Unscrambling cancer genomes via integrated analysis of structural variation and copy number

Integrated analyses highlight interactions between the three-dimensional genome and DNA, RNA and epigenomic alterations in metastatic prostate cancer

The impact of variations in the three-dimensional structure of the genome has been recognized, but solid cancer tissue studies are limited. Here, we performed integrated deep Hi-C sequencing with matched whole-genome sequencing, whole-genome bisulfite sequencing, 5-hydroxymethylcytosine (5hmC) sequencing and RNA sequencing across a cohort of 80 biopsy samples from patients with metastatic castration-resistant prostate cancer. Dramatic differences were present in gene expression, 5-methylcytosine/5hmC methylation and in structural variation versus mutation rate between A and B (open and closed) chromatin compartments. A subset of tumors exhibited depleted regional chromatin contacts at the AR locus, linked to extrachromosomal circular DNA (ecDNA) and worse response to AR signaling inhibitors. We also identified topological subtypes associated with stark differences in methylation structure, gene expression and prognosis. Our data suggested that DNA interactions may predispose to structural variant formation, exemplified by the recurrent TMPRSS2-ERG fusion. This comprehensive integrated sequencing effort represents a unique clinical tumor resource.

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.

Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads

Most current studies rely on short-read sequencing to detect somatic structural variation (SV) in cancer genomes. Long-read sequencing offers the advantage of better mappability and long-range phasing, which results in substantial improvements in germline SV detection. However, current long-read SV detection methods do not generalize well to the analysis of somatic SVs in tumor genomes with complex rearrangements, heterogeneity, and aneuploidy. Here, we present Severus: a method for the accurate detection of different types of somatic SVs using a phased breakpoint graph approach. To benchmark various short- and long-read SV detection methods, we sequenced five tumor/normal cell line pairs with Illumina, Nanopore, and PacBio sequencing platforms; on this benchmark Severus showed the highest F1 scores (harmonic mean of the precision and recall) as compared to long-read and short-read methods. We then applied Severus to three clinical cases of pediatric cancer, demonstrating concordance with known genetic findings as well as revealing clinically relevant cryptic rearrangements missed by standard genomic panels.

Whole-genome doubling is a double-edged sword: the heterogeneous role of whole-genome doubling in various cancer types

Whole-genome doubling (WGD), characterized by the duplication of an entire set of chromosomes, is commonly observed in various tumors, occurring in approximately 30-40% of patients with different cancer types. The effect of WGD on tumorigenesis varies depending on the context, either promoting or suppressing tumor progression. Recent advances in genomic technologies and large-scale clinical investigations have led to the identification of the complex patterns of genomic alterations underlying WGD and their functional consequences on tumorigenesis progression and prognosis. Our comprehensive review aims to summarize the causes and effects of WGD on tumorigenesis, highlighting its dualistic influence on cancer cells. We then introduce recent findings on WGD-associated molecular signatures and genetic aberrations and a novel subtype related to WGD. Finally, we discuss the clinical implications of WGD in cancer subtype classification and future therapeutic interventions. Overall, a comprehensive understanding of WGD in cancer biology is crucial to unraveling its complex role in tumorigenesis and identifying novel therapeutic strategies. [BMB Reports 2024; 57(3): 125-134].

Urine-derived bladder cancer organoids (urinoids) as a tool for cancer longitudinal response monitoring and therapy adaptation

BACKGROUND

Bladder cancer is one of the most common cancer types worldwide. Generally, research relies on invasive sampling strategies.

METHODS

Here, we generate bladder cancer organoids directly from urine (urinoids). In this project, we establish 12 urinoid lines from 22 patients with non-muscle and muscle-invasive bladder tumours, with an efficiency of 55%.

RESULTS

The histopathological features of the urinoids accurately resemble those of the original bladder tumours. Genetically, there is a high concordance of single nucleotide polymorphisms (92.56%) and insertions & deletions (91.54%) between urinoids and original tumours from patient 4. Furthermore, these urinoids show sensitivity to bladder cancer drugs, similar to their tissue-derived organoid counterparts. Genetic analysis of longitudinally generated tumoroids and urinoids from one patient receiving systemic immunotherapy, identify alterations that may guide the choice for second-line therapy. Successful treatment adaptation was subsequently demonstrated in the urinoid setting.

CONCLUSION

Therefore, urinoids can advance precision medicine in bladder cancer as a non-invasive platform for tumour pathogenesis, longitudinal drug-response monitoring, and therapy adaptation.

Unified framework for patient-derived, tumor-organoid-based predictive testing of standard-of-care therapies in metastatic colorectal cancer

Predictive drug testing of patient-derived tumor organoids (PDTOs) holds promise for personalizing treatment of metastatic colorectal cancer (mCRC), but prospective data are limited to chemotherapy regimens with conflicting results. We describe a unified framework for PDTO-based predictive testing across standard-of-care chemotherapy and biologic and targeted therapy options. In an Australian community cohort, PDTO predictions based on treatment-naive patients (n = 56) and response rates from first-line mCRC clinical trials achieve 83% accuracy for forecasting responses in patients receiving palliative treatments (18 patients, 29 treatments). Similar assay accuracy is achieved in a prospective study of third-line or later mCRC treatment, AGITG FORECAST-1 (n = 30 patients). "Resistant" predictions are associated with inferior progression-free survival; misclassification rates are similar by regimen. Liver metastases are the optimal site for sampling, with testing achievable within 7 weeks for 68.8% cases. Our findings indicate that PDTO drug panel testing can provide predictive information for multifarious standard-of-care therapies for mCRC.

Multi-omic characterization of ILC and ILC-like cell lines as part of ILC cell line encyclopedia (ICLE) defines new models to study potential biomarkers and explore therapeutic opportunities

Invasive lobular carcinoma (ILC), the most common histological "special type", accounts for ∼10-15% of all BC diagnoses, is characterized by unique features such as E-cadherin loss/deficiency, lower grade, hormone receptor positivity, larger diffuse tumors, and specific metastatic patterns. Despite ILC being acknowledged as a disease with distinct biology that necessitates specialized and precision medicine treatments, the further exploration of its molecular alterations with the goal of discovering new treatments has been hindered due to the scarcity of well-characterized cell line models for studying this disease. To address this, we generated the ILC Cell Line Encyclopedia (ICLE), providing a comprehensive multi-omic characterization of ILC and ILC-like cell lines. Using consensus multi-omic subtyping, we confirmed luminal status of previously established ILC cell lines and uncovered additional ILC/ILC-like cell lines with luminal features for modeling ILC disease. Furthermore, most of these luminal ILC/ILC-like cell lines also showed RNA and copy number similarity to ILC patient tumors. Similarly, ILC/ILC-like cell lines also retained molecular alterations in key ILC genes at similar frequency to both primary and metastatic ILC tumors. Importantly, ILC/ILC-like cell lines recapitulated the CDH1 alteration landscape of ILC patient tumors including enrichment of truncating mutations in and biallelic inactivation of CDH1 gene. Using whole-genome optical mapping, we uncovered novel genomic-rearrangements including novel structural variations in CDH1 and functional gene fusions and characterized breast cancer specific patterns of chromothripsis in chromosomes 8, 11 and 17. In addition, we systematically analyzed aberrant DNAm events and integrative analysis with RNA expression revealed epigenetic activation of TFAP2B - an emerging biomarker of lobular disease that is preferentially expressed in lobular disease. Finally, towards the goal of identifying novel druggable vulnerabilities in ILC, we analyzed publicly available RNAi loss of function breast cancer cell line datasets and revealed numerous putative vulnerabilities cytoskeletal components, focal adhesion and PI3K/AKT pathway in ILC/ILC-like vs NST cell lines. In summary, we addressed the lack of suitable models to study E-cadherin deficient breast cancers by first collecting both established and putative ILC models, then characterizing them comprehensively to show their molecular similarity to patient tumors along with uncovering their novel multi-omic features as well as highlighting putative novel druggable vulnerabilities. Not only we expand the array of suitable E-cadherin deficient cell lines available for modelling human-ILC disease but also employ them for studying epigenetic activation of a putative lobular biomarker as well as identifying potential druggable vulnerabilities for this disease towards enabling precision medicine research for human-ILC.

Druggable growth dependencies and tumor evolution analysis in patient-derived organoids of neuroendocrine neoplasms from multiple body sites

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Treatment options for patients with NENs are limited, in part due to lack of accurate models. We establish patient-derived tumor organoids (PDTOs) from pulmonary NETs and derive PDTOs from an understudied subtype of NEC, large cell neuroendocrine carcinoma (LCNEC), arising from multiple body sites. PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through hypothesis-driven drug sensitivity analyses, we identify ASCL1 as a potential biomarker for response of LCNEC to treatment with BCL-2 inhibitors. Additionally, we discover a dependency on EGF in pulmonary NET PDTOs. Consistent with these findings, we find that, in an independent cohort, approximately 50% of pulmonary NETs express EGFR. This study identifies an actionable vulnerability for a subset of pulmonary NETs, emphasizing the utility of these PDTO models.

ReConPlot: an R package for the visualization and interpretation of genomic rearrangements

MOTIVATION

Whole-genome sequencing studies of human tumours have revealed that complex forms of structural variation, collectively known as complex genome rearrangements (CGRs), are pervasive across diverse cancer types. Detection, classification, and mechanistic interpretation of CGRs requires the visualization of complex patterns of somatic copy number aberrations (SCNAs) and structural variants (SVs). However, there is a lack of tools specifically designed to facilitate the visualization and study of CGRs.

RESULTS

We present ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort. Overall, ReConPlot facilitates the exploration, interpretation, and reporting of CGR patterns.

AVAILABILITY AND IMPLEMENTATION

The R package ReConPlot is available at https://github.com/cortes-ciriano-lab/ReConPlot. Detailed documentation and a tutorial with examples are provided with the package.

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram

Breakage-fusion-bridge (BFB) is a complex rearrangement that leads to tumor malignancy. Existing models for detecting BFBs rely on the ideal BFB hypothesis, ruling out the possibility of BFBs entangled with other structural variations, that is, complex BFBs. We propose an algorithm Ambigram to identify complex BFB and reconstruct the rearranged structure of the local genome during the cancer subclone evolution process. Ambigram handles data from short, linked, long, and single-cell sequences, and optical mapping technologies. Ambigram successfully deciphers the gold- or silver-standard complex BFBs against the state-of-the-art in multiple cancers. Ambigram dissects the intratumor heterogeneity of complex BFB events with single-cell reads from melanoma and gastric cancer. Furthermore, applying Ambigram to liver and cervical cancer data suggests that the BFB mechanism may mediate oncovirus integrations. BFB also exists in noncancer genomics. Investigating the complete human genome reference with Ambigram suggests that the BFB mechanism may be involved in two genome reorganizations of Homo Sapiens during evolution. Moreover, Ambigram discovers the signals of recurrent foldback inversions and complex BFBs in whole genome data from the 1000 genome project, and congenital heart diseases, respectively.

Long-molecule scars of backup DNA repair in BRCA1- and BRCA2-deficient cancers

Homologous recombination (HR) deficiency is associated with DNA rearrangements and cytogenetic aberrations1. Paradoxically, the types of DNA rearrangements that are specifically associated with HR-deficient cancers only minimally affect chromosomal structure2. Here, to address this apparent contradiction, we combined genome-graph analysis of short-read whole-genome sequencing (WGS) profiles across thousands of tumours with deep linked-read WGS of 46 BRCA1- or BRCA2-mutant breast cancers. These data revealed a distinct class of HR-deficiency-enriched rearrangements called reciprocal pairs. Linked-read WGS showed that reciprocal pairs with identical rearrangement orientations gave rise to one of two distinct chromosomal outcomes, distinguishable only with long-molecule data. Whereas one (cis) outcome corresponded to the copying and pasting of a small segment to a distant site, a second (trans) outcome was a quasi-balanced translocation or multi-megabase inversion with substantial (10 kb) duplications at each junction. We propose an HR-independent replication-restart repair mechanism to explain the full spectrum of reciprocal pair outcomes. Linked-read WGS also identified single-strand annealing as a repair pathway that is specific to BRCA2 deficiency in human cancers. Integrating these features in a classifier improved discrimination between BRCA1- and BRCA2-deficient genomes. In conclusion, our data reveal classes of rearrangements that are specific to BRCA1 or BRCA2 deficiency as a source of cytogenetic aberrations in HR-deficient cells.

Genomic landscape of TP53-mutated myeloid malignancies

TP53-mutated myeloid malignancies are associated with complex cytogenetics and extensive structural variants, which complicates detailed genomic analysis by conventional clinical techniques. We performed whole-genome sequencing (WGS) of 42 acute myeloid leukemia (AML)/myelodysplastic syndromes (MDS) cases with paired normal tissue to better characterize the genomic landscape of TP53-mutated AML/MDS. WGS accurately determines TP53 allele status, a key prognostic factor, resulting in the reclassification of 12% of cases from monoallelic to multihit. Although aneuploidy and chromothripsis are shared with most TP53-mutated cancers, the specific chromosome abnormalities are distinct to each cancer type, suggesting a dependence on the tissue of origin. ETV6 expression is reduced in nearly all cases of TP53-mutated AML/MDS, either through gene deletion or presumed epigenetic silencing. Within the AML cohort, mutations of NF1 are highly enriched, with deletions of 1 copy of NF1 present in 45% of cases and biallelic mutations in 17%. Telomere content is increased in TP53-mutated AMLs compared with other AML subtypes, and abnormal telomeric sequences were detected in the interstitial regions of chromosomes. These data highlight the unique features of TP53-mutated myeloid malignancies, including the high frequency of chromothripsis and structural variation, the frequent involvement of unique genes (including NF1 and ETV6) as cooperating events, and evidence for altered telomere maintenance.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

BACKGROUND

All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no computationally efficient bioinformatics tool that allows visualizing and exploring these large-scale mutational events.

RESULTS

Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment.

CONCLUSIONS

The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

One-step generation of tumor models by base editor multiplexing in adult stem cell-derived organoids

Optimization of CRISPR/Cas9-mediated genome engineering has resulted in base editors that hold promise for mutation repair and disease modeling. Here, we demonstrate the application of base editors for the generation of complex tumor models in human ASC-derived organoids. First we show efficacy of cytosine and adenine base editors in modeling CTNNB1 hot-spot mutations in hepatocyte organoids. Next, we use C > T base editors to insert nonsense mutations in PTEN in endometrial organoids and demonstrate tumorigenicity even in the heterozygous state. Moreover, drug sensitivity assays on organoids harboring either PTEN or PTEN and PIK3CA mutations reveal the mechanism underlying the initial stages of endometrial tumorigenesis. To further increase the scope of base editing we combine SpCas9 and SaCas9 for simultaneous C > T and A > G editing at individual target sites. Finally, we show that base editor multiplexing allow modeling of colorectal tumorigenesis in a single step by simultaneously transfecting sgRNAs targeting five cancer genes.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2,700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures. SigProfilerAssignment is freely available at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Detecting gene breakpoints in noisy genome sequences using position-annotated colored de-Bruijn graphs

BACKGROUND

Identifying the locations of gene breakpoints between species of different taxonomic groups can provide useful insights into the underlying evolutionary processes. Given the exact locations of their genes, the breakpoints can be computed without much effort. However, often, existing gene annotations are erroneous, or only nucleotide sequences are available. Especially in mitochondrial genomes, high variations in gene orders are usually accompanied by a high degree of sequence inconsistencies. This makes accurately locating breakpoints in mitogenomic nucleotide sequences a challenging task.

RESULTS

This contribution presents a novel method for detecting gene breakpoints in the nucleotide sequences of complete mitochondrial genomes, taking into account possible high substitution rates. The method is implemented in the software package DeBBI. DeBBI allows to analyze transposition- and inversion-based breakpoints independently and uses a parallel program design, allowing to make use of modern multi-processor systems. Extensive tests on synthetic data sets, covering a broad range of sequence dissimilarities and different numbers of introduced breakpoints, demonstrate DeBBI 's ability to produce accurate results. Case studies using species of various taxonomic groups further show DeBBI 's applicability to real-life data. While (some) multiple sequence alignment tools can also be used for the task at hand, we demonstrate that especially gene breaks between short, poorly conserved tRNA genes can be detected more frequently with the proposed approach.

CONCLUSION

The proposed method constructs a position-annotated de-Bruijn graph of the input sequences. Using a heuristic algorithm, this graph is searched for particular structures, called bulges, which may be associated with the breakpoint locations. Despite the large size of these structures, the algorithm only requires a small number of graph traversal steps.

Pan-cancer whole-genome comparison of primary and metastatic solid tumours

Metastatic cancer remains an almost inevitably lethal disease1-3. A better understanding of disease progression and response to therapies therefore remains of utmost importance. Here we characterize the genomic differences between early-stage untreated primary tumours and late-stage treated metastatic tumours using a harmonized pan-cancer analysis (or reanalysis) of two unpaired primary4 and metastatic5 cohorts of 7,108 whole-genome-sequenced tumours. Metastatic tumours in general have a lower intratumour heterogeneity and a conserved karyotype, displaying only a modest increase in mutations, although frequencies of structural variants are elevated overall. Furthermore, highly variable tumour-specific contributions of mutational footprints of endogenous (for example, SBS1 and APOBEC) and exogenous mutational processes (for example, platinum treatment) are present. The majority of cancer types had either moderate genomic differences (for example, lung adenocarcinoma) or highly consistent genomic portraits (for example, ovarian serous carcinoma) when comparing early-stage and late-stage disease. Breast, prostate, thyroid and kidney renal clear cell carcinomas and pancreatic neuroendocrine tumours are clear exceptions to the rule, displaying an extensive transformation of their genomic landscape in advanced stages. Exposure to treatment further scars the tumour genome and introduces an evolutionary bottleneck that selects for known therapy-resistant drivers in approximately half of treated patients. Our data showcase the potential of pan-cancer whole-genome analysis to identify distinctive features of late-stage tumours and provide a valuable resource to further investigate the biological basis of cancer and resistance to therapies.

ERα-associated translocations underlie oncogene amplifications in breast cancer

Focal copy-number amplification is an oncogenic event. Although recent studies have revealed the complex structure1-3 and the evolutionary trajectories4 of oncogene amplicons, their origin remains poorly understood. Here we show that focal amplifications in breast cancer frequently derive from a mechanism-which we term translocation-bridge amplification-involving inter-chromosomal translocations that lead to dicentric chromosome bridge formation and breakage. In 780 breast cancer genomes, we observe that focal amplifications are frequently connected to each other by inter-chromosomal translocations at their boundaries. Subsequent analysis indicates the following model: the oncogene neighbourhood is translocated in G1 creating a dicentric chromosome, the dicentric chromosome is replicated, and as dicentric sister chromosomes segregate during mitosis, a chromosome bridge is formed and then broken, with fragments often being circularized in extrachromosomal DNAs. This model explains the amplifications of key oncogenes, including ERBB2 and CCND1. Recurrent amplification boundaries and rearrangement hotspots correlate with oestrogen receptor binding in breast cancer cells. Experimentally, oestrogen treatment induces DNA double-strand breaks in the oestrogen receptor target regions that are repaired by translocations, suggesting a role of oestrogen in generating the initial translocations. A pan-cancer analysis reveals tissue-specific biases in mechanisms initiating focal amplifications, with the breakage-fusion-bridge cycle prevalent in some and the translocation-bridge amplification in others, probably owing to the different timing of DNA break repair. Our results identify a common mode of oncogene amplification and propose oestrogen as its mechanistic origin in breast cancer.

Circlehunter: a tool to identify extrachromosomal circular DNA from ATAC-Seq data

In cancer, extrachromosomal circular DNA (ecDNA), or megabase-pair amplified circular DNA, plays an essential role in intercellular heterogeneity and tumor cell revolution because of its non-Mendelian inheritance. We developed circlehunter ( https://github.com/suda-huanglab/circlehunter ), a tool for identifying ecDNA from ATAC-Seq data using the enhanced chromatin accessibility of ecDNA. Using simulated data, we showed that circlehunter has an F1 score of 0.93 at 30× local depth and read lengths as short as 35 bp. Based on 1312 ecDNAs predicted from 94 publicly available datasets of ATAC-Seq assays, we found 37 oncogenes contained in these ecDNAs with amplification characteristics. In small cell lung cancer cell lines, ecDNA containing MYC leads to amplification of MYC and cis-regulates the expression of NEUROD1, resulting in an expression pattern consistent with the NEUROD1 high expression subtype and sensitive to Aurora kinase inhibitors. This showcases that circlehunter could serve as a valuable pipeline for the investigation of tumorigenesis.

Genetic immune escape landscape in primary and metastatic cancer

Studies have characterized the immune escape landscape across primary tumors. However, whether late-stage metastatic tumors present differences in genetic immune escape (GIE) prevalence and dynamics remains unclear. We performed a pan-cancer characterization of GIE prevalence across six immune escape pathways in 6,319 uniformly processed tumor samples. To address the complexity of the HLA-I locus in the germline and in tumors, we developed LILAC, an open-source integrative framework. One in four tumors harbors GIE alterations, with high mechanistic and frequency variability across cancer types. GIE prevalence is generally consistent between primary and metastatic tumors. We reveal that GIE alterations are selected for in tumor evolution and focal loss of heterozygosity of HLA-I tends to eliminate the HLA allele, presenting the largest neoepitope repertoire. Finally, high mutational burden tumors showed a tendency toward focal loss of heterozygosity of HLA-I as the immune evasion mechanism, whereas, in hypermutated tumors, other immune evasion strategies prevail.

Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

Cancer genomes harbor a broad spectrum of structural variants (SVs) driving tumorigenesis, a relevant subset of which escape discovery using short-read sequencing. We employed Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assembled complex rearrangements, including a 1.55-Mbp chromothripsis event, and we uncover a complex SV pattern termed templated insertion (TI) thread, characterized by short (mostly <1 kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50 kbp in size. TI threads occur in 3% of cancers, with a prevalence up to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read-based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in cancer-driver genes. Our study shows the advantage of long-read sequencing in the discovery and characterization of complex somatic rearrangements.

Predicting response to enzalutamide and abiraterone in metastatic prostate cancer using whole-omics machine learning

Response to androgen receptor signaling inhibitors (ARSI) varies widely in metastatic castration resistant prostate cancer (mCRPC). To improve treatment guidance, biomarkers are needed. We use whole-genomics (WGS; n = 155) with matching whole-transcriptomics (WTS; n = 113) from biopsies of ARSI-treated mCRPC patients for unbiased discovery of biomarkers and development of machine learning-based prediction models. Tumor mutational burden (q < 0.001), structural variants (q < 0.05), tandem duplications (q < 0.05) and deletions (q < 0.05) are enriched in poor responders, coupled with distinct transcriptomic expression profiles. Validating various classification models predicting treatment duration with ARSI on our internal and external mCRPC cohort reveals two best-performing models, based on the combination of prior treatment information with either the four combined enriched genomic markers or with overall transcriptomic profiles. In conclusion, predictive models combining genomic, transcriptomic, and clinical data can predict response to ARSI in mCRPC patients and, with additional optimization and prospective validation, could improve treatment guidance.

Extrachromosomal DNA in the cancerous transformation of Barrett's oesophagus

Oncogene amplification on extrachromosomal DNA (ecDNA) drives the evolution of tumours and their resistance to treatment, and is associated with poor outcomes for patients with cancer1-6. At present, it is unclear whether ecDNA is a later manifestation of genomic instability, or whether it can be an early event in the transition from dysplasia to cancer. Here, to better understand the development of ecDNA, we analysed whole-genome sequencing (WGS) data from patients with oesophageal adenocarcinoma (EAC) or Barrett's oesophagus. These data included 206 biopsies in Barrett's oesophagus surveillance and EAC cohorts from Cambridge University. We also analysed WGS and histology data from biopsies that were collected across multiple regions at 2 time points from 80 patients in a case-control study at the Fred Hutchinson Cancer Center. In the Cambridge cohorts, the frequency of ecDNA increased between Barrett's-oesophagus-associated early-stage (24%) and late-stage (43%) EAC, suggesting that ecDNA is formed during cancer progression. In the cohort from the Fred Hutchinson Cancer Center, 33% of patients who developed EAC had at least one oesophageal biopsy with ecDNA before or at the diagnosis of EAC. In biopsies that were collected before cancer diagnosis, higher levels of ecDNA were present in samples from patients who later developed EAC than in samples from those who did not. We found that ecDNAs contained diverse collections of oncogenes and immunomodulatory genes. Furthermore, ecDNAs showed increases in copy number and structural complexity at more advanced stages of disease. Our findings show that ecDNA can develop early in the transition from high-grade dysplasia to cancer, and that ecDNAs progressively form and evolve under positive selection.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

Background

All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events.

Results

Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment.

Conclusions

The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Genomic landscape of TP53 -mutated myeloid malignancies

TP53 -mutated myeloid malignancies are most frequently associated with complex cytogenetics. The presence of complex and extensive structural variants complicates detailed genomic analysis by conventional clinical techniques. We performed whole genome sequencing of 42 AML/MDS cases with paired normal tissue to characterize the genomic landscape of TP53 -mutated myeloid malignancies. The vast majority of cases had multi-hit involvement at the TP53 genetic locus (94%), as well as aneuploidy and chromothripsis. Chromosomal patterns of aneuploidy differed significantly from TP53 -mutated cancers arising in other tissues. Recurrent structural variants affected regions that include ETV6 on chr12p, RUNX1 on chr21, and NF1 on chr17q. Most notably for ETV6 , transcript expression was low in cases of TP53 -mutated myeloid malignancies both with and without structural rearrangements involving chromosome 12p. Telomeric content is increased in TP53 -mutated AML/MDS compared other AML subtypes, and telomeric content was detected adjacent to interstitial regions of chromosomes. The genomic landscape of TP53 -mutated myeloid malignancies reveals recurrent structural variants affecting key hematopoietic transcription factors and telomeric repeats that are generally not detected by panel sequencing or conventional cytogenetic analyses.

Key Points

WGS comprehensively determines TP53 mutation status, resulting in the reclassification of 12% of cases from mono-allelic to multi-hit Chromothripsis is more frequent than previously appreciated, with a preference for specific chromosomes ETV6 is deleted in 45% of cases, with evidence for epigenetic suppression in non-deleted cases NF1 is mutated in 48% of cases, with multi-hit mutations in 17% of these cases TP53 -mutated AML/MDS is associated with altered telomere content compared with other AMLs.

Genomic features of renal cell carcinoma developed during end-stage renal disease and dialysis

Patients with end-stage renal disease (ESRD) or receiving dialysis have a much higher risk for renal cell carcinoma (RCC), but carcinogenic mechanisms and genomic features remain little explored and undefined. This study's goal was to identify the genomic features of ESRD RCC and characterize them for associations with tumor histology and dialysis exposure. In this study, we obtained 33 RCCs, with various histological subtypes, that developed in ESRD patients receiving dialysis and performed whole-genome sequencing and transcriptome analyses. Driver events, copy-number alteration (CNA) analysis and mutational signature profiling were performed using an analysis pipeline that integrated data from germline and somatic SNVs, Indels and structural variants as well as CNAs, while transcriptome data were analyzed for differentially expressed genes and through gene set enrichment analysis. ESRD related clear cell RCCs' driver genes and mutations mirrored those in sporadic ccRCCs. Longer dialysis periods significantly correlated with a rare mutational signature SBS23, whose etiology is unknown, and increased mitochondrial copy number. All acquired cystic disease (ACD)-RCCs, which developed specifically in ESRD patients, showed chromosome 16q amplification. Gene expression analysis suggests similarity between certain ACD-RCCs and papillary RCCs and in TCGA papillary RCCs with chromosome 16 gain identified enrichment for genes related to DNA repair, as well as pathways related to reactive oxygen species, oxidative phosphorylation and targets of Myc. This analysis suggests that ESRD or dialysis could induce types of cellular stress that impact some specific types of genomic damage leading to oncogenesis.

γδ T cells are effectors of immunotherapy in cancers with HLA class I defects

DNA mismatch repair-deficient (MMR-d) cancers present an abundance of neoantigens that is thought to explain their exceptional responsiveness to immune checkpoint blockade (ICB)^1,2. Here, in contrast to other cancer types^3-5, we observed that 20 out of 21 (95%) MMR-d cancers with genomic inactivation of β2-microglobulin (encoded by B2M) retained responsiveness to ICB, suggesting the involvement of immune effector cells other than CD8⁺ T cells in this context. We next identified a strong association between B2M inactivation and increased infiltration by γδ T cells in MMR-d cancers. These γδ T cells mainly comprised the Vδ1 and Vδ3 subsets, and expressed high levels of PD-1, other activation markers, including cytotoxic molecules, and a broad repertoire of killer-cell immunoglobulin-like receptors. In vitro, PD-1⁺ γδ T cells that were isolated from MMR-d colon cancers exhibited enhanced reactivity to human leukocyte antigen (HLA)-class-I-negative MMR-d colon cancer cell lines and B2M-knockout patient-derived tumour organoids compared with antigen-presentation-proficient cells. By comparing paired tumour samples from patients with MMR-d colon cancer that were obtained before and after dual PD-1 and CTLA-4 blockade, we found that immune checkpoint blockade substantially increased the frequency of γδ T cells in B2M-deficient cancers. Taken together, these data indicate that γδ T cells contribute to the response to immune checkpoint blockade in patients with HLA-class-I-negative MMR-d colon cancers, and underline the potential of γδ T cells in cancer immunotherapy.

Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care

PURPOSE

The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking.

METHODS

Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation.

RESULTS

We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test.

CONCLUSION

WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer.

Leveraging extrachromosomal DNA to fine-tune trials of targeted therapy for glioblastoma: opportunities and challenges

Glioblastoma evolution is facilitated by intratumour heterogeneity, which poses a major hurdle to effective treatment. Evidence indicates a key role for oncogene amplification on extrachromosomal DNA (ecDNA) in accelerating tumour evolution and thus resistance to treatment, particularly in glioblastomas. Oncogenes contained within ecDNA can reach high copy numbers and expression levels, and their unequal segregation can result in more rapid copy number changes in response to therapy than is possible through natural selection of intrachromosomal genomic loci. Notably, targeted therapies inhibiting oncogenic pathways have failed to improve glioblastoma outcomes. In this Perspective, we outline reasons for this disappointing lack of clinical translation and present the emerging evidence implicating ecDNA as an important driver of tumour evolution. Furthermore, we suggest that through detection of ecDNA, patient selection for clinical trials of novel agents can be optimized to include those most likely to benefit based on current understanding of resistance mechanisms. We discuss the challenges to successful translation of this approach, including accurate detection of ecDNA in tumour tissue with novel technologies, development of faithful preclinical models for predicting the efficacy of novel agents in the presence of ecDNA oncogenes, and understanding the mechanisms of ecDNA formation during cancer evolution and how they could be attenuated therapeutically. Finally, we evaluate the feasibility of routine ecDNA characterization in the clinic and how this process could be integrated with other methods of molecular stratification to maximize the potential for clinical translation of precision medicines.