Thymic lymphoma detection in RORγ knockout mice using 5-hydroxymethylcytosine profiling of circulating cell-free DNA.

A high incidence of thymic lymphoma has been noted in mice deficient of retinoid-related orphan receptor γ2 (RORγ2), which is required for differentiation of naïve CD4+ T cells into TH17 cells. Using a RORγ homozygous knockout (KO) mouse model of thymic lymphoma, we characterized this tumor progression and investigated the utility of 5-hydroxymethylcytosine (5hmC) signatures as a non-invasive circulating biomarker for early prediction of malignancy. No evidence for malignancy was noted in the wild-type mice, while primary thymic lymphoma with multi-organ metastasis was observed microscopically in 97% of the homozygous RORγ KO mice. The severity of thymic lymphoma was not age-dependent in the KO mice of 2 to 4 months old. Differential enrichment of 5hmC in thymic DNA and plasma cell-free DNA (cfDNA) was compared across different stages of tumor progression. Random forest modeling of plasma cfDNA achieved good predictivity (AUC = 0.74) in distinguishing early non-metastatic thymic lymphoma compared to cancer-free controls, while perfect predictivity was achieved with advanced multi-organ metastatic disease (AUC = 1.00). Lymphoid-specific genes involved in thymocyte selection during T cell development (Themis, Tox) were differentially enriched in both plasma and thymic tissue. This could help in differentiating thymic lymphoma from other tumors commonly detected in rodent carcinogenicity studies used in pharmaceutical drug development to inform human malignancy risk. Overall, these results provide a proof-of-concept for using circulating cfDNA profiles in rodent carcinogenicity studies for early risk assessment of novel pharmaceutical targets.

A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.

BACKGROUND: Inflammatory bowel disease (IBD) is a gastrointestinal chronic disease with an unpredictable disease course. Computational methods such as machine learning (ML) have the potential to stratify IBD patients for the provision of individualized care. The use of ML methods for IBD was surveyed, with an additional focus on how the field has changed over time. METHODS: On May 6, 2021, a systematic review was conducted through a search of MEDLINE and Embase databases, with the search structure ("machine learning" OR "artificial intelligence") AND ("Crohn* Disease" OR "Ulcerative Colitis" OR "Inflammatory Bowel Disease"). Exclusion criteria included studies not written in English, no human patient data, publication before 2001, studies that were not peer reviewed, nonautoimmune disease comorbidity research, and record types that were not primary research. RESULTS: Seventy-eight (of 409) records met the inclusion criteria. Random forest methods were most prevalent, and there was an increase in neural networks, mainly applied to imaging data sets. The main applications of ML to clinical tasks were diagnosis (18 of 78), disease course (22 of 78), and disease severity (16 of 78). The median sample size was 263. Clinical and microbiome-related data sets were most popular. Five percent of studies used an external data set after training and testing for additional model validation. DISCUSSION: Availability of longitudinal and deep phenotyping data could lead to better modeling. Machine learning pipelines that consider imbalanced data and that feature selection only on training data will generate more generalizable models. Machine learning models are increasingly being applied to more complex clinical tasks for specific phenotypes, indicating progress towards personalized medicine for IBD.

The MicroRNA-based Liquid Biopsy Improves Early Assessment of Lethal Acetaminophen Poisoning: A Case Report.

BACKGROUND Acetaminophen overdose is the most common cause of acute liver failure. Nevertheless, new biomarker approaches enabling early prediction of the outcome of the acetaminophen overdose are needed. Recently, using next-generation sequencing analysis of serum from human study participants we uncovered injury-specific signatures of circulating microRNAs (miRNAs) that represented underlying molecular mechanisms of toxicity. This case study is first to show the application of miRNA profiling to assess prognosis of acetaminophen poisoning. CASE REPORT The patient was admitted to the hospital following supra therapeutic acetaminophen ingestion. The patient showed elevated levels of biomarkers of hepatocellular injury alanine aminotransferase, aspartate transaminase, and glutamate dehydrogenase. Even though treatment with N-acetyl cysteine was initiated 24 hours post-ingestion, levels of alanine-aminotransferase and aspartate transaminase peaked at about 40 hours post ingestion of acetaminophen. We analyzed global circulating miRNA levels from 24 consecutive serum samples from this study participant covering the period from admission to time of death. CONCLUSIONS The resulting global miRNA profiles were compared with profiles from study participants with non-lethal acetaminophen poisoning and healthy controls. At the admission, the miRNA profiles of both lethal and non-lethal acetaminophen poisoning showed induction of cellular stress and oxidative damage. Later, the miRNA profiles of the lethal poisoning featured fibrosis and coagulation pathways while profiles of non-lethal cases resembled those of healthy study participants. Although additional confirmatory studies are needed, our case study is first to indicate that global miRNA profiles to be used as liquid biopsies have potential to facilitate the assessment of acetaminophen poisoning.

Demodifying RNA for Transcriptomic Analyses of Archival Formalin-Fixed Paraffin-Embedded Samples.

Archival formalin-fixed paraffin-embedded (FFPE) tissue samples offer a vast but largely untapped resource for genomic research. The primary technical issues limiting use of FFPE samples are RNA yield and quality. In this study, we evaluated methods to demodify RNA highly fragmented and crosslinked by formalin fixation. Primary endpoints were RNA recovery, RNA-sequencing quality metrics, and transcriptional responses to a reference chemical (phenobarbital, PB). Frozen mouse liver samples from control and PB groups (n = 6/group) were divided and preserved for 3 months as follows: frozen (FR); 70% ethanol (OH); 10% buffered formalin for 18 h followed by ethanol (18F); or 10% buffered formalin (3F). Samples from OH, 18F, and 3F groups were processed to FFPE blocks and sectioned for RNA isolation. Additional sections from 3F received the following demodification protocols to mitigate RNA damage: short heated incubation with Tris-Acetate-EDTA buffer; overnight heated incubation with an organocatalyst using 2 different isolation kits; or overnight heated incubation without organocatalyst. Ribo-depleted, stranded, total RNA libraries were built and sequenced using the Illumina HiSeq 2500 platform. Overnight incubation (± organocatalyst) increased RNA yield >3-fold and RNA integrity numbers and fragment analysis values by > 1.5- and >3.0-fold, respectively, versus 3F. Postsequencing metrics also showed reduced bias in gene coverage and deletion rates for overnight incubation groups. All demodification groups had increased overlap for differentially expressed genes (77%-84%) and enriched pathways (91%-97%) with FR, with the highest overlap in the organocatalyst groups. These results demonstrate simple changes in RNA isolation methods that can enhance genomic analyses of FFPE samples.

Use of Rat Primary Mesenteric Cells for the Prediction of PDE4 Inhibitor Drug-Induced Vascular Injury.

Drug-induced vascular injury (DIVI) in preclinical studies can delay, if not terminate, a drug development program. Clinical detection of DIVI can be very difficult as there are no definitive biomarkers known to reliably detect this disorder in all instances. The preclinical identification of DIVI requires detailed microscopic examination of a wide range of tissues although one of the most commonly affected areas in rats is the mesenteric vasculature. The reason for this predisposition of mesenteric arteries in rats as well as the exact mechanism and cell types involved in the initial development of these lesions have not been fully elucidated. We hypothesized that by using a mixed culture of cells from rat mesenteric tissue, we would be able to identify an RNA expression signature that could predict the invivo development of DIVI. Five compounds designed to inhibit Phosphodiesterase 4 activity (PDE4i) were chosen as positive controls. PDE4i's are well known to induce DIVI in the mesenteric vasculature of rats and there is microscopic evidence that this is associated, at least in part, with a proinflammatory mechanism. We surveyed, by qRT-PCR, the expression of 96 genes known to be involved in inflammation and using a Random-Forest model, identified 12 genes predictive of invivo DIVI outcomes in rats. Using these genes, we were able to cross-validate the ability of the Random-Forest modeling to predict the concentration at which PDE4i caused DIVI invivo.

The genomic sequence of lymphocryptovirus from cynomolgus macaque.

Lymphocryptoviruses such as Epstein-Barr virus (EBV) cause persistent infections in human and non-human primates, and suppression of the immune system can increase the risk of lymphocryptovirus (LCV)-associated tumor development in both human and non-human primates. To enable LCV infection as a non-clinical model to study effects of therapeutics on EBV immunity, we determined the genomic DNA sequence of the LCV from cynomolgus macaque, a species commonly used for non-clinical testing. Comparison to rhesus macaque LCV and human EBV sequences indicates that LCV from the cynomolgus macaque has the same genomic arrangement and a high degree of similarity in most genes, especially with rhesus macaque LCV. Genes showing lower similarity were those encoding proteins involved in latency and/or tumor promotion or immune evasion. The genomic sequence of LCV from cynomolgus macaque should aid the development of non-clinical tools for identifying therapeutics that impact LCV immunity and carry potential lymphoma risk.

Identification of tubular injury microRNA biomarkers in urine: comparison of next-generation sequencing and qPCR-based profiling platforms.

BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNAs that regulate protein levels post-transcriptionally. miRNAs play important regulatory roles in many cellular processes and have been implicated in several diseases. Recent studies have reported significant levels of miRNAs in a variety of body fluids, raising the possibility that miRNAs could serve as useful biomarkers. Next-generation sequencing (NGS) is increasingly employed in biomedical investigations. Although concordance between this platform and qRT-PCR based assays has been reported in high quality specimens, information is lacking on comparisons in biofluids especially urine. Here we describe the changes in miRNA expression patterns in a rodent model of renal tubular injury (gentamicin). Our aim is to compare RNA sequencing and qPCR based miRNA profiling in urine specimen from control and rats with confirmed tubular injury. RESULTS: Our preliminary examination of the concordance between miRNA-seq and qRT-PCR in urine specimen suggests minimal agreement between platforms probably due to the differences in sensitivity. Our results suggest that although miRNA-seq has superior specificity, it may not detect low abundant miRNAs in urine samples. Specifically, miRNA-seq did not detect some sequences which were identified by qRT-PCR. On the other hand, the qRT-PCR analysis was not able to detect the miRNA isoforms, which made up the majority of miRNA changes detected by NGS. CONCLUSIONS: To our knowledge, this is the first time that miRNA profiling platforms including NGS have been compared in urine specimen. miRNAs identified by both platforms, let-7d, miR-203, and miR-320, may potentially serve as promising novel urinary biomarkers for drug induced renal tubular epithelial injury.

Transcriptomic analysis of genetically defined autism candidate genes reveals common mechanisms of action.

BACKGROUND: Austism spectrum disorder (ASD) is a heterogeneous behavioral disorder or condition characterized by severe impairment of social engagement and the presence of repetitive activities. The molecular etiology of ASD is still largely unknown despite a strong genetic component. Part of the difficulty in turning genetics into disease mechanisms and potentially new therapeutics is the sheer number and diversity of the genes that have been associated with ASD and ASD symptoms. The goal of this work is to use shRNA-generated models of genetic defects proposed as causative for ASD to identify the common pathways that might explain how they produce a core clinical disability. METHODS: Transcript levels of Mecp2, Mef2a, Mef2d, Fmr1, Nlgn1, Nlgn3, Pten, and Shank3 were knocked-down in mouse primary neuron cultures using shRNA constructs. Whole genome expression analysis was conducted for each of the knockdown cultures as well as a mock-transduced culture and a culture exposed to a lentivirus expressing an anti-luciferase shRNA. Gene set enrichment and a causal reasoning engine was employed to identify pathway level perturbations generated by the transcript knockdown. RESULTS: Quantification of the shRNA targets confirmed the successful knockdown at the transcript and protein levels of at least 75% for each of the genes. After subtracting out potential artifacts caused by viral infection, gene set enrichment and causal reasoning engine analysis showed that a significant number of gene expression changes mapped to pathways associated with neurogenesis, long-term potentiation, and synaptic activity. CONCLUSIONS: This work demonstrates that despite the complex genetic nature of ASD, there are common molecular mechanisms that connect many of the best established autism candidate genes. By identifying the key regulatory checkpoints in the interlinking transcriptional networks underlying autism, we are better able to discover the ideal points of intervention that provide the broadest efficacy across the diverse population of autism patients.

The role of hypoxia in 2-butoxyethanol-induced hemangiosarcoma.

To understand the molecular mechanisms underlying compound-induced hemangiosarcomas in mice, and therefore, their human relevance, a systems biology approach was undertaken using transcriptomics and Causal Network Modeling from mice treated with 2-butoxyethanol (2-BE). 2-BE is a hemolytic agent that induces hemangiosarcomas in mice. We hypothesized that the hemolysis induced by 2-BE would result in local tissue hypoxia, a well-documented trigger for endothelial cell proliferation leading to hemangiosarcoma. Gene expression data from bone marrow (BM), liver, and spleen of mice exposed to a single dose (4 h) or seven daily doses of 2-BE were used to develop a mechanistic model of hemangiosarcoma. The resulting mechanistic model confirms previous work proposing that 2-BE induces macrophage activation and inflammation in the liver. In addition, the model supports local tissue hypoxia in the liver and spleen, coupled with increased erythropoeitin signaling and erythropoiesis in the spleen and BM, and suppression of mechanisms that contribute to genomic stability, events that could be contributing factors to hemangiosarcoma formation. Finally, an immunohistochemistry method (Hypoxyprobe) demonstrated that tissue hypoxia was present in the spleen and BM. Together, the results of this study identify molecular mechanisms that initiate hemangiosarcoma, a key step in understanding safety concerns that can impact drug decision processes, and identified hypoxia as a possible contributing factor for 2-BE-induced hemangiosarcoma in mice.

Electronically subtracting expression patterns from a mixed cell population.

MOTIVATION: Biological samples frequently contain multiple cell-types that each can play a crucial role in the development and/or regulation of adjacent cells or tissues. The search for biomarkers, or expression patterns of, one cell-type in those samples can be a complex and time-consuming process. Ordinarily, extensive laboratory bench work must be performed to separate the mixed cell population into its subcomponents, such that each can be accurately characterized. RESULTS: We have developed a methodology to electronically subtract gene expression in one or more components of a mixed cell population from a mixture, to reveal the expression patterns of other minor or difficult to isolate components. Examination of simulated data indicates that this procedure can reliably determine the expression patterns in cell-types that contribute as little as 5% of the total expression in a mixed cell population. We re-analyzed microarray expression data from the viral infection of macrophages and from the T-cells of wild type and Foxp3 deletion mice. Using our subtraction methodology, we were able to substantially improve the identification of genes involved in processes of subcomponent portions of these samples.

The small ubiquitin-like modifier (SUMO) protein modification system in Arabidopsis. Accumulation of SUMO1 and -2 conjugates is increased by stress.

Small ubiquitin-like modifier (SUMO) is a member of the superfamily of ubiquitin-like polypeptides that become covalently attached to various intracellular target proteins as a way to alter their function, location, and/or half-life. Here we show that the SUMO conjugation system operates in plants through a characterization of the Arabidopsis SUMO pathway. An eight-gene family encoding the SUMO tag was discovered as were genes encoding the various enzymes required for SUMO processing, ligation, and release. A diverse array of conjugates could be detected, some of which appear to be SUMO isoform-specific. The levels of SUMO1 and -2 conjugates but not SUMO3 conjugates increased substantially following exposure of seedlings to stress conditions, including heat shock, H(2)O(2), ethanol, and the amino acid analog canavanine. The heat-induced accumulation could be detected within 2 min from the start of a temperature upshift, suggesting that SUMO1/2 conjugation is one of the early plant responses to heat stress. Overexpression of SUMO2 enhanced both the steady state levels of SUMO2 conjugates under normal growth conditions and the subsequent heat shock-induced accumulation. This accumulation was dampened in an Arabidopsis line engineered for increased thermotolerance by overexpressing the cytosolic isoform of the HSP70 chaperonin. Taken together, the SUMO conjugation system appears to be a complex and functionally heterogeneous pathway for protein modification in plants with initial data indicating that one important function may be in stress protection and/or repair.