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Background: Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC. Methods: The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs. Results: A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs. Conclusion: The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC. [ABSTRACT FROM AUTHOR]

Background: It is difficult to experimentally infect volunteers with RV strains to which the subject demonstrates serological immunity. However, in RV challenges, viral clearance begins before de novo adaptive immune responses would develop. We speculated that adaptive immunity to RV reflects heterologous immunity by effector memory cells. Methods: DCs were generated from monocytes using GM-CSF and IL-4 and RV39 loading accomplished with a dose of ∼350 TCID50/105 cells. RV-induced maturation was established as modulation of MHC class II, CD80, CD83, and CD86. Circulating RV targeting CD4 and CD8 T cells were investigated as induction of RV-specific proliferation (CFSE-dilution). Results: Maturation of DC by RV was confirmed as upregulation of MHC Class II (83.3±5.0% to 87.8±4.1%), CD80 (39.4±7.2% to 47.6±7.7%) and CD86 (78.4±4.7% to 84.1±3.4%). Both CD4 and CD8 memory T cells were recognized in the circulation of healthy subjects. Conclusions: RV drives DC maturation and results in their ability to present RV antigens to both T helper and cytotoxic lymphocytes. Both CD4 and CD8 cells capable of recognizing RV-associated antigens are present in the circulation of healthy subjects where they are presumably involved in immune surveillance and explain the rapid recruitment of an adaptive immune response during RV infection. [ABSTRACT FROM AUTHOR]

Lipids have been identified as important carbon sources for Mycobacterium tuberculosis (Mtb) to utilize in vivo. Thus gluconeogenesis bears a key role for Mtb to survive and replicate in host. A rate-limiting enzyme of gluconeogenesis, fructose 1, 6-bisphosphatase (FBPase) is encoded by the gene glpX. The functions of glpX were studied in M. marinum, a closely related species to Mtb. The glpX deletion strain (ΔglpX) displayed altered gluconeogenesis, attenuated virulence, and altered bacterial proliferation. Metabolic profiles indicate an accumulation of the FBPase substrate, fructose 1, 6-bisphosphate (FBP) and altered gluconeogenic flux when ΔglpX is cultivated in a gluconeogenic carbon substrate, acetate. In both macrophages and zebrafish, the proliferation of ΔglpX was halted, resulting in dramatically attenuated virulence. Intracellular ΔglpX exhibited an elongated morphology, which was also observed when ΔglpX was grown in a gluconeogenic carbon source. This elongated morphology is also supported by the observation of unseparated multi-nucleoid cell, indicating that a complete mycobacterial division in vivo is correlated with intact gluconeogenesis. Together, our results indicate that glpX has essential functions in gluconeogenesis, and plays an indispensable role in bacterial proliferation in vivo and virulence of M. marinum. [ABSTRACT FROM AUTHOR]

Background: The malignant mesothelioma (MM) survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM. Methodology/Principal Findings: A T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs) using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1). Conclusions/Significance: Our results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis. [ABSTRACT FROM AUTHOR]