RNA Sequencing Of Samples Research Articles

Abstract 269: Small non-coding RNA profiling in stool and plasma samples to explore potential biomarkers for colorectal cancer diagnosis

Abstract Colorectal cancer (CRC) is one of the most frequent cancers worldwide. The available screening tests have reduced the incidence and mortality for this cancer; however, the research of new potential molecular biomarkers to use concomitantly could improve advanced adenomas/CRC early detection. Small non-coding RNAs (sncRNAs) are stable, easy detectable molecules that have been found dysregulated in several diseases including CRC. Besides the most studied microRNAs (miRNAs), sncRNAs include also P-element-induced wimpy testis (PIWI)-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), small nuclear RNAs (snRNAs), transfer RNAs (tRNAs) and other miscellaneous RNAs, all with key roles in post-transcriptional regulation. The aim of the present study was to identify by next-generation sequencing (NGS) signatures of sncRNAs other than miRNAs, in fecal and plasma extracellular vesicles (EVs) samples potentially able to detect patients with adenomas or CRC. We initially performed a small RNA-sequencing in samples from 221 subjects collected at colonoscopy. The group included: i) 80 healthy subjects with negative colonoscopy results; (ii) 43 adenoma patients; (iii) 41 individuals with inflammatory bowel disease and (iv) 57 newly diagnosed CRC patients. A computational pipeline for the identification of sncRNAs after miRNA mapping reads was previously implemented by our group. In stool samples, comparing the categories of interest mentioned above, we identified 395 differentially expressed sncRNAs (DEsncRNAs), mainly piRNAs (46.3%) and tRNAs (43.6%) (likelihood ratio test adjusting for sex and age, FDR adjusted p ≤ 0.05). Similarly, a group of 32 DEsncRNAs was detected in plasma EVs with piRNAs (41%) and tRNAs (44%) resulting among the most altered. Small RNA-sequencing has also been performed in a subset of 24 paired colorectal tumor and adjacent non-malignant tissues from the CRC patients for whom stool and plasma samples were analysed. Fifty-seven DEsncRNAs were found in tumor vs. non-malignant adjacent tissue with a similar distribution of dysregulated sncRNA biotypes. Some DEsncRNAs were shared between stool and tissues (n=35), plasma EVs and tissues (n=11) and, interestingly, among the profiles of the three different biospecimens (n=10). To validate our findings, we also sequenced stool samples from an independent cohort from the Czech Republic (at present 22 healthy subjects, 19 with inflammations, 21 with adenomas and 34 CRC patients). A total of 100 DEsncRNAs were detected in this validation cohort, among which 43 overlapped with those detected in the Italian cohort. In conclusions, we show that besides the most widely performed miRNA profiling, also the detection of sncRNAs in surrogate tissues by NGS may help to identify reliable and comparable results with those of primary tissues. To further investigate these molecules may provide new accurate markers for CRC diagnostic purposes. Citation Format: Antonio Francavilla, Sonia Tarallo, Giulio Ferrero, Francesca Cordero, Gaetano Gallo, Veronika Vymetalkova, Ludmila Vodickova, Pavel Vodicka, Barbara Pardini, Alessio Naccarati. Small non-coding RNA profiling in stool and plasma samples to explore potential biomarkers for colorectal cancer diagnosis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 269.

Abstract 5490: Scales and dynamics of intratumor heterogeneity

Abstract Current dogma stipulates that more heterogenous tumor cell populations results from compounding genetic and epigenetic changes and instability, ultimately driving unfavorable outcomes for these patients. Nonetheless, some cancers, including many pediatric cancers and some leukemias, have limited genomic diversity. As a result, we have a limited number of biomarkers available to stratify patients into high versus low-risk groups by their mutational cellular diversity or heterogeneity. For these cases, we have developed a method to quantify intratumor heterogeneity, for example at the transcriptomic level, using a generalized diversity index (GDI) from ecology. This index allows control of a scaling parameter called the order of diversity, q, to tailor the scale or resolution of the cellular diversity to a given context. However, the question remains, what role does the order of diversity play in the context of relative tumor age or disease stage? We show that the order of diversity parameter allows to either emphasize clonal richness (at low values of q), while high values shift the analysis toward the abundance of potential drivers of the tumor evolution. To gain deeper quantitative insight, we use evolutionary dynamics approaches that model the dynamics of heterogeneous cell populations over time, to understand how a patient's tumor diversity could emerge, persist, and change over time. Applying the replicator-mutator dynamics framework, we explore the effects and magnitude of frequency-dependent (positive or negative) selection on GDI. These analyses suggest that GDI often peaks at intermediate time points and, when run over a sufficiently long timescale, they reduce as the tumor population presumable becomes clonally dominant or otherwise stable before a major transition (e.g. metastasis). We explore GDI changes over time further in vitro in sequential single-cell RNA sequencing samples of fused breast cancer cells, where at earlier passages after fusion, the GDI peaks, and at later passages after fusion the GDI returns to levels similar to that of the parental breast cancer cell lines. Overall, GDI, as a means to quantify intratumor heterogeneity at select time points, can be a powerful tool to stratify high-risk patients. Our analyses show how computational analyses and mathematical modeling tools can be coupled with clinical and experimental data to understand eco-evolutionary dynamics of a patient's tumor. Citation Format: Meghan C. Ferrall-Fairbanks, Gregory J. Kimmel, Philipp M. Altrock. Scales and dynamics of intratumor heterogeneity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5490.

Abstract A17: Gene expression changes associated with metastasis in mice with bladder cancer

Abstract Background: Prognosis for bladder cancer is dependent on both tumor stage and grade. In patients with non-muscle invasive bladder cancer, the tumor invariably recurs and may progress. Patients who subsequently develop metastatic disease or present with it have a worse prognosis. The purpose of this study was to detect and find differences in patterns of gene expression between the primary tumor and common metastatic sites in a mouse model of bladder cancer to identify possible triggering events that result in metastasis. Methods: Five- to six-week-old female C57BL/6 mice were orthotopically implanted with MB49-PSA (murine bladder cancer cells secreting human prostate-specific antigen as a tumor marker). The institutional animal care and use committee approved the use of mice. At termination (up to 78 days after tumor implantation), bladders, kidneys, lymph nodes, and lungs were snap frozen and RNA was extracted by homogenizing the tissue in Trizol. Tumor presence in the tissues was confirmed by PSA gene expression, which was quantified by real-time PCR. Gene expression level profiling of the transcriptome was analyzed via RNA sequencing of samples from 4 bladders, 4 kidneys, 3 lymph nodes, and 2 lungs. Gene expression of a select group of genes was verified by real-time PCR with a bigger population of RNA samples. Results: Common differentially expressed genes were found between bladder and kidney (42 genes), bladder and lung (54 genes), and bladder and lymph nodes (198 genes). Bioinformatics software Panther and String were used to assign the genes into 6 pathways. These were morphogenesis of a branching epithelium; positive regulation of transcription from RNA polymerase II promoter; cell differentiation; negative regulation of epithelial to mesenchymal transition; epithelial cell differentiation; and transcriptional mis-regulation in cancer. Expression of paired-box 8 (Pax8), a transcription factor involved in embryonic development, was significantly higher in the kidneys compared to the other tissues. This suggests that overexpression of Pax8 may facilitate malignant development but may not be required for later stages of cell differentiation. Nanog, also a transcription regulator, was significantly higher in the kidneys when compared to bladders and was elevated in the lungs as well. It promotes epithelial-mesenchymal transition, resulting in metastasis; thus, increased expression of Nanog in cancer cells may indicate tumor aggressiveness. In the literature, Pax8 is expressed in noninvasive bladder tumors but not in normal bladder tissue in humans and Nanog expression is high in bladder tumors. Conclusion: Pax8 and Nanog expression indicates that the murine model of bladder cancer with metastatic disease is similar to that observed in patients. Thus, this model could be used to evaluate methods of blocking progression. Citation Format: Sin Mun Tham, Stefanie Alicia Fung, Kesavan Esuvaranathan, Ratha Mahendran. Gene expression changes associated with metastasis in mice with bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr A17.

Tackling the Molecular Drug Sensitivity in the Sea Louse Caligus rogercresseyi Based on mRNA and lncRNA Interactions.

Caligus rogercresseyi, commonly known as sea louse, is an ectoparasite copepod that impacts the salmon aquaculture in Chile, causing losses of hundreds of million dollars per year. This pathogen is mainly controlled by immersion baths with delousing drugs, which can lead to resistant traits selection in lice populations. Bioassays are commonly used to assess louse drug sensitivity, but the current procedures may mask relevant molecular responses. This study aimed to discover novel coding genes and non-coding RNAs that could evidence drug sensitivity at the genomic level. Sea lice samples from populations with contrasting sensitivity to delousing drugs were collected. Bioassays using azamethiphos, cypermethrin, and deltamethrin drugs were conducted to evaluate the sensitivity and to collect samples for RNA-sequencing. Transcriptome sequencing was conducted on samples exposed to each drug to evaluate the presence of coding and non-coding RNAs associated with the response of these compounds. The results revealed specific transcriptome patterns in lice exposed to azamethiphos, deltamethrin, and cypermethrin drugs. Enrichment analyses of Gene Ontology terms showed specific biological processes and molecular functions associated with each delousing drug analyzed. Furthermore, novel long non-coding RNAs (lncRNAs) were identified in C. rogercresseyi and tightly linked to differentially expressed coding genes. A significant correlation between gene transcription patterns and phenotypic effects was found in lice collected from different salmon farms with contrasting drug treatment efficacies. The significant correlation among gene transcription patterns with the historical background of drug sensitivity suggests novel molecular mechanisms of pharmacological resistance in lice populations.

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.

Single Nucleotide Polymorphism Charting of P. patens Reveals Accumulation of Somatic Mutations During in vitro Culture on the Scale of Natural Variation by Selfing.

Introduction: Physcomitrium patens (Hedw.) Mitten (previously known as Physcomitrella patens) was collected by H.L.K. Whitehouse in Gransden Wood (Huntingdonshire, United Kingdom) in 1962 and distributed across the globe starting in 1974. Hence, the Gransden accession has been cultured in vitro in laboratories for half a century. Today, there are more than 13 different pedigrees derived from the original accession. Additionally, accessions from other sites worldwide were collected during the last decades.Methods and Results: In this study, 250 high throughput RNA sequencing (RNA-seq) samples and 25 gDNA samples were used to detect single nucleotide polymorphisms (SNPs). Analyses were performed using five different P. patens accessions and 13 different Gransden pedigrees. SNPs were overlaid with metadata and known phenotypic variations. Unique SNPs defining Gransden pedigrees and accessions were identified and experimentally confirmed. They can be successfully employed for PCR-based identification.Conclusion: We show independent mutations in different Gransden laboratory pedigrees, demonstrating that somatic mutations occur and accumulate during in vitro culture. The frequency of such mutations is similar to those observed in naturally occurring populations. We present evidence that vegetative propagation leads to accumulation of deleterious mutations, and that sexual reproduction purges those. Unique SNP sets for five different P. patens accessions were isolated and can be used to determine individual accessions as well as Gransden pedigrees. Based on that, laboratory methods to easily determine P. patens accessions and Gransden pedigrees are presented.

Host gill attachment causes blood-feeding by the salmon louse (Lepeophtheirus salmonis) chalimus larvae and alters parasite development and transcriptome

BackgroundBlood-feeding is a common strategy among parasitizing arthropods, including the ectoparasitic salmon louse (Lepeophtheirus salmonis), feeding off its salmon host’s skin and blood. Blood is rich in nutrients, among these iron and heme. These are essential molecules for the louse, yet their oxidative properties render them toxic to cells if not handled appropriately. Blood-feeding might therefore alter parasite gene expression.MethodsWe infected Atlantic salmon with salmon louse copepodids and sampled the lice in two different experiments at day 10 and 18 post-infestation. Parasite development and presence of host blood in their intestines were determined. Lice of similar instar age sampled from body parts with differential access to blood, namely from gills versus lice from skin epidermis, were analysed for gene expression by RNA-sequencing in samples taken at day 10 for both experiments and at day 18 for one of the experiments.ResultsWe found that lice started feeding on blood when becoming mobile preadults if sitting on the fish body; however, they may initiate blood-feeding at the chalimus I stage if attached to gills. Lice attached to gills develop at a slower rate. By differential expression analysis, we found 355 transcripts elevated in lice sampled from gills and 202 transcripts elevated in lice sampled from skin consistent in all samplings. Genes annotated with “peptidase activity” were among the ones elevated in lice sampled from gills, while in the other group genes annotated with “phosphorylation” and “phosphatase” were pervasive. Transcripts elevated in lice sampled from gills were often genes relatively highly expressed in the louse intestine compared with other tissues, while this was not the case for transcripts elevated in lice sampled from skin. In both groups, more than half of the transcripts were from genes more highly expressed after attachment.ConclusionsGill settlement results in an alteration in gene expression and a premature onset of blood-feeding likely causes the parasite to develop at a slower pace.

Comparative Transcriptomic Analysis to Identify the Genes Related to Delayed Gland Morphogenesis in Gossypium bickii.

Cotton is one of the major industrial crops that supply natural fibers and oil for industries. This study was conducted to understand the mechanism of delayed gland morphogenesis in seeds of Gossypium bickii. In this study, we compared glandless seeds of G. bickii with glanded seeds of Gossypium arboreum. High-throughput sequencing technology was used to explore and classify the expression patterns of gland-related genes in seeds and seedlings of cotton plants. Approximately 131.33 Gigabases of raw data from 12 RNA sequencing samples with three biological replicates were generated. A total of 7196 differentially-expressed genes (DEGs) were identified in all transcriptome data. Among them, 3396 genes were found up-regulated and 3480 genes were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were performed to identify different functions between genes unique to glandless imbibed seeds and glanded seedlings. Co-expression network analysis revealed four modules that were identified as highly associated with the development of glandless seeds. Here the hub genes in each module were identified by weighted gene co-expression network analysis (WGCNA). In total, we have selected 13 genes involved in transcription factors, protein and MYB-related functions, that were differentially expressed in transcriptomic data and validated by quantitative reverse-transcription polymerase chain reaction (qRT-PCR). These selected genes may play an important role for delayed gland morphogenesis. Our study provides comprehensive insight into the key genes related to glandless traits of seeds and plants, and can be further exploited by functional and molecular studies.

Host Transcriptional Responses to High- and Low-Virulent Avian Malaria Parasites.

The transcriptional response of hosts to genetically similar pathogens can vary substantially, with important implications for disease severity and host fitness. A low pathogen load can theoretically elicit both high and low host responses, as the outcome depends on both the effectiveness of the host at suppressing the pathogen and the ability of the pathogen to evade the immune system. Here, we investigate the transcriptional response of Eurasian siskins (Spinus spinus) to two closely related lineages of the malaria parasite Plasmodium relictum. Birds were infected with either the high-virulent lineage P. relictum SGS1, the low-virulent sister lineage P. relictum GRW4, or sham-injected (controls). Blood samples for RNA sequencing were collected at four time points during the course of infection, totaling 76 transcriptomes from 19 birds. Hosts infected with SGS1 experienced up to 87% parasitemia and major transcriptome shifts throughout the infection, and multiple genes showed strong correlation with parasitemia. In contrast, GRW4-infected hosts displayed low parasitemia (maximum 0.7%) with a minor transcriptional response. We furthermore demonstrate that the baseline gene expression levels of hosts prior to infection were irrelevant as immunocompetence markers, as they could not predict future pathogen load. This study shows that the magnitude of the host transcriptional response can differ markedly from related parasites with different virulence, and it enables a better understanding of the molecular interactions taking place between hosts and parasites.

Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions.

The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.

Investigation of Antigen-Specific T-Cell Receptor Clusters in Human Cancers.

Cancer antigen-specific T cells are key components in antitumor immune response, yet their identification in the tumor microenvironment remains challenging, as most cancer antigens are unknown. Recent advance in immunology suggests that similar T-cell receptor (TCR) sequences can be clustered to infer shared antigen specificity. This study aims to identify antigen-specific TCRs from the tumor genomics sequencing data. We used the TRUST (Tcr Repertoire Utilities for Solid Tissue) algorithm to assemble the TCR hypervariable CDR3 regions from 9,700 bulk tumor RNA-sequencing (RNA-seq) samples, and developed a computational method, iSMART, to group similar TCRs into antigen-specific clusters. Integrative analysis on the TCR clusters with multi-omics datasets was performed to profile cancer-associated T cells and to uncover novel cancer antigens. Clustered TCRs are associated with signatures of T-cell activation after antigen encounter. We further elucidated the phenotypes of clustered T cells using single-cell RNA-seq data, which revealed a novel subset of tissue-resident memory T-cell population with elevated metabolic status. An exciting application of the TCR clusters is to identify novel cancer antigens, exemplified by our identification of a candidate cancer/testis gene, HSFX1, through integrated analysis of HLA alleles and genomics data. The target was further validated using vaccination of humanized HLA-A*02:01 mice and ELISpot assay. Finally, we showed that clustered tumor-infiltrating TCRs can differentiate patients with early-stage cancer from healthy donors, using blood TCR repertoire sequencing data, suggesting potential applications in noninvasive cancer detection. Our analysis on the antigen-specific TCR clusters provides a unique resource for alternative antigen discovery and biomarker identification for cancer immunotherapies.

Genome-Wide Identification of lncRNAs During Rice Seed Development.

Rice seed is a pivotal reproductive organ that directly determines yield and quality. Long non-coding RNAs (lncRNAs) have been recognized as key regulators in plant development, but the roles of lncRNAs in rice seed development remain unclear. In this study, we performed a paired-end RNA sequencing in samples of rice pistils and seeds at three and seven days after pollination (DAP) respectively. A total of 540 lncRNAs were obtained, among which 482 lncRNAs had significantly different expression patterns during seed development. Results from semi-qPCR conducted on 15 randomly selected differentially expressed lncRNAs suggested high reliability of the transcriptomic data. RNA interference of TCONS_00023703, which is predominantly transcribed in developing seeds, significantly reduced grain length and thousand-grain weight. These results expanded the dataset of lncRNA in rice and enhanced our understanding of the biological functions of lncRNAs in rice seed development

Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers

We sought to define the landscape of alternative pre-mRNA splicing in prostate cancers and the relationship of exon choice to known cancer driver alterations. To do so, we compiled a metadataset composed of 876 RNA-sequencing (RNA-Seq) samples from five publicly available sources representing a range of prostate phenotypes from normal tissue to drug-resistant metastases. We subjected these samples to exon-level analysis with rMATS-turbo, purpose-built software designed for large-scale analyses of splicing, and identified 13,149 high-confidence cassette exon events with variable incorporation across samples. We then developed a computational framework, pathway enrichment-guided activity study of alternative splicing (PEGASAS), to correlate transcriptional signatures of 50 different cancer driver pathways with these alternative splicing events. We discovered that Myc signaling was correlated with incorporation of a set of 1,039 cassette exons enriched in genes encoding RNA binding proteins. Using a human prostate epithelial transformation assay, we confirmed the Myc regulation of 147 of these exons, many of which introduced frameshifts or encoded premature stop codons. Our results connect changes in alternative pre-mRNA splicing to oncogenic alterations common in prostate and many other cancers. We also establish a role for Myc in regulating RNA splicing by controlling the incorporation of nonsense-mediated decay-determinant exons in genes encoding RNA binding proteins.

Clinical and functional significance of circular RNAs in cytogenetically normal AML

AbstractCircular RNAs (circRNAs) are noncoding RNA molecules that display a perturbed arrangement of exons, called backsplicing. To examine the prognostic and biologic significance of circRNA expression in cytogenetically normal acute myeloid leukemia (CN-AML), we conducted whole-transcriptome profiling in 365 younger adults (age 18-60 years) with CN-AML. We applied a novel pipeline, called Massive Scan for circRNA, to identify and quantify circRNA expression. We validated the high sensitivity and specificity of our pipeline by performing RNase R treatment and RNA sequencing in samples of AML patients and cell lines. Unsupervised clustering analyses identified 3 distinct circRNA expression–based clusters with different frequencies of clinical and molecular features. After dividing our cohort into training and validation data sets, we identified 4 circRNAs (circCFLAR, circKLHL8, circSMC1A, and circFCHO2) that were prognostic in both data sets; high expression of each prognostic circRNA was associated with longer disease-free, overall, and event-free survival. In multivariable analyses, high circKLHL8 and high circFCHO2 expression were independently associated with better clinical outcome of CN-AML patients, after adjusting for other covariates. To examine the biologic relevance of circRNA expression, we performed knockdown screening experiments in a subset of prognostic and gene mutation–related candidate circRNAs. We identified circFBXW7, but not its linear messenger RNA, as a regulator of the proliferative capacity of AML blasts. In summary, our findings underscore the molecular associations, prognostic significance, and functional relevance of circRNA expression in CN-AML.

Virus expression detection reveals RNA-sequencing contamination in TCGA

BackgroundContamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al., for example, found HeLa-derived human papillomavirus 18 (H-HPV18) in several of The Cancer Genome Atlas (TCGA) RNA-sequencing samples. This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years.ResultsWe confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the “common reference”, which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the “common reference”. One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells.ConclusionsAltogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV.

Dual Vascular Endothelial Growth Factor Receptor and Fibroblast Growth Factor Receptor Inhibition Elicits Antitumor Immunity and Enhances Programmed Cell Death-1 Checkpoint Blockade in Hepatocellular Carcinoma

Background and Aims: Combining anti-angiogenic therapy with immune checkpoint blockade with anti-programmed cell death-1 (PD-1) antibodies is a promising treatment for hepatocellular carcinoma (HCC). Tyrosine kinase inhibitors are well-known anti-angiogenic agents and offer potential for combination with anti-PD-1 antibodies. This study investigated the possible underlying immunomodulatory mechanisms of combined therapy. Methods: HCC tissue samples for RNA-sequencing (RNA-seq) were obtained from patients with differential prognoses following anti-PD-1 treatment. Recombinant basic fibroblast growth factor (bFGF) and vascular endothelial growth factor A (VEGFA) were used to stimulate T cells following lenvatinib or sorafenib treatment, respectively. T cell function was analyzed by flow cytometry and lactate dehydrogenase assay. In vivo experiments were conducted in murine H22 and Hepa 1–6 competent models of HCC. Local immune infiltration in the tumor microenvironment (TME) was assessed using multicolor flow cytometry. Gene regulation was evaluated by RNA-seq. Microvascular density was measured by immunohistochemistry, and PD-1 ligand (PD-L1) induction was quantified by western blot. Results: The baseline expression of VEGF and fibroblast growth factor (FGF) in patients with progressive disease was significantly higher than in patients achieving stable disease following anti-PD-1 treatment. VEGFA and bFGF significantly upregulated the expression of PD-1, cytotoxic T-lymphocyte-associated protein-4, and Tim-3 on T cells, while inhibiting the secretion of interferon gamma (IFNG) and granzyme B and suppressing T cell cytotoxicity. This immunosuppressive effect was reverted by lenvatinib but not sorafenib. Furthermore, dual lenvatinib/anti-PD-1 antibody therapy led to better antitumor effects than either sorafenib or fibroblast growth factor receptor (FGFR) inhibitor (BGJ398) in H22 murine models of HCC. Combined lenvatinib/anti-PD-1 treatment also led to long-term immune memory formation, while synergistically modulating the TME and enhancing the cytotoxic effect of T cells. Finally, lenvatinib inhibited PD-L1 expression on human umbilical vein endothelial cells, which improved the function of T cells. Conclusions: Inhibition of vascular endothelial growth factor receptor and FGFR augmented the efficacy of anti-PD-1 antibodies. Combined lenvatinib/anti-PD-1 treatment appears to exert antitumor activity by synergistically modulating effector T cell function in the TME and by mutually regulating tumor vessel normalization.

Biological Network Approach for the Identification of Regulatory Long Non-Coding RNAs Associated With Metabolic Efficiency in Cattle.

Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle.Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F2-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set.Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.

Maize transposable elements contribute to long non-coding RNAs that are regulatory hubs for abiotic stress response

BackgroundSeveral studies have mined short-read RNA sequencing datasets to identify long non-coding RNAs (lncRNAs), and others have focused on the function of individual lncRNAs in abiotic stress response. However, our understanding of the complement, function and origin of lncRNAs – and especially transposon derived lncRNAs (TE-lncRNAs) - in response to abiotic stress is still in its infancy.ResultsWe utilized a dataset of 127 RNA sequencing samples that included total RNA datasets and PacBio fl-cDNA data to discover lncRNAs in maize. Overall, we identified 23,309 candidate lncRNAs from polyA+ and total RNA samples, with a strong discovery bias within total RNA. The majority (65%) of the 23,309 lncRNAs had sequence similarity to transposable elements (TEs). Most had similarity to long-terminal-repeat retrotransposons from the Copia and Gypsy superfamilies, reflecting a high proportion of these elements in the genome. However, DNA transposons were enriched for lncRNAs relative to their genomic representation by ~ 2-fold. By assessing the fraction of lncRNAs that respond to abiotic stresses like heat, cold, salt and drought, we identified 1077 differentially expressed lncRNA transcripts, including 509 TE-lncRNAs. In general, the expression of these lncRNAs was significantly correlated with their nearest gene. By inferring co-expression networks across our large dataset, we found that 39 lncRNAs are as major hubs in co-expression networks that respond to abiotic stress, and 18 appear to be derived from TEs.ConclusionsOur results show that lncRNAs are enriched in total RNA samples, that most (65%) are derived from TEs, that at least 1077 are differentially expressed during abiotic stress, and that 39 are hubs in co-expression networks, including a small number that are evolutionary conserved. These results suggest that lncRNAs, including TE-lncRNAs, may play key regulatory roles in moderating abiotic responses.

Fusion gene detection across a large cohort of multiple myeloma patients

Gene fusions are an important class of genetic variation relevant across cancer types. We detected gene fusion events from a cohort of 742 patients from the Multiple Myeloma Research Foundation CoMMpass Dataset, combining sequencing data from RNA and DNA with clinical information to form a landscape of fusion events. From the 742 patients, 53 had data from multiple time points for a total of 806 samples in this study. We ran five fusion detection tools on each sample's RNA sequencing data and required fusions to pass several filtering criteria.

Screen and classify genes on bladder cancer associated with metastasis

ObjectiveBladder urothelial carcinoma (BLCA) is a common tumor in humans and a multi-factorial disease. Gene expression may predict the metastasis of cancer. This study aimed to screen differential expression genes related to metastasis of bladder cancer and classify these genes in different groups. MethodsThe clinical and RNA sequencing (RNA-Seq) expression data in patients with BLCA were downloaded from the TCGA data portal. A total of 407 BLCA samples were available in the TCGA database, for which the clinical information was acquired, of which 407 are RNA-Seq samples with a total of 19 paired samples. SPSS 22.0 was used to find the differentially expressed genes related to bladder cancer with metastasis. Software ‘Gcluto’ was used to cluster the patients with bladder cancer according to the expression of genes and the character of clinical information. ResultsTwo hundred and fourteen differentially expressed genes related to metastasis of bladder cancer were found from 20,530 genes. Genes were clustered according to the signal pathways, and 19 pairs of patients were clustered according to clinical information and gene expression into 5 groups and the relationships between the genes and the clinical information were found. ConclusionFBN2 may be related to the papillary subtype of bladder cancer, DEIP1 may be related to the smoking history and the with tumor status of bladder cancer patients. Patients with IER2, C19orf6, CAPZA1, AES, MYL12B and ATPIF1 may have high opportunity of bladder cancer, while CLDND2, PCDHGA6 and SLITRK4 may have less association to bladder cancer compared with other genes.