Myxoma virus lacking the host range determinant M062 stimulates cGAS-dependent type 1 interferon response and unique transcriptomic changes in human monocytes/macrophages.

The evolutionarily successful poxviruses possess effective and diverse strategies to circumvent or overcome host defense mechanisms. Poxviruses encode many immunoregulatory proteins to evade host immunity to establish a productive infection and have unique means of inhibiting DNA sensing-dependent type 1 interferon (IFN-I) responses, a necessity given their dsDNA genome and exclusively cytoplasmic life cycle. We found that the key DNA sensing inhibition by poxvirus infection was dominant during the early stage of poxvirus infection before DNA replication. In an effort to identify the poxvirus gene products which subdue the antiviral proinflammatory responses (e.g., IFN-I response), we investigated the function of one early gene that is the known host range determinant from the highly conserved poxvirus host range C7L superfamily, myxoma virus (MYXV) M062. Host range factors are unique features of poxviruses that determine the species and cell type tropism. Almost all sequenced mammalian poxviruses retain at least one homologue of the poxvirus host range C7L superfamily. In MYXV, a rabbit-specific poxvirus, the dominant and broad-spectrum host range determinant of the C7L superfamily is the M062R gene. The M062R gene product is essential for MYXV infection in almost all cells tested from different mammalian species and specifically inhibits the function of host Sterile α Motif Domain-containing 9 (SAMD9), as M062R-null (ΔM062R) MYXV causes abortive infection in a SAMD9-dependent manner. In this study we investigated the immunostimulatory property of the ΔM062R. We found that the replication-defective ΔM062R activated host DNA sensing pathway during infection in a cGAS-dependent fashion and that knocking down SAMD9 expression attenuated proinflammatory responses. Moreover, transcriptomic analyses showed a unique feature of the host gene expression landscape that is different from the dsDNA alone-stimulated inflammatory state. This study establishes a link between the anti-neoplastic function of SAMD9 and the regulation of innate immune responses.

TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use.

BACKGROUND: The study of cancer genomics continually matures as the number of patient samples sequenced increases. As more data is generated, oncogenic drivers for specific cancer types are discovered along with their associated risks. This in turn leads to potential treatment strategies that pave the way to precision medicine. However, significant financial and analytical barriers make it infeasible to sequence the entire genome of every patient. In contrast, targeted sequencing panels give reliable information on relevant portions of the genome at a fiscally responsible cost. Therefore, we have created the Targeted Panel (TarPan) Viewer, a software tool, to investigate this type of data. RESULTS: TarPan Viewer helps investigators understand data from targeted sequencing data by displaying the information through a web browser interface. Through this interface, investigators can easily observe copy number changes, mutations, and structural events in cancer samples. The viewer runs in R Shiny with a robust SQLite backend and its input is generated from bioinformatic algorithms reliably described in the literature. Here we show the results from using TarPan Viewer on publicly available follicular lymphoma, breast cancer, and multiple myeloma data. In addition, we have tested and utilized the viewer internally, and this data has been used in high-impact peer-reviewed publications. CONCLUSIONS: We have designed a flexible, simple to setup viewer that is easily adaptable to any type of cancer targeted sequencing, and has already proven its use in a research laboratory environment. Further, we believe with deeper sequencing and/or more targeted application it could be of use in the clinic in conjunction with an appropriate targeted sequencing panel as a cost-effective diagnostic test, especially in cancers such as acute leukemia or diffuse large B-cell lymphoma that require rapid interventions.

Clonal selection and double-hit events involving tumor suppressor genes underlie relapse in myeloma.

To elucidate the mechanisms underlying relapse from chemotherapy in multiple myeloma, we performed a longitudinal study of 33 patients entered into Total Therapy protocols investigating them using gene expression profiling, high-resolution copy number arrays, and whole-exome sequencing. The study illustrates the mechanistic importance of acquired mutations in known myeloma driver genes and the critical nature of biallelic inactivation events affecting tumor suppressor genes, especially TP53, the end result being resistance to apoptosis and increased proliferation rates, which drive relapse by Darwinian-type clonal evolution. The number of copy number aberration changes and biallelic inactivation of tumor suppressor genes was increased in GEP70 high risk, consistent with genomic instability being a key feature of high risk. In conclusion, the study highlights the impact of acquired genetic events, which enhance the evolutionary fitness level of myeloma-propagating cells to survive multiagent chemotherapy and to result in relapse.

Enhancing cancer clonality analysis with integrative genomics.

INTRODUCTION: It is understood that cancer is a clonal disease initiated by a single cell, and that metastasis, which is the spread of cancer from the primary site, is also initiated by a single cell. The seemingly natural capability of cancer to adapt dynamically in a Darwinian manner is a primary reason for therapeutic failures. Survival advantages may be induced by cancer therapies and also occur as a result of inherent cell and microenvironmental factors. The selected "more fit" clones outmatch their competition and then become dominant in the tumor via propagation of progeny. This clonal expansion leads to relapse, therapeutic resistance and eventually death. The goal of this study is to develop and demonstrate a more detailed clonality approach by utilizing integrative genomics. METHODS: Patient tumor samples were profiled by Whole Exome Sequencing (WES) and RNA-seq on an Illumina HiSeq 2500 and methylation profiling was performed on the Illumina Infinium 450K array. STAR and the Haplotype Caller were used for RNA-seq processing. Custom approaches were used for the integration of the multi-omic datasets. RESULTS: Reported are major enhancements to CloneViz, which now provides capabilities enabling a formal tumor multi-dimensional clonality analysis by integrating: i) DNA mutations, ii) RNA expressed mutations, and iii) DNA methylation data. RNA and DNA methylation integration were not previously possible, by CloneViz (previous version) or any other clonality method to date. This new approach, named iCloneViz (integrated CloneViz) employs visualization and quantitative methods, revealing an integrative genomic mutational dissection and traceability (DNA, RNA, epigenetics) thru the different layers of molecular structures. CONCLUSION: The iCloneViz approach can be used for analysis of clonal evolution and mutational dynamics of multi-omic data sets. Revealing tumor clonal complexity in an integrative and quantitative manner facilitates improved mutational characterization, understanding, and therapeutic assignments.

Revealing the inherent heterogeneity of human malignancies by variant consensus strategies coupled with cancer clonal analysis.

Tumors are heterogeneous in composition. They are composed of cancer cells proper, along with stromal elements that collectively form a microenvironment, all of which are necessary to nurture the malignant process. In addition, many of the stromal cells are modified to support the unique needs of the malignant state. Tumors are composed of a variety of clones or subpopulations of cancer cells, which may differ in karyotype, growth rate, expression of cell surface markers, sensitivity to therapeutics, etc. New tools and methods to provide an improved understanding of tumor clonal architecture are needed to guide therapy.

Leveraging the new with the old: providing a framework for the integration of historic microarray studies with next generation sequencing.

Next Generation Sequencing (NGS) methods are rapidly providing remarkable advances in our ability to study the molecular profiles of human cancers. However, the scientific discovery offered by NGS also includes challenges concerning the interpretation of large and non-trivial experimental results. This task is potentially further complicated when a multitude of molecular profiling modalities are available, with the goal of a more integrative and comprehensive analysis of the cancer biology.

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

BACKGROUND: Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. METHODS: Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. RESULTS: Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. CONCLUSION: A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

An advanced molecular medicine case report of a rare human tumor using genomics, pathomics, and radiomics.

Background: Pulmonary Sclerosing Pneumocytoma (PSP) is a rare tumor of the lung with a low malignant potential that primarily affects females. Initial studies of PSP focused primarily on analyzing features uncovered using conventional X-ray or CT imaging. In recent years, because of the widespread use of next-generation sequencing (NGS), the study of PSP at the molecular-level has emerged. Methods: Analytical approaches involving genomics, radiomics, and pathomics were performed. Genomics studies involved both DNA and RNA analyses. DNA analyses included the patient's tumor and germline tissues and involved targeted panel sequencing and copy number analyses. RNA analyses included tumor and adjacent normal tissues and involved studies covering expressed mutations, differential gene expression, gene fusions and molecular pathways. Radiomics approaches were utilized on clinical imaging studies and pathomics techniques were applied to tumor whole slide images. Results: A comprehensive molecular profiling endeavor involving over 50 genomic analyses corresponding to 16 sequencing datasets of this rare neoplasm of the lung were generated along with detailed radiomic and pathomic analyses to reveal insights into the etiology and molecular behavior of the patient's tumor. Driving mutations (AKT1) and compromised tumor suppression pathways (TP53) were revealed. To ensure the accuracy and reproducibility of this study, a software infrastructure and methodology known as NPARS, which encapsulates NGS and associated data, open-source software libraries and tools including versions, and reporting features for large and complex genomic studies was used. Conclusion: Moving beyond descriptive analyses towards more functional understandings of tumor etiology, behavior, and improved therapeutic predictability requires a spectrum of quantitative molecular medicine approaches and integrations. To-date this is the most comprehensive study of a patient with PSP, which is a rare tumor of the lung. Detailed radiomic, pathomic and genomic molecular profiling approaches were performed to reveal insights regarding the etiology and molecular behavior. In the event of recurrence, a rational therapy plan is proposed based on the uncovered molecular findings.

Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples.

Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens (KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.

NPARS-A Novel Approach to Address Accuracy and Reproducibility in Genomic Data Science.

Background: Accuracy and reproducibility are vital in science and presents a significant challenge in the emerging discipline of data science, especially when the data are scientifically complex and massive in size. Further complicating matters, in the field of genomic-based science high-throughput sequencing technologies generate considerable amounts of data that needs to be stored, manipulated, and analyzed using a plethora of software tools. Researchers are rarely able to reproduce published genomic studies. Results: Presented is a novel approach which facilitates accuracy and reproducibility for large genomic research data sets. All data needed is loaded into a portable local database, which serves as an interface for well-known software frameworks. These include python-based Jupyter Notebooks and the use of RStudio projects and R markdown. All software is encapsulated using Docker containers and managed by Git, simplifying software configuration management. Conclusion: Accuracy and reproducibility in science is of a paramount importance. For the biomedical sciences, advances in high throughput technologies, molecular biology and quantitative methods are providing unprecedented insights into disease mechanisms. With these insights come the associated challenge of scientific data that is complex and massive in size. This makes collaboration, verification, validation, and reproducibility of findings difficult. To address these challenges the NGS post-pipeline accuracy and reproducibility system (NPARS) was developed. NPARS is a robust software infrastructure and methodology that can encapsulate data, code, and reporting for large genomic studies. This paper demonstrates the successful use of NPARS on large and complex genomic data sets across different computational platforms.

Exogenous phosphatidic acid reduces acetaminophen-induced liver injury in mice by activating hepatic interleukin-6 signaling through inter-organ crosstalk.

We previously demonstrated that endogenous phosphatidic acid (PA) promotes liver regeneration after acetaminophen (APAP) hepatotoxicity. Here, we hypothesized that exogenous PA is also beneficial. To test that, we treated mice with a toxic APAP dose at 0 h, followed by PA or vehicle (Veh) post-treatment. We then collected blood and liver at 6, 24, and 52 h. Post-treatment with PA 2 h after APAP protected against liver injury at 6 h, and the combination of PA and N-acetyl-l-cysteine (NAC) reduced injury more than NAC alone. Interestingly, PA did not affect canonical mechanisms of APAP toxicity. Instead, transcriptomics revealed that PA activated interleukin-6 (IL-6) signaling in the liver. Consistent with that, serum IL-6 and hepatic signal transducer and activator of transcription 3 (Stat3) phosphorylation increased in PA-treated mice. Furthermore, PA failed to protect against APAP in IL-6-deficient animals. Interestingly, IL-6 expression increased 18-fold in adipose tissue after PA, indicating that adipose is a source of PA-induced circulating IL-6. Surprisingly, however, exogenous PA did not alter regeneration, despite the importance of endogenous PA in liver repair, possibly due to its short half-life. These data demonstrate that exogenous PA is also beneficial in APAP toxicity and reinforce the protective effects of IL-6 in this model.

Sustained fetal hematopoiesis causes juvenile death from leukemia: evidence from a dual-age-specific mouse model.

It is not clear whether disrupted age-specific hematopoiesis contributes to the complex manifestations in leukemia patients who carry identical mutations, particularly in pediatric and adult patients with similar clinical characteristics. By studying a dual-age-specific mouse model, we demonstrate that (1) loss of Pten during the fetal-to-adult hematopoiesis switch (hematopoiesis switch) causes sustained fetal hematopoiesis, resulting in death in juvenile leukemia; (2) myeloid-biased hematopoiesis in juvenile mice is associated with the sustained fetal properties of hematopoietic stem cells (HSCs); (3) the age specificity of juvenile myelomonocytic leukemia depends on the copy number of Pten and Nf1; (4) single-allelic Pten deletion during the hematopoiesis switch causes constitutive activation of MAPK in juvenile mice with Nf1 loss of heterozygosity (LOH); and (5) Nf1 LOH causes monocytosis in juvenile mice with Pten haploinsufficiency but does not cause lethality until adulthood. Our data suggest that 1 copy of Pten is sufficient to maintain an intact negative-feedback loop of the Akt pathway and HSC function in reconstitution, despite MAPK being constitutively activated in juvenile Pten+/ΔNf1LOH mice. However, 2 copies of Pten are required to maintain the integrity of the MAPK pathway in juvenile mice with Nf1 haploinsufficiency. Our data indicate that previous investigations of Pten function in wild-type mice may not reflect the impact of Pten loss in mice with Nf1 mutations or other genetic defects. We provide a proof of concept that disassociated age-specific hematopoiesis contributes to leukemogenesis and pediatric demise.