Somatic Structural Variants Research Articles

Abstract 3786: Genomic and transcriptomic characterization of peritoneal, lung and liver metastases of colorectal carcinoma reveals site-specific differences

Abstract Background: Metastasis in colorectal cancer (CRC) is a critical factor in patient outcomes, with 20% of patients affected at the time of diagnosis and up to 50% developing metachronous metastatic disease later on. Despite the growing importance of metastatic sites as independent predictors of overall survival (OS) and the ongoing development of new treatments, there has been limited effort to personalize systemic treatment based on specific metastatic locations. Aim: This study aims to compare the genomic landscape of different metastatic sites in CRC to detect novel diagnostic and therapeutic targets. Methods: DNA whole-genome-sequencing and RNA gene expression data from metastatic CRC samples were retrieved from the Hartwig Medical Foundation (HMF). Single nucleotide variants (SNVs), somatic copy number aberrations (SCNAs) and structural variants (SVs) were reported by HMF with their pipelines. In addition, focal amplifications and deletions were identified using GISTIC2 (v6.15.30). We included 464 microsatellite stable samples derived from liver metastases (n=369), peritoneal metastases (n=58) and lung metastases (n=37). We compared DNA mutation frequencies between tumors from different metastatic sites (two-sided Mann-Whitney tests) and performed differential gene expression and pathway enrichment analysis. Results: Liver metastases had the highest number of focal SCNAs per sample (median 33 vs 17 in peritoneum (p < 0.001); vs 18 in lung (p < 0.001)). Furthermore, we observed 39 site-specific SCNAs in liver, 9 in peritoneal and 15 in lung metastases. Of these, the most significant focal SCNAs were an amplification within 20q13.12 (79%) and deletion within 1p35.3 (64%) in peritoneal metastases and a deletion within 18q21.1 (84%) in lung metastases. Furthermore, peritoneal metastases displayed less genomic instability, featuring lower ploidy (median 2.65 vs 2.94 in liver (p=0.025); vs 3.15 in lung (p=0.025)) and lower aneuploidy scores (median 19 vs 26 in liver (p=0.016); vs 30 in lung (p=0.016)) while having no significant differences in tumor mutational burden or individual SNVs. Analysis of SVs revealed that peritoneal metastases exhibited fewer deletions (≥10kb; 1.3x fold change increase in liver and lung) and fewer duplications (≥1kb; 1.4x fold change increase in liver). Differential gene expression analysis uncovered higher expression of gene sets involved in the apical junction and the TGF-beta-signaling pathway in peritoneal metastases. Conclusion: Specific focal SCNA and differences in genomic instability exhibit an association with preferential organotropism in CRC metastasis and could offer potential targets for the development of new diagnostic and therapeutic approaches. Citation Format: Nerma Crnovrsanin, Soufyan Lakbir, Renske d. Wit, Steven L. Ketelaars, Niels F. Kok, Petur Snaebjornsson, Gerrit A. Meijer, Sanne Abeln, Remond J. Fijneman. Genomic and transcriptomic characterization of peritoneal, lung and liver metastases of colorectal carcinoma reveals site-specific differences [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3786.

Abstract 5665: Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma

Abstract Osteosarcoma (OS) is an aggressive bone malignancy affecting children and young adults. Implementation and optimization of neoadjuvant chemotherapy led to significant improvements in outcome, but patients with recurrence or metastases at diagnosis continue to have poor prognosis. Whole genome sequencing (WGS) revealed that a hallmark of OS is a highly rearranged genome with complex copy number aberrations rather than point mutations. A better understanding of the key genomic and epigenetic factors driving clonal evolution may provide insights into the tumor progression and the therapy response. Canine OS recapitulates the majority of the hallmark genetic and molecular factors of human OS and is recognized as an informative model. A significant difference is that initial surgery in canine OS allows us to explore tumor evolution unperturbed by treatment, providing invaluable resources to study the genetic and molecular landscape of tumor evolution. Here, we present the first study to date in which we performed bulk WGS of multiple tumor sites and distal normal tissue in two dogs using nanopore long-read sequencing to analyze the genetic and epigenetic evolution of OS. In both subjects, somatic structural variation detection using Severus revealed chromothripsis-like rearrangements in chr11, leading to the deletion of Cdkn2a, a known cell cycle regulator and tumor suppressor. Interestingly, in one of the subjects, the majority of the SVs (n = 131) shared across all the samples were localized on chr5, coinciding with perturbed copy number profiles and bi-allelic frequency of the SNVs, with all mutations identified using complementary bioinformatics analysis of the same native nanopore reads. The multi-site sample analysis identified subclonal structural alterations in TP53 and ATRX genes. With phased nanopore reads, we observed subject-specific copy-neutral loss-of-heterozygosity events and long identical-by-descent blocks. Haplotype-specific copy-number analysis of tumors showed different aneuploidy patterns in both subjects, highlighted clonal compositions of samples from distinct sites, and identified regions of copy-number heterogeneity. Furthermore, phased nanopore reads also revealed haplotype-specific 5mC and 5hmC methylation differences across tumor samples, where samples from different sites of the same tumor demonstrate distinct methylation patterns that overlap DLG2, RUNX2, KDR, and other genes known as mutational hotspots in canine/human OS. Overall, we showcase how a single sequencing assay allows for a joint analysis of genetic and epigenetic tumor alterations, thus providing a richer understanding of the drivers of somatic evolution and their association with the molecular landscape in the canine OS. These findings can be translated into human disease and shed light on tumor progression and therapy response. Citation Format: Ayse Keskus, Sergey Aganezov, Tanveer Ahmad, Xiaoguang Dai, Robert Walker, John Beaulaurier, Scott Hickey, Sissel Juul, Amy Kathleen LeBlanc, Paul S. Meltzer, Mikhail Kolmogorov. Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5665.

Abstract 4336: Homologous recombination repair deficiency, and not recurrence, determines mutational burden and clonal dynamics in high grade serous ovarian cancer

Abstract High grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy, killing more than 9,000 women each year in the United States. Nearly 80% of patients with HGSOC will experience recurrence within 5 years, but little is known about the mechanisms that drive this process. Up to 60% of the genome in an HGSOC tumor is impacted by structural variant mutations and pronounced intratumoral heterogeneity. Intratumor heterogeneity is believed to be a key feature of recurrence and therapy resistance with some evidence indicating diverse and complex mechanisms of the seeding of metastatic sites and recurrent tumors. We included 35 HGSOC patients for whom paired chemo-naive and chemoresistant tumors as well as germline DNA was available. Whole genome sequencing was used to identify somatic single nucleotide variants (SNV) insertion/deletion variants (indels), and structural variants (SVs) in each tumor. The number of somatic SVs and indels was higher in tumors with homologous recombination repair deficiency (HRD; P=0.000252 SVs, P=0.00385 Indel) but was not affected by recurrent status (P=0.826 SV, P=0.145 SNV/indel). Clonal composition and dynamics were measured using SNVs/indels as tumors progressed from chemo-naïve primary samples to recurrent chemo-resistant tumors. Surprisingly, few changes were observed in clonal abundance and complexity through progression. When this analysis was repeated with SVs homologous recombination repair proficient tumors tend to be polyclonal while HRD tumors tend to be monoclonal. Five denovo structural variant signatures were identified in our cohort and led to three distinct structural variant classes tumors defined by deletion, tumors defined by duplication, and tumors defined by copy number neutral changes (inversions, translocations and balanced complex events). Patients with tumors defined by deletions and copy number neutral changes carry pathogenic SVs correlating with reduced survival (P=0.00023), while DNA gains are less subject to pathogenic alterations. Each class displayed distinct regions of the chromosome that was frequently affected by large scale SV events (>5Mb), which was also observed in the HRP/HRD status. Although no regions were notably altered across recurrence, GO analysis revealed that recurrent tumors have a significantly reduced immune response, which was not seen in the primary tumors. Within a subset of tumors, we are plan to utilize Oxford Nanopore Technologies ultra long read sequencing which will allow for confirmation of SVs observed in the WGS as well as identification of more complex events that cannot be deciphered using WGS techniques. Citation Format: Michael A. Diaz, Nicole Gull, Pei-Chen Peng, Kate Lawrenson, Bobbie J. Rimel, Jenny Lester, Beth Karlan, Simon A. Gayther, Michelle R. Jones. Homologous recombination repair deficiency, and not recurrence, determines mutational burden and clonal dynamics in high grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4336.

Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection.

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs. However, structural variant discovery by short-read sequencing is challenging, primarily because of the difficulty in mapping regions of repetitive sequences. Optical genome mapping (OGM) is a recent technology used for imaging and assembling long DNA strands to detect structural variations. To capture the structural variant landscape more thoroughly in the human genome, we developed an integrated pipeline that combines Bionano OGM and Illumina whole-genome sequencing and applied it to samples from 29 pediatric B-ALL patients. The addition of OGM allowed us to identify 511 deletions, 506 insertions, 93 duplications/gains, and 145 translocations that were otherwise missed in the short-read data. Moreover, we identified several novel gene fusions, the expression of which was confirmed by RNA sequencing. Our results highlight the benefit of integrating OGM and short-read detection methods to obtain a comprehensive analysis of genetic variation that can aid in clinical diagnosis, provide new therapeutic targets, and improve personalized medicine in cancers driven by structural variation.

Abstract PR-012: Proteogenomic analysis of enriched tumor epithelium identifies prognostic signatures and an increased dependency of homologous recombination proficient cells on bmi1 in high grade serous ovarian cancer

Abstract Background: Proteogenomic characterization efforts of high-grade serous ovarian cancer (HGSOC) have largely assessed tumors with high tumor cellularity (“purity”) to enhance detection of cancer-related biomarkers. Comprehensive analyses of cancers independent of purity are needed to reflect a “real-world” spectrum of patient phenotypes. To improve identification of clinically relevant molecular alterations associated with HGSOC independent of tumor purity, we applied cellular enrichment techniques coupled with comprehensive multi-omic analyses in HGSOC patient tumors spanning a broad spectrum of purity. Methods: Seventy HGSOC patient tumors were selected exhibiting low to high tumor purity (20-90%) balanced by clinical outcomes. Whole genome sequencing (WGS), mRNA-seq, quantitative global proteomics, methylation array and reverse phase protein array analyses of Bulk Tumor and laser microdissected (LMD) Enriched Tumor (ET) cells separately for each case. Prognostic and homologous recombination deficient (HRD) expression signatures were validated in two independent cohorts. Results: Analysis of WGS in ET compared to WT resulted in significant increases in sensitivity to identify somatic SNV, indel, structural variants, and neoepitopes (SNV p = 4.8E−3; indel p = 7.7E−5; SV, p = 1.1E−8, neoepitopes, p= 1.0E−10). Following LMD, 63% of cases characterized as mesenchymal subtype (C4) in WT samples were reclassified to other molecular subtypes (1.0E−3) suggesting that historical HGSOC expression subtypes strongly reflect tumor purity. Analysis of paired primary and metastatic tumors demonstrated that WT proteomic profiles largely cluster by anatomic location while ET proteomic profiles co-cluster in a patient centric manner. Hierarchical cluster analysis identified patients with longer progression free survival associated with increased immune signatures and validated proteins correlating with tumor infiltrating lymphocytes (TILs) in 65 tumors collected from an independent cohort of 12 HGSOC patients, as well as with overall survival in an additional cohort of 126 HGSOC patients. We identified that homologous recombination deficient (HRD) tumors express transcriptomic and proteomic pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts, including 69 HRD-positive HGSOC tumors. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells exhibit increased sensitivity to BMI-1 inhibition. Conclusion: Proteogenomic alterations in HGSOC tumors uncovered using enrichment techniques highlight the importance of specimen preparation in the identification of tumor alterations. Our efforts provide insights into low purity HGSOC correlating TILs with improved disease prognosis, expression alterations associated with HRD status, and increased sensitivity of HRP tumor cells to BMI-1 inhibitors. Citation Format: George Larry Maxwell, Nicholas Bateman, Tamara Abulez, Anthony Soltis, Andrew McPherson, Seongmin Choi, Dale Garsed, Chunqiao Tian, Brian Hood, Kelly Conrads, Pang-ning Teng, Julie Oliver, Glenn Gist, Dave Mitchell, Tracy Litzi, Christopher Tarney, Clifton Dalgard, Matthew Wilkerson, Mariaelena Pierobon, Emmanuel Petricoin, Chunhua Yan, Daoud Meerzaman, Clara Bodelon, Nicolas Wentzensen, Jerry S. H. Lee, David Huntsman, Sohrab Shah, Craig Shriver, Neil Phippen, Kathleen Darcy, David Bowtell, Thomas Conrads. Proteogenomic analysis of enriched tumor epithelium identifies prognostic signatures and an increased dependency of homologous recombination proficient cells on bmi1 in high grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr PR-012.

Long-read sequencing unveils novel somatic variants and methylation patterns in the genetic information system of early lung cancer

Lung cancer poses a global health challenge, necessitating advanced diagnostics for improved outcomes. Intensive efforts are ongoing to pinpoint early detection biomarkers, such as genomic variations and DNA methylation, to elevate diagnostic precision. We conducted long-read sequencing on cancerous and adjacent non-cancerous tissues from a patient with lung adenocarcinoma. We identified somatic structural variations (SVs) specific to lung cancer by integrating data from various SV calling methods and differentially methylated regions (DMRs) that were distinct between these two tissue samples, revealing a unique methylation pattern associated with lung cancer. This study discovered over 40,000 somatic SVs and over 180,000 DMRs linked to lung cancer. We identified approximately 700 genes of significant relevance through comprehensive analysis, including genes intricately associated with many lung cancers, such as NOTCH1, SMOC2, CSMD2, and others. Furthermore, we observed that somatic SVs and DMRs were substantially enriched in several pathways, such as axon guidance signaling pathways, which suggests a comprehensive multi-omics impact on lung cancer progression across various biological investigation levels. These datasets can potentially serve as biomarkers for early lung cancer detection and may hold significant value in clinical diagnosis and treatment applications.

Genetic Characterization of Primary Mediastinal B-Cell Lymphoma: Pathogenesis and Patient Outcomes.

Primary mediastinal large B-cell lymphoma (PMBCL) is a rare aggressive lymphoma predominantly affecting young female patients. Large-scale genomic investigations and genetic markers for risk stratification are lacking. To elucidate the full spectrum of genomic alterations, samples from 340 patients with previously untreated PMBCL were investigated by whole-genome (n = 20), whole-exome (n = 78), and targeted (n = 308) sequencing. Statistically significant prognostic variables were identified using a multivariable Cox regression model and confirmed by L1/L2 regularized regressions. Whole-genome sequencing revealed a commonly disrupted p53 pathway with nonredundant somatic structural variations (SVs) in TP53-related genes (TP63, TP73, and WWOX) and identified novel SVs facilitating immune evasion (DOCK8 and CD83). Integration of mutation and copy-number data expanded the repertoire of known PMBCL alterations (eg, ARID1A, P2RY8, and PLXNC1) with a previously unrecognized role for epigenetic/chromatin modifiers. Multivariable analysis identified six genetic lesions with significant prognostic impact. CD58 mutations (31%) showed the strongest association with worse PFS (hazard ratio [HR], 2.52 [95% CI, 1.50 to 4.21]; P < .001) and overall survival (HR, 2.33 [95% CI, 1.14 to 4.76]; P = .02). IPI high-risk patients with mutated CD58 demonstrated a particularly poor prognosis, with 5-year PFS and OS rates of 41% and 58%, respectively. The adverse prognostic significance of the CD58 mutation status was predominantly observed in patients treated with nonintensified regimens, indicating that dose intensification may, to some extent, mitigate the impact of this high-risk marker. By contrast, DUSP2-mutated patients (24%) displayed durable responses (PFS: HR, 0.2 [95% CI, 0.07 to 0.55]; P = .002) and prolonged OS (HR, 0.11 [95% CI, 0.01 to 0.78]; P = .028). Upon CHOP-like treatment, these patients had very favorable outcome, with 5-year PFS and OS rates of 93% and 98%, respectively. This large-scale genomic characterization of PMBCL identified novel treatment targets and genetic lesions for refined risk stratification. DUSP2 and CD58 mutation analyses may guide treatment decisions between rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone and dose-adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab.

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

Whole-genome sequencing studies of human tumours have revealed that complex forms of structural variation, collectively known as complex genome rearrangements (CGRs), are pervasive across diverse cancer types. Detection, classification, and mechanistic interpretation of CGRs requires the visualization of complex patterns of somatic copy number aberrations (SCNAs) and structural variants (SVs). However, there is a lack of tools specifically designed to facilitate the visualization and study of CGRs. We present ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort. Overall, ReConPlot facilitates the exploration, interpretation, and reporting of CGR patterns. The R package ReConPlot is available at https://github.com/cortes-ciriano-lab/ReConPlot. Detailed documentation and a tutorial with examples are provided with the package.

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

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes $$\\end{document} sequencing coverage experiments requires 4–5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

Comprehensive genomic profiling reveals prognostic signatures and insights into the molecular landscape of colorectal cancer.

Colorectal cancer (CRC) is a prevalent malignancy with diverse molecular characteristics. The NGS-based approach enhances our comprehension of genomic landscape of CRC and may guide future advancements in precision oncology for CRC patients. In this research, we conducted an analysis using Next-Generation Sequencing (NGS) on samples collected from 111 individuals who had been diagnosed with CRC. We identified somatic and germline mutations and structural variants across the tumor genomes through comprehensive genomic profiling. Furthermore, we investigated the landscape of driver mutations and their potential clinical implications. Our findings underscore the intricate heterogeneity of genetic alterations within CRC. Notably, BRAF, ARID2, KMT2C, and GNAQ were associated with CRC prognosis. Patients harboring BRAF, ARID2, or KMT2C mutations exhibited shorter progression-free survival (PFS), whereas those with BRAF, ARID2, or GNAQ mutations experienced worse overall survival (OS). We unveiled 80 co-occurring and three mutually exclusive significant gene pairs, enriched primarily in pathways such as TP53, HIPPO, RTK/RAS, NOTCH, WNT, TGF-Beta, MYC, and PI3K. Notably, co-mutations of BRAF/ALK, BRAF/NOTCH2, BRAF/CREBBP, and BRAF/FAT1 correlated with worse PFS. Furthermore, germline AR mutations were identified in 37 (33.33%) CRC patients, and carriers of these variants displayed diminished PFS and OS. Decreased AR protein expression was observed in cases with AR germline mutations. A four-gene mutation signature was established, incorporating the aforementioned prognostic genes, which emerged as an independent prognostic determinant in CRC via univariate and multivariate Cox regression analyses. Noteworthy BRAF and ARID2 protein expression decreases detected in patients with their respective mutations. The integration of our analyses furnishes crucial insights into CRC's molecular characteristics, drug responsiveness, and the construction of a four-gene mutation signature for predicting CRC prognosis.

A Novel Comprehensive Tumor-Informed Plasma cfDNA Assay to Monitor Minimal Residual Disease for Hematological and Solid Malignancies

Background: Cell-free DNA (cfDNA) in peripheral blood plasma is a promising tool for monitoring minimal residual disease (MRD) in hematologic and solid malignancies. Unlike conventional biopsy methods, cfDNA extraction is non-invasive, and the short turnaround time enables the analysis of patient samples across multiple time points over an extended period to monitor disease progression. Currently available tests are difficult to scale because they detect only a limited number of mutations, require patient- and mutation-specific customization, and demand constant review by experts. Here, we describe a novel and comprehensive cfDNA testing platform encompassing all major clinically reliable genetic hotspots that we validated using plasma samples from a cancer patient cohort. We also analyzed plasma samples collected from a follicular lymphoma (FL) patient at multiple time points to illustrate disease relapse before clinical manifestation and to show the applicability of our assay in MRD testing. Methods: We constructed a panel of 216 clinically actionable genes, including exonic and intronic regions, capable of tracking point somatic mutations (SNVs/indels), structural variants, and microsatellite instability (MSI). To identify mutational events, we used deep sequencing (median exon coverage of at least 2000×) and a tumor-informed variant calling algorithm developed in-house. Next, we determined the limit of detection (LOD), sensitivity, and specificity of our assay using plasma samples from 74 patients with various solid cancer diagnoses. We tested our platform on standard reference dilutions (Seraseq® ctDNA Complete™ Mutation Mix 0.1%, 0.25%, 0.5%, 1%, 2.5%; Twist cfDNA Pan-cancer Reference Standard 0.1%, 0.25%, 0.5%, 1%, 2%) to validate our results. Our assay was validated by sequencing samples from the internal cohort (n = 74) in replicates and by repeat sequencing of the reference materials in various input amounts in triplicate. Finally, we analyzed plasma samples from an FL patient at five timepoints to showcase our ability to detect mutations in disease recurrence before clinical manifestation. Results: We established the capability of our assay using plasma samples from a cancer patient cohort (n = 74) and two sets of dilutions of reference materials. With an LOD &amp;gt; 0.05% variant allele frequency (VAF) and sequencing depth of more than 2000x our assay achieved a sensitivity of 93-97% and a specificity of 98-99%. It also detected a clonal hematopoiesis of indeterminate potential (CHIP) mutation in one plasma sample, implying that it was more sensitive than variant calling from solid tumors and may allow us to distinguish true somatic mutations from CHIP mutations. VAF comparison between two plasma replicates showed high correlation (Pearson's r &amp;gt; 0.99, p &amp;lt; 0.0001), indicating that our assay is robust and suitable for comparing samples from the same patient across multiple time points. Using different amounts of the reference cfDNA as the starting material for library preparation (15 ng, 25 ng, 50 ng), we assessed the variability of VAF to determine the error range associated with each amount used. By identifying the appropriate amount of starting material needed in order to maintain the LOD at 0.05% VAF across all samples analyzed, we were able to account for variations in cfDNA levels in plasma samples collected at different time points from the same patient. As such, it ensured the reliability of our test across all analyzed samples. We used our assay to analyze plasma samples from a patient diagnosed with stage III FL in 2014 who underwent six cycles of therapy with bendamustine and rituximab. The five plasma samples analyzed were collected in 2021, 2022, and 2023 ( Figure 1). Our assay detected clinically relevant mutations in samples from Mar 2021, which was 14 months earlier than mutation calling from blood cells. Conclusions: At a LOD of 0.05% VAF and with all performance metrics greater than 95%, our assay meets the requirements for MRD testing. Analysis of plasma samples from an FL patient also shows that our assay can detect clinically relevant mutations in plasma samples much earlier than mutation calling from blood cells. We will further validate our assay with more clinical samples and expand our scope to include structural variants and MSI, to further lower the LOD.

Genetic Profile of Myeloid Neoplasms Developed with Fanconi Anemia and Aldehyde Degradation Deficiency Syndrome

Background Fanconi anemia (FA) is an inherited bone marrow failure syndrome which develops on the basis of defective cellular responses to DNA damage. Aldehyde degradation deficiency (ADD) syndrome has been recently found as a disease caused by the defect of degradation of endogenous formaldehyde, which shares similar clinical features with FA. Although genomic abnormalities in these diseases have been associated with the high propensity of myeloid malignancies such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), the mechanism of the early development of MDS/AML remains unclear. Therefore, in this study, we aimed to understand the mechanism of the development of hematological malignancies by analyzing the genomic abnormalities seen in these diseases. Method We performed whole-exome sequencing (WES) and whole-genome sequencing (WGS) for 2 AML and 6 MDS developed in Japanese patients with FA (n = 6) and ADD syndrome (n = 2). Skin or bone marrow fibroblasts derived from the same patients were also studied as germline controls. We investigated somatic mutations, structural variants (SVs), and copy number alterations (CNAs) by WES and WGS. Mutational signature was analyzed to understand the mutational processes in these diseases. Result The number of somatic mutations and CNAs in AML identified by WES were 24 and 5 per patient on average, respectively, which were higher than those in MDS (6.8 mutations and 1.8 CNAs per patient) (P=0.07 and 0.06, respectively). However, no significant difference was observed for the number of SVs identified by WGS between MDS (35 counts per patient) and AML (52 counts per patient). Somatic mutations affected known driver genes in myeloid malignancies, such as RUNX1 (n = 1), ASXL1 (n = 1), SRSF2 (n = 1) and NRAS (n = 1) (Figure1). SVs also involved known driver genes in myeloid malignancies, such as CBL (n = 1), KDM6A (n = 1), PHF6 (n = 1), and RUNX1 (n = 1). In total, RUNX1 was most frequently altered (2/6, 33%). CNAs were more frequently accumulated in recurrent regions, including +1q (n = 5), +3q (n = 4), and -7q (n = 2) (Figure1). As previously reported, MDM4 and EVI1 were contained in +1q and +3q, respectively. Higher cancer cell fraction implied that most of these copy number changes were clonal, which suggested the early acquisition of copy number changes and their driver role in leukemic transformation. For mutational signatures, three known signatures were identified, which included clock-like SBS1 and SBS5 caused by endogenous mutational processes, and SBS3 related to defective homologous recombination. In addition, a novel mutational signature (Sig-A) was also detected. SBS3 and Sig-A were mainly detected in patients with FA and ADD syndrome, respectively, indicating that the different mutational processes are operating in the two diseases. Conclusion WES and WGS revealed the genetic landscape of FA and ADD syndrome mutation accumulation. Myeloid neoplasms related with FA and ADD syndrome were characterized by a unique pattern of driver mutations and CNAs, such as RUNX1 mutations/SVs, +1q and +3q. Although the two diseases share some clinical features, our study has revealed the different mutational processes in these diseases. Further investigation is warranted to reveal the underling mechanisms of mutation accumulation and the role of driver mutations in these diseases.

Super-enhancer hijacking drives ectopic expression of hedgehog pathway ligands in meningiomas

Hedgehog signaling mediates embryologic development of the central nervous system and other tissues and is frequently hijacked by neoplasia to facilitate uncontrolled cellular proliferation. Meningiomas, the most common primary brain tumor, exhibit Hedgehog signaling activation in 6.5% of cases, triggered by recurrent mutations in pathway mediators such as SMO. In this study, we find 35.6% of meningiomas that lack previously known drivers acquired various types of somatic structural variations affecting chromosomes 2q35 and 7q36.3. These cases exhibit ectopic expression of Hedgehog ligands, IHH and SHH, respectively, resulting in Hedgehog signaling activation. Recurrent tandem duplications involving IHH permit de novo chromatin interactions between super-enhancers within DIRC3 and a locus containing IHH. Our work expands the landscape of meningioma molecular drivers and demonstrates enhancer hijacking of Hedgehog ligands as a route to activate this pathway in neoplasia.

Somatic structural variation signatures in pediatric brain tumors

Brain cancer is the leading cause of cancer-related death in children. Somatic structural variations (SVs), large-scale alterations in DNA, remain poorly understood in pediatric brain tumors. Here, we detect a total of 13,199 high-confidence somatic SVs in 744 whole-genome sequences of pediatric brain tumors from the Pediatric Brain Tumor Atlas. The somatic SV occurrences have tremendous diversity among the cohort and across different tumor types. We decompose mutational signatures of clustered complex SVs, non-clustered complex SVs, and simple SVs separately to infer their mutational mechanisms. Our finding of many tumor types carrying unique sets of SV signatures suggests that distinct molecular mechanisms shape genome instability in different tumor types. The patterns of somatic SV signatures in pediatric brain tumors are substantially different from those in adult cancers. The convergence of multiple SV signatures on several major cancer driver genes implies vital roles of somatic SVs in disease progression.

Global impact of somatic structural variation on the cancer proteome

Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.

Developmental Instability and Gene Dysregulation in an Extracted Tetraploid from Hexaploid Wheat.

The BBAA subgenomes of hexaploid common wheat can be 'extracted' to constitute a viable and self-reproducing novel tetraploid wheat, termed extracted tetraploid wheat (ETW). Prior studies have shown ETW manifesting phenotypic abnormalities and alteration in gene expression and epigenetic modifications. No population level investigation has been conducted, leaving the issue unclear regarding whether developmental stability, an essential property evolved in all natural organisms, might have been undermined in ETW. Here, we measured variations in five morphological traits and somatic chromosomal stability in populations of ETW and of its hexaploid donor, a resynthesized hexaploid and a natural tetraploid wheat. We observed phenotypic defects in ETW. Meanwhile, we documented much greater within-population variations in ETW than in the other wheat genotypes, most probably due to disrupted developmental stability in ETW. Also, somatic structural chromosome variations were detected only in ETW. Comparative transcriptome analyses indicated that the disrupted developmental stability of ETW is likely linked to massive dysregulation of genome-wide gene expression rather than to genetic mutations. Population network analysis of gene expression implicated intrinsic connectivity among the variable traits, while gene set enrichment analysis provided possible links between dysregulated gene expression and interlaced trait variation.

Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration

Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.

SFyNCS detects oncogenic fusions involving non-coding sequences in cancer.

Fusion genes are well-known cancer drivers. However, most known oncogenic fusions are protein-coding, and very few involve non-coding sequences due to lack of suitable detection tools. We develop SFyNCS to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. The main advantage of this study is that we use somatic structural variations detected from genomic data to validate fusions detected from transcriptomic data. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We show that SFyNCS has superior sensitivity and specificity over existing algorithms through extensive benchmarking in cancer cell lines and patient samples. We then apply SFyNCS to 9565 tumor samples across 33 tumor types in The Cancer Genome Atlas cohort and detect a total of 165,139 fusions. Among them, 72% of the fusions involve non-coding sequences. We find a long non-coding RNA to recurrently fuse with various oncogenes in 3% of prostate cancers. In addition, we discover fusions involving two non-coding RNAs in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.

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

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

Structural variants integration and visualization: A comprehensive R package for integration of somatic structural variations from multiple callers and visualization

Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural variations (SVs) in genomes. However, different SV callers can produce variable results due to the distinct rationale and sensitivity of pipelines, highlighting the need for effective tools to compare and merge results from multiple callers. Here, we developed an R package, structural variants integration and visualization, to facilitate the integration, classification, and visualization of SV results from multiple callers, allowing for accurate identification of the most reliable SVs. Our package relies on a complex translocation projection and clustering method, enabling the projection of each translation to a point in a Cartesian coordinate system and visualization of SVs at both whole-genome and individual chromosome levels. Thus, our approach provides a valuable framework for analyzing SVs from WGS data, improving the accuracy and efficiency of SV detection, and enhancing the potential of WGS for clinical and research applications.