Analysis Of RNA Sequencing Data Research Articles

Restricting Colorectal Cancer Cell Metabolism with Metformin: An Integrated Transcriptomics Study.

Metformin is a first-line therapy for type 2 diabetes as it disrupts cellular metabolism. Despite the association between metformin and lower cancer incidence, the anti-tumour activity of the drug in colorectal cancer (CRC) is incompletely understood. This study identifies underlying molecular mechanisms by which metformin slows colorectal cancer cell proliferation by investigating metformin-associated microRNA (miRNA) and target gene pairs implicated in signalling pathways. The present study analysed changes in miRNAs and the coding transcriptome in CRC cells treated with a sublethal dose of metformin, followed by the contextual validation of potential miRNA-target gene pairs. Analyses of small RNA and transcriptome sequencing data revealed 104 miRNAs and 1221 mRNAs to be differentially expressed in CRC cells treated with metformin for 72 h. Interaction networks between differentially expressed miRNAs and putative target mRNAs were identified. Differentially expressed genes were mainly implicated in metabolism and signalling processes, such as the PI3K-Akt and MAPK/ERK pathways. Further validation of potential miRNA-target mRNA pairs revealed that metformin induced miR-2110 and miR-132-3p to target PIK3R3 and, consequently, regulate CRC cell proliferation, cell cycle progression and the PI3K-Akt signalling pathway. Metformin also induced miR-222-3p and miR-589-3p, which directly target STMN1 to inhibit CRC cell proliferation and cell cycle progression. This study identified novel changes in the coding transcriptome and small non-coding RNAs associated with metformin treatment of CRC cells. Integration of these datasets highlighted underlying mechanisms by which metformin impedes cell proliferation in CRC. Importantly, it identified the post-transcriptional regulation of specific genes that impact both metabolism and cell proliferation.

Identification of the CD8 + T-cell Related Signature for Predicting the Prognosis of Gastric Cancer Based on Integrated Analysis of Bulk and Single-cell RNA Sequencing Data.

The infiltration of CD8 + T cells in the tumor microenvironment is associated with better survival and immunotherapy response. However, their roles in gastric cancer have not been explored so far. In here, the profiles of GC gene expression were collected from The Cancer Genome Atlas database. Single-cell transcriptomic data originated from GSE134520. Cell clustering, annotation, and CD8 + T-cell differential genes were from the TISCH database. We determined 896 CD8 + T-cell differential genes by scRNA-seq analysis. After integrating immune-related genes, 174 overlapping genes were obtained and a novel risk model was subsequently built. The performance of CD8 + T-cell-associated gene signature was assessed in the training and external validation sets. The gene signature showed independent risk factors of overall survival for GC. A quantitative nomogram was built to enhance the clinical efficacy of this signature. Furthermore, low-risk individuals showed higher mutation status, higher immune checkpoint expression, low Tumour Immune Dysfunction and Exclusion (TIDE) scores, and higher IPS-PD-1 combined IPS-CTLA4 scores, indicating a greater response to immunotherapy. In addition, analysis of IMvigor210 immunotherapy cohort demonstrated that low-risk individuals had a favorable response to prognosis and immunotherapy. In conclusion, we generated a CD8 + T-cell-related signature that can serve as a promising tool for personalized prognosis prediction and guiding decisions regarding immunotherapy in GC patients.

FABP4 as potential indicator for GDM-induced fetal endothelial dysfunction

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): DFG project no. 288034826—International Research Training Group (IRTG) 2251 Background Gestational diabetes mellitus (GDM) is linked to an elevated risk of developing cardiovascular diseases (CVD) both for the mother and the baby in later life. Previous studies have identified fatty acid-binding protein 4 (FABP4) as a prime candidate involved in the pathophysiology of GDM. FABP4 is known to promote an inflammatory response and vascular permeability, induce oxidative stress in endothelial cells (ECs), and impair the nitric oxide signaling pathway, thereby promoting endothelial dysfunction. Indeed, women with GDM exhibit elevated blood levels of FABP4, suggesting its potential as a biomarker for endothelial dysfunction and cardiovascular risk assessment in GDM. However, the role that FABP4 plays in the fetal endothelial function remains poorly understood. Purpose Thus, our aim is to understand the role of FABP4 in fetal endothelial dysfunction and its regulation to mitigate the impact of GDM on the vasculature. Methods Fetoplacental vessels and primary human umbilical vein endothelial cells (HUVECs) were isolated from placentas and umbilical cords obtained from both normoglycemic (NG) and GDM pregnancies. We also obtained the clinical data from the mothers and collected the cord blood. Total mRNA from HUVECs was used for bulk RNA sequencing to compare gene expression, while gene expression analysis in the vessels was conducted using RT-qPCR. Additionally, NG HUVECs were pooled and cultured under high laminar flow conditions (30 dyn/cm²) or subjected to various treatments, including insulin (5nM), glucose (25mM), simvastatin (10nm), or VEGF-A stimulation. Subsequent RT-qPCRs were performed to analyze the gene expression of several genes of interest. Results The bulk RNA sequencing data analysis revealed FABP4 as an overexpressed gene in GDM HUVECs compared to NG. Furthermore, the analysis of data through Gene Set Enrichment Analysis provided a list of different gene sets that are enriched in GDM samples. Among these gene sets are pathways or processes implicated in endothelial dysfunction, such as angiogenesis, PI3K/AKT/mTOR signaling, reactive oxygen species pathway, or inflammatory response. In vitro experiments provided evidence for an elevated FABP4 mRNA expression after VEGF treatment of HUVECs. Conversely, both simvastatin treatment and exposure to laminar flow reduced FABP4 mRNA expression and increased eNOS expression, suggesting a potential inhibitory effect of nitric oxide on FABP4. Conclusion We provided evidence that FABP4 could be involved in fetal GDM-induced endothelial dysfunction. Shear stress and statins might protect the endothelium against the negative impact of FABP4.

Circadian Rhythm Disruption in Hepatocellular Carcinoma Investigated by Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data.

Circadian rhythms are essential regulators of a multitude of physiological and behavioral processes, such as the metabolism and function of the liver. Circadian rhythms are crucial to liver homeostasis, as the liver is a key metabolic organ accountable for the systemic equilibrium of the body. Circadian rhythm disruption alone is sufficient to cause liver cancer through the maintenance of hepatic metabolic disorder. Although there is evidence linking CRD to hepatocarcinogenesis, the precise cellular and molecular mechanisms that underlie the circadian crosstalk that leads to hepatocellular carcinoma remain unknown. The expression of CRD-related genes in HCC was investigated in this study via bulk RNA transcriptomic analysis and single-cell sequencing. Dysregulated CRD-related genes are predominantly found in hepatocytes and fibroblasts, according to the findings. By using a combination of single-cell RNA sequencing and bulk RNA sequencing analyses, the dysregulated CRD-related genes ADAMTS13, BIRC5, IGFBP3, MARCO, MT2A, NNMT, and PGLYRP2 were identified. The survival analysis using the Kaplan-Meier method revealed a significant correlation between the expression levels of BIRC5 and IGFBP3 and the survival of patients diagnosed with HCC.

CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data.

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations, especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservations. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations, and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks, and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice, zebrafish, and chick, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify conserved cell types even in evolutionarily distant species. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature for identifying conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations, and intercellular interactions, providing insights into the cellular and molecular mechanisms of species evolution.

Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing.

This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on RNA sequencing (RNAseq) data analysis in an interactive format that uses appropriate cloud resources for data access and analyses. Biomedical research is increasingly data-driven, and dependent upon data management and analysis methods that facilitate rigorous, robust, and reproducible research. Cloud-based computing resources provide opportunities to broaden the application of bioinformatics and data science in research. Two obstacles for researchers, particularly those at small institutions, are: (i) access to bioinformatics analysis environments tailored to their research; and (ii) training in how to use Cloud-based computing resources. We developed five reusable tutorials for bulk RNAseq data analysis to address these obstacles. Using Jupyter notebooks run on the Google Cloud Platform, the tutorials guide the user through a workflow featuring an RNAseq dataset from a study of prophage altered drug resistance in Mycobacterium chelonae. The first tutorial uses a subset of the data so users can learn analysis steps rapidly, and the second uses the entire dataset. Next, a tutorial demonstrates how to analyze the read count data to generate lists of differentially expressed genes using R/DESeq2. Additional tutorials generate read counts using the Snakemake workflow manager and Nextflow with Google Batch. All tutorials are open-source and can be used as templates for other analysis.

Analyzing RNA-Seq Data from Chlamydia with Super Broad Transcriptomic Activation: Challenges, Solutions, and Implications for Other Systems.

RNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression. Standard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends. By incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection. While the strategies employed are developed in the context of Chlamydia, the principles of flexible and context-aware normalization may inform adjustments in other systems with unbalanced gene expression dynamics, such as bacterial spore germination. The code for reproducing the presented bioinformatic analysis is available at https://zenodo.org/records/11201379.

Inhibition of miR-199b-5p reduces pathological alterations in osteoarthritis by potentially targeting Fzd6 and Gcnt2

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p. Thus, these results indicated that MiR-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Inhibition of miR-199b-5p reduces pathological alterations in osteoarthritis by potentially targeting Fzd6 and Gcnt2.

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p. Thus, these results indicated that MiR-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a myeloid cell-related regulon predicting neoadjuvant immunotherapy response across cancers

BackgroundImmunotherapy has brought about a paradigm shift in the treatment of cancer. However, the majority of patients exhibit resistance or become refractory to immunotherapy, and the underlying mechanisms remain to be explored.MethodsSing-cell RNA sequencing (scRNA‑seq) datasets derived from 1 pretreatment and 1 posttreatment achieving pathological complete response (pCR) patient with lung adenocarcinoma (LUAD) who received neoadjuvant immunotherapy were collected, and pySCENIC was used to find the gene regulatory network (GRN) between cell types and immune checkpoint inhibitor (ICI) response. A regulon predicting ICI response was identified and validated using large‑scale pan-cancer data, including a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 5 ICI transcriptomic cohorts. Symphony reference mapping was performed to construct the myeloid cell map.ResultsThirteen major cluster cell types were identified by comparing pretreatment and posttreatment patients, and the fraction of myeloid cells was higher in the posttreatment group (19.0% vs. 11.8%). A PPARG regulon (containing 23 target genes) was associated with ICI response, and its function was validated by a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, TCGA pan-cancer cohort, and 5 ICI transcriptomic cohorts. Additionally, a myeloid cell map was developed, and cluster I, II, and III myeloid cells with high expression of PPARG were identified. Moreover, we constructed a website called PPARG (https://pparg.online/PPARG/ or http://43.134.20.130:3838/PPARG/), which provides a powerful discovery tool and resource value for researchers.ConclusionsThe PPARG regulon is a predictor of ICI response. The myeloid cell map enables the identification of PPARG subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Genome-wide investigation of lncRNAs revealed their tight association with gastric cancer

BackgroundGastric cancer (GC) is a significant health issue globally, ranking as the fifth most common cancer with over 10,000 new cases reported annually. Long non-coding RNA (lncRNA) has emerged as a critical player in cellular functions, influencing GC's development, growth, metastasis, and prognosis. However, our understanding of lncRNA's role in the pathogenesis of GC remains limited. Therefore, it is particularly important to explore the relationship between lncRNA and gastric cancer.Methodswe conducted a comprehensive analysis of RNA sequencing data from the GEO database and stomach adenocarcinoma (STAD) data from the TCGA database to identify lncRNAs that exhibit altered expression levels in GC and the mechanisms underlying lncRNA-mediated transcription and post-transcriptional regulation were explored.ResultsThis study uncovered 94 lncRNAs with differential expression and, through co-expression analysis, linked these to 1508 differentially expressed genes (DEGs). GO functional enrichment analysis highlighted that these DEGs are involved in critical pathways, such as cell adhesion and the positive regulation of cell migration. By establishing a lncRNA-miRNA-mRNA regulatory network, we found that the ceRNA mechanism, particularly involving RP11-357H14.17 and CTD-2377D24.4, could play a role in GC progression. Experimental validation of selected differentially expressed lncRNAs and mRNAs (including RP11-357H14.17-CLDN1, BBOX1, TRPM2-AS, CLDN1, PLAU, HOXB7) confirmed the RNA-seq results.ConclusionsOverall, our findings highlight the critical role of the lncRNA-mRNA regulatory network in the development and progression of GC, offering potential biomarkers for diagnosis and targets for innovative treatment strategies.

Pro-resolving lipid mediator reduces amyloid-β42-induced gene expression in human monocyte-derived microglia.

JOURNAL/nrgr/04.03/01300535-202503000-00031/figure1/v/2024-06-17T092413Z/r/image-tiff Specialized pro-resolving lipid mediators including maresin 1 mediate resolution but the levels of these are reduced in Alzheimer's disease brain, suggesting that they constitute a novel target for the treatment of Alzheimer's disease to prevent/stop inflammation and combat disease pathology. Therefore, it is important to clarify whether they counteract the expression of genes and proteins induced by amyloid-β. With this objective, we analyzed the relevance of human monocyte-derived microglia for in vitro modeling of neuroinflammation and its resolution in the context of Alzheimer's disease and investigated the pro-resolving bioactivity of maresin 1 on amyloid-β42-induced Alzheimer's disease-like inflammation. Analysis of RNA-sequencing data and secreted proteins in supernatants from the monocyte-derived microglia showed that the monocyte-derived microglia resembled Alzheimer's disease-like neuroinflammation in human brain microglia after incubation with amyloid-β42. Maresin 1 restored homeostasis by down-regulating inflammatory pathway related gene expression induced by amyloid-β42 in monocyte-derived microglia, protection of maresin 1 against the effects of amyloid-β42 is mediated by a re-balancing of inflammatory transcriptional networks in which modulation of gene transcription in the nuclear factor-kappa B pathway plays a major part. We pinpointed molecular targets that are associated with both neuroinflammation in Alzheimer's disease and therapeutic targets by maresin 1. In conclusion, monocyte-derived microglia represent a relevant in vitro microglial model for studies on Alzheimer's disease-like inflammation and drug response for individual patients. Maresin 1 ameliorates amyloid-β42-induced changes in several genes of importance in Alzheimer's disease, highlighting its potential as a therapeutic target for Alzheimer's disease.

Long non-coding RNA RP11-197K6.1 as ceRNA promotes colorectal cancer progression via miR-135a-5p/DLX5 axis

BackgroundColorectal cancer (CRC) remains a major global health challenge, with high incidence and mortality rates. The role of long noncoding RNAs (lncRNAs) in cancer progression has received considerable attention. The present study aimed to investigate the function and mechanisms underlying the role of lncRNA RP11-197K6.1, microRNA-135a-5p (hsa-miR-135a-5p), and DLX5 in CRC development.MethodsWe analyzed RNA sequencing data from The Cancer Genome Atlas Colorectal Cancer dataset to identify the association between lncRNA RP11-197K6.1 and CRC progression. The expression levels of lncRNA RP11-197K6.1 and DLX5 in CRC samples and cell lines were determined by real-time quantitative PCR and western blotting assays. Fluorescence in situ hybridization was used to confirm the cellular localization of lncRNA RP11-197K6.1. Cell migration capabilities were assessed by Transwell and wound healing assays, and flow cytometry was performed to analyze apoptosis. The interaction between lncRNA RP11-197K6.1 and miR-135a-5p and its effect on DLX5 expression were investigated by the dual-luciferase reporter assay. Additionally, a xenograft mouse model was used to study the in vivo effects of lncRNA RP11-197K6.1 on tumor growth, and an immunohistochemical assay was performed to assess DLX5 expression in tumor tissues.ResultslncRNA RP11-197K6.1 was significantly upregulated in CRC tissues and cell lines as compared to that in normal tissues, and its expression was inversely correlated with patient survival. It promoted the migration and metastasis of CRC cells by interacting with miR-135a-5p, alleviated suppression of DLX5 expression, and facilitated tumor growth.ConclusionThis study demonstrated the regulatory network and mechanism of action of the lncRNA RP11-197K6.1/miR-135a-5p/DLX5 axis in CRC development. These findings provided insights into the molecular pathology of CRC and suggested potential therapeutic targets for more effective treatment of patients with CRC.

METTL3 Modulates Ctsk+ Lineage Supporting Cranial Osteogenesis via Hedgehog

N6-methyladenosine (m6A) modification, a eukaryotic messenger RNA modification catalyzed by methyltransferase-like 3 (METTL3), plays a pivotal role in stem cell fate determination. Calvarial bone development and maintenance are orchestrated by the cranial sutures. Cathepsin K (CTSK)–positive calvarial stem cells (CSCs) contribute to mice calvarial ossification. However, the role of m6A modification in regulating Ctsk+ lineage cells during calvarial development remains elusive. Here, we showed that METTL3 was colocalized with cranial nonosteoclastic Ctsk+ lineage cells, which were also associated with GLI1 expression. During neonatal development, depletion of Mettl3 in the Ctsk+ lineage cells delayed suture formation and decreased mineralization. During adulthood maintenance, loss of Mettl3 in the Ctsk+ lineage cells impaired calvarial bone formation, which was featured by the increased bone porosity, enhanced bone marrow cavity, and decreased number of osteocytes with the less-developed cellular outline. The analysis of methylated RNA immunoprecipitation sequencing and RNA sequencing data indicated that loss of METTL3 reduced Hedgehog (Hh) signaling pathway. Restoration of Hh signaling pathway by crossing Sufufl/+ alleles or by local administration of SAG21 partially rescued the abnormity. Our data indicate that METTL3 modulates Ctsk+ lineage cells supporting calvarial bone formation by regulating the Hh signaling pathway, providing new insights for clinical treatment of skull vault osseous diseases.

Exercise rejuvenates microglia and reverses T cell accumulation in the aged female mouse brain.

Slowing and/or reversing brain ageing may alleviate cognitive impairments. Previous studies have found that exercise may mitigate cognitive decline, but the mechanisms underlying this remain largely unclear. Here we provide unbiased analyses of single-cell RNA sequencing data, showing the impacts of exercise and ageing on specific cell types in the mouse hippocampus. We demonstrate that exercise has a profound and selective effect on aged microglia, reverting their gene expression signature to that of young microglia. Pharmacologic depletion of microglia further demonstrated that these cells are required for the stimulatory effects of exercise on hippocampal neurogenesis but not cognition. Strikingly, allowing 18-month-old mice access to a running wheel did by and large also prevent and/or revert T cell presence in the ageing hippocampus. Taken together, our data highlight the profound impact of exercise in rejuvenating aged microglia, associated pro-neurogenic effects and on peripheral immune cell presence in the ageing female mouse brain.

Augmentation of hepatocellular carcinoma malignancy by annexin A5 through modulation of invasion and angiogenesis

ABSTRUCT Background Hepatocellular carcinoma (HCC) continues to play a substantial role in cancer-related morbidity and mortality, largely owing to its pronounced tumor heterogeneity and propensity for recurrence. This underscores the pressing need for in-depth examination of its highly malignant mechanisms. Annexin A5 (ANXA5), recognized as a hallmark tumor protein, has emerged as a focal point of interest because of its ambiguous function and mechanism in HCC prognosis. This study aimed to provide a comprehensive understanding of the role of ANXA5 in the malignant progression of human HCC cells by employing an integrative approach that combines conventional experimental methods with RNA sequencing. Methods Differences in ANXA5 expression between HCC tissues and corresponding nontumor tissues were evaluated using immunofluorescence (n = 25). Correlation analysis was subsequently performed to assess the association between ANXA5 expression and clinicopathological features (n = 65). The role of ANXA5 in human HCC cell lines with ANXA5 gene knockout and overexpression was explored in vitro using migration and invasion assays and Ki-67 indices and in vivo based on node mice xenograft model. A tube formation assay using human umbilical vein endothelial cells (HUVECs) was conducted to demonstrate the angiogenic effects of ANXA5 in HCC. Single-cell and bulk RNA sequencing was used to further investigate the underlying mechanisms involved. Results This study revealed that ANXA5 is highly expressed in patients with HCC and correlates with poor prognosis. Assays for migration, invasion, and proliferation based on ANXA5 gene knockout and overexpression systems in human HCC cell lines have demonstrated that ANXA5 enhances HCC malignancy in vitro and in vivo. Tube formation assays of HUVECs indicated that ANXA5 facilitates angiogenesis and recruits endothelial cells to HCC cells. Single-cell and bulk RNA sequencing data analysis further confirmed that ANXA5 expression in HCC is associated with hepatocyte metabolism, immune response activation, and various oncogenic signaling pathways. Conclusions This study revealed a meaningful association between elevated ANXA5 expression in tumor tissues and an unfavorable prognosis in patients with HCC. In addition, ANXA5 promotes HCC malignancy by promoting invasion and angiogenesis. Thus, ANXA5 has emerged as a promising therapeutic target for HCC and has the potential to improve patient outcomes.

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

BackgroundCharacterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell–cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.MethodsCCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.ResultsA shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64–10.25]) and ovarian cancer in UKBB (5.53[2.08–8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97–2.96]) compared to females (1.84[1.44–2.37]).ConclusionWe identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

LINC01002 functions as a ceRNA to regulate FRMD8 by sponging miR-4324 for the development of COVID-19

BackgroundSyndrome coronavirus-2 (SARS-CoV-2) has developed various strategies to evade the antiviral impact of type I IFN. Non-structural proteins and auxiliary proteins have been extensively researched on their role in immune escape. Nevertheless, the detailed mechanisms of structural protein-induced immune evasion have not been well elucidated.MethodsHuman alveolar basal epithelial carcinoma cell line (A549) was stimulated with polyinosinic-polycytidylic acid (PIC) and independently transfected with four structural proteins expression plasmids, including nucleocapsid (N), spike (S), membrane (M) and envelope (E) proteins. By RT-qPCR and ELISA, the structural protein with the most pronounced inhibitory effects on IFN-β induction was screened. RNA-sequencing (RNA-Seq) and two differential analysis strategies were used to obtain differentially expressed genes associated with N protein inhibition of IFN-β induction. Based on DIANA-LncBase and StarBase databases, the interactive competitive endogenous RNA (ceRNA) network for N protein-associated genes was constructed. By combining single-cell sequencing data (GSE158055), lncRNA-miRNA-mRNA axis was further determined. Finally, RT-qPCR was utilized to illustrate the regulatory functions among components of the ceRNA axis.ResultsSARS-CoV-2 N protein inhibited IFN-β induction in human alveolar epithelial cells most significantly compared with other structural proteins. RNA-Seq data analysis revealed genes related to N protein inhibiting IFNs induction. The obtained 858 differentially expressed genes formed the reliable ceRNA network. The function of LINC01002-miR-4324-FRMD8 axis in the IFN-dominated immune evasion was further demonstrated through integrating single-cell sequencing data. Moreover, we validated that N protein could reverse the effect of PIC on LINC01002, FRMD8 and miR-4324 expression, and subsequently on IFN-β expression level. And LINC01002 could regulate the production of FRMD8 by inhibiting miR-4324.ConclusionSARS-CoV-2 N protein suppressed the induction of IFN-β by regulating LINC01002 which was as a ceRNA, sponging miR-4324 and participating in the regulation of FRMD8 mRNA. Our discovery provides new insights into early intervention therapy and drug development on SARS-CoV-2 infection.

Hepatitis B-related hepatocellular carcinoma: classification and prognostic model based on programmed cell death genes.

Hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma (HCC). Programmed cell death (PCD) is a critical process in suppressing tumor growth, and alterations in PCD-related genes may contribute to the progression of HBV-HCC. This study aims to develop a prognostic model that incorporates genomic and clinical information based on PCD-related genes, providing novel insights into the molecular heterogeneity of HBV-HCC through bioinformatics analysis and experimental validation. In this study, we analyzed 139 HBV-HCC samples from The Cancer Genome Atlas (TCGA) and validated them with 30 samples from the Gene Expression Omnibus (GEO) database. Various bioinformatics tools, including differential expression analysis, gene set variation analysis, and machine learning algorithms were used for comprehensive analysis of RNA sequencing data from HBV-HCC patients. Furthermore, among the PCD-related genes, we ultimately chose DLAT for further research on tissue chips and patient cohorts. Besides, immunohistochemistry, qRT-PCR and Western blot analysis were conducted. The cluster analysis identified three distinct subgroups of HBV-HCC patients. Among them, Cluster 2 demonstrated significant activation in DNA replication-related pathways and tumor-related processes. Analysis of copy number variations (CNVs) of PCD-related genes also revealed distinct patterns in the three subgroups, which may be associated with differences in pathway activation and survival outcomes. DLAT in tumor tissues of HBV-HCC patients is upregulated. Based on the PCD-related genes, we developed a prognostic model that incorporates genomic and clinical information and provided novel insights into the molecular heterogeneity of HBV-HCC. In our study, we emphasized the significance of PCD-related genes, particularly DLAT, which was examined in vitro to explore its potential clinical implications.

CASi: A framework for cross-timepoint analysis of single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) technology has been widely used to study the differences in gene expression at the single cell level, providing insights into the research of cell development, differentiation, and functional heterogeneity. Various pipelines and workflows of scRNA-seq analysis have been developed but few considered multi-timepoint data specifically. In this study, we develop CASi, a comprehensive framework for analyzing multiple timepoints’ scRNA-seq data, which provides users with: (1) cross-timepoint cell annotation, (2) detection of potentially novel cell types emerged over time, (3) visualization of cell population evolution, and (4) identification of temporal differentially expressed genes (tDEGs). Through comprehensive simulation studies and applications to a real multi-timepoint single cell dataset, we demonstrate the robust and favorable performance of the proposal versus existing methods serving similar purposes.