Identification of TPD52 and DNAJB1 as two novel bile biomarkers for cholangiocarcinoma by iTRAQ‑based quantitative proteomics analysis

CircBIRC6 affects prostate cancer progression by regulating miR-574-5p and DNAJB1

BACKGROUND

Prostate cancer (PCa) is among the three main types of cancer. Although prostate-specific antigen (PSA) is routinely tested, it has disadvantages, such as poor prognostic ability. Therefore, finding more PCa markers and therapeutic targets remains a subject of study. CircRNAs have been found to have regulatory roles in various diseases, such as diabetes, Central Nervous System (CNS) neuropathy, etc. where their application in cancer is even more valuable. Therefore, this paper aims to search for differentially expressed circRNAs in PCa and find downstream targeting pathways related to autophagy.

METHOD

By detecting the expression of circRNA in the samples, hsa_circ_0119816 was finally identified as the research target. The properties of circRNA were verified by RNase R, actinomycin D, and fluorescence in situ hybridization (FISH). The downstream target miRNAs and target proteins were predicted by an online database, and the targeting relationship was verified using dual luciferase and RNA Immunoprecipitation. The effects of circRNAs and their downstream signalling pathways on prostate cancer cell proliferation, migration, EMT and autophagy were examined by CCK-8, Transwell, immunofluorescence and Western blotting.

RESULTS

CircBIRC6 is highly expressed in prostate cancer samples. Knockdown of its expression inhibits cell proliferation, invasion, EMT and autophagy and promotes apoptosis. CircBIRC6/miRNA-574-5p/DNAJB1 is a molecular axis that regulates prostate cancer cells.

Insight into the mechanism of gallstone disease by proteomic and metaproteomic characterization of human bile

Introduction

Cholesterol gallstone disease is a prevalent condition that has a significant economic impact. However, the role of the bile microbiome in its development and the host's responses to it remain poorly understood.

Methods

In this study, we conducted a comprehensive analysis of microbial and human bile proteins in 40 individuals with either gallstone disease or gallbladder polyps. We employed a combined proteomic and metaproteomic approach, as well as meta-taxonomic analysis, functional pathway enrichment, and Western blot analyses.

Results

Our metaproteomic analysis, utilizing the lowest common ancestor algorithm, identified 158 microbial taxa in the bile samples. We discovered microbial taxa that may contribute to gallstone formation, including β-glucuronidase-producing bacteria such as Streptococcus, Staphylococcus, and Clostridium, as well as those involved in biofilm formation like Helicobacter, Cyanobacteria, Pseudomonas, Escherichia coli, and Clostridium. Furthermore, we identified 2,749 human proteins and 87 microbial proteins with a protein false discovery rate (FDR) of 1% and at least 2 distinct peptides. Among these proteins, we found microbial proteins crucial to biofilm formation, such as QDR3, ompA, ndk, pstS, nanA, pfIB, and dnaK. Notably, QDR3 showed a gradual upregulation from chronic to acute cholesterol gallstone disease when compared to polyp samples. Additionally, we discovered other microbial proteins that enhance bacterial virulence and gallstone formation by counteracting host oxidative stress, including sodB, katG, rbr, htrA, and ahpC. We also identified microbial proteins like lepA, rtxA, pckA, tuf, and tpiA that are linked to bacterial virulence and potential gallstone formation, with lepA being upregulated in gallstone bile compared to polyp bile. Furthermore, our analysis of the host proteome in gallstone bile revealed enhanced inflammatory molecular profiles, including innate immune molecules against microbial infections. Gallstone bile exhibited overrepresented pathways related to blood coagulation, folate metabolism, and the IL-17 pathway. However, we observed suppressed metabolic activities, particularly catabolic metabolism and transport activities, in gallstone bile compared to polyp bile. Notably, acute cholelithiasis bile demonstrated significantly impaired metabolic activities compared to chronic cholelithiasis bile.

Conclusion

Our study provides a comprehensive metaproteomic analysis of bile samples related to gallstone disease, offering new insights into the microbiome-host interaction and gallstone formation mechanism.

Multi-Faceted Roles of DNAJB Protein in Cancer Metastasis and Clinical Implications

Heat shock proteins (HSPs) are highly conserved molecular chaperones with diverse cellular activities, including protein folding, assembly or disassembly of protein complexes, and maturation process under diverse stress conditions. HSPs also play essential roles in tumorigenesis, metastasis, and therapeutic resistance across cancers. Among them, HSP40s are widely accepted as regulators of HSP70/HSP90 chaperones and an accumulating number of biological functions as molecular chaperones dependent or independent of either of these chaperones. Despite large numbers of HSP40s, little is known about their physiologic roles, specifically in cancer progression. This article summarizes the multi-faceted role of DNAJB proteins as one subclass of the HSP40 family in cancer development and metastasis. Regulation and deregulation of DNAJB proteins at transcriptional, post-transcriptional, and post-translational levels contribute to tumor progression, particularly cancer metastasis. Furthermore, understanding differences in function and regulating mechanism between DNAJB proteins offers a new perspective on tumorigenesis and metastasis to improve therapeutic opportunities for malignant diseases.

Diagnosis Biomarkers of Cholangiocarcinoma in Human Bile: An Evidence-Based Study

Simple Summary

A liquid biopsy has the characteristics of low trauma and easy acquisition in the diagnosis of cholangiocarcinoma. Many researchers try to find diagnostic or prognostic biomarkers of CCA through blood, urine, bile and other body fluids. Due to the close proximity of bile to the lesion and the stable nature, bile gradually comes into people’s view. The evaluation of human bile diagnostic biomarkers is not only to the benefit of screening more suitable clinical markers but also of exploring the pathological changes of the disease.

Abstract

Cholangiocarcinoma (CCA) is a multifactorial malignant tumor of the biliary tract, and the incidence of CCA is increasing in recent years. At present, the diagnosis of CCA mainly depends on imaging and invasive examination, with limited specificity and sensitivity and late detection. The early diagnosis of CCA always faces the dilemma of lacking specific diagnostic biomarkers. Non-invasive methods to assess the degree of CAA have been developed throughout the last decades. Among the many specimens looking for CCA biomarkers, bile has gotten a lot of attention lately. This paper mainly summarizes the recent developments in the current research on the diagnostic biomarkers for CCA in human bile at the levels of the gene, protein, metabolite, extracellular vesicles and volatile organic compounds.

A seven-autophagy-related gene signature for predicting the prognosis of differentiated thyroid carcinoma

Background

Numerous studies have implicated autophagy in the pathogenesis of thyroid carcinoma. This investigation aimed to establish an autophagy-related gene model and nomogram that can help predict the overall survival (OS) of patients with differentiated thyroid carcinoma (DTHCA).

Methods

Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. We also downloaded autophagy-related genes (ARGs) from the Gene Set Enrichment Analysis website and the Human Autophagy Database. First, we assigned patients into training and testing groups. R software was applied to identify differentially expressed ARGs for further construction of a protein-protein interaction (PPI) network for gene functional analyses. A risk score-based prognostic risk model was subsequently developed using univariate Cox regression and LASSO-penalized Cox regression analyses. The model’s performance was verified using Kaplan-Meier (KM) survival analysis and ROC curve. Finally, a nomogram was constructed for clinical application in evaluating the patients with DTHCA. Finally, a 7-gene prognostic risk model was developed based on gene set enrichment analysis.

Results

Overall, we identified 54 differentially expressed ARGs in patients with DTHCA. A new gene risk model based on 7-ARGs (CDKN2A, FGF7, CTSB, HAP1, DAPK2, DNAJB1, and ITPR1) was developed in the training group and validated in the testing group. The predictive accuracy of the model was reflected by the area under the ROC curve (AUC) values. Univariate and multivariate Cox regression analysis indicated that the model could independently predict the prognosis of patients with THCA. The constrained nomogram derived from the risk score and age also showed high prediction accuracy.

Conclusions

Here, we developed a 7-ARG prognostic risk model and nomogram for differentiated thyroid carcinoma patients that can guide clinical decisions and individualized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02590-6.

Gene Expression Characteristics of Tumor and Adjacent Non-Tumor Tissues of Pancreatic Ductal Adenocarcinoma (PDAC) In-Silico

BACKGROUND

One of the deadliest and most prevalent cancer is pancreatic ductal adenocarcinoma (PDAC). Microarray has become an important tool in the research of PDAC genes and target therapeutic drugs.

OBJECTIVES

This study intends to clarify the promising prognostic and biomarker targets in PDAC using GSE78229 and GSE62452 datasets, publicly accessible at the Gene Expression Omnibus database.

MATERIALS AND METHODS

Utilizing GEOquery, Bio base, gplots, and ggplot2 packages in the R program, this study detects 428 differentially expressed genes that are further applied to build a co-expression network by the weighted correlation network analysis (WGCNA). The turquoise module presented a higher correlation with PDAC progression. 79 candidate genes were selected based on the co-expression and protein-protein interaction (PPI) networks. In addition, the functional enrichment analysis was studied.

RESULTS

Five significant KEGG pathways linked to PDAC were detected, in which the endoplasmic reticulum protein processing pathway was remarked to be vital. The resulting 19 hub genes as HSPA4, PABPC1, HSP90B1, PPP1CC, USP9X, EIF2S3, MSN, RAB10, BMPR2, P4HB, UBC, B2M, SLC25A5, MMP7, SPTBN1, RALB, DNAJB1, CENPE, and PDIA6 were identified by the Network Analyst web tool founded on PPI network by the STRING. These were identified as the most connected hub proteins. The quantification of the expression of levels and survival probabilities were analyzed overall survival (OS) of the real hub genes and were investigated by Kaplan-Meier (KM) plotter through The Cancer Genome Atlas Program (TCGA) database.

CONCLUSIONS

The protein-protein interactions and KEGG pathway enrichment by DAVID indicated that some pathways were involved in PDAC, such as "pathways in cancer (hsa05200)", "protein processing in the endoplasmic reticulum (hsa04141)", "antigen processing and presentation (hsa04612)", "dopaminergic synapse (hsa04728)", and "measles (hsa05162)"; in which these pathways, the "protein processing in endoplasmic reticulum (hsa04141)", was further studied because of its closely relationship with PDAC. The rest of the hub genes reviewed throughout the study might be promising targets for diagnosing and treating PDAC and relevant diseases.

Regulation of p53 and Cancer Signaling by Heat Shock Protein 40/J-Domain Protein Family Members

Heat shock proteins (HSPs) are molecular chaperones that assist diverse cellular activities including protein folding, intracellular transportation, assembly or disassembly of protein complexes, and stabilization or degradation of misfolded or aggregated proteins. HSP40, also known as J-domain proteins (JDPs), is the largest family with over fifty members and contains highly conserved J domains responsible for binding to HSP70 and stimulation of the ATPase activity as a co-chaperone. Tumor suppressor p53 (p53), the most frequently mutated gene in human cancers, is one of the proteins that functionally interact with HSP40/JDPs. The majority of p53 mutations are missense mutations, resulting in acquirement of unexpected oncogenic activities, referred to as gain of function (GOF), in addition to loss of the tumor suppressive function. Moreover, stability and levels of wild-type p53 (wtp53) and mutant p53 (mutp53) are crucial for their tumor suppressive and oncogenic activities, respectively. However, the regulatory mechanisms of wtp53 and mutp53 are not fully understood. Accumulating reports demonstrate regulation of wtp53 and mutp53 levels and/or activities by HSP40/JDPs. Here, we summarize updated knowledge related to the link of HSP40/JDPs with p53 and cancer signaling to improve our understanding of the regulation of tumor suppressive wtp53 and oncogenic mutp53 GOF activities.

Development and validation of an autophagy-related prognostic signature in esophageal cancer

Background

Autophagy has a dual function in cancer, and its role in carcinogenesis of the esophagus remains poorly understood. In the present study, we explored the prognostic value of autophagy in esophageal cancer (ESCA), one of the leading causes of cancer-related deaths worldwide.

Methods

Using ESCA RNA-sequencing (RNA-Seq) data from 158 primary patients with ESCA, including esophageal adenocarcinoma and esophageal squamous cell carcinoma, were downloaded from The Cancer Genome Atlas (TCGA) for this study. We obtained differentially expressed autophagy-related genes (ARGs) by the “limma” package of R. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses unveiled several fundamental signaling pathways associated with the differentially expressed ARGs in ESCA. Univariate Cox regression analyses were used to estimate associations between ARGs and overall survival (OS) in the TCGA ESCA cohort. A Cox proportional hazards model (iteration =1,000) with a lasso penalty was used to create the optimal multiple-gene prognostic signature utilizing an R package called “glmnet”.

Results

A prognostic signature was constructed with four ARGs (DNAJB1, BNIP1, VAMP7 and TBK1) in the training set, which significantly divided ESCA patients into high- and low-risk groups in terms of OS [hazard ratio (HR) =1.508, 95% confidence interval (CI): 1.201–1.894, P<0.001]. In the testing set, the risk score remained an independent prognostic factor in the multivariate analyses (HR =1.572, 95% CI: 1.096–2.257, P=0.014). The area under the curve (AUC) of the receiver operating characteristic (ROC) predicting 1-year survival showed a better predictive power for the prediction model. The AUC in training and testing cohorts were 0.746 and 0.691, respectively. Therefore, the prognostic signature of the four ARGs was successfully validated in the independent cohort.

Conclusions

The prognostic signature may be an independent predictor of survival for ESCA patients. The prognostic nomogram may improve the prediction of individualized outcome. This study also highlights the importance of autophagy in the outcomes of patients with ESCA.

A Prognostic Prediction Model Developed Based on Four CpG Sites and Weighted Correlation Network Analysis Identified DNAJB1 as a Novel Biomarker for Pancreatic Cancer

Background

The prognosis of pancreatic cancer, which is among the solid tumors associated with high mortality, is poor. There is a need to improve the overall survival rate of patients with pancreatic cancer.

Materials and Methods

The Cancer Genome Atlas (TCGA) dataset with 153 samples and the International Cancer Genome Consortium (ICGC) dataset with 235 samples were used as the discovery and validation cohorts, respectively. The least absolute shrinkage and selection operator regression was used to construct the prognostic prediction model based on the DNA methylation markers. The predictive efficiency of the model was evaluated based on the calibration curve, concordance index, receiver operating characteristic curve, area under the curve, and decision curve. The xenograft model and cellular functional experiments were used to investigate the potential role of DNAJB1 in pancreatic cancer.

Results

A prognostic prediction model based on four CpG sites (cg00609645, cg13512069, cg23811464, and cg03502002) was developed using TCGA dataset. The model effectively predicted the overall survival rate of patients with pancreatic cancer, which was verified in the ICGC dataset. Next, a nomogram model based on the independent prognostic factors was constructed to predict the overall survival rate of patients with pancreatic cancer. The nomogram model had a higher predictive value than TCGA or ICGC datasets. The low-risk group with improved prognosis exhibited less mutational frequency and high immune infiltration. The brown module with 247 genes derived from the WGCNA analysis was significantly correlated with the prognostic prediction model, tumor grade, clinical stage, and T stage. The bioinformatic analysis indicated that DNAJB1 can serve as a novel biomarker for pancreatic cancer. DNAJB1 knockdown significantly inhibited the proliferation, migration, and invasion of pancreatic cancer cells in vivo and in vitro.

Conclusion

The prognostic prediction model based on four CpG sites is a new method for predicting the prognosis of patients with pancreatic cancer. The molecular characteristic analyses, including Gene Ontology, Gene Set Enrichment Analysis, mutation spectrum, and immune infiltration of the subgroups, stratified by the model provided novel insights into the initiation and development of pancreatic cancer. DNAJB1 may serve as diagnostic and prognostic biomarkers for pancreatic cancer.

Pilot Multi-Omic Analysis of Human Bile from Benign and Malignant Biliary Strictures: A Machine-Learning Approach

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accuracy.

Role of Endoscopy in Primary Sclerosing Cholangitis

Primary sclerosing cholangitis (PSC) is a progressive disease of the bile ducts that usually results in chronic liver disease often requiring liver transplantation. Endoscopy remains crucial to the care of these patients, although magnetic resonance cholangiopancreatography has replaced endoscopic retrograde cholangiopancreatography (ERCP) as the primary imaging modality for diagnosis. For detection of dysplasia or cholangiocarcinoma, ERCP with intraductal sampling remains compulsory. Moreover, dominant strictures play an important part in the disease development, and management by balloon dilatation or stenting could contribute to long-term prognosis. In addition, endoscopy offers management for adverse events such as bile leaks and anastomotic strictures after liver transplantation. Finally, the special phenotype of inflammatory bowel disease associated with PSC as well as the frequent occurrence of portal hypertension mandates close follow-up with colonoscopy and upper endoscopy. With the emergence of novel techniques, the endoscopist remains a key member of the multidisciplinary team caring for PSC patients.