Prospective Study Using Plasma Apolipoprotein A2-Isoforms to Screen for High-Risk Status of Pancreatic Cancer. Cancers (Basel). 2020;12. [PMID: 32937962 PMCID: PMC7564617 DOI: 10.3390/cancers12092625]

The role of biomarkers in the early detection of pancreatic cancer

Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.

Clinical development of a blood biomarker using apolipoprotein-A2 isoforms for early detection of pancreatic cancer

BACKGROUND

We have previously reported apolipoprotein A2-isoforms (apoA2-is) as candidate plasma biomarkers for early-stage pancreatic cancer. The aim of this study was the clinical development of apoA2-is.

METHODS

We established a new enzyme-linked immunosorbent sandwich assay for apoA2-is under the Japanese medical device Quality Management System requirements and performed in vitro diagnostic tests with prespecified end points using 2732 plasma samples. The clinical equivalence and significance of apoA2-is were compared with CA19-9.

RESULTS

The point estimate of the area under the curve to distinguish between pancreatic cancer (n = 106) and healthy controls (n = 106) was higher for apoA2-ATQ/AT [0.879, 95% confidence interval (CI): 0.832-0.925] than for CA19-9 (0.849, 95% CI 0.793-0.905) and achieved the primary end point. The cutoff apoA2-ATQ/AT of 59.5 μg/mL was defined based on a specificity of 95% in 2000 healthy samples, and the reliability of specificities was confirmed in two independent healthy cohorts as 95.3% (n = 106, 95% CI 89.4-98.0%) and 95.8% (n = 400, 95% CI 93.3-97.3%). The sensitivities of apoA2-ATQ/AT for detecting both stage I (47.4%) and I/II (50%) pancreatic cancers were higher than those of CA19-9 (36.8% and 46.7%, respectively). The combination of apoA2-ATQ/AT (cutoff, 59.5 μg/mL) and CA19-9 (37 U/mL) increased the sensitivity for pancreatic cancer to 87.7% compared with 69.8% for CA19-9 alone. The clinical performance of apoA2-is was blindly confirmed by the National Cancer Institute Early Detection Research Network.

CONCLUSIONS

The clinical performance of ApoA2-ATQ/AT as a blood biomarker is equivalent to or better than that of CA19-9.

EphA2 Proteolytic Fragment as a Sensitive Diagnostic Biomarker for Very Early-stage Pancreatic Ductal Carcinoma

Cleavage of erythropoietin-producing hepatocellular ephrin receptor A2 (EphA2) triggers malignant progression and yields an N-terminal fragment (EphA2-NF) detectable in sera from patients with pancreatic ductal carcinoma. We established a quantitative automated chemiluminescence immunoassay for EphA2-NF and evaluated serum EphA2-NF levels as a biomarker to diagnose pancreatic ductal carcinoma in the test and validation cohorts. The EphA2-NF value was elevated (above the cutoff: mean ± SD) in more than half of the patients with stage I/II pancreatic ductal carcinoma. Among patients receiving standard chemotherapy for pancreatic ductal carcinoma [gemcitabine plus nab-paclitaxel (GnP)], the median survival time of patients with elevated serum EphA2-NF was half that of patients with values below the cutoff. Patients with intraductal papillary mucinous neoplasm (IPMN), a precancerous pancreatic ductal carcinoma lesion, also show high serum EphA2 levels, which are associated with an increase in pancreatic duct size and the development of pancreatic ductal carcinoma in some cases. IHC showed loss of EphA2-NF staining in IPMN with pancreatic ductal carcinoma, but not in the normal epithelium or IPMN without pancreatic ductal carcinoma, regardless of the histologic grade. These results suggest that EphA2 cleavage is an essential event that occurs very early in pancreatic ductal carcinoma development, and that the consequent release of EphA2-NF can be detected in the serum. Thus, serum EphA2-NF could be a diagnostic biomarker for very early-stage pancreatic ductal carcinoma and pancreatic ductal carcinoma development from high-risk IPMN and as a prognostic biomarker after chemotherapy with GnP.

SIGNIFICANCE

EphA2 N-terminus deletion is involved in pancreatic ductal carcinoma development from high-risk IPMN and EphA2-NF produced by cleavage can be used as a serum biomarker to diagnose pancreatic ductal carcinoma and predict pancreatic ductal carcinoma development from high-risk IPMN.

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis.

Methods

To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis.

Results

A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results.

Conclusions

On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

Apolipoproteins: New players in cancers

Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.

Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers around the world. Precision oncology will be crucial for further improving the prognosis of HCC patients. Compared with traditional bulk RNA-seq, single-cell RNA sequencing (scRNA-seq) enables the transcriptomes of a great deal of individual cells assayed in an unbiased manner, showing the potential to deeply reveal tumor heterogeneity. In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. Expression profiles of HCC cells and normal liver cells were first analyzed by maximum relevance minimum redundancy (mRMR) to get a top 50 signature gene feature. For further analysis, the incremental feature selection (IFS) method and leave-one-out cross validation (LOOCV) were conducted to build an optimal classification model and to extract 21 potentially essential biomarkers for HCC cells. Our results provided new insights into HCC pathogenesis that might be valuable for HCC diagnosis and therapy.

Risk stratification of pancreatic cancer by a blood test for apolipoprotein A2-isoforms

Though pancreatic cancer is uncommon, with an age-adjusted annual incidence of 12.9 cases per 100,000 person-years, it is considered a refractory cancer due to the mortality of 11.0 per 100,000 person-years. To efficiently identify patients with potentially surgically-curable pancreatic cancer, high-risk individuals (HRIs) for pancreatic cancer should be identified by easily and minimally invasive methods from the general population. We have identified unique processing patterns in the C-terminal amino acids of apolipoprotein A2 homodimer in the blood of patients with pancreatic cancer and in HRIs, and we called them apoA2-isoforms (apoA2-i). We then established an enzyme-linked immunosorbent assay (ELISA) to measure circulating apoA2-i in the blood stream. The diagnostic accuracy of apoA2-i to distinguish pancreatic cancer HRIs was verified by several retrospective studies, blind testing with the National Cancer Institute (NCI) Early Detection Research Network (EDRN), a prospective study with prediagnostic samples organized by the European Prospective Investigation into Cancer and Nutrition (EPIC) study, and the prospective screening study of pancreatic cancer in Kobe.The apoA2-i blood test is a potential biomarker to identify HRIs and the curative stage of pancreatic cancer in the general population.

Noninvasive risk stratification of intraductal papillary mucinous neoplasia with malignant potential by serum apolipoprotein-A2-isoforms

Intraductal papillary mucinous neoplasms (IPMNs) are premalignant lesions of pancreatic cancer. An accurate serum biomarker, which allows earlier identification of asymptomatic individuals with high-risk for developing cancer, is of urgent need. Apolipoprotein A2-isoforms (apoA2-i) have previously been identified as biomarkers in pancreatic cancer. This study investigates a potential clinical application of the serum apoA2-i for risk stratification of IPMN and associated cancer. The concentrations of apoA2-i were retrospectively determined in 523 patient sera specimen, composed of 305 IPMNs with preinvasive lesions with different grades of dysplasia and invasive cancer, 140 pancreatic ductal adenocarcinoma, 78 with other cystic lesions and healthy controls cohorts, using an apoA2-i enzyme-linked immunosorbent assay kit. The diagnostic performance of serum apoA2-i was assessed and compared to routine clinical marker CA 19-9. ApoA2-i levels were significantly reduced in all IPMN samples regardless of stage compared to healthy controls. Receiver operating characteristic curve analysis of IPMNs with high-grade dysplasia and IPMN with associated carcinoma revealed the area under curve (AUC) of 0.91 and >0.94, respectively. The respective sensitivities were 70% and 83% with a specificity of 95%, and significantly higher than the gold standard biomarker CA 19-9. AUC values of apoA2-i for detecting IPMN-associated carcinoma of colloid and ductal subtypes were 0.990 and 0.885, respectively. ApoA2-i has the potential to early detect the risk of malignancy of patients with IPMN. The serological apoA2-i test in combination with imaging modalities could help improve the diagnosis of IPMN malignancy. Further validation in larger and independent international cohort studies is needed.

Five genes involved in circular RNA-associated competitive endogenous RNA network correlates with metastasis in papillary thyroid carcinoma

This study aimed to identify potential circular RNA (circRNA), microRNA (miRNA) and mRNA biomarkers as well as their underlying regulatory mechanisms in papillary thyroid carcinoma (PTC). Three microarray datasets from the Gene Expression Omnibus database as well as expression data and clinical phenotype from The Cancer Genome Atlas (TCGA) were downloaded, followed by differential expression, functional enrichment, protein-protein interaction (PPI), and module analyses. The support vector machine (SVM)-recursive feature elimination (RFE) algorithm was used to screen the key circRNAs. Finally, the mRNA-miRNA-circRNA regulatory network and competitive endogenous RNA (ceRNA) network were constructed. The prognostic value and clinical correlations of key mRNAs were investigated using TCGA dataset, and their expression was validated using the UALCAN database. A total of 1039 mRNAs, 18 miRNAs and 137 circRNAs were differentially expressed in patients with PTC. A total of 37 key circRNAs were obtained using the SVM-RFE algorithm, whereas 46 key mRNAs were obtained from significant modules in the PPI network. A total of 11 circRNA-miRNA pairs and 40 miRNA-mRNA pairs were predicted. Based on these interaction pairs, 46 circRNA-miRNA-mRNA regulatory pairs were integrated, of which 8 regulatory pairs in line with the ceRNA hypothesis were obtained, including two circRNAs (circ_0004053 and circ_0028198), three miRNAs (miR-199a-5p, miR-199b-5p, and miR-7-5p), and five mRNAs, namely APOA2, CCL20, LPAR5, MFGE8, and TIMP1. Survival analysis showed that LPAR5 expression was associated with patient survival. APOA2 expression showed significant differences between metastatic and non-metastatic tumors, whereas CCL20, LPAR5, MFGE8 and TIMP1 showed significant differences between metastatic and non-metastatic lymph nodes. Overall, we identified several potential targets and regulatory mechanisms involved in PTC. APOA2, CCL20, LPAR5, MFGE8, and TIMP1 may be correlated with PTC metastasis.

Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?

Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).