LEO-Based Satellite Constellation for Moving Target Detection

With the rapid development of cooperative detection technology, target fusion detection with regard of LEO satellites can be realized by means of their diverse observation configurations. However, the existing constant false alarm ratio (CFAR) detection research rarely involves the space-based target fusion detection theory. In this paper, a novel multi-source fusion detection method based on LEO satellites is presented. Firstly, the pre-compensation function is constructed by employing the range and Doppler history of the cell where the antenna beam center is pointed. As a result, not only is the Doppler band broadening problem caused by the high-speed movement of the satellite platform, but the Doppler frequency rate (DFR) offset issue resulted from different observation configurations are alleviated synchronously. Then, the theoretical upper and lower limits of DFR are designed to achieve the effective clutter suppression and the accurate target echo fusion. Finally, the CFAR detection threshold based on the exponential weighted likelihood ratio is derived, which effectively increases the contrast ratio between the target cell and other background cells, and thus to provide an effective multi-source fusion detection method for LEO-based satellite constellation. Simulation results verify the effectiveness of the proposed algorithm.

FDJD: RNA-Seq Based Fusion Transcript Detection Using Jaccard Distance

Gene fusions events, which are the result of two genes fused together to create a hybrid gene, were first described in cancer cells in the early 1980s. These events are relatively common in many cancers including prostate, lymphoid, soft tissue, and breast. Recent advances in next-generation sequencing (NGS) provide a high volume of genomic data, including cancer genomes. The detection of possible gene fusions requires fast and accurate methods. However, current methods suffer from inefficiency, lack of sufficient accuracy, and a high false-positive rate. We present an RNA-Seq fusion detection method that uses dimensionality reduction and parallel computing to speed up the computation. We convert the RNA categorical space into a compact binary array called binary fingerprints, which enables us to reduce the memory usage and increase efficiency. The search and detection of fusion candidates are done using the Jaccard distance. The detection of candidates is followed by refinement. We benchmarked our fusion prediction accuracy using both simulated and genuine RNA-Seq datasets. Paired-end Illumina RNA-Seq genuine data were obtained from 60 publicly available cancer cell line data sets. The results are compared against the state-of-the-art-methods such as STAR-Fusion, InFusion, and TopHat-Fusion. Our results show that FDJD exhibits superior accuracy compared to popular alternative fusion detection methods. We achieved 90% accuracy on simulated fusion transcript inputs, which is the highest among the compared methods while maintaining comparable run time.

NTRK Gene Fusion Detection in Atypical Spitz Tumors

Atypical Spitz tumors (AST) deviate from stereotypical Spitz nevi for one or more atypical features and are now regarded as an intermediate category of melanocytic tumors with uncertain malignant potential. Activating NTRK1/NTRK3 fusions elicit oncogenic events in Spitz lesions and are targetable with kinase inhibitors. However, their prevalence among ASTs and the optimal approach for their detection is yet to be determined. A series of 180 ASTs were screened with pan-TRK immunohistochemistry and the presence of NTRK fusions was confirmed using FISH, two different RNA-based NGS panels for solid tumors, and a specific real time RT-PCR panel. Overall, 26 ASTs showed pan-TRK immunostaining. NTRK1 fusions were detected in 15 of these cases showing cytoplasmic immunoreaction, whereas NTRK3 was detected in one case showing nuclear immunoreaction. Molecular tests resulted all positive in only two ASTs (included the NTRK3 translocated), RNA-based NGS and real time RT-PCR were both positive in three cases, and FISH and real time RT-PCR in another two cases. In seven ASTs NTRK1 fusions were detected only by FISH and in two cases only by real time RT-PCR. The frequency of NTRK fusions in ASTs is 9%, with a clear prevalence of NTRK1 compared to NTRK3 alterations. Pan-TRK immunohistochemistry is an excellent screening test. Confirmation of NTRK fusions may require the use of different molecular techniques.

A Novel NGS-Based Simultaneous Detection of DNA and RNA Biomarkers Using Total Nucleic Acid (TNA) for Acute Lymphocytic Leukemia (ALL)

Background: Acute Lymphocytic Leukemia (ALL) is the most common childhood cancer and accounts for about a quarter of adult acute leukemias. Current NCCN recommendations for clinical testing for risk stratification and treatment guidance include karyotyping, FISH testing for translocations, and RT-PCR for gene fusions and sequencing for DNA mutations detection. Most NGS based approaches test DNA mutations and RNA fusions separately, thereby requiring higher input material and multiple workflows adding to the cost and turn-around-time. An NGS based assay for the detection of DNA variants (NeoGenomics Heme NGS assay) in heme malignancies using Total Nucleic Acid (TNA) is already available in our clinical laboratory and complements FISH based fusion detection and karyotyping but an integral assay to detect both DNA and RNA alterations with a simple workflow for ALL is needed. Methods: We used TNA or RNA spiked-in with DNA to simulate TNA samples, extracted from 93 bone marrow and peripheral blood samples from patients and healthy donors, along with commercial fusion reference myeloid samples Seraseq Myeloid Fusion RNA Mix (SeraCare Inc.) controls. DNA/RNA libraries were prepared using a custom amplicon based Multimodal NGS panel (Qiagen Inc.) targeting 297 genes and 213 genes (select exons) for DNA and RNA fusion detection, respectively. The enriched dual indexed amplicon libraries were sequenced on an Illumina NovaSeq 6000. The sequence data was processed with a customized bioinformatic pipeline for DNA variant as well as a novel machine learning algorithm for RNA fusion detection. We analyzed sensitivity, specificity, accuracy, reproducibility, and repeatability for clinical use. The DNA variants were orthogonally confirmed using other NGS assays, and the RNA fusions were confirmed on an RNA-seq Archer assay or RT-Sanger confirmation assays. Results: Here, we developed and validated a single tube comprehensive NGS panel using a custom multimodal chemistry that uses TNA as input for simultaneous dual detection of DNA and RNA abnormalities in ALL patients' samples. We performed the analytical validation of our Heme NGS assay for the RNA panel to detect fusions in ALL, using TNA input for comprehensive DNA and RNA mutation detection. The fusion concordance was 95% for the RNA fusion panel. The assay detected BCR-ABL1 (7/7), ETV6-RUNX1 (1/1), KMT2A fusions (4/5), TCF3-PBX1 (1/1), and PCM1-JAK2(1/1). The specificity was determined at 100% using a set of 42 fusion negative samples. The limit of detection (LOD) was analyzed using serial dilutions to up to 3 log reduction (LR) using a the Seraseq Myeloid Fusion sample. The fusions were detected down to 1 LR. The reproducibility was tested using a positive fusion and Seraseq samples across three runs and was reported at 100%. Next, a small cohort of ALL samples (n=8) was included as part of this study to simultaneously evaluate DNA and RNA mutations. We detected pathogenic DNA variants in genes previously reported in ALL that included NOTCH1, PTEN, FLT3, IKZF1, JAK1, JAK2, KRAS, NF1, PAX5, U2AF1, TP53, and also RNA fusion BCR-ABL1, and the results were confirmed by an orthogonal NGS assay (NexCourse and RNA-Seqv1 for fusions). One sample carrying a BCR-ABL1 fusion (detected by RNA panel) also harbored mutations in IKZF1 in DNA (detected by DNA panel) that is reported as unfavorable prognostic biomarker for Ph-Like ALL demonstrating comprehensive panel could identify multiple variants within the same sample, demonstrating the advantage DNA+RNA testing has over the classical single gene FISH/RT-PCR testing for the efficient risk stratification and treatment in ALL patients. Conclusions: In this study, we demonstrated that the single tube TNA based NeoGenomics NGS assay can simultaneously detect the DNA and RNA biomarkers associated with ALL for improved diagnostic and prognostic recommendations. The single-tube assay for detection of both RNA fusions and DNA variants using the same sample could offer comprehensive and cost-effective solution for clinical laboratory test for ALL patient care. This is a promising approach that might be used as a dual DNA/RNA alterations detection on other hematological neoplasia. Disclosures Ramesh: Neo Genomics Laboratories: Current Employment. Koo: Neo Genomics Laboratories: Current Employment. Kang: Neo Genomics Laboratories: Current Employment. Ghosal: NeoGenomics Laboratories: Current Employment. Alarcon: NeoGenomics Laboratories: Current Employment. Gyuris: Neo Genomics Laboratories: Current Employment. Jung: NeoGenomics Laboratories, Inc.: Current Employment. Magnan: NeoGenomics Laboratories, Inc.: Current Employment. Nam: NeoGenomics Laboratories, Inc.: Current Employment. Thomas: NeoGenomics Laboratories, Inc.: Current Employment. Fabunan: NeoGenomics Laboratories, Inc.: Current Employment. Petersen: Neo Genomics Laboratories: Current Employment. Lopez-Diaz: NeoGenomics Laboratories, Inc.: Current Employment. Bender: NeoGenomics Laboratories, Inc.: Current Employment. Agersborg: NeoGenomics Laboratories, Inc.: Current Employment. Ye: Neo Genomics Laboratories: Current Employment. Funari: NeoGenomics Laboratories, Inc.: Current Employment.

RNA-Sequencing Improves Diagnostics and Treatment of Pediatric Hematological Malignancies

Background Diagnosis and treatment of hematological malignancies relies increasingly on the detection of underlying genetic abnormalities. Various laboratory techniques, including karyotyping, SNP-array, FISH, MLPA and RT-PCR are typically required to detect the full spectrum of clinically relevant genetic aberrations. These techniques are also hampered in their sensitivity by their targeted approach or lack of resolution. Ideally, an unbiased genome wide approach like RNA sequencing (RNA-seq) as a one-test-fits-all, could save costs and efforts and streamline diagnostic procedures. In the Netherlands, the care for all children with oncological disorders has been concentrated in a single, national center. Within the Laboratory of Childhood Cancer Pathology, we aim for a comprehensive diagnostic pipeline by implementing RNA-seq to aid diagnosis, prognosis and treatment of all children with cancer in the Netherlands. Methods We have established an RNA-seq based diagnostic pipeline, primarily aimed at detecting gene fusion events. Library prep is performed on 50-300 ng total RNA isolated from fresh (frozen) samples, followed by ribo-depletion and subsequent paired-end sequencing (2x150 nt) using the Illumina NovaSeq platform. Data is analyzed using the StarFusion algorithm for gene-fusion detection. We are prospectively comparing the results with routine diagnostic procedures. In addition, we are validating the detection of single nucleotide variants (SNVs) from RNA-seq data and developing a diagnostic classifier, using a nearest neighbor network approach. Results Based on RNA-seq profiling in diagnostics for all patients entering the Princess Maxima Center, there are several use-cases that highlight the value of RNA-seq. 1) In a prospective cohort of 244 patients (pan-cancer, including 97 hematological malignancies) we have shown that the diagnostic yield for detecting gene fusion events increased by approximately 40% compared to classical methods. An example is the TNIP1--PDGFRB gene fusion in a patient with pre B-ALL, making this patient eligible for imatinib treatment, which was not detected by other methods. 2) Variant calling on RNA-seq shows that activating mutations in e.g. KRAS are detected with high sensitivity, stratifying patients for therapeutic MEK intervention. 3) By expression outlier analysis, we were able to detect various promotor exchanges, e.g. IGH-MYC or IGH--DUX4, which are typically hard to detect by molecular techniques since the genomic breakpoint is highly variable and no chimeric transcript is formed. 4) Preliminary results from our diagnostic classifier show its potential to predict subclasses of hematological malignancies, e.g. high-hyperdiploid or bi-phenotypic ALL patients. 5) Fusion gene breakpoints detected by RNA-seq serve as a target for MRD analysis, allowing us to monitor disease progression and therapy response in individual patients. Currently, RNA-seq data is available for more than 1500 pediatric tumor samples. At the upcoming conference we will present an update of our results and some typical cases highlighting the added value of RNA-seq in routine diagnostics. Conclusion We show that RNA-seq on pediatric cancer samples is feasible and of great value for routine diagnostics. It has a higher sensitivity to detect gene fusion events compared to targeted assays. RNA-seq based gene fusion detection, in combination with mutation and expression analysis, is also promising to improve classification of malignancies, prognosis and stratification of patients for targeted therapies. Disclosures No relevant conflicts of interest to declare.

SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA

Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a de-novo assembly approach. Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified.

Methods for actionable gene fusion detection in lung cancer: now and in the future

Although gene fusions occur rarely in non-small-cell lung cancer (NSCLC) patients, they represent a relevant target in treatment decision algorithms. To date, immunohistochemistry and fluorescence in situ hybridization are the two principal methods used in clinical trials. However, using these methods in routine clinical practice is often impractical and time consuming because they can only analyze single genes and the quantity of tissue material is often insufficient. Thus, novel technologies, able to test multiple genes in a single run with minimal sample input, are being under investigation. Here, we discuss the utility of next-generation sequencing and nCounter technologies in detecting simultaneous gene fusions in NSCLC patients.