Transcriptomic Markers Research Articles

Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning‐enabled molecular diagnostics

Limited therapy options due to antibiotic resistance underscore the need for optimization of current diagnostics. In some bacterial species, antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug‐resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and expression profiles, we generated predictive models and identified biomarkers of resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8–0.9) or very high (> 0.9) sensitivity and predictive values. For all drugs except for ciprofloxacin, gene expression information improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. The implementation of a molecular susceptibility test system in routine microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

The immunogenomic difference between Asian and non-Asian esophageal squamous cell carcinoma (ESCC) patients: An analysis of the Cancer Genome Atlas (TCGA) cohort.

27 Background: Recently reported global phase 3 trials of immune checkpoint inhibitor (ICI) versus second-line chemotherapy for esophageal cancer revealed that Asian population appear to obtain more benefit from ICI than non-Asian patients even in ESCC subgroups. Whether this observation could be explained by the immunogenomic difference between Asian and non-Asian ESCC remains uncertain. Methods: We retrieved the data of genetic alterations and gene expression profiling from ESCC patients of TCGA dataset, and compared the mutational profiles, immune subtypes, composition of immune cell infiltrates, and T cell-related signatures between Asian and Non-Asian patients with ESCC. Abundance of immune cell infiltrates were estimated by averaging expression values of the corresponding immune cells’ transcriptomic markers defined by Danaher et al. (J Immunother Cancer. 2017; 5:18.). The 6 immune subtypes were adopted from Thorsson et al (Immunity. 2018;48(4):812-830). The T-cell related signatures were determined by averaging the corresponding genes' expression values following previous reports. Results: We retrieved 93 patients with ESCC (Asian: non-Asian= 45: 48) from TCGA database. There is no statistical difference in overall survival between Asian and non-Asian ESCC patients. Higher mutation frequencies of TP53, NFE2L2, ZNF750, and lower mutation frequency of SMARCA4 were seen in Asian patients than in non-Asian patients. As for the immune contexture, we found that the composition of immune cell infiltrate, the distribution of immune subtypes, and a variety of T cell-related gene signatures including the 6-gene interferon-gamma signature, the 10-gene interferon-gamma signature defined by Merck or by Ribas et al, and the 13-gene inflammatory signature defined by Gajewski et al, were not significantly different between Asian and non-Asian groups. Conclusions: Our analysis failed to identify statistically significant difference in the immunogenomics of ESCC tumors between Asian and non-Asian patients in the TCGA cohort. Further immunogenomic studies focusing on patients from Asian countries with high ESCC prevalence are warranted.

Conflicting signal in transcriptomic markers leads to a poorly resolved backbone phylogeny of chalcidoid wasps

AbstractChalcidoidea (Hymenoptera) are a megadiverse superfamily of wasps with astounding variation in both morphology and biology. Most species are parasitoids and important natural enemies of insects in terrestrial ecosystems. In this study, we present a transcriptome‐based phylogeny of Chalcidoidea; we found that poorly resolved relationships could only be marginally improved by adding more genes (a total of 5591) and taxa (a total of 65), proof‐checking for errors of homology and contamination, and decreasing missing data. Concatenation analyses consistently place Mymaridae and Trichogrammatidae sister to remaining Chalcidoidea. However, our coalescent analyses provide a different hypothesis with a grouping of (Mymaridae (((Trichogrammatidae, Eulophidae), (Encyrtidae, Aphelinidae)), remaining Chalcidoidea)). This hypothesis complicates our hypothesis of egg parasitism as being the ancestral state in Chalcidoidea. At the deeper nodes, the results uncovered a wide spectrum of gene discordance in the transcriptomic markers and identified a strong signal of functional bias in genes supporting alternative phylogenies. These deeper nodes of the phylogeny are thus strongly influenced by biased support from different functional gene complexes. Shallower nodes showed similar gene discordance, but without strong functional bias. Understanding and identifying mechanisms that result in gene tree discordance may be beneficial and even essential for elucidating deeper relationships, especially for groups that have undergone extremely rapid radiation.

Effects of cryopreservation on stallion sperm protamine messenger RNAs.

Protamines substitute DNA-binding histones during late spermatogenesis in sperm nucleus. Stallion sperm contains all three variants of these arginine-rich and positively charged nuclear proteins (P1, P2 and P3). Two variants of protamine-2, that is P2 and P3, constitute approximately 15% of the entire protamine content. Also, the ratio of protamine-1 to protamine-2 varies among different mammalian species, and abnormal protamine ratios and protamine content are correlated with male infertility. In this study, changes in protamine mRNA abundance for all three protamines were investigated in stallion sperm during cryopreservation. Twelve ejaculates were collected from six sexually mature stallions. Sperm samples were divided into two parts for total mRNA extraction: one as fresh and the other as cryopreserved sample. Levels of three protamine transcripts were determined by real-time reverse transcriptase polymerase chain reaction. Results of relative expression showed that cryopreservation can significantly alter protamine transcripts: protamine 2 was downregulated, while protamine 3 was upregulated in cryopreserved samples relative to the control. Changes in protamine 1 were not significant after cryopreservation. This study is the first to evaluate changes in mRNA abundance of protamine genes in stallion sperm following cryopreservation. Such evaluations are important in finding transcriptomic markers for success in fertilization and assisted reproductivetechniques.

Maternal whole blood mRNA signatures identify women at risk of early preeclampsia: a longitudinal study

Purpose To determine whether previously established mRNA signatures are predictive of early preeclampsia when evaluated by maternal cellular transcriptome analysis in samples collected before clinical manifestation. Materials and methods We profiled gene expression at exon-level resolution in whole blood samples collected longitudinally from 49 women with normal pregnancy (controls) and 13 with early preeclampsia (delivery <34 weeks of gestation). After preprocessing and removal of gestational age-related trends in gene expression, data were converted into Z-scores based on the mean and standard deviation among controls for six gestational-age intervals. The average Z-scores of mRNAs in each previously established signature considered herein were compared between cases and controls at 9–11, 11–17, 17–22, 22–28, 28–32, and 32–34 weeks of gestation. Results: (1) Average expression of the 16-gene untargeted cellular mRNA signature was higher in women diagnosed with early preeclampsia at 32–34 weeks of gestation, yet more importantly, also prior to diagnosis at 28–32 weeks and 22–28 weeks of gestation, compared to controls (all, p < .05). (2) A combination of four genes from this signature, including a long non-protein coding RNA [H19 imprinted maternally expressed transcript (H19)], fibronectin 1 (FN1), tubulin beta-6 class V (TUBB6), and formyl peptide receptor 3 (FPR3) had a sensitivity of 0.85 (0.55–0.98) and a specificity of 0.92 (0.8–0.98) for prediction of early preeclampsia at 22–28 weeks of gestation. (3) H19, FN1, and TUBB6 were increased in women with early preeclampsia as early as 11–17 weeks of gestation (all, p < .05). (4) After diagnosis at 32–34 weeks, but also prior to diagnosis at 11–17 weeks, women destined to have early preeclampsia showed a coordinated increase in whole blood expression of several single-cell placental signatures, including the 20-gene signature of extravillous trophoblast (all, p < .05). (5) A combination of three mRNAs from the extravillous trophoblast signature (MMP11, SLC6A2, and IL18BP) predicted early preeclampsia at 11–17 weeks of gestation with a sensitivity of 0.83 (0.52–0.98) and specificity of 0.94 (0.79–0.99). Conclusions Circulating early transcriptomic markers for preeclampsia can be found either by untargeted profiling of the cellular transcriptome or by focusing on placental cell-specific mRNAs. The untargeted cellular mRNA signature was consistently increased in early preeclampsia after 22 weeks of gestation, and individual mRNAs of this signature were significantly increased as early as 11–17 weeks of gestation. Several single-cell placental signatures predicted future development of the disease at 11–17 weeks and were also increased in women already diagnosed at 32–34 weeks of gestation.

The genetic diversity and population structure of Sophora alopecuroides (Faboideae) as determined by microsatellite markers developed from transcriptome.

Sophora alopecuroides (Faboideae) is an endemic species, mainly distributed in northwest China. However, the limited molecular markers range for this species hinders breeding and genetic studies. A total of 20,324 simple sequence repeat (SSR) markers were identified from 118,197 assembled transcripts and 18 highly polymorphic SSR markers were used to explore the genetic diversity and population structure of S. alopecuroides from 23 different geographical populations. A relatively low genetic diversity was found in S. alopecuroides based on mean values of the number of effective alleles (Ne = 1.81), expected heterozygosity (He = 0.39) and observed heterozygosity (Ho = 0.55). The results of AMOVA indicated higher levels of variation within populations than between populations. Bayesian-based cluster analysis, principal coordinates analysis and Neighbor-Joining phylogeny analysis roughly divided all genotypes into four major groups with some admixtures. Meanwhile, geographic barriers would have restricted gene flow between the northern and southern regions (separated by Tianshan Mountains), wherein the two relatively ancestral and independent clusters of S. alopecuroides occur. History trade and migration along the Silk Road would together have promoted the spread of S. alopecuroides from the western to the eastern regions of the northwest plateau in China, resulting in the current genetic diversity and population structure. The transcriptomic SSR markers provide a valuable resource for understanding the genetic diversity and population structure of S. alopecuroides, and will assist effective conservation management.

Gene Expression and Genomic Markers Identify a Subpopulation of Poor Prognosis t(4;14) Patients in Newly Diagnosed Multiple Myeloma

Cytogenetics is an important prognostic marker in multiple myeloma (MM). Patients with t(4;14) (~15% of newly diagnosed MM patients) are known to have short progression free survival (PFS) and overall survival (OS). This feature, measured by FISH, is used in combination with ISS=3 as a selection marker for patients with high risk (HR) of progression. Only a subset of patients grouped by t(4;14) and ISS=3 display genuinely poor survival, however, with ~25% dying within 24 months after diagnosis (similar to the Double Hit subgroup defined by Walker et al1). To elucidate this observation, we created the largest dataset of MM t(4;14) patients to date by combining data from the Myeloma Genome Project (MGP, n=73) and data from TOUL (n=100, patients analyzed in routine practice) to identify transcriptomic and/or genomic markers associated with HR t(4;14). Gene expression (GE), copy number aberration (CNA), single nucleotide variant (SNV) and translocations were derived from RNAseq and WGS/WES profiling of biopsies from patients aged less than 75 years who received transplant, and integrated with clinical information (including Age, PFS and OS). Demographics: MGP median age=61; 30% female; median PFS (mPFS)=26.2months (m) and median OS (mOS) not reached. TOUL median age=60; 35% female, mPFS=23.7m and mOS = 86.1m. Our previous work (Ortiz ASH 2018, Ortiz EHA 2018) identified a molecularly-defined HR MM patient subgroup (MDMS8, mPFS&amp;lt;20m, m0S&amp;lt;35m) defined by GE patterns related to cell cycle dysregulation. In that analysis, 24% of t(4;14) patients were identified as MDMS8 (mPFS&amp;lt;13m, mOS&amp;lt;30m), the rest (76%) were grouped in other lower risk molecular segments (mPFS&amp;lt;30m, mOS NR). A GE classifier for t(4;14) in MDMS8 vs the rest of t(4;14) patients was created on the MGP dataset and applied to identify similar patients in the TOUL data, obtaining a significant difference between MDMS8-like t(4;14) patients (20% prevalence, mPFS&amp;lt;15m, mOS&amp;lt;26m) in the TOUL dataset and non-HR t(4;14) (mPFS&amp;lt;26m, mOS&amp;lt;103m) in both PFS (p.value&amp;lt;1e-3) and OS (p.value&amp;lt;1e-5). Although there are some conventional t(4;14) gene expression surrogates, they do not identify the HR t(4:14) subgroup. Comparison of known t(4;14) gene expression markers MMSET and FGFR3 in HR t(4;14) (OS &amp;lt; 24ms &amp; not_alive, N=34) versus non-HR t(4;14) patients (N=94) across both datasets combined did not yield significant differential expression of either gene (p.value&amp;gt;0.10). MMSET was over-expressed in all t(4;14) patients, while FGFR3 displayed a binomial distribution (two groups of patients with high (N=37, median value=10 log2CPM) and low (N=91, median value=2 log2CPM) FGFR3 expression) within t(4;14) patients (p.value&amp;lt;0.05) without association with outcome (p.value&amp;gt;0.10). GE analysis of HR t(4;14) vs non-HR t(4;14) patients aligned with MDMS8 biology, but identified new pathways also including DNA repair, MYC targets and Oxidative Phosphorylation being up-regulated in the HR t(4;14) group. A gene-set variation analysis based on the MSigDb C1 gene-set, wherein genes are grouped based on their genomic location, was performed to identify GE changes of potentially epigenomic origin. Results highlighted chr9q22, chr9q33, and chr13q13 as down-regulated in the HR t(4;14) group, while genes in 16q24 were significantly up-regulated. CNA analysis identified amplifications in chromosomes 3 and 19 and deletions in chr12p as significantly associated with the HR t(4;14) population (p.value &amp;lt; 0.05); while deletions in chr14q (preceding the translocated region) occurred more frequently in the non-HR t(4;14) group. Our results provide new insights into identification of these patients and underlying biology that could drive poor prognosis in t(4;14) patients. Molecular identification of HR t(4;14) patients would enable proper risk classification for this MM patient group and understanding differences in HR t(4;14) biology could provide the basis for identification of a specific therapeutic target for this HR subpopulation. An ongoing aim of this work is development of a clinically applicable classifier that accurately identifies this subpopulation of MM patients and the biological drivers of their high-risk disease. Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Towfic:Celgene Corporation: Employment, Equity Ownership. Flynt:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Sampath:Celgene Corporation: Employment, Equity Ownership. Rozelle:Celgene Corporation: Other: Contractor for Celgene. Trotter:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene: Employment, Equity Ownership.

Antibiotic treatment of Chlamydia-induced cystitis in the koala is linked to expression of key inflammatory genes in reactive oxygen pathways.

Chlamydial-induced cystitis in the koala (Phascolarctos cinereus) is currently treated by antibiotics. However, while reducing the chlamydial load, this treatment can also lead to gastrointestinal complications and death. Development of alternative treatments, such as a therapeutic chlamydial vaccine, are hindered by the lack of detailed understanding of the innate immune response to chlamydial clearance and disease regression during antibiotic treatment. Through clinical, microbiological and transcriptomic approaches, disease regression, bacterial clearance and innate immune responses were mapped in koalas with signs of chlamydial-induced cystitis while receiving anti-chlamydial antibiotics. Significant reduction in the signs of cystitis were observed during and post antibiotic treatment. This was observed as a thinning of the bladder wall and complete reversal of urinary incontinence. Transcriptomic analysis before treatment, at the end of treatment and prior to release identified significant down-regulation of specific genes involved in 21 biological pathways. Of these, the chemokine receptor signalling and NOD-like receptor signalling pathways where identified as important markers of inflammation. Specific genes within these pathways (NCF1 and NOX2) were significantly down-regulated, suggesting a decrease in reactive oxygen species production. Through the monitoring of specific clinical and transcriptomic markers, these findings allow detailed profiling of the clinical response to therapeutic vaccination in koalas with current signs of disease. This also adds to our understanding of innate immune responses to chlamydial infections and indicates that chlamydial-induced cystitis in the koala is linked to the regulation of reactive oxygen pathways.

The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

Tumors of different molecular subtypes can show strongly deviating responses to drug treatment, making stratification of patients based on molecular markers an important part of cancer therapy. Pharmacogenomic studies have led to the discovery of selected genomic markers (e.g., BRAFV600E), whereas transcriptomic and proteomic markers so far have been largely absent in clinical use, thus constituting a potentially valuable resource for further substratification of patients. To systematically assess the explanatory power of different -omics data types, we assembled a panel of 49 melanoma cell lines, including genomic, transcriptomic, proteomic, and pharmacological data, showing that drug sensitivity models trained on transcriptomic or proteomic data outperform genomic-based models for most drugs. These results were confirmed in eight additional tumor types using published datasets. Furthermore, we show that drug sensitivity models can be transferred between tumor types, although after correcting for training sample size, transferred models perform worse than within-tumor-type predictions. Our results suggest that transcriptomic/proteomic signals may be alternative biomarker candidates for the stratification of patients without known genomic markers.

A transcriptomic model to predict increase in fibrous cap thickness in response to high-dose statin treatment: Validation by serial intracoronary OCT imaging

BackgroundFibrous cap thickness (FCT), best measured by intravascular optical coherence tomography (OCT), is the most important determinant of plaque rupture in the coronary arteries. Statin treatment increases FCT and thus reduces the likelihood of acute coronary events. However, substantial statin-related FCT increase occurs in only a subset of patients. Currently, there are no methods to predict which patients will benefit. We use transcriptomic data from a clinical trial of rosuvastatin to predict if a patient's FCT will increase in response to statin therapy. MethodsFCT was measured using OCT in 69 patients at (1) baseline and (2) after 8–10 weeks of 40 mg rosuvastatin. Peripheral blood mononuclear cells were assayed via microarray. We constructed machine learning models with baseline gene expression data to predict change in FCT. Finally, we ascertained the biological functions of the most predictive transcriptomic markers. FindingsMachine learning models were able to predict FCT responders using baseline gene expression with high fidelity (Classification AUC = 0.969 and 0.972). The first model (elastic net) using 73 genes had an accuracy of 92.8%, sensitivity of 94.1%, and specificity of 91.4%. The second model (KTSP) using 18 genes has an accuracy of 95.7%, sensitivity of 94.3%, and specificity of 97.1%. We found 58 enriched gene ontology terms, including many involved with immune cell function and cholesterol biometabolism. InterpretationIn this pilot study, transcriptomic models could predict if FCT increased following 8–10 weeks of rosuvastatin. These findings may have significance for therapy selection and could supplement invasive imaging modalities.

Evaluation of endocrine and transcriptomic markers of male maturation in winter-run Steelhead Trout (Oncorhynchus mykiss)

Steelhead Trout (Oncorhynchus mykiss) display a varied life-history, including precocious male maturation at age-1 or age-2. In wild fish, precocious male maturation represents an important component of a diverse life-history portfolio. In hatchery programs, however, it is undesirable if rearing practices increase rates of early male maturation and reduce numbers of anadromous male adults. Our study aimed to develop endocrine and molecular markers for identifying males at early stages of maturation in the spring (prior to smolt release) and evaluated the potential use of these markers for quantifying early male maturation rates at a hatchery scale. In a laboratory study, Skookumchuck winter-run Steelhead Trout were reared at a high growth rate in order to increase the occurrence of precocious male maturation. Fish were lethally sub-sampled in February, prior to the time of smolt release; in May, at the time of smolt release; and in September, when 1+ age maturing males that would spawn the following spring were clearly identifiable based solely on gonadosomatic index (GSI). In February and May samples, we measured GSI, plasma 11-ketotestosterone (11KT), mRNAs for pituitary follicle stimulating hormone (fshb) and luteinizing hormone (lhb) beta subunits, and analyzed stage of spermatogenesis by testis histology. Additionally, in May, we measured testis anti-Müllerian hormone (amh) and insulin-like growth factor 3 (igf3) mRNA. Our primary goal was to evaluate the aforementioned maturation indices for their efficacy in forecasting the proportion of fish initiating early male maturation in the spring (approximately 1 year prior to spermiation), compared to the proportion that actually matured. Combining measures of GSI, plasma 11KT, and pituitary fshb and lhb mRNA expression provided a useful, but conservative, estimate of the proportion of males initiating maturation in the spring (21%) compared to the proportion that were ultimately destined to mature (37%) the following spring. These results suggest that maturation may be less synchronous than previously appreciated and some males may have initiated maturation after our census in May.

Substantial fat mass loss reduces low-grade inflammation and induces positive alteration in cardiometabolic factors in normal-weight individuals

The accumulation of fat, especially in visceral sites, is a significant risk factor for several chronic diseases with altered cardiometabolic homeostasis. We studied how intensive long-term weight loss and subsequent weight regain affect physiological changes, by longitudinally interrogating the lipid metabolism and white blood cell transcriptomic markers in healthy, normal-weight individuals. The current study examined 42 healthy, young (age: 27.5 ± 4.0 years), normal-weight (body mass index, BMI: 23.4 ± 1.7 kg/m2) female athletes, of which 25 belong to the weight loss and regain group (diet group), and 17 to the control group. Participants were evaluated, and fasting blood samples were drawn at three time points: at baseline (PRE); at the end of the weight loss period (MID: 21.1 ± 3.1 weeks after PRE); and at the end of the weight regain period (POST: 18.4 ± 2.9 weeks after MID). Following the weight loss period, the diet group experienced a ~73% reduction (~0.69 kg) in visceral fat mass (false discovery rate, FDR < 2.0 × 10−16), accompanied by anti-atherogenic effects on transcriptomic markers, decreased low-grade inflammation (e.g., as α1–acid glycoprotein (FDR = 3.08 × 10−13) and hs-CRP (FDR = 2.44 × 10−3)), and an increase in functionally important anti-atherogenic high-density lipoprotein -associated metabolites (FDR < 0.05). This occurred even though these values were already at favorable levels in these participants, who follow a fitness-lifestyle compared to age- and BMI-matched females from the general population (n = 58). Following the weight regain period, most of the observed beneficial changes in visceral fat mass, and metabolomic and transcriptomic profiles dissipated. Overall, the beneficial anti-atherogenic effects of weight loss can be observed even in previously healthy, normal-weight individuals.

Targeted expression profiling by RNA-Seq improves detection of cellular dynamics during pregnancy and identifies a role for T cells in term parturition

Development of maternal blood transcriptomic markers to monitor placental function and risk of obstetrical complications throughout pregnancy requires accurate quantification of gene expression. Herein, we benchmark three state-of-the-art expression profiling techniques to assess in maternal circulation the expression of cell type-specific gene sets previously discovered by single-cell genomics studies of the placenta. We compared Affymetrix Human Transcriptome Arrays, Illumina RNA-Seq, and sequencing-based targeted expression profiling (DriverMapTM) to assess transcriptomic changes with gestational age and labor status at term, and tested 86 candidate genes by qRT-PCR. DriverMap identified twice as many significant genes (q < 0.1) than RNA-Seq and five times more than microarrays. The gap in the number of significant genes remained when testing only protein-coding genes detected by all platforms. qRT-PCR validation statistics (PPV and AUC) were high and similar among platforms, yet dynamic ranges were higher for sequencing based platforms than microarrays. DriverMap provided the strongest evidence for the association of B-cell and T-cell gene signatures with gestational age, while the T-cell expression was increased with spontaneous labor at term according to all three platforms. We concluded that sequencing-based techniques are more suitable to quantify whole-blood gene expression compared to microarrays, as they have an expanded dynamic range and identify more true positives. Targeted expression profiling achieved higher coverage of protein-coding genes with fewer total sequenced reads, and it is especially suited to track cell type-specific signatures discovered in the placenta. The T-cell gene expression signature was increased in women who underwent spontaneous labor at term, mimicking immunological processes at the maternal-fetal interface and placenta.

Transcriptome-wide mining, characterization, and development of microsatellite markers in Lychnis kiusiana (Caryophyllaceae)

BackgroundLychnis kiusiana Makino is an endangered perennial herb native to wetland areas in Korea and Japan. Despite its conservational and evolutionary significance, population genetic resources are lacking for this species. Next-generation sequencing has been accepted as a rapid and cost-effective solution for the identification of microsatellite markers in nonmodel plants.ResultsUsing Illumina HiSeq 2000 sequencing technology, we assembled 67,498,600 reads into 91,900 contigs and identified 11,403 microsatellite repeat motifs in 9563 contigs. A total of 4510 microsatellite-containing transcripts had Gene Ontology (GO) annotations, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 124 pathways with significant scores. Many microsatellites in the L. kiusiana leaf transcriptome were linked to genes involved in the plant response to light intensity, salt stress, temperature stimulus, and nutrient and water deprivation. A total of 12,486 single-nucleotide polymorphisms (SNPs) were identified on transcripts harboring microsatellites. The analysis of nucleotide substitution rates for 2389 unigenes indicated that 39 genes were under strong positive selection. The primers of 6911 microsatellites were designed, and 40 of 50 selected primer pairs were consistently and successfully amplified from 51 individuals. Twenty-five of these were polymorphic, and the average number of alleles per SSR locus was 6.96, with a range from 2 to 15. The observed and expected heterozygosities ranged from 0.137 to 0.902 and 0.131 to 0.827, respectively, and locus-specific FIS estimates ranged from − 0.116 to 0.290. Eleven of the 25 primer pairs were successfully amplified in three additional species of Lychnis: 56% in L. wilfordii, 64% in L. cognata and 80% in L. fulgens.ConclusionsThe transcriptomic SSR markers of Lychnis kiusiana provide a valuable resource for understanding the population genetics, evolutionary history, and effective conservation management of this species. Furthermore, the identified microsatellite loci linked to the annotated genes should be useful for developing functional markers of L. kiusiana. The developed markers represent a potentially valuable source of transcriptomic SSR markers for population genetic analyses with moderate levels of cross-taxon portability.

Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome.

We analyzed the blood transcriptome of sepsis framed within community-acquired pneumonia (CAP) and characterized its molecular and cellular heterogeneity in terms of functional modules of co-regulated genes with impact for the underlying pathophysiological mechanisms. Our results showed that CAP severity is associated with immune suppression owing to T-cell exhaustion and HLA and chemokine receptor deactivation, endotoxin tolerance, macrophage polarization, and metabolic conversion from oxidative phosphorylation to glycolysis. We also found footprints of host’s response to viruses and bacteria, altered levels of mRNA from erythrocytes and platelets indicating coagulopathy that parallel severity of sepsis and survival. Finally, our data demonstrated chromatin re-modeling associated with extensive transcriptional deregulation of chromatin modifying enzymes, which suggests the extensive changes of DNA methylation with potential impact for marker selection and functional characterization. Based on the molecular footprints identified, we propose a novel stratification of CAP cases into six groups differing in the transcriptomic scores of CAP severity, interferon response, and erythrocyte mRNA expression with impact for prognosis. Our analysis increases the resolution of transcriptomic footprints of CAP and reveals opportunities for selecting sets of transcriptomic markers with impact for translation of omics research in terms of patient stratification schemes and sets of signature genes.

In Search for Reliable Markers of Glioma-Induced Polarization of Microglia.

Immune cells accumulating in the microenvironment of malignant tumors are tumor educated and contribute to its growth, progression, and evasion of antitumor immune responses. Glioblastoma (GBM), the common and most malignant primary brain tumor in adults, shows considerable accumulation of resident microglia and peripheral macrophages, and their polarization into tumor-supporting cells. There are controversies regarding a functional phenotype of glioma-associated microglia/macrophages (GAMs) due to a lack of consistent markers. Previous categorization of GAM polarization toward the M2 phenotype has been found inaccurate because of oversimplification of highly complex and heterogeneous responses. In this study, we characterized functional responses and gene expression in mouse and human microglial cultures exposed to fresh conditioned media [glioma-conditioned medium (GCM)] from human U87 and LN18 glioma cells. Functional analyses revealed mutual communication reflected by strong stimulation of glioma invasion by microglial cells and increased microglial phagocytosis after GCM treatment. To define transcriptomic markers of GCM-activated microglia, we performed selected and global gene expression analyses of stimulated microglial cells. We found activated pathways associated with immune evasion and TGF signaling. We performed computational comparison of the expression patterns of GAMs from human GBMs and rodent experimental gliomas to select genes consistently changed in different datasets. The analyses of marker genes in GAMs from different experimental models and clinical samples revealed only a small set of common genes, which reflects variegated responses in clinical and experimental settings. Tgm2 and Gpnmb were the only two genes common in the analyzed data sets. We discuss potential sources of the observed differences and stress a great need for definitive elucidation of a functional state of GAMs.

Mononuclear cell transcriptome changes associated with dimethyl fumarate in MS.

ObjectiveTo identify short-term changes in gene expression in peripheral blood mononuclear cells (PBMCs) associated with treatment response to dimethyl fumarate (DMF, Tecfidera) in patients with relapsing-remitting MS (RRMS).MethodsBlood samples were collected from 24 patients with RRMS (median Expanded Disability Status Scale score, 2.0; range 1–7) at baseline, 6 weeks, and 15 months after the initiation of treatment with DMF (BG-12; Tecfidera). Seven healthy controls were also recruited, and blood samples were collected over the same time intervals. PBMCs were extracted from blood samples and sequenced using next-generation RNA sequencing. Treatment responders were defined using the composite outcome measure “no evidence of disease activity” (NEDA-4). Time-course and cross-sectional differential expression analyses were performed to identify transcriptomic markers of treatment response.ResultsTreatment responders (NEDA-4 positive, 8/24) over the 15-month period had 478 differentially expressed genes (DEGs) 6 weeks after the start of treatment. These were enriched for nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and inhibition of nuclear factor κB (NFκB) pathway transcripts. For patients who showed signs of disease activity, there were no DEGs at 6 weeks relative to their (untreated) baseline. Contrasting transcriptomes expressed at 6 weeks with those at 15 months of treatment, 0 and 1,264 DEGs were found in the responder and nonresponder groups, respectively. Transcripts in the nonresponder group (NEDA-4 negative, 18/24) were enriched for T-cell signaling genes.ConclusionShort-term PBMC transcriptome changes reflecting activation of the Nrf2 and inhibition of NFκB pathways distinguish patients who subsequently show a medium-term treatment response with DMF. Relative stabilization of gene expression patterns may accompany treatment-associated suppression of disease activity.

The effects of graded caloric restriction: XII. Comparison of mouse to human impact on cellular senescence in the colon.

SummaryCalorie restriction (CR) is an effective strategy to delay the onset and progression of aging phenotypes in a variety of organisms. Several molecular players are involved in the anti‐aging effects of CR, but mechanisms of regulation are poorly understood. Cellular senescence—a cellular state of irreversible growth arrest—is considered a basic mechanism of aging. Senescent cells accumulate with age and promote a number of age‐related pathologies. Whether environmental conditions such as diet affect the accumulation of cellular senescence with age is still unclear. Here, we show that a number of classical transcriptomic markers of senescent cells are reduced in adult but relatively young mice under CR. Moreover, we demonstrate that such senescence markers are not induced in the colon of middle‐age human volunteers under CR in comparison with age‐matched volunteers consuming normal Western diets. Our data support the idea that the improvement in health span observed in different organisms under CR might be partly due to a reduction in the number of senescent cells.

Abstract P1-07-20: Developing prognostic indicators of poor outcomes in PRAEGNANT metastatic breast cancer cohort

Abstract Background: Despite novel, targeted therapies, metastatic breast cancer patients have an extremely unfavourable prognosis. Prognostic and predictive factors for patients with advanced breast cancer are not well understood. Molecular assessment of the patient and the tumor in the metastatic situation is not routinely performed despite advances in molecular precision medicine indicating great benefit to this patient group. Here we present early findings from the first 142 patients of a prospective molecular breast cancer registry with completed transcriptomic profiling. Methods: The PRAEGNANT study proctocol (NCT02338767) is a molecular registry designed to provide an infrastructure for the real-time comprehensive analysis of tumor and patient molecular characteristics under study conditions. Formalin fixed paraffin embedded tumors have been used from this registry to identify molecular, transcriptomic predictors for overall survival (OS). Known clinical correlates for OS (e.g. hormone-receptor status, age at diagnosis, and BMI) were analyzed by Cox proportional hazard ratios, and compared to transcriptomic markers of outcomes. Transcriptomes for all patient tumors were sequenced on the Illumina sequencing platform, and analyzed by RSEM to estimate transcripts per million (TPM) values for each gene isoform. Log-TPM values were used in established (PAM50) and novel (hierarchical clustering) expression-based subtyping of tumor samples. Expression-based subtypes were demonstrated to be strong prognostic indicators by Cox analysis. A Lasso regression machine learning algorithm was used to develop an expression-based predictive model of OS. Results: Hormone receptor positivity (HR=0.7, p&amp;lt;0.006) and TNBC status (HR=1.4, p&amp;lt;0.01) were significantly associated with outcomes. PAM50 subtypes were also strong indicators of outcomes (e.g. Basal disease compared to Luminal-A subtype has HR=1.4, p&amp;lt;0.017). A novel expression-based high-risk cluster in this cohort was more indicative of poor prognosis than clinical variates or Basal-type, with a HR=2.7 (p&amp;lt;0.009) when compared to Luminal-A subtype. An expression-based survival prediction model achieved a concordance-index of 0.65 in an unseen validation cohort. Patients predicted as having the shortest survival times were in the high-risk cluster. Conclusions: Here we demonstrate using molecular profiling to develop prognostic signatures that out-perform standard clinical correlates of poor outcomes, even in a small subset of the total cohort. As the PRAEGNANT cohort expands these prognostic tools will continue to improve and supplement physician knowledge to improve patient outcomes. Citation Format: Szeto C, Benz S, Nguyen A, Rübner M, Wallwiener D, Tesch H, Hadji P, Fehm TN, Janni W, Overkamp F, Lueftner D, Lux MP, Wallwiener M, Beckmann MW, Huebner H, Ettl J, Hartkopf AD, Mueller V, Taran FA, Belleville E, Schneeweiss A, Soon-Shiong P, Rabizadeh S, Fasching PA. Developing prognostic indicators of poor outcomes in PRAEGNANT metastatic breast cancer cohort [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-07-20.

Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case\u2013control validation study

BackgroundSepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset.MethodsUsing the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis to identify co-expression modules significantly associated with pediatric sepsis. Functional interpretation (gene ontology and pathway analysis) and enrichment analysis with known transcription factors and microRNAs of the identified candidate modules were then performed. In modules significantly associated with sepsis, the intramodular analysis was further performed and “hub genes” were identified and validated by quantitative real-time PCR (qPCR) in this study.Results15 co-expression modules in total were detected, and four modules (“midnight blue”, “cyan”, “brown”, and “tan”) were most significantly associated with pediatric sepsis and suggested as potential sepsis-associated modules. Gene ontology analysis and pathway analysis revealed that these four modules strongly associated with immune response. Three of the four sepsis-associated modules were also enriched with known transcription factors (false discovery rate-adjusted P < 0.05). Hub genes were identified in each of the four modules. Four of the identified hub genes (MYB proto-oncogene like 1, killer cell lectin like receptor G1, stomatin, and membrane spanning 4-domains A4A) were further validated to be differentially expressed between septic children and controls by qPCR.ConclusionsFour pediatric sepsis-associated co-expression modules were identified in this study. qPCR results suggest that hub genes in these modules are potential transcriptomic markers for pediatric sepsis diagnosis. These results provide novel insights into the pathogenesis of pediatric sepsis and promote the generation of diagnostic gene sets.