Global Knowledge Map and Emerging Research Trends in Induced Pluripotent Stem Cells and Hereditary Diseases: A CiteSpace-based Visualization and Analysis.

The rise of induced pluripotent stem cells (iPSCs) technology has ushered in a landmark shift in the study of hereditary diseases. However, there is a scarcity of reports that offer a comprehensive and objective overview of the current state of research at the intersection of iPSCs and hereditary diseases. Therefore, this study endeavors to categorize and synthesize the publications in this field over the past decade through bibliometric methods and visual knowledge mapping, aiming to visually analyze their research focus and clinical trends. The English language literature on iPSCs and hereditary diseases, published from 2014 to 2023 in the Web of Science Core Collection (WoSCC), was examined. The CiteSpace (version 6.3.R1) software was utilized to visualize and analyze country/region, institution, scholar, co-cited authors, and co-cited journals. Additionally, the co-occurrence, clustering, and bursting of co-cited references were displayed. Analysis of 347 articles that met the inclusion criteria revealed a steady increase in the number of published articles and citation frequency in the field over the past decade. With regard to the countries/regions, institutions, scholars, and journals where the articles were published, the highest numbers were found in the USA, the University of California System, Suren M. Zakian, and Stem Cell Research, respectively. The current research is focused on the construction of disease models, both before and after correction, as well as drug target testing for single-gene hereditary diseases. Chromosome transplantation genomic therapy for hereditary diseases with abnormal chromosome structures may emerge as a future research hotspot in this field.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Ameliorating role of microRNA-378 carried by umbilical cord mesenchymal stem cells-released extracellular vesicles in mesangial proliferative glomerulonephritis.

BACKGROUND: Mesenchymal stem cells (MSCs) and their released extracellular vesicles (Evs) have shown protective effects against kidney diseases. This study aims to study the functions of umbilical cord MSCs-released Evs (ucMSC-Evs) and their implicated molecules in mesangial proliferative glomerulonephritis (MsPGN). METHODS: A rat model of MsPGN was induced by anti-Thy-1.1, and rat mesangial cells (rMCs) HBZY-1 were treated with PDGF-BB/DD to mimic MsPGN condition in vitro. Rats and cells were treated with different doses of ucMSC-Evs, and then the pathological changes in renal tissues and proliferation of rMCs were determined. Differentially expressed microRNAs (miRNAs) after Evs treatment were screened by microarray analysis. The interactions among miR-378, PSMD14, and TGFBR1 were analyzed. Gain- and loss-of function studies of miR-378 and PSMD14 were performed to explore their effects on tissue hyperplasia and rMC proliferation and their interactions with the TGF-ß1/Smad2/3 signaling pathway. RESULTS: The ucMSC-Evs treatment ameliorated mesangial hyperplasia and fibrosis in rat renal tissues and suppressed the aberrant proliferation of rMCs in a dose-dependent manner. miR-378 was the most upregulated miRNA in tissues and cells after ucMSC-Evs treatment. miR-378 directly targeted PSMD14, and PSMD14 maintained the stability of TGFBR1 through deubiquitination modification, which led to TGF-ß1/Smad2/3 activation. Either miR-378 knockdown or PSMD14 overexpression diminished the protective functions of ucMSC-Evs by activating the TGF-ß1/Smad2/3 signaling pathway. CONCLUSION: UcMSC-Evs ameliorate pathological process in MsPGN through the delivery of miR-378, which suppresses PSMD14-mediated TGFBR1 stability and inactivates the TGF-ß1/Smad2/3 signaling pathway to reduce tissue hyperplasia and rMC proliferation. Video abstract.

Zinc finger C3H1-type containing serves as a novel prognostic biomarker in human pan-cancer.

BACKGROUND: Zinc finger C3H1 domain-containing protein (ZFC3H1) is differentially expressed between primary tumor and the normal in most cancers. Additionally, a recent study has suggested that ZFC3H1 could serve as a novel marker for the prognosis of prostate adenocarcinoma (PRAD). However, the relationship between ZFC3H1 expression and the prognostic values in most tumors remains unclear. Our study is mainly for exploring the prognosis of ZFC3H1 in pan-cancer and for further discovering a potential therapeutics target. METHODS: Based on the clinical big data, we performed a pan-cancer analysis of ZFC3H1, including gene expression, survival prognosis, genetic alteration, protein phosphorylation, immune infiltration and enrichment analysis. In addition, Real-Time PCR and Western Blot were used to further confirm the role of ZFC3H1 in the colorectal cancer. RESULTS: We found that ZFC3H1 expression was connected with the prognosis of multiple malignant tumors. Furthermore, we also observed that ZFC3H1 was highly expressed in colorectal cancer through Real-Time PCR and Western Blot. The primary tumors presented higher phosphorylation level of the S655 site in lung adenocarcinoma, colon adenocarcinoma and uterine corpus endometrial carcinoma. ZFC3H1 expression was positively correlated with the immune infiltration of Cancer-associated fibroblasts (CAFs) in some tumors, such as liver hepatocellular carcinoma. And RNA surveillance pathways may be closely associated with the occurrence of tumors. CONCLUSIONS: Our study first reveals that ZFC3H1 could serve as a novel prognostic biomarker of pan-cancer, especially colorectal cancer.

Prospective Analysis of Proteins Carried in Extracellular Vesicles with Clinical Outcome in Hepatocellular Carcinoma.

Background: Extracellular vehicles (EVs) contain different proteins that relay information between tumor cells, thus promoting tumorigenesis. Therefore, EVs can serve as an ideal marker for tumor pathogenesis and clinical application. Objective: Here, we characterised EV-specific proteins in hepatocellular carcinoma (HCC) samples and established their potential protein-protein interaction (PPI) networks. Materials and Methods: We used multi-dimensional bioinformatics methods to mine a network module to use as a prognostic signature and validated the model's prediction using additional datasets. The relationship between the prognostic model and tumor immune cells or the tumor microenvironment status was also examined. Results: 1134 proteins from 316 HCC samples were mapped to the exoRBase database. HCC-specific EVs specifically expressed a total of 437 proteins. The PPI network revealed 321 proteins and 938 interaction pathways, which were mined to identify a three network module (3NM) with significant prognostic prediction ability. Validation of the 3NM in two more datasets demonstrated that the model outperformed the other signatures in prognostic prediction ability. Functional analysis revealed that the network proteins were involved in various tumor-related pathways. Additionally, these findings demonstrated a favorable association between the 3NM signature and macrophages, dendritic, and mast cells. Besides, the 3NM revealed the tumor microenvironment status, including hypoxia and inflammation. Conclusion: These findings demonstrate that the 3NM signature reliably predicts HCC pathogenesis. Therefore, the model may be used as an effective prognostic biomarker in managing patients with HCC.

Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer.

The aim of this study was to explore the potential molecular mechanisms of Gastric cancer (GC) and identify new prognostic markers for GC. RNA sequencing data were downloaded from the Gene Expression Omnibus database, and 418 differentially expressed genes (DEGs) were screened. Weighted correlation network analysis (WGCNA) was performed to identify six hub modules related to the clinical features of GC. Cytoscape software was used to identify five hub genes in the co-expression network, including CST1, CEMIP, COL8A1, PMEPA1, and MSLN. The TCGA database was used to verify hub gene expression in GC. The overall survival in the high CEMIP expression group was significantly lower than that of patients in the low CEMIP expression group. CEMIP expression was also found to be negatively correlated with B cell and CD4 + T cell infiltration. Further, associated in vitro experiments confirmed that CEMIP downregulation suppressed the proliferation and migration of GC cells and impaired the chemoresistance of GC cells to 5-fluorouracil.Our study effectively identified and validated prognostic biomarkers for GC, laying a new foundation for the therapeutic target, occurrence, and development of gastric cancer.

Integrating Spatial Transcriptomics and Single-Cell RNA-seq Reveals the Gene Expression Profling of the Human Embryonic Liver.

The liver is one of vital organs of the human body, and it plays an important role in the metabolism and detoxification. Moreover, fetal liver is one of the hematopoietic places during ontogeny. Understanding how this complex organ develops during embryogenesis will yield insights into how functional liver replacement tissue can be engineered and how liver regeneration can be promoted. Here, we combine the advantages of single-cell RNA sequencing and Spatial Transcriptomics (ST) technology for unbiased analysis of fetal livers over developmental time from 8 post-conception weeks (PCW) and 17 PCW in humans. We systematically identified nine cell types, and defined the developmental pathways of the major cell types. The results showed that human fetal livers experienced blood rapid growth and immigration during the period studied in our experiments, and identified the differentially expressed genes, and metabolic changes in the developmental process of erythroid cells. In addition, we focus on the expression of liver disease related genes, and found that 17 genes published and linked to liver disease mainly expressed in megakaryocyte and endothelial, hardly expressed in any other cell types. Together, our findings provide a comprehensive and clear understanding of the differentiation processes of all main cell types in the human fetal livers, which may provide reference data and information for liver disease treatment and liver regeneration.

FAM65A as a novel prognostic biomarker in human tumors reveal by a pan-cancer analysis.

BACKGROUND: Family with sequence similarity 65 member A (FAM65A), also known as RIPOR1, is differentially expressed between human tumor and non-tumor tissues in kinds of cancers. In addition, it was reported that the product of FAM65A may be a biomarker for cholangiocarcinoma patients. However, there is still no evidence on the relationship between the FAM65A and different types of tumors. Our study is mainly for exploring the prognostic values of FAM65A in pan-cancer and for further discovering a potential therapeutics target. METHODS: We analyzed FAM65A expression, prognostic values, genetic alteration, protein phosphorylation, immune infiltration and enrichment analysis across different types of human malignant tumors based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Additionally, Real-Time PCR (RT-qPCR) was performed to further confirm the roles of FAM65A in the pathogenesis of colorectal cancer. RESULTS: We found that FAM65A expression was associated with the prognosis of multiple human tumors, especially colorectal cancer. Moreover, we also observed that FAM65A was highly expressed in colorectal cancer through RT-qPCR. We observed that decreasing phosphorylation level of the S351 locus in colon adenocarcinoma, uterine corpus endometrial carcinoma and lung adenocarcinoma. And the expression of FAM65A was positively related to cancer-associated fibroblasts (CAFs) infiltration in many tumors, such as colon adenocarcinoma. Therefore, FAM65A may be a potential prognostic biomarker of human tumors.

No difference in TCRß repertoire of CD4+ naive T cell between patients with primary biliary cholangitis and healthy control subjects.

Primary biliary cholangitis (PBC) is considered as a model of organ-specific autoimmune disease based on the serological findings of anti-mitochondrial antibodies (AMA), infiltrates of T cells, and selective destruction of epithelial cells in the liver. T-cell-mediated autoimmune mechanisms are considered to be involved in the pathogenesis of primary biliary cholangitis (PBC). In this context, we used a combination of multiplex-PCR, Illumina sequencing and IMGT/HighV-QUEST for a standardized analysis of the T cell receptor ß-chain (TCRß) repertoire of CD4＋naive T cells in PBC patients compared with healthy volunteers. Nonfunctional TCRs were used to study the pre-selection TCR repertoire, as they are not subject to functional selection (positive and negative selection). Functional TCRs were used to study the post-selection TCR repertoire. The results showed that there was not significant difference between PBC patients and healthy volunteers in TCRß diversity, CDR3 length distributions, degree of sequence sharing, and usage frequency of TRBV and TRBJ segments, no matter in Pre-selection or Post-selection repertoires. In conclusion, early events in thymic T cell development and repertoire generation are not abnormality in PBC patients. The breakdown of self-tolerance to autoantigen may be derived from other immunological dysregulation or environmental agents.

T cell repertoire following kidney transplantation revealed by high-throughput sequencing.

Delayed T cell recovery and restricted T cell receptor (TCR) diversity after kidney transplantation are associated with increased risks of infection and malignancy. Technical challenges limit the faithful measurement of TCR diversity after kidney transplantation. In this study, we used a combination of multiplex-PCR, Illumina sequencing and IMGT/HighV-QUEST to directly assess millions of TCRs per individual before and at two time points after kidney transplantation (1days and 7days after transplantation) in a cohort of 10 patients compared to a normal control (NC) group (n=10). We identified the most commonly observed CDR3 length, VD indel length, and DJ indel length in transplantation group and normal group. In addition, we found that the TCR repertoire diversity of transplantation groups was relatively lower compared to NC group. T cell depletion in Post-1 group can be observed, which resulted in the altered distribution characteristics of clonotype abundance. A modest proportion of high abundance clones were shared among the pre-1 group, post-1 group and post-7 group, and it did not exist in the NC group, which exhibited a signature of antigen selection. Moreover, our results also demonstrated that various TRBV expression increased and some public sequences at different time points after kidney transplantation, which may provide biomarkers to monitor the immune status of transplant patients.