% of blood production. Most clones had begun their expansion before the subject was 40 years old, but only 22% had known driver mutations. Genome-wide selection analysis estimated that between 1 in 34 and 1 in 12 non-synonymous mutations were drivers, accruing at constant rates throughout life, affecting more genes than identified in blood cancers. Loss of the Y chromosome conferred selective benefits in males. Simulations of haematopoiesis, with constant stem cell population size and constant acquisition of driver mutations conferring moderate fitness benefits, entirely explained the abrupt change in clonal structure in the elderly. Rapidly decreasing clonal diversity is a universal feature of haematopoiesis in aged humans, underpinned by pervasive positive selection acting on many more genes than currently identified.

Combining nucleotide variations and structure variations for improving astaxanthin biosynthesis

Background

Mutational technology has been used to achieve genome-wide variations in laboratory and industrial microorganisms. Genetic polymorphisms of natural genome evolution include nucleotide variations and structural variations, which inspired us to suggest that both types of genotypic variations are potentially useful in improving the performance of chassis cells for industrial applications. However, highly efficient approaches that simultaneously generate structural and nucleotide variations are still lacking.

Results

The aim of this study was to develop a method of increasing biosynthesis of astaxanthin in yeast by Combining Nucleotide variations And Structure variations (CNAS), which were generated by combinations of Atmospheric and room temperature plasma (ARTP) and Synthetic Chromosome Recombination and Modification by LoxP-Mediated Evolution (SCRaMbLE) system. CNAS was applied to increase the biosynthesis of astaxanthin in yeast and resulted in improvements of 2.2- and 7.0-fold in the yield of astaxanthin. Furthermore, this method was shown to be able to generate structures (deletion, duplication, and inversion) as well as nucleotide variations (SNPs and InDels) simultaneously. Additionally, genetic analysis of the genotypic variations of an astaxanthin improved strain revealed that the deletion of YJR116W and the C2481G mutation of YOL084W enhanced yield of astaxanthin, suggesting a genotype-to-phenotype relationship.

Conclusions

This study demonstrated that the CNAS strategy could generate both structure variations and nucleotide variations, allowing the enhancement of astaxanthin yield by different genotypes in yeast. Overall, this study provided a valuable tool for generating genomic variation diversity that has desirable phenotypes as well as for knowing the relationship between genotypes and phenotypes in evolutionary processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01793-6.

Cancer Genomic Rearrangements and Copy Number Alterations from Errors in Cell Division

Analysis of cancer genomes has shown that a large fraction of chromosomal changes originate from catastrophic events including whole-genome duplication, chromothripsis, breakage-fusion-bridge cycles, and chromoplexy. Through sophisticated computational analysis of cancer genomes and experimental recapitulation of these catastrophic alterations, we have gained significant insights into the origin, mechanism, and evolutionary dynamics of cancer genome complexity. In this review, we summarize this progress and survey the major unresolved questions, with particular emphasis on the relative contributions of chromosome fragmentation and DNA replication errors to complex chromosomal alterations.

Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. Using whole-genome sequencing data of the pediatric tumor neuroblastoma, we here identified a type of amplification, termed 'seismic amplification', that is characterized by multiple rearrangements and discontinuous copy number levels. Overall, seismic amplifications occurred in 9.9% (274 of 2,756) of cases across 38 cancer types, and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification showed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and overexpression in a substantial fraction of human malignancies.

Convergent somatic mutations in metabolism genes in chronic liver disease

The progression of chronic liver disease to hepatocellular carcinoma is caused by the acquisition of somatic mutations that affect 20-30 cancer genes1-8. Burdens of somatic mutations are higher and clonal expansions larger in chronic liver disease9-13 than in normal liver13-16, which enables positive selection to shape the genomic landscape9-13. Here we analysed somatic mutations from 1,590 genomes across 34 liver samples, including healthy controls, alcohol-related liver disease and non-alcoholic fatty liver disease. Seven of the 29 patients with liver disease had mutations in FOXO1, the major transcription factor in insulin signalling. These mutations affected a single hotspot within the gene, impairing the insulin-mediated nuclear export of FOXO1. Notably, six of the seven patients with FOXO1S22W hotspot mutations showed convergent evolution, with variants acquired independently by up to nine distinct hepatocyte clones per patient. CIDEB, which regulates lipid droplet metabolism in hepatocytes17-19, and GPAM, which produces storage triacylglycerol from free fatty acids20,21, also had a significant excess of mutations. We again observed frequent convergent evolution: up to fourteen independent clones per patient with CIDEB mutations and up to seven clones per patient with GPAM mutations. Mutations in metabolism genes were distributed across multiple anatomical segments of the liver, increased clone size and were seen in both alcohol-related liver disease and non-alcoholic fatty liver disease, but rarely in hepatocellular carcinoma. Master regulators of metabolic pathways are a frequent target of convergent somatic mutation in alcohol-related and non-alcoholic fatty liver disease.

Increased somatic mutation burdens in normal human cells due to defective DNA polymerases

Mutation accumulation in somatic cells contributes to cancer development and is proposed as a cause of aging. DNA polymerases Pol ε and Pol δ replicate DNA during cell division. However, in some cancers, defective proofreading due to acquired POLE/POLD1 exonuclease domain mutations causes markedly elevated somatic mutation burdens with distinctive mutational signatures. Germline POLE/POLD1 mutations cause familial cancer predisposition. Here, we sequenced normal tissue and tumor DNA from individuals with germline POLE/POLD1 mutations. Increased mutation burdens with characteristic mutational signatures were found in normal adult somatic cell types, during early embryogenesis and in sperm. Thus human physiology can tolerate ubiquitously elevated mutation burdens. Except for increased cancer risk, individuals with germline POLE/POLD1 mutations do not exhibit overt features of premature aging. These results do not support a model in which all features of aging are attributable to widespread cell malfunction directly resulting from somatic mutation burdens accrued during life.

Deciphering complex genome rearrangements in C. elegans using short-read whole genome sequencing

Genomic rearrangements cause congenital disorders, cancer, and complex diseases in human. Yet, they are still understudied in rare diseases because their detection is challenging, despite the advent of whole genome sequencing (WGS) technologies. Short-read (srWGS) and long-read WGS approaches are regularly compared, and the latter is commonly recommended in studies focusing on genomic rearrangements. However, srWGS is currently the most economical, accurate, and widely supported technology. In Caenorhabditis elegans (C. elegans), such variants, induced by various mutagenesis processes, have been used for decades to balance large genomic regions by preventing chromosomal crossover events and allowing the maintenance of lethal mutations. Interestingly, those chromosomal rearrangements have rarely been characterized on a molecular level. To evaluate the ability of srWGS to detect various types of complex genomic rearrangements, we sequenced three balancer strains using short-read Illumina technology. As we experimentally validated the breakpoints uncovered by srWGS, we showed that, by combining several types of analyses, srWGS enables the detection of a reciprocal translocation (eT1), a free duplication (sDp3), a large deletion (sC4), and chromoanagenesis events. Thus, applying srWGS to decipher real complex genomic rearrangements in model organisms may help designing efficient bioinformatics pipelines with systematic detection of complex rearrangements in human genomes.

[The molecular tumor board]

BACKGROUND

New diagnostic tools in the field of oncology that became available with introduction of the next generation sequencing call for adjustments in the current clinical workflow. To ensure correct interpretation, newly collected data need to be processed and categorized properly. Thus, current experts in oncology need to be trained and new experts from other fields need to be recruited.

OBJECTIVES

The molecular tumor board was introduced to bring experts from various specialties together. The goal is to discuss and assess complex oncological cases in the context of new molecular diagnostics and give recommendations regarding individualized therapy.

RESULTS

After the introduction of the molecular tumor board 2 years ago, the number of cases processed within the molecular tumor board has increased steadily. Of these patients, 70% exhibit molecular alterations that are relevant to therapy. Preliminary results indicate positive responses to the applied therapies and clear improvements in the progression-free and overall survival of patients who would have been considered "untreatable" in the classical clinical setting.

CONCLUSION

The introduction of new molecular diagnostics makes the establishment of advanced clinical structures mandatory. In this regard, the molecular tumor board continues to gain in importance. Preliminary results point towards a significant impact on the therapy of advanced malignancies. The advancements in sequencing and newly established insights into the interpretation of sequencing results will lead to new therapeutic routes. Inevitably, this will make the molecular tumor board indispensable in the future.

Post-Transformation IGHV-IGHD-IGHJ Mutations in Chronic Lymphocytic Leukemia B Cells: Implications for Mutational Mechanisms and Impact on Clinical Course

Analyses of IGHV gene mutations in chronic lymphocytic leukemia (CLL) have had a major impact on the prognostication and treatment of this disease. A hallmark of IGHV-mutation status is that it very rarely changes clonally over time. Nevertheless, targeted and deep DNA sequencing of IGHV-IGHD-IGHJ regions has revealed intraclonal heterogeneity. We used a DNA sequencing approach that achieves considerable depth and minimizes artefacts and amplification bias to identify IGHV-IGHD-IGHJ subclones in patients with prolonged temporal follow-up. Our findings extend previous studies, revealing intraclonal IGHV-IGHD-IGHJ diversification in almost all CLL clones. Also, they indicate that some subclones with additional IGHV-IGHD-IGHJ mutations can become a large fraction of the leukemic burden, reaching numerical criteria for monoclonal B-cell lymphocytosis. Notably, the occurrence and complexity of post-transformation IGHV-IGHD-IGHJ heterogeneity and the expansion of diversified subclones are similar among U-CLL and M-CLL patients. The molecular characteristics of the mutations present in the parental, clinically dominant CLL clone (CDC) differed from those developing post-transformation (post-CDC). Post-CDC mutations exhibit significantly lower fractions of mutations bearing signatures of activation induced deaminase (AID) and of error-prone repair by Polη, and most of the mutations were not ascribable to those enzymes. Additionally, post-CDC mutations displayed a lower percentage of nucleotide transitions compared with transversions that was also not like the action of AID. Finally, the post-CDC mutations led to significantly lower ratios of replacement to silent mutations in VH CDRs and higher ratios in VH FRs, distributions different from mutations found in normal B-cell subsets undergoing an AID-mediated process. Based on these findings, we propose that post-transformation mutations in CLL cells either reflect a dysfunctional standard somatic mutational process or point to the action of another mutational process not previously associated with IG V gene loci. If the former option is the case, post-CDC mutations could lead to a lesser dependence on antigen dependent BCR signaling and potentially a greater influence of off-target, non-IG genomic mutations. Alternatively, the latter activity could add a new stimulatory survival/growth advantage mediated by the BCR through structurally altered FRs, such as that occurring by superantigen binding and stimulation.

AID in Chronic Lymphocytic Leukemia: Induction and Action During Disease Progression

The enzyme activation-induced cytidine deaminase (AID) initiates somatic hypermutation (SHM) and class switch recombination (CSR) of immunoglobulin (Ig) genes, critical actions for an effective adaptive immune response. However, in addition to the benefits generated by its physiological roles, AID is an etiological factor for the development of human and murine leukemias and lymphomas. This review highlights the pathological role of AID and the consequences of its actions on the development, progression, and therapeutic refractoriness of chronic lymphocytic leukemia (CLL) as a model disease for mature lymphoid malignancies. First, we summarize pertinent aspects of the expression and function of AID in normal B lymphocytes. Then, we assess putative causes for AID expression in leukemic cells emphasizing the role of an activated microenvironment. Thirdly, we discuss the role of AID in lymphomagenesis, in light of recent data obtained by NGS analyses on the genomic landscape of leukemia and lymphomas, concentrating on the frequency of AID signatures in these cancers and correlating previously described tumor-gene drivers with the presence of AID off-target mutations. Finally, we discuss how these changes could affect tumor suppressor and proto-oncogene targets and how they could be associated with disease progression. Collectively, we hope that these sections will help to better understand the complex paradox between the physiological role of AID in adaptive immunity and its potential causative activity in B-cell malignancies.

Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma

Recent advances in throughput and accuracy mean that the Oxford Nanopore Technologies PromethION platform is a now a viable solution for genome sequencing. Much of the validation of bioinformatic tools for this long-read data has focussed on calling germline variants (including structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated by the effects of tumour purity/subclonality. Here, we evaluate the extent to which Nanopore sequencing enables detection and analysis of somatic variation. We do this through sequencing tumour and germline genomes for a patient with diffuse B-cell lymphoma and comparing results with 150 bp short-read sequencing of the same samples. Calling germline single nucleotide variants (SNVs) from specific chromosomes of the long-read data achieved good specificity and sensitivity. However, results of somatic SNV calling highlight the need for the development of specialised joint calling algorithms. We find the comparative genome-wide performance of different tools varies significantly between structural variant types, and suggest long reads are especially advantageous for calling large somatic deletions and duplications. Finally, we highlight the utility of long reads for phasing clinically relevant variants, confirming that a somatic 1.6 Mb deletion and a p.(Arg249Met) mutation involving TP53 are oriented in trans.

PVT1: A long non-coding RNA recurrently involved in neoplasia-associated fusion transcripts

NGS technologies and bioinformatics tools allow the rapid identification of chimeric transcripts in cancer. More than 40,000 fusions are so far reported in the literature; however, for most of them, the role in oncogenesis is still not fully understood. This is the case for fusions involving the long non-coding RNA (lncRNA) Plasmacytoma variant translocation 1 (PVT1) (8q24.21). This lncRNA displays oncogenic functions in several cancer types interacting with microRNAs and proteins, but the role of PVT1 fusion transcripts is more obscure. These chimeras have been identified in both hematological malignancies and solid tumors, mainly arising from rearrangements and/or amplification of the 8q24 chromosomal region. In this review, we detail the full spectrum of PVT1 fusions in cancer, summarizing current knowledge about their genesis, function, and role as biomarkers.

Combining targeted sequencing and ultra-low-pass whole-genome sequencing for accurate somatic copy number alteration detection

This study investigated the feasibility of combining targeted sequencing and ultra-low-pass whole-genome sequencing (ULP-WGS) for improved somatic copy number alteration (SCNA) detection, due to its role in tumorigenesis and prognosis. Cerebrospinal fluid and matched blood samples were obtained from 29 patients with brain metastasis derived from lung cancer. Samples were subjected to targeted sequencing (genomic coverage: 300 kb) and 2×ULP-WGS. The SCNA was detected by the CTLW_CNV, Control-FreeC, and CNVkit methods and their accuracy was analyzed. Eighteen tumor samples showed consistent SCNA results between the three methods, while a small fraction of samples resulted in different SCNA estimations. Further analysis indicated that consistency of SCNA highly correlated with the difference of baseline depth (normalized depth of regions without SCNA events) estimation between methods. Conflict Index showed that CTLW_CNV significantly improved the accuracy of SCNA detection through precise baseline depth estimation. CTLW_CNV combines targeted sequencing and ULP-WGS for improved SCNA detection. The improvement in detection accuracy is mainly due to a refined baseline depth estimation, guided by single-nucleotide polymorphism allele frequencies within the deeply sequenced region (targeted sequencing). This method is especially suitable for tumor samples with biased aneuploidy, a previously under-estimated genomic characteristic across different cancer types.

Efficient identification of genomic insertions and flanking regions through whole-genome sequencing in three transgenic soybean events

Genomic insertions and flanking regions of transgenes in host genomes constitute a critical component of precise molecular characterization and event-specific detection, which are required in the development and assessment for regulatory approval of genetically modified (GM) crops. Previously, we reported three transgenic soybean events harboring the inverted repeats of the soybean mosaic virus NIb (nuclear inclusion b) gene, exhibiting significantly enhanced resistance to multiple Potyvirus strains. To facilitate safety assessment and event-specific detection, we identified the transgene insertion sites and flanking sequences of the events L120, L122, and L123 using whole-genome sequencing. More than 14.48 Gb sequence data (13 × coverage) were generated using the Illumina HiSeq Xten platform for each event. The sequence reads corresponding to boundaries of inserted T-DNA, and associated native flanking sequences were identified by bioinformatic comparison with the soybean reference genome (Wm82.a2.v1) and the transformation vector sequence. The results indicated that two T-DNA insertions occurred in L120, on Chr07 and Chr13, while L122 and L123 showed single insertions, on Chr02 and Chr06, respectively. Based on the flanking sequences of the inserted T-DNA, the event-specific detection for each event was established using specific PCR primers, and PCR amplification followed by sequencing of PCR products further confirmed the putative insertion loci and flanking regions in the transgenic lines. Our results demonstrate the efficacy and robustness of whole-genome sequencing in identifying the genomic insertions and flanking regions in GM crops. Moreover, the characterization of insertion loci and the establishment of event-specific detection will facilitate the application and development of broad-spectrum virus-resistant transgenic soybean cultivars.

Geographic assessment of cancer genome profiling studies

Cancers arise from the accumulation of somatic genome mutations, which can be influenced by inherited genomic variants and external factors such as environmental or lifestyle-related exposure. Due to the heterogeneity of cancers, precise information about the genomic composition of germline and malignant tissues has to be correlated with morphological, clinical and extrinsic features to advance medical knowledge and treatment options. With global differences in cancer frequencies and disease types, geographic data is of importance to understand the interplay between genetic ancestry and environmental influence in cancer incidence, progression and treatment outcome. In this study, we analyzed the current landscape of oncogenomic screening publications for geographic information content and quality, to address underrepresented study populations and thereby to fill prominent gaps in our understanding of interactions between somatic variations, population genetics and environmental factors in oncogenesis. We conclude that while the use of proxy-derived geographic annotations can be useful for coarse-grained associations, the study of geo-correlated factors in cancer causation and progression will benefit from standardized geographic provenance annotations. Additionally, publication-derived geographic provenance data allowed us to highlight stark inequality in the geographies of cancer genome profiling, with a near lack of sizable studies from Africa and other large regions.

DNA Copy Number Changes in Diffuse Large B Cell Lymphomas

Copy number aberrations (CNV/CNA) represent a major contribution to the somatic mutation landscapes in cancers, and their identification can lead to the discovery of oncogenetic targets as well as improved disease (sub-) classification. Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma in Western Countries and up to 40% of the affected individuals still succumb to the disease. DLBCL is an heterogenous group of disorders, and we call DLBCL today is not necessarily the same disease of a few years ago. This review focuses on types and frequencies of regional DNA CNVs in DLBCL, not otherwise specified, and in two particular conditions, the transformation from indolent lymphomas and the DLBCL in individuals with immunodeficiency.

Uncovering Clinically Relevant Gene Fusions with Integrated Genomic and Transcriptomic Profiling of Metastatic Cancers

PURPOSE

Gene fusions are important oncogenic drivers and many are actionable. Whole-genome and transcriptome (WGS and RNA-seq, respectively) sequencing can discover novel clinically relevant fusions.

EXPERIMENTAL DESIGN

Using WGS and RNA-seq, we reviewed the prevalence of fusions in a cohort of 570 patients with cancer, and compared prevalence to that predicted with commercially available panels. Fusions were annotated using a consensus variant calling pipeline (MAVIS) and required that a contig of the breakpoint could be constructed and supported from ≥2 structural variant detection approaches.

RESULTS

In 570 patients with advanced cancer, MAVIS identified 81 recurrent fusions by WGS and 111 by RNA-seq, of which 18 fusions by WGS and 19 by RNA-seq were noted in at least 3 separate patients. The most common fusions were EML4-ALK in thoracic malignancies (9/69, 13%), and CMTM8-CMTM7 in colorectal cancer (4/73, 5.5%). Combined genomic and transcriptomic analysis identified novel fusion partners for clinically relevant genes, such as NTRK2 (novel partners: SHC3, DAPK1), and NTRK3 (novel partners: POLG, PIBF1).

CONCLUSIONS

Utilizing WGS/RNA-seq facilitates identification of novel fusions in clinically relevant genes, and detected a greater proportion than commercially available panels are expected to find. A significant benefit of WGS and RNA-seq is the innate ability to retrospectively identify variants that becomes clinically relevant over time, without the need for additional testing, which is not possible with panel-based approaches.

Extensive heterogeneity in somatic mutation and selection in the human bladder

The extent of somatic mutation and clonal selection in the human bladder remains unknown. We sequenced 2097 bladder microbiopsies from 20 individuals using targeted (n = 1914 microbiopsies), whole-exome (n = 655), and whole-genome (n = 88) sequencing. We found widespread positive selection in 17 genes. Chromatin remodeling genes were frequently mutated, whereas mutations were absent in several major bladder cancer genes. There was extensive interindividual variation in selection, with different driver genes dominating the clonal landscape across individuals. Mutational signatures were heterogeneous across clones and individuals, which suggests differential exposure to mutagens in the urine. Evidence of APOBEC mutagenesis was found in 22% of the microbiopsies. Sequencing multiple microbiopsies from five patients with bladder cancer enabled comparisons with cancer-free individuals and across histological features. This study reveals a rich landscape of mutational processes and selection in normal urothelium with large heterogeneity across clones and individuals.

Large Copy-Number Variants in UK Biobank Caused by Clonal Hematopoiesis May Confound Penetrance Estimates

Large copy-number variants (CNVs) are strongly associated with both developmental delay and cancer, but the type of disease depends strongly on when and where the mutation occurred, i.e., germline versus somatic. We used microarray data from UK Biobank to investigate the prevalence and penetrance of large autosomal CNVs and chromosomal aneuploidies using a standard CNV detection algorithm not designed for detecting mosaic variants. We found 160 individuals that carry >10 Mb copy number changes, including 56 with whole chromosome aneuploidies. Nineteen (12%) individuals had a diagnosis of Down syndrome or other developmental disorder, while 84 (52.5%) individuals had a diagnosis of hematological malignancies or chronic myeloproliferative disorders. Notably, there was no evidence of mosaicism in the blood for many of these large CNVs, so they could easily be mistaken for germline alleles even when caused by somatic mutations. We therefore suggest that somatic mutations associated with blood cancers may result in false estimates of rare variant penetrance from population biobanks.

Breakage-Fusion-Bridge Events Trigger Complex Genome Rearrangements and Amplifications in Developmentally Arrested T Cell Lymphomas

To reveal the relative contribution of the recombination activating gene (RAG)1/2 nuclease to lymphomagenesis, we conducted a genome-wide analysis of T cell lymphomas from p53-deficient mice expressing or lacking RAG2. We found that while p53^−/− lymphoblastic T cells harbor primarily ectopic DNA deletions, Rag2^−/−p53^−/− T cell lymphomas display complex genomic rearrangements associated with amplification of the chromosomal location 9qA4-5.3. We show that this amplicon is generated by breakage-fusion-bridge during mitosis and arises distinctly in T cell lymphomas originating from an early progenitor stage. Notably, we report amplification of the corresponding syntenic region (11q23) in a subset of human leukemia leading to the overexpression of several cancer genes, including MLL/KMT2A. Our findings provide direct evidence that lymphocytes undergo malignant transformation through distinct genome architectural routes that are determined by both RAG-dependent and RAG-independent DNA damage and a block in cell development.

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Lymphomas from RAG2/p53- and p53-deficient mice bear distinct genome architectures

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Block in T cell development leads to 9qA4-5.3 rearrangements and amplifications

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Breakage-fusion-bridge events trigger 9qA4-5.3 aberrations in early T cell lymphomas

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The syntenic region 11q23 is amplified in some human hematological cancers

TP53 mutational landscape of metastatic head and neck cancer reveals patterns of mutation selection

Background

Head and neck squamous cell carcinoma is a heterogeneous disease with respect to the anatomic site of the primary tumor. On the other hand, it is highly recurrent, and once metastatic, it is associated with poor prognosis. TP53 is the most commonly mutated gene in primary disease. TP53 mutations occur in different structural elements of the protein while the biological outcome can be diverse.

Methods

Here we aimed to find differences in the mutation profile of TP53 in primary and metastatic disease and the impact of TP53 mutations in metastasis, specific copy number alterations, tumor mutation burden and response to immune checkpoint inhibitors. Somatic mutation and clinical data for 512 primary and 134 metastatic biopsies were studied.

Findings

Overall TP53 mutation frequency is significantly lower in metastases compared to primary tumors. One the other hand, missense mutations in the DNA binding region are significantly enriched in metastases and are associated with a common fragile site in chromosome 11, leading to amplification and overexpression of genes with established role in metastasis. Finally, TP53 mutations are associated with higher TMB score in metastatic but not primary tumors, and poorer response to immune checkpoint inhibitors for the latter.

Interpretation

TP53 mutations affect clinical and molecular aspects of head and neck tumorigenesis including metastasis, genetic alterations and therapeutic response.

Funding

This work was supported by a Horizon 2020 grant (801347) to AK, and a Greek General Secretariat for Research and Technology and the Hellenic Foundation for Research and Innovation grant (472‐EpiNotch) to TR.

Nano-GLADIATOR: real-time detection of copy number alterations from nanopore sequencing data

MOTIVATION

The past few years have seen the emergence of nanopore-based sequencing technologies which interrogate single molecule of DNA and generate reads sequentially.

RESULTS

In this paper, we demonstrate that, thanks to the sequentiality of the nanopore process, the data generated in the first tens of minutes of a typical MinION/GridION run can be exploited to resolve the alterations of a human genome at a karyotype level with a resolution in the order of tens of Mb, while the data produced in the first 6-12 h allow to obtain a resolution comparable to currently available array-based technologies, and thanks to a novel probabilistic approach are capable to predict the allelic fraction of genomic alteration with high accuracy. To exploit the unique characteristics of nanopore sequencing data we developed a novel software tool, Nano-GLADIATOR, that is capable to perform copy number variants/alterations detection and allelic fraction prediction during the sequencing run ('On-line' mode) and after experiment completion ('Off-line' mode). We tested Nano-GLADIATOR on publicly available ('Off-line' mode) and on novel whole genome sequencing dataset generated with MinION device ('On-line' mode) showing that our tool is capable to perform real-time copy number alterations detection obtaining good results with respect to other state-of-the-art tools.

AVAILABILITY AND IMPLEMENTATION

Nano-GLADIATOR is freely available at https://sourceforge.net/projects/nanogladiator/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mechanisms Underlying Recurrent Genomic Amplification in Human Cancers

Focal copy-number increases (genomic amplification) pinpoint oncogenic driver genes and therapeutic targets in cancer genomes. With the advent of genomic technologies, recurrent genomic amplification has been mapped throughout the genome. Recurrent amplification could be solely due to positive selection for the tumor-promoting effects of amplified gene products. Alternatively, recurrence could result from the susceptibility of the loci to amplification. Distinguishing between these possibilities requires a full understanding of the amplification mechanisms. Two mechanisms, the formation of double minute (DM) chromosomes and breakage-fusion-bridge (BFB) cycles, have been repeatedly linked to genomic amplification, and the impact of both mechanisms has been confirmed in cancer genomics data. We review the details of these mechanisms and discuss the mechanisms underlying recurrence.

Minimum error calibration and normalization for genomic copy number analysis

BACKGROUND

Copy number variations (CNV) are regional deviations from the normal autosomal bi-allelic DNA content. While germline CNVs are a major contributor to genomic syndromes and inherited diseases, the majority of cancers accumulate extensive "somatic" CNV (sCNV or CNA) during the process of oncogenetic transformation and progression. While specific sCNV have closely been associated with tumorigenesis, intriguingly many neoplasias exhibit recurrent sCNV patterns beyond the involvement of a few cancer driver genes. Currently, CNV profiles of tumor samples are generated using genomic micro-arrays or high-throughput DNA sequencing. Regardless of the underlying technology, genomic copy number data is derived from the relative assessment and integration of multiple signals, with the data generation process being prone to contamination from several sources. Estimated copy number values have no absolute or strictly linear correlation to their corresponding DNA levels, and the extent of deviation differs between sample profiles, which poses a great challenge for data integration and comparison in large scale genome analysis.

RESULTS

In this study, we present a novel method named "Minimum Error Calibration and Normalization for Copy Numbers Analysis" (Mecan4CNA). It only requires CNV segmentation files as input, is platform independent, and has a high performance with limited hardware requirements. For a given multi-sample copy number dataset, Mecan4CNA can batch-normalize all samples to the corresponding true copy number levels of the main tumor clones. Experiments of Mecan4CNA on simulated data showed an overall accuracy of 93% and 91% in determining the normal level and single copy alteration (i.e. duplication or loss of one allele), respectively. Comparison of estimated normal levels and single copy alternations with existing methods and karyotyping data on the NCI-60 tumor cell line produced coherent results. To estimate the method's impact on downstream analyses, we performed GISTIC analyses on the original and Mecan4CNA normalized data from the Cancer Genome Atlas (TCGA) where the normalized data showed prominent improvements of both sensitivity and specificity in detecting focal regions.

CONCLUSIONS

Mecan4CNA provides an advanced method for CNA data normalization, especially in meta-analyses involving large profile numbers and heterogeneous source data quality. With its informative output and visualization options, Mecan4CNA also can improve the interpretation of individual CNA profiles. Mecan4CNA is freely available as a Python package and through its code repository on Github.

Mechanisms generating cancer genome complexity from a single cell division error

The chromosome breakage-fusion-bridge (BFB) cycle is a mutational process that produces gene amplification and genome instability. Signatures of BFB cycles can be observed in cancer genomes alongside chromothripsis, another catastrophic mutational phenomenon. We explain this association by elucidating a mutational cascade that is triggered by a single cell division error-chromosome bridge formation-that rapidly increases genomic complexity. We show that actomyosin forces are required for initial bridge breakage. Chromothripsis accumulates, beginning with aberrant interphase replication of bridge DNA. A subsequent burst of DNA replication in the next mitosis generates extensive DNA damage. During this second cell division, broken bridge chromosomes frequently missegregate and form micronuclei, promoting additional chromothripsis. We propose that iterations of this mutational cascade generate the continuing evolution and subclonal heterogeneity characteristic of many human cancers.