Somatic Structural Variants Research Articles

Genomes and epigenomes of matched normal and tumor breast tissue reveal diverse evolutionary trajectories and tumor-host interactions.

Normal tissues adjacent to the tumor (NATs) may harbor early breast carcinogenesis events driven by field cancerization. Although previous studies have characterized copy-number (CN) and transcriptomic alterations, the evolutionary history of NATs in breast cancer (BC) remains poorly characterized. Utilizing whole-genome sequencing (WGS), methylation profiling, and RNA sequencing (RNA-seq), we analyzed paired germline, NATs, and tumor samples from 43 individuals with BC in Hong Kong (HK). We found that single-nucleotide variants (SNVs) were common in NATs, with one-third of NAT samples exhibiting SNVs in driver genes, many of which were present in paired tumor samples. The most frequently mutated genes in both tumor and NAT samples were PIK3CA, TP53, GATA3, and AKT1. In contrast, large-scale aberrations such as somatic CN alterations (SCNAs) and structural variants (SVs) were rarely detected in NAT samples. We generated phylogenetic trees to investigate the evolutionary history of paired NAT and tumor samples. They could be categorized into tumor only, shared, and multiple-tree groups, the last of which is concordant with non-genetic field cancerization. These groups exhibited distinct genomic and epigenomic characteristics in both NAT and tumor samples.Specifically, NAT samples in the shared-tree group showed higher number of mutations, while NAT samples belonging to the multiple-tree group showed a less inflammatory tumor microenvironment (TME), characterized by a higher proportion ofregulatory Tcells (Tregs) and lower presence of CD14 cell populations. In summary, our findings highlight the diverse evolutionary history in BC NAT/tumor pairs and the impact of field cancerization and TME in shaping the genomic evolutionary historyof tumors.

Performance of somatic structural variant calling in lung cancer using Oxford Nanopore sequencing technology

BackgroundLung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes).ResultsDifferent combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%.ConclusionLong-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Epigenomic, transcriptomic and proteomic characterizations of reference samples.

A variety of newly developed next-generation sequencing technologies are making their way rapidly into the research and clinical applications, for which accuracy and cross-lab reproducibility are critical, and reference standards are much needed. Our previous multicenter studies under the SEQC-2 umbrella using a breast cancer cell line with paired B-cell line have produced a large amount of different genomic data including whole genome sequencing (Illumina, PacBio, Nanopore), HiC, and scRNA-seq with detailed analyses on somatic mutations, single-nucleotide variations (SNVs), and structural variations (SVs). However, there is still a lack of well-characterized reference materials which include epigenomic and proteomic data. Here we further performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic analyses and provided a comprehensive catalog of the epigenomic landscape, which overlapped with the transcriptomes and proteomes for the two cell lines. We identified >7,700 peptide isoforms, where the majority (95%) of the genes had a single peptide isoform. Protein expression of the transcripts overlapping CGIs were much higher than the protein expression of the non-CGI transcripts in both cell lines. We further demonstrated the evidence that certain SNVs were incorporated into mutated peptides. We observed that open chromatin regions had low methylation which were largely regulated by CG density, where CG-rich regions had more accessible chromatin, low methylation, and higher gene and protein expression. The CG-poor regions had higher repressive epigenetic regulations (higher DNA methylation) and less open chromatin, resulting in a cell line specific methylation and gene expression patterns. Our studies provide well-defined reference materials consisting of two cell lines with genomic, epigenomic, transcriptomic, scRNA-seq and proteomic characterizations which can serve as standards for validating and benchmarking not only on various omics assays, but also on bioinformatics methods. It will be a valuable resource for both research and clinical communities.

Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Abstract Objective: Structural variations (SVs) constitute the greatest source of genomic alterations leading to the oncogenesis of many cancers, including the deadliest pancreatic cancer (PC). However, SVs in PC remain largely undefined due to technological limitations of the traditional short-read sequencing. This study aims to establish a comprehensive signature of genomic SVs in PC. Methods: PacBio whole genome long-read sequencing was employed to investigate the genomic landscape of SVs in eight tissues from four pancreatic cancer patients. A variety of SVs callers, including pbsv, Sniffles, cuteSV, and svim, were comprehensively adopted to improve the accuracy of SVs detection. Many undefined characteristics of germline and somatic SVs were revealed by comparing with multiple previously published databases. Besides, the impacts of structural variations on 3D chromatin organization were analyzed by integrating multi-omics data including Hi-C, RNA seq and ChIP seq. Results: A total of 26,844 and 27,028 non-redundant SVs were identified in human pancreatic cancer and matched para-cancerous tissues, respectively. Notably, among these SVs, 23.97% were novel and had not been previously reported. Germline SVs were further characterized and found enriched in 25 well-known susceptible genes, such as TP63, PVT1, and ABO. Additionally, we proposed a panel of germline SVs with predicted highest pathogenicity, involving STOX1, DSPP, and WRN. Totally, 616 somatic SVs were identified and presented high burdens in patients with lymph node metastasis. We observed that somatic DELs and INSs were significantly more prevalent in repetitive regions than in non-repetitive regions. Interestingly, DELs showed a decrease in the proportion occurring in simple repeat regions but an increase in the proportion occurring in LINE and SINE regions compared to INSs. Moreover, it was observed that deletions within topologically associated domains were associated with local enhanced interactions and disrupted chromatin loops, which might influence H3K27ac modification of histone contributing to enhancer or silencer hijacking. Conclusion: This study provides insights into the genomic signature of SVs in human pancreatic cancer. These findings might shed new light on the complexity of SVs and their pathogenesis by interplaying with chromatin organization. Citation Format: Yongxing Du, Xiaohao Zheng, Yunjie Duan, Chengfeng Wang. Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A083.

433. UNRAVELLING THE MOLECULAR MECHANISMS BEHIND TUMOUR DIFFERENTIATION IN ESOPHAGEAL ADENOCARCINOMA

Abstract Background Esophageal adenocarcinoma tumors are divided into three grades based on the tumour’s histological differentiation: well, moderate and poor. Poorly differentiated tumours have a worse survival rate than moderate and well tumours. Understanding the molecular programs of this differentiation may lead to the identification of novel therapeutic interventions specific to tumour differentiation. We have utilized laser-capture microdissection to enrich tumour cells followed by gene expression profiling (RNA-seq) to identify gene expression programs and whole genome sequencing for differentiating specific mutations and copy number changes. Collectively, these results will enable us to unravel the molecular drivers of tumour differentiation. Methods Laser capture microdissection was applied to N=127 RNA-seq samples from N=74 patients and N=103 from N=81 patients from a mix of primary tumour biopsies, resections, and metastatic biopsies. Most samples have a matching RNA-seq and WGS sample. We used a standard pipeline to analyze the WGS data and produce somatic mutation, structural variant, and copy number calls. The gene expression data was segregated into two sets a test set consisting of N=74 samples and a test set of N=53 samples. Non-negative matrix factorization was used to identify eleven gene expression programs. Results Our testing RNA-seq cohort consisted of N=74 samples from N=74 patients with N=4 G1, N=26 G2, N=35 G3, and N=9 missing differentiation data. Our initial goal was to unravel the gene expression programs that correlate with tumour differentiation. Our non-negative matrix factorization analysis yielded 11 gene signatures, N=3 programs enriched in glandular gene expression, N=3 enriched in EMT pathways, N=2 with fibroblasts, and N=3 associated with immune / inflammation genes (not shown) (Figure 1). Moreover, the glandular signatures were associated with G1/G2 and the EMT and fibroblast signatures with G3. Moreover, the glandular 2 signature was associated with HER2 amplifications. Conclusion In this work we have begun to unravel the gene expression and genomic changes associated with tumour differentiation. We have found signatures enriched for both G1/G2 and G3 tumours and from these signatures we have observed gene expression heterogeneity within the different tumour differentiation categories. Moreover, the G3 tumours are enriched in fibroblasts despite our laser-capture microdissection. We are currently working on a classification model to predict tumor differentiation from these gene expression programs and are looking to further integrate our whole genome data to find additional genomic drivers.

Comprehensive analysis of somatic mutations and structural variations in domestic pig.

Understanding somatic mutations and structural variations in domestic pigs (Sus scrofa domestica) is critical due to their increasing importance as model organisms in biomedical research. In this study, we conducted a comprehensive analysis through whole-genome sequencing of skin, organs, and blood samples. By examining two pig pedigrees, we investigated the inheritance and sharedness of structural variants among fathers, mothers, and offsprings. Utilizing single-cell clonal expansion techniques, we observed significant variations in the number of somatic mutations across different tissues. An in-house developed pipeline enabled precise filtering and analysis of these mutations, resulting in the construction of individual phylogenetic trees for two pigs. These trees explored the developmental relationships between different tissues, revealing insights into clonal expansions from various anatomical locations. This study enhances the understanding of pig genomes, affirming their increasing value in clinical and genomic research, and provides a foundation for future studies in other animals, paralleling previous studies in mice and humans. This approach not only deepens our understanding of mammalian genomic variations but also strengthens the role of pigs as a crucial model in human health and disease research.

The DNA methylome of pediatric brain tumors appears shaped by structural variation and predicts survival

Structural variation heavily influences the molecular landscape of cancer, in part by impacting DNA methylation-mediated transcriptional regulation. Here, using multi-omic datasets involving >2400 pediatric brain and central nervous system tumors of diverse histologies from the Children’s Brain Tumor Network, we report hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of somatic structural variant (SV) breakpoints is recurrently associated with altered expression or DNA methylation, respectively, including tumor suppressor genes ATRX and CDKN2A. Altered DNA methylation near enhancers associates with nearby somatic SV breakpoints, including MYC and MYCN. A subset of genes with SV-CGI methylation associations also have expression associations with patient survival, including BCOR, TERT, RCOR2, and PDLIM4. DNA methylation changes in recurrent or progressive tumors compared to the initial tumor within the same patient can predict survival in pediatric and adult cancers. Our comprehensive and pan-histology genomic analyses reveal mechanisms of noncoding alterations impacting cancer genes.

Beyond tobacco: genomic disparities in lung cancer between smokers and never-smokers

BackgroundTobacco use is one of the main risk factors for Lung Cancer (LC) development. However, about 10–20% of those diagnosed with the disease are never-smokers. For Non-Small Cell Lung Cancer (NSCLC) there are clear differences in both the clinical presentation and the tumor genomic profiles between smokers and never-smokers. For example, the Lung Adenocarcinoma (LUAD) histological subtype in never-smokers is predominately found in young women of European, North American, and Asian descent. While the clinical presentation and tumor genomic profiles of smokers have been widely examined, never-smokers are usually underrepresented, especially those of a Latin American (LA) background. In this work, we characterize, for the first time, the difference in the genomic profiles between smokers and never-smokers LC patients from Chile.MethodsWe conduct a comparison by smoking status in the frequencies of genomic alterations (GAs) including somatic mutations and structural variants (fusions) in a total of 10 clinically relevant genes, including the eight most common actionable genes for LC (EGFR, KRAS, ALK, MET, BRAF, RET, ERBB2, and ROS1) and two established driver genes for malignancies other than LC (PIK3CA and MAP2K1). Study participants were grouped as either smokers (current and former, n = 473) or never-smokers (n = 200) according to self-report tobacco use at enrollment.ResultsOur findings indicate a higher overall GA frequency for never-smokers compared to smokers (58 vs. 45.7, p-value < 0.01) with the genes EGFR, KRAS, and PIK3CA displaying the highest prevalence while ERBB2, RET, and ROS1 the lowest. Never-smokers present higher frequencies in seven out of the 10 genes; however, smokers harbor a more complex genomic profile. The clearest differences between groups are seen for EGFR (15.6 vs. 21.5, p-value: < 0.01), PIK3CA (6.8 vs 9.5) and ALK (3.2 vs 7.5) in favor of never-smokers, and KRAS (16.3 vs. 11.5) and MAP2K1 (6.6 vs. 3.5) in favor of smokers. Alterations in these genes are comprised almost exclusively by somatic mutations in EGFR and mainly by fusions in ALK, and only by mutations in PIK3CA, KRAS and MAP2K1.ConclusionsWe found clear differences in the genomic landscape by smoking status in LUAD patients from Chile, with potential implications for clinical management in these limited-resource settings.

HYENA detects oncogenes activated by distal enhancers in cancer.

Somatic structural variations (SVs) in cancer can shuffle DNA content in the genome, relocate regulatory elements, and alter genome organization. Enhancer hijacking occurs when SVs relocate distal enhancers to activate proto-oncogenes. However, most enhancer hijacking studies have only focused on protein-coding genes. Here, we develop a computational algorithm 'HYENA' to identify candidate oncogenes (both protein-coding and non-coding) activated by enhancer hijacking based on tumor whole-genome and transcriptome sequencing data. HYENA detects genes whose elevated expression is associated with somatic SVs by using a rank-based regression model. We systematically analyze 1146 tumors across 25 types of adult tumors and identify a total of 108 candidate oncogenes including many non-coding genes. A long non-coding RNA TOB1-AS1 is activated by various types of SVs in 10% of pancreatic cancers through altered 3-dimensional genome structure. We find that high expression of TOB1-AS1 can promote cell invasion and metastasis. Our study highlights the contribution of genetic alterations in non-coding regions to tumorigenesis and tumor progression.

Endogenous retroviruses mediate transcriptional rewiring in response to oncogenic signaling in colorectal cancer.

Cancer cells exhibit rewired transcriptional regulatory networks that promote tumor growth and survival. However, the mechanisms underlying the formation of these pathological networks remain poorly understood. Through a pan-cancer epigenomic analysis, we found that primate-specific endogenous retroviruses (ERVs) are a rich source of enhancers displaying cancer-specific activity. In colorectal cancer and other epithelial tumors, oncogenic MAPK/AP1 signaling drives the activation of enhancers derived from the primate-specific ERV family LTR10. Functional studies in colorectal cancer cells revealed that LTR10 elements regulate tumor-specific expression of multiple genes associated with tumorigenesis, such as ATG12 and XRCC4. Within the human population, individual LTR10 elements exhibit germline and somatic structural variation resulting from a highly mutable internal tandem repeat region, which affects AP1 binding activity. Our findings reveal that ERV-derived enhancers contribute to transcriptional dysregulation in response to oncogenic signaling and shape the evolution of cancer-specific regulatory networks.

Comprehensive identification of pathogenic variants in retinoblastoma by long- and short-read sequencing

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. The causal variants in RB are mostly characterized by previously used short-read sequencing (SRS) analysis, which has technical limitations in identifying structural variants (SVs) and phasing information. Long-read sequencing (LRS) technology has advantages over SRS in detecting SVs, phased genetic variants, and methylation. In this study, we comprehensively characterized the genetic landscape of RB using combinatorial LRS and SRS of 16 RB tumors and 16 matched blood samples. We detected a total of 232 somatic SVs, with an average of 14.5 SVs per sample across the whole genome in our cohort. We identified 20 distinct pathogenic variants disrupting RB1 gene, including three novel small variants and five somatic SVs. We found more somatic SVs were detected from LRS than SRS (140 vs. 122) in RB samples with WGS data, particularly the insertions (18 vs. 1). Furthermore, our analysis shows that, with the exception of one sample who lacked the methylation data, all samples presented biallelic inactivation of RB1 in various forms, including two cases with the biallelic hypermethylated promoter and four cases with compound heterozygous mutations which were missing in SRS analysis. By inferring relative timing of somatic events, we reveal the genetic progression that RB1 disruption early and followed by copy number changes, including amplifications of Chr2p and deletions of Chr16q, during RB tumorigenesis. Altogether, we characterize the comprehensive genetic landscape of RB, providing novel insights into the genetic alterations and mechanisms contributing to RB initiation and development. Our work also establishes a framework to analyze genomic landscape of cancers based on LRS data.

Comparison of germline and somatic structural variants in cancers reveal systematic differences in variant generating and selection processes.

Although several recent studies have characterized structural variants (SVs) in germline and cancer genomes, the features of SVs in these different contexts have not been directly compared. We examined similarities and differences between 2 million germline and 115 thousand tumor SVs from a cohort of 963 patients from The Cancer Genome Atlas (TCGA). We found significant differences in features related to their genomic sequences and localization that suggest differences between SV-generating processes and selective pressures. For example, we found that transposon-mediated processes shape germline much more than somatic SVs, while somatic SVs more frequently show features characteristic of chromoanagenesis. These differences were extensive enough to enable us to develop a classifier - "the great GaTSV" - that accurately distinguishes between germline and cancer SVs in tumor samples that lack a matched normal sample.

Abstract B006: Data-driven discoveries of molecular mechanism and therapeutic vulnerabilities of CDK12 mutant tumors

Abstract Somatic structural variations (SVs) are common in cancer. Although a small fraction of SVs in breast and ovarian cancers can be attributed to homologous recombination deficiency, the underlying molecular mechanisms for the vast majority of somatic SVs remain unclear. Here, we focus on the roles of transcription and DNA replication collisions in genomic instability in cancer. Such collisions are unavoidable in cells since both transcription and replication use the same DNA as template. We hypothesized that transcription replication collisions (TRCs), if not properly repaired, would lead to collapsed replication forks and result in SVs. To this end, we studied somatic SVs in 6193 high-coverage whole-genome sequenced primary and metastatic tumors from three independent pan-cancer cohorts. A total of 13 conserved SV signatures, representing independent molecular mechanisms, were deconvoluted from these cohorts using non-negative matrix factorization approach. We detected replicated-strand bias, the expected footprint of transcription-replication collision, in large tandem duplications (TDs) across multiple cohorts. This bias was only observed in expressed genes, consistent with TRCs depending on transcription activity. Large TDs were abundant in female-specific (breast, ovarian and uterus), upper gastric-intestinal tract, and prostate cancers. They were associated with CDK12 mutations and worse patient survival. CDK12 is a cyclin-dependent kinase, a key regulator of transcription elongation and termination. Deleting or suppressing CDK12 using CRISPR-Cas9 in prostate cell lines increased RNA:DNA hybrids (R-loops), promoted TRCs, and ultimately led to large TDs. Finally, we found that cells lacking CDK12 were sensitive to WEE1, CHK1 and ATR inhibitors. In summary, our data suggest that large TDs in cancer form due to impaired TRC repair and can be used as a biomarker for prognosis and treatment. Citation Format: Lixing Yang. Data-driven discoveries of molecular mechanism and therapeutic vulnerabilities of CDK12 mutant tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B006.

Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.

Somatic structural variants drive distinct modes of oncogenesis in melanoma.

The diversity of structural variants (SVs) in melanoma and how they impact oncogenesis are incompletely known. We performed harmonized analysis of SVs across melanoma histological and genomic subtypes, and we identified distinct global properties between subtypes. These included the frequency and size of SVs and SV classes, their relation to chromothripsis events, and the role of topologically associated domain (TAD) boundary altering SVs on cancer-related genes. Following our prior identification of double-stranded break repair deficiency in a subset of triple wild-type cutaneous melanoma, we identified MRE11 and NBN loss-of-function SVs in melanomas with this mutational signature. Experimental knockouts of MRE11 and NBN, followed by olaparib cell viability assays in melanoma cells, indicated that dysregulation of each of these genes may cause sensitivity to PARPi in cutaneous melanomas. Broadly, harmonized analysis of melanoma SVs revealed distinct global genomic properties and molecular drivers, which may have biological and therapeutic impact.

De novo and somatic structural variant discovery with SVision-pro.

Long-read-based de novo and somatic structural variant (SV) discovery remains challenging, necessitating genomic comparison between samples. We developed SVision-pro, a neural-network-based instance segmentation framework that represents genome-to-genome-level sequencing differences visually and discovers SV comparatively between genomes without any prerequisite for inference models. SVision-pro outperforms state-of-the-art approaches, in particular, the resolving of complex SVs is improved, with low Mendelian error rates, high sensitivity of low-frequency SVs and reduced false-positive rates compared with SV merging approaches.

Abstract 2338: Benchmarking long- and short-read somatic structural variation callers using a multi-technology panel of six tumor/normal cell lines

Abstract Better structural variation (SV) detection could improve cancer diagnosis, treatment and prevention. Yet many cancer genomics studies have only reliably detected single nucleotide variants and small indels due to technological limitations of short-read sequencing. While structural variants can be inferred from discordant short read pairs, as much as 70% of SVs remain undetected because of the mappability difficulties. This is especially true for SVs in regions where GC content is greater than 45% or regions which harbor tandem repeats and segmental duplications. Advances in long-read sequencing enabled direct observation of SVs with recall and precision over 95% across a larger portion of the genome. To harness this technology, we developed Severus - a long-read SV caller that provides phased detection of both simple germline SVs as well as complex rearrangements commonly found in cancer genomes. Such rearrangements are built into a breakpoint graph to reconstruct derived tumor chromosome structure. To benchmark Severus and other long-read SV calling methods, we sequenced six tumor/normal cell line pairs using Nanopore, HiFi, short-read and Hi-C sequencing technologies. We combined the calls from multiple tools and technologies to generate benchmarking sets of somatic SV for each tumor cell line, and evaluated short- and long-read tools against this benchmark set. Current tools for SV merging and comparison (such as truvari) were primarily designed for long indels, rather than breakends that are more common in somatic SVs. Another challenge is that different tools may represent the same variants differently in a VCF output. To enable robust somatic SV outputs comparison, we developed a tool called Minda that translates an input VCF entries into a unified representation, and then compares the calls in either pairwise or multi-tool mode. As expected, in our benchmarking of cell six tumor cell line pairs, short-read methods had substantially lower recall and precision, compared to long-read methods. Among the long-read methods, Severus consistently had substantially better recall and precision, compared to Sniffles2, nanomonsv and SAVANA. An analysis of publicly available long-read sequencing of a melanoma cell line (for which curated benchmark SV set is available) produced consistent results. Citation Format: Ayse Keskus, Asher Bryant, Tanveer Ahmad, Ataberk Donmez, Isabel Rodriguez, Nicole Rossi, Yi Xie, Byunggil Yoo, Rose Milano, Hong Lou, Jimin Park, Joshua Gardner, Brandy McNulty, Karen Miga, Mike Dean, Midhat Farooqi, Benedict Paten, Mikhail Kolmogorov. Benchmarking long- and short-read somatic structural variation callers using a multi-technology panel of six tumor/normal cell lines [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 2338.

Abstract 1763: Long-read sequencing of pediatric leukemia identifies clinically relevant genomic rearrangements

Abstract Clinical detection of genomic rearrangements currently depends on a range of complementary and overlapping methods including fluorescence in situ hybridization (FISH), karyotyping, and DNA and/or RNA sequencing. This requirement for multiple tests results in higher total costs, extended analysis time, and increased usage of sometimes limited tumor material. In our laboratory, we apply long high-fidelity reads to human samples using PacBio circular consensus sequencing (HiFi-GS) of 12-18kb DNA fragments, which offers better structural variant detection relative to short-read sequencing. Here, we assess the ability of HiFi-GS to detect clinically relevant genomic rearrangements (CRGRs) in pediatric leukemia. We selected 11 pediatric leukemia cases with corresponding normal (remission) samples, including 7 cases of B-cell acute lymphoblastic leukemia (B-ALL) and 4 cases of acute myeloid leukemia (AML); 5 of these 11 leukemia cases had known CRGRs as below. The remaining 6 leukemia cases had also undergone clinical genetic profiling via karyotyping, FISH, microarray, and sequencing yet a clinical grade genomic driver was not identified. DNA from each sample was sequenced on a Revio instrument (PacBio, Menlo Park, CA) to a target depth of 30x. The PacBio Human Whole Genome Sequencing (WGS) workflow was used to process HiFi reads for haplotagged alignment and phasing, followed by somatic structural variant calling using Severus. Subsequent analysis focused on the presence of break ends in known cancer-relevant genes. We found that HiFi-GS detected the known CRGRs in all 5 cases with prior findings, providing precise break ends and clarifying sometimes unclear cytogenetic observations (such as exact partner genes), in these cases. These included detection of an ETV6-RUNX1 fusion, NUP98-NSD1 fusion, KMT2A-AFF1 fusion, KMT2A-AFDN fusion, and RUNX1-RUNX1T1 fusion. HiFi sequencing also detected CRGRs in 2 of the 6 “undiagnosed cases”; namely, one case of ZNF384-TCF3 fusion and one case of KMT2A-MLLT10 fusion. The former can be cytogenetically cryptic, while the latter can often be missed due to its potentially complex nature. Our results demonstrate that HiFi-GS can reliably detect CRGRs, bringing us closer to the promise of a single comprehensive genetic test for cancer characterization. Additional work examining other somatic structural and copy number variants (i.e., inversions, deletions, and duplications) in these cases, as well as oncogenic sequence variants, is ongoing. Citation Format: Byunggil Yoo, Ayse Keskus, Chengpeng Bi, Lisa Lansdon, Tanveer Ahmad, Irina Pushel, Adam Walter, Margaret Gibson, Erin Guest, Tomi Pastinen, Mikhail Kolmogorov, Midhat S. Farooqi. Long-read sequencing of pediatric leukemia identifies clinically relevant genomic rearrangements [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 1763.

Abstract 4895: Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software

Abstract Solid tumors can show highly complex somatic structural and copy number variants (CNVs) of multiple classes. These variants can reveal mechanisms behind carcinogenesis, including the amplification of oncogenes, deletion or inactivation of tumor suppressor genes, and fusions to create new oncogenes. High degrees of heterogeneity within solid tumors can complicate analysis. Optical Genome Mapping (OGM) is a comprehensive technology which combines the resolution of molecular-level data with the scale of cytogenomic analysis. ≈5-15mg sections of freshly frozen tumor are homogenized in buffer to release ultra-high molecular weight DNA. Long fragments are then labeled at a regular 6mer, then linearized and imaged with native long-range structure (≥150kbp) preserved. In silico molecules are assembled into maps and aligned to a reference genome to detect structural variants with sensitivity to ≥5% allele fraction. Bionano VIATM software provides tools for visualization and interpretation of structural variants detected with OGM. VIA also provides CNV calling and detection of Absence of Heterozygosity (AOH) and allelic imbalance using SNP-FASST3, a segmentation algorithm for detecting mosaic events in OGM and other types of data. VIA calculates a B-Allele frequency (BAF) distribution from OGM data and adds a genome-wide BAF track to the applications suite, enabling calling of allelic imbalance events such as AOH. Visualized together, the overlay of structural variant information on copy number data provides context for chromosome fusions underlying copy number change. Additionally, balanced fusions are revealed consistently in cases where the impact is copy neutral. To demonstrate the utility of integrative analysis of structural, copy number, and allelic imbalance variants in solid tumor datasets, we processed a pilot set of six diverse solid tumors through Bionano software. Brain, breast, kidney, lung, ovarian, and prostate tumor data which had undergone previous analysis in Bionano Solve 3.7 were freshly analyzed in Solve 3.8 and VIA 7.0. In the lung tumor dataset there are clear allelic imbalance segments spanning most of chromosome 4 with no concomitant copy number change. In VIA, these segments can be merged on examination, converted to AOH calls, and further specified to reflect mosaic copy neutral loss of heterozygosity (CN-LOH). In the complex kidney tumor dataset, it is difficult to resolve ploidy state based on copy number data alone. This ambiguity is resolvable with VIA, by leveraging the copy number and BAF-based allelic imbalance distributions and recentering probes to a manually defined diploid region. The comprehensive OGM data approach facilitated by VIA can streamline analysis in challenging solid tumor datasets. Structural variant visualization, CNV detection and AOH detection are available in VIA 7.0. Citation Format: Samer I. Al-Saffar, Benjamin Clifford, Aliz Raksi, Alex Hastie, Neil Miller, Alka Chaubey. Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software [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 4895.

Abstract 401: The impact of DNA structural variants on PRKN gene function and colorectal cancer pathogenesis

Abstract Background: Cancer is caused by somatic DNA alterations, such as single nucleotide variants, somatic copy number alterations and structural variants (SVs). PRKN is among the genes most frequently affected by SVs in colorectal cancer (CRC), with 37% of primary cancers and 56% of metastatic lesions having focal deletions in PRKN. PRKN encodes the E3 ubiquitin ligase Parkin, which regulates the biological activity and degradation of substrates via post-translational modifications. The genomic location of PRKN is within a common fragile site. Therefore, it remains unclear whether the high frequency of SVs in PRKN are passenger events due to genomic instability or driver events of CRC pathogenesis. Aim: Our study aims to investigate the impact of SVs on the functionality of Parkin in CRC pathogenesis. Methods: We used publicly available DNA deep whole genome sequencing (WGS) and tumor-matched RNA sequencing data (n=394) to estimate the impact of SVs in PRKN on tumor biology. For this, the transcriptome-wide p-value distribution generated by differential expression analysis was used as a measure of biological impact. The HCT116-MLH1-repaired cell line and patient-derived adenoma organoids were genetically modified using CRISPR/Cas9 to mimic the SVs observed in patient material and analyze their impact. RNA-sequencing, whole proteome and ubiquitin remnant-specific proteomics were used to assess the effect of SVs on gene function and identify altered biological processes. Results: Analysis of WGS and RNA sequencing of patient material showed that SVs in PRKN have a large impact on CRC biology, comparable to the impact of mutations in TP53 (impact score 0.379 vs 0.332). The most pronounced effects are seen in the ubiquitin-like, RING0 and RING1 domains. These domains are important for recognition and/or binding to ubiquitin, E2 ubiquitin-conjugating enzymes and substrates. In the HCT116-MLH1-repaired CRC cell line, hemizygous introduction of an SV in PRKN had minimal effects on genome-wide gene expression. In contrast, homozygous deletion altered the expression of nearly 2000 genes. Analyses of ubiquitin motif remnants showed differential ubiquitination of proteins involved in DNA repair following the introduction of an SV in PRKN in the CRC cell line. These proteins include TOP2A (Log2 fold change (L2FC) = -3.69, P = 5.71−5), RAD18 (L2FC = -4.55, P = 1.35−4) and Spartan (SPRTN; L2FC = -2.57, P = 7.43−4). Conclusion: SVs in PRKN have a high impact on tumor biology and result in aberrant gene expression and post-translational modifications of proteins related to DNA repair. Further research will expand to the patient-derived adenoma organoids and focus on understanding if these recurrent somatic alterations contribute to genomic instability and the development of CRC pathogenesis. Citation Format: Elisabeth J. van Bree, Soufyan Lakbir, Carmen Rubio-Alarcón, Renske de Wit, Anne Bolijn, Pien Delis-van Diemen, Marianne Tijssen, Ellen Stelloo, Harma Feitsma, Gerrit A. Meijer, Beatriz Carvalho, Sanne Abeln, Remond J. Fijneman. The impact of DNA structural variants on PRKN gene function and colorectal cancer pathogenesis [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 401.