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OBJECTIVE To evaluate the diagnostic, prognostic, and therapeutic utility of a cancer genomic diagnostic assay (SearchLight DNA; Vidium Animal Health) for diagnostically ambiguous cancer cases. ANIMALS 69 privately owned dogs with ambiguous cancer diagnoses and for which the genomic assay was performed. PROCEDURES Genomic assay reports generated between September 28, 2020, and July 31, 2022, for dogs with malignancy or suspected malignancy were reviewed to determine the assay’s clinical utility defined as providing diagnostic clarity, prognostic information, and/or therapeutic options. RESULTS Genomic analysis provided diagnostic clarity in 37 of 69 cases (54%; group 1) and therapeutic and/or prognostic information in 22 of the remaining 32 cases (69%; group 2) for which the diagnosis remained elusive. Overall, the genomic assay was clinically useful in 86% (59/69) of cases. CLINICAL RELEVANCE To our knowledge, this was the first study to evaluate the multifaceted clinical utility of a single cancer genomic test in veterinary medicine. Study findings supported the use of tumor genomic testing for dogs with cancer, particularly those that are diagnostically ambiguous and therefore inherently challenging to manage. This evidence-driven genomic assay provided diagnostic guidance, prognostic support, and therapeutic options for most patients with an unclear cancer diagnosis that would otherwise have an unsubstantiated clinical plan. Furthermore, 38% (26/69) of samples were easily obtained aspirates. Sample factors (sample type, percentage of tumor cells, and number of mutations) did not influence diagnostic yield. Our study demonstrated the value of genomic testing for the management of canine cancer.

Speedy Genetic Diagnosis Infantile encephalopathy is associated with approximately 1500 genetic diseases. Without prompt treatment, permanent neurologic injury or death may occur. Here, the genome ...

The human genome is diploid with one haploid genome inherited from the maternal and one from the paternal lineage. Within each haploid genome, large structural variants such as deletions, duplications, inversions, and translocations are extensively present and many are known to affect biological functions and cause disease. The ultimate goal is to resolve these large complex structural variants (SVs) and place them in the correct haploid genome with correct location, orientation, and copy number. Current methods such as karyotyping, chromosomal microarray (CMA), PCR-based tests, and next-generation sequencing fail to reach this goal either due to limited resolution, low throughput, or short read length. Bionano Genomics9 next-generation mapping (NGM) offers a high-throughput, genome-wide method able to detect SVs of one kilobase pairs (kbp) and up. By imaging extremely long genomic molecules of up to megabases in size, the structure and copy number of complex regions of the genome including interspersed and long tandem repeats can be elucidated in their native form without inference. Here we tested Bionano9s SV high sensitivity discovery algorithm, Bionano Solve 3.0, on in silico generated diploid genomes with artificially incorporated SVs based on the reference genome, hg19, achieving over 90% overall detection sensitivity for heterozygous SVs larger than 1 kbp. Next, in order to benchmark large SV detection sensitivity and accuracy on real biological data, we used Bionano NGM to map two naturally occurring hydatidiform mole cell lines, CHM1 and CHM13, each containing a different duplicated haploid genome. By de novo assembling each of two mole9s genome separately followed by assembling a mixture of CHM1 and CHM13 data, we were able to call 2156 unique SVs (> 1.5 kbp) in each haploid mole and a simulated diploid. By comparing the simulated diploid SV calls against the SV calls in each single haploid mole assembly we established 87.4% sensitivity for detection of heterozygous SVs and 99.2% sensitivity for homozygous SVs. In comparison, a recent SV study on the same CHM1/CHM13 samples using long read NGS alone showed 54% sensitivity for detection of heterozygous SVs and 77.9% for homozygous SVs larger than 1.5 kbp. We also compared an SV call set of the diploid cell line NA12878 with the results of an earlier mapping study (Mak AC, 2016) and found concordance with 89% of the detected SVs found in the previous study and, in addition, 2599 novel SVs were detected. Finally, two pathogenic SVs were found in cell lines from individuals with developmental disorders. De novo comprehensive SV discovery by Bionano NGM is shown to be a fast, inexpensive and robust method, now with an automated informatics workflow.

Background Circulating cell free fetal DNA has enabled non-invasive prenatal fetal aneuploidy testing without direct discrimination of the genetically distinct maternal and fetal DNA. Current testing may be improved by specifically enriching the sample material for fetal DNA. DNA methylation may allow for such a separation of DNA and thus support additional clinical opportunities; however, this depends on knowledge of the methylomes of ccf DNA and its cellular contributors. Results Whole genome bisulfite sequencing was performed on a set of unmatched samples including ccf DNA from 8 non-pregnant (NP) and 7 pregnant female donors and genomic DNA from 7 maternal buffy coat and 5 placenta samples. We found CpG cytosines within longer fragments were more likely to be methylated, linking DNA methylation and fragment size in ccf DNA. Comparison of the methylomes of placenta and NP ccf DNA revealed many of the 51,259 identified differentially methylated regions (DMRs) were located in domains exhibiting consistent placenta hypomethylation across millions of consecutive bases, regions we termed placenta hypomethylated domains (PHDs). We found PHDs were consistently located within regions exhibiting low CpG and gene density. DMRs identified when comparing placenta to NP ccf DNA were recapitulated in pregnant ccf DNA, confirming the ability to detect differential methylation in ccf DNA mixtures. Conclusions We generated methylome maps for four sample types at single base resolution, identified a link between DNA methylation and fragment length in ccf DNA, identified DMRs between sample groups, and uncovered the presence of megabase-size placenta hypomethylated domains. Furthermore, we anticipate these results to provide a foundation to which future studies using discriminatory DNA methylation may be compared.

The immune epitope database analysis resource (IEDB-AR: http://tools.iedb.org) is a collection of tools for prediction and analysis of molecular targets of T- and B-cell immune responses (i.e. epitopes). Since its last publication in the NAR webserver issue in 2008, a new generation of peptide:MHC binding and T-cell epitope predictive tools have been added. As validated by different labs and in the first international competition for predicting peptide:MHC-I binding, their predictive performances have improved considerably. In addition, a new B-cell epitope prediction tool was added, and the homology mapping tool was updated to enable mapping of discontinuous epitopes onto 3D structures. Furthermore, to serve a wider range of users, the number of ways in which IEDB-AR can be accessed has been expanded. Specifically, the predictive tools can be programmatically accessed using a web interface and can also be downloaded as software packages.

We present a new release of the immune epitope database analysis resource (IEDB-AR, http://tools.immuneepitope.org), a repository of web-based tools for the prediction and analysis of immune epitopes. New functionalities have been added to most of the previously implemented tools, and a total of eight new tools were added, including two B-cell epitope prediction tools, four T-cell epitope prediction tools and two analysis tools.

Background Circulating cell-free (ccf) fetal DNA comprises 3–20% of all the cell-free DNA present in maternal plasma. Numerous research and clinical studies have described the analysis of ccf DNA using next generation sequencing for the detection of fetal aneuploidies with high sensitivity and specificity. We sought to extend the utility of this approach by assessing semi-automated library preparation, higher sample multiplexing during sequencing, and improved bioinformatic tools to enable a higher throughput, more efficient assay while maintaining or improving clinical performance. Methods Whole blood (10mL) was collected from pregnant female donors and plasma separated using centrifugation. Ccf DNA was extracted using column-based methods. Libraries were prepared using an optimized semi-automated library preparation method and sequenced on an Illumina HiSeq2000 sequencer in a 12-plex format. Z-scores were calculated for affected chromosomes using a robust method after normalization and genomic segment filtering. Classification was based upon a standard normal transformed cutoff value of z = 3 for chromosome 21 and z = 3.95 for chromosomes 18 and 13. Results Two parallel assay development studies using a total of more than 1900 ccf DNA samples were performed to evaluate the technical feasibility of automating library preparation and increasing the sample multiplexing level. These processes were subsequently combined and a study of 1587 samples was completed to verify the stability of the process-optimized assay. Finally, an unblinded clinical evaluation of 1269 euploid and aneuploid samples utilizing this high-throughput assay coupled to improved bioinformatic procedures was performed. We were able to correctly detect all aneuploid cases with extremely low false positive rates of 0.09%

Background Circulating cell-free fetal DNA has enabled non-invasive prenatal fetal aneuploidy testing without direct discrimination of the maternal and fetal DNA. Testing may be improved by specifically enriching the sample material for fetal DNA. DNA methylation may allow for such a separation of DNA; however, this depends on knowledge of the methylomes of circulating cell-free DNA and its cellular contributors. Results We perform whole genome bisulfite sequencing on a set of unmatched samples including circulating cell-free DNA from non-pregnant and pregnant female donors and genomic DNA from maternal buffy coat and placenta samples. We find CpG cytosines within longer fragments are more likely to be methylated. Comparison of the methylomes of placenta and non-pregnant circulating cell-free DNA reveal many of the 51,259 identified differentially methylated regions are located in domains exhibiting consistent placenta hypomethylation across millions of consecutive bases. We find these placenta hypomethylated domains are consistently located within regions exhibiting low CpG and gene density. Differentially methylated regions identified when comparing placenta to non-pregnant circulating cell-free DNA are recapitulated in pregnant circulating cell-free DNA, confirming the ability to detect differential methylation in circulating cell-free DNA mixtures. Conclusions We generate methylome maps for four sample types at single-base resolution, identify a link between DNA methylation and fragment length in circulating cell-free DNA, identify differentially methylated regions between sample groups, and uncover the presence of megabase-size placenta hypomethylated domains. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0645-x) contains supplementary material, which is available to authorized users.