Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer.

Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD patterns in colorectal cancer (CRC) remains unknown. In this study, we developed a multiple PCD index (MPCDI) based on 19 PCD patterns using two machine learning algorithms for risk stratification, prognostic prediction, construction of nomograms, immune cell infiltration analysis, and chemotherapeutic drug sensitivity analysis. As a result, in the TCGA-COAD, GSE17536, and GSE29621 cohorts, the MPCDI can effectively distinguished survival outcomes in CRC patients and served as an independent factor for CRC patients. We then explored the immune infiltration landscape in two groups using the nine algorithms and found more overall immune infiltration in the high-MPCDI group. TIDE scores suggested that the increased immune evasion potential and immune checkpoint inhibition therapy may be less effective in the high-MPCDI group. Immunophenoscores indicated that anti-PD1, anti-cytotoxic T-lymphocyte associated antigen 4 (anti-CTLA4), and anti-PD1-CTLA4 combination therapies are less effective in the high-MPCDI group. In addition, the high-MPCDI group was more sensitive to AZD1332, Foretinib, and IGF1R_3801, and insensitive to AZD3759, AZD5438, AZD6482, Erlotinib, GSK591, IAP_5620, and Picolinici-acid, which suggests that the MPCDI can guide drug selection for CRC patients. As a new clinical classifier, the MPCDI can more accurately distinguish CRC patients who benefit from immunotherapy and develop personalized treatment strategies for CRC patients.

Single-cell RNA sequencing reveals the gene expression profile and cellular communication in human fetal heart development.

The heart is the central organ of the circulatory system, and its proper development is vital to maintain human life. As fetal heart development is complex and poorly understood, we use single-cell RNA sequencing to profile the gene expression landscapes of human fetal hearts from the four-time points: 8, 10, 11, 17 gestational weeks (GW8, GW10, GW11, GW17), and identified 11 major types of cells: erythroid cells, fibroblasts, heart endothelial cells, ventricular cardiomyocytes, atrial cardiomyocytes, macrophage, DCs, smooth muscle, pericytes, neural cells, schwann cells. In addition, we identified a series of differentially expressed genes and signaling pathways in each cell type between different gestational weeks. Notably, we found that ANNEXIN, MIF, PTN, GRN signalling pathways were simple and fewer intercellular connections in GW8, however, they were significantly more complex and had more intercellular communication in GW10, GW11, and GW17. Notably, the interaction strength of OSM signalling pathways was gradually decreased during this period of time (from GW8 to GW17). Together, in this study, we presented a comprehensive and clear description of the differentiation processes of all the main cell types in the human fetal hearts, which may provide information and reference data for heart regeneration and heart disease treatment.

Exploring the relationship between infectious agents and autoimmune diseases: a review.

The relationship between infectious agents and autoimmune diseases is a complex issue. In recent years, increasing clinical cases have indicated that infectious agents play an important role in the development of autoimmune diseases. Molecular mimicry is currently widely regarded as the primary pathogenic mechanism of various autoimmune diseases in humans. Components of infectious agents can undergo molecular mimicry with components in patients' bodies, leading to the development of various autoimmune diseases. In this article, we provide a brief overview of current research of the current research status on the relationship between infectious agents and autoimmune diseases, and describe our current understanding of their mechanisms of action in order to better understand the pathogenesis, diagnosis, and treatment of autoimmune diseases.

Multi­dimensional analysis reveals NCKAP5L is a promising biomarker for the diagnosis and prognosis of human cancers, especially colorectal cancer.

The Nck-associated protein 5-like (NCKAP5L) gene, also known as Cep169, is associated with certain cancers. However, the diagnosis and prognosis value of NCKAP5L in several types of human cancer, including colorectal cancer, is not fully understood. In the present study, a comprehensive pan-cancer analysis of NCKAP5L was performed using several approaches, including gene expression and alteration, protein phosphorylation, immune infiltration, survival prognosis analyses and gene enrichment using the following: The University of California Santa Cruz Genome Browser Human Dec. 2013 (GRCh38/hg38) Assembly, Tumor Immune Estimation Resource (version 2), Human Protein Atlas, Gene Expression Profiling Interactive Analysis (version 2), University of Alabama at Birmingham Cancer Data Analysis portal, the Kaplan-Meier Plotter, cBioportal, Search Tool for the Retrieval of Interacting Genes/Proteins, Jvenn and the Metascape server. The role of NCKAP5L in colorectal cancer was further assessed by reverse transcription-quantitative PCR. The results demonstrated that NCKAP5L was upregulated in the majority of cancer types, including colorectal cancer. The high expression of NCKAP5L was significantly correlated with patient survival prognosis and immune infiltration of cancer-associated fibroblasts in numerous types of cancer, including colorectal cancer. Furthermore, Gene Ontology analysis identified that NCKAP5L may serve an important role in metabolic and cellular processes in human cancers. In summary, the data from the present study demonstrate that NCKAP5L is a potential tumor biomarker for the diagnosis and prognosis of human cancers, especially colorectal cancer.

Single-cell transcriptional profiling reveals aberrant gene expression patterns and cell states in autoimmune diseases.

Multiple sclerosis(MS), primary Sjögren syndrome (pSS), and systemic lupus erythematosus (SLE) share numerous clinical symptoms and serological characteristics. We analyzed 153550 cells of scRNA-seq data of 17 treatment-naive patients (5 MS, 5 pSS, and 7 SLE) and 10 healthy controls, and we examined the enrichment of biological processes, differentially expressed genes (DEGs), immune cell types, and their subpopulations, and cell-cell communication in peripheral blood mononuclear cells (PBMCs). The percentage of B cells, megakaryocytes, monocytes, and proliferating T cells presented significant changes in autoimmune diseases. The enrichment of cell types based on gene expression revealed an elevated monocyte. MIF, MK, and GALECTIN signaling networks were obvious differences in autoimmune diseases. Taken together, our analysis provides a comprehensive map of the cell types and states of ADs patients at the single-cell level to understand better the pathogenesis and treatment of these ADs.

High-throughput sequencing reveals Jatrorrhizine inhibits colorectal cancer growth by ferroptosis-related genes.

BACKGROUND: Colorectal cancer is a malignant tumor that poses a serious threat to human health. The main objective of this study is to investigate the mechanism by which Jatrorrhizine (JAT), a root extract from Stephania Epigaea Lo, exerts its anticancer effects in colorectal cancer. METHODS: We initially assessed the inhibitory properties of JAT on SW480 cells using MTT and cell scratch assays. Flow cytometry was employed to detect cell apoptosis. Differentially expressed genes were identified through high-throughput sequencing, and they were subjected to functional enrichment and signaling pathway analysis and PPI network construction. RT-qPCR was used to evaluate gene expression and identify critical differentially expressed genes. Finally, the function and role of differentially expressed genes produced by JAT-treated SW480 cells in colorectal cancer will be further analyzed using the TCGA database. RESULTS: Our study demonstrated that JAT exhibits inhibitory effects on SW480 cells at concentrations of 12.5µM, 25µM, 50µM, and 75µM without inducing cell apoptosis. Through high-throughput sequencing, we identified 244 differentially expressed genes. KEGG and GO analysis of high-throughput sequencing results showed that differentially expressed genes were significantly enriched in MAPK, Wnt, and P53 signaling pathways. Notably, JAT significantly altered the expression of genes associated with ferroptosis. Subsequent RT-qPCR showed that the expression of ferroptosis genes SLC2A3 and ASNS was significantly lower in JAT-treated SW480 cells than in the control group. Analysis by TCGA data also showed that ferroptosis genes SLC2A3 and ASNS were significantly highly expressed in COAD. The prognosis of SLC2A3 was significantly worse in COAD compared to the normal group. SLC2A3 may be a core target of JAT for the treatment of COAD. CONCLUSIONS: JAT can inhibit COAD growth by ferroptosis-related genes. And it is a potential natural substance for the treatment of COAD.

The dynamic TRß/IGH CDR3 repertoire features in patients with liver transplantation.

OBJECTIVE: At present, little is known about the immune mechanism of liver transplantation caused by decompensated cirrhosis. Lymphocytes play an essential important role in the immune rejection of liver transplantation. In this study, we aimed to comprehensively analyze changes in complementary determinant 3 (CDR3) repertoire of T cell receptor ß chain (TRß) and immunoglobulin heavy chain (IGH) in liver transplantation patients and healthy controls (HC). METHODS: High-throughput sequencing technology was used to study the characteristics of TRß/IGH CDR3 repertoire, and identify the amino acid sequences of TRß and IGH associated with liver transplantation patients and HC. RESULTS: We found that some TRß and IGH CDR3 repertoire characteristics differed between liver transplant patients and HC. The diversity of TRß CDR3 increased in the liver transplantation group. First and seven days after live transplantation patients showed a lower degree of T cell clone amplification compared to the HC group. The CDR3 repertoire of the TRß/IGH chain was certainly biased in the use of some V, D, and J gene segments, TRß/IGH V-J combined frequency was also skewed and TRß CDR3 clonotypes were shared at a higher degree in the liver transplantation patients. Importantly, one amino acid sequence in the decompensated cirrhosis group was significantly higher than that in the healthy group. It should be noted that the frequency of some CDR3 sequences is closely correlated with the different stages of liver transplantation, and these sequences may play a key role in liver transplantation. CONCLUSION: Based on the above results, we can better understand the dynamic changes of TCß/IGH CDR3 repertoire in patients during liver transplantation.

Metabolomic and proteomic analyses of primary Sjogren's syndrome.

The pathogenesis of primary Sjogren's syndrome (pSS) has not been fully elucidated. We explored differentially expressed proteins and metabolic pathways in pSS using proteomics and metabolomics. 456 named proteins in total were identified, among which 50 were significantly changed in the pSS. Altered proteins were significantly associated with signaling pathways such as antigen processing and presentation, human immunodeficiency virus 1 infection, and FC gamma R-mediated phagocytosis. Meanwhile, 12 proteins, such as SH3BGRL3, TPM4, and CA1, can be used as potential clinical molecular markers. Moreover, 128 metabolites were significantly expressed in the pSS group. A total of 96 pathways were significantly enriched including central carbon metabolism in cancer, taurine and hypotaurine metabolism, and ABC transporters. Notably, both proteomics and metabolomics enriched glycolysis/gluconeogenesis metabolism, pentose phosphate pathway, and glutathione metabolism pathways. In this study, the progression mechanism of pSS was analyzed and novel biomarkers were identified by proteomics and metabolomics.

Research progress on the application of single-cell sequencing in autoimmune diseases.

Autoimmune diseases (AIDs) are caused by immune tolerance deficiency or abnormal immune regulation, leading to damage to host organs. The complicated pathogenesis and varied clinical symptoms of AIDs pose great challenges in diagnosing and monitoring this disease. Regrettably, the etiological factors and pathogenesis of AIDs are still not completely understood. It is noteworthy that the development of single-cell RNA sequencing (scRNA-seq) technology provides a new tool for analyzing the transcriptome of AIDs. In this essay, we have summarized the development of scRNA-seq technology, and made a relatively systematic review of the current research progress of scRNA-seq technology in the field of AIDs, providing a reference to preferably understand the pathogenesis, diagnosis, and treatment of AIDs.

Characterisation of T and B cell receptor repertoire in patients with systemic lupus erythematosus.

OBJECTIVES: Systemic lupus erythematosus (SLE) is an autoimmune disease with extreme heterogeneity, marked clinically by multi-systemic inflammatory involvement. However, the molecular mechanism of breakdown of self-tolerance is still unclear. T cell/B cell-mediated immune disorders may play a vital role in the pathogenesis of SLE. METHODS: In this context, we used a combination of multiplex-PCR, Illumina sequencing and IMGT/HighV-QUEST for a standardised analysis of the T cell receptor ß-chain (TCRß) and B cell receptor H-chain (BCR-H) repertoire of peripheral blood mononuclear cells in SLE patients compared with healthy volunteers. RESULTS: The results showed that there was an obvious reduction in BCR-H repertoire diversity and BCR-H CDR3 length in SLE patients. Notably, the pre-selection BCR-H CDR3s in SLE patients also displayed abnormal shortening, which suggests that early events in bone marrow B cell development and repertoire generation were abnormal in SLE patients. However, there was no obvious change of T cell repertoire in SLE patients, including repertoire diversity and CDR3 length. In addition, there was skewed usage of V genes and CDR3 sequences in SLE patients, which might be the result of physiological responses to environmental antigens or pathogens. CONCLUSIONS: In conclusion, our data revealed the specific changes of the TCR and BCR repertoires in SLE patients, which may provide new ideas for its prevention and treatment.

A case of anti-myelin oligodendrocyte glycoprotein (MOG)-immunoglobulin G (IgG) associated disorder (MOGAD) with clinical manifestations of acute disseminated encephalomyelitis: Secondary to mycoplasma pneumoniae infection.

Anti-myelin oligodendrocyte glycoprotein (MOG)-immunoglobulin G (IgG) associated disorder (MOGAD) is an immune-mediated central nervous system (CNS) inflammatory demyelinating disorder that has been widely recognized in recent years. It is distinct from multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), which are separate disease spectrums. Here we report the case of a 5-year-old boy who was admitted for 3 days with fever, headache, and vomiting. Magnetic resonance imaging revealed abnormal hyperintensity in the left thalamus and positive serum IgM for M. pneumoniae. After treatment with azithromycin, the headache gradually disappeared, but paralysis and urinary retention occurred on the 6th day after admission. MRI re-examination showed that the original abnormal signal in the left thalamus was significantly weakened, but new abnormal signals appeared in the brain and cerebrospinal cord, and the serum MOG-IgG was positive. After treatment, the child has fully recovered and is still receiving follow-up care. We believe that this is a case of MOGAD in a child with a biphasic ADEM phenotype secondary to M. pneumoniae infection, which has potential value in elucidating the pathophysiology of MOGAD.

Multiplexed analysis of gene expression and chromatin accessibility of human umbilical cord blood using scRNA-Seq and scATAC-Seq.

Nowadays, umbilical cord blood (UCB) cells has been increasingly replacing fetal and adult-derived cells in adoptive cell therapy. However, gene expression and chromatin accessibility in umbilical cord blood cells has not yet been fully elucidated. In this study, we used an integration of scRNA-seq with the scATAC-seq technology to perform unbiased analysis of UCBCs over developmental time from 31 gestational week (GW) to 37 GW in humans. We identified several distinct cell types (erythroid cell, T cell, B cell, erythroid precursor cells, NK cell, and endothelial progenitor cell) and subpopulations (6 different clusters of erythroid cells) in UCB cells. In addition, we also identified a series of differentially expressed genes and chromatin accessibility in each cell type between different gestational weeks. Interestingly, the gene expression pattern of umbilical cord blood cells from normal fetuses of similar gestational weeks were more consistent. In conclusion, our analysis presents a better understanding of the chromatin landscape and regulatory networks in UCB cells.

Comprehensive analysis of B and T cell receptor repertoire in patients after kidney transplantation by high-throughput sequencing.

PURPOSE: The dynamic immunity of kidney transplant patients has not been fully elucidated. In this study, we explored the repertoire features of B/T cell receptor (BCR/TCR) of kidney transplant patients. METHODS: Using combined multiplex PCR amplification and high-throughput sequencing technique, we analyzed the uremic patients' BCR H chain and TCR beta chain repertoire which obtained 1 day before kidney transplantation (PRE-1), 1 day and 7 day after kidney transplantation (POST-1 and POST-7). RESULTS: Our analysis results showed the diversity of TCRß CDR3 in POST-7 group was highest. In addition, there were specific skewed usage of TRBV gene subfamilies, and V-J combinations in different time points during kidney transplantation. Moreover, the overlap degrees of BCR-H (TCR-ß) CDR3 repertoire among each group were identified. Notably, the abundance of some TCR-ß CDR3 sequences changed regularly in the time point of kidney transplantation. CONCLUSIONS: The BCR-H (TCR-ß) CDR3 repertoire of kidney transplant patients changed dynamically.

Classification and Prognostic Characteristics of Hepatocellular Carcinoma Based on Glycolysis Cholesterol Synthesis Axis.

Background: Liver hepatocellular carcinoma (LIHC) is among the most frequent causes of cancer-related death across the world with a considerably poor prognosis. The current study targeted providing a new type of LIHC from the perspective of the glycolysis/cholesterol synthesis axis, predicting its prognostic characteristics, and exploring the potential role and mechanism of the glycolysis/cholesterol synthesis axis in the occurrence and development of LIHC. Methods: Based on the two expression profile data and clinical information of LIHC in The Cancer Genome Atlas (TCGA) database and hepatocellular carcinoma database (HCCDB), as well as glycolysis/cholesterol-related genes from the Molecular Signatures Database (MSigDB), unsupervised consistent clustering method was used to identify molecular subtypes. In addition, the differential genes were identified by limma package, and then the gene set was enriched, analyzed, and annotated by WebGestaltR package. At the same time, the immune infiltration analysis of tumor samples was carried out using the ESTIMATE to evaluate the tumor immune score of the samples. Finally, the differences in clinical characteristics among molecular subtypes were measured using univariate and multivariate Cox analyses. Results: According to the median standardized expression levels of glycolysis/cholesterol production genes, samples were divided into four groups (molecular subtypes): Quiescent group, Glycolysis group, Cholesterol group, and Mixed group. Significant prognostic differences were observed among the four groups. In both TCGA and HCCDB18 datasets, the prognosis of subtype Mixed was the worst, while Quiescent had a good prognosis. Cell cycle and oncogenic pathways were significantly enriched in the Mixed group. In addition, glycolysis and cholesterol production gene expressions were related to the prognostic LIHC subtype classification genes' expression levels. Conclusion: Metabolic classification regarding glycolysis and cholesterol production pathways provided new insights into the biological aspects of LIHC molecular subtypes and might help to develop personalized therapies for unique tumor metabolic profiles.

The Association between Immune Subgroups and Gene Modules for the Clinical, Cellular, and Molecular Characteristic of Hepatocellular Carcinoma.

The heterogeneity of hepatocellular carcinoma (HCC) is related to immune cell infiltration and genetic aberrations in the tumor microenvironment. This study aimed to identify the novel molecular typing of HCC according to the genetic and immune characteristics, to obtain accurate clinical management of this disease. We performed consensus clustering to divide 424 patients into different immune subgroups and assessed the reproducibility and efficiency in two independent cohorts with 921 patients. The associations between molecular typing and molecular, cellular, and clinical characteristics were investigated by a multidimensional bioinformatics approach. Furthermore, we conducted graph structure learning-based dimensionality reduction to depict the immune landscape to reveal the interrelation between the immune and gene systems in molecular typing. We revealed and validated that HCC patients could be segregated into 5 immune subgroups (IS1-5) and 7 gene modules with significantly different molecular, cellular, and clinical characteristics. IS5 had the worst prognosis and lowest enrichment of immune characteristics and was considered the immune cold type. IS4 had the longest overall survival, high immune activity, and antitumorigenesis, which were defined as the immune hot and antitumorigenesis types. In addition, immune landscape analysis further revealed significant intraclass heterogeneity within each IS, and each IS represented distinct clinical, cellular, and molecular characteristics. Our study provided 5 immune subgroups with distinct clinical, cellular, and molecular characteristics of HCC and may have clinical implications for precise therapeutic strategies and facilitate the investigation of immune mechanisms in HCC.

Identification and Characterization of Genes Related to the Prognosis of Hepatocellular Carcinoma Based on Single-Cell Sequencing.

The heterogeneity of hepatocellular carcinoma (HCC) highlights the importance of precision therapy. In recent years, single-cell RNA sequencing has been used to reveal the expression of genes at the single-cell level and comprehensively study cell heterogeneity. This study combined big data analytics and single-cell data mining to study the influence of genes on HCC prognosis. The cells and genes closely related to the HCC were screened through single-cell RNA sequencing (71,915 cells, including 34,414 tumor cells) and big data analysis. Comprehensive bioinformatics analysis of the key genes of HCC was conducted for molecular classification and multi-dimensional correlation analyses, and a prognostic model for HCC was established. Finally, the correlation between the prognostic model and clinicopathological features was analyzed. 16,880 specific cells, screened from the single-cell expression profile matrix, were divided into 20 sub-clusters. Cell typing revealed that 97% of these cells corresponded to HCC cell lines, demonstrating the high specificity of cells derived from single-cell sequencing. 2,038 genes with high variability were obtained. The 371 HCC samples were divided into two molecular clusters. Cluster 1 (C1) was associated with tumorigenesis, high immune score, immunotherapy targets (PD-L1 and CYLA-4), high pathological stage, and poor prognosis. Cluster 2 (C2) was related to metabolic and immune function, low immune score, low pathological stage, and good prognosis. Seven differentially expressed genes (CYP3A4, NR1I2, CYP2C9, TTR, APOC3, CYP1A2, and AFP) identified between the two molecular clusters were used to construct a prognostic model. We further validated the correlation between the seven key genes and clinical features, and the established prognostic model could effectively predict HCC prognosis. Our study identified seven key genes related to HCC that were used to construct a prognostic model through single-cell sequencing and big data analytics. This study provides new insights for further research on clinical targets of HCC and new biomarkers for clinical application.

CCR5 as a prognostic biomarker correlated with immune infiltrates in head and neck squamous cell carcinoma by bioinformatic study.

BACKGROUND: C-C chemokine receptor 5 (CCR5) has recently been recognized as an underlying therapeutic target for various malignancies. However, the association of CCR5 with prognosis in the head and neck squamous cell carcinoma (HNSC) patients and tumor-infiltrating lymphocytes (TILs) is unclear. METHODS: In the current experiment, methods such as the Tumor Immune Estimation Resource Analysis (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier plotter Analysis were used to comprehensively evaluate the expression of CCR5 in human various malignancies and the clinical prognosis in HNSC patients. Subsequently, we used the TIMER database and the TISIDB platform to investigate the correlation between CCR5 expression levels and immune cell infiltration in the HNSC tumor microenvironment. Furthermore, immunomodulatory and chemokine profiling were performed using the TISIDB platform to analyse the correlation between CCR5 expression levels and immunomodulation in HNSC patients. RESULTS: We found that CCR5 expression in HNSC tumor tissues was significantly upregulated than in normal tissues. In HNSC, patients with high CCR5 expression levels had worse overall survival (OS, HR = 0.59, p = 0.00015) and worse recurrence-free survival (RFS, HR = 3.27, p = 0.00098). Upregulation of CCR5 expression is closely associated with immunomodulators, chemokines, and infiltrating levels of CD4+ T cells, neutrophils, macrophages, and myeloid dendritic cells. Furthermore, upregulated CCR5 was significantly associated with different immune markers in the immune cell subsets of HNSC. CONCLUSIONS: High expression of CCR5 plays an important prognostic role in HNSC patients and may serve as a prognostic biomarker correlated with immune infiltration, and further studies are still needed to investigate therapeutic targeting HNSC patients in the future.

Microarray and bioinformatic analysis reveal the parental genes of m6A modified circRNAs as novel prognostic signatures in colorectal cancer.

Background: Accumulating evidences have revealed that the abnormal N6-methyladenosine (m6A) modification is closely associated with the occurrence, development, progression and prognosis of cancer. It is noteworthy that m6A modification is widely existed in circRNAs and found its key biological functions in regulating circRNAs metabolism. However, the role of m6A modified circRNAs in colorectal cancer (CRC) remains unknown. To better understand the role of circRNAs in the pathogenesis of CRC, we focus on the relationship between m6A-modified circRNAs and their parental genes. Methods: Arraystar m6A-circRNA epitranscriptomic microarray was used to identify differentially m6A modified circRNAs between CRC and the control group. In addition, TCGA-COAD and GSE106582 cohort were used to identify differentially expressed mRNAs. In this study, we screened the parental genes for which both circRNAs and mRNAs were down-regulated further to analyze, including gene expression, survival prognosis, enrichment analysis. Additionally, Western Blotting was used to further validate the role of the parental gene in CRC. Results: We found that 1405 significantly downregulated circRNAs in CRC by our microarray data. Moreover, we obtained 113 parental genes for which both circRNAs and mRNAs were down-regulated to analyze the relationship with the prognosis of CRC based on TCGA-COAD cohort. And we identified nine potential prognostic genes, including ABCD3, ABHD6, GAB1, MIER1, MYOCD, PDE8A, RPS6KA5, TPM1 and WDR78. And low expression of these genes was associated with poor survival prognosis of the patients with CRC. In addition, we found that TPM1 is downregulated in CRC by western blotting experiment. And the calcium-signaling pathway may involve the process of the CRC progression. Conclusions: We identified nine potential prognostic genes, after analyzed the relationship between the parental genes of m6A modified circRNAs and the progression of CRC. Above all, our study further validated TPM1 can serve as a potentail signature for CRC patients.

Analysis of Gene Expression and TCR/B Cell Receptor Profiling of Immune Cells in Primary Sjögren's Syndrome by Single-Cell Sequencing.

Primary Sjögren's syndrome (pSS) is a chronic autoimmune disease that is estimated to affect 35 million people worldwide and is characterized by lymphocytic infiltration, elevated circulating autoantibodies, and proinflammatory cytokines. The key immune cell subset changes and the TCR/BCR repertoire alterations in pSS patients remain unclear. In this study, we sought to comprehensively characterize the transcriptional changes in PBMCs of pSS patients by single-cell RNA sequencing and single-cell V(D)J sequencing. Naive CD8+ T cells and mucosal-associated invariant T cells were markedly decreased but regulatory T cells were increased in pSS patients. There were a large number of differentially expressed genes shared by multiple subpopulations of T cells and B cells. Abnormal signaling pathways, including Ag processing and presentation, the BCR signaling pathway, the TCR signaling pathway, and Epstein-Barr virus infection, were highly enriched in pSS patients. Moreover, there were obvious differences in the CD30, FLT3, IFN-II, IL-1, IL-2, IL-6, IL-10, RESISTIN, TGF-ß, TNF, and VEGF signaling networks between pSS patients and healthy controls. Single-cell TCR and BCR repertoire analysis showed that there was a lower diversity of T cells in pSS patients than in healthy controls; however, there was no significant difference in the degree of clonal expansion, CDR3 length distribution, or degree of sequence sharing. Notably, our results further emphasize the functional importance of αß pairing in determining Ag specificity. In conclusion, our analysis provides a comprehensive single-cell map of gene expression and TCR/BCR profiles in pSS patients for a better understanding of the pathogenesis, diagnosis, and treatment of pSS.

Molecular Typing of Gastric Cancer Based on Invasion-Related Genes and Prognosis-Related Features.

Background: This study aimed to construct a prognostic stratification system for gastric cancer (GC) using tumour invasion-related genes to more accurately predict the clinical prognosis of GC. Methodology: Tumour invasion-related genes were downloaded from CancerSEA, and their expression data in the TCGA-STAD dataset were used to cluster samples via non-negative matrix factorisation (NMF). Differentially expressed genes (DEGs) between subtypes were identified using the limma package. KEGG pathway and GO functional enrichment analyses were conducted using the WebGestaltR package (v0.4.2). The immune scores of molecular subtypes were evaluated using the R package ESTIMATE, MCPcounter and the ssGSEA function of the GSVA package. Univariate, multivariate and lasso regression analyses of DEGs were performed using the coxph function of the survival package and the glmnet package to construct a RiskScore model. The robustness of the model was validated using internal and external datasets, and a nomogram was constructed based on the model. Results: Based on 97 tumour invasion-related genes, 353 GC samples from TCGA were categorised into two subtypes, thereby indicating the presence of inter-subtype differences in prognosis. A total of 569 DEGs were identified between the two subtypes; of which, four genes were selected to construct the risk model. This four-gene signature was robust and exhibited stable predictive performance in different platform datasets (GSE26942 and GSE66229), indicating that the established model performed better than other existing models. Conclusion: A prognostic stratification system based on a four-gene signature was developed with a desirable area under the curve in the training and independent validation sets. Therefore, the use of this system as a molecular diagnostic test is recommended to assess the prognostic risk of patients with GC.