P4HB: A novel diagnostic and prognostic biomarker for bladder carcinoma

Current look at the most promising proteomic and glycomic biomarkers of bladder cancer

BACKGROUND

Bladder cancer (BC) belongs to the most frequent cancer types. The diagnostic process is still long and costly, with a high percentage of false-positive or -negative results. Due to the cost and lack of effectiveness, older methods need to be supplemented or replaced by a newer more reliable method. In this regard, proteins and glycoproteins pose high potential.

METHODS

We performed an online search in PubMed/Medline, Scopus, and Web of Science databases to find relevant studies published in English up until May 2023. If applicable, we set the AUC threshold to 0.90 and sensitivity/specificity (SN/SP) to 90%.

FINDINGS

Protein and glycoprotein biomarkers are a demonstrably viable option in BC diagnostics. Cholinesterase shows promise in progression-free survival. BLCA-4, ORM-1 along with HTRA1 in the detection of BC. Matrix metallopeptidase 9 exhibits potential for stratification of muscle-invasive subtypes with high negative predictive value for aggressive phenotypes. Distinguishing non-muscle invasive subtypes benefits from Keratin 17. Neu5Gc-modified UMOD glycoproteins pose potential in BC diagnosis, while fibronectin, laminin-5, collagen type IV, and lamprey immunity protein in early detection of BC.

Bone morphogenetic protein 1: a prognostic indicator and potential biomarker in three cancer types

BACKGROUND

Bone morphogenetic protein 1 (BMP1) is a metalloprotease that plays a role in activating both transforming growth factor-β (TGF-β) and BMP signaling pathways. TGF-β has been identified as a factor initiating and facilitating cancer development. Consequently, we propose the hypothesis that dysregulation of BMP1 could potentially contribute to the onset and advancement of human cancers.

METHODS

In this research, we aimed to analyze BMP1 expression level and the associated clinical outcomes across various cancers using online cancer OMICS databases, advanced Bioinformatics tools, and molecular analyses.

RESULTS

The outcomes of our web server-based expression analysis indicated an up-regulation of BMP1 in a majority of the human cancers examined. External validation using clinical samples also showed higher expression of BMP1. Moreover, heightened BMP1 expression exhibited a noteworthy correlation with reduced overall survival (OS) duration in Bladder Cancer (BLCA), Kidney Renal Clear Cell Carcinoma (KIRC), and Lung Adenocarcinoma (LUAD) patients. This suggests a substantial involvement of the BMP1 gene in the development and progression of these three types of cancers. The major signaling pathways related with BMP1 enriched genes were "ECM-receptor interaction, Amoebiasis, Focal adhesion, Protein digestion and absorption, progesterone-mediated, PI3K-Akt signaling pathway, and platelet activation". Moreover, we also explored some interesting correlations among BMP1 expression and its DNA promoter methylation level, CD8+ T immune cells level, and genetic variations.

CONCLUSION

In conclusion, our study has provided some solid basis for BMP1 to be used as a reliable common biomarker for BLCA, KIRC, and LUAD patients.

Prognostic model development and molecular subtypes identification in bladder urothelial cancer by oxidative stress signatures

BACKGROUND

Mounting studies indicate that oxidative stress (OS) significantly contributes to tumor progression. Our study focused on bladder urothelial cancer (BLCA), an escalating malignancy worldwide that is growing rapidly. Our objective was to verify the predictive precision of genes associated with overall survival (OS) by constructing a model that forecasts outcomes for bladder cancer and evaluates the prognostic importance of these genetic markers.

METHODS

Transcriptomic data were obtained from TCGA-BLCA and GSE31684, which are components of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. To delineate distinct molecular subtypes, we employed the non-negative matrix factorization (NMF)method. The significance of OS-associated genes in predicting outcomes was assessed using lasso regression, multivariate Cox analysis, and univariate Cox regression analysis. For external validation, we employed the GSE31684 dataset. CIBERSORT was utilized to examine the tumor immune microenvironment (TIME). A nomogram was created and verified using calibration and receiver operating characteristic (ROC) curves, which are based on risk signatures. We examined variations in clinical characteristics and tumor mutational burden (TMB) among groups classified as high-risk and low-risk. To evaluate the potential of immunotherapy, the immune phenomenon score (IPS) was computed based on the risk score. In the end, the pRRophetic algorithm was employed to forecast the IC50 values of chemotherapy medications.

RESULTS

In our research, we examined the expression of 275 genes associated with OS in 19 healthy and 414 cancerous tissues of the bladder obtained from the TCGA database. As a result, a new risk signature was created that includes 4 genes associated with OS (RBPMS, CRYAB, P4HB, and PDGFRA). We found two separate groups, C1 and C2, that showed notable variations in immune cells and stromal score. According to the Kaplan-Meier analysis, patients classified as high-risk experienced a considerably reduced overall survival in comparison to those categorized as low-risk (P<0.001). The predictive capability of the model was indicated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve surpassing 0.6. Our model showed consistent distribution of samples from both the GEO database and TCGA data. Both the univariate and multivariate Cox regression analyses validated the importance of the risk score in relation to overall survival (P < 0.001). According to our research, patients with a lower risk profile may experience greater advantages from using a CTLA4 inhibitor, whereas patients with a higher risk profile demonstrated a higher level of responsiveness to Paclitaxel and Cisplatin. In addition, methotrexate exhibited a more positive outcome in patients with low risk compared to those with high risk.

CONCLUSIONS

Our research introduces a novel model associated with OS gene signature in bladder cancer, which uncovers unique survival results. This model can assist in tailoring personalized treatment approaches and enhancing patient therapeutic effect in the management of bladder cancer.

Establishment of novel ferroptosis-related prognostic subtypes correlating with immune dysfunction in prostate cancer patients

Background

We aimed to identify two new prognostic subtypes and create a predictive index for prostate cancer (PCa) patients based on ferroptosis database.

Methods

The nonnegative matrix factorization approach was used to identify molecular subtypes. We investigate the differences between cluster 1 and cluster 2 in terms of clinical features, functional pathways, tumour stemness, tumour heterogeneity, gene mutation and tumour immune microenvironment score after identifying the two molecular subtypes. Colony formation assay and flow cytometry assay were performed.

Results

The stratification of two clusters was closely connected to BCR-free survival using the nonnegative matrix factorization method, which was validated in the other three datasets. Furthermore, multivariate Cox regression analysis revealed that this classification was an independent risk factor for patients with PCa. Ribosome, aminoacyl tRNA production, oxidative phosphorylation, and Parkinson's disease-related pathways were shown to be highly enriched in cluster 1. In comparison to cluster 2, patients in cluster 1 exhibited significantly reduced CD4+ T cells, CD8+ T cells, neutrophils, dendritic cells and tumor immune microenvironment scores. Only HHLA2 was more abundant in cluster 1. Moreover, we found that P4HB downregulation could significantly inhibit the colony formation ability and contributed to cell apoptosis of C4-2B and DU145 cell lines.

Conclusions

We discovered two new prognostic subtypes associated with immunological dysfunction in PCa patients based on ferroptosis-related genes and found that P4HB downregulation could significantly inhibit the colony formation ability and contributed to cell apoptosis of PCa cell lines.

Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.

COL15A1 interacts with P4HB to regulate the growth and malignancy of HepG2.2.15 cells

Liver cancer is the fourth most common cause of cancer related deaths, ranking sixth in terms of incidence rate, and hepatocellular carcinoma (HCC) is the main type of liver cancer. Hepatitis B virus (HBV) infection is the main cause of HCC, and currently, HBV related HCC has become an important public health issue. COL15A1 encodes the alpha chain of collagen XV, a member of the FACIT collagen family, which has anti-angiogenic and anti-tumoral properties and play a vital role in tissue homeostasis in the liver, and its specific function in HBV-related HCC still needs further exploration. This study aimed to determine the regulatory role of COL15A1 in HBV-related HCC and explored the underlying mechanisms at the cellular level. Firstly, the biochip analysis results showed that the expression of COL15A1 was increased in human HBV-related HCC tissues. Furthermore, HBV induction also could significantly increase the expression of COL15A1 in hepatoma cell lines. Functionally, it found that COL15A1 silencing could significantly inhibit apoptosis and promote proliferation, migration, invasion and growth of HepG2.2.15. Mechanically, it found that COL15A1 could interact with P4HB，and its silencing could significantly increase the expression level of P4HB, thereby inhibiting the GRP76 expression and promoting growth and malignancy of HepG2.2.15 cells, revealing COL15A1 might play an anticancer role in HBV-related HCC.

Expression, localization, and function of P4HB in the spermatogenesis of Chinese mitten crab (Eriocheir sinensis)

Background

The sperm of Chinese mitten crab (Eriocheir sinensis) have special noncondensed nuclei. The formation and stability of the special nuclei are closely related to the correct folding of proteins during spermatogenesis. P4HB plays a key role in protein folding, but its expression and role in the spermatogenesis of E. sinensis are unclear.

Objective

To investigate the expression and distribution characteristics of P4HB in the spermatogenesis of E. sinensis as well as its possible role.

Methods

The testis tissues of adult and juvenile E. sinensis were used as materials. We utilized a variety of techniques, including homology modeling, phylogenetic analysis, RT-qPCR, western blotting, and immunofluorescence staining to predict the protein structure and sequence homology of P4HB, analyze its expression in the testis tissues, and localize and semi-quantitatively assess its expression in different male germ cells.

Results

The sequence of P4HB protein in E. sinensis shared a high similarity of 58.09% with the human protein disulfide isomerase, and the phylogenetic tree analysis indicated that the protein sequence was highly conserved among crustaceans, arthropods, and other animals species. P4HB was found to be expressed in both juvenile and adult E. sinensis testis tissues, with different localization patterns observed all over the developmental stages of male germ cells. It was higher expressed in the spermatogonia, spermatocytes, and stage I spermatids, followed by the mature sperm than in the stage II and III spermatids. The subcellular localization analysis revealed that P4HB was predominantly expressed in the cytoplasm, cell membrane, and extracellular matrix in the spermatogonia, spermatocytes, stage I and stage II spermatids, with some present in specific regions of the nuclei in the spermatogonia. In contrast, P4HB was mainly localized in the nuclei of stage III spermatids and sperm, with little expression observed in the cytoplasm.

Conclusion

P4HB was expressed in the testis tissues of both adult and juvenile E. sinensis, but the expression and localization were different in male germ cells at various developmental stages. The observed differences in the expression and localization of P4HB may be an essential factor in maintaining the cell morphology and structure of diverse male germ cells in E. sinensis. Additionally, P4HB expressed in the nuclei of spermatogonia, late spermatids, and sperm may play an indispensable role in maintaining the stability of the noncondensed spermatozoal nuclei in E. sinensis.

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Current evidence indicate that cancer-associated fibroblasts (CAFs) play an important role in prostate cancer (PCa) development and progression. In this study, we identified CAF-related molecular subtypes and prognostic index for PCa patients undergoing radical prostatectomy through integrating single-cell and bulk RNA sequencing data. We completed analyses using software R 3.6.3 and its suitable packages. Through single-cell and bulk RNA sequencing analysis, NDRG2, TSPAN1, PTN, APOE, OR51E2, P4HB, STEAP1 and ABCC4 were used to construct molecular subtypes and CAF-related gene prognostic index (CRGPI). These genes could clearly divide the PCa patients into two subtypes in TCGA database and the BCR risk of subtype 1 was 13.27 times higher than that of subtype 2 with statistical significance. Similar results were observed in MSKCC2010 and GSE46602 cohorts. In addtion, the molucular subtypes were the independent risk factor of PCa patients. We orchestrated CRGPI based on the above genes and divided 430 PCa patients in TCGA database into high- and low- risk groups according to the median value of this score. We found that high-risk group had significant higher risk of BCR than low-risk group (HR: 5.45). For functional analysis, protein secretion was highly enriched in subtype 2 while snare interactions in vesicular transport was highly enriched in subtype 1. In terms of tumor heterogeneity and stemness, subtype 1 showd higher levels of TMB than subtype 2. In addition, subtype 1 had significant higher activated dendritic cell score than subtype 2. Based on eight CAF-related genes, we developed two prognostic subtypes and constructed a gene prognostic index, which could predict the prognosis of PCa patients very well.

A prognostic model for bladder cancer based on cytoskeleton-related genes

BACKGROUND

A typical cancerous growth in the urinary tract, bladder cancer (BLCA) has a dismal survival rate and a poor chance of being cured. The cytoskeleton has been shown to be tightly related to tumor invasion and metastasis. Nevertheless, the expression of genes associated with the cytoskeleton and their prognostic significance in BLCA remain unknown.

METHODS

In our study, we performed differential expression analysis of cytoskeleton-related genes between BLCA versus normal bladder tissues. According to the outcomes of this analysis of differentially expressed genes, all BLCA cases doing nonnegative matrix decomposition clustering analysis be classified into different molecular subtypes and were subjected to Immune cell infiltration analysis. We then constructed a cytoskeleton-associated gene prediction model for BLCA, and performed risk score independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, enrichment analysis, clinical correlation analysis of prognostic models, and immune cell correlation analysis were carried out.

RESULTS

We identified 546 differentially expressed genes that are linked to the cytoskeleton, including 314 up-regulated genes and 232 down-regulated genes. All BLCA cases doing nonnegative matrix decomposition clustering analysis could be classified into 2 molecular subtypes, and we observed differences (P < .05) in C1 and C2 immune scores about 9 cell types. Next, we obtained 129 significantly expressed cytoskeleton-related genes. A final optimized model was constructed consisting of 11 cytoskeleton-related genes. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with BLCA. Survival curves and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Significant enrichment pathways for cytoskeleton-associated genes in bladder cancer samples were explored by Gene set enrichment analysis enrichment analysis. After we obtained the risk scores, a clinical correlation analysis was performed to examine which clinical traits were related to the risk scores. Finally, we demonstrated a correlation between different immune cells.

CONCLUSION

Cytoskeleton-related genes have an important predictive value for BLCA, and the prognostic model we constructed may enable personalized treatment of BLCA.

A meta-analysis and bioinformatics analysis of P4HB expression levels in the prognosis of cancer patients

BACKGROUND

P4HB (prolyl 4-hydroxylase, beta polypeptide) is a human chromosomal gene that encodes an endoplasmic reticulum (ER) molecular chaperone protein with oxidoreductase, chaperone and isomerase activities. Recent studies indicated that P4HB may have clinical significance, with elevated P4HB expression reported in cancer patients, but its impact on tumor prognosis is not yet clear. To our knowledge, this is the first meta-analysis to show an association between P4HB expression and the prognosis of various cancers.

METHODS

We conducted a systematic literature search in the PubMed, PubMed Central, Web of Science, Embase, CNKI, Wanfang and Weipu databases, followed by a quantitative meta-analysis using Stata SE14.0 and R statistics software 4.2.1. The hazard ratio (HR) and relative risk (RR) were analyzed to evaluate the relationships of P4HB expression levels with overall survival (OS), disease-free survival (DFS), and clinicopathological parameters of cancer patients. Subsequently, P4HB expression in various cancer types was validated using the Gene Expression Profiling Interactive Analysis (GEPIA) online database.

RESULTS

Ten articles containing the data of 4121 cancer patients were included in the analysis, and a significant correlation of high P4HB expression with apparently shorter OS was found (HR, 1.90; 95% CI, 1.50-2.40; P < 0.01), while there was no significant correlation with gender (RR, 1.06; 95% CI, 0.91-1.22; P = 0.084), or age. Additionally, GEPIA online analysis revealed significant upregulation of P4HB in 13 types of cancer. Among them, P4HB overexpression was associated with shorter OS in 9 and worse DFS in 11 cancer types.

CONCLUSIONS

Upregulation of P4HB is correlated with worse prognosis in various cancers, which could provide new ideas for the development of P4HB-related diagnostic biomarkers and new therapeutic targets.

Cytoskeleton regulator RNA expression on cancer-associated fibroblasts is associated with prognosis and immunotherapy response in bladder cancer

Background

Dysregulation of long noncoding RNAs (lncRNAs) has been reported to be associated with multiple tumors where they act as tumor suppressors or accelerators. The lncRNA CYTOR was identified as an oncogene involved in many cancers, such as gastric cancer, colorectal cancer, hepatocellular carcinoma, and renal cell carcinoma. However, the role of CYTOR in bladder cancer (BCa) has rarely been reported.

Methods

Using cancer datasets from The Cancer Genome Atlas (TCGA) program, we analyzed the association between CYTOR expression and prognostic value, oncogenic pathways, antitumor immunity and immunotherapy response in BCa. The influence of CYTOR on the immune infiltration pattern in the urothelial carcinoma microenvironment was further verified in our dataset. Single-cell analysis revealed the role of CYTOR in the tumor microenvironment (TME) of BCa. Finally, we evaluated the expression of CYTOR in BCa in the Peking University First Hospital (PKU-BCa) dataset and its correlation with the malignant phenotype of BCa in vitro and in vivo.

Results

The results indicated that CYTOR was highly expressed in multiple cancer samples, including BCa, and increased CYTOR expression contributed to poor overall survival (OS). Additionally, elevated CYTOR expression was significantly correlated with clinicopathological features of BCa, such as female sex, advanced TNM stage, high histological grade and non-papillary subtype. Functional characterization revealed that CYTOR may be involved in immune-related pathways and the epithelial mesenchymal transformation (EMT) process. Moreover, CYTOR had a significant association with infiltrating immune cells, including M2 macrophages and regulatory T cells (Tregs). CYTOR facilitates the crosstalk between cancer-associated fibroblasts (CAFs) and macrophages, and mediates M2 polarization of macrophages. Correlation analysis revealed a positive correlation between CYTOR expression and programmed cell death-1 (PD-1)/programmed death ligand 1 (PD-L1)/expression and other targets for specific immunotherapy in BCa, which are recognized to predict the efficacy of immunotherapy.

Conclusions

These results suggest that CYTOR serves as a potential biomarker for predicting survival outcome, TME cell infiltration characteristics and immunotherapy response in BCa.

The Effect of N6-Methyladenosine Regulators and m6A Reader YTHDC1-Mediated N6-Methyladenosine Modification Is Involved in Oxidative Stress in Human Aortic Dissection

Aortic dissection (AD) develops pathological changes in the separation of the true and false aortic lumen, with high lethality. m6A methylation and oxidative stress have also been shown to be involved in the onset of AD. Through bioinformatics methods, three differentially expressed m6A regulators (YTHDC1, YTHDC2, and RBM15) were excavated from the GSE52093 dataset in the Gene Expression Omnibus (GEO) database, and functional enrichment analysis of the differentially expressed genes (DEGs) regulated by m6A regulators was performed. Then, the genes with oxidative stress-related functions among these genes were found. The protein interaction network of the oxidative stress-related genes and the competing endogenous RNA- (ceRNA-) miRNA-mRNA network were constructed. Among them, DHCR24, P4HB, and PDGFRA, which have m6A differences in AD samples, were selected as key genes. We also performed immune infiltration analysis, as well as cell-gene correlation analysis, on samples from the dataset. The results showed that YTHDC1 was positively correlated with macrophage M1 and negatively correlated with macrophage M2. Finally, we extracted AD and healthy aorta RNA and protein from human tissues that were taken from AD patients and patients who received heart transplants, performed quantitative real-time PCR (qRT-PCR) on YTHDC2 and RBM15, and performed qRT-PCR and western blot (WB) detection on YTHDC1 to verify their differences in AD. The mRNA and protein levels of YTHDC1 were consistent with the results of bioinformatics analysis and were downregulated in AD. Immunofluorescence (IF) was used to colocalize YTHDC1 and endothelial cell marker CD31. After knocking down YTHDC1 in human umbilical vein endothelial cells (HUVECs), reactive oxygen species (ROS) levels had a tendency to increase and the expression of peroxide dismutase SOD2 was decreased. This study provides assistance in discovering the role of m6A regulator YTHDC1 in AD. In particular, m6A modification participates in oxidative stress and jointly affects AD.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

Construction of noninvasive prognostic model of bladder cancer patients based on urine proteomics and screening of natural compounds

BACKGROUND

Bladder cancer (BCa) has a high incidence and recurrence rate worldwide. So far, there is no noninvasive detection of BCa therapy and prognosis based on urine multi-omics. Therefore, it is necessary to explore noninvasive predictive models and novel treatment modalities for BCa.

METHODS

First, we performed protein analysis of urine from five BCa patients and five healthy individuals using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Combining multi-omics data to mine particular and sensitive molecules to predict BCa prognosis. Second, urine proteomics data were combined with TCGA transcriptome data to select differential genes that were specifically highly expressed in urine and tissues. Further, the Lasso equation was used to screen specific molecules to construct a noninvasive prediction model of BCa. Finally, natural compounds of specific molecules were selected by combined network pharmacology and molecular docking to complete molecular structure docking.

RESULTS

A noninvasive predictive model was constructed using PSMB5, P4HB, S100A16, GET3, CNP, TFRC, DCXR, and MPZL1, specific molecules screened by multi-omics, and clinical features, which had good predictive value at 1, 3, and 5 years of prediction. High expression of these target genes suggests a poor prognosis in patients with BCa, and they were mainly involved in cell adhesion molecules and the IGF pathway. In addition, the corresponding drugs and natural compounds were selected by network pharmacology, and the molecular structure 7NHT of PSMB5 was found to be well docked to Ellagic acid, a natural compound in Hetaoren that we found. The 3D structure 6I7S of P4HB was able to bind to Stigmasterol in Shanzha stably, and the structure 6WRV of TFRC as an iron transport carrier was also able to bind to Stigmasterol in Shanzha stably. The structures 1WOJ, 3D3W, and 6IGW of CNP, DCXR, and MPZL1 can also play an important role in combination with the natural compounds (S)-Stylopine, Kryptoxanthin, and Sitosterol in Maqianzi, Yumixu, and Laoguancao.

CONCLUSION

The noninvasive prediction model based on urinomics had excellent potential in predicting the prognosis of patients with BCa. The multi-omics screening of specific molecules combined with pharmacology and compound molecular docking can promote the research and development of novel drugs.

ERp44 Regulates the Proliferation, Migration, Invasion, and Apoptosis of Gastric Cancer Cells Via Activation of ER Stress

Gastric cancer (GC) is one of the most prevalent malignancies worldwide. Endoplasmic reticulum (ER) stress plays a key role in the progression of GC. Rapid proliferation of tumor cells interferes with ER homeostasis, leading to ER stress and triggering unfolded protein response. Therefore, it is very necessary to investigate abnormally expressed ER resident proteins (ERp) in cancer cells. This study aimed to investigate the possible roles of ERp44. The mRNA and protein expression of genes were detected using qRT-PCR and western blot. Cell apoptosis was calculated using flow cytometry. Cell proliferation was determined using CCK-8 and colony formation assay. Cell migration was detected by wound healing, and cell invasion was measured by transwell assay. We found that ERp44 was obviously decreased in GC tissues. Furthermore, ERp44 overexpression distinctly suppressed the proliferation, migration, and invasion of MGC-803 and KATO III cells. In contrast, apoptosis was promoted by ERp44 overexpression. Furthermore, mechanistic studies revealed that overexpression of ERp44 inhibited malignant biological processes by regulating the eIF-2α/CHOP signaling pathway. Taken together, our data demonstrated that ERp44 regulated the proliferation, migration, invasion, and apoptosis via ERp44/eIF-2α/CHOP axis in GC. Targeting the ERp44and ER stress may be a promising strategy for GC.

Integrated Analysis and Identification of Critical RNA-Binding Proteins in Bladder Cancer

Simple Summary

The role of RNA-binding proteins (RBPs) in bladder cancer (BC) remains unclear. Therefore, we analyzed the clinical information and RNA sequencing data from patients with BC and identified RBPs that may be promising predictors of BC.

Abstract

RBPs in the development and progression of BC remains unclear. Here, we elucidated the role of RBPs in predicting the survival of patients with BC. Clinical information and RNA sequencing data of the training and validation cohorts were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Survival-related differentially expressed RBPs were identified using Cox regression analyses. A total of 113 upregulated and 54 downregulated RBPs were observed, with six showing prognostic values (AHNAK, MAP1B, LAMA2, P4HB, FASN, and GSDMB). In both the GSE32548 and GSE31684 datasets, patients with low-risk scores in survival-related six RBPs-based prognostic model showed longer overall survival than those with high-risk scores. AHNAK, MAP1B, P4HB, and FASN expression were significantly upregulated in both BC tissues and cell lines. BC tissues from high-risk group showed higher proportions of naive CD4+ T cells, M0 and M2 macrophages, and neutrophils and lower proportions of plasma cells, CD8+ T cells, and T-cell follicular helper compared to low-risk group. AHNAK knockdown significantly inhibited the proliferation, invasion, and migration of BC cells in vitro and inhibited the growth of subcutaneous tumors in vivo. We thus developed and functionally validated a novel six RBPs-based prognostic model for BC.

Meta-Analysis of EGF-Stimulated Normal and Cancer Cell Lines to Discover EGF-Associated Oncogenic Signaling Pathways and Prognostic Biomarkers

BACKGROUND

Although epidermal growth factor (EGF) controls many crucial processes in the human body, it can increase the risk of developing cancer when overexpresses.

OBJECTIVES

This study focused on detecting cancer-associated genes that are dysregulated by EGF overexpression.

MATERIALS AND METHODS

To identify differentially expressed genes (DEGs), two independent meta-analyses with normal and cancer RNA-Seq samples treated by EGF were conducted. The new DEGs detected only via two meta-analyses were used in all downstream analyses. To reach count data, the tools of FastQC, Trimmomatic, HISAT2, SAMtools, and HTSeq-count were employed. DEGs in each individual RNA-Seq study and the meta-analysis of RNA-Seq studies were identified using DESeq2 and metaSeq R package, respectively. MCODE detected densely interconnected top clusters in the protein-protein interaction (PPI) network of DEGs obtained from normal and cancer datasets. The DEGs were then introduced to Enrichr and ClueGO/CluePedia, and terms, pathways, and hub genes enriched in Gene Ontology (GO) and KEGG and Reactome were detected.

RESULTS

The meta-analysis of normal and cancer datasets revealed 990 and 541 new DEGs, all upregulated. A number of DEGs were enriched in protein K48-linked deubiquitination, ncRNA processing, ribosomal large subunit binding, and protein processing in endoplasmic reticulum. Hub genes overexpression (DHX33, INTS8, NMD3, OTUD4, P4HB, RPS3A, SEC13, SKP1, USP34, USP9X, and YOD1) in tumor samples were validated by TCGA and GTEx databases. Overall survival and disease-free survival analysis also confirmed worse survival in patients with hub genes overexpression.

CONCLUSIONS

The detected hub genes could be used as cancer biomarkers when EGF overexpresses.

Abnormal ECA-Binding Membrane Glycans and Galactosylated CAT and P4HB in Lesion Tissues as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Hepatocellular carcinoma (HCC) is one of the most common types of cancer. Despite decades of research efforts, the search for novel biomarkers is still urgently needed for the diagnosis of HCC and the improvement of clinical outcomes. Previous studies of HCC clinical biomarkers have usually focused on serum and urine samples (e.g., serum Alpha-fetoprotein (AFP). However, cellular membrane proteins in lesion tissues are less used in HCC diagnosis. The abnormal expression of membrane glycoproteins in tumor lesions are considered as potential targets for tumor diagnosis and tumor therapies. Here, a lectin array has been employed to screen and identify abnormal glycopatterns and cellular membrane glycans in HCC lesion tissues compared with adjacent non-tumor tissues. We found that there was significantly less expression of Erythrina cristagalli (ECA) lectin binding (Galβ1-3/β1-4) glycans on the cellular membrane of HCC lesion tissues compared with those of adjacent non-tumor tissues. Immunohistochemistry analysis further showed that ECA-binding ability on the membrane proteins of HCC tissues progressively decreased in different tumor-node-metastasis (TNM) stages (stage I to stage III) as the malignancy of liver cancer increased. Receiver operating curve (ROC) analysis showed ECA-binding ability yielding a sensitivity of 85% and specificity of 75%, and a combination of ECA and AFP has better clinical diagnostic efficiency, yielding a sensitivity of 90% and specificity of 85%, than ECA or AFP assay alone. ECA pull-down followed by mass spectrometry further showed that there was significantly less expression of ECA binding membrane catalase (CAT) and prolyl 4-hydroxylase beta polypeptide (P4HB) in HCC tissues compared with the adjacent non-tumor tissues. The abnormally increased expression of total CAT and P4HB and decreased expression of galactosylated membrane CAT and P4HB in HCC cell lines were correlated with an HCC metastasis status. Our findings suggest that abnormal declined ECA-binding galatosylated membrane glycans and two galactosylated-CAT and P4HB glycoproteins in lesion tissues are potential biomarkers in the diagnosis and/or metastasis prediction for HCC.

An Unfolded Protein Response Related Signature Could Robustly Predict Survival Outcomes and Closely Correlate With Response to Immunotherapy and Chemotherapy in Bladder Cancer

Background: The unfolded protein response (UPR) plays a significant role in maintaining protein hemostasis in tumor cells, which are crucial for tumor growth, invasion, and resistance to therapy. This study aimed to develop a UPR-related signature and explore its correlation with immunotherapy and chemotherapy in bladder cancer. Methods: The differentially expressed UPR-related genes were put into Lasso regression to screen out prognostic genes, which constituted the UPR signature, and were incorporated into multivariate Cox regression to generate risk scores. Subsequently, the predictive performance of this signature was estimated by receiver operating characteristic (ROC) curves. The CIBERSORTx, the maftool, and Gene set enrichment analysis (GSEA) were applied to explore infiltrated immune cells, tumor mutational burden (TMB), and enriched signaling pathways in both risk groups, respectively. Moreover, The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC) databases were used to predict responses to chemotherapy and immunotherapy. Results: Twelve genes constituted the UPR-related signature. Patients with higher risk scores had worse overall survival (OS) in training and three validation sets. The UPR-related signature was closely correlated with clinicopathologic parameters and could serve as an independent prognostic factor. M0 macrophages showed a significantly infiltrated difference in both risk groups. TMB analysis showed that the risk score in the wild type and mutation type of FGFR3 was significantly different. GSEA indicated that the immune-, extracellular matrix-, replication and repair associated pathways belonged to the high risk group and metabolism-related signal pathways were enriched in the low risk group. Prediction of immunotherapy and chemotherapy revealed that patients in the high risk group might benefit from chemotherapy, but had a worse response to immunotherapy. Finally, we constructed a predictive model with age, stage, and UPR-related risk score, which had a robustly predictive performance and was validated in GEO datasets. Conclusion: We successfully constructed and validated a novel UPR-related signature in bladder cancer, which could robustly predict survival outcomes and closely correlate with the response to immunotherapy and chemotherapy in bladder cancer.

Comprehensive bioinformatics analyses of APOBECs family and identification of APOBEC3D as the unfavorable prognostic biomarker in clear cell renal cell carcinoma

Purpose: At present, how early screening for ccRCC is still a thorny issue for urologists. Probing the mechanisms underlying the development of ccRCC and finding relevant prognostic biomarkers remains crucial. Therefore, we systematically analyzed the APOBEC family in this study and identified APOBEC3D as a prognostic biomarker. Methods: In this study, based on the TCGA database, we systematically assessed the expression and prognosis of the APOBEC family and analyzed potential bioinformatic pathways. We then constructed nomograms to predict the prognosis of ccRCC patients better. Afterward, we further focused on APOBEC3D in our data on ccRCC specimens. The APOBEC3D should be extensively studied in ccRCC in the future. Results: The results showed that the APOBEC family showed the most significant changes in expression in ccRCC. The pathway enrichment analysis showed that APOBEC3 family members mainly regulated cytidine and cytosine-related processes. Subsequently, the Cox regression was used to construct prognostic signature, and validated in ICGC and GEO databases. Next, a nomogram was created integrating clinical parameters showing good predictive performance. Finally, we screened for APOBEC3D and found in our clinical sample that patients with high expression of APOBEC3D had a worse prognosis. Conclusion: Based on these results, APOBEC family members play important roles in the development of ccRCC, and APOBEC3D could serve as the biomarker for predicting patient prognosis.

High expression of transmembrane P24 trafficking protein 9 predicts poor prognosis in breast carcinoma

Over the years, molecular subtypes based on estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER-2) status have been observed to effectively guide decision-making for the optimal treatment of patients with breast carcinoma (BRCA). However, despite this progress, there are still more than 41,000 BRCA-related fatalities each year in the United States. Moreover, effective drug targets for triple-negative breast carcinoma (TNBC) are still lacking. Given its high mortality rate, it is necessary to investigate more biomarkers with prognostic and pathological relevance in BRCA. In our study, we examined the expression patterns and prognostic implications of transmembrane P24 trafficking protein 9 (TMED9) in BRCA using multiple public cohorts and BRCA specimens collected from Shanghai General Hospital. In addition to this, in vitro experiments were also performed to evaluate the effects of TMED9 expression in BRCA cell proliferation and migration. Our results have demonstrated that a high expression of TMED9 promoted BRCA cell proliferation and migration and predicted poor prognosis in patients with BRCA. In conclusion, TMED9 is a potential prognostic indicator and a possible drug target of BRCA.

Pathological Significance and Prognostic Roles of Thrombospondin-3, 4 and 5 in Bladder Cancer

BACKGROUND/AIM

The pathological significance of thrombospondin (TSP)-1 and -2 in bladder cancer (BC) is well-known whereas that of TSP-3, 4 and 5 remains unclear. Our aim is to clarify the pathological significance and prognostic roles of TSP-3 to 5 expression in BC patients.

PATIENTS AND METHODS

TSP-3 to 5 expression, proliferation index (PI), apoptotic index (AI) and microvessel density (MVD) were evaluated in 206 BC patients by immunohistochemical techniques.

RESULTS

TSP-5 expression was positively associated with grade, T stage, metastasis, and worse prognosis. PI in TSP-5-positive tissues was significantly higher compared to negative tissues. In contrast, AI in TSP-5-positive tissues was significantly lower compared to negative tissues. Expressions of TSP-3 and 4 were not associated with any clinicopathological features, survival, PI, or AI.

CONCLUSION

TSP-5 plays important roles in malignant behavior via cell survival regulation whereas the pathological significance of TSP-3 and TSP-4 in BC might be minimal.

Identification of an 11-Autophagy-Related-Gene Signature as Promising Prognostic Biomarker for Bladder Cancer Patients

Simple Summary

Human bladder cancer, one of the most common cancers worldwide, is a molecularly heterogenous and complex disease. Identifying novel prognostic biomarkers and establishing new predictive signatures are important for personalized medicine and effective treatment of bladder cancer patients. Autophagy, a cell self-maintenance process that removes damaged organelles and misfolded proteins, displays both tumor promotion and suppression activities. The aim of our study is to investigate the function of autophagy-related genes in bladder cancer with the main focus on their contribution to prognostic outcome. By analyzing data obtained from The Cancer Genome Atlas (TCGA), we identified 32 autophagy-related genes that were highly associated with overall survival of bladder cancer patients. Further statistical assessment established an 11-autophagy-related-gene signature as an effective prognostic biomarker to predict the survival outcomes of bladder cancer patients.

Abstract

Background: Survival rates for highly invasive bladder cancer (BC) patients have been very low, with a 5-year survival rate of 6%. Accurate prediction of tumor progression and survival is important for diagnosis and therapeutic decisions for BC patients. Our study aims to develop an autophagy-related-gene (ARG) signature that helps to predict the survival of BC patients. Methods: RNA-seq data of 403 BC patients were retrieved from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database. Univariate Cox regression analysis was performed to identify overall survival (OS)-related ARGs. The Lasso Cox regression model was applied to establish an ARG signature in the TCGA training cohort (N = 203). The performance of the 11-gene ARG signature was further evaluated in a training cohort and an independent validation cohort (N = 200) using Kaplan-Meier OS curve analysis, receiver operating characteristic (ROC) analysis, as well as univariate and multivariate Cox regression analysis. Results: Our study identified an 11-gene ARG signature that is significantly associated with OS, including APOL1, ATG4B, BAG1, CASP3, DRAM1, ITGA3, KLHL24, P4HB, PRKCD, ULK2, and WDR45. The ARGs-derived high-risk bladder cancer patients exhibited significantly poor OS in both training and validation cohorts. The prognostic model showed good predictive efficacy, with the area under the ROC curve (AUCs) for 1-year, 3-year, and 5-year overall survival of 0.702 (0.695), 0.744 (0.640), and 0.794 (0.658) in the training and validation cohorts, respectively. A prognostic nomogram, which included the ARGs-derived risk factor, age and stage for eventual clinical translation, was established. Conclusion: We identified a novel ARG signature for risk-stratification and robust prediction of overall survival for BC patients.