Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis

Genetic analysis from multiple cohorts implies causality between 2200 druggable genes, telomere length, and leukemia

BACKGROUND

Clinical therapeutic targets for leukemia remain to be identified and the causality between leukemia and telomere length is unclear.

METHODS

This work employed cis expression quantitative trait locus (eQTL) for 2,200 druggable genes from the eQTLGen Consortium and genome-wide association studies (GWAS) summary data for telomere length in seven blood cell types from the UK Biobank, Netherlands Cohort as exposures. GWAS data for lymphoid leukemia (LL) and myeloid leukemia (ML) from FinnGen and Lee Lab were used as outcomes for discovery and replication cohorts, respectively. Robust Mendelian randomization (MR) findings were generated from seven MR models and a series of sensitivity analyses. Summary-data-based MR (SMR) analysis and transcriptome-wide association studies (TWAS) were further implemented to verify the association between identified druggable genes and leukemia. Single-cell type expression analysis was employed to identify the specific expression of leukemia casual genes on human bone marrow and peripheral blood immune cells. Multivariable MR analysis, linkage disequilibrium score regression (LDSC), and Bayesian colocalization analysis were performed to further validate the relationship between telomere length and leukemia. Mediation analysis was used to assess the effects of identified druggable genes affecting leukemia via telomere length. Phenome-wide MR (Phe-MR) analysis for assessing the effect of leukemia causal genes and telomere length on 1,403 disease phenotypes.

RESULTS

Combining the results of the meta-analysis for MR estimates from two cohorts, SMR and TWAS analysis, we identified five LL causal genes (TYMP, DSTYK, PPIF, GDF15, FAM20A) and three ML causal genes (LY75, ADA, ABCA2) as promising drug targets for leukemia. Univariable MR analysis showed genetically predicted higher leukocyte telomere length increased the risk of LL (odds ratio [OR] = 2.33, 95 % confidence interval [95 % CI] 1.70-3.18; P = 1.33E-07), and there was no heterogeneity and horizontal pleiotropy. Evidence from the meta-analysis of two cohorts strengthened this finding (OR = 1.88, 95 % CI 1.06-3.05; P = 0.01). Multivariable MR analysis showed the causality between leukocyte telomere length and LL without interference from the other six blood cell telomere length (OR = 2.72, 95 % CI 1.88-3.93; P = 1.23E-07). Evidence from LDSC supported the positive genetic correlation between leukocyte telomere length and LL (rg = 0.309, P = 0.0001). Colocalization analysis revealed that the causality from leukocyte telomere length on LL was driven by the genetic variant rs770526 in the TERT region. The mediation analysis via two-step MR showed that the causal effect from TYMP on LL was partly mediated by leukocyte telomere length, with a mediated proportion of 12 %.

CONCLUSION

Our study identified several druggable genes associated with leukemia risk and provided new insights into the etiology and drug development of leukemia. We also found that genetically predicted higher leukocyte telomere length increased LL risk and its potential mechanism of action.

Construction and validation of a TAMRGs prognostic signature for gliomas by integrated analysis of scRNA and bulk RNA sequencing data

BACKGROUND

This study aimed to construct and validate a prognostic model based on tumor associated macrophage-related genes (TAMRGs) by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data.

METHODS

The scRNA-seq data of three inhouse glioma tissues were used to identify the tumor-associated macrophages (TAMs) marker genes, the DEGs from the The Cancer Genome Atlas (TCGA) - Genotype-Tissue Expression (GTEx) dataset were used to further select TAMs marker genes. Subsequently, a TAMRG-score was constructed by Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis in the TCGA dataset and validated in the Chinese Glioma Genome Atlas (CGGA) dataset.

RESULTS

We identified 186 TAMs marker genes, and a total of 6 optimal prognostic genes including CKS2, LITAF, CTSB, TWISTNB, PPIF and G0S2 were selected to construct a TAMRG-score. The high TAMRG-score was significantly associated with worse prognosis (log-rank test, P<0.001). Moreover, the TAMRG-score outperformed the other three models with AUC of 0.808. Immune cell infiltration, TME scores, immune checkpoints, TMB and drug susceptibility were significantly different between TAMRG-score groups. In addition, a nomogram were constructed by combing the TAMRG-score and clinical information (Age, Grade, IDH mutation and 1p19q codeletion) to predict the survival of glioma patients with AUC of 0.909 for 1-year survival.

CONCLUSION

The high TAMRG-score group was associated with a poor prognosis. A nomogram by incorporating TMARG-score could precisely predict glioma survival, and provide evidence for personalized treatment of glioma.

Dissecting prostate Cancer: Single-Cell insight into Macrophage Diversity, molecular Prognosticators, and the role of Peptidylprolyl Isomerase F

BACKGROUND

Prostate cancer remains a prominent challenge in oncology, with advanced stages showing poor prognosis. The tumor microenvironment (TME), and particularly tumor-associated macrophages (TAMs), plays a crucial role in disease progression. This study explores the single-cell transcriptomics of prostate cancer, determines macrophage heterogeneity, identifies prognostic gene markers, and assesses the role of PPIF in TAMs.

METHODS

Single-cell RNA sequencing data from the GEO database (GSE176031) and transcriptome data from the TCGA were processed to characterize cell populations and identify prognostic genes in prostate cancer. Macrophage subpopulations were examined through clustering, followed by gene set scoring based on migration, activation, and proliferation. PPIF expression in macrophages was investigated using multiplex immunofluorescence staining on matched prostate cancer and adjacent non-tumoral tissues.

RESULTS

The single-cell analysis identified 9,178 cells, categorized into 10 principal cell types, with macrophages constituting a significant part of the immune microenvironment. Four macrophage subgroups demonstrated distinct functional pathways: phagocytic, immune-regulatory, and proliferative. A total of 39 genes correlated with prostate cancer prognosis were identified, of which 10 carried the most significant prognostic information. Peptidylprolyl Isomerase F (PPIF) expression was significantly higher in TAMs from tumor tissue than normal tissue, indicating its potential regulatory role in the immune microenvironment.

CONCLUSION

The intricate cellular architecture of the prostate cancer TME has been elucidated, with a focus on macrophage heterogeneity and functional specialization. Prognostic genes, including PPIF, were associated with survival outcomes, providing potential therapeutic targets. PPIF's prominent expression in TAMs may serve as a lever in cancer progression, warranting further investigation as a biomarker and a molecule of interest for therapeutic targeting within the prostate cancer milieu.

Peptidyl-prolyl isomerase F as a prognostic biomarker associated with immune infiltrates and mitophagy in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is among the most prevalent malignancies worldwide, with unfavorable treatment outcomes. Peptidyl-prolyl isomerase F (PPIF) is known to influence the malignancy traits of tumor progression by modulating the bioenergetics and mitochondrial permeability in cancer cells; however, its role in LUAD remains unclear. Our study seeks to investigate the clinical significance, tumor proliferation, and immune regulatory functions of PPIF in LUAD.

Methods

The expression of PPIF in LUAD tissues and cells was assessed using bioinformatics analysis, immunohistochemistry (IHC), and Western blotting. Survival curve analysis was conducted to examine the prognostic association between PPIF expression and LUAD. The immunomodulatory role of PPIF in LUAD was assessed through the analysis of PPIF expression and immune cell infiltration. A series of gain- and loss-of-function experiments were conducted on PPIF to investigate its biological functions in LUAD both in vitro and in vivo. The mechanisms underlying PPIF's effects on LUAD were delineated through functional enrichment analysis and Western blotting assays.

Results

PPIF exhibited overexpression in LUAD tissues compared to normal controls. Survival curve analysis revealed that patients with LUAD exhibiting higher PPIF expression demonstrated decreased overall survival and a shorter progression-free interval. PPIF was implicated in modulating immune cell infiltration, particularly in regulating the T helper 1-T helper 2 cell balance. Functionally, PPIF was discovered to promote tumor cell proliferation and advance cell-cycle progression. Furthermore, PPIF could impede mitophagy by targeting the FOXO3a/PINK1-Parkin signaling pathway.

Conclusions

The findings of this study indicate that the prognosis-related gene PPIF may have a significant role in the regulation of LUAD cell proliferation, tumor-associated immune cell infiltration, and mitophagy, and thus PPIF may be a promising therapeutic target of LUAD.

Comprehensive Analysis of TICRR in Hepatocellular Carcinoma Based on Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA ( www.tcga-data.nci.nih.gov/tcga/ ) datasets and GEO ( www.ncbi.nlm.nih.gov/geo ) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy.

Cinnamtannin B-1 Inhibits the Progression of Osteosarcoma by Regulating the miR-1281/PPIF Axis

Osteosarcoma (OS), one of the bone tumors, occurs mainly during childhood and adolescence and has an incidence rate of 5%. Cinnamtannin B-1 (CTB-1) is a natural trimeric proanthocyanidin compound found in plants Cinnamomum zeylanicum and Laurus nobilis. Previously, several articles have demonstrated that CTB-1 exerts a certain effect on melanoma and cervical cancer. However, their role in OS remains unclear. In this study, CTB-1 was found to inhibit the proliferation of OS cancer cells, with the dose of CTB-1 positively correlated to the survival rate of HOS and MG-63 cells. Recently, microRNAs (miRNAs) were also reported to play an important role in tumor proliferation. Hence, we performed the miRNA sequencing analysis after CTB-1 treatment to identify miRNA levels in HOS cells and found that the expression of miR-1281 was significantly upregulated. According to the functional analysis, CTB-1 inhibited the growth and migration of OS by upregulating the expression of miR-1281. Additionally, miR-1281 acted as a sponge for Peptidylprolyl Isomerase F (PPIF), inhibiting its expression levels. The rescue experiments revealed that CTB-1 delayed the development of OS by regulating the miR-1281/PPIF pathway. Hence, our findings suggested that CTB-1 inhibited the cell growth, invasion, and migration of OS by upregulating miR-1281 and inhibiting PPIF expression, thereby providing a possible target drug for OS treatment.

Dawn-to-dusk dry fasting induces anti-atherosclerotic, anti-inflammatory, and anti-tumorigenic proteome in peripheral blood mononuclear cells in subjects with metabolic syndrome

Background

Metabolic syndrome characterized by abdominal obesity, high blood pressure, elevated fasting glucose and triglyceride levels and low high-density lipoprotein cholesterol level is associated with pro-inflammatory state, increased risk for atherosclerosis, and multiple cancers. Our previous results on subjects with metabolic syndrome showed that 4-week dawn-to-dusk (sunset) dry fasting resulted in significant changes in the serum proteome and improvement in several metabolic risk factors. Peripheral blood mononuclear cells (PBMC) proteomics is a powerful tool that can provide mechanistic insights into how dawn-to-dusk dry fasting affects protein expression in metabolic pathways at cellular level. In this study, we determined whether dawn-to-dusk dry fasting would induce favorable changes in PBMC proteome in subjects with metabolic syndrome, similar to the changes induced by dawn-to-dusk dry fasting in the same subjects' serum proteome.

Methods

We conducted a prospective study on subjects with metabolic syndrome and collected blood specimens before 4-week dawn-to-dusk dry fasting, at the end of 4-week dawn-to-dusk dry fasting, and one week after 4-week dawn-to-dusk dry fasting. We performed untargeted proteomics using nano ultra-high performance liquid chromatography-tandem mass spectrometry to assess the impact of 4-week dawn-to-dusk dry fasting on PBMC proteome.

Results

There were 14 subjects with metabolic syndrome with a mean age of 59 who fasted from dawn to dusk (strict dry fasting without any liquid or food intake) for more than 14 h daily for 29 days. The quantitative proteome analysis showed that apolipoprotein B (APOB) gene protein products (GP) levels were downregulated and had the most statistical significance of the observed difference at the end of 4-week dawn-to-dusk dry fasting (P = 0.008) and one week after 4-week dawn-to-dusk dry fasting (P = 0.0004) compared with the levels before 4-week dawn-to-dusk dry fasting. The comparison between GP levels before and at the end of 4-week dawn-to-dusk dry fasting showed an alteration in the expression of genes associated with lipid and atherosclerosis pathway (P = 6.014e-4) and C-type lectin receptor signaling pathway (P = 1.064e-5). The genes that were differentially expressed in the lipid and atherosclerosis pathway were APOB (P = 0.008), CD36 (P = 0.040), CALM1, CALM2, CALM3 (P = 0.015), and HSPA8 (P = 0.047). One of the differentially expressed genes in the C-type lectin receptor signaling pathway was lymphocyte-specific protein 1 (LSP1), which showed an average of 19-fold increase at the end of 4-week dawn-to-dusk dry fasting compared with the GP levels before fasting (P = 0.004). Several GPs associated with tumor-suppressor effect (TUBB4B, LSP1, ACTR3B) were upregulated, and GPs associated with tumor-promoter effect (CD36, CALM1, CALM2, CALM3, FLOT2, PPIF) were downregulated at the end of 4-week dawn-to-dusk dry fasting or one week after 4-week dawn-to-dusk dry fasting compared with the GP levels before 4-week dawn-to-dusk dry fasting.

Conclusion

Based on our results, we conclude that in subjects with metabolic syndrome, 4-week dawn-to-dusk dry fasting induced anti-atherosclerotic, anti-inflammatory, and anti-tumorigenic PMBC proteome. Randomized, controlled clinical trials are needed to further investigate the effect of dawn-to-dusk dry fasting on subjects with chronic metabolic diseases and metabolic syndrome-induced cancers.

A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma

Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients’ prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients.

Characterization of DNA methylation as well as mico-RNA expression and screening of epigenetic markers in adipogenesis

This study aimed to use bioinformatics methods to characterize epigenetic changes in terms of micro-RNA(miRNA) expression and DNA methylation during adipogenesis. The mRNA and miRNA expression microarray and DNA methylation dataset were obtained from the GEO database. Differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs) and differentially methylated probes (DMPs) were filtered using the limma package. The R language cluster profile package was used for functional and enrichment analysis. A protein–protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. The Connection map (CMap) website tool was used to screen potential therapeutic drugs for adipogenesis. When comparing the early and late stages of adipogenesis, 111 low miRNA targeted upregulated genes and 64 high miRNA targeted downregulated genes were obtained, as well as 663 low-methylated high-expressed genes and 237 high-methylated low-expressed genes. In addition, 41 genes (24 upregulated and 17 downregulated) were simultaneously regulated by abnormal miRNA changes and DNA methylation. Ten chemicals were identified as putative therapeutics for adipogenesis. In addition, among the dual-regulated genes identified, CANX, HNRNPA1, MCL1, and PPIF may play key roles in the epigenetic regulation of adipogenesis and may serve as aberrant methylation or miRNA targeting biomarkers.

Identification of condition-specific biomarker systems in uterine cancer

Uterine cancer is the fourth most common cancer among women, projected to affect 66,000 US women in 2021. Uterine cancer often arises in the inner lining of the uterus, known as the endometrium, but can present as several different types of cancer, including endometrioid cancer, serous adenocarcinoma, and uterine carcinosarcoma. Previous studies have analyzed the genetic changes between normal and cancerous uterine tissue to identify specific genes of interest, including TP53 and PTEN. Here we used Gaussian Mixture Models to build condition-specific gene coexpression networks for endometrial cancer, uterine carcinosarcoma, and normal uterine tissue. We then incorporated uterine regulatory edges and investigated potential coregulation relationships. These networks were further validated using differential expression analysis, functional enrichment, and a statistical analysis comparing the expression of transcription factors and their target genes across cancerous and normal uterine samples. These networks allow for a more comprehensive look into the biological networks and pathways affected in uterine cancer compared with previous singular gene analyses. We hope this study can be incorporated into existing knowledge surrounding the genetics of uterine cancer and soon become clinical biomarkers as a tool for better prognosis and treatment.

Human exposure to low dose ionizing radiation affects miR-21 and miR-625 expression levels

BACKGROUND

Recently exposure to ionizing radiation driven by artificial radiation sources such as Medical X-rays and Nuclear medicine has increased hastily. Ionizing radiation-induced the DNA damage and activate the DNA damage response signaling pathways. The aim of this study was to evaluate the role of miR-21 and miR-625 in response to low-dose ionizing radiation.

MATERIALS AND METHODS

In this study, the blood sample of 38 volunteer patients who underwent Cardiac scans before and after ^99mTc-MIBI injection were used. The WBC of patients was used for RNA extraction and after cDNA synthesis by the poly-A method the expression level of miR-21 and miR-625 was evaluated by real-time PCR method.

RESULTS

The results of this study indicated that miR-21 and miR- 625 were significantly upregulated under exposure to low-dose ionizing radiation. The expression level of these miRNAs was not significantly correlated with the age and BMI of patients. More ever the bioinformatics analysis indicated that SP1 was a common target of both miRNAs and had the highest degree between hub genes.

CONCLUSION

In summary miR-21 and miR-625 can contribute to the response to acute low dose ionizing radiation by targeting the SP1. However further studies should be carried out on the molecular mechanism of effects of miR-21 and miR-625 in response to low dose ionizing radiation by targeting the SP1.

The CRL4DTL E3 ligase induces degradation of the DNA replication initiation factor TICRR/TRESLIN specifically during S phase

A DNA replication program, which ensures that the genome is accurately and wholly replicated, is established during G1, before the onset of S phase. In G1, replication origins are licensed, and upon S phase entry, a subset of these will form active replisomes. Tight regulation of the number of active replisomes is crucial to prevent replication stress-induced DNA damage. TICRR/TRESLIN is essential for DNA replication initiation, and the level of TICRR and its phosphorylation determine the number of origins that initiate during S phase. However, the mechanisms regulating TICRR protein levels are unknown. Therefore, we set out to define the TICRR/TRESLIN protein dynamics throughout the cell cycle. Here, we show that TICRR levels are high during G1 and dramatically decrease as cells enter S phase and begin DNA replication. We show that degradation of TICRR occurs specifically during S phase and depends on ubiquitin ligases and proteasomal degradation. Using two targeted siRNA screens, we identify CRL4DTL as a cullin complex necessary for TICRR degradation. We propose that this mechanism moderates the level of TICRR protein available for replication initiation, ensuring the proper number of active origins as cells progress through S phase.