High Transaldolase 1 expression predicts poor survival of patients with upper tract urothelial carcinoma

MicroRNA-145-5p suppresses cell proliferation, migration, and invasion in upper tract urothelial carcinoma by targeting 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase

Upper tract urothelial carcinoma (UTUC), including renal, pelvic, and ureteral carcinoma, has a high incidence rate in Taiwan, which is different from that in Western countries. Therefore, it is imperative to elucidate the mechanisms underlying UTUC growth and metastasis. To explore the function of miR-145-5p in UTUC, we transfected the BFTC909 cell line with miR-145-5p mimics and analyzed the differences in protein levels by performing two-dimensional polyacrylamide gel electrophoresis. Real-time polymerase chain reaction and Western blot analysis were used to analyze 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inositol monophosphate cyclohydrolase (ATIC) messenger RNA and protein levels. A dual-luciferase assay was performed to identify the target of miR-145-5p in ATIC. The effects of miR-145-5p and ATIC expression by cell transfection on cell proliferation, migration, and invasion were also assessed. miR-145-5p downregulated ATIC protein expression. High ATIC expression is associated with tumor stage, metastasis, recurrence, and a poor prognosis in patients with UTUC. Cell function assays revealed that ATIC knockdown inhibited the proliferation, migration, and invasive abilities of UTUC cells. In contrast, miR-145-5p affected the proliferation, migration, and invasive abilities of UTUC cells by directly targeting the 3'-untranslated regions of ATIC. Furthermore, we used RNA sequencing and Ingenuity Pathway Analysis to identify possible downstream genes regulated by ATIC and found that miR-145-5p regulated the protein levels of fibronectin 1, Slug, cyclin A2, cyclin B1, P57, and interferon-induced transmembrane 1 via ATIC. ATIC may be a valuable predictor of prognosis and a potential therapeutic target for UTUC.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and immunotherapy response in bladder cancer

BACKGROUND

T cells have been proven to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in bladder cancer (BLCA).

METHODS

Single-cell RNA-sequencing (scRNA-seq) data were downloaded from the gene expression omnibus (GEO) database to screen T-cell marker genes. Bulk RNA-sequencing data and clinical information from BLCA patients were downloaded from the cancer genome atlas (TCGA) database to develop a prognosis signature. We analyzed the association of different risk groups with survival analysis, gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and immunotherapy response.

RESULTS

Based on 192 T-cell marker genes identified by scRNA-seq analysis, we constructed a prognostic signature containing 7 genes in the training cohort, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5 years were 0.734, 0.742 and 0.726 in the training cohort, 0.697, 0.671 and 0.670 in the testing cohort, 0.702, 0.665 and 0.629 in the GEO cohort, respectively. In addition, we constructed a nomogram based on clinical factors and the risk score of the signature. The low-risk group exhibited higher immune-related pathways, immune cell infiltration and TMB levels. Importantly, immunophenotype score and immunotherapy cohort (IMvigor210) analyses showed that the low-risk group had better immunotherapy response and prognosis.

CONCLUSIONS

Our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for BLCA patients.

Transaldolase inhibits CD36 expression by modulating glutathione-p38 signaling, exerting protective effects against macrophage foam cell formation

In atherosclerosis, macrophage-derived foam cell formation is considered to be a hallmark of the pathological process; this occurs via the uptake of modified lipoproteins. In the present study, we aim to determine the role of transaldolase in foam cell formation and atherogenesis and reveal the mechanisms underlying its role. Bone marrow-derived macrophages (BMDMs) isolated from mice successfully form foam cells after treatment with oxidized low-density lipoprotein (80 μg/mL). Elevated transaldolase levels in the foam cell model are assessed by quantitative polymerase chain reaction and western blot analysis. Transaldolase overexpression and knockdown in BMDMs are achieved via plasmid transfection and small interfering RNA technology, respectively. We find that transaldolase overexpression effectively attenuates, whereas transaldolase knockdown accelerates, macrophage-derived foam cell formation through the inhibition or activation of cholesterol uptake mediated by the scavenger receptor cluster of differentiation 36 (CD36) in a p38 mitogen-activated protein kinase (MAPK) signaling-dependent manner. Transaldolase-mediated glutathione (GSH) homeostasis is identified as the upstream regulator of p38 MAPK-mediated CD36-dependent cholesterol uptake in BMDMs. Transaldolase upregulates GSH production, thereby suppressing p38 activity and reducing the CD36 level, ultimately preventing foam cell formation and atherosclerosis. Thus, our findings indicate that the transaldolase-GSH-p38-CD36 axis may represent a promising therapeutic target for atherosclerosis.

Oral microbiota signatures in post-traumatic stress disorder (PTSD) veterans

Post-traumatic stress disorder (PTSD) represents a global public health concern, affecting about 1 in 20 individuals. The symptoms of PTSD include intrusiveness (involuntary nightmares or flashbacks), avoidance of traumatic memories, negative alterations in cognition and mood (such as negative beliefs about oneself or social detachment), increased arousal and reactivity with irritable reckless behavior, concentration problems, and sleep disturbances. PTSD is also highly comorbid with anxiety, depression, and substance abuse. To advance the field from subjective, self-reported psychological measurements to objective molecular biomarkers while considering environmental influences, we examined a unique cohort of Israeli veterans who participated in the 1982 Lebanon war. Non-invasive oral 16S RNA sequencing was correlated with psychological phenotyping. Thus, a microbiota signature (i.e., decreased levels of the bacteria sp_HMT_914, 332 and 871 and Noxia) was correlated with PTSD severity, as exemplified by intrusiveness, arousal, and reactivity, as well as additional psychopathological symptoms, including anxiety, hostility, memory difficulties, and idiopathic pain. In contrast, education duration correlated with significantly increased levels of sp_HMT_871 and decreased levels of Bacteroidetes and Firmicutes, and presented an inverted correlation with adverse psychopathological measures. Air pollution was positively correlated with PTSD symptoms, psychopathological symptoms, and microbiota composition. Arousal and reactivity symptoms were correlated with reductions in transaldolase, an enzyme controlling a major cellular energy pathway, that potentially accelerates aging. In conclusion, the newly discovered bacterial signature, whether an outcome or a consequence of PTSD, could allow for objective soldier deployment and stratification according to decreases in sp_HMT_914, 332, 871, and Noxia levels, coupled with increases in Bacteroidetes levels. These findings also raise the possibility of microbiota pathway-related non-intrusive treatments for PTSD.

Tumor Suppressor Role of Wild-Type P53-Dependent Secretome and Its Proteomic Identification in PDAC

The study of the cancer secretome is gaining even more importance in cancers such as pancreatic ductal adenocarcinoma (PDAC), whose lack of recognizable symptoms and early detection assays make this type of cancer highly lethal. The wild-type p53 protein, frequently mutated in PDAC, prevents tumorigenesis by regulating a plethora of signaling pathways. The importance of the p53 tumor suppressive activity is not only primarily involved within cells to limit tumor cell proliferation but also in the extracellular space. Thus, loss of p53 has a profound impact on the secretome composition of cancer cells and marks the transition to invasiveness. Here, we demonstrate the tumor suppressive role of wild-type p53 on cancer cell secretome, showing the anti-proliferative, apoptotic and chemosensitivity effects of wild-type p53 driven conditioned medium. By using high-resolution SWATH-MS technology, we characterized the secretomes of p53-deficient and p53-expressing PDAC cells. We found a great number of secreted proteins that have known roles in cancer-related processes, 30 of which showed enhanced and 17 reduced secretion in response to p53 silencing. These results are important to advance our understanding on the link between wt-p53 and cancer microenvironment. In conclusion, this approach may detect a secreted signature specifically driven by wild-type p53 in PDAC.

A novel prognostic model based on single-cell RNA sequencing data for hepatocellular carcinoma

Background

The tumour heterogeneous make-up of immune cell infiltrates is a key factor for the therapy response and prognosis of hepatocellular carcinoma (HCC). However, it is still a major challenge to comprehensively understand the tumour immune microenvironment (TIME) at the genetic and cellular levels.

Methods

HCC single-cell RNA sequencing (scRNA-seq) data were downloaded from the Gene Expression Omnibus (GEO) database, and gene expression data were retrieved from The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was performed to evaluate the abundance of immune infiltrating cells. We employed weighted gene coexpression network analysis (WGCNA) to construct a gene coexpression network. Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were further used to construct a risk model. Moreover, the expression levels of model genes were assessed by qPCR.

Results

We defined 25 cell clusters based on the scRNA-seq dataset (GSE149614), and the clusters were labelled as various cell types by marker genes. Then, we constructed a weighted coexpression network and identified a total of 6 modules, among which the brown module was most highly correlated with tumours. Moreover, we found that the brown module was most closely related to monocytes (cluster 21). Through univariate Cox and LASSO analyses, we constructed a 3-gene risk model (RiskScore = 0.257*Expression _CSTB + 0.263* Expression _TALDO1 + 0.313* Expression _CLTA). This risk model showed excellent predictive efficacy for prognosis in the TCGA-LIHC and ICGC cohorts. Additionally, patients with high risk scores were found to be less likely to benefit from immunotherapy.

Conclusions

We developed a 3-gene signature (including CLTA, TALDO1 and CSTB) based on the heterogeneity of the TIME to predict the survival outcome and immunotherapy response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02469-2.