Mitotic tethering enables inheritance of shattered micronuclear chromosomes.

Chromothripsis, the shattering and imperfect reassembly of one (or a few) chromosome(s)1, is an ubiquitous2 mutational process generating localized and complex chromosomal rearrangements that drive genome evolution in cancer. Chromothripsis can be initiated by mis-segregation errors in mitosis3,4 or DNA metabolism5-7 that lead to entrapment of chromosomes within micronuclei and their subsequent fragmentation in the next interphase or following mitotic entry6,8-10. Here we use inducible degrons to demonstrate that chromothriptically produced pieces of a micronucleated chromosome are tethered together in mitosis by a protein complex consisting of mediator of DNA damage checkpoint 1 (MDC1), DNA topoisomerase II-binding protein 1 (TOPBP1) and cellular inhibitor of PP2A (CIP2A), thereby enabling en masse segregation to the same daughter cell. Such tethering is shown to be crucial for the viability of cells undergoing chromosome mis-segregation and shattering after transient inactivation of the spindle assembly checkpoint. Transient, degron-induced reduction in CIP2A following chromosome micronucleation-dependent chromosome shattering is shown to drive acquisition of segmental deletions and inversions. Analyses of pancancer tumour genomes showed that expression of CIP2A and TOPBP1 was increased overall in cancers with genomic rearrangements, including copy number-neutral chromothripsis with minimal deletions, but comparatively reduced in cancers with canonical chromothripsis in which deletions were frequent. Thus, chromatin-bound tethers maintain the proximity of fragments of a shattered chromosome enabling their re-encapsulation into, and religation within, a daughter cell nucleus to form heritable, chromothriptically rearranged chromosomes found in the majority of human cancers.

Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA.

Clustered somatic mutations are common in cancer genomes and previous analyses reveal several types of clustered single-base substitutions, which include doublet- and multi-base substitutions1-5, diffuse hypermutation termed omikli6, and longer strand-coordinated events termed kataegis3,7-9. Here we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome-sequenced cancers from 30 types of cancer10. Clustered mutations were highly enriched in driver genes and associated with differential gene expression and changes in overall survival. Several distinct mutational processes gave rise to clustered indels, including signatures that were enriched in tobacco smokers and homologous-recombination-deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, whereas most multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, which have previously been attributed to APOBEC3 activity6, accounted for a large proportion of clustered substitutions; however, only 16.2% of omikli matched APOBEC3 patterns. Kataegis was generated by multiple mutational processes, and 76.1% of all kataegic events exhibited mutational patterns that are associated with the activation-induced deaminase (AID) and APOBEC3 family of deaminases. Co-occurrence of APOBEC3 kataegis and extrachromosomal DNA (ecDNA), termed kyklonas (Greek for cyclone), was found in 31% of samples with ecDNA. Multiple distinct kyklonic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kyklonic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fuelling the evolution of ecDNA.

Signatures of copy number alterations in human cancer.

Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage-fusion-bridge cycles, among others, which may lead to chromosomal instability and aneuploidy1,2. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance3-5. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.

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/ .

An overview of mutational and copy number signatures in human cancer.

The genome of each cell in the human body is constantly under assault from a plethora of exogenous and endogenous processes that can damage DNA. If not successfully repaired, DNA damage generally becomes permanently imprinted in cells, and all their progenies, as somatic mutations. In most cases, the patterns of these somatic mutations contain the tell-tale signs of the mutagenic processes that have imprinted and are termed mutational signatures. Recent pan-cancer genomic analyses have elucidated the compendium of mutational signatures for all types of small mutational events, including (1) single base substitutions, (2) doublet base substitutions, and (3) small insertions/deletions. In contrast to small mutational events, where, in most cases, DNA damage is a prerequisite, aneuploidy, which refers to the abnormal number of chromosomes in a cell, usually develops from mistakes during DNA replication. Such mistakes include DNA replication stress, mitotic errors caused by faulty microtubule dynamics, or cohesion defects that contribute to chromosomal breakage and can lead to copy number (CN) alterations (CNAs) or even to structural rearrangements. These aberrations also leave behind genomic scars which can be inferred from sequencing as CN signatures and rearrangement signatures. The analyses of mutational signatures of small mutational events have been extensively reviewed, so we will not comprehensively re-examine them here. Rather, our focus will be on summarising the existing knowledge for mutational signatures of CNAs. As studying CN signatures is an emerging field, we briefly summarise the utility that mutational signatures of small mutational events have provided in basic science, cancer treatment, and cancer prevention, and we emphasise the future role that CN signatures may play in each of these fields. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The genomics of undifferentiated sarcoma of soft tissue: Progress, challenges and opportunities.

Undifferentiated sarcoma of soft tissue (USTS) are aggressive sarcomas that remain a diagnosis of exclusion and show extreme genomic complexity. Many advances in diagnostic criteria have resulted in several revisions in the definition of this rare cancer type. Recent sequencing efforts have illuminated the nature of the genome complexity and have revealed extensive copy number heterogeneity and multiple evolutionary patterns of development. This review places these recent advances into their historical and translational context and covers the changes in nomenclature, molecular classification, and the promise of personalised medicine.

H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours.

Diagnosing MPNST can be challenging, but genetic alterations recently identified in polycomb repressive complex 2 (PRC2) core component genes, EED and SUZ12, resulting in global loss of the histone 3 lysine 27 trimethylation (H3K27me3) epigenetic mark, represent drivers of malignancy and a valuable diagnostic tool. However, the reported loss of H3K27me3 expression ranges from 35% to 84%. We show that advances in molecular pathology now allow many MPNST mimics to be classified confidently. We confirm that MPNSTs harbouring mutations in PRC2 core components are associated with loss of H3K27me3 expression; whole-genome doubling was detected in 68%, and SSTR2 was amplified in 32% of MPNSTs. We demonstrate that loss of H3K27me3 expression occurs overall in 38% of MPNSTs, but is lost in 76% of histologically classical cases, whereas loss was detected in only 23% cases with heterologous elements and 14% where the diagnosis could not be provided on morphology alone. H3K27me3 loss is rarely seen in other high-grade sarcomas and was not found to be associated with an inferior outcome in MPNST. We show that DNA methylation profiling distinguishes MPNST from its histological mimics, was unrelated to anatomical site, and formed two main clusters, MeGroups 4 and 5. MeGroup 4 represents classical MPNSTs lacking H3K27me3 expression in the majority of cases, whereas MeGroup 5 comprises MPNSTs exhibiting non-classical histology and expressing H3K27me3 and cluster with undifferentiated sarcomas. The two MeGroups are distinguished by differentially methylated PRC2-associated genes, the majority of which are hypermethylated in the promoter regions in MeGroup 4, indicating that the PRC2 target genes are not expressed in these tumours. The methylation profiles of MPNSTs with retention of H3K27me3 in MeGroups 4 and 5 are independent of mutations in PRC2 core components and the driver(s) in these groups remain to be identified. Our results open new avenues of investigation. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Undifferentiated pleomorphic sarcomas with PRDM10 fusions have a distinct gene expression profile.

Undifferentiated pleomorphic sarcoma (UPS) is a highly aggressive soft tissue tumor. A subset of UPS is characterized by a CITED2-PRDM10 or a MED12-PRDM10 gene fusion. Preliminary data suggest that these so-called PRDM10-rearranged tumors (PRT) are clinically more indolent than classical high-grade UPS, and hence important to recognize. Here, we assessed the spectrum of accompanying mutations and the gene expression profile in PRT using genomic arrays and sequencing of the genome (WGS) and transcriptome (RNA-seq). The fusion protein's function was further investigated by conditional expression of the CITED2-PRDM10 fusion in a fibroblast cell line, followed by RNA-seq and an assay for transposase-accessible chromatin (ATAC-seq). The CADM3 gene was found to be differentially up-regulated in PRT and cell lines and was also evaluated for expression at the protein level using immunohistochemistry (IHC). The genomic analyses identified few and nonrecurrent mutations in addition to the structural variants giving rise to the gene fusions, strongly indicating that the PRDM10-fusions represent the critical driver mutations. RNA-seq of tumors showed a distinct gene expression profile, separating PRT from high-grade UPS and other soft tissue tumors. CADM3 was among the genes that was consistently and highly expressed in both PRT and fibroblasts expressing CITED2-PRDM10, suggesting that it is a direct target of the PRDM10 transcription factor. This conclusion is in line with sequencing data from ATAC-seq, showing enrichment of PRDM10 binding sites, suggesting that the amino-terminal fusion partner contributes by making the DNA more accessible to PRDM10 binding. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Evaluation of low-template DNA profiles using peak heights.

In recent years statistical models for the analysis of complex (low-template and/or mixed) DNA profiles have moved from using only presence/absence information about allelic peaks in an electropherogram, to quantitative use of peak heights. This is challenging because peak heights are very variable and affected by a number of factors. We present a new peak-height model with important novel features, including over- and double-stutter, and a new approach to dropin. Our model is incorporated in open-source R code likeLTD. We apply it to 108 laboratory-generated crime-scene profiles and demonstrate techniques of model validation that are novel in the field. We use the results to explore the benefits of modeling peak heights, finding that it is not always advantageous, and to assess the merits of pre-extraction replication. We also introduce an approximation that can reduce computational complexity when there are multiple low-level contributors who are not of interest to the investigation, and we present a simple approximate adjustment for linkage between loci, making it possible to accommodate linkage when evaluating complex DNA profiles.

Worldwide F(ST) estimates relative to five continental-scale populations.

We estimate the population genetics parameter FST (also referred to as the fixation index) from short tandem repeat (STR) allele frequencies, comparing many worldwide human subpopulations at approximately the national level with continental-scale populations. FST is commonly used to measure population differentiation, and is important in forensic DNA analysis to account for remote shared ancestry between a suspect and an alternative source of the DNA. We estimate FST comparing subpopulations with a hypothetical ancestral population, which is the approach most widely used in population genetics, and also compare a subpopulation with a sampled reference population, which is more appropriate for forensic applications. Both estimation methods are likelihood-based, in which FST is related to the variance of the multinomial-Dirichlet distribution for allele counts. Overall, we find low FST values, with posterior 97.5 percentiles < 3% when comparing a subpopulation with the most appropriate population, and even for inter-population comparisons we find FST < 5%. These are much smaller than single nucleotide polymorphism-based inter-continental FST estimates, and are also about half the magnitude of STR-based estimates from population genetics surveys that focus on distinct ethnic groups rather than a general population. Our findings support the use of FST up to 3% in forensic calculations, which corresponds to some current practice.

Choice of population database for forensic DNA profile analysis.

When evaluating the weight of evidence (WoE) for an individual to be a contributor to a DNA sample, an allele frequency database is required. The allele frequencies are needed to inform about genotype probabilities for unknown contributors of DNA to the sample. Typically databases are available from several populations, and a common practice is to evaluate the WoE using each available database for each unknown contributor. Often the most conservative WoE (most favourable to the defence) is the one reported to the court. However the number of human populations that could be considered is essentially unlimited and the number of contributors to a sample can be large, making it impractical to perform every possible WoE calculation, particularly for complex crime scene profiles. We propose instead the use of only the database that best matches the ancestry of the queried contributor, together with a substantial FST adjustment. To investigate the degree of conservativeness of this approach, we performed extensive simulations of one- and two-contributor crime scene profiles, in the latter case with, and without, the profile of the second contributor available for the analysis. The genotypes were simulated using five population databases, which were also available for the analysis, and evaluations of WoE using our heuristic rule were compared with several alternative calculations using different databases. Using FST=0.03, we found that our heuristic gave WoE more favourable to the defence than alternative calculations in well over 99% of the comparisons we considered; on average the difference in WoE was just under 0.2 bans (orders of magnitude) per locus. The degree of conservativeness of the heuristic rule can be adjusted through the FST value. We propose the use of this heuristic for DNA profile WoE calculations, due to its ease of implementation, and efficient use of the evidence while allowing a flexible degree of conservativeness.

The mutagenic forces shaping the genomic landscape of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock-Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR-mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10-5), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10-5). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

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 Patterns of Malignant Peripheral Nerve Sheath Tumor (MPNST) Evolution Correlate with Clinical Outcome and Are Detectable in Cell-Free DNA.

Malignant peripheral nerve sheath tumor (MPNST), an aggressive soft-tissue sarcoma, occurs in people with neurofibromatosis type 1 (NF1) and sporadically. Whole-genome and multiregional exome sequencing, transcriptomic, and methylation profiling of 95 tumor samples revealed the order of genomic events in tumor evolution. Following biallelic inactivation of NF1, loss of CDKN2A or TP53 with or without inactivation of polycomb repressive complex 2 (PRC2) leads to extensive somatic copy-number aberrations (SCNA). Distinct pathways of tumor evolution are associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumors with H3K27me3 loss evolve through extensive chromosomal losses followed by whole-genome doubling and chromosome 8 amplification, and show lower levels of immune cell infiltration. Retention of H3K27me3 leads to extensive genomic instability, but an immune cell-rich phenotype. Specific SCNAs detected in both tumor samples and cell-free DNA (cfDNA) act as a surrogate for H3K27me3 loss and immune infiltration, and predict prognosis. SIGNIFICANCE: MPNST is the most common cause of death and morbidity for individuals with NF1, a relatively common tumor predisposition syndrome. Our results suggest that somatic copy-number and methylation profiling of tumor or cfDNA could serve as a biomarker for early diagnosis and to stratify patients into prognostic and treatment-related subgroups. This article is highlighted in the In This Issue feature, p. 517.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor.

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Clinical outcomes, Kadish-INSICA staging and therapeutic targeting of somatostatin receptor 2 in olfactory neuroblastoma.

INTRODUCTION: Olfactory neuroblastoma (ONB) is a rare cancer of the sinonasal region. We provide a comprehensive analysis of this malignancy with molecular and clinical trial data on a subset of our cohort to report on the potential efficacy of somatostatin receptor 2 (SSTR2)-targeting imaging and therapy. METHODS: We conducted a retrospective analysis of 404 primary, locally recurrent, and metastatic olfactory neuroblastoma (ONB) patients from 12 institutions in the United States of America, United Kingdom and Europe. Clinicopathological characteristics and treatment approach were evaluated. SSTR2 expression, SSTR2-targeted imaging and the efficacy of peptide receptor radionuclide therapy [PRRT](177Lu-DOTATATE) were reported in a subset of our cohort (LUTHREE trial; NCT03454763). RESULTS: Dural infiltration at presentation was a significant predictor of overall survival (OS) and disease-free survival (DFS) in primary cases (n = 278). Kadish-Morita staging and Dulguerov T-stage both had limitations regarding their prognostic value. Multivariable survival analysis demonstrated improved outcomes with lower stage and receipt of adjuvant radiotherapy. Prophylactic neck irradiation significantly reduces the rate of nodal recurrence. 82.4% of the cohort were positive for SSTR2; treatment of three metastatic cases with SSTR2-targeted peptide-radionuclide receptor therapy (PRRT) in the LUTHREE trial was well-tolerated and resulted in stable disease (SD). CONCLUSIONS: This study presents pertinent clinical data from the largest dataset, to date, on ONB. We identify key prognostic markers and integrate these into an updated staging system, highlight the importance of adjuvant radiotherapy across all disease stages, the utility of prophylactic neck irradiation and the potential efficacy of targeting SSTR2 to manage disease.

Whole-genome sequencing of single circulating tumor cells from neuroendocrine neoplasms.

Single-cell profiling of circulating tumor cells (CTCs) as part of a minimally invasive liquid biopsy presents an opportunity to characterize and monitor tumor heterogeneity and evolution in individual patients. In this study, we aimed to compare single-cell copy number variation (CNV) data with tissue and define the degree of intra- and inter-patient genomic heterogeneity. We performed next-generation sequencing (NGS) whole-genome CNV analysis of 125 single CTCs derived from seven patients with neuroendocrine neoplasms (NEN) alongside matched white blood cells (WBC), formalin-fixed paraffin-embedded (FFPE), and fresh frozen (FF) samples. CTC CNV profiling demonstrated recurrent chromosomal alterations in previously reported NEN copy number hotspots, including the prognostically relevant loss of chromosome 18. Unsupervised hierarchical clustering revealed CTCs with distinct clonal lineages as well as significant intra- and inter-patient genomic heterogeneity, including subclonal alterations not detectable by bulk analysis and previously unreported in NEN. Notably, we also demonstrated the presence of genomically distinct CTCs according to the enrichment strategy utilized (EpCAM-dependent vs size-based). This work has significant implications for the identification of therapeutic targets, tracking of evolutionary change, and the implementation of CTC-biomarkers in cancer.

Therapeutic vulnerability to PARP1,2 inhibition in RB1-mutant osteosarcoma.

Loss-of-function mutations in the RB1 tumour suppressor are key drivers in cancer, including osteosarcoma. RB1 loss-of-function compromises genome-maintenance and hence could yield vulnerability to therapeutics targeting such processes. Here we demonstrate selective hypersensitivity to clinically-approved inhibitors of Poly-ADP-Polymerase1,2 inhibitors (PARPi) in RB1-defective cancer cells, including an extended panel of osteosarcoma-derived lines. PARPi treatment results in extensive cell death in RB1-defective backgrounds and prolongs survival of mice carrying human RB1-defective osteosarcoma grafts. PARPi sensitivity is not associated with canonical homologous recombination defect (HRd) signatures that predict PARPi sensitivity in cancers with BRCA1,2 loss, but is accompanied by rapid activation of DNA replication checkpoint signalling, and active DNA replication is a prerequisite for sensitivity. Importantly, sensitivity in backgrounds with natural or engineered RB1 loss surpasses that seen in BRCA-mutated backgrounds where PARPi have established clinical benefit. Our work provides evidence that PARPi sensitivity extends beyond cancers identifiable by HRd and advocates PARP1,2 inhibition as a personalised strategy for RB1-mutated osteosarcoma and other cancers.

Somatostatin receptor 2 expression in nasopharyngeal cancer is induced by Epstein Barr virus infection: impact on prognosis, imaging and therapy.

Nasopharyngeal cancer (NPC), endemic in Southeast Asia, lacks effective diagnostic and therapeutic strategies. Even in high-income countries the 5-year survival rate for stage IV NPC is less than 40%. Here we report high somatostatin receptor 2 (SSTR2) expression in multiple clinical cohorts comprising 402 primary, locally recurrent and metastatic NPCs. We show that SSTR2 expression is induced by the Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) via the NF-κB pathway. Using cell-based and preclinical rodent models, we demonstrate the therapeutic potential of SSTR2 targeting using a cytotoxic drug conjugate, PEN-221, which is found to be superior to FDA-approved SSTR2-binding cytostatic agents. Furthermore, we reveal significant correlation of SSTR expression with increased rates of survival and report in vivo uptake of the SSTR2-binding 68Ga-DOTA-peptide radioconjugate in PET-CT scanning in a clinical trial of NPC patients (NCT03670342). These findings reveal a key role in EBV-associated NPC for SSTR2 in infection, imaging, targeted therapy and survival.

Undifferentiated Sarcomas Develop through Distinct Evolutionary Pathways.

Undifferentiated sarcomas (USARCs) of adults are diverse, rare, and aggressive soft tissue cancers. Recent sequencing efforts have confirmed that USARCs exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the molecular basis of the structural complexity in USARCs by integrating DNA sequencing, ploidy analysis, gene expression, and methylation profiling. We identified whole genome duplication as a prevalent and pernicious force in USARC tumorigenesis. Using mathematical deconvolution strategies to unravel the complex copy-number profiles and mutational timing models we infer distinct evolutionary pathways of these rare cancers. In addition, 15% of tumors exhibited raised mutational burdens that correlated with gene expression signatures of immune infiltration, and good prognosis.