Genomic Breakpoints Research Articles

KMT2A Rearrangements in Leukemias: Molecular Aspects and Therapeutic Perspectives.

KMT2A (alias: mixed-lineage leukemia [MLL]) gene mapping on chromosome 11q23 encodes the lysine-specific histone N-methyltransferase 2A and promotes transcription by inducing an open chromatin conformation. Numerous genomic breakpoints within the KMT2A gene have been reported in young children and adults with hematologic disorders and are present in up to 10% of acute leukemias. These rearrangements describe distinct features and worse prognosis depending on the fusion partner, characterized by chemotherapy resistance and high rates of relapse, with a progression-free survival of 30-40% and overall survival below 25%. Less intensive regimens are used in pediatric patients, while new combination therapies and targeted immunotherapeutic agents are being explored in adults. Beneficial therapeutic effects, and even cure, can be reached with hematopoietic stem cell transplantation, mainly in young children with dismal molecular lesions; however, delayed related toxicities represent a concern. Herein, we summarize the translocation partner genes and partial tandem duplications of the KMT2A gene, their molecular impact, clinical aspects, and novel targeted therapies.

A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing.

The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21) ETV6::RUNX1 translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-yr-old at relapse, the cell line offers a practical model for the study of pediatric B-ALL. In recent years, short- and long-read DNA and RNA sequencing have emerged as a complement to karyotyping techniques in the resolution of structural variants in an oncological context. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole-genome sequencing, IsoSeq RNA sequencing, and short-read Illumina sequencing to create a detailed genomic and transcriptomic characterization of the REH cell line. Whole-genome sequencing clarified the molecular traits of disrupted ALL-associated genes including CDKN2A, PAX5, BTG1, VPREB1, and TBL1XR1, as well as the glucocorticoid receptor NR3C1 Meanwhile, transcriptome sequencing identified seven fusion genes within the genomic breakpoints. Together, our extensive whole-genome investigation makes high-quality open-source data available to the leukemia genomics community.

Precision genome profiling for pediatric leukemia with a software-controlled enrichment method using nanopore sequencer.

10027 Background: The real-time nature of nanopore sequencing allows for simultaneous basecalling of DNA sequences during sequencing. This unique capability enables adaptive sampling (AS), a software-controlled targeted sequencing method. AS is notable for its ability to rapidly and flexibly enrich multiple genes with long fragment reads and detect various modalities of genetic aberrations in a single run. However, the feasibility and significance of AS for cancer have not been previously reported. Methods: We performed AS on a GridION sequencer using samples from 28 pediatric leukemia patients (10 acute myeloid leukemia, 13 B-cell acute lymphoblastic leukemia, and 5 T-cell acute lymphoblastic leukemia). Target regions were comprised of 466 genes associated with hematologic malignancies and included 30-kilo base pairs of flanking regions. After 3 days of sequencing, single-nucleotide variants (SNVs), structural variations (SVs), and copy number variations (CNVs) were determined. In 21 samples, variant calling accuracy was evaluated using short-read-based whole genome sequencing (WGS). Results: In the on-target regions, mean depth was 21.0× and N50 was 11,191 bps at the median. Of the 13 samples with genetic alterations previously detected through clinical testing for diagnostic classifications, all were reconfirmed by AS. Detecting DUX4 rearrangement needed an additional analysis pipeline because of its structural complexity. Among the 15 remaining samples whose genetic alterations had not been determined by clinical diagnostic testing, AS identified putative driver aberrations in 14 samples. All of these genomic abnormalities were structural variations (SVs) or copy number variations (CNVs), most of which were not encompassed within the genes or regions targeted in clinical diagnostic testing. Detected SVs were described with accurate genomic breakpoints, enabling the efficient detection of gene rearrangements and deletions of the entire region of an exon or a gene. Regarding CNVs, both chromosomal-level CNVs, such as high-hyperdiploid, and focal CNVs, such as CDKN2A deletion, were detectable using genome-wide low-coverage reads in the off-target regions. In the other case with acute myeloid leukemia in which genetic abnormalities were not detected either by clinical testing or AS, WGS identified an NPM1 frameshift deletion located outside of known hotspots. Among variants identified by WGS, AS detected 60.9% of the SNVs, 17.6% of the small indels, and 89.2% of the SVs, with a tendency of poor detection efficiency for variants with low variant allele frequency. Conclusions: AS provides a rapid and precise description of the genomic profile of pediatric leukemia, particularly advantageous for identifying SVs and CNVs, which are difficult to detect by capture-based short-read sequencing.

Mechanisms and pathologies of human mitochondrial DNA replication and deletion formation.

Human mitochondria possess a multi-copy circular genome, mitochondrial DNA (mtDNA), that is essential for cellular energy metabolism. The number of copies of mtDNA per cell, and their integrity, are maintained by nuclear-encoded mtDNA replication and repair machineries. Aberrant mtDNA replication and mtDNA breakage are believed to cause deletions within mtDNA. The genomic location and breakpoint sequences of these deletions show similar patterns across various inherited and acquired diseases, and are also observed during normal ageing, suggesting a common mechanism of deletion formation. However, an ongoing debate over the mechanism by which mtDNA replicates has made it difficult to develop clear and testable models for how mtDNA rearrangements arise and propagate at a molecular and cellular level. These deletions may impair energy metabolism if present in a high proportion of the mtDNA copies within the cell, and can be seen in primary mitochondrial diseases, either in sporadic cases or caused by autosomal variants in nuclear-encoded mtDNA maintenance genes. These mitochondrial diseases have diverse genetic causes and multiple modes of inheritance, and show notoriously broad clinical heterogeneity with complex tissue specificities, which further makes establishing genotype-phenotype relationships challenging. In this review, we aim to cover our current understanding of how the human mitochondrial genome is replicated, the mechanisms by which mtDNA replication and repair can lead to mtDNA instability in the form of large-scale rearrangements, how rearranged mtDNAs subsequently accumulate within cells, and the pathological consequences when this occurs.

Abstract A034: Development of a novel class of genomic biomarkers through mathematical modeling of cancer genome contiguity

Abstract Introduction: Chromosomal instability (CIN) is a hallmark of cancer aggressiveness. However, in lung adenocarcinoma (LUAD) the most common methods for measuring genomic instability, such as the weighted Genome Instability Index (wGII), are not reliable predictors of patient outcomes. The wGII measures the portion of the genome altered by copy number variation (CNV). The wGII quantifies aneuploidy but ignores other properties of CNVs such as their length distribution. We hypothesized that quantification of genome contiguity may overcome the limitations of wGII and help identify novel prognostic biomarkers. Method: We develop a novel measure of CIN based on mathematical modeling of genome breakage patterns. Utilizing segmented CNV profiles we infer two properties of the genome breakage process – its intensity and dispersion. Intensity is proportional to the number of genome breakpoints and is estimated by the total number of CNV segments. Dispersion quantifies spatial dependence of breakpoints over a wide range of genomic scales. It is computed by Ripley’s K-function which compares the distribution of breakpoints with a random Poisson point process. Jointly, intensity and dispersion, which we term the weighted Genome Contiguity Index (wGCI), estimate the contiguity of the genome. We contrast the wGCI with a heuristic score based on quantiles of segment lengths. Results: We sought to evaluate the association between the wGCI and patients’ survival in a proteogenomic cohort of 215 primary LUAD tumors profiled using whole-genome sequencing (WGS). In support of our hypothesis, we observed that patients had significantly better outcomes if their tumor genomes had longer segments compared to those with a high degree of fragmentation (P=0.014). Utilizing the wGCI, we found that tumor genomes with dispersed breakage (and low contiguity) were associated with worst outcomes (P=0.01). To identify mechanisms associated with dispersed breakage patterns we compared genomic features of the two groups. We found that LUAD tumors with highly fragmented genomes have a higher rate of TERT amplifications (P=0.005) and increased TERT RNA expression (P=2e-6). These tumors are also enriched for TP53 mutations (P=2e-16) and MYC amplifications (P=0.01). Given the cost and practical challenges of clinical WGS we leveraged mass-spectrometry proteomics to identify protein biomarkers. We found IGF2BP3 to be significantly upregulated (P=0.0006) in highly fragmented tumors and to be associated with worse outcomes (P=0.011). We use immunohistochemistry (IHC) to develop and validate IGF2BP3 as a prognostic biomarker in independent lung cancer cohorts. Conclusion: We introduced a novel quantitative measure of CIN that uniquely captures the impact of chromosome breakage on LUAD patients' clinical outcomes. Further, we identified upregulation of IGF2BP3 as a proxy to identify fragmented genomes using IHC. Our work underscores the value of mathematical modeling of genome breakage patterns to develop complex genomic biomarkers. Citation Format: Noshad Hosseini, Rahul Mannan, Alexey Nesvizhskii, Saravana Dhanasekaran, Marcin Cieslik. Development of a novel class of genomic biomarkers through mathematical modeling of cancer genome contiguity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr A034.

Improved detection of clinically relevant fusion transcripts in cancer by machine learning classification

BackgroundGenomic rearrangements in cancer cells can create fusion genes that encode chimeric proteins or alter the expression of coding and non-coding RNAs. In some cancer types, fusions involving specific kinases are used as targets for therapy. Fusion genes can be detected by whole genome sequencing (WGS) and targeted fusion panels, but RNA sequencing (RNA-Seq) has the advantageous capability of broadly detecting expressed fusion transcripts.ResultsWe developed a pipeline for validation of fusion transcripts identified in RNA-Seq data using matched WGS data from The Cancer Genome Atlas (TCGA) and applied it to 910 tumors from 11 different cancer types. This resulted in 4237 validated gene fusions, 3049 of them with at least one identified genomic breakpoint. Utilizing validated fusions as true positive events, we trained a machine learning classifier to predict true and false positive fusion transcripts from RNA-Seq data. The final precision and recall metrics of the classifier were 0.74 and 0.71, respectively, in an independent dataset of 249 breast tumors. Application of this classifier to all samples with RNA-Seq data from these cancer types vastly extended the number of likely true positive fusion transcripts and identified many potentially targetable kinase fusions. Further analysis of the validated gene fusions suggested that many are created by intrachromosomal amplification events with microhomology-mediated non-homologous end-joining.ConclusionsA classifier trained on validated fusion events increased the accuracy of fusion transcript identification in samples without WGS data. This allowed the analysis to be extended to all samples with RNA-Seq data, facilitating studies of tumor biology and increasing the number of detected kinase fusions. Machine learning could thus be used in identification of clinically relevant fusion events for targeted therapy. The large dataset of validated gene fusions generated here presents a useful resource for development and evaluation of fusion transcript detection algorithms.

CD74/SLC34A2-ROS1 Fusion Variants Involving the Transmembrane Region Predict Poor Response to Crizotinib in NSCLC Independent of TP53 Mutations

IntroductionVariable partners and breakpoints have been reported in patients with ROS1-rearranged NSCLC. Here, we investigated the association of fusion partners and breakpoints with crizotinib efficacy in NSCLCs with common ROS1 fusions. MethodsDNA and RNA next-generation sequencing (NGS) and immunohistochemistry were performed to characterize ROS1 fusions. ResultsUsing DNA NGS, we identified ROS1 fusions in 210 cases, comprising 171 common (CD74/EZR/TPM3/SDC4/SLC34A2-ROS1) and 39 uncommon (variants identified in <5%) ROS1 fusion cases. DNA NGS detected variable ROS1 genomic breakpoints in common ROS1 fusions, whereas RNA NGS found ROS1 breakpoints mainly occurring in exons 32, 34 and 35, resulting in long (exon 32) and short (exon 34 or 35) ROS1 fusions. ROS1 immunohistochemistry revealed that membranous and cytoplasmic staining was predominant in long ROS1 fusions, whereas cytoplasmic staining was predominant in short ROS1 fusions (p = 0.006). For patients who received first-line crizotinib, median progression-free survival (mPFS) was lower in patients with long ROS1 fusions than those with short ROS1 fusions (8.0 versus 24.0 mo, p = 0.006). Moreover, mPFS for patients with and without TP53 mutations was 8.0 and 19.0 months, respectively (p = 0.159); mPFS for patients with and without BIM deletion polymorphism was 5.0 and 22.0 months, respectively (p = 0.003). When analyzing together with fusion partners, patients with long CD74/SLC34A2-ROS1 fusions were found to have shorter PFS than those with other ROS1, regardless of the presence or absence of TP53 mutations (p < 0.001 and p = 0.002, respectively). ConclusionsLong CD74/SLC34A2-ROS1 fusions, which retain transmembrane regions in ROS1 and fusion partners, are associated with poor response to crizotinib independent of TP53 mutations.

Distinct Pattern of ABL1 Genomic Breakpoints in Chronic Myeloid Leukemia and BCR::ABL1-Positive Acute Lymphoblastic Leukemia: Analysis of 884 Patients with Minor and Major BCR::ABL1 Fusion

The BCR::ABL1 fusion gene is a hallmark of chronic myeloid leukemia (CML) but is also found in patients with acute lymphoblastic leukemia (ALL). There are two main breakpoint clusters in BCR - “minor” (between exons 1-2, resulting in p190 fusion protein, prevalent in ALL and scarce in CML) and “Major” (between exons 13-15, resulting in p210 protein). On the ABL1 side, the breakpoints are mostly localized between exons 1-3. Due to large intronic areas where the breakpoints occur, only a few papers have been published focusing on the structure of BCR::ABL1 fusions. Moreover, with a single exception, these studies included only the Major- BCR::ABL1 patients. Here, we focused on the analysis of BCR::ABL1 breakpoints involving CML and ALL, children and adults, and Major and minor forms of fusion. To our knowledge, we present data on the largest cohort of patients with BCR::ABL1 fusion identified at the DNA level described to date. Genomic breakpoints were found in 884 patients with BCR::ABL1+ ALL (n=463) and CML (n=421) by multiplex long distance PCR/Sanger sequencing or by NGS Custom Target Enrichment. The RSS database, MEME software and RepeatMasker were used to search RSS, specific motifs known for mediation of DNA breaks (59 motifs) and interspersed and other types of repeats within particular DNA areas. The uniformity test performed on breakpoint distribution within the minor (n=356) and Major (n=528) BCR areas revealed a non-random pattern (p=2.34e-21 and p=2.56e-10, respectively) with breakpoints accumulated in the second halves of the intron 1 (minor BCR) and intron 13 (Major BCR). Within the ABL1 area, breakpoint sites were distributed more randomly (p=9.28e-03); however, the breakpoint distribution within the ABL1 differed significantly between patients with CML and ALL (p=7.43e-05; see Figure) with higher accumulation of breakpoints near the 5‘ end of the ABL1 intron 1 in CML and near the 3‘ end of the intron 1 in ALL. The difference was not driven by the type of fusion (minor vs. Major BCR) as it was still visible even if only Major BCR::ABL1+ patients were analysed (414 CML and 108 ALL; p=2.28e-03). Comparison between various groups of patients (females vs. males; adults vs. children; various age groups, minor vs. Major BCR fusion [in ALL patients]), did not reveal a significantly distinct breakpoint distribution in any BCR or ABL1 area. Analysis of genomic breakpoints showed that fusions are mostly formed in loci with short homologies (49%; 1-71bp, median=2bp), by blunt end junctions (36%) or by a junction with insertion of random nucleotides (13%; 1-42bp, median=3bp) strongly suggesting NHEJ mechanism of double-strand break repair in vast majority of cases. In 313 patients we compared BCR::ABL1 and the reciprocal ABL1::BCR fusion. Vast majority of the BCR::ABL1 and ABL1::BCR breakpoints (81% and 79% on BCR and ABL1 area, respectively) were located within ±100bp window, showing almost precise reciprocal translocation, with negligible losses/gains of DNA resulting from the fusion. Analysis of the association of breakpoints with DNA motifs and chromatin structure did not reveal any significant association with the localization of breakpoints. In conclusion, we show different breakpoint distribution in ABL1 between CML and BCR::ABL1+ ALL. The double-strand breaks are repaired by NHEJ; however, we have not found any DNA or epigenetic motif, which might be responsible for the breakpoints. Our data suggest that the differences in breakpoint distribution are due to different chromatin accessibility and/or different relative positions of the BCR and ABL1 genes throughout the cell development, reflecting the origin of CML in earlier stages of hematopoiesis compared to ALL. Supported by AZV (NU21-03-00128) and NICR No. LX22NPO5102.

Circulating Tumor DNA (ctDNA) for Plasma Genotyping and Disease Monitoring in ALK-Positive Anaplastic Lymphoma (ALK+ALCL): A Proof of Concept Study

Introduction Circulating tumor DNA (ctDNA) detection has not been reported yet in ALK-positive anaplastic large cell lymphoma (ALK+ALCL), a rare aggressive non-Hodgkin lymphoma with a peak incidence in children, adolescents and young adults. In this study, we aimed to evaluate whether ctDNA can be detected, characterized and used to monitor minimal residual disease (MRD) in ALK+ALCL. Patients and Methods Plasma samples were collected from 23 French patients diagnosed with ALK+ALCL between November 2020 and March 2023. Based on cell-free DNA (cfDNA) extracted from plasma, we performed shallow whole genome sequencing (shWGS) and a comprehensive genomic profiling (CGP) of more than 500 genes covered at a median depth of over 3000 unique reads to assess ctDNA content. In this study, we defined samples as positive if they had a tumor fraction over 3%, evaluated by shWGS analysis, or if ALK rearrangements were identified using CGP. Additionally, ALK rearrangement genomic breakpoint were defined by CGP analysis. For each patient, specific digital droplet PCR (ddPCR) assays were designed based on the identified breakpoints to monitor ctDNA content during the ALK+ALCL disease follow-up. Results The median age of patients at the time of diagnosis was 13 years (range: 4-54). Sixteen patients, (69.6%) received at least one ALK tyrosine kinase inhibitor (TKI). A total of 80 plasma samples were collected at various time points from the 23 patients, with a median of 3 samples per patient (range: 1 - 20). Four samples failed for DNA extraction, resulting in 76 samples available for molecular analysis Of the 76 samples, 43 (56.6%) were analyzed using shWGS, 19 (25%) using CGP among which, 14 were analyzed using both techniques. CGP was found to be a more sensitive method for detecting ctDNA in ALK+ALCL compared to shWGS, with 12 out of 14 samples (85.7%) tested positive with CGP, compared to 5 out of 14 samples (35.7%) with shWGS (p&amp;lt;0.01). Of the 19 samples tested with CGP, ALK rearrangement was identified in 14 samples (73.7%), with NPM1:: ALK fusion detected in 11 samples, and ATIC:: ALK, TRAF1:: ALK and EEF1G:: ALK detected in one sample each. The average tumor mutational burden was low, with 5.3 mutations per megabase (mut/Mb) (range: 0-14.5 mut/Mb). No microsatellite instability was detected. Amplification of MDM4 and MYC genes was observed in three patients each. ANKRD26 was the most frequently mutated gene in the study, with four patients affected. LRP1B, epigenetic modifiers such as EP300 and KMT2A, and TP53 were mutated in three patients each. Interestingly, CGP allowed the identification of the ALK:c.3520T&amp;gt;C;p.(Phe1174Leu) mutation in a plasma sample collected during disease progression while the patient was on long lasting crizotinib therapy. Finally, we monitored MRD, based on ctDNA detection in 49 samples from 12 patients using ddPCR assays. Our results were compared with the established gold standard for MRD monitoring in ALK+ALCL, i.e. RT-PCR on circulating cells performed on the same samples. The ddPCR assay showed a 87% sensitivity, 100% specificity, 100% positive predictive value, and 83% negative predictive value. However, four samples had false-negative results due to pre-analytical sampling issues. These samples had been stored at room temperature without undergoing centrifugation for more than 24 hours. Conclusion To date, this study is the first to report on the feasibility and clinical value of ctDNA for the management of ALK+ALCL patients. CGP demonstrated high sensitivity in detecting ctDNA, identifying the genomic breakpoint within the ALK gene and, for the first time in ALK+ALCL, detecting resistance mutations to ALK TKI. Additionally, our unique patient-specific ddPCR approach was proven to be a cost-effective method for MRD monitoring. Altogether, these findings serve as a proof-of-concept for the development of ctDNA techniques in the clinical management of ALK+ALCL.

AML with t(4;12)(q12;p13): A Detailed Genomic and Transcriptomic Analysis Reveals Genomic Breakpoint Heterogeneity, Absence of Pdgfra Fusion Transcripts and Presence of Pdgfra Overexpression in a Subset of Cases

Background: Gene fusions are a frequent event in acute myeloid leukaemia (AML). It is estimated that about 40% of AML patients harbour a cytogenetic abnormality resulting in a gene fusion. However, AML with t(4;12)(q12;p13) is very rare, but it is often accompanied by an aggressive clinical course and a poor prognosis. As frequently indicated by fluorescence in situ hybridization analyses (FISH), patients are assumed to harbor an ETV6::PDGFRA fusion, which impacts the choice of therapy, as these patients can be treated with tyrosine kinase inhibitors. The genomic region on chromosome 4 involved in ETV6 rearrangements is densly packed with genes in close spatial proximity. Therefore, the resolution of chromosome banding analysis and also FISH is not sufficient to fully elucidate the fusion partners involved. Recent studies have pointed out that many of these patients do not harbor an ETV6::PDGFRA fusion but other rather unknown fusion partners have been elucidated. Aim: (1) Evaluation of the genomic breakpoints in patients with t(4;12)(q12;p13) ETV6-rearranged AML; (2) determine the alteration of PDGFRA expression in patients with t(4;12). Patients and Methods: 10 patients (F: 4, M: 6; median age: 63 [44-82] years) with a t(4;12)(q12;p13) indicated by FISH and chromosome analysis were included. Samples were analysed by whole genome and whole transcriptome sequencing (WGS/WTS). Sequencing was performed on NovaSeq instrument (Illumina). Fusions were called with Arriba, STAR-Fusion and Manta. For gene expression analysis WTS data were log2 transformed and normalized with the trimmed mean of M-values (TMM) method. Results: Based on chromosome analysis and FISH patients showed break events in 4q12 and 12p13. In all cases a FISH signal constellation typical for an ETV6 rearrangement was observed. The mutation spectrum for each patient of the most commonly mutated genes in AML was examined by use of WGS data. The median number of mutations was 3, with mutations in ASXL1 being the most common (6 patients) and none of the patients featuring mutations in the PDGFRA gene. WTS analysis revealed in-frame fusions in 6 of 10 patients involving genes located on chromosomes 4 and 12 (4 patients with ETV6::CHIC2, 1 patients with ETV6::SCFD2, 1 patient with ETV6::ADAMTS3). None of the 10 examined patients showed a gene fusion, or a fusion transcript involving PDGFRA. Based on WTS data, 7 of the 10 patients showed a PDGFRA overexpression. WGS breakpoint analysis showed that genetic breakpoints on chromosome 12 cluster in introns 1 (4 patients) and 2 (6 patients) of the ETV6 gene. In contrast chromosome breaks on chromosome 4 are heterogeneously distributed in the 4q12 region. Breakpoint comparison indicated that patients with chromosome breaks in a range from chr4:54,804,230-54,962,206 (7 patients) display PDGFRA overexpression. In contrast patients with chromosome breaks further downstream chr4:55,021,511-73,409,362 (3 patients) did not exhibit an increased PDGFRA expression. This suggests an ectopic expression of PDGFRA triggered by the translocation and independent of the existence of an in-frame fusion transcript. A chromosome break in the range of chr4:54,804,230-54,962,206 (seen in 7 patients) might result in the inactivation of a CTCF binding site (chr4:54,796,345-54,796,360) upstream of these chromosome breaks that is already known to induce PDGFRA overexpression when disrupted. Conclusions: Analysis of AML with t(4;12)(q12;p13) translocation by WGS and WTS provides detailed information that separates two subsets distinguished by distinct breakpoint cluster regions on 4q12 and PDGFRA gene expression. The clinical impact of increased PDGFRA gene expression on response to TKI and prognosis as well as the presence of additional fusion transcripts has to be evaluated in further studies.

Comprehensive NGS profiling to enable detection of ALK gene rearrangements and MET amplifications in non-small cell lung cancer.

Next-generation sequencing (NGS) is currently widely used for biomarker studies and molecular profiling to identify concurrent alterations that can lead to the better characterization of a tumor's molecular landscape. However, further evaluation of technical aspects related to the detection of gene rearrangements and copy number alterations is warranted. There were 12 ALK rearrangement-positive tumor specimens from patients with non-small cell lung cancer (NSCLC) previously detected via fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and an RNA-based NGS assay, and 26 MET high gene copy number (GCN) cases detected by FISH, selected for this retrospective study. All 38 pre-characterized cases were reassessed utilizing the PGDx™ elio™ tissue complete assay, a 505 gene targeted NGS panel, to evaluate concordance with these conventional diagnostic techniques. The detection of ALK rearrangements using the DNA-based NGS assay demonstrated excellent sensitivity with the added benefit of characterizing gene fusion partners and genomic breakpoints. MET copy number alterations were also detected; however, some discordances were observed likely attributed to differences in algorithm, reporting thresholds and gene copy number state. TMB was also assessed by the assay and correlated to the presence of NSCLC driver alterations and was found to be significantly lower in cases with NGS-confirmed canonical driver mutations compared with those without (p=0.0019). Overall, this study validates NGS as an accurate approach for detecting structural variants while also highlighting the need for further optimization to enable harmonization across methodologies for amplifications.

ABL-class Genomic Breakpoint Q-PCR: A Patient-specific Approach for MRD Monitoring in Acute Lymphoblastic Leukemia.

ABL-class Genomic Breakpoint Q-PCR: A Patient-specific Approach for MRD Monitoring in Acute Lymphoblastic Leukemia.

Fast and sensitive validation of fusion transcripts in whole-genome sequencing data

BackgroundIn cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications.ResultsWe describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing (WGS) data. Our pipeline uses discordant read pairs to identify supported fusion events and analyzes soft-clipped read alignments to determine genomic breakpoints. We have tested it on matched RNA-Seq and WGS data for both tumors and cancer cell lines and show that it can be used to validate both new predicted gene fusions and experimentally validated fusion events. It was considerably faster and more sensitive than using BreakDancer and Manta, software that is instead designed to detect many different types of structural variants on a genome-wide scale.ConclusionsWe have developed a fast and very sensitive pipeline for validation of gene fusions detected by RNA-Seq in matched WGS data. It can be used to identify high-quality gene fusions for further bioinformatic and experimental studies, including validation of genomic breakpoints and studies of the mechanisms that generate fusions. In a clinical setting, it could help find expressed gene fusions for personalized therapy.

Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer - bioinformatics study for a potential link to MMEJ.

Microhomology-mediated end joining (MMEJ), an error-prone DNA damage repair mechanism, frequently leads to chromosomal rearrangements due to its ability to engage in promiscuous end joining of genomic instability and also leads to increasing mutational load at the sequences flanking the breakpoints (BPs). In this study, we systematically investigated the homology sequences around the genomic breakpoint area of human fusion genes, which were formed by the chromosomal rearrangements initiated by DNA double-strand breakage. Since the RNA-seq data is the typical data set to check the fusion genes, for the known exon junction fusion breakpoints identified from RNA-seq data, we have to infer the high chance of genomic breakpoint regions. For this, we utilized the high feature importance score area calculated from our recently developed fusion BP prediction model, FusionAI and identified 151K microhomologies among ~24K fusion BPs in 20K fusion genes. From our multiple bioinformatics studies, we found a relationship between sequence homologies and the immune system. This in-silico study will provide novel knowledge on the sequence homologies around the coded structural variants.

Genomic breakpoint-specific monitoring of measurable residual disease in pediatric non-standard-risk acute myeloid leukemia.

Pediatric acute myeloid leukemia (AML) is a highly heterogeneous disease making standardized measurable residual disease (MRD) assessment challenging. Currently, patient-specific DNA-based assays are only rarely applied for MRD assessment in pediatric AML. We tested whether quantification of genomic breakpoint-specific sequences via quantitative polymerase chain reaction (gDNA-PCR) provides a reliable means of MRD quantification in children with non-standardrisk AML and compared its results to those obtained with state-of-the-art ten-color flow cytometry (FCM). Breakpointspecific gDNA-PCR assays were established according to Euro-MRD consortium guidelines. FCM-MRD assessment was performed according to the European Leukemia Network guidelines with adaptations for pediatric AML. Of 77 consecutively recruited non-standard-risk pediatric AML cases, 49 (64%) carried a chromosomal translocation potentially suitable for MRD quantification. Genomic breakpoint analysis returned a specific DNA sequence in 100% (41/41) of the cases submitted for investigation. MRD levels were evaluated using gDNA-PCR in 243 follow-up samples from 36 patients, achieving a quantitative range of at least 10-4 in 231/243 (95%) of samples. Comparing gDNA-PCR with FCM-MRD data for 183 bone marrow follow-up samples at various therapy timepoints showed a high concordance of 90.2%, considering a cut-off of ≥0.1%. Both methodologies outperformed morphological assessment. We conclude that MRD monitoring by gDNA-PCR is feasible in pediatric AML with traceable genetic rearrangements and correlates well with FCM-MRD in the currently applied clinically relevant range, while being more sensitive below that. The methodology should be evaluated in larger cohorts to pave the way for clinical application.

Identification of complex and cryptic chromosomal rearrangements by optical genome mapping

BackgroundOptical genome mapping (OGM) has developed into a highly promising method for detecting structural variants (SVs) in human genomes. Complex chromosomal rearrangements (CCRs) and cryptic translocations are rare events that are considered difficult to detect by routine cytogenetic methods. In this study, OGM was applied to delineate the precise chromosomal rearrangements in three cases with uncertain or unconfirmed CCRs detected by conventional karyotyping and one case with a cryptic translocation suggested by fetal chromosomal microarray analysis (CMA).ResultsIn the three cases with CCRs, OGM not only confirmed or revised the original karyotyping results but also refined the precise chromosomal structures. In the case with a suspected translocation not detected by karyotyping, OGM efficiently identified the cryptic translocation and defined the genomic breakpoints with relatively high accuracy.ConclusionsOur study confirmed OGM as a robust alternative approach to karyotyping for the detection of chromosomal structural rearrangements, including CCRs and cryptic translocations.

The KMT2A recombinome of acute leukemias in 2023

Chromosomal rearrangements of the human KMT2A/MLL gene are associated with de novo as well as therapy-induced infant, pediatric, and adult acute leukemias. Here, we present the data obtained from 3401 acute leukemia patients that have been analyzed between 2003 and 2022. Genomic breakpoints within the KMT2A gene and the involved translocation partner genes (TPGs) and KMT2A-partial tandem duplications (PTDs) were determined. Including the published data from the literature, a total of 107 in-frame KMT2A gene fusions have been identified so far. Further 16 rearrangements were out-of-frame fusions, 18 patients had no partner gene fused to 5’-KMT2A, two patients had a 5’-KMT2A deletion, and one ETV6::RUNX1 patient had an KMT2A insertion at the breakpoint. The seven most frequent TPGs and PTDs account for more than 90% of all recombinations of the KMT2A, 37 occur recurrently and 63 were identified so far only once. This study provides a comprehensive analysis of the KMT2A recombinome in acute leukemia patients. Besides the scientific gain of information, genomic breakpoint sequences of these patients were used to monitor minimal residual disease (MRD). Thus, this work may be directly translated from the bench to the bedside of patients and meet the clinical needs to improve patient survival.

Abstract 313: Mechanisms of oncogenic tyrosine kinase fusion formation and selection in human cancers

Abstract Introduction: Tyrosine kinase (TK) fusions are common events in the development of resistance to targeted therapy for non-small cell lung cancer (NSCLC) and others. The mechanisms by which recurrent breakpoints are generated in solid tumors and by which they are selected are unclear. APOBEC3 proteins are the main factors for mutations in solid cancers and the mutagenic activity of APOBEC3 can activate the DNA damage response by contributing to double-strand break (DSB) formation. However, the possibility that APOBEC3 proteins could induce chromosomal translocations in solid tumors has not been investigated. In addition, mechanistic explanations on how recurrent chromosomal translocation occur in lung cancer and solid tumors in precise genomic breakpoints and with specific partners are lacking. In this work, we present a newly developed functionally active chromosomal translocation sequencing (FACTS) approach to provide insights on the mechanisms that determine the selection of oncogenic fusions in human cancers. Methods: We applied FACTS to lung cells to map genome-wide translocations when DNA DSB is introduced in TK genes by the CRISPR/Cas9 system. We generated genomic maps of DNA breakpoints joining to anaplastic lymphoma kinase (ALK) before and after selection by high-throughput genome-wide translocation sequencing (HTGTS). We tested the effect of APOBEC3 proteins in an overexpression system or in an all seven APOBEC3 gene knockout lung cells by FACTS. Results: Overexpression of APOBEC3 proteins significantly increased the formation of functional fusions compared to control cells. In addition, deletion of APOBEC3 genes significantly decreased the formation of functional fusions compared to APOBEC3 wild-type cells. With the FACTS data and bioinformatics analyses, we found that gene expression rather than locus accessibility dictates the selection of TK fusions and that TK fusions are likely selected from a pool of translocations occurring at the right position in transcribe genes. In addition, we found that active transcription in silent genes was sufficient to introduce the spontaneous formation of functional fusions. By using HTGTS approach, we found that breakpoints before selection did not show a preferential strand bias, but after selection the breakpoints showed a strong bias. By comparing oncogenic potential of EML4-ALK fusion variants, we found that protein stability, but not subcellular localization, is key to determining the exon usage of EML-ALK fusions. In addition, we revealed that the selection of fusion partners for each TK is more likely dictated by protein stability rather than by mRNA expression. Conclusion: FACTS allows rapid and comprehensive mapping of functional chromosomal translocations and provides insights into the mechanisms of their formation and selection. The FACTS approach could be used to predict the oncogenic activity of fusion proteins to guide clinical decisions. Citation Format: Taek-Chin Cheong, Ahram Jang, Qi Wang, Giulia C. Leonardi, Maria K. Lehtinen, Marian H. Harris, Roberto Chiarle. Mechanisms of oncogenic tyrosine kinase fusion formation and selection in human cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 313.

Deciphering integration loci of CHO manufacturing cell lines using long read nanopore sequencing

Despite advances in genetic characterization of Chinese hamster ovary (CHO) cell lines regarding identification of integration sites using next generation sequencing, e.g. targeted locus amplification sequencing (TLA-seq), the concatemer structure of the integrated vectors remains elusive. Here, the entire integration locus of two CHO manufacturing cell lines was reconstructed combining CRISPR/Cas9 target enrichment, nanopore sequencing and the Canu de novo assembly pipeline. An IgG producing CHO cell line integrated 3 vector copies, which were near full-length and contained all relevant vector elements such as transgenes and their promoters on each of the vector copies. In contrast, a second CHO cell line producing a bivalent bispecific antibody integrated 7 highly fragmented vector copies in different orientations leading to head-to-head and tail-to-tail fusions. The size of the vector fragments ranged from 3.0 to 11.4 kbp each carrying 1–3 transgenes. The breakpoints of the genome-vector and vector-vector junctions were validated using Sanger sequencing and Southern blotting. A comparison to TLA-seq data confirmed the genomic breakpoints, but most of the breakpoints of the vector-vector fusions were missed by TLA-seq. For the first time, the complete transgene locus of CHO manufacturing cell lines could be deciphered. Strikingly, the application of the nanopore long-read sequencing technology led to novel insights into the complexity of genomic transgene integrations of CHO manufacturing cell lines generated via random integration.

Copy Number Variation and Allele Ratio Analysis in Candida albicans Using Whole Genome Sequencing Data.

Whole genome sequencing of human fungal pathogens has revolutionized the speed and accuracy in which sequence variants that cause antifungal resistance can be identified. Genome rearrangements resulting in copy number variation (CNV) are a significant source of acquired antifungal drug resistance across diverse fungal species. Some CNVs are transient in nature, while other CNVs are stable and well tolerated even in the absence of antifungal drugs. By visualizing whole genome sequencing read depth as a function of genomic location, CNVs and CNV breakpoints (genomic positions where the copy number changes occur relative to the rest of the genome) are rapidly identified. A similar analysis can be used to visualize allele ratio changes that occur across the genomes of heterozygous fungal species, both in the presence and absence of CNVs. This protocol walks through the bioinformatic analysis of CNVs and allele ratios utilizing free, open-source visualization tools. We provide code to use with an example dataset (matched antifungal drug-sensitive and drug-resistant Candida albicans isolates) and notes on how to expand this protocol to other fungal genomes.