Published Transcriptome Data Research Articles

Lack of TGFβ signaling competency predicts immune poor cancer conversion to immune rich and response to checkpoint blockade.

Transforming growth factor beta (TGFβ) is well-recognized as an immunosuppressive player in the tumor microenvironment but also has a significant impact on cancer cell phenotypes. Loss of TGFβ signaling impairs DNA repair competency, which is described by a transcriptomic score, βAlt. Cancers with high βAlt have more genomic damage and are more responsive to genotoxic therapy. The growing appreciation that cancer DNA repair deficits are important determinants of immune response prompted us to investigate the association of βAlt with response to immune checkpoint blockade (ICB). We predicted that high βAlt tumors would be infiltrated with lymphocytes because of DNA damage burden and hence responsive to ICB. We analyzed public transcriptomic data from clinical trials and preclinical models using transcriptomic signatures of TGFβ targets, DNA repair genes, tumor educated immune cells and interferon. A high βAlt, immune poor mammary tumor derived transplant model resistant to programmed death ligand 1 (PD-L1) antibodies was studied using multispectral flow cytometry to interrogate the immune system. Metastatic bladder patients in IMvigor 210 who responded to ICB had significantly increased βAlt scores and experienced significantly longer overall survival compared to those with low βAlt scores (hazard ratio 0.62, P=0.011) . Unexpectedly, 75% of high βAlt cancers were immune poor as defined by low expression of tumor educated immune cell and interferon signatures. The association of high βAlt with immune poor cancer was also evident in TCGA and preclinical cancer models. We used a high βAlt, immune poor cancer to test therapeutic strategies to overcome its inherent anti-PD-L1 resistance. Combination treatment with radiation and TGFβ inhibition were necessary for lymphocytic infiltration and activated NK cells were required for ICB response. Bioinformatic analysis identified high βAlt, immune poor B16 and CT26 preclinical models and paired biopsies of cancer patients that also demonstrated NK cell activation upon response to ICB. Our studies support βAlt as a biomarker that predicts response to ICB albeit in immune poor cancers, which has implications for the development of therapeutic strategies to increase the number of cancer patients who will benefit from immunotherapy.

Constructing a novel prognostic model for triple-negative breast cancer based on genes associated with vasculogenic mimicry.

Research has shown a connection between vasculogenic mimicry (VM) and cancer progression. However, the functions of genes related to VM in the emergence and progression of TNBC have not been completely elucidated. A survival risk model was constructed by screening biomarkers using DESeq2 and WGCNA based on public TNBC transcriptome data. Furthermore, gene set enrichment analysis was performed, and tumor microenvironment and drug sensitivity were analyzed. The selected biomarkers were validated via quantitative PCR detection, immunohistochemical staining, and protein detection in breast cancer cell lines. Biomarkers related to the proliferation and migration of TNBC cells were validated via in vitro experiments. The findings revealed that 235 target genes were connected to the complement and coagulation cascade pathways. The risk score was constructed using KCND2, NRP1, and VSTM4. The prognosis model using the risk score and pathological T stage yielded good validation results. The clinical risk of TNBC was associated with the angiogenesis signaling pathway, and the low-risk group exhibited better sensitivity to immunotherapy. Quantitative PCR and immunohistochemistry indicated that the expression levels of KCND2 in TNBC tissues were higher than those in adjacent nontumor tissues. In the TNBC cell line, the protein expression of KCND2 was increased. Knockdown of KCND2 and VSTM4 inhibited the proliferation and migration of TNBC cells in vitro. In this study, three VM-related biomarkers were identified, including KCND2, NRP1, and VSTM4. These findings are likely to aid in deepening our understanding of the regulatory mechanism of VM in TNBC.

Abstract PO1-25-04: PTN-positive luminal progenitors induce angiogenesis and metastasis in inflammatory breast cancer

Abstract Background Inflammatory breast cancer (IBC) is a lethal subtype of breast cancer characterized by rapidly arising diffuse erythema and edema of the overlying skin that was thought to contribute to rapid metastasis. Dissecting the intricate cellular ecosystems within tumors and affected skin and their complex interplay may be pivotal in unraveling the aggressive nature of IBC. Methods Integrative analysis containing single-cell RNA sequencing, bulk RNA sequencing, and whole exome sequencing, was performed on paired tumor and skin samples from 17 treatment-naive IBC patients and 5 non-IBC patients from multiple centers. Meanwhile, paraffin sections and serum specimens from two centers were conducted to validate the omics results. Additionally, public single-cell transcriptomic data of non-IBC tumors and normal mammary glands, RNA microarray data from IBC cases, and the Cancer Genome Atlas (TCGA) database were utilized to validate the characteristics of IBC microenvironment. The regulatory mechanism was verified by in vitro experiments. Results We delineated the landscapes of IBC tumor and affected skin microenvironment at the single-cell level and demonstrated that the luminal progenitors (LP) cells highly expressing pleiotrophin (PTN) were most significantly enriched in IBC tumors compared to non-IBC tumors and normal mammary glands, in two independent cohorts. Moreover, the serum concentrations of PTN were significantly higher in IBC patients compared with non-IBC patients. Notably, PTN secreted by PTN+ LP cells interacted with Neuropilin 1(NRP1) receptor on endothelial tip cells in both tumor and affected skin of IBC. Moreover, in vitro assay demonstrated knocking down the expression of NRP1 on human umbilical vein endothelial cells significantly blocked PTN-induced migration, tube formation and sprouting, which might be independent of VEGFA. In addition, two immature phenotypes of PVL_MMP9 and PVL_CCL19 cells recruited by endothelial tip cells via PDGFB/PDGFRB axis were accumulated in affected skin of IBC, which might be associated with promotion of malignant cell metastasis. Finally, we revealed that malignant cells in affected skin of IBC had a higher ability of epithelial-mesenchymal transition than IBC intratumoral malignant cells and identified enhanced crosstalk between immature PVL cells and malignant cells in the skin affected with IBC , through TNFSF12-TNFRSF12A, TGFB-TGFBR1/TGFBR2, MDK-SDC1/4/NCL/(ITGA6+ITGB1). Conclusion We identified a unique, non-malignant epithelial cell subpopulation PTN+ LP cells, which induce massive angiogenesis via the PTN-NRP1 axis, recruit the immature phenotype PVL cells accumulated in affected skin of IBC thus promoting tumor progression. Our findings offer comprehensive insights into the pathogenesis of IBC and uncover a previously unknown, promising therapeutic target. Patient of discovery cohort details Clinical and pathology details for inflammatory breast cancer(IBC) and non-IBC patients analysed by single-cell RNA sequencing(scRNA-seq), bulk RNA sequencing(bulk RNA-seq) and whole exome sequencing(WES) in this study. Clinicalpathological feature of validation cohort Citation Format: Mengmeng Zhang, Kaiwen Zhou, Ting Liu, Filipa Lynce, Filipa Lynce, Wendy Chen, Qianjun Chen, Xiaoping Li, Zhongyu Yuan, Juan Xu, Zhenhai Cai, Jianping Guo, Nan Shao, Ying Lin. PTN-positive luminal progenitors induce angiogenesis and metastasis in inflammatory breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-25-04.

Integrative informatics analysis identifies that ginsenoside Re improves renal fibrosis through regulation of autophagy.

We previously demonstrated that ginsenoside Re (G-Re) has protective effects on acute kidney injury. However, the underlying mechanism is still unclear. In this study, we conducted a meta-analysis and pathway enrichment analysis of all published transcriptome data to identify differentially expressed genes (DEGs) and pathways of G-Re treatment. We then performed in vitro studies to measure the identified autophagy and fibrosis markers in HK2 cells. In vivo studies were conducted using ureteric obstruction (UUO) and aristolochic acid nephropathy (AAN) models to evaluate the effects of G-Re on autophagy and kidney fibrosis. Our informatics analysis identified autophagy-related pathways enriched for G-Re treatment. Treatment with G-Re in HK2 cells reduced autophagy and mRNA levels of profibrosis markers with TGF-β stimulation. In addition, induction of autophagy with PP242 neutralized the anti-fibrotic effects of G-Re. In murine models with UUO and AAN, treatment with G-Re significantly improved renal function and reduced the upregulation of autophagy and profibrotic markers. A combination of informatics analysis and biological experiments confirmed that ginsenoside Re could improve renal fibrosis and kidney function through the regulation of autophagy. These findings provide important insights into the mechanisms of G-Re's protective effects in kidney injuries.

The DBB Family in Populus trichocarpa: Identification, Characterization, Evolution and Expression Profiles.

The B-box proteins (BBXs) encode a family of zinc-finger transcription factors that regulate the plant circadian rhythm and early light morphogenesis. The double B-box (DBB) family is in the class of the B-box family, which contains two conserved B-box domains and lacks a CCT (CO, CO-like and TOC1) motif. In this study, the identity, classification, structures, conserved motifs, chromosomal location, cis elements, duplication events, and expression profiles of the PtrDBB genes were analyzed in the woody model plant Populus trichocarpa. Here, 12 PtrDBB genes (PtrDBB1-PtrDBB12) were identified and classified into four distinct groups, and all of them were homogeneously spread among eight out of seventeen poplar chromosomes. The collinearity analysis of the DBB family genes from P. trichocarpa and two other species (Z. mays and A. thaliana) indicated that segmental duplication gene pairs and high-level conservation were identified. The analysis of duplication events demonstrates an insight into the evolutionary patterns of DBB genes. The previously published transcriptome data showed that PtrDBB genes represented distinct expression patterns in various tissues at different stages. In addition, it was speculated that several PtrDBBs are involved in the responsive to drought stress, light/dark, and ABA and MeJA treatments, which implied that they might function in abiotic stress and phytohormone responses. In summary, our results contribute to the further understanding of the DBB family and provide a reference for potential functional studies of PtrDBB genes in P. trichocarpa.

A System Biology Approach Reveals New Targets for Human Thyroid Gland Toxicity in Embryos and Adult Individuals.

Compounds of natural or synthetic origin present in personal care products, food additives, and packaging may interfere with hormonal regulation and are called endocrine-disrupting chemicals (EDCs). The thyroid gland is an important target of these compounds. The objective of this study was to analyze public data on the human thyroid transcriptome and investigate potential new targets of EDCs in the embryonic and adult thyroid glands. We compared the public transcriptome data of adult and embryonic human thyroid glands and selected 100 up- or downregulated genes that were subsequently subjected to functional enrichment analysis. In the embryonic thyroid, the most highly expressed gene was PRMT6, which methylates arginine-4 of histone H2A (86.21%), and the downregulated clusters included plasma lipoprotein particles (39.24%) and endopeptidase inhibitory activity (24.05%). For the adult thyroid gland, the most highly expressed genes were related to the following categories: metallothionein-binding metals (56.67%), steroid hormone biosynthetic process (16.67%), and cellular response to vascular endothelial growth factor stimulus (6.67%). Several compounds ranging from antihypertensive drugs to enzyme inhibitors were identified as potentially harmful to thyroid gland development and adult function.

A multi-cell model for the C4 photosynthetic pathway in developing wheat grains based upon tissue-specific transcriptome data

A non-Kranz C4 photosynthesis of the NAD-ME subtype, specifically in developing wheat grains (14 dpa, days post-anthesis) was originally demonstrated using transcriptome-based RNA-seq. Here we present a re-examination of evidence for C4 photosynthesis in the developing grains of wheat and, more broadly, the Pooideae and an investigation of the evolutionary processes and implications. The expression profiles for the genes associated with C4 photosynthesis (C4- and C3-specific) were evaluated using published transcriptome data for the outer pericarp, inner pericarp, and endosperm tissues of the developing wheat grains. The expression of the C4-specific genes across these three tissues revealed the involvement of all three tissues in an orderly fashion to accomplish the non-Kranz NAD-ME-dependent C4 photosynthesis. Based on their expression levels in RPKM (reads per kilobase per million mapped reads) values, a model involving multiple cell- and tissue-types is proposed for C4 photosynthesis involved in the refixation of the respired CO2 from the endosperm tissues in the developing wheat grains. This multi-cell C4 model, proposed to involve more than two cell types, requires further biochemical validation.

Genome-wide characterization of heavy metal-associated isoprenylated plant protein gene family from Citrus sinensis in response to huanglongbing.

Heavy metal-associated isoprenylated plant proteins (HIPPs) play vital roles in maintaining heavy metal balance and responding to both biotic and abiotic stresses in vascular plants. However, the role of HIPPs in the response to Huanglongbing (HLB), a harmful disease of citrus caused by the phloem-colonizing bacterium Candidatus Liberibacter asiaticus (CLas), has not been examined. In this study, a total of 26 HIPP genes were identified in Citrus sinensis, and they were grouped into 5 clades. The CsHIPP genes are distributed on 8 chromosomes and exhibited considerable synteny with HIPPs found in Arabidopsis thaliana. Additionally, we analyzed the gene structure, conserved motifs and domains of the CsHIPPs. Various cis-acting elements related to plant hormones and stress responses were identified in the promoters of CsHIPPs. Public transcriptome data and RT-qPCR analysis showed that the expression level of CsHIPP03 was significantly reduced in samples infected by CLas and Xanthomonas citri ssp. citri (Xcc). Furthermore, silencing the homologous gene of CsHIPP03 in Nicotiana benthamiana increased the disease resistance of plants to bacteria. Our results provide a basis for functional studies of HIPP gene family in C. sinensis, highlighting their functions in bacterial resistance, and improve our understanding to the susceptibility mechanism of HLB.

Abstract 4428: Integrated multi-omics analysis reveals systemic and localized metabolic disruptions in colorectal cancer

Abstract Despite technological advances in molecular medicine over the last 30 years, no single approach has proven to be sufficient to meet the diagnostic needs in cancer care. Here we use a multiomic approach leveraging proteomic, metabolomic, and transcriptomic technologies to study the metabolic shifts that occur during colorectal cancer (CRC) progression, Our integrated analysis identified systemic changes to beta oxidation pathways and localized changes to tyrosine metabolism within the tumor, creating a mechanistic, actionable description of the core CRC metabolic program. We conducted untargeted proteomics and metabolomics profiling on serum samples from CRC patients (n=10) and healthy controls (n=10). Our serum proteomics data is generated through sample enrichment on the Seer Proteograph system followed by LC/MS analysis with the Thermo Orbitrap Astral. Our metabolomics approach employs LC/MS assays for unbiased profiling of the serum metabolome, exposome, and lipidome. We supplemented this discovery work with both targeted serum and tumor-specific approaches including targeted proteomics to quantify select targets, inflammatory profiling with Alamar proteomics, public transcriptomics data from TCGA, and in vitro metabolic flux data. These large and diverse datasets were then integrated through joint pathway analysis and network integration. The global serum proteomics and metabolomics profiles generated show distinct separation between healthy and diseased individuals. Joint pathway analysis of these discovery datasets highlighted enrichment in beta oxidation pathways and tyrosine metabolism, among others. Interestingly, the Alamar inflammatory panel revealed that many of the analytes in the tyrosine metabolism pathway were well correlated with inflammatory status, while the beta oxidation signature had a lower correlation. To determine the relationship of these systemic findings from serum to tumor metabolism itself, we integrated tumor-specific transcriptomics data and found alterations to tyrosine metabolism with differences in tyrosine aminotransferase expression. The beta oxidation related genes, on the other hand, were not concordant with the serum findings. However, our in vitro metabolic flux studies have shown beta oxidation in CRC cells is upregulated to provide additional fuel for oxidative phosphorylation. This result suggests that beta oxidation may not be transcriptionally regulated in the tumor but rather a consequence of organismal metabolic rewiring. The results of this work, which is currently expanding into a larger and more diverse patient population, underscores the power of multiomic profiling for enhancing our understanding of metabolic dysregulation in CRC. Ultimately, a comprehensive model of the molecular alterations in CRC will yield a better understanding of tumor phenotypes and inform better diagnostics and therapies. Citation Format: Gary Patti, Ethan Stancliffe, Adam Richardson, Ashima Mehta, Monil Gandhi, Kevin Cho. Integrated multi-omics analysis reveals systemic and localized metabolic disruptions in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4428.

Abstract 1065: Two-step method for early detection of ovarian cancer with high specificity via platelet RNA

Abstract Owing to lack of disease-specific symptoms and screening methods, most of patients with ovarian cancer are diagnosed at an advanced stage. Recent technology based on platelet RNA aids in detection of tumors at the early stages. Also, for population screening of low-prevalence diseases like cancer, accurate detection with high specificity is essential to improve diagnostic methods. Thus, we proposed platelet RNA-based early ovarian cancer detection with great specificity. It is a two-step method for detecting ovarian tumors with more than 99% specificity using exon-exon junction features and sampling invariant normalization and finding their malignancy with more than 99% negative predictive value using exon-exon junction and hematology parameters. First, we downloaded public platelet transcriptome data of gynecological cancer including ovarian cancer (n=151), benign tumor (n=30), and healthy counterparts (n=218) from GEO (GSE158508, 89843, and 183635). Second, we prospectively enrolled patients with gynecological cancer (n=31), benign tumors (n=20), and healthy women (n=18) at Seoul National University Hospital (SNUH) and Boaz Medical Center and obtained platelet transcriptome data (FMH data). Feature selection and model development were conducted using public training set (n=243), public validation set (n=156), and FMH training/validation set (n=47). The batch-invariant normalization was performed, and 198 splice junctions were selected as features from training/validation set for the bootstrap aggregation of the SVM model diagnosing the existence of an ovarian tumor. The model performance was assessed from a separate test set only composed of FMH data (n=22). Our model that demonstrated 96.8% sensitivity, 100.0% specificity, with a predetermined cut-off value. Next, FMH training/validation set was used for model development of following malignancy test. 10 splice junctions and 19 hematology parameters were selected and SVM models were separately developed for splice junctions and hematology parameters using 5-fold cross validation. The predictions were combined using a logical OR operation to obtain the final prediction result. The result showed its diagnostic performance with 100% sensitivity or NPV, and 50.0% specificity in the test data set with a predetermined cut-off value. We proposed a two-step method to operationally improve the existing protocol for ovarian cancer screening. Our model initially excludes most healthy individuals who do not have ovarian tumors and excludes patients with benign ovarian tumors who do not necessitate medical testing. To conclude, our model allows physicians to identify a subset of ovarian tumor patients with a higher risk of malignancy even at early stages; it exhibits potential in enhancing early diagnosis of ovarian cancer, leading to increase of treatment effectiveness and ultimately augmenting the survival of patients with ovarian cancer. Citation Format: Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Yeochan Kim, Eunchong Huang, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, TaeJin Ahn, Yong-Sang Song. Two-step method for early detection of ovarian cancer with high specificity via platelet RNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1065.

Decomposition of dynamic transcriptomic responses during effector-triggered immunity reveals conserved responses in two distinct plant cell populations

Rapid plant immune responses in the appropriate cells are needed for effective defense against pathogens. Although transcriptome analysis is often used to describe overall immune responses, collection of transcriptome data with sufficient resolution in both space and time is challenging. We reanalyzed public Arabidopsis time-course transcriptome data obtained after low-dose inoculation with a Pseudomonas syringae strain expressing the effector AvrRpt2, which induces effector-triggered immunity in Arabidopsis. Double-peak time-course patterns are prevalent among thousands of upregulated genes. We implemented a multi-compartment modeling approach to decompose the double-peak pattern into two single-peak patterns for each gene. The decomposed peaks reveal an “echoing” pattern: the peak times of the first and second peaks correlate well across most upregulated genes. We demonstrated that the two peaks likely represent responses of two distinct cell populations that respond either cell autonomously or indirectly to AvrRpt2. Thus, the peak decomposition has extracted spatial information from the time-course data. The echoing pattern also indicates a conserved transcriptome response with different initiation times between the two cell populations despite different elicitor types. A gene set highly overlapping with the conserved gene set is also upregulated with similar kinetics during pattern-triggered immunity. Activation of a WRKY network via different entry-point WRKYs can explain the similar but not identical transcriptome responses elicited by different elicitor types. We discuss potential benefits of the properties of the WRKY activation network as an immune signaling network in light of pressure from rapidly evolving pathogens.

Multi-omics characterization and identification of small non-coding RNAs in Spiroplasma eriocheiris

Spiroplasma eriocheiris is the major pathogen in the aquaculture shrimp and crab tremor disease; its infection causes heavy losses in aquaculture. Previous investigations concentrated on how the host responds to S. eriocheiris infection, with little known on the regulation of virulence and pathogenesis by the bacteria themselves. A body of increasing evidence shows that bacterial small noncoding RNAs (sRNAs) play a crucial part in regulating bacterial virulence and pathogenesis; however, whether there are some sRNAs in S. eriocheiris and how those sRNAs regulate virulence and pathogenesis are still unclear. This study analyzed multi-omics data integration to identify the potential sRNAs and their mediated regulatory network in S. eriocheiris. First, through an integration analysis of the public genomic and transcriptomic data, 54 potential sRNAs were identified in S. eriocheiris with a 50–250 nt length distribution and the base composition mainly AT. Next, sRNA profiling of the in vitro logarithmic and decline phase of S. eriocheiris, as well as the early and onset stage of infection in Eriocheir sinensis, was performed, showing that 4 sRNAs (SR01, SR05, SR08, and S04) were both down-regulated in the logarithmic and the onset stage of infection. Subsequently, integrated with sRNAs target gene prediction and target gene expression analysis, a regulatory network composed of four sRNAs and 96 target genes was constructed. Last, an RNA pull-down experiment was performed on the SR01, which exhibited the highest abundance and the highest number of target genes, resulting in 37 highly credible target genes with multiple genes related to bacterial virulence, such as GTPases and virulence factor coding genes. Collectively, this study identified the sRNAs in S. eriocheiris and revealed their mediated regulatory network for regulating virulence and pathogenesis, thus paving a new avenue for disease prevention and control in aquaculture.

Identification and Characterization of the AREB/ABF Gene Family in Three Orchid Species and Functional Analysis of DcaABI5 in Arabidopsis.

AREB/ABF (ABA response element binding) proteins in plants are essential for stress responses, while our understanding of AREB/ABFs from orchid species, important traditional medicinal and ornamental plants, is limited. Here, twelve AREB/ABF genes were identified within three orchids' complete genomes and classified into three groups through phylogenetic analysis, which was further supported with a combined analysis of their conserved motifs and gene structures. The cis-element analysis revealed that hormone response elements as well as light and stress response elements were widely rich in the AREB/ABFs. A prediction analysis of the orchid ABRE/ABF-mediated regulatory network was further constructed through cis-regulatory element (CRE) analysis of their promoter regions. And it revealed that several dominant transcriptional factor (TF) gene families were abundant as potential regulators of these orchid AREB/ABFs. Expression profile analysis using public transcriptomic data suggested that most AREB/ABF genes have distinct tissue-specific expression patterns in orchid plants. Additionally, DcaABI5 as a homolog of ABA INSENSITIVE 5 (ABI5) from Arabidopsis was selected for further analysis. The results showed that transgenic Arabidopsis overexpressing DcaABI5 could rescue the ABA-insensitive phenotype in the mutant abi5. Collectively, these findings will provide valuable information on AREB/ABF genes in orchids.

Circulating tRNA-derived fragments are decreased in patients with rheumatoid arthritis and increased in patients with psoriatic arthritis

Introduction tRNA-derived fragments (tRFs) play an important role in immune responses. To clarify the role of tRFs in autoimmunity we studied circulating tRF-levels in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), and in a murine model for arthritis. Material and methods Circulating tRF-levels were quantified by miR-Q RT-qPCR. tRNA processing and modification enzyme expression was analysed by RT-qPCR and public transcriptomics data. Results Significant reduction (up to 3-fold on average) of tRF-levels derived from tRNA-Gly-GCC,CCC, tRNA-Glu-CTC and tRNA-Val-CAC,AAC was observed in RA patients, whereas tRNA-Glu-CTC and tRNA-Val-CAC,AAC tRFs were found at significantly higher levels (up to 3-fold on average) in PsA patients, compared to healthy controls. Also in arthritic IL1Ra-KO mice reduced levels of tRNA-Glu-CTC fragments were seen. The expression of NSUN2, a methyltransferase catalysing tRNA methylation, was increased in RA-peripheral blood mononuclear cells (PBMCs) compared to PsA, but this is not consistently supported by public transcriptomics data. Discussion The observed changes of specific tRF-levels may be involved in the immune responses in RA and PsA and may be applicable as new biomarkers. Conclusion Circulating tRF-levels are decreased in RA and increased in PsA and this may, at least in part, be mediated by methylation changes.

Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups

Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Do differentially expressed genes explain high myopia in congenital stationary night blindness?

Myopia is the most common eye disorder, caused by heterogeneous genetic and environmental factors. Rare inherited retinal disorders are often associated with high myopia. Genes implicated in myopia encode proteins involved in eye morphogenesis, extracellular matrix organization, visual perception, circadian rhythms, and retinal signalling. Differentially expressed genes (DEGs) identified in animal models mimicking myopia are helpful in suggesting candidate genes implicated in human myopia. Complete congenital stationary night blindness (cCSNB) in humans and animal models represents an ON‐bipolar cell signal transmission defect and is also associated with high myopia. The purpose of this work was to identify the molecular cause of myopia present in cCSNB. A whole transcriptome sequencing (RNA‐seq) approach was performed using retina from three mouse lines with cCSNB, Gpr179−/−, Lrit3−/− and Grm6−/− and the expression data compared to data of age‐matched wild‐type littermates (n = 5). DEGs with fold changes of at least 1.2, P‐values of ≤0.01, an expression value of at least 5 transcripts per million reads and appearing in at least two cCSNB mouse lines were investigated in detail. A meta‐analysis was performed by a) comparing our data with published transcriptome data from purified retinal cells and single cell RNA‐Seq data, b) pathway analyses, c) myopia databases and publications concerning their role in normal vision. Several of the DEGs were validated by RT‐qPCR experiments and analysed by western blot and immunolocalization studies. More than 50 DEGs were found in at least two cCSNB mouse lines. Expression of those was found in different retinal cell types. The difference in expression was independent of the number of nuclei present in wild‐type and mutant inner retina. Pathway analysis revealed that mitogen‐activated protein kinase pathways, synaptic signalling, G protein‐coupled receptor ligand binding pathways, and proteins implicated in eye, endoderm and connective tissue development were affected in cCSNB. More than half of the genes were already associated with myopia. Our study reveals DEGs in all retinal cell types of cCSNB models, previously associated with myopia and novel candidates. These studies combined with pathway analyses provide the basis for the development of pharmacological and optical myopia therapies.

Global Analysis of the WOX Transcription Factor Family in Akebia trifoliata.

Akebia trifoliata is an economically important, self-incompatible fruit tree in the Lardizabalaceae family. Asexual propagation is the main strategy used to maintain excellent agronomic traits. However, the generation of adventitious roots during asexual propagation is very difficult. To study the important role of the WUSCHEL-related homeobox (WOX) transcription factor in adventitious root growth and development, we characterized this transcription factor family in the whole genome of A. trifoliata. A total of 10 AktWOXs were identified, with the following characteristics: length (657~11,328 bp), exon number (2~5), isoelectric point (5.65~9.03), amino acid number (176~361 AA) and molecular weight (20.500~40.173 kDa), and their corresponding expression sequence could also be detectable in the public transcriptomic data for A. trifoliata fruit. A total of 10 AktWOXs were classified into modern (6), intermediate (2) and ancient clades (2) and all AktWOXs had undergone strong purifying selection during evolution. The expression profile of AktWOXs during A. trifoliata adventitious root formation indicated that AktWOXs play an important role in the regulation of adventitious root development. Overall, this is the first study to identify and characterize the WOX family in A. trifoliata and will be helpful for further research on A. trifoliata adventitious root formation.

Combined metabolomics and transcriptomics analysis of rats under neuropathic pain and pain-related depression.

Neuropathic pain often leads to negative emotions, which in turn can enhance the sensation of pain. This study aimed to investigate the molecular mechanisms mediating neuropathic pain and negative emotions. Chronic constriction injury (CCI) rats were used as model animals and behavioral tests were conducted to assess pain and negative emotions. Then, the rat anterior cingulate cortex (ACC) was analyzed using UPLC-MS/MS and subsequently integrated with our previously published transcriptome data. Metabolomics analysis revealed that 68 differentially expressed metabolites (DEMs) were identified, mainly in amino acid metabolites and fatty acyls. Combined with our previously published transcriptome data, we predicted two genes that potentially exhibited associations with these metabolites, respectively Apolipoprotein L domain containing 1 (Apold1) and WAP four-disulfide core domain 1 (Wfdc1). Taken together, our results indicated that peripheral nerve injury contributing to neuropathic pain and pain-related depression may be associated with these metabolites and genes. This research provides new insights into the molecular regulatory mechanism, which could serve as a reference for the treatment of neuropathic pain and pain-related depression.

Study on Screening Core Biomarkers of Noise and Drug-Induced Hearing Loss Based on Transcriptomics.

Background Noise and drug-induced hearing loss (HL) is becoming more and more serious, but the integration and analysis based on transcriptomics and proteomics are lacking. On the one hand, this study aims to integrate existing public transcriptomic data on noise and gentamicin-induced HL. On the other hand, the study aims to establish the gentamicin and noise-induced HL model of guinea pigs, then to perform the transcriptomic and proteomic analyses. Through comprehensive analysis of the above data, we aim to screen, predict, and preliminarily verify biomarkers closely related to HL. Material and Methods We screened the Gene Expression Omnibus database to obtain transcriptome data expression profiles of HL caused by noise and gentamicin, then constructed the guinea pig HL model and perform the transcriptomic and proteomic analyses. Differential expression and enrichment analysis were performed on public and self-sequenced data, and common differentially expressed genes (DEGs) and signaling pathways were obtained. Finally, we used proteomic data to screen for common differential proteins and validate common differential expression genes for HL. Results By integrating the public data set with self-constructed model data set, we eventually obtained two core biomarkers of HL, which were RSAD2 and matrix metalloproteinase-3 (MMP3). Their main function is to regulate the development of sense organ in the inner ear and they are mainly involved in mitogen-activated protein kinase and phosphoinositol-3 kinase/protein kinase B signaling pathways. Finally, by integrating the proteomic data of the self-constructed model, we also found differential expression of MMP3 protein. This also preliminarily and partially verified the above-mentioned core biomarkers. Conclusion and Significance In this study, public database and transcriptomic data of self-constructed model were integrated, and we screened out two core genes and various signal pathways of HL through differential analysis, enrichment analysis, and other analysis methods. Then, we preliminarily validated the MMP3 by proteomic analysis of self-constructed model. This study pointed out the direction for further laboratory verification of key biomarkers of HL, which is of great significance for revealing the core pathogenic mechanism of HL.

Drug Repositioning for Amyloid Transthyretin Amyloidosis by Interactome Network Corrected by Graph Neural Networks and Transcriptome Analysis.

Amyloid transthyretin (ATTR) amyloidosis caused by transthyretin misfolded into amyloid deposits in nerve and heart is a progressive rare disease. The unknown pathogenesis and the lack of therapy make the 5-year survival prognosis extremely poor. Currently available ATTR drugs can only relieve symptoms and slow down progression, but no drug has demonstrated curable effect for this disease. The growing volume of pharmacological data and large-scale genome and transcriptome data bring new opportunities to find potential new ATTR drugs through computational drug repositioning. We collected the ATTR-related in the disease pathogenesis and differentially expressed (DE) genes from five public databases and Gene Expression Omnibus expression profiles, respectively, then screened drug candidates by a corrected protein-protein network analysis of the ATTR-related genes as well as the drug targets from DrugBank database, and then filtered the drug candidates on the basis of gene expression data perturbed by compounds. We collected 139 and 56 ATTR-related genes from five public databases and transcriptome data, respectively, and performed functional enrichment analysis. We screened out 355 drug candidates based on the proximity to ATTR-related genes in the corrected interactome network, refined by graph neural networks. An Inverted Gene Set Enrichment analysis was further applied to estimate the effect of perturbations on ATTR-related and DE genes. High probability drug candidates were discussed. Drug repositioning using systematic computational processes on an interactome network with transcriptome data were performed to screen out several potential new drug candidates for ATTR.