Screening and analysis of RNAs associated with activated memory CD4 and CD8 T cells in liver cancer

Integrative Analyses of Bulk and Single-Cell RNA Seq Identified the Shared Genes in Acute Respiratory Distress Syndrome and Rheumatoid Arthritis

Acute respiratory distress syndrome (ARDS), a progressive status of acute lung injury (ALI), is primarily caused by an immune-mediated inflammatory disorder, which can be an acute pulmonary complication of rheumatoid arthritis (RA). As a chronic inflammatory disease regulated by the immune system, RA is closely associated with the occurrence and progression of respiratory diseases. However, it remains elusive whether there are shared genes between the molecular mechanisms underlying RA and ARDS. The objective of this study is to identify potential shared genes for further clinical drug discovery through integrated analysis of bulk RNA sequencing datasets obtained from the Gene Expression Omnibus database, employing differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA). The hub genes were identified through the intersection of common DEGs and WGCNA-derived genes. The Random Forest (RF) and least absolute shrinkage and selection operator (LASSO) algorithms were subsequently employed to identify key shared target genes associated with two diseases. Additionally, RA immune infiltration analysis and COVID-19 single-cell transcriptome analysis revealed the correlation between these key genes and immune cells. A total of 59 shared genes were identified from the intersection of DEGs and gene clusters obtained through WGCNA, which analyzed the integrated gene matrix of ALI/ARDS and RA. The RF and LASSO algorithms were employed to screen for target genes specific to ALI/ARDS and RA, respectively. The final set of overlapping genes (FCMR, ADAM28, HK3, GRB10, UBE2J1, HPSE, DDX24, BATF, and CST7) all exhibited a strong predictive effect with an area under the curve (AUC) value greater than 0.8. Then, the immune infiltration analysis revealed a strong correlation between UBE2J1 and plasma cells in RA. Furthermore, scRNA-seq analysis demonstrated differential expression of these nine target genes primarily in T cells and NK cells, with CST7 showing a significant positive correlation specifically with NK cells. Beyond that, transcriptome sequencing was conducted on lung tissue collected from ALI mice, confirming the substantial differential expression of FCMR, HK3, UBE2J1, and BATF. This study provides unprecedented evidence linking the pathophysiological mechanisms of ALI/ARDS and RA to immune regulation, which offers novel understanding for future clinical treatment and experimental research.

Immune Gene Expression Profiling in Individuals with Turner Syndrome, Graves' Disease, and a Healthy Female by Single-Cell RNA Sequencing: A Comparative Study

Turner syndrome (TS) can be determined by karyotype analysis, marked by the loss of one X chromosome in females. However, the genes involved in autoimmunity in TS patients remain unclear. In this study, we aimed to analyze differences in immune gene expression between a patient with TS, a healthy female, and a female patient with Graves' disease using single-cell RNA sequencing (scRNA-seq) analysis of antigen-specific CD4(+) T cells. We identified 43 differentially expressed genes in the TS patient compared with the healthy female and the female patient with Graves' disease. Many of these genes have previously been suggested to play a role in immune system regulation. This study provides valuable insights into the differences in immune-related gene expression between TS patients, healthy individuals, and those with autoimmune diseases.

IL-21 and IL-33 May Be Effective Biomarkers to Predict the Efficacy of PD-1 Monoclonal Antibody for Advanced Cholangiocarcinoma

Background and Objective: Treatment options for patients with advanced biliary tract cancer (BTC) are limited. The programmed cell death protein-1 (PD-1) inhibitors may have synergistic effects with chemotherapy. Therefore, the aim of our study was to provide real-world data on treatment outcomes in BTC patients receiving chemotherapy alone versus a combination of chemotherapy and PD-1 inhibitors. Additionally, we explored potential markers predictive of PD-1 inhibitor efficacy in this combined therapy. Methods: We conducted a review of patients at Changzhou First People's Hospital who received PD-1 inhibitors in combination with chemotherapy or chemotherapy alone as first-line treatment for advanced BTC. The primary endpoints of the study were progression-free survival (PFS) and overall survival (OS). Kaplan-Meier survival curves and the log-rank test were used to analyze the data. Immunohistochemistry showed the expression of interleukin-21 (IL-21), interleukin-33 (IL-33), and Eomes in the tumor tissue of patients who received PD-1 inhibitors in combination with chemotherapy. Results: The study enrolled 61 patients receiving PD-1 inhibitors combined with chemotherapy and 65 receiving chemotherapy alone. The median OS and PFS for patients receiving PD-1 inhibitors in combination with chemotherapy were 11.7 and 6.7 months, respectively. These durations were significantly longer than those for chemotherapy alone: OS of 10.3 months (95% CI: 0.16-0.21, p = 0.031) and PFS of 5.3 months (95% Confidence interval (CI) 0.25-0.32, p = 0.018). High IL-21 expression or low IL-33 expression in tumor tissue correlated with better response rates to chemotherapy combined with PD-1 inhibitors. Conclusions: Combining PD-1 inhibitors with chemotherapy shows good antitumor activity, making it an effective way to treat BTC. The expression profiles of IL-21 and IL-33 hold promise as potential markers for guiding the chemotherapy combined with immunotherapy in BTC patients.

Unraveling the interplay of CD8 + T cells and microRNA signaling in cancer: implications for immune dysfunction and therapeutic approaches

MicroRNAs (miRNAs) emerge as critical regulators of CD8 + T cell function within the complex tumor microenvironment (TME). This review explores the multifaceted interplay between miRNAs and CD8 + T cells across various cancers. We discuss how specific miRNAs influence CD8 + T cell activation, recruitment, infiltration, and effector function. Dysregulation of these miRNAs can contribute to CD8 + T cell exhaustion and immune evasion, hindering anti-tumor immunity. Conversely, manipulating miRNA expression holds promise for enhancing CD8 + T cell activity and improving cancer immunotherapy outcomes. We delve into the role of miRNAs in CD8 + T-cell function across different cancer types, including gliomas, gastric and colon cancer, oral squamous cell carcinoma, thyroid carcinoma, lymphomas, melanoma, breast cancer, renal cell carcinoma, ovarian cancer, uterine corpus endometrial cancer, bladder cancer, acute myeloid leukemia, chronic myelogenous leukemia, and osteosarcoma. Additionally, we explore how extracellular vesicles and cytokines modulate CD8 + T-cell function through complex interactions with miRNAs. Finally, we discuss the potential impact of radiotherapy and specific drugs on miRNA expression and CD8 + T-cell activity within the TME. This review highlights the immense potential of targeting miRNAs to manipulate CD8 + T-cell activity for the development of novel and improved cancer immunotherapies.

Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics

AIM

In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics.

METHODS

Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. Subsequently, the cases were randomly divided into a training cohort of 165 cases and a validation cohort of 69 cases. Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves. Additionally, the correlation between the Pathomics score (PS) and immune genes was examined.

RESULTS

In the multivariate analysis, heightened infiltration of activated CD4 memory T cells was strongly associated with improved overall survival (HR = 0.505, 95 % CI = 0.342-0.745, P < 0.001). The pathomic model, exhibiting robust predictive capability, demonstrated impressive AUC values of 0.844 and 0.750 in both study cohorts. The Decision Curve Analysis (DCA) unequivocally underscored the model's exceptional clinical utility. In a subsequent multivariate analysis, heightened infiltration of the PS also emerged as a significant protective factor for overall survival (HR = 0.506, 95 % CI = 0.329-0.777, P = 0.002).

CONCLUSION

The pathomic model based on H&E slides for predicting the infiltration degree of activated CD4 memory T cells, along with integrated bioinformatics analysis elucidating potential molecular mechanisms, offers novel prognostic indicators for the precise stratification and individualized prognosis of gastric cancer patients.

Effects of sinomenine on a rat orthotopic liver carcinoma model

OBJECTIVE

Liver carcinoma is a common malignant tumor. In this study, an orthotopic liver carcinoma model was established by B-ultrasound, and the therapeutic effect of sinomenine (Sin) on the disease was investigated.

METHODS

SD rats were randomly divided into control, Sin, Sorafenib (Sor), and combination (Sin+Sor) groups (n=8). An orthotopic liver carcinoma model was established by inoculating N1-S1 cells into the rat liver by B-ultrasound-guided, and tumor volume was monitored three times by B-ultrasound after inoculation. After drug treatment, the tumor tissues were stained with HE and TUNEL, and the levels of inflammatory cytokines, ALT and AST were detected by ELISA. The numbers of erythrocytes, leukocytes and platelets were detected. Immunohistochemistry and immunofluorescence were used to detect the expression of Ki-67, CD44, VEGF and CD31. The levels of cell cycle, apoptosis-related proteins were detected by western blot.

RESULTS

B-ultrasound monitoring found that Sin reduced tumor volume. Moreover, Sin improved tissue lesions, and promoted cancer cell apoptosis. Sin decreased the levels of inflammatory cytokines, AST and ALT, and decreased the numbers of erythrocytes, leukocytes and platelets. Simultaneously, the expressions of Ki-67, CD44, VEGF and CD31 were decreased in the Sin group. Furthermore, Sin decreased the Bcl-2, Cyclin D1, CDK4, CDK6 and Survivin levels, but increased Bax, Cleaved-caspase3/pro-caspase3, P21 and P27 levels. More importantly, the combination of Sin and Sor treatment was more effective than treatment alone.

CONCLUSION

A rat orthotopic liver carcinoma model was established under the guidance of B-ultrasound, and Sin had a therapeutic effect on orthotopic liver carcinoma.

DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection

BACKGROUND

Single-cell sequencing provides detailed insights into biological processes including cell differentiation and identity. While providing deep cell-specific information, the method suffers from technical constraints, most notably a limited number of expressed genes per cell, which leads to suboptimal clustering and cell type identification.

RESULTS

Here, we present DISCERN, a novel deep generative network that precisely reconstructs missing single-cell gene expression using a reference dataset. DISCERN outperforms competing algorithms in expression inference resulting in greatly improved cell clustering, cell type and activity detection, and insights into the cellular regulation of disease. We show that DISCERN is robust against differences between batches and is able to keep biological differences between batches, which is a common problem for imputation and batch correction algorithms. We use DISCERN to detect two unseen COVID-19-associated T cell types, cytotoxic CD4+ and CD8+ Tc2 T helper cells, with a potential role in adverse disease outcome. We utilize T cell fraction information of patient blood to classify mild or severe COVID-19 with an AUROC of 80% that can serve as a biomarker of disease stage. DISCERN can be easily integrated into existing single-cell sequencing workflow.

CONCLUSIONS

Thus, DISCERN is a flexible tool for reconstructing missing single-cell gene expression using a reference dataset and can easily be applied to a variety of data sets yielding novel insights, e.g., into disease mechanisms.

Cervical cancer immune infiltration microenvironment identification, construction of immune scores, assisting patient prognosis and immunotherapy

Background

The immune microenvironment is of great significance in cervical cancer. However, there is still a lack of systematic research on the immune infiltration environment of cervical cancer.

Methods

We obtained cervical cancer transcriptome data and clinical information from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, evaluated the immune microenvironment of cervical cancer, determined immune subsets, constructed an immune cell infiltration scoring system, screened key immune-related genes, and performed single-cell data analysis and cell function analysis of key genes.

Results

We combined the TCGA and GEO data sets and obtained three different immune cell populations. We obtained two gene clusters, extracted 119 differential genes, and established an immune cell infiltration (ICI) scoring system. Finally, three key genes, IL1B, CST7, and ITGA5, were identified, and single-cell sequencing data were mined to distribute these key genes in different cell types. By up-regulating CST7 and down-regulating IL1B and ITGA5, cervical cancer cells’ proliferation ability and invasion ability were successfully reduced.

Conclusion

We conducted a comprehensive assessment of the state of the tumor immune microenvironment in cervical cancer, constructed the ICI scoring system, and identified the ICI scoring system as a potential indicator of susceptibility to immunotherapy for cervical cancer, identifying key genes suggesting that IL1B, CST7, and ITGA5 play an essential role in cervical cancer.

Genome-wide identification of alternative splicing and splicing regulated in immune infiltration in osteosarcoma patients

Background: Osteosarcoma typically occurs in adolescents, and the survival rate of patients with metastatic and recurrent osteosarcoma remains low. Abnormal regulation of alternative splicing is associated with the development of osteosarcoma. However, there is no genome-wide analysis of the function and regulatory mechanisms of aberrant alternative splicing associated with osteosarcoma. Methods: Published transcriptome data on osteosarcoma (GSE126209) derived from osteosarcoma patient tissue were downloaded. Gene expression profiling by high-throughput sequencing was performed on 9 normal samples and 10 tumor samples for genome-wide identification of osteosarcoma-related alternative splicing events. The potential function of osteosarcoma-associated alternative splicing events was examined by immune infiltration and correlation analysis. Regulation of aberrantly expressed RNA-binding proteins (RBPs) related to alternative splicing in osteosarcoma was clarified by co-expression analysis. Results: A total of 63 alternative splicing events, which are highly credible and dominant, were identified. GO enrichment analysis indicated that alternative splicing may be closely related to the immune response process. Immune infiltration analysis showed significant changes in the percentages of CD8 T cells, resting memory CD4 T cells, activated memory CD4 T cells, monocytes, resting dendritic cells, and activated mast cells in tumors compared to normal tissues, indicating the involvement of these immune cell types in the occurrence of osteosarcoma. Moreover, the analysis identified alternative splicing events that were co-altered with resting memory CD4 T cells, resting dendritic cells, and activated mast cells, events that may be associated with regulation of the osteosarcoma immune microenvironment. In addition, a co-regulatory network (RBP-RAS-immune) of osteosarcoma-associated RBPs with aberrant alternative splicing and altered immune cells was established. These RBPs include NOP58, FAM120C, DYNC1H1, TRAP1, and LMNA, which may serve as molecular targets for osteosarcoma immune regulation. Conclusion: These findings allow us to further understand the causes of osteosarcoma development and provide a new research direction for osteosarcoma immunotherapy or targeted therapy.

Regulation of CD4 T Cell Responses by the Transcription Factor Eomesodermin

Central to the impacts of CD4 T cells, both positive in settings of infectious disease and cancer and negative in the settings of autoimmunity and allergy, is their ability to differentiate into distinct effector subsets with specialized functions. The programming required to support such responses is largely dictated by lineage-specifying transcription factors, often called ‘master regulators’. However, it is increasingly clear that many aspects of CD4 T cell immunobiology that can determine the outcomes of disease states involve a broader transcriptional network. Eomesodermin (Eomes) is emerging as an important member of this class of transcription factors. While best studied in CD8 T cells and NK cells, an increasing body of work has focused on impacts of Eomes expression in CD4 T cell responses in an array of different settings. Here, we focus on the varied impacts reported in these studies that, together, indicate the potential of targeting Eomes expression in CD4 T cells as a strategy to improve a variety of clinical outcomes.

Construction and experimental verification of user-friendly molecular subtypes mediated by immune-associated genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) accounts for third most cancer death globally, and its prognosis continues to be poor even with many novel therapeutic approaches emerging. The advent of immunotherapy seems to offer new hope, but low response rates are an unresolved problem. To gain further knoeledge of the effect of immune-related genes in HCC, we examined the connection between immune-related genes and the immune microenvironment in HCC through the HCC transcriptome dataset. The study also aimed to construct and experimentally validate user-friendly molecular subtypes mediated by immune-related genes in HCC. The immune cell infiltration patterns differs in HCC adjacent non-disease tissues and cancerous tissues. Patients with HCC could be classified into 2 subtypes: subtype A and subtype B. Specifically, subtype A shows characteristics of a hot tumor, in which the infiltration of cells exhibiting antigens and the expression of other crucial factors associated with immune function are higher than in a cold tumor. In addition, we identified Hub genes for the different subtypes and constructed a prognostic prediction model based on six genes (KLRB1, KLF2, S100A9, MSC, ANXA5, and IMPDH1). Further experimental analysis of HCC samples exhibited that the expression levels of KLF2 and ANXA5 were associated with immune cell infiltration and expression of PD-L1 in cancer tissues. Our work suggests that the expression of immune-related genes has crucial effect on the tumor microenvironment and prognosis of HCC patients and may be associated with immunotherapeutic response, which provides new clues for the widespread and effective application of immunotherapy in HCC.

Positive regulation of ataxia-telangiectasia-mutated protein (ATM) by E2F transcription Factor 1 (E2F-1) in cisplatin-resistant nasopharyngeal carcinoma cells

Objective

To explore the mechanism of E2F transcription Factor 1 (E2F-1)-mediated ataxia-telangiectasia-mutated protein (ATM) in cisplatin (DDP)-resistant nasopharyngeal carcinoma (NPC).

Methods

E2F-1 and ATM expression was assessed in DDP-resistant NPC cell lines (CNE2/DDP and HNE1/DDP) and parental cells. Then, DDP-resistant NPC cells were transfected with control shRNA (short hairpin RNA) or E2F-1 shRNAs with or without ATM lentiviral activation particles. The half maximal inhibitory concentration (IC50) was evaluated by 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay, and the cell cycle and cell proliferation were measured by flow cytometry and EdU staining, respectively. In addition, the expression of genes and proteins was quantified by quantitative reverse-transcription polymerase chain reaction (qRT–PCR) and western blotting, respectively.

Results

Both E2F-1 and ATM expression in DDP-resistant NPC cells was much higher than that in parental cells. E2F-1 shRNA reduced ATM expression in DDP-resistant NPC cells, but ATM overexpression had no significant effect on E2F-1. ATM overexpression enhanced DDP resistance in DDP-resistant NPC cells with increased IC50 values, which was reversed by E2F-1 inhibition. Meanwhile, ATM overexpression resulted in upregulation of ABCA2 and ABCA5 in DDP-resistant NPC cells, induced elevations in the transition of the cells into S-phase, and increased cell proliferation with enhanced expression of cyclin E1, CDK2, and Ki67, which was reversed by E2F-1 shRNAs.

Conclusion

Downregulation of E2F-1, possibly by regulating ATM, could block the cell cycle in the G1 phase and reduce the proliferation of CNE2/DDP cells, thereby reversing the resistance of human NPC cells to DDP.

Integrated analysis of ceRNA network reveals potential prognostic Hint1-related lncRNAs involved in hepatocellular carcinoma progression

BACKGROUND

Hint1 is a novel tumor suppressor gene, and inactivation of its expression is closely associated with the carcinogenesis of a variety of malignancies. The effects of Hint1 deficiency on the competing endogenous RNA (ceRNA) regulatory network in the context of HCC remains to be fully characterized. This study aims to explore Hint1-related hub lncRNAs in HCC and to establish a reliable prognostic model for HCC patients based on these hub lncRNAs.

METHODS

lncRNA + mRNA microarray was used to identify differentially expressed (DE) lncRNAs and mRNAs in Huh7 cells before and after Hint1 knockdown. A Hint1-related ceRNA network was mapped by bioinformation technology. The DEmRNAs in the network were analyzed via GO and KEGG enrichment analyses. Hub DElncRNAs associated with HCC patient prognosis were then detected through univariate and multivariate Cox regression analyses and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, and nomograms. We also utilized Kaplan-Meier curves to validate the relationship between hub lncRNAs and the overall survival (OS) of HCC patients. Finally, A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was mapped.

RESULTS

We identified 417 differentially expressed DElncRNAs and 2096 DEmRNAs in Huh7 cells before and after Hint1 knockdown. Three hub DElncRNAs (LINC00324, SNHG3, and DIO3OS) in the Hint1-associated ceRNA network were screened out using univariate and multivariate Cox regression analyses. A hepatocellular carcinoma (HCC) prognostic risk-scoring model and nomogram were constructed using these three hub lncRNAs, and it was confirmed that the risk score of the model could be used as an independent predictor of HCC prognosis. A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was also mapped.

CONCLUSION

We constructed a reliable prognostic model for HCC patients based on three Hint1-related hub lncRNAs, and we believe these three hub lncRNAs may play critical roles in hepatocarcinogenesis, and progression.