CopywriteR: DNA copy number detection from off-target sequence data

Deciphering lineage specification during early embryogenesis in mouse gastruloids using multilayered proteomics

Gastrulation is a critical stage in embryonic development during which the germ layers are established. Advances in sequencing technologies led to the identification of gene regulatory programs that control the emergence of the germ layers and their derivatives. However, proteome-based studies of early mammalian development are scarce. To overcome this, we utilized gastruloids and a multilayered mass spectrometry-based proteomics approach to investigate the global dynamics of (phospho) protein expression during gastruloid differentiation. Our findings revealed many proteins with temporal expression and unique expression profiles for each germ layer, which we also validated using single-cell proteomics technology. Additionally, we profiled enhancer interaction landscapes using P300 proximity labeling, which revealed numerous gastruloid-specific transcription factors and chromatin remodelers. Subsequent degron-based perturbations combined with single-cell RNA sequencing (scRNA-seq) identified a critical role for ZEB2 in mouse and human somitogenesis. Overall, this study provides a rich resource for developmental and synthetic biology communities endeavoring to understand mammalian embryogenesis.

Comparison of Optical Genome Mapping With Conventional Diagnostic Methods for Structural Variant Detection in Hematologic Malignancies

Background

Structural variants (SVs) are currently analyzed using a combination of conventional methods; however, this approach has limitations. Optical genome mapping (OGM), an emerging technology for detecting SVs using a single-molecule strategy, has the potential to replace conventional methods. We compared OGM with conventional diagnostic methods for detecting SVs in various hematologic malignancies.

Methods

Residual bone marrow aspirates from 27 patients with hematologic malignancies in whom SVs were observed using conventional methods (chromosomal banding analysis, FISH, an RNA fusion panel, and reverse transcription PCR) were analyzed using OGM. The concordance between the OGM and conventional method results was evaluated.

Results

OGM showed concordance in 63% (17/27) and partial concordance in 37% (10/27) of samples. OGM detected 76% (52/68) of the total SVs correctly (concordance rate for each type of SVs: aneuploidies, 83% [15/18]; balanced translocation, 80% [12/15] unbalanced translocation, 54% [7/13] deletions, 81% [13/16]; duplications, 100% [2/2] inversion 100% [1/1]; insertion, 100% [1/1]; marker chromosome, 0% [0/1]; isochromosome, 100% [1/1]). Sixteen discordant results were attributed to the involvement of centromeric/telomeric regions, detection sensitivity, and a low mapping rate and coverage. OGM identified additional SVs, including submicroscopic SVs and novel fusions, in five cases.

Conclusions

OGM shows a high level of concordance with conventional diagnostic methods for the detection of SVs and can identify novel variants, suggesting its potential utility in enabling more comprehensive SV analysis in routine diagnostics of hematologic malignancies, although further studies and improvements are required.

Immune Checkpoint Blockade Delays Cancer and Extends Survival in Murine DNA Polymerase Mutator Syndromes

Mutations in polymerases Pold1 and Pole exonuclease domains in humans are associated with increased cancer incidence, elevated tumor mutation burden (TMB) and response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond. Here we generated Pold1 and Pole proofreading mutator mice and show that ICB treatment of mice with high TMB tumors did not improve survival as only a subset of tumors responded. Similarly, introducing the mutator alleles into mice with Kras/p53 lung cancer did not improve survival, however, passaging mutator tumor cells in vitro without immune editing caused rejection in immune-competent hosts, demonstrating the efficiency by which cells with antigenic mutations are eliminated. Finally, ICB treatment of mutator mice earlier, before observable tumors delayed cancer onset, improved survival, and selected for tumors without aneuploidy, suggesting the use of ICB in individuals at high risk for cancer prevention.

Highlights

Germline somatic and conditional Pold1 and Pole exonuclease domain mutations in mice produce a mutator phenotype. Spontaneous cancers arise in mutator mice that have genomic features comparable to human tumors with these mutations.ICB treatment of mutator mice with tumors did not improve survival as only a subset of tumors respond. Introduction of the mutator alleles into an autochthonous mouse lung cancer model also did not produce immunogenic tumors, whereas passaging mutator tumor cells in vitro caused immune rejection indicating efficient selection against antigenic mutations in vivo . Prophylactic ICB treatment delayed cancer onset, improved survival, and selected for tumors with no aneuploidy.

Leveraging Off-Target Reads in Panel Sequencing for Homologous Recombination Repair Deficiency Screening in Tumor

Targeted tumor only sequencing has become a standard practice in cancer diagnostics. This study aims to develop an approach for robust copy number variant calling in tumor samples using only off-target region (OTR) reads. We also established a clinical use case for homologous recombination deficiency (HRD) score estimation (HRDest) using the sum of telomeric-allelic imbalance and large-scale state transition scores without the need for loss of heterozygosity information. A strong correlation was found between HRD score and the sum of telomeric-allelic imbalance + large-scale state transition in The Cancer Genome Atlas cohort (ρ = 0.99, P < 2.2 × 10-16) and in a clinical in-house cohort of 34 tumors (ρ = 0.9, P = 5.1 × 10-13) comparing whole-exome sequencing and targeted sequencing data. HRDest scores from 1086 clinical cases were compared with The Cancer Genome Atlas data set. There were no significant differences in HRD score distribution within the analyzed tumor types. As a control, commercially available HRD standards were also sequenced, and the HRDest scores obtained from the OTR reads were well within the HRD reference range provided by the manufacturer. In conclusion, OTR reads of tumor-only panel sequencing can be used to determine genome-wide copy number variant profiles and to approximate HRD scores.

Clinician-Driven Reanalysis of Exome Sequencing Data From Patients With Inherited Retinal Diseases

Importance

Despite advances in next-generation sequencing (NGS), a significant proportion of patients with inherited retinal disease (IRD) remain undiagnosed after initial genetic testing. Exome sequencing (ES) reanalysis in the clinical setting has been suggested as one method for improving diagnosis of IRD.

Objective

To investigate the association of clinician-led reanalysis of ES data, which incorporates updated clinical information and comprehensive bioinformatic analysis, with the diagnostic yield in a cohort of patients with IRDs in Korea.

Design, Setting, and Participants

This was a multicenter prospective cohort study involving 264 unrelated patients with IRDs, conducted in Korea between March 2018 and February 2020. Comprehensive ophthalmologic examinations and ES analyses were performed, and ES data were reanalyzed by an IRD specialist for single nucleotide variants, copy number variants, mobile element insertions, and mitochondrial variants. Data were analyzed from March to July 2023.

Main Outcomes and Measures

Diagnostic rate of conventional bioinformatic analysis and clinician-driven ES reanalysis.

Results

A total of 264 participants (151 [57.2%] male; mean [SD] age at genetic testing, 33.6 [18.9] years) were enrolled, including 129 patients (48.9%) with retinitis pigmentosa and 26 patients (9.8%) with Stargardt disease or macular dystrophy. Initial bioinformatic analysis diagnosed 166 patients (62.9%). Clinician-driven reanalysis identified the molecular cause of diseases in an additional 22 patients, corresponding to an 8.3-percentage point increase in diagnostic rate. Key factors associated with new molecular diagnoses included clinical phenotype updates (4 patients) and detection of previously overlooked variation, such as structural variants (9 patients), mitochondrial variants (3 patients), filtered or not captured variants (4 patients), and noncanonical splicing variants (2 patients). Among the 22 patients, variants in 7 patients (31.8%) were observed in the initial analysis but not reported to patients, while those in the remaining 15 patients (68.2%) were newly detected by the ES reanalysis.

Conclusions and Relevance

In this cohort study, clinician-centered reanalysis of ES data was associated with improved molecular diagnostic yields in patients with IRD. This approach is important for uncovering missed genetic causes of retinal disease.

Detection of elusive DNA copy-number variations in hereditary disease and cancer through the use of noncoding and off-target sequencing reads

Copy-number variants (CNVs) play a substantial role in the molecular pathogenesis of hereditary disease and cancer, as well as in normal human interindividual variation. However, they are still rather difficult to identify in mainstream sequencing projects, especially involving exome sequencing, because they often occur in DNA regions that are not targeted for analysis. To overcome this problem, we developed OFF-PEAK, a user-friendly CNV detection tool that builds on a denoising approach and the use of "off-target" DNA reads, which are usually discarded by sequencing pipelines. We benchmarked OFF-PEAK on data from targeted sequencing of 96 cancer samples, as well as 130 exomes of individuals with inherited retinal disease from three different populations. For both sets of data, OFF-PEAK demonstrated excellent performance (>95% sensitivity and >80% specificity vs. experimental validation) in detecting CNVs from in silico data alone, indicating its immediate applicability to molecular diagnosis and genetic research.

Increased genomic instability and reshaping of tissue microenvironment underlie oncogenic properties of Arid1a mutations

Oncogenic mutations accumulating in many chromatin-associated proteins have been identified in different tumor types. With a mutation rate from 10 to 57%, ARID1A has been widely considered a tumor suppressor gene. However, whether this role is mainly due to its transcriptional-related activities or its ability to preserve genome integrity is still a matter of intense debate. Here, we show that ARID1A is largely dispensable for preserving enhancer-dependent transcriptional regulation, being ARID1B sufficient and required to compensate for ARID1A loss. We provide in vivo evidence that ARID1A is mainly required to preserve genomic integrity in adult tissues. ARID1A loss primarily results in DNA damage accumulation, interferon type I response activation, and chronic inflammation leading to tumor formation. Our data suggest that in healthy tissues, the increased genomic instability that follows ARID1A mutations and the selective pressure imposed by the microenvironment might result in the emergence of aggressive, possibly immune-resistant, tumors.

The effect of missing data on evolutionary analysis of sequence capture bycatch, with application to an agricultural pest

Sequence capture is a genomic technique that selectively enriches target sequences before high throughput next-generation sequencing, to generate specific sequences of interest. Off-target or 'bycatch' data are often discarded from capture experiments, but can be leveraged to address evolutionary questions under some circumstances. Here, we investigated the effects of missing data on a variety of evolutionary analyses using bycatch from an exon capture experiment on the global pest moth, Helicoverpa armigera. We added > 200 new samples from across Australia in the form of mitogenomes obtained as bycatch from targeted sequence capture, and combined these into an additional larger dataset to total > 1000 mitochondrial cytochrome c oxidase subunit I (COI) sequences across the species' global distribution. Using discriminant analysis of principal components and Bayesian coalescent analyses, we showed that mitogenomes assembled from bycatch with up to 75% missing data were able to return evolutionary inferences consistent with higher coverage datasets and the broader literature surrounding H. armigera. For example, low-coverage sequences broadly supported the delineation of two H. armigera subspecies and also provided new insights into the potential for geographic turnover among these subspecies. However, we also identified key effects of dataset coverage and composition on our results. Thus, low-coverage bycatch data can offer valuable information for population genetic and phylodynamic analyses, but caution is required to ensure the reduced information does not introduce confounding factors, such as sampling biases, that drive inference. We encourage more researchers to consider maximizing the potential of the targeted sequence approach by examining evolutionary questions with their off-target bycatch where possible-especially in cases where no previous mitochondrial data exists-but recommend stratifying data at different genome coverage thresholds to separate sampling effects from genuine genomic signals, and to understand their implications for evolutionary research.

Compartment-specific multiomic profiling identifies SRC and GNAS as candidate drivers of epithelial-to-mesenchymal transition in ovarian carcinosarcoma

BACKGROUND

Ovarian carcinosarcoma (OCS) is an exceptionally aggressive and understudied ovarian cancer type harbouring distinct carcinomatous and sarcomatous compartments. Here, we seek to identify shared and compartment-specific events that may represent potential therapeutic targets and candidate drivers of sarcomatous compartment formation through epithelial-to-mesenchymal transition (EMT).

METHODS

We performed multiomic profiling (exome sequencing, RNA-sequencing, microRNA profiling) of paired carcinomatous and sarcomatous components in 12 OCS cases.

RESULTS

While paired sarcomatous and carcinomatous compartments demonstrate substantial genomic similarities, multiple loci are recurrently copy number-altered between components; regions containing GNAS and SRC are recurrently gained within the sarcomatous compartment. CCNE1 gain is a common event in OCS, occurring more frequently than in high grade serous ovarian carcinoma (HGSOC). Transcriptomic analysis suggests increased MAPK activity and subtype switching toward poor prognosis HGSOC-derived transcriptomic subtypes within the sarcomatous component. The two compartments show global differences in microRNA profiles, with differentially expressed microRNAs targeting EMT-related genes (SIRT1, ZEB2) and regulators of pro-tumourigenic pathways (TGFβ, NOTCH); chrX is a highly enriched target of these microRNAs and is also frequently deleted across samples. The sarcomatous component harbours significantly fewer CD8-positive cells, suggesting poorer immune engagement.

CONCLUSION

CCNE1 gain and chrX loss are frequent in OCS. SRC gain, increased GNAS expression and microRNA dysregulation represent potential mechanisms driving sarcomatous compartment formation.

T proliferating cells derived autophagy signature associated with prognosis and immunotherapy resistance in a pan-cancer analysis

Despite autophagy modulating tumor immunity in the tumor microenvironment (TME), the immunotherapeutic efficacy and potential mechanism of autophagy signature was not explicit. We manually curated an autophagy gene set and defined a pan-cancer autophagy signature by comparing malignant tissues and normal tissues in The Cancer Genome Atlas (TCGA) cohort. The pan-cancer autophagy signature was derived from T proliferating cells as demonstrated in multiple single-cell RNA sequencing (scRNA-seq) datasets. The pan-cancer autophagy signature could influence the cell-cell interactions in the TME and predict the responsiveness of immune checkpoint inhibitors (ICIs) in the metastatic renal cell carcinoma, non-small cell lung cancer, bladder cancer, and melanoma cohorts. Metabolism inactivation accompanied with dysregulation of autophagy was investigated with transcriptomic and proteomic data. The immunotherapeutic predictive role and mechanism regulation of the autophagy signature was validated in an in-house cohort. Our study provides valuable insights into the mechanisms of ICI resistance.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

A proteogenomics data-driven knowledge base of human cancer

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.

Proteogenomic Approaches for the Identification of NF1/Neurofibromin-depleted Estrogen Receptor-positive Breast Cancers for Targeted Treatment

NF1 is a key tumor suppressor that represses both RAS and estrogen receptor-α (ER) signaling in breast cancer. Blocking both pathways by fulvestrant (F), a selective ER degrader, together with binimetinib (B), a MEK inhibitor, promotes tumor regression in NF1-depleted ER⁺ models. We aimed to establish approaches to determine how NF1 protein levels impact B+F treatment response to improve our ability to identify B+F sensitive tumors. We examined a panel of ER⁺ patient-derived xenograft (PDX) models by DNA and mRNA sequencing and found that more than half of these models carried an NF1 shallow deletion and generally have low mRNA levels. Consistent with RAS and ER activation, RET and MEK levels in NF1-depleted tumors were elevated when profiled by mass spectrometry (MS) after kinase inhibitor bead pulldown. MS showed that NF1 can also directly and selectively bind to palbociclib-conjugated beads, aiding quantification. An IHC assay was also established to measure NF1, but the MS-based approach was more quantitative. Combined IHC and MS analysis defined a threshold of NF1 protein loss in ER⁺ breast PDX, below which tumors regressed upon treatment with B+F. These results suggest that we now have a MS-verified NF1 IHC assay that can be used for patient selection as a complement to somatic genomic analysis.

Significance

A major challenge for targeting the consequence of tumor suppressor disruption is the accurate assessment of protein functional inactivation. NF1 can repress both RAS and ER signaling, and a ComboMATCH trial is underway to treat the patients with binimetinib and fulvestrant. Herein we report a MS-verified NF1 IHC assay that can determine a threshold for NF1 loss to predict treatment response. These approaches may be used to identify and expand the eligible patient population.

Technological and computational approaches to detect somatic mosaicism in epilepsy

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma

Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.

Association between hepatic angiosarcoma and end-stage renal disease: nationwide population-based evidence and enriched mutational signature of aristolochic acid exposure

Hepatic angiosarcoma (HAS) is an aggressive mesenchymal malignancy that remains underexplored with respect to its etiology and mutational landscapes. To clarify the association between HAS and end-stage renal disease (ESRD), we used nationwide data of the National Health Insurance Research Database (NHIRD) in Taiwan, covering ~99% of the population, from 2001 to 2016. To investigate molecular signatures, we performed whole-exome sequencing (WES) in 27 surgical specimens, including nine ESRD-associated cases. The NHIRD analysis demonstrated that HAS ranked second among all angiosarcomas in Taiwan, with the incidence rates of HAS being 0.08, 2.49, and 5.71 per 100,000 person-years in the general population, chronic kidney disease (CKD), and ESRD patients, respectively. The standardized incidence ratios of HAS in CKD and ESRD patients were 29.99 and 68.77, respectively. In comparison with nonhepatic angiosarcoma, the multivariate regression analysis of our institutional cohort confirmed CKD/ESRD as an independent risk factor for HAS (odds ratio: 9.521, 95% confidence interval: 2.995-30.261, p < 0.001). WES identified a high tumor mutation burden (TMB; median: 8.66 variants per megabase) and dominant A:T-to-T:A transversion in HAS with frequent TP53 (81%) and ATRX (41%) mutations, KDR amplifications/gains (56%), and CDKN2A/B deletions (48%). Notably, ESRD-associated HAS had a significantly higher TMB (17.62 variants per megabase, p = 0.01) and enriched mutational signatures of aristolochic acid exposure (COSMIC SBS22, p < 0.001). In summary, a significant proportion of HAS in Taiwan is associated with ESRD and harbors a distinctive mutational signature, which concomitantly links nephrotoxicity and mutagenesis resulting from exposure to aristolochic acid or related compounds. A high TMB may support the eligibility for immunotherapy in treating ESRD-associated HAS. © 2023 The Pathological Society of Great Britain and Ireland.

Whole exome sequencing of low grade serous ovarian carcinoma identifies genomic events associated with clinical outcome

OBJECTIVES

Low-grade serous ovarian carcinoma (LGSOC) is a distinct, rare, ovarian cancer type characterised by younger patient age and intrinsic chemoresistance. Understanding the molecular landscape is crucial for optimising targeted therapy.

METHODS

Genomic data from whole exome sequencing of tumour tissue was analysed in a LGSOC cohort with detailed clinical annotation.

RESULTS

63 cases were analysed and three subgroups identified based on single nucleotide variants: canonical MAPK mutant (cMAPKm: 52%, KRAS/BRAF/NRAS), MAPK-associated gene mutation (MAPK-assoc: 27%) and MAPK wild-type (MAPKwt: 21%). NOTCH pathway disruption occurred across all subgroups. Tumour mutational burden (TMB), mutational signatures and recurrent copy number (CN) changes varied across the cohort with co-occurrence of chromosome 1p loss and 1q gain (CN Chr1pq) a recurrent feature. Low TMB and CN Chr1pq were associated with inferior disease-specific survival (HR 6.43; p < 0.001 and HR 3.29, p = 0.011 respectively). Stepwise genomic classification in relation to outcome resulted in four groups (TMB low; CN Chr1pq; MAPKwt/MAPKassoc; cMAPKm). 5 year disease-specific survival was 46%, 55%, 79% and 100% respectively for these groups. The two most favourable genomic subgroups were enriched for the SBS10b mutational signature, particularly the cMAPKm subgroup.

CONCLUSIONS

LGSOC comprises multiple genomic subgroups with distinct clinical and molecular features. Chr1pq CN arm disruption and TMB represent promising methods to identify individuals with poorer prognosis. Further investigation of the molecular basis for these observations is required. MAPKwt cases represent around a fifth of patients. NOTCH inhibitors represent a candidate therapeutic strategy worthy of exploration across these cases.

Distinct histopathological features are associated with molecular subtypes and outcome in low grade serous ovarian carcinoma

Low grade serous ovarian carcinoma (LGSOC) demonstrates unique clinical and molecular features compared to other ovarian cancer types. The relationship between common histological features of LGSOC and molecular events, such as hormone receptor expression patterns and MAPK gene mutation status, remains poorly understood. Recent data suggest some of these molecular features may be biomarkers of response to recently introduced biologically-targeted therapies, namely endocrine therapy and MEK inhibitors. We utilize a cohort of 63 pathologically-confirmed LGSOC cases with whole exome sequencing and hormone receptor expression data to investigate these relationships. LGSOC cases demonstrated uniformly high oestrogen receptor (ER) expression, but variable progesterone receptor (PR) expression intensity. 60% and 37% of cases demonstrated micropapillary and macropapillary patterns of stromal invasion, respectively. 63% of cases demonstrated desmoplasia, which was significantly associated with advanced disease stage and visible residual disease after cytoreductive surgery. MAPK-mutant cases (KRAS, BRAF, NRAS) more frequently demonstrated macropapillary stromal invasion, while Chr1p loss was associated with desmoplasia and low PR expression. Presence of micropapillary stromal invasion and low PR expression were associated with significantly poorer survival after accounting for stage and residual disease status. Together, these data identify novel relationships between histopathological features and molecularly-defined subgroups in LGSOC.

Simultaneous Copy Number Alteration and Single-Nucleotide Variation Analysis in Matched Aqueous Humor and Tumor Samples in Children with Retinoblastoma

Retinoblastoma (RB) is a childhood cancer that forms in the developing retina of young children; this tumor cannot be biopsied due to the risk of provoking extraocular tumor spread, which dramatically alters the treatment and survival of the patient. Recently, aqueous humor (AH), the clear fluid in the anterior chamber of the eye, has been developed as an organ-specific liquid biopsy for investigation of in vivo tumor-derived information found in the cell-free DNA (cfDNA) of the biofluid. However, identifying somatic genomic alterations, including both somatic copy number alterations (SCNAs) and single nucleotide variations (SNVs) of the RB1 gene, typically requires either: (1) two distinct experimental protocols-low-pass whole genome sequencing for SCNAs and targeted sequencing for SNVs-or (2) expensive deep whole genome or exome sequencing. To save time and cost, we applied a one-step targeted sequencing method to identify both SCNAs and RB1 SNVs in children with RB. High concordance (median = 96.2%) was observed in comparing SCNA calls derived from targeted sequencing to the traditional low-pass whole genome sequencing method. We further applied this method to investigate the degree of concordance of genomic alterations between paired tumor and AH samples from 11 RB eyes. We found 11/11 AH samples (100%) had SCNAs, and 10 of them (90.1%) with recurrent RB-SCNAs, while only nine out of 11 tumor samples (81.8%) had positive RB-SCNA signatures in both low-pass and targeted methods. Eight out of the nine (88.9%) detected SNVs were shared between AH and tumor samples. Ultimately, 11/11 cases have somatic alterations identified, including nine RB1 SNVs and 10 recurrent RB-SCNAs with four focal RB1 deletions and one MYCN gain. The results presented show the feasibility of utilizing one sequencing approach to obtain SCNA and targeted SNV data to capture a broad genomic scope of RB disease, which may ultimately expedite clinical intervention and be less expensive than other methods.

KaryoCreate: A CRISPR-based technology to study chromosome-specific aneuploidy by targeting human centromeres

Aneuploidy, the presence of chromosome gains or losses, is a hallmark of cancer. Here, we describe KaryoCreate (karyotype CRISPR-engineered aneuploidy technology), a system that enables the generation of chromosome-specific aneuploidies by co-expression of an sgRNA targeting chromosome-specific CENPA-binding ɑ-satellite repeats together with dCas9 fused to mutant KNL1. We design unique and highly specific sgRNAs for 19 of the 24 chromosomes. Expression of these constructs leads to missegregation and induction of gains or losses of the targeted chromosome in cellular progeny, with an average efficiency of 8% for gains and 12% for losses (up to 20%) validated across 10 chromosomes. Using KaryoCreate in colon epithelial cells, we show that chromosome 18q loss, frequent in gastrointestinal cancers, promotes resistance to TGF-β, likely due to synergistic hemizygous deletion of multiple genes. Altogether, we describe an innovative technology to create and study chromosome missegregation and aneuploidy in the context of cancer and beyond.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.

Immunogenomic analysis of human brain metastases reveals diverse immune landscapes across genetically distinct tumors

Brain metastases (BrMs) are the most common form of brain tumors in adults and frequently originate from lung and breast primary cancers. BrMs are associated with high mortality, emphasizing the need for more effective therapies. Genetic profiling of primary tumors is increasingly used as part of the effort to guide targeted therapies against BrMs, and immune-based strategies for the treatment of metastatic cancer are gaining momentum. However, the tumor immune microenvironment (TIME) of BrM is extremely heterogeneous, and whether specific genetic profiles are associated with distinct immune states remains unknown. Here, we perform an extensive characterization of the immunogenomic landscape of human BrMs by combining whole-exome/whole-genome sequencing, RNA sequencing of immune cell populations, flow cytometry, immunofluorescence staining, and tissue imaging analyses. This revealed unique TIME phenotypes in genetically distinct lung- and breast-BrMs, thereby enabling the development of personalized immunotherapies tailored by the genetic makeup of the tumors.

BMI-CNV: a Bayesian framework for multiple genotyping platforms detection of copy number variants

Whole-exome sequencing (WES) enables the detection of copy number variants (CNVs) with high resolution in protein-coding regions. However, variants in the intergenic or intragenic regions are excluded from studies. Fortunately, many of these samples have been previously sequenced by other genotyping platforms which are sparse but cover a wide range of genomic regions, such as SNP array. Moreover, conventional single sample-based methods suffer from a high false discovery rate due to prominent data noise. Therefore, methods for integrating multiple genotyping platforms and multiple samples are highly demanded for improved copy number variant detection. We developed BMI-CNV, a Bayesian Multisample and Integrative CNV (BMI-CNV) profiling method with data sequenced by both whole-exome sequencing and microarray. For the multisample integration, we identify the shared copy number variants regions across samples using a Bayesian probit stick-breaking process model coupled with a Gaussian Mixture model estimation. With extensive simulations, BMI-copy number variant outperformed existing methods with improved accuracy. In the matched data from the 1000 Genomes Project and HapMap project data, BMI-CNV also accurately detected common variants and significantly enlarged the detection spectrum of whole-exome sequencing. Further application to the data from The Research of International Cancer of Lung consortium (TRICL) identified lung cancer risk variant candidates in 17q11.2, 1p36.12, 8q23.1, and 5q22.2 regions.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31-33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications.

SIGNIFICANCE

Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31-33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483.

p53 mutation in normal esophagus promotes multiple stages of carcinogenesis but is constrained by clonal competition

Aging normal human oesophagus accumulates TP53 mutant clones. These are the origin of most oesophageal squamous carcinomas, in which biallelic TP53 disruption is almost universal. However, how p53 mutant clones expand and contribute to cancer development is unclear. Here we show that inducing the p53R245W mutant in single oesophageal progenitor cells in transgenic mice confers a proliferative advantage and clonal expansion but does not disrupt normal epithelial structure. Loss of the remaining p53 allele in mutant cells results in genomically unstable p53R245W/null epithelium with giant polyaneuploid cells and copy number altered clones. In carcinogenesis, p53 mutation does not initiate tumour formation, but tumours developing from areas with p53 mutation and LOH are larger and show extensive chromosomal instability compared to lesions arising in wild type epithelium. We conclude that p53 has distinct functions at different stages of carcinogenesis and that LOH within p53 mutant clones in normal epithelium is a critical step in malignant transformation.

Proteogenomic analysis of cancer aneuploidy and normal tissues reveals divergent modes of gene regulation across cellular pathways

How cells control gene expression is a fundamental question. The relative contribution of protein-level and RNA-level regulation to this process remains unclear. Here, we perform a proteogenomic analysis of tumors and untransformed cells containing somatic copy number alterations (SCNAs). By revealing how cells regulate RNA and protein abundances of genes with SCNAs, we provide insights into the rules of gene regulation. Protein complex genes have a strong protein-level regulation while non-complex genes have a strong RNA-level regulation. Notable exceptions are plasma membrane protein complex genes, which show a weak protein-level regulation and a stronger RNA-level regulation. Strikingly, we find a strong negative association between the degree of RNA-level and protein-level regulation across genes and cellular pathways. Moreover, genes participating in the same pathway show a similar degree of RNA- and protein-level regulation. Pathways including translation, splicing, RNA processing, and mitochondrial function show a stronger protein-level regulation while cell adhesion and migration pathways show a stronger RNA-level regulation. These results suggest that the evolution of gene regulation is shaped by functional constraints and that many cellular pathways tend to evolve one predominant mechanism of gene regulation at the protein level or at the RNA level.

Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Many genetic variants affect disease risk by altering context-dependent gene regulation. Such variants are difficult to study mechanistically using current methods that link genetic variation to steady-state gene expression levels, such as expression quantitative trait loci (eQTLs). To address this challenge, we developed the cistrome-wide association study (CWAS), a framework for identifying genotypic and allele-specific effects on chromatin that are also associated with disease. In prostate cancer, CWAS identified regulatory elements and androgen receptor-binding sites that explained the association at 52 of 98 known prostate cancer risk loci and discovered 17 additional risk loci. CWAS implicated key developmental transcription factors in prostate cancer risk that are overlooked by eQTL-based approaches due to context-dependent gene regulation. We experimentally validated associations and demonstrated the extensibility of CWAS to additional epigenomic datasets and phenotypes, including response to prostate cancer treatment. CWAS is a powerful and biologically interpretable paradigm for studying variants that influence traits by affecting transcriptional regulation.

Multiomic Characterization of High-Grade Serous Ovarian Carcinoma Enables High-Resolution Patient Stratification

PURPOSE

High-grade serous ovarian carcinoma (HGSOC) is the most common ovarian cancer type; most patients experience disease recurrence that accumulates chemoresistance, leading to treatment failure. Genomic and transcriptomic features have been associated with differential outcome and treatment response. However, the relationship between events at the gene sequence, copy number, and gene-expression levels remains poorly defined.

EXPERIMENTAL DESIGN

We perform multiomic characterization of a large HGSOC cohort (n = 362) with detailed clinical annotation to interrogate the relationship between patient subgroups defined by specific molecular events.

RESULTS

BRCA2-mutant (BRCA2m) and EMSY-overexpressing cases demonstrated prolonged survival [multivariable hazard ratios (HR) 0.40 and 0.51] and significantly higher first- and second-line chemotherapy response rate. CCNE1-gained (CCNE1g) cases demonstrated underrepresentation of FIGO stage IV cases, with shorter survival but no significant difference in treatment response. We demonstrate marked overlap between the TCGA- and Tothill-derived subtypes. IMR/C2 cases displayed higher BRCA1/2m frequency (25.5%, 32.5%) and significantly greater immune cell infiltration, whereas PRO/C5 cases had the highest CCNE1g rate (23.9%, 22.2%) and were uniformly low in immune cell infiltration. The survival benefit for cases with aberrations in homologous recombination repair (HRR) genes was apparent across all transcriptomic subtypes (HR range, 0.48-0.68). There was significant co-occurrence of RB loss and HRR gene aberrations; RB loss was further associated with favorable survival within HRR-aberrant cases (multivariable HR, 0.50).

CONCLUSIONS

These data paint a high-resolution picture of the molecular landscape in HGSOC, better defining patients who may benefit most from specific molecular therapeutics and highlighting those for whom novel treatment strategies are needed to improve outcomes.

Genomic profiling identifies distinct genetic subtypes in extra-nodal natural killer/T-cell lymphoma

Extra-nodal NK/T-cell lymphoma, nasal type (ENKTCL) is a highly aggressive Epstein-Barr virus associated lymphoma, typically presenting in the nasal and paranasal areas. We assembled a large series of ENKTCL (n = 209) for comprehensive genomic analysis and correlative clinical study. The International Lymphoma Prognostic Index (IPI), site of disease, stage, lymphadenopathy, and hepatomegaly were associated with overall survival. Genetic analysis revealed frequent oncogenic activation of the JAK/STAT3 pathway and alterations in tumor suppressor genes (TSGs) and genes associated with epigenomic regulation. Integrated genomic analysis including recurrent mutations and genomic copy number alterations using consensus clustering identified seven distinct genetic clusters that were associated with different clinical outcomes, thus constituting previously unrecognized risk groups. The genetic profiles of ENTKCLs from Asian and Hispanic ethnic groups showed striking similarity, indicating shared pathogenetic mechanism and tumor evolution. Interestingly, we discovered a novel functional cooperation between activating STAT3 mutations and loss of the TSG, PRDM1, in promoting NK-cell growth and survival. This study provides a genetic roadmap for further analysis and facilitates investigation of actionable therapeutic opportunities in this aggressive lymphoma.

Adult NTRK-rearranged spindle cell neoplasms of the viscera: with an emphasis on rare locations and heterologous elements

NTRK-rearranged mesenchymal neoplasms mostly affect the soft tissues of pediatric patients. Given the responsiveness to selective NTRK inhibitors, it remains critical to identify those ultra-rare cases occurring in the viscera of adults. In five females and two males aged 18-53 years, we characterized visceral mesenchymal tumors harboring TPM3-NTRK1 [uterine cervix (N = 2), pleura, prostate], LMNA-NTRK1 (lung), SQSTM1-NTRK3 (heart), and NTRK3 rearrangement with unknown fusion partner (colon/mesocolon) with RNA sequencing, FISH, RT-PCR, and immunohistochemistry. The tumors exhibited spindled to ovoid/epithelioid or pleomorphic cells, often arranged in fascicles, and were low-to-intermediate-grade and high-grade in three and four cases, respectively. Keloid-like stromal collagen and perivascular hyalinization was noted in five. Adenosarcoma-like appearances were observed in two, manifesting frond-like protrusions in one cervical tumor and phyllodes-like architecture in the prostatic tumor. Abrupt high-grade transformation into pleomorphic liposarcoma was found in another cervical tumor, while the pleural tumor contained intermixed rhabdomyoblasts. Pan-TRK immunostaining was positive in all cases. All cases expressed CD34, while five were S100-positive. CDKN2A homozygous deletion with concomitant p16 loss occurred in 4/7. Whole-exome sequencing identified TP53 mutation (c.672+2T>C, involving a splice site, with concomitant protein loss) in a cervical sarcoma, limited to its heterologous liposarcomatous component. At least moderate pan-TRK immunoreactivity was present in varying proportions of potential pathologic mimics, with BCOR-positive sarcoma (56%, 5/9), undifferentiated uterine sarcoma (50%, 3/6), and spindle cell/sclerosing rhabdomyosarcoma (33%, 2/6) being among the most frequent. This underscored the unsatisfactory specificity of pan-TRK immunohistochemistry and warranted molecular confirmation in the diagnosis of adult NTRK-rearranged visceral mesenchymal neoplasms. The current report highlights the ever-expanding clinicopathologic and genetic spectrum of this entity by describing the unprecedented cardiac and pleural locations and heterologous differentiation, as well as the second NTRK-rearranged "prostatic stromal sarcoma," while substantiating CDKN2A deletion as a frequent occurrence.

Molecular characterization of low-grade serous ovarian carcinoma identifies genomic aberrations according to hormone receptor expression

Hormone receptor expression is a characteristic of low-grade serous ovarian carcinoma (LGSOC). Studies investigating estrogen receptor (ER) and progesterone receptor (PR) expression levels suggest its prognostic and predictive significance, although their associations with key molecular aberrations are not well understood. As such, we sought to describe the specific genomic profiles associated with different ER/PR expression patterns and survival outcomes in a cohort of patients with advanced disease. The study comprised fifty-five advanced-staged (III/IV) LGSOCs from the Canadian Ovarian Experimental Unified Resource (COEUR) for which targeted mutation sequencing, copy-number aberration, clinical and follow-up data were available. ER, PR, and p16 expression were assessed by immunohistochemistry. Tumors were divided into low and high ER/PR expression groups based on Allred scoring. Copy number analysis revealed that PR-low tumors (Allred score <2) had a higher fraction of the genome altered by copy number changes compared to PR-high tumors (p = 0.001), with cancer genes affected within specific loci linked to altered peptidyl-tyrosine kinase, MAP-kinase, and PI3-kinase signaling. Cox regression analysis showed that ER-high (p = 0.02), PR-high (p = 0.03), stage III disease (p = 0.02), low residual disease burden (p = 0.01) and normal p16 expression (p<0.001) were all significantly associated with improved overall survival. This study provides evidence that genomic aberrations are linked to ER/PR expression in primary LGSOC.

Risk assessment with low pass whole genome sequencing of cell free DNA before CD19 CAR T-cells for large B-cell lymphoma

FCS, defined by lpWGS of cfDNA, is associated with inferior outcomes in patients with LBCL treated with CAR T-cell therapy.

FCS, LDH, and number of extranodal sites significantly stratified outcomes in a large single center cohort of CAR T cell–treated patients.

Patients with relapsed or refractory large B-cell lymphomas (rrLBCL) can achieve long-term remission after CD19 chimeric antigen receptor T-cell therapy (CART19). However, more than half of recipients will experience treatment failure. Thus, approaches are needed to identify high-risk patients who may benefit from alternative or consolidative therapy. We evaluated low-pass whole-genome sequencing (lpWGS) of cell-free DNA (cfDNA) before CART19 as a new approach for risk stratification. We performed lpWGS on pretreatment plasma samples from 122 patients at time of leukapheresis who received standard-of-care CART19 for rrLBCL to define DNA copy number alterations (CNAs). In multivariable selection, high focal CNA score (FCS) denoting genomic instability was the most significant pretreatment variable associated with inferior 3-month complete response rates (28% vs 56%, P = .0029), progression-free survival (PFS; P = .0007; hazard ratio, 2.11), and overall survival (OS; P = .0026; hazard ratio, 2.10). We identified 34 unique focal CNAs in 108 (89%) patients; of these, deletion 10q23.3 leading to loss of FAS death receptor was the most highly associated with poor outcomes, leading to inferior PFS (P < .0001; hazard ratio, 3.49) and OS (P = .0027; hazard ratio, 2.68). By combining FCS with traditional markers of increased tumor bulk (elevated lactate dehydrogenase and >1 extranodal site), we built a simple risk model that could reliably risk stratify patients. Thus, lpWGS of cfDNA is a minimally invasive assay that could rapidly identify high-risk patients and may guide patient selection for and targeted therapies to evaluate in future clinical trials.

Computational analysis of cancer genome sequencing data

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer

BACKGROUND

The utility of circulating tumour DNA (ctDNA) for longitudinal tumour monitoring in pancreatic ductal adenocarcinoma (PDAC) has not been explored beyond mutations in the KRAS proto-oncogene. Here, we aimed to characterise and track patient-specific somatic ctDNA variants, to assess longitudinal changes in disease burden and explore the landscape of actionable alterations.

METHODS

We followed 3 patients with resectable disease and 4 patients with unresectable disease, including 4 patients with ≥ 3 serial follow-up samples, of whom 2 were rare long survivors (> 5 years). We performed whole exome sequencing of tumour gDNA and plasma ctDNA (n = 20) collected over a ~ 2-year period from diagnosis through treatment to death or final follow-up. Plasma from 3 chronic pancreatitis cases was used as a comparison for analysis of ctDNA mutations.

RESULTS

We detected > 55% concordance between somatic mutations in tumour tissues and matched serial plasma. Mutations in ctDNA were detected within known PDAC driver genes (KRAS, TP53, SMAD4, CDKN2A), in addition to patient-specific variants within alternative cancer drivers (NRAS, HRAS, MTOR, ERBB2, EGFR, PBRM1), with a trend towards higher overall mutation loads in advanced disease. ctDNA alterations with potential for therapeutic actionability were identified in all 7 patients, including DNA damage response (DDR) variants co-occurring with hypermutation signatures predictive of response to platinum chemotherapy. Longitudinal tracking in 4 patients with follow-up > 2 years demonstrated that ctDNA mutant allele fractions and clonal trends were consistent with CA19-9 measurements and/or clinically reported disease burden. The estimated prevalence of 'stem clones' was highest in an unresectable patient where changes in ctDNA dynamics preceded CA19-9 levels. Longitudinal evolutionary trajectories revealed ongoing subclonal evolution following chemotherapy.

CONCLUSION

These results provide proof-of-concept for the use of exome sequencing of serial plasma to characterise patient-specific ctDNA profiles, and demonstrate the sensitivity of ctDNA in monitoring disease burden in PDAC even in unresectable cases without matched tumour genotyping. They reveal the value of tracking clonal evolution in serial ctDNA to monitor treatment response, establishing the potential of applied precision medicine to guide stratified care by identifying and evaluating actionable opportunities for intervention aimed at optimising patient outcomes for an otherwise intractable disease.

Genomic and Molecular Signatures of Successful Patient-Derived Xenografts for Oral Cavity Squamous Cell Carcinoma

Background

Oral cavity squamous cell carcinoma (OSCC) is an aggressive malignant tumor with high recurrence and poor prognosis in the advanced stage. Patient-derived xenografts (PDXs) serve as powerful preclinical platforms for drug testing and precision medicine for cancer therapy. We assess which molecular signatures affect tumor engraftment ability and tumor growth rate in OSCC PDXs.

Methods

Treatment-naïve OSCC primary tumors were collected for PDX models establishment. Comprehensive genomic analysis, including whole-exome sequencing and RNA-seq, was performed on case-matched tumors and PDXs. Regulatory genes/pathways were analyzed to clarify which molecular signatures affect tumor engraftment ability and the tumor growth rate in OSCC PDXs.

Results

Perineural invasion was found as an important pathological feature related to engraftment ability. Tumor microenvironment with enriched hypoxia, PI3K-Akt, and epithelial–mesenchymal transition pathways and decreased inflammatory responses had high engraftment ability and tumor growth rates in OSCC PDXs. High matrix metalloproteinase-1 (MMP1) expression was found that have a great graft advantage in xenografts and is associated with pooled disease-free survival in cancer patients.

Conclusion

This study provides a panel with detailed genomic characteristics of OSCC PDXs, enabling preclinical studies on personalized therapy options for oral cancer. MMP1 could serve as a biomarker for predicting successful xenografts in OSCC patients.

Plasticity of Extrachromosomal and Intrachromosomal BRAF Amplifications in Overcoming Targeted Therapy Dosage Challenges

Focal amplifications (FA) can mediate targeted therapy resistance in cancer. Understanding the structure and dynamics of FAs is critical for designing treatments that overcome plasticity-mediated resistance. We developed a melanoma model of dual MAPK inhibitor (MAPKi) resistance that bears BRAFV600 amplifications through either extrachromosomal DNA (ecDNA)/double minutes (DM) or intrachromosomal homogenously staining regions (HSR). Cells harboring BRAFV600E FAs displayed mode switching between DMs and HSRs, from both de novo genetic changes and selection of preexisting subpopulations. Plasticity is not exclusive to ecDNAs, as cells harboring HSRs exhibit drug addiction-driven structural loss of BRAF amplicons upon dose reduction. FA mechanisms can couple with kinase domain duplications and alternative splicing to enhance resistance. Drug-responsive amplicon plasticity is observed in the clinic and can involve other MAPK pathway genes, such as RAF1 and NRAS. BRAF FA-mediated dual MAPKi-resistant cells are more sensitive to proferroptotic drugs, extending the spectrum of ferroptosis sensitivity in MAPKi resistance beyond cases of dedifferentiation.

SIGNIFICANCE

Understanding the structure and dynamics of oncogene amplifications is critical for overcoming tumor relapse. BRAF amplifications are highly plastic under MAPKi dosage challenges in melanoma, through involvement of de novo genomic alterations, even in the HSR mode. Moreover, BRAF FA-driven, dual MAPKi-resistant cells extend the spectrum of resistance-linked ferroptosis sensitivity. This article is highlighted in the In This Issue feature, p. 873.

SavvyCNV: Genome-wide CNV calling from off-target reads

Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this ‘free data’ to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.

We have created SavvyCNV, a new tool for calling genetic variants. Large regions of the genome can be deleted or duplicated–these variants can have important consequences, for example causing a patient’s genetic disease. However, many standard genetic tests only target a small fraction of the genome and will miss variants outside of these regions. Therefore, we developed a tool to exploit sequencing data which falls outside of these regions (due to flaws in the targeting process) to call large deletions and duplications. This allows large deletions and duplications to be detected anywhere in the genome. Researchers and diagnostic laboratories can use this tool to discover more genetic variants by re-analysing their sequencing data.

Integration of tumour sequencing and case-control data to assess pathogenicity of RAD51C missense variants in familial breast cancer

While protein-truncating variants in RAD51C have been shown to predispose to triple-negative (TN) breast cancer (BC) and ovarian cancer, little is known about the pathogenicity of missense (MS) variants. The frequency of rare RAD51C MS variants was assessed in the BEACCON study of 5734 familial BC cases and 14,382 population controls, and findings were integrated with tumour sequencing data from 21 cases carrying a candidate variant. Collectively, a significant enrichment of rare MS variants was detected in cases (MAF < 0.001, OR 1.57, 95% CI 1.00-2.44, p = 0.05), particularly for variants with a REVEL score >0.5 (OR 3.95, 95% CI 1.40-12.01, p = 0.006). Sequencing of 21 tumours from 20 heterozygous and 1 homozygous carriers of nine candidate MS variants identified four cases with biallelic inactivation through loss of the wild-type allele, while six lost the variant allele and ten that remained heterozygous. Biallelic loss of the wild-type alleles corresponded strongly with ER- and TN breast tumours, high homologous recombination deficiency scores and mutational signature 3. Using this approach, the p.Gly264Ser variant, which was previously suspected to be pathogenic based on small case-control analyses and loss of activity in in vitro functional assays, was shown to be benign with similar prevalence in cases and controls and seven out of eight tumours showing no biallelic inactivation or characteristic mutational signature. Conversely, evaluation of case-control findings and tumour sequencing data identified p.Ile144Thr, p.Arg212His, p.Gln143Arg and p.Gly114Arg as variants warranting further investigation.

Proteogenomic characterization identifies clinically relevant subgroups of intrahepatic cholangiocarcinoma

We performed proteogenomic characterization of intrahepatic cholangiocarcinoma (iCCA) using paired tumor and adjacent liver tissues from 262 patients. Integrated proteogenomic analyses prioritized genetic aberrations and revealed hallmarks of iCCA pathogenesis. Aflatoxin signature was associated with tumor initiation, proliferation, and immune suppression. Mutation-associated signaling profiles revealed that TP53 and KRAS co-mutations may contribute to iCCA metastasis via the integrin-FAK-SRC pathway. FGFR2 fusions activated the Rho GTPase pathway and could be a potential source of neoantigens. Proteomic profiling identified four patient subgroups (S1-S4) with subgroup-specific biomarkers. These proteomic subgroups had distinct features in prognosis, genetic alterations, microenvironment dysregulation, tumor microbiota composition, and potential therapeutics. SLC16A3 and HKDC1 were further identified as potential prognostic biomarkers associated with metabolic reprogramming of iCCA cells. This study provides a valuable resource for researchers and clinicians to further identify molecular pathogenesis and therapeutic opportunities in iCCA.

Precision Medicine through Next-Generation Sequencing in Inherited Eye Diseases in a Korean Cohort

In this study, we investigated medically or surgically actionable genes in inherited eye disease, based on clinical phenotype and genomic data. This retrospective consecutive case series included 149 patients with inherited eye diseases, seen by a single pediatric ophthalmologist, who underwent genetic testing between 1 March 2017 and 28 February 2018. Variants were detected using a target enrichment panel of 429 genes and known deep intronic variants associated with inherited eye disease. Among 149 patients, 38 (25.5%) had a family history, and this cohort includes heterogeneous phenotype including anterior segment dysgenesis, congenital cataract, infantile nystagmus syndrome, optic atrophy, and retinal dystrophy. Overall, 90 patients (60.4%) received a definite molecular diagnosis. Overall, NGS-guided precision care was provided to 8 patients (5.4%). The precision care included cryotherapy to prevent retinal detachment in COL2A1 Stickler syndrome, osteoporosis management in patients with LRP5-associated familial exudative vitreoretinopathy, and avoidance of unnecessary phlebotomy in hyperferritinemia-cataract syndrome. A revision of the initial clinical diagnosis was made in 22 patients (14.8%). Unexpected multi-gene deletions and dual diagnosis were noted in 4 patients (2.7%). We found that precision medical or surgical managements were provided for 8 of 149 patients (5.4%), and multiple locus variants were found in 2.7% of cases. These findings are important because individualized management of inherited eye diseases can be achieved through genetic testing.

High resolution copy number inference in cancer using short-molecule nanopore sequencing

Genome copy number is an important source of genetic variation in health and disease. In cancer, Copy Number Alterations (CNAs) can be inferred from short-read sequencing data, enabling genomics-based precision oncology. Emerging Nanopore sequencing technologies offer the potential for broader clinical utility, for example in smaller hospitals, due to lower instrument cost, higher portability, and ease of use. Nonetheless, Nanopore sequencing devices are limited in the number of retrievable sequencing reads/molecules compared to short-read sequencing platforms, limiting CNA inference accuracy. To address this limitation, we targeted the sequencing of short-length DNA molecules loaded at optimized concentration in an effort to increase sequence read/molecule yield from a single nanopore run. We show that short-molecule nanopore sequencing reproducibly returns high read counts and allows high quality CNA inference. We demonstrate the clinical relevance of this approach by accurately inferring CNAs in acute myeloid leukemia samples. The data shows that, compared to traditional approaches such as chromosome analysis/cytogenetics, short molecule nanopore sequencing returns more sensitive, accurate copy number information in a cost effective and expeditious manner, including for multiplex samples. Our results provide a framework for short-molecule nanopore sequencing with applications in research and medicine, which includes but is not limited to, CNAs.

Multiparametric Circulating Tumor Cell Analysis to Select Targeted Therapies for Breast Cancer Patients

Simple Summary

Liquid biopsies may act as a dynamic tool for identification of targets for precision therapy while circumventing limitations of tissue biopsies. In opposite to most liquid biopsy-related studies that analyze limited patient material for only one parameter, this study is based on a longitudinal and multiparametric analysis of circulating tumor cells (CTCs). A metastatic breast cancer patient was followed over a period of three years and analyses of the genome, RNA profiling, and in vitro drug testing on cultured CTCs were performed in a unique manner. We show that combining the strengths of multiple technologies for analysis yielded maximum information on the ongoing disease and, eventually, allowed choosing an effective therapy, which led to a massive reduction in CTC numbers. This approach provides a concept for future detailed longitudinal and multiparametric CTC analyses.

Abstract

Background: The analysis of liquid biopsies, e.g., circulating tumor cells (CTCs) is an appealing diagnostic concept for targeted therapy selection. In this proof-of-concept study, we aimed to perform multiparametric analyses of CTCs to select targeted therapies for metastatic breast cancer patients. Methods: First, CTCs of five metastatic breast cancer patients were analyzed by whole exome sequencing (WES). Based on the results, one patient was selected and monitored by longitudinal and multiparametric liquid biopsy analyses over more than three years, including WES, RNA profiling, and in vitro drug testing of CTCs. Results: Mutations addressable by targeted therapies were detected in all patients, including mutations that were not detected in biopsies of the primary tumor. For the index patient, the clonal evolution of the tumor cells was retraced and resistance mechanisms were identified. The AKT1 E17K mutation was uncovered as the driver of the metastatic process. Drug testing on the patient’s CTCs confirmed the efficacy of drugs targeting the AKT1 pathway. During a targeted therapy chosen based on the CTC characterization and including the mTOR inhibitor everolimus, CTC numbers dropped by 97.3% and the disease remained stable as determined by computer tomography/magnetic resonance imaging. Conclusion: These results illustrate the strength of a multiparametric CTC analysis to choose and validate targeted therapies to optimize cancer treatment in the future. Furthermore, from a scientific point of view, such studies promote the understanding of the biology of CTCs during different treatment regimens.

Mutant clones in normal epithelium outcompete and eliminate emerging tumours

Human epithelial tissues accumulate cancer-driver mutations with age1-9, yet tumour formation remains rare. The positive selection of these mutations suggests that they alter the behaviour and fitness of proliferating cells10-12. Thus, normal adult tissues become a patchwork of mutant clones competing for space and survival, with the fittest clones expanding by eliminating their less competitive neighbours11-14. However, little is known about how such dynamic competition in normal epithelia influences early tumorigenesis. Here we show that the majority of newly formed oesophageal tumours are eliminated through competition with mutant clones in the adjacent normal epithelium. We followed the fate of nascent, microscopic, pre-malignant tumours in a mouse model of oesophageal carcinogenesis and found that most were rapidly lost with no indication of tumour cell death, decreased proliferation or an anti-tumour immune response. However, deep sequencing of ten-day-old and one-year-old tumours showed evidence of selection on the surviving neoplasms. Induction of highly competitive clones in transgenic mice increased early tumour removal, whereas pharmacological inhibition of clonal competition reduced tumour loss. These results support a model in which survival of early neoplasms depends on their competitive fitness relative to that of mutant clones in the surrounding normal tissue. Mutant clones in normal epithelium have an unexpected anti-tumorigenic role in purging early tumours through cell competition, thereby preserving tissue integrity.

Subtype heterogeneity and epigenetic convergence in neuroendocrine prostate cancer

Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyze cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single-cell analysis of human clinical samples exhibits a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall, our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.

Neuroendocrine carcinomas (NECs) arise from different anatomic sites, but have similar histological and clinical features. Here, the authors show that the epigenetic landscape of a range of NECs converges towards a common epigenetic state, while distinct subtypes occur within neuroendocrine prostate cancer contributing to intratumor heterogeneity in clinical samples.

A Local Outlier Factor-Based Detection of Copy Number Variations From NGS Data

Copy number variation (CNV) is a major type of genomic structural variations that play an important role in human disorders. Next generation sequencing (NGS) has fueled the advancement in algorithm design to detect CNVs at base-pair resolution. However, accurate detection of CNVs of low amplitudes remains a challenging task. This paper proposes a new computational method, CNV-LOF, to identify CNVs of full-range amplitudes from NGS data. CNV-LOF is distinctly different from traditional methods, which mainly consider aberrations from a global perspective and rely on some assumed distribution of NGS read depths. In contrast, CNV-LOF takes a local view on the read depths and assigns an outlier factor to each genome segment. With the outlier factor profile, CNV-LOF uses a boxplot procedure to declare CNVs without the reliance of any distribution assumptions. Simulation experiments indicate that CNV-LOF outperforms five existing methods with respect to F1-measure, sensitivity, and precision. CNV-LOF is further validated on real sequencing samples, yielding highly consistent results with peer methods. CNV-LOF is able to detect CNVs of low and moderate amplitudes where the other existing methods fail, and it is expected to become a routine approach for the discovery of novel CNVs on whole sequencing genome.

Reprogramming of bivalent chromatin states in NRAS mutant melanoma suggests PRC2 inhibition as a therapeutic strategy

The dynamic evolution of chromatin state patterns during metastasis, their relationship with bona fide genetic drivers, and their therapeutic vulnerabilities are not completely understood. Combinatorial chromatin state profiling of 46 melanoma samples reveals an association of NRAS mutants with bivalent histone H3 lysine 27 trimethylation (H3K27me3) and Polycomb repressive complex 2. Reprogramming of bivalent domains during metastasis occurs on master transcription factors of a mesenchymal phenotype, including ZEB1, TWIST1, and CDH1. Resolution of bivalency using pharmacological inhibition of EZH2 decreases invasive capacity of melanoma cells and markedly reduces tumor burden in vivo, specifically in NRAS mutants. Coincident with bivalent reprogramming, the increased expression of pro-metastatic and melanocyte-specific cell-identity genes is associated with exceptionally wide H3K4me3 domains, suggesting a role for this epigenetic element. Overall, we demonstrate that reprogramming of bivalent and broad domains represents key epigenetic alterations in metastatic melanoma and that EZH2 plus MEK inhibition may provide a promising therapeutic strategy for NRAS mutant melanoma patients.

CoBRA: Containerized Bioinformatics Workflow for Reproducible ChIP/ATAC-seq Analysis

Chromatin immunoprecipitation sequencing (ChIP-seq) and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) have become essential technologies to effectively measure protein–DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples, correction of copy number variations, and integration of new downstream analysis tools. Here we present Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis (CoBRA), a modularized computational workflow which quantifies ChIP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses. CoBRA provides a comprehensive state-of-the-art ChIP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience. This enables researchers to gain rapid insight into protein–DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference database, and pathway analysis. CoBRA is publicly available online at https://bitbucket.org/cfce/cobra

Comparison of the oncogenomic landscape of canine and feline hemangiosarcoma shows novel parallels with human angiosarcoma

Angiosarcoma (AS) is a highly aggressive tumor of blood and lymphatic vessels in humans that shares many similarities with spontaneously occurring hemangiosarcoma (HSA) in dogs and cats. To investigate the genetic suitability of HSA as a model for AS, we sequenced ∼1000 cancer genes in 41 cases of HSA and matched germline tissue: 15 canine visceral HSAs, 13 canine skin HSAs and 13 feline skin HSAs. Analysis of visceral HSAs from dogs presenting with concurrent splenic and cardiac neoplasms showed that the tumors were not independent primaries, consistent with the highly metastatic nature of HSA. Comparison of HSA to AS revealed that several driver genes were recurrently mutated in both species, such as TP53, PIK3CA, ATRX, GRIN2A and LRP1B. Similar to AS, a UV mutational signature was found in a subset of canine cutaneous HSAs and both species show differing mutational profiles between tissue sites. Our characterization of canine and feline HSA demonstrates many important parallels to AS and provides hope that future studies on these cancers will benefit of all three species.

CIRCNV: Detection of CNVs Based on a Circular Profile of Read Depth from Sequencing Data

Simple Summary

In this study, we propose a copy number variation (CNV) detection method called CIRCNV, which is based on a circular profile of the read depth from sequencing data. The proposed method is an extended version of our previously developed method CNV-LOF. The main difference of CIRCNV from CNV-LOF lies in its two new features: (1) it transfers the read depth profile from a line shape to a circular shape via a polar coordinate transformation to generate a meaningful two-dimensional dataset for CNV analysis and promote fairness between the ends and middle part of the genome, and (2) it performs two rounds of CNV declaration via estimating tumor purity and recovering the truth circular RD profile. We test and evaluate the performance of CIRCNV via conducting simulation studies and real sequencing tumor sample applications. The experimental results show that CIRCNV outperforms peer methods with respect to sensitivity, precision, and the F1-score. The experiments prove that the proposed method is a reliable and effective tool in the field of variation analysis of tumor genomes.

Abstract

Copy number variation (CNV) is a common type of structural variation in the human genome. Accurate detection of CNVs from tumor genomes can provide crucial information for the study of tumor genesis and cancer precision diagnosis. However, the contamination of normal genomes in tumor genomes and the crude profiles of the read depth make such a task difficult. In this paper, we propose an alternative approach, called CIRCNV, for the detection of CNVs from sequencing data. CIRCNV is an extension of our previously developed method CNV-LOF, which uses local outlier factors to predict CNVs. Comparatively, CIRCNV can be performed on individual tumor samples and has the following two new features: (1) it transfers the read depth profile from a line shape to a circular shape via a polar coordinate transformation, in order to improve the efficiency of the read depth (RD) profile for the detection of CNVs; and (2) it performs a second round of CNV declaration based on the truth circular RD profile, which is recovered by estimating tumor purity. We test and validate the performance of CIRCNV based on simulation and real sequencing data and perform comparisons with several peer methods. The results demonstrate that CIRCNV can obtain superior performance in terms of sensitivity and precision. We expect that our proposed method will be a supplement to existing methods and become a routine tool in the field of variation analysis of tumor genomes.