Differential Expression Data Research Articles

HATZFS predicts pancreatic cancer driver biomarkers by hierarchical reinforcement learning and zero-forcing set

The search for cancer biomarkers is of great significance for the early diagnosis and clinical treatment planning of pancreatic cancer. RNA transcription networks can effectively represent the interactions between RNA molecules, and the irregular perturbations in these interactions can lead to pathological states, making them commonly used for identifying cancer biomarkers. However, traditional network-based methods for identifying cancer biomarkers often rely on prior information and mutation data. Furthermore, most network controllability-based methods face the limitation of high computational complexity, preventing their integration with deep learning methods. In this paper, we propose a novel deep learning framework, called HATZFS, for identifying driver biomarkers in pancreatic cancer using RNA differential expression data. The proposed model combines hierarchical deep Q-network (HDQN), graph attention network (GAT), and zero-forcing set (ZFS). Firstly, a pancreatic cancer RNA transcription regulatory network is constructed to embed the complex relationship among Long non-coding RNA (lncRNA), microRNA (miRNA) and messenger RNA (mRNA). Then, we transform it into multiple subgraphs using graph sampling method, and apply GAT to learn the node features of the subgraphs. Finally, the HATZFS performs HDQN to select subgraphs and identify important RNA as driver nodes, and determining the controllability of the subgraphs based on ZFS. More important, the paper theoretically proves that when all subgraphs are controllable, the original graph is also controllable, and the union of the driver node sets of all subgraphs is equal to the driver node set of the original graph. To confirm the effectiveness of the proposed model, comprehensive experiments are conducted on the benchmark dataset consisting of 14 databases, comparing it with eight other algorithms. The experimental results demonstrate that the proposed model outperforms other methods. Overall, HATZFS not only provides the importance of all RNA molecules in the pancreatic cancer RNA regulatory network, but also identifies the driver node set of the network as driver biomarkers. Source code can be accessed at https://github.com/HongJieTongXue/HATZFS.

Differential Expression Analysis Reveals Possible New Quaternary Ammonium Compound Resistance Gene in Highly Resistant Serratia sp. HRI.

During the COVID-19 pandemic, the surge in disinfectant use emphasised their pivotal role in infection control. While the majority of antimicrobial resistance research focuses on antibiotics, resistance to biocides, which are present in disinfectants and sanitisers, is escalating. Serratia sp. HRI is a highly resistant isolate, and through the study of this organism, the molecular mechanisms of resistance may be uncovered. Serratia sp. HRI was treated with the disinfectant benzalkonium chloride in preparation for RNA sequencing. Through mining of the RNA-Seq differential expression data, an uncharacterised Major Facilitator Superfamily (MFS) efflux pump gene was found to be up-regulated at least four-fold at four different time points of exposure. Real-time PCR revealed this uncharacterised MFS efflux gene was up-regulated after exposure to benzalkonium chloride and two additional disinfectants, didecyldimethylammonium chloride (DDAC) and VirukillTM. Additionally, expression of this gene was found to be higher at 20 min versus 90 min of exposure, indicating that the up-regulation of this gene is an initial response to biocide treatment that decreases over time. This suggests that MFS efflux pumps may be an initial survival mechanism for microorganisms, allowing time for longer-term resistance mechanisms. This work puts forward a novel biocide resistance gene that could have a major impact on biocide susceptibility and resistance.

E2F1 modulates RCCD1 expression to participate in the initiation and progression of EMT in colorectal cancer

ObjectiveMetastases in the advanced stages of colorectal cancer (CRC) present a major challenge to its treatment. Epithelial-Mesenchymal Transition (EMT) plays a crucial role in enhancing the metastasis and invasion ability of cancer cells. However, the progress of E2F transcription factor 1 (E2F1) and Regulator of chromatin condensation 1 (RCCD1) in CRC on EMT has not been studied. MethodsThe CRC differential expression data from The Cancer Genome Atlas database were analyzed by Gene Set Enrichment Analysis to verify the difference in expression of E2F1 and RCCD1 in cancerous and para-cancerous tissues.DNA-pull down and dual luciferase experiments confirmed that E2F1 regulates RCCD1. Western-blot and q-PCR experiments confirmed that E2F1 regulates RCCD1 and participates in the EMT-related progress of CRC.EDU, Wound healing and Transwell experiments verified the effects of regulation of E2F1 and RCCD1 on the proliferation, migration and invasion of CRC cells. ResultsE2F1 and RCCD1 are highly expressed in cancer tissues and cancer cells. E2F1 binds to the upstream promoter of RCCD1 to regulate RCCD1 and affect the expression of EMT-related targets in CRC cells. It also affects the proliferation, migration and invasion of CRC cells. ConclusionsE2F1 regulates the involvement of RCCD1 in CRC EMT and affects the proliferation, migration and invasion ability of CRC cells.

Perineural invasion in prostate cancer is associated with Schwann cells and disruption of circadian rhythm-related gene expression: A bioinformatics approach

Schwann cells in the tumor microenvironment are reportedly involved in the production of several factors that benefit cancer cell growth. During this process, Schwann cells are dedifferentiated and facilitate cancer cellular proliferation. The cells then migrate to the region close to the tumor tissue and assist the development of the neoplastic cells. Accordingly, the present study was designed to evaluate the perineural invasion in prostate cancer, in association with disrupted circadian rhythm-related gene expression in Schwann cells. Initially, we identified a database reporting gene expression in Schwann cells in a neoplastic context from the GEO Datasets platform in the GEO repository. The database contains the expression results from experiments in which two factors produced by tumor cells were added to cell cultures. Comparisons were made between samples from the first and third passages. Then, these data were used in differential gene expression analysis and combined with differential expression data of genes upregulated in perineural invasion-negative and -positive prostate cancers. We observed that the “axon guidance” pathway was upregulated in perineural invasion-negative prostate cancers. Meanwhile, upregulated mRNAs activated the “axon guidance” pathway and, together with ROBO1 and MPZ upregulation, inhibited perineural invasion pathways. Both genes are also associated with inhibition of Schwann cell migration. PER3, NR3C1, PPARGC1A, TIMP3, ID2, PDE6B, and CAVIN1 were upregulated in perineural invasion-negative tumors, while SLC25A10 was upregulated. We also observed upregulated expression in perineural invasion-positive tumors for genes such as PPARGC1A, TIMP3, S100A8, ID2, DEFB1, AQP3, ASS1, PDE6B, NEFH, and CAVIN1. AQP3 and NEFH were upregulated only in perineural invasion-positive tumors and PER3 and NR3C1 were upregulated only in perineural invasion-negative samples. The findings revealed that circadian rhythm and/or melatonin disruption are associated with dedifferentiation of Schwann cells, which consequently produce a set of factors that drive tumor progression. These processes may also be involved in tumor invasion into the perineural tissue in prostate cancer.

O05 Single-cell transcriptomic signature of paradoxical eczema in patients with psoriasis treated with biologics

Abstract Introduction and aims Biologics targeting the tumour necrosis factor (TNF) and the interleukin (IL)-17/23 axis are highly effective treatments for psoriasis but can result in cutaneous adverse events. The pathogenesis of paradoxical eczema, an atopic dermatitis (AD) phenotype occurring after biologic initiation in people with psoriasis, is unknown. This study explored the systemic disease signature of paradoxical eczema. Methods We used single-cell RNA-Seq on peripheral blood mononuclear cells (PBMCs) from three patients with psoriasis with paradoxical eczema, and three matched, biologic-treated controls who had psoriasis. Differential gene expression, gene network expression and cell–cell interaction (using MultiNicheNet) analyses allowed comparison of cases and controls. We assessed overlap between paradoxical eczema and AD using six AD transcriptome datasets. Results Overall, 32 827 PBMCs (14 521 from cases, 18 306 from controls) were included and categorized into 27 clusters. Between cases and controls, there were 727 differentially expressed genes (DEGs) (log fold-change > 0.25, adjusted P < 0.05). A total of 94 of the top 100 DEGs were from monocytes. Significant DEG networks (P < 0.05) mostly mapped to T-cell and monocyte clusters, with commonly enriched pathways in cases including interferon (IFN)-γ, IFN-α, TNF, IL-2/signal transducer and activator of transcription 5 and T-cell differentiation pathways. Cell–cell interaction analysis revealed that the most prioritized interactions in controls, based on differential expression data and known ligand-receptor interactions, included immune regulatory interactions (including ligands such as transforming growth factor β1 and lymphocyte-activation gene 3). In cases, functions of prioritized interactions included chemotaxis, leucocyte activation, T-cell priming and IFN-γ signalling. There was significant enrichment of concordance in the direction of effect of DEGs (65%, P = 5.39 × 10−6) and enriched pathways (85%, P = 3.62 × 10−13) between AD and paradoxical eczema. Conclusions Patients with paradoxical eczema have reduced immune regulatory mechanisms and evidence of monocyte and T-cell activation systemically, with increased production IFN-γ, IFN-α and TNF. There is a significant overlap with the AD transcriptome.

Transcriptomic and western blot characterisation of the human CLEFF4 clone, a new rapid cell line replacement for the Caco2 model

The CLEFF4 sub clone from stock late passage Caco2 cells has a unique property of being able to develop polarised cell monolayers with high P-gp expression and tight junctions much quicker than the original cell line. Instead of being useful for transport studies 21–24 days after initiating culture, the CLEFF4 cell line matures in 5–6 days with tight junctions surpassing that of 3 week old Caco2 cells in that time frame [1].This has enabled the CLEFF4 cell line to provide measures of apparent permeability for potential drug candidates, so important for pre-clinical drug development, 4 times faster than the original cell line. RNA samples were collected and analysed at days 4 and 7 of culture over a 3 year period and had full RNA transcriptome analysed by the ranaseq.eu open bioinformatics platform. Protein was also collected from day 4 to day 22 of culture. Differential expression data from the FASTQ files have shown significant differences in expression in multiple genes involved with drug efflux, tight junctions, phase 2 metabolism and growth factors, which have been confirmed from protein determination that may hold the key to understanding accelerated human cell maturation. These gene expression results may be significant for other tissues beyond the gastrointestinal tract, and potentially for accelerated cell growth for the new field of laboratory grown tissues for organ replacement. The data also confirms the different genetic expression in CLEFF4 cells compared to Caco2 and the stable nature of the different expression over many years.

Comprehensive single-cell transcriptomic profiling reveals molecular subtypes and prognostic biomarkers with implications for targeted therapy in esophageal squamous cell carcinoma

BackgroundEsophageal squamous cell carcinoma (ESCC) is a genetically heterogeneous disease with poor clinical outcomes. Identification of biomarkers linked to DNA replication stress may enable improved prognostic risk stratification and guide therapeutic decision making. We performed integrated single-cell RNA sequencing and computational analyses to define the molecular determinants and subtypes underlying ESCC heterogeneity. MethodsSingle-cell RNA sequencing was performed on ESCC samples and analyzed using Seurat. Differential gene expression analysis was used to identify esophageal cell phenotypes. DNA replication stress-related genes were intersected with single-cell differential expression data to identify potential prognostic genes, which were used to generate a DNA replication stress (DRS) score. This score and associated genes were evaluated in survival analysis. Putative prognostic biomarkers were evaluated by Cox regression and consensus clustering. Mendelian randomization analyses assessed the causal role of PRKCB. ResultsHigh DRS score associated with poor survival. Four genes (CDKN2A, NUP155, PPP2R2A, PRKCB) displayed prognostic utility. Three molecular subtypes were identified with discrete survival and immune properties. A 12-gene signature displayed robust prognostic performance. PRKCB was overexpressed in ESCC, while PRKCB knockdown reduced ESCC cell migration. ConclusionsThis integrated single-cell sequencing analysis provides new insights into the molecular heterogeneity and prognostic determinants underlying ESCC. The findings identify potential prognostic biomarkers and a gene expression signature that may enable improved patient risk stratification in ESCC. Experimental validation of the role of PRKCB substantiates the potential clinical utility of our results.

Enrichment on steps, not genes, improves inference of differentially expressed pathways.

Enrichment analysis is frequently used in combination with differential expression data to investigate potential commonalities amongst lists of genes and generate hypotheses for further experiments. However, current enrichment analysis approaches on pathways ignore the functional relationships between genes in a pathway, particularly OR logic that occurs when a set of proteins can each individually perform the same step in a pathway. As a result, these approaches miss pathways with large or multiple sets because of an inflation of pathway size (when measured as the total gene count) relative to the number of steps. We address this problem by enriching on step-enabling entities in pathways. We treat sets of protein-coding genes as single entities, and we also weight sets to account for the number of genes in them using the multivariate Fisher's noncentral hypergeometric distribution. We then show three examples of pathways that are recovered with this method and find that the results have significant proportions of pathways not found in gene list enrichment analysis.

Abstract 6254: Casein kinase II (CK2) expression in pediatric solid tumors

Abstract Despite recent advances, high-risk neuroblastoma (NB) and sarcomas account for 15% and 5% of all pediatric cancer deaths, respectively. Many patients attain remission, but approximately half of patients relapse. Genomic alterations such as MYCN amplification and ALK mutations have been shown to be important in prognosis and treatment. Despite improvements, approximately 20% of patients have refractory or recurrent disease after therapy, underscoring the need for further genomic understanding and new approaches to treatment.CK2 is a serine/threonine kinase that regulates numerous cellular processes such as cell growth, proliferation, and survival. Overexpression of CK2 is associated with a poor prognosis in several adult solid tumors, making it a potential target of interest in pediatric solid tumors. This study aims to investigate CK2 expression among patients with NB, Ewing sarcoma (EWS), and rhabdomyosarcoma (RMS) and its correlation with patient survival. MethodsPatients were enrolled in NMTRC008/009: “Feasibility Trial Using Molecular Guided Therapy for Patients with Relapsed/Refractory Childhood Cancer” and BCC-001. WES and RNA-Seq were performed at the Translational Genomics Research Institute and Sema4 or Caris respectively. RNA expression levels were compared to a normal whole-body reference and a pediatric cancer reference. Differential expression data were interpreted in the context of systems biology.ResultsTumor WES was performed on 297 patients (212 NB, 50 EWS, 35 RMS) and RNA-Seq on 284 patients (210 NB, 39 EWS, 35 RMS). The most common mutations or copy number alterations were seen in MYCN, ATRX, ALK, CDKN2A, and chr17q+ in NB; EWSR1-FLI1 fusion in EWS; PAX3-FOXO1 fusion in RMS. RNA expression analysis was performed to understand MYCN-driver status by covariance and interactions and to identify subsets of patients with high/low expression of CK2 in different tumors. CK2 bimodal expression is seen across various cancers and normal tissues, implying distinct sub-groups exist in the data. In NB, overexpression of the CK2 gene with statistical significance was found in MYCN-amplified and chr17q+ tumors. A positive and negative correlation of the CK2 gene is seen with several target genes like MYCN, TRIM71, LIN28B, and HMGA2, JAK2, AR, STAT3, EGFR, LEF1, and NFKB2, respectively. In EWS and RMS, subgroups are identified with high and low expression of the CK2 gene.ConclusionGenomic sequencing of pediatric solid tumors showed a low mutation burden. RNA analysis resulted in the identification of potential novel therapeutic targets involving CK2 pathways. High expression of CK2 correlates with MYCN status. Further analysis of patient molecular subgroups is ongoing. Citation Format: Abhinav Beeravally Nagulapally, Chandrika Behura, Divya Gandra, Giselle Saulnier Sholler. Casein kinase II (CK2) expression in pediatric solid tumors [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 6254.

Abstract 1733: SET-NUP214 rearranges the DNA-methylation landscape to upregulate the HOX-gene cluster in acute myeloid leukemia

Abstract The SET-NUP214 (S/N) fusion gene, which results from either cryptic t(9:9) (q34;q34) or del(9) (q34.11q34.13), is found in a very narrow spectrum of patients diagnosed with Acute Myeloid Leukemia (AML) or T-cell acute lymphoblastic leukemia (T-ALL). AML patients with S/N fusion were reported to have relatively poor prognostic outcomes despite receiving myeloablative conditioning. While previously, the fusion has been described to overrepresent HOX cluster genes, the underlying mechanism of gene regulation that contributes to the pathology remains elusive due to the rare incidence of the disease. The current study used the MEGAL (ACC719, DSMZ) cell line, identified as the solo megakaryocytic AML line expressing the S/N-fusion, for determining genome-wide DNA methylation (DNAm) and gene expression using 935K Infinium MethylationEPIC v2.0 BeadChip array and RNA-sequencing, respectively. The differential DNAm and expression data were analyzed and compared to the hematopoietic stem progenitor cells (HSPC) or normal megakaryocytes (MK). The ChIP-sequencing data from the S/N positive T-ALL cell line LOUCY has been used to represent the coincidence of regulatory chromatin marks and differentially methylated CpG (mC) sites. We observed n=1934 genes upregulated and n=2396 downregulated in MEGAL, compared to both HSPC and MK. The direction of expression changes between MEGAL and HSPC and MEGAL and MK showed a high correlation (r=0.92, p< 0.01). Per the previous literature, we observed an overrepresentation of HOX genes (n=19) in MEGAL. Based on DNAm profiling, we noticed a propensity of hypermethylation in MEGAL across the promoters (93%±0.6), bodies (93%±0.8), and intergenic (85%±0.3) regions, compared to HSPC/MK. Next, we integrated the mC and expression at the promoters and identified that the majority (75%±3) of the genes belong to the hyper-down (n=2563 against HPSC; n=1907 against MK) or hyper-up (n=965 against HPSC; n=923 against MK) clusters. We further investigated the HOXB (HOXB7, HOXB8, HOXB9) and HOXC (HOXC10, HOXC12, HOXC13, HOXC13-AS, HOXC4, HOXC5, HOC6, HOXC8, HOXC9, HOXC-AS1, HOXC-AS2, and HOXC-AS3) cluster genes, where hypermethylated CpGs mainly were concentrated at the CpG islands and overlapped with active promoter (H3K4me3, H3K4me1) signatures or enhancer-like (CTCF bound) elements. We also observed frequent overlaps between mC and H3K36me3 across the observed genes. The differentially expressed genes in this AML subtype were enriched for the hippo-signaling pathway, calcium signaling, focal adhesion, and PI3-Akt pathways. Collectively, our data showed that S/N favors genome-wide hypermethylation, which, in conjunction with the cis-regulatory elements, induces overrepresentation of the HOX cluster genes. These novel epigenetic vulnerabilities are worth pursuing for investigating the cellular function and pathophysiology of the disease. Citation Format: Samrat Roy Choudhury, Akhilesh Kaushal. SET-NUP214 rearranges the DNA-methylation landscape to upregulate the HOX-gene cluster in acute myeloid leukemia [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 1733.

Single-Cell RNA-seq reveals transcriptomic modulation of Alzheimer's disease by activated protein C.

Single-Cell RNA sequencing reveals changes in cell population in Alzheimer's disease (AD) model 5xFAD (5x Familial AD mutation) versus wild type (WT) mice. The returned sequencing data was processed through the 10x Genomics CellRanger platform to perform alignment and form corresponding matrix to perform bioinformatic analysis. Alterations in glial cells occurred in 5xFAD versus WT, especially increases in microglia proliferation were profound in 5xFAD. Differential expression testing of glial cells in 5xFAD versus WT revealed gene regulation. Globally, the critical genes implicated in AD progression are upregulated such as Apoe, Ctsb, Trem2, and Tyrobp. Using this differential expression data, GO term enrichment was completed to observe possible biological processes impacted by AD progression. Utilizing anti-inflammatory and cyto-protective recombinant Activated Protein C (APC), we uncover inflammatory processes to be downregulated by APC treatment in addition to recuperation of nervous system processes. Moreover, animal studies demonstrated that administration of recombinant APC significantly attenuated Aβ burden and improved cognitive function of 5xFAD mice. The downregulation of highly expressed AD biomarkers in 5xFAD could provide insight into the mechanisms by which APC administration benefits AD.

Angiopoietin-Like Protein 2 Serves as an Independent Prognostic Biomarker and Correlates with Immune Infiltration in Osteosarcoma

Osteosarcoma mostly occurs in adolescents, with high disability and mortality rates and poor prognosis. Angiopoietin-like protein 2 (ANGPTL2) is a secreted glycoprotein protein, which plays important roles in cellular processes and various diseases. Microarray gene expression data GSE16088 and GSE36001 were downloaded from Gene Expression Omnibus (GEO, <ext-link ext-link-type="uri" xlink:href="http://www.ncbi.nlm.nih.gov/geo">http://www.ncbi.nlm.nih.gov/geo</ext-link>). The Complex Heatmap package was used to construct heatmaps, the gglot2 R language package to plot volcanoes and differential expression data, and the “VennDiagram” R language package to plot Wayne plots. Western booting and qRT-PCR was used to detect ANGPTL2 expression in osteosarcoma tissues. proteins. In addition, the GeneMANIA database (<ext-link ext-link-type="uri" xlink:href="http://www.genemania.org">http://www.genemania.org</ext-link>) was cited to predict the ANGPTL2 interaction network. We used the single-sample gene-set enrichment analysis (ss GSEA) algorithm to quantify the immune infiltration of osteosarcoma. In the GSE16088 database there were 5005 that met the selected threshold of |log2(FC)| > 1 and P <0.05, of which 2719 were highly expressed and 2286 were lowly expressed. WB and qRT-PCR results showed that ANGPTL2 was significantly up-regulated in osteosarcoma tissues. ssGSEA showed that high ANGPTL2 expression in osteosarcoma patients had a worse prognosis. ssGSEA showed that high ANGPTL2 expression was correlated with Mast cells and Th1 cells. Collectively, ANGPTL2 can be an independent prognostic biomarker and correlated with immune infiltration in osteosarcoma.

Epigenetic Modulation Through KAT5/HDAC2 Regulates Synaptic Genes in a Disease‐State Specific Manner

AbstractBackgroundThe balance between histone acetylation and deacetylation by lysine acetyltransferases (KATs) and histone deacetylases (HDAC) plays a central role in neurodegeneration. In this work, we leverage the informatics infrastructure developed for TREAT‐AD, to align epigenetic regulation from two different models: the KAT5 knockout mouse and HDAC2 knockdown iPSC‐derived neurons of control and FAD genetic lineages.MethodThe KAT5 knockout mouse differential expression data derived from the CA1 of the hippocampus was compared to three groups: 1) human late onset Alzheimer’s disease (LOAD), 2) the 5X FAD mice and 3) human FAD patient transcriptomic data. In each comparison, the data was assessed in the context of the biological domains (19 core AD endophenotypes computationally defined for the TREAT‐AD bioinformatics pipeline). The KAT5 data are compared to the differential expression data derived from WT and FAD lines of iPSC‐derived neurons with or without HDAC2 knockdown (KD) post‐differentiation.ResultThe biological domain focused analysis found a consistent modulation of synaptic and immune genes across models. Interestingly, there is a statistically significant correlation between down‐regulated synaptic genes in the KAT5 knockout mouse data and human LOAD differential expression observed in the 1700 brains of transcriptomic data and 1100 brains of proteomic data analyzed for TREAT‐AD and concomitantly identified in early stage pseudotemporal models of AD. Not surprisingly, there is better correlation between the KAT5 KO mouse and the 5X FAD mice, with the human FAD data falling in between these comparisons. The examination of the FAD and WT iPSC‐derived neurons with and without HDAC2 KD, demonstrates that HDAC2 KD ameliorates the down‐regulation of synaptic genes in the FAD neurons, but appears to have the opposite effect in WT human neurons.ConclusionThe comparison of the two systems of epigenetic regulation suggest that KAT5 and HDAC2 exert opposite effects upon synaptic gene expression. However, the observation that decreasing HDAC2 levels increases synaptic gene expression in FAD neurons but decreases synaptic gene expression in normal healthy neurons suggest that there is an optimal chromatin state associated with maximal synaptic gene expression, and that too much or too little histone acetylation may impair synaptic homeostasis.

PRMT5 and CDK4/6 inhibition result in distinctive patterns of alternative splicing in melanoma.

Drugs targeting cyclin-dependent kinases 4 and 6 (CDK4/6) are promising new treatments for melanoma and other solid malignancies. In studies on CDK4/6 inhibitor resistance, protein arginine methyltransferase 5 (PRMT5) regulation of alternative splicing was shown to be an important downstream component of the CDK4/6 pathway. However, the full effects of inhibition of CDK4/6 on splicing events in melanoma and the extent to which they are dependent on PRMT5 has not been established. We performed full-length mRNA sequencing on CHL1 and A375 melanoma cell lines treated with the CDK4/6 inhibitor palbociclib and the PRMT5 inhibitor GSK3326595 and analysed data for differential gene expression and differential pre-mRNA splicing induced by these agents. Changes in gene expression and RNA splicing were more extensive under PRMT5 inhibition than under CDK4/6 inhibition. Although PRMT5 inhibition and CDK4/6 inhibition induced common RNA splicing events and gene expression profiles, the majority of events induced by CDK4/6 inhibition were distinct. Our findings indicate CDK4/6 has the ability to regulate alternative splicing in a manner that is distinct from PRMT5 inhibition, resulting in divergent changes in gene expression under each therapy.

Label-Free Quantitative Thermal Proteome Profiling Reveals Target Transcription Factors with Activities Modulated by MC3R Signaling.

Thermal proteome profiling with label-free quantitation using ion-mobility-enhanced LC-MS offers versatile data sets, providing information on protein differential expression, thermal stability, and the activities of transcription factors. We developed a multidimensional data analysis workflow for label-free quantitative thermal proteome profiling (TPP) experiments that incorporates the aspects of gene set enrichment analysis, differential protein expression analysis, and inference of transcription factor activities from LC-MS data. We applied it to study the signaling processes downstream of melanocortin 3 receptor (MC3R) activation by endogenous agonists derived from the proopiomelanocortin prohormone: ACTH, α-MSH, and γ-MSH. The obtained information was used to map signaling pathways downstream of MC3R and to deduce transcription factors responsible for cellular response to ligand treatment. Using our workflow, we identified differentially expressed proteins and investigated their thermal stability. We found in total 298 proteins with altered thermal stability, resulting from MC3R activation. Out of these, several proteins were transcription factors, indicating them as being downstream target regulators that take part in the MC3R signaling cascade. We found transcription factors CCAR2, DDX21, HMGB2, SRSF7, and TET2 to have altered thermal stability. These apparent target transcription factors within the MC3R signaling cascade play important roles in immune responses. Additionally, we inferred the activities of the transcription factors identified in our data set. This was done with Bayesian statistics using the differential expression data we obtained with label-free quantitative LC-MS. The inferred transcription factor activities were validated in our bioinformatic pipeline by the phosphorylated peptide abundances that we observed, highlighting the importance of post-translational modifications in transcription factor regulation. Our multidimensional data analysis workflow allows for a comprehensive characterization of the signaling processes downstream of MC3R activation. It provides insights into protein differential expression, thermal stability, and activities of key transcription factors. All proteomic data generated in this study are publicly available at DOI: 10.6019/PXD039945.

Identification of the Immune Landscapes and Follicular Helper T Cell-Related Genes for the Diagnosis of Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a progressive ocular ailment causing age-associated vision deterioration, characterized by dysregulated immune cell activity. Notably, follicular helper T (Tfh) cells have emerged as pivotal contributors to AMD pathogenesis. Nonetheless, investigations into Tfh-associated gene biomarkers for this disorder remain limited. Utilizing gene expression data pertinent to AMD procured from the Gene Expression Omnibus (GEO) repository, we employed the "DESeq2" R software package to standardize and preprocess expression levels. Concurrently, CIBERSORT analysis was utilized to compute the infiltration proportions of 22 distinct immune cell types. Subsequent to weighted gene correlation network analysis (WGCNA), coupled with differential expression scrutiny, we pinpointed genes intricately linked with Tfh cells. These potential genes underwent further screening using the MCODE function within Cytoscape software. Ultimately, a judicious selection of pivotal genes from these identified clusters was executed through the LASSO algorithm. Subsequently, a diagnostic nomogram was devised based on these selected genes. Evident Tfh cell disparities between AMD and control cohorts were observed. Our amalgamated analysis, amalgamating differential expression data with co-expression patterns, unveiled six genes closely associated with Tfh cells in AMD. Subsequent employment of the LASSO algo-rithm facilitated identification of the most pertinent genes conducive to predictive modeling. From these, GABRB3, MFF, and PROX1 were elected as prospective diagnostic biomarkers for AMD. This investigation discerned three novel biomarker genes, linked to inflammatory mechanisms and pivotal in diagnosing AMD. Further exploration of these genes holds potential to foster novel therapeutic modalities and augment comprehension of AMD's disease trajectory.

Unveiling the prognostic significance of SOX5 in esophageal squamous cell carcinoma: a comprehensive bioinformatic and experimental analysis.

This study aimed to investigate the expression and prognostic significance of SOX5 in esophageal squamous cell carcinoma (ESCC). Gene Expression Omnibus (GEO) data were analyzed to assess SOX5 expression in ESCC and normal tissues. Survival analysis was performed to evaluate its prognostic significance. Pathway enrichment analysis was conducted to identify pathways associated with low SOX5 expression. Methylation status of CpG sites in ESCC cases was examined, and SOX5 expression was evaluated. Differential expression and ChIP-seq data analyses were used to identify genes significantly correlated with SOX5 and to obtain target genes. A protein-protein interaction (PPI) network was constructed using hub genes, and their association with immune cell infiltration was determined. In vitro ESCC cell experiments validated the findings. SOX5 was significantly downregulated in ESCC samples compared to normal samples. Its downregulation was associated with shorter survival in ESCC patients. Pathway enrichment analysis revealed enrichment in regulated necrosis, NLRP3 inflammasome, formation of the cornified envelope, and PD-1 signaling. Methylation status of two CpG sites negatively correlated with SOX5 expression. Differential expression analysis identified 122 genes significantly correlated with SOX5, and 28 target genes were obtained from ChIP-seq analysis. Target genes were enriched in DNA replication, cell cycle, spindle, and ATPase activity. Five hub genes were identified, and the PPI network showed significant associations with immune cell infiltration. In vitro experiments confirmed SOX5 downregulation, upregulation of hub genes, and their functional effects on ESCC cell apoptosis and proliferation. These findings enhance understanding of SOX5 in ESCC and potential therapeutic strategies.

Characterisation of acetogen formatotrophic potential using Eubacterium limosum.

Formate is a promising energy carrier that could be used to transport renewable electricity. Some acetogenic bacteria, such as Eubacterium limosum, have the native ability to utilise formate as a sole substrate for growth, which has sparked interest in the biotechnology industry. However, formatotrophic metabolism in E. limosum is poorly understood, and a system-level characterisation in continuous cultures is yet to be reported. Here, we present the first steady-state dataset for E. limosum formatotrophic growth. At a defined dilution rate of 0.4 d-1, there was a high specific uptake rate of formate (280 ± 56mmol/gDCW/d; gDCW = gramme dry cell weight); however, most carbon went to CO2 (150 ± 11mmol/gDCW/d). Compared to methylotrophic growth, protein differential expression data and intracellular metabolomics revealed several key features of formate metabolism. Upregulation of phosphotransacetylase (Pta) appears to be a futile attempt of cells to produce acetate as the major product. Instead, a cellular energy limitation resulted in the accumulation of intracellular pyruvate and upregulation of pyruvate formate ligase (Pfl) to convert formate to pyruvate. Therefore, metabolism is controlled, at least partially, at the protein expression level, an unusual feature for an acetogen. We anticipate that formate could be an important one-carbon substrate for acetogens to produce chemicals rich in pyruvate, a metabolite generally in low abundance during syngas growth. KEY POINTS: First Eubacterium limosum steady-state formatotrophic growth omics dataset High formate specific uptake rate, however carbon dioxide was the major product Formate may be the cause of intracellular stress and biofilm formation.

Multi‐omics characterization of brain‐based pseudotime estimates for Alzheimer’s disease progression

AbstractBackgroundThe cascade of molecular changes that leads to Alzheimer’s disease (AD) onset and progression remains incompletely understood. Recently, researchers have utilized manifold learning techniques to construct pseudo‐temporal models of the disease using brain transcriptomics data and quantify the progression of individuals along this trajectory using pseudotime (Mukherjee et al. Nat Commun 2020;11:5781). Downstream analyses provided insights into potentially disease‐driving pathways, including links to mitochondrial dysfunction. Here, we embedded these models into a multi‐omics context to enable a more comprehensive molecular characterization of disease progression.MethodThe AD Atlas (https://adatlas.org/) integrates multi‐scale molecular data from different studies and cohorts, including omics QTLs, correlation networks, differential expression data, as well as omics associations with AD and endophenotypes. Here, we used the AD Atlas to annotate metabolites that were significantly associated with brain‐based pseudotime estimates. Metabolite (n = 667) levels were measured in brain tissue samples (dorsolateral prefrontal cortex) from 154 female ROS/MAP participants using untargeted metabolomics and tested for association using linear regression. We used the resulting set of significant metabolites as input for the AD Atlas to extract a multi‐omics context network augmented with associations to AD. Subsequently, we applied pathway enrichment analysis to derive overrepresented biological processes potentially involved in disease progression.ResultIn total, 89 of the 667 metabolites showed a significant association with pseudotime after Bonferroni adjustment, 34 of which could be mapped to the AD Atlas database. The resulting multi‐omics network contained a total of 619 genes, 197 metabolites and links to 12 AD‐related phenotypes, including CSF amyloid pathology, brain glucose uptake measured by FDG‐PET and cognitive measures. Five of the 34 metabolites and nearly one‐third of the genes contained in the network showed significant associations with AD, with transcriptional changes most pronounced in the temporal cortex (n = 193). Enrichment analysis revealed functional links to neurotransmission and bioenergetics, pathways previously implicated in the pathogenesis of AD.ConclusionBy using metabolites as proxies for transcriptome‐derived pseudotime, we were able to investigate the molecular underpinnings of AD progression in a multi‐omics context. Our analysis provides further molecular evidence for pathways implicated in AD and emphasizes the potential of such an approach for future studies.

A statistical approach for identifying primary substrates of ZSWIM8-mediated microRNA degradation in small-RNA sequencing data

BackgroundOne strategy for identifying targets of a regulatory factor is to perturb the factor and use high-throughput RNA sequencing to examine the consequences. However, distinguishing direct targets from secondary effects and experimental noise can be challenging when confounding signal is present in the background at varying levels.ResultsHere, we present a statistical modeling strategy to identify microRNAs that are primary substrates of target-directed miRNA degradation (TDMD) mediated by ZSWIM8. This method uses a bi-beta-uniform mixture (BBUM) model to separate primary from background signal components, leveraging the expectation that primary signal is restricted to upregulation and not downregulation upon loss of ZSWIM8. The BBUM model strategy retained the apparent sensitivity and specificity of the previous ad hoc approach but was more robust against outliers, achieved a more consistent stringency, and could be performed using a single cutoff of false discovery rate (FDR).ConclusionsWe developed the BBUM model, a robust statistical modeling strategy to account for background secondary signal in differential expression data. It performed well for identifying primary substrates of TDMD and should be useful for other applications in which the primary regulatory targets are only upregulated or only downregulated. The BBUM model, FDR-correction algorithm, and significance-testing methods are available as an R package at https://github.com/wyppeter/bbum.