Diagnostic Value of CA 19-9 and Carcinoembryonic Antigen for Pancreatic Cancer: A Meta-Analysis. Gastroenterol Res Pract. 2018;2018:8704751. [PMID: 30584422 PMCID: PMC6280291 DOI: 10.1155/2018/8704751]

An updated review on the development of a nanomaterial-based field-effect transistor-type biosensors to detect exosomes for cancer diagnosis

Cancer, a life-threatening genetic disease caused by abnormalities in normal cell growth regulatory functions, poses a significant challenge that current medical technologies cannot fully overcome. The current desired breakthrough is to diagnose cancer as early as possible and increase survival rates through treatments tailored to the prognosis and appropriate follow-up. From a perspective that reflects this contemporary paradigm of cancer diagnostics, exosomes are emerging as promising biomarkers. Exosomes, serving as mobile biological information repositories of cancer cells, have been known to create a microtumor environment in surrounding cells, and significant insight into the clinical significance of cancer diagnosis targeting them has been reported. Therefore, there are growing interests in constructing a system that enables continuous screening with a focus on patient-friendly and flexible diagnosis, aiming to improve cancer screening rates through exosome detection. This review focuses on a proposed exosome-embedded biological information-detecting platform employing a field-effect transistor (FET)-based biosensor that leverages portability, cost-effectiveness, and rapidity to minimize the stages of sacrifice attributable to cancer. The FET-applied biosensing technique, stemming from variations in an electric field, is considered an early detection system, offering high sensitivity and a prompt response frequency for the qualitative and quantitative analysis of biomolecules. Hence, an in-depth discussion was conducted on the understanding of various exosome-based cancer biomarkers and the clinical significance of recent studies on FET-based biosensors applying them.

Detection of Tumor-Associated Autoantibodies in the Sera of Pancreatic Cancer Patients Using Engineered MUC1 Glycopeptide Nanoparticle Probes

Pancreatic cancer is one of the deadliest cancers worldwide, mainly due to late diagnosis. Therefore, there is an urgent need for novel diagnostic approaches to identify the disease as early as possible. We have developed a diagnostic assay for pancreatic cancer based on the detection of naturally occurring tumor associated autoantibodies against Mucin-1 (MUC1) using engineered glycopeptides on nanoparticle probes. We used a structure-guided approach to develop unnatural glycopeptides as model antigens for tumor-associated MUC1. We designed a collection of 13 glycopeptides to bind either SM3 or 5E5, two monoclonal antibodies with distinct epitopes known to recognize tumor associated MUC1. Glycopeptide binding to SM3 or 5E5 was confirmed by surface plasmon resonance and rationalized by molecular dynamics simulations. These model antigens were conjugated to gold nanoparticles and used in a dot-blot assay to detect autoantibodies in serum samples from pancreatic cancer patients and healthy volunteers. Nanoparticle probes with glycopeptides displaying the SM3 epitope did not have diagnostic potential. Instead, nanoparticle probes displaying glycopeptides with high affinity for 5E5 could discriminate between cancer patients and healthy controls. Remarkably, the best-discriminating probes show significantly better true and false positive rates than the current clinical biomarkers CA19-9 and carcinoembryonic antigen (CEA).

Misdiagnosis Based on Neoplastic Markers-Extremely High Alpha-Fetoprotein in Patients with Intrahepatic Cholangiocarcinoma with Literature Review of the Published Cases

Background: Alpha-fetoprotein (AFP) and carbohydrate antigen 19-9 (CA 19-9) are two tumor markers that are widely used in the differential diagnosis in patients with primary liver tumors. Very high levels of AFP are sporadically observed in patients with intrahepatic cholangiocarcinoma (ICC) and may cause an incorrect initial diagnosis of hepatocellular carcinoma (HCC). Methods: Two cases of tumors in cirrhotic livers were described, in which the initial diagnosis, based on very high AFP levels (Patient I: 10,464 ng/mL, Patient II: 2212 ng/mL, reference range: ≤8.04 ng/mL) was HCC. In addition, the PubMed database was searched for cases of ICC with elevated AFP. Discussion: In both individuals, liver cirrhosis was diagnosed, but there was no typical rapid "washout" in the contrast-enhanced computed tomography. Based on the histological assessment of samples obtained in the core biopsies, the initially assumed diagnosis of HCC was changed to ICC in both cases. Only nine cases of patients with ICC and high AFP levels were found in the PubMed database. The AFP levels ranged from slightly elevated to over 16,000 ng/mL. Conclusions: A very high AFP level does not necessarily correlate with the presence of HCC. Therefore, the diagnosis has to be verified histologically, when the radiological imaging is uncertain in patients with liver cirrhosis.

Pancreatic ductal adenocarcinoma: the latest on diagnosis, molecular profiling, and systemic treatments

Pancreatic ductal adenocarcinoma (PDAC) is currently the fourth leading cause of death in the United States and is expected to be ranked second in the next 10 years due to poor prognosis and a rising incidence. Distant metastatic PDAC is associated with the worst prognosis among the different phases of PDAC. The diagnostic options for PDAC are convenient and available for staging, tumor response evaluation, and management of resectable or borderline resectable PDAC. However, imaging is crucial in PDAC diagnosis, monitoring, resectability appraisal, and response evaluation. The advancement of medical technologies is evolving, hence the use of imaging in PDAC treatment options has grown as well as the utilization of ctDNA as a tumor marker. Treatment options for metastatic PDAC are minimal with the primary goal of therapy limited to symptom relief or palliation, especially in patients with low functional capacity at the point of diagnosis. Molecular profiling has shown promising potential solutions that would push the treatment boundaries for patients with PDAC. In this review, we will discuss the latest updates from evidence-based guidelines regarding diagnosis, therapy response evaluation, prognosis, and surveillance, as well as illustrating novel therapies that have been recently investigated for PDAC, in addition to discussing the molecular profiling advances in PDAC.

Highly sensitive serum volatolomic biomarkers for pancreatic cancer diagnosis

The discovery of new diagnostic tools for the early detection of diseases with poor prognosis such as pancreatic adenocarcinoma (PAC) is of high importance. The results from a control-case study (20 PAC patients, 19 healthy controls) for the search of new biomarkers of pancreatic cancer based in differences in the serum volatolome are presented in this work. Volatolomics were performed following a non-targeted HS-SPME-GC/MS approach, and a total of 433 volatile organic compounds (VOCs) was detected in the human serum samples. Of these, 125 VOC indexes showed a significant variation when controls and patients were compared (p-value < 0.05). Bonferroni corrected p-values < 0.05 were found for 40 features. PCA analysis showed the control-PAC discrimination capability of VOCs in serum, and PLS-DA was performed to select the best candidate biomarkers for the diagnosis of PAC. For the 40 selected VOCs, calculated areas under the curve (AUC) ranged from 0.98 to 0.85, and 11 of them were successfully validated using an independent set of samples (5 PAC patients, 5 healthy controls). Four of the proposed PAC biomarkers were identified as toluene, 2-ethyl-1-hexanol, pentylbenzene, and butoxymethylbenzene. Combinations of the identified PAC biomarkers were tested and showed AUC > 0.90, with the more promising candidate being butoxymethylbenzene (AUC = 0.98).

Circulating cell-free DNA methylation-based multi-omics analysis allows early diagnosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a 5-year survival rate of 7.2% in China. However, effective approaches for diagnosis of PDAC are limited. Tumor-originating genomic and epigenomic aberration in circulating free DNA (cfDNA) have potential as liquid biopsy biomarkers for cancer diagnosis. Our study aims to assess the feasibility of cfDNA-based liquid biopsy assay for PDAC diagnosis. In this study, we performed parallel genomic and epigenomic profiling of plasma cfDNA from Chinese PDAC patients and healthy individuals. Diagnostic models were built to distinguish PDAC patients from healthy individuals. Cancer-specific changes in cfDNA methylation landscape were identified, and a diagnostic model based on six methylation markers achieved high sensitivity (88.7% for overall cases and 78.0% for stage I patients) and specificity (96.8%), outperforming the mutation-based model significantly. Moreover, the combination of the methylation-based model with carbohydrate antigen 19-9 (CA19-9) levels further improved the performance (sensitivity: 95.7% for overall cases and 95.5% for stage I patients; specificity: 93.3%). In conclusion, our findings suggest that both methylation-based and integrated liquid biopsy assays hold promise as non-invasive tools for detection of PDAC.

Identification of Transcriptomic Signatures of Pancreatic Ductal Adenocarcinoma-Derived Exosomes That Promote Macrophage M2 Polarization and Predict Prognosis: S100A9 Reveals Tumor Progression

Background

Exosomes play a role in intercellular communication and participate in the interaction between pancreatic ductal adenocarcinoma (PDAC) cells and immune cells. Macrophages can receive tumor cell-derived exosomes to polarize into M2-type macrophages, which can enhance the invasion and metastasis of pancreatic cancer, leading to poor prognosis. However, the mechanism by which pancreatic cancer cell-derived exosomes promote M2-type macrophages is still unclear.

Methods

M2 macrophage-associated exosome-derived key module genes were identified by differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) analysis using exoRbase 2.0, The Cancer Genome Atlas (TCGA), and The International Cancer Genome Consortium (ICGC) databases. Multivariate Cox regression analysis was used to identify key prognostic genes and obtain regression coefficients to establish prognostic signature. Immune infiltration, tumor mutations, and GSEA among different risk groups were compared. exoRbase 2.0, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), HPA, and TISCH2 databases were used to further analyze the expression pattern of S100A9 in pancreatic cancer. In vitro experiments, cell-derived exosome isolation, quantitative polymerase chain reaction (qPCR), western blot, flow cytometry analysis, cell transfection, transwell assay, and CCK-8 assay were applied to investigate the roles of S100A9 in macrophage M2 polarization and tumor progression.

Results

The key genes of PDAC-derived exosomes promoting M2-type macrophage polarization were identified, and a risk score model was established. The risk score is related to the expression of common immune checkpoints, immune score, and stromal score, and the tumor mutational burden and biological function of high- and low-risk groups were also different. S100A9 was positively correlated with M2-type macrophage marker. In addition, scRNA-seq data from the TISCH2 database revealed that S100A9 is predominantly expressed in pancreatic cancer cells and mono/macrophage cells, suggesting that S100A9 in pancreatic cancer cells could be received by macrophages, thereby inducing macrophage polarization. In vitro, we used exosomes from BxPC-3 cell lines to coculture macrophages and found that macrophages were mainly polarized toward M2 type, which further promoted the proliferation and metastasis of PDAC.

Conclusions

Our study established a reliable risk score model for PDAC-derived exosomes and M2 macrophages, identified the important role of S100A9 in macrophage M2 polarization, which provides a new strategy for the diagnosis and treatment of PDAC, and strengthened the understanding of the mechanism of tumor development and metastasis.

Highly accurate diagnosis of pancreatic cancer by integrative modeling using gut microbiome and exposome data

The noninvasive detection of pancreatic ductal adenocarcinoma (PDAC) remains an immense challenge. In this study, we proposed a robust, accurate, and noninvasive classifier, namely Multi-Omics Co-training Graph Convolutional Networks (MOCO-GCN). It achieved high accuracy (0.9 ± 0.06), F1 score (0.9± 0.07), and AUROC (0.89± 0.08), surpassing contemporary approaches. The performance of model was validated on an external cohort of German PDAC patients. Additionally, we discovered that the exposome may impact PDAC development through its complex interplay with gut microbiome by mediation analysis. For example, Fusobacterium hwasookii nucleatum, known for its ability to induce inflammatory responses, may serve as a mediator for the impact of rheumatoid arthritis on PDAC. Overall, our study sheds light on how exposome and microbiome in concert could contribute to PDAC development, and enable PDAC diagnosis with high fidelity and interpretability.

Postbiotic butyrate: role and its effects for being a potential drug and biomarker to pancreatic cancer

Postbiotics are produced by microbes and have recently gained importance in the field of oncology due to their beneficial effects to the host, effectiveness against cancer cells, and their ability to suppress inflammation. In particular, butyrate dominates over all other postbiotics both in quantity and anticancer properties. Pancreatic cancer (PC), being one of the most malignant and lethal cancers, reported a decreased 5-year survival rate in less than 10% of the patients. PC causes an increased mortality rate due to its inability to be detected at an early stage but still a promising strategy for its diagnosis has not been achieved yet. It is necessary to diagnose Pancreatic cancer before the metastatic progression stage. The available blood biomarkers lack accurate and proficient diagnostic results. Postbiotic butyrate is produced by gut microbiota such as Rhuminococcus and Faecalibacterium it is involved in cell signalling pathways, autophagy, and cell cycle regulation, and reduction in butyrate concentration is associated with the occurrence of pancreatic cancer. The postbiotic butyrate is a potential biomarker that could detect PC at an early stage, before the metastatic progression stage. Thus, this review focused on the gut microbiota butyrate's role in pancreatic cancer and the immuno-suppressive environment, its effects on histone deacetylase and other immune cells, microbes in major butyrate synthesis pathways, current biomarkers in use for Pancreatic Cancer.

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.

Diagnostic plasma small extracellular vesicles miRNA signatures for pancreatic cancer using machine learning methods

BACKGROUND

Identifying biomarkers may lead to easier detection and a better understanding of pathogenesis of pancreatic ductal adenocarcinoma (PDAC).

METHODS

Plasma small extracellular vesicles (sEV) from 106 participants, including 20 healthy controls (HC), 12 chronic pancreatitis (CP) patients, 12 benign pancreatic tumour (BPT) patients, and 58 PDAC patients, were profiled for microRNA (miRNA) sequencing. Three machine learning methods were applied to establish and evaluate the diagnostic model.

RESULTS

The plasma sEV miRNA diagnostic signature (d-signature) selected using the three machine learning methods could distinguish PDAC patients from non-PDAC individuals, HC, and benign pancreatic disease (BPD, CP plus BPT) both in training and validation cohort. Combining the d-signature with carbohydrate antigen 19-9 (CA19-9) performed better than with each model alone. Plasma sEV miR-664a-3p was selected by all methods and used to predict PDAC diagnosis with high accuracy combined with CA19-9. Plasma sEV miR-664a-3p was significantly positively associated with the presence of vascular invasion, lower surgery ratio, and poor differentiation. MiR-664a-3p was mainly distributed in the PDAC cancer stroma, including fibers and vessels, and was accompanied by VEGFA expression. Overexpression of miR-664a-3p could promote the epithelial-mesenchymal transition (EMT) and angiogenesis.

CONCLUSION

In conclusion, our study demonstrated the potential utility of the sEV-miRNA d-signature in the diagnosis of PDAC via machine learning methods. A novel sEV biomarker, miR-664a-3p, was identified for the diagnosis of PDAC. It can also potentially promote angiogenesis and metastasis, provide insight into PDAC pathogenesis, and reveal novel regulators of this disease.

Raman spectroscopy and Raman optical activity of blood plasma for differential diagnosis of gastrointestinal cancers

Improving the early diagnosis of gastrointestinal cancers is a crucial step in reducing their mortality. Given the non-specificity of the initial symptoms, the ability of any diagnostic method to differentiate between various types of gastrointestinal cancers also needs to be addressed. To detect disease-specific alterations in biomolecular structure and composition of the blood plasma, we have implemented an approach combining Raman spectroscopy and its conformation-sensitive polarized version, Raman optical activity, to analyze blood plasma samples of patients suffering from three different types of gastrointestinal cancer - hepatocellular, colorectal and pancreatic. First, we aimed to discriminate any type of gastrointestinal cancer from healthy control individuals; inthenext step, the focus was on differentiating among the three cancer types studied. The more straightforward of the two statistical approaches tested, the combination of linear discriminant analysis and principal component analysis applied to the entire spectral dataset, allowed the discrimination of cancer and control samples with 87% accuracy. The three gastrointestinal cancers were classified with an overall accuracy of 76%. The second method, the linear discriminant analysis applied to a selection of spectral bands, yielded even higher values. Cancer and control samples were distinguished with 89% accuracy and hepatocellular, colorectal and pancreatic cancer with an overall accuracy of 87%. The results obtained in our study suggest that the proposed approach may become a disease-specific diagnostic tool in daily clinical practice.

Evaluations of the combined use of blood- and tissue-based protein biomarkers for pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a low 5-year survival rate. Biomarkers may be of value for the early diagnosis of pancreatic cancer. This study assessed blood- and tumour tissue-based biomarkers associated with pancreatic cancer.

METHODS

We studied 61 patients who underwent pancreatic resection. Of these 61 patients, 46 patients had PDAC, and 15 patients had inflammatory tumours. Blood and tumour tissue levels of VEGF, hypoxia-inducible factor 1α (HIF-1α) and glucose transporter 1 (GLUT1) were measured.

RESULTS

Blood concentrations of VEGF (p < 0.000001) and HIF-1α (p = 0.000002) were significantly higher in the PDAC group than in the inflammatory tumour group. Tumour tissue concentrations of VEGF (p < 0.000001), HIF-1α (p = 0.000005) and GLUT1 (0.000002) were also significantly higher in the PDAC group. Univariate analyses revealed that age, BMI, and blood levels of CA19-9, VEGF, and HIF-1α were potential predictors of PDAC. Potential predictors of PDAC in tumour tissue were VEGF, HIF-1α and GLUT1. Multivariate analyses found that VEGF was the most powerful independent predictor of PDAC in blood (OR = 1.016; 95% CI: 1.007-1.025; 0.001) and tumour tissue (OR = 1.02; 95% CI: 1.008-1.032, p = 0.001). The cut-off point for blood VEGF was 134.56 pg/ml, with a sensitivity of 97.8%, specificity of 86.7%, PPV of 95.7%, and NPV of 92.9%. The cut-off point for tissue tumour VEGF in PDAC was 208.59 pg/mg, with a sensitivity, specificity, PPV and NPV of 97.7%, 92.9%, 97.7%, and 92.9%, respectively.

CONCLUSIONS

There are significant differences in blood-based biomarkers for differentiating between PDAC and inflammatory tumours of the pancreas. VEGF was an independent predictor of PDAC independent of its addition to the routinely used tumour marker CA19-9 antigen.

An integrated computational biology approach defines the crucial role of TRIP13 in pancreatic cancer

Pancreatic cancer (PanCa) is one of the most aggressive forms of cancer and its incidence rate is continuously increasing every year. It is expected that by 2030, PanCa will become the 2nd leading cause of cancer-related deaths in the United States due to the lack of early diagnosis and extremely poor survival. Despite great advancements in biomedical research, there are very limited early diagnostic modalities available for the early detection of PanCa. Thus, understanding of disease biology and identification of newer diagnostic and therapeutic modalities are high priority. Herein, we have utilized high dimensional omics data along with some wet laboratory experiments to decipher the expression level of hormone receptor interactor 13 (TRIP13) in various pathological staging including functional enrichment analysis. The functional enrichment analyses specifically suggest that TRIP13 and its related oncogenic network genes are involved in very important patho-physiological pathways. These analyses are supported by qPCR, immunoblotting and IHC analysis. Based on our study we proposed TRIP13 as a novel molecular target for PanCa diagnosis and therapeutic interventions. Overall, we have demonstrated a crucial role of TRIP13 in pathogenic events and progression of PanCa through applied integrated computational biology approaches.

[Sarcopenia in patients with pancreatic cancer, an independant prognostic factor]

BACKGROUND

Pancreatic cancer is despite modern diagnostic tools and treatment regimen associated with poor outcome. Many patients show cachexia and sarcopenia.

METHODS

In a retrospective analysis the SMI (cm²/m²) was measured by determining the skelettal muscle area in a computed tomography image at lumbar vertebrae 3. Further clinical parameters were measured to determine the outcome.

RESULTS

The mean survival after diagnosis in the population with sarcopenia was significantly lower (14,4 vs 17,7 months, p=0,046). Significantly shorter survival was also seen for higher age (p=0,006), no tumor resection (p=0,004), metastases (p=0,002) and high CA19-9 level (p=0,002) CONCLUSION: Sarcopenia is an indipendant prognostic factor in patients with pancreatic cancer. SMI should be measured clinical practice and further studies are necessary to asses a potential therapeutic strategy.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Development of a metabolite calculator for diagnosis of pancreatic cancer

BACKGROUND

Carbohydrate antigen (CA) 19-9 is a known pancreatic cancer (PC) biomarker, but is not commonly used for general screening due to its low sensitivity and specificity. This study aimed to develop a serum metabolites-based diagnostic calculator for detecting PC with high accuracy.

METHODS

A targeted quantitative approach of direct flow injection-tandem mass spectrometry combined with liquid chromatography-tandem mass spectrometry was employed for metabolomic analysis of serum samples using an Absolute IDQ™ p180 kit. Integrated metabolomic analysis was performed on 241 pooled or individual serum samples collected from healthy donors and patients from nine disease groups, including chronic pancreatitis, PC, other cancers, and benign diseases. Orthogonal partial least squares discriminant analysis (OPLS-DA) based on characteristics of 116 serum metabolites distinguished patients with PC from those with other diseases. Sparse partial least squares discriminant analysis (SPLS-DA) was also performed, incorporating simultaneous dimension reduction and variable selection. Predictive performance between discrimination models was compared using a 2-by-2 contingency table of predicted probabilities obtained from the models and actual diagnoses.

RESULTS

Predictive values obtained through OPLS-DA for accuracy, sensitivity, specificity, balanced accuracy, and area under the receiver operating characteristic curve (AUC) were 0.9825, 0.9916, 0.9870, 0.9866, and 0.9870, respectively. The number of metabolite candidates was narrowed to 76 for SPLS-DA. The SPLS-DA-obtained predictive values for accuracy, sensitivity, specificity, balanced accuracy, and AUC were 0.9773, 0.9649, 0.9832, 0.9741, and 0.9741, respectively.

CONCLUSIONS

We successfully developed a 76 metabolome-based diagnostic panel for detecting PC that demonstrated high diagnostic performance in differentiating PC from other diseases.

Approach to Pancreatic Head Mass in the Background of Chronic Pancreatitis

Chronic pancreatitis (CP) is a known risk factor for pancreatic cancer. CP may present with an inflammatory mass, and differentiation from pancreatic cancer is often difficult. Clinical suspicion of malignancy dictates a need for further evaluation for underlying pancreatic cancer. Imaging modalities remain the mainstay of evaluation for a mass in background CP; however, they have their shortcomings. Endoscopic ultrasound (EUS) has become the go-to investigation. Adjunct modalities such as contrast-harmonic EUS and EUS elastography, as well as EUS-guided sampling using newer-generation needles are useful in differentiating inflammatory from malignant masses in the pancreas. Paraduodenal pancreatitis and autoimmune pancreatitis often masquerade as pancreatic cancer. In this narrative review, we discuss the various modalities used to differentiate inflammatory from malignant masses of the pancreas.

Fungi and cancer

The microbiome may impact cancer development, progression and treatment responsiveness, but its fungal components remain insufficiently studied in this context. In this review, we highlight accumulating evidence suggesting a possible involvement of commensal and pathogenic fungi in modulation of cancer-related processes. We discuss the mechanisms by which fungi can influence tumour biology, locally by activity exerted within the tumour microenvironment, or remotely through secretion of bioactive metabolites, modulation of host immunity and communications with neighbouring bacterial commensals. We examine prospects of utilising fungi-related molecular signatures in cancer diagnosis, patient stratification and assessment of treatment responsiveness, while highlighting challenges and limitations faced in performing such research. In all, we demonstrate that fungi likely constitute important members of mucosal and tumour-residing microbiomes. Exploration of fungal inter-kingdom interactions with the bacterial microbiome and the host and decoding of their causal impacts on tumour biology may enable their harnessing into cancer diagnosis and treatment.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

Can combined use of tumor markers in pancreatic cancer be a solution to short- and long-term consequences?: A retrospective study

As in other types of cancer, tumor markers are used in pancreatic ductal adenocarcinoma (PDAC) for disease follow-up, especially after surgery. There has been shown to be a significant correlation between the tumor marker levels and poor prognosis in locally or systemic advanced stage PDAC patients. However, there is no significant correlation between prognosis and marker levels in patients with early stage PDAC patients. This study aimed to examine the effect of the carbohydrate antigen 19-9 (Ca19-9)/carcinoembryogenic antigen (CEA) ratio in ductal adenocarcinoma of the pancreatic head on disease prognosis and mean survival. This retrospective study was conducted with 129 pancreatic head adenocarcinoma patients who were treated with whipple procedure at the Ankara University Surgical Oncology Clinic between 2010 and 2020. All patients' demographics, stage of the disease, CEA, CA 19-9 levels, and CEA/Ca 19-9 ratio were enrolled and compared statistically. A new cutoff value was calculated for the Ca19-9/CEA ratio. A Ca19-9/CEA ratio >29.77 showed 69.9% sensitivity and 70.9% specificity for the probability of the T3 and T4 stages. The cutoff value for the Ca19-9/CEA ratio was 27.18. This cutoff value had a sensitivity of 79.4% and a specificity of 80.3% for lymph node metastasis. Patients with a Ca19-9/CEA ratio below the cutoff value of 28.475 had a mean survival of 93.161 months and those with a value higher than the cutoff value had a mean survival of 28.541 months (P < .001). A simple combination of tumor markers was determined to have higher accuracy rates in predicting tumor prognosis and in determining mean survival, which are particularly needed in early stage cancers.

Prognostic Relevance of PDL1 and CA19-9 Expression in Gallbladder Cancer vs. Inflammatory Lesions

Chronic inflammation in the gallbladder leading to persistent epithelium damage promotes invasive cancer. The study aimed to assess the prognostic value of PDL1 and CA19-9 markers in cancer/inflammatory lesions of the gallbladder. A total of 29 cases (19 cancer and 10 inflammatory) were included. The PDL1 protein concentration level and mRNA expression were assessed in the tissues' lysates by ELISA and real-time PCR, respectively. PDL1 and CA19-9 concentration levels were compared and statistically related with clinico-pathological variables. The PDL1 protein level and its relative mRNA expression were correlated. Kaplan-Meir survival and Cox regression analyses were conducted for predicting prognosis. This study investigated the PDL1 and CA19-9 marker expression in both cancer and inflammatory cases of the gallbladder (p = 0.48 and p = 0.17 respectively). PDL1 protein expression was significantly associated with the hormonal profile of the cases (p = 0.04) at an optimum cut-off value of 13 pg/mL, while the CA19-9 marker expression was correlated with the status of liver metastasis (p = 0.0043) and size of the tumor (p = 0.004). A low PDL1 concentration was found when compared to the CA19-9 level among cancer cases (p = 0.12) and proportional in the inflammatory lesions (p = 0.63). A significant positive correlation was found between the PDL1 protein and its relative mRNA expressions in the inflammatory lesions (p = 0.029) when compared to cancer cases (p = 0.069). Our results showed that a protein-based assay for PDL1 expression would be more sensitive compared to RNA based assays for GBC risk stratifications. Overall survival was predicted with CA19-9 and PDL1 levels (p = 0.0074, p = 0.23, respectively). PDL1 and CA19-9 may act as a probable predictor of a poor prognosis in gallbladder cancer (GBC) cases.

Blood-based protein biomarkers and red blood cell aggregation in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is highly malignant with a low 5-year survival rate. Blood biomarkers may be of value for the noninvasive diagnosis of pancreatic cancer.

OBJECTIVE

This study assessed blood-based biomarkers and disturbances in red blood cell aggregation associated with pancreatic cancer.

METHODS

We studied 61 patients who underwent pancreatic resection. Of these 61 patients, 46 patients had PDAC, and 15 patients had inflammatory tumours. Serum VEGF, hypoxia-inducible factor (HIF-1α), elastin-derived peptides (EDPs), total sialic acid (TSA) and resistin levels were measured. Red blood cell aggregation was assessed by a laser-assisted optical rotational cell analyser.

RESULTS

VEGF (p < 0.000001), HIF-1α (p = 0.000002), resistin (p = 0.000349), EDP (p = 0.000089) and TSA (p = 0.000013) levels were significantly higher in the PDAC group than in the inflammatory tumour group. The aggregation index (AI), syllectogram amplitude (AMP) and threshold shear rate (γthr) were significantly higher in the PDAC group, whereas the aggregation half-time (t1/2) was lower than in the inflammatory tumour group. Multivariate analyses revealed that VEGF, TSA and EDP levels were variables that predicted PDAC. VEGF levels were the most powerful predictor of PDAC independent of CA 19-9 levels. The cut-off points for VEGF, TSA and EDP levels were 134.56 pg/ml, 109.11 mg/dl and 36.4 ng/ml, respectively, with sensitivities of 97.8%, 87% and 69.6%, respectively, and specificities of 86.7%, 86.7% and 93.3%, respectively.

CONCLUSION

This study indicated that there are significant differences in blood-based biomarkers for differentiating between PDAC and inflammatory tumours of the pancreas. We also confirmed that PDAC is associated with the excessive aggregation of RBCs.

Oral mycobiota and pancreatic ductal adenocarcinoma

Early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for survival. Preliminary research demonstrated significant associations between structural alternation of mycobiota and PDAC. In this study, we investigated the associations between oral mycobiota and PDAC. We further explored mycobiota biomarkers for PDAC detection. We enrolled 34 PDAC patients and 35 matched healthy controls from West China hospital in Southwest China. Demographic data, clinical information, and salivary samples were collected. Mycobiota characteristics were defined using Internal Transcribed Spacer (ITS) ribosomal RNA sequencing. We found that the PDAC patients had significant increase in fungal abundance (P < 0.001) and significant decrease in fungal diversity (P < 0.001) in comparison to the healthy controls. A higher abundance of Basidiomycota and Unclassifed_p_Ascomycota was associated with an increased risk of PDAC. With each increase of abundance of g__unclassified_k__Fungi and g__unclassified_p__Ascomycota in PDAC patients, the risk of pancreatic cancer increased by 1.359 odds and 1.260 odds, respectively. Aspergillus (AUC = 0.983, 95% CI 0.951-1.000) and Cladosporium (AUC = 0.969, 95% CI 0.921-1.000) achieved high classification powers to distinguish PDAC patients from the healthy controls. The rapid, inexpensive tests of ITS1 sequencing of mycobiota and PCR detection of potential fungal biomarkers make it promising for the clinical practice to use oral microbes for PDAC early detection and prevention. Results of our study provide evidence that salivary mycobiota may provide insights into cancer risk, prevention, and detection.

Value of serological markers for early diagnosis and prognosis prediction of pancreatic cancer

Pancreatic cancer (PC) is a kind of malignant tumor with a poor prognosis. Its incidence rate is almost equal to the mortality rate, which shows an increasing trend, especially in recent years. At present, the radical cure of pancreatic cancer is mainly achieved by surgery, but the complex pathophysiology, the lack of early diagnosis and prognostic markers, and low surgical survival rate are the main obstacles to surgical treatment of pancreatic cancer. Serological markers are sensitive biological markers, and they have been used in recent years for the diagnosis and prediction of the prognosis of patients with postoperative pancreatic cancer. Therefore, serum markers are of vital importance in pancreatic cancer. This article summarizes various serological markers for early diagnosis and prognosis prediction of pancreatic cancer to provide a theoretical reference for clinical workers.

Artificial intelligence in pancreatic cancer

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for those not diagnosed with early screening. Therefore, early diagnosis and early treatment of pancreatic cancer are particularly critical. However, as a rare disease, the general screening cost of pancreatic cancer is high, the accuracy of existing tumor markers is not enough, and the efficacy of treatment methods is not exact. In terms of early diagnosis, artificial intelligence technology can quickly locate high-risk groups through medical images, pathological examination, biomarkers, and other aspects, then screening pancreatic cancer lesions early. At the same time, the artificial intelligence algorithm can also be used to predict the survival time, recurrence risk, metastasis, and therapy response which could affect the prognosis. In addition, artificial intelligence is widely used in pancreatic cancer health records, estimating medical imaging parameters, developing computer-aided diagnosis systems, etc. Advances in AI applications for pancreatic cancer will require a concerted effort among clinicians, basic scientists, statisticians, and engineers. Although it has some limitations, it will play an essential role in overcoming pancreatic cancer in the foreseeable future due to its mighty computing power.

Contrast-enhanced ultrasound of solid pancreatic head lesions: a prospective study

OBJECTIVE

To evaluate the role of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of solid pancreatic head lesions (SPHL).

METHODS

This prospective study comprised consecutive patients with SPHL who underwent CEUS evaluation of the pancreas. Findings recorded at CEUS were enhancement patterns (degree, completeness, centripetal enhancement, and percentage enhancement) and presence of central vessels. In addition, time to peak (TTP) and washout time (WT) were recorded. The final diagnosis was based on histopathology or cytology. Multivariate analysis was performed to identify parameters that were significantly associated with pancreatic ductal adenocarcinoma (PDAC).

RESULTS

Ninety-eight patients (median age 53.8 years, 59 males) were evaluated. The final diagnosis was PDAC (n = 64, 65.3%), inflammatory mass (n = 16, 16.3%), neuroendocrine tumor (NET, n = 14, 14.3%), and other tumors (n = 4, 4.1%). Hypoenhancement, incomplete enhancement, and centripetal enhancement were significantly more common in PDAC than non-PDAC lesions (p = 0.001, p = 0.031, and p = 0.002, respectively). Central vessels were present in a significantly greater number of non-PDAC lesions (p = 0.0001). Hypoenhancement with < 30% enhancement at CEUS had sensitivity and specificity of 80.6% and 67.7%, respectively, for PDAC. There was no significant difference in the TTP and WT between PDAC and non - PDAC lesions. However, the WT was significantly shorter in PDAC compared to NET (p = 0.011). In multivariate analysis, lack of central vessels was significantly associated with a PDAC diagnosis.

CONCLUSION

CEUS is a useful tool for the evaluation of SPHL. CEUS can be incorporated into the diagnostic algorithm to differentiate PDAC from non-PDAC lesions.

KEY POINTS

• Hypoenhancement and incomplete enhancement at CEUS were significantly more common in PDAC than in non-PDAC. • Central vessels at CEUS were significantly associated with PDAC. • There was no difference in TTP and WT between PDAC and non-PDAC lesions.

Value of multi-detector computed tomography combined with serum tumor markers in diagnosis, preoperative, and prognostic evaluation of pancreatic cancer

Background

Multi-detector computed tomography (MDCT) and serum tumor markers are commonly used in the diagnosis of pancreatic cancer (PC). In this article, we focused on the evaluation of the clinical value of MDCT combined with serum tumor markers CA199, CA242, and CEA in diagnosis, preoperative, and prognostic evaluation of PC.

Methods

Eighty-five PC patients (PC group) and 39 patients with pancreatitis (control group) admitted to our hospital were selected for our present research study. MDCT, CA199, CA242, and CEA examination were examined in all patients, and their value in diagnosis, preoperative, and prognostic evaluation of PC was retrospectively analyzed.

Results

There were 69 patients whose clinical staging results of MDCT were consistent with the postoperative pathological diagnosis. The coincidence rate was 70.00% in stage I, 62.96% in stage II, 72.72% in stage III, and 80.00% in stage IV, respectively, and the overall coincidence rate was 69.57%The levels of CA199, CA242, and CEA in PC group were remarkably higher than those in control group and were sharply correlated with clinical stage, differentiation degree, and distant metastasis. The sensitivity, accuracy, and negative predictive value of MDCT combined with serum CA199, CA242 and CEA in the diagnosis of PC were significantly improved compared with those of each single test. In PC group, the 2-year event-free survival rate of the group with high CA199, CA242, and CEA expression was remarkably lower than that of the low expression group.

Conclusion

MDCT combined with CA199, CA242, and CEA notably improved the diagnostic efficiency of PC and had guiding significance for preoperative and prognostic evaluation of PC.

Diagnostic value of serum carbohydrate antigen 19-9 in pancreatic cancer: a systematic review and meta-analysis

Carbohydrate antigen 19-9 (CA19-9) is the most widely used serum biomarker for detecting pancreatic cancer (PC). Since early diagnosis is important for improving PC prognosis, a comprehensive understanding of the diagnostic performance of CA19-9 is critical. This study focused on comprehensive evaluation of the efficacy of CA19-9 in PC diagnosis. Literature research was based on the seven databases. Studies released from January 2002 to January 2022 focused on the efficacy of CA19-9 in the detection of PC were included. Summarized sensitivity, specificity, and sROC/accuracy of discrimination (AUC) were estimated. Potential publication bias was measured with Funnel plot and Egger's test. Meta-regression was performed to detect possible causes of heterogeneity. Subgroup analysis was used to assess the diagnostic efficacy of CA19-9 under different conditions. The study is registered on PROSPERO (CRD42021253861). Seventy-nine studies containing 20 991 participants who met the criteria were included. The pooled sensitivity, specificity, and AUC of CA19-9 in diagnose PC were 72% (95% CI, 71-73%), 86% (95% CI, 85-86%), and 0.8474 (95% CI, 0.8272-0.8676). Subgroup analysis suggested that the diagnostic efficiency of CA19-9 in studies with healthy controls was the highest, followed by intraductal papillary mucinous neoplasm, in pancreatitis and diabetes were consistent with the overall result. Our analysis showed that serum CA19-9 had high and stable diagnostic efficacy for PC (not affected by diabetes). Subgroup analysis showed that serum CA19-9 yielded highest effectiveness in the diagnosis of pancreatic precancerous lesions, which indicated an irreplaceable clinical value in the early detection and warning value for PC.

A faecal microbiota signature with high specificity for pancreatic cancer

BACKGROUND

Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression.

OBJECTIVE

To explore the faecal and salivary microbiota as potential diagnostic biomarkers.

METHODS

We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase.

RESULTS

Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation.

CONCLUSION

Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Serum Nardilysin as a Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Background: Nardilysin, (N-arginine dibasic convertase, NRDC) has been reported to play an important role in cancer progression, and is associated with tumor proliferation signals and inflammatory signals, such as tumor necrosis factor-a (TNF-a) and heparin-binding epidermal growth factor-like growth factor (HB-EGF), through the activation of disintegrin and metalloproteinase (ADAM) proteases. NRDC has recently been revealed to be involved in the tumorigenesis of various types of cancer, including intrahepatic cholangiocarcinoma, malignant cerebral infarction, esophageal squamous cell carcinoma, and gastric cancer. However, the expression profiles and biological relevance of NRDC in pancreatic ductal adenocarcinoma have rarely been reported. Methods: We analyzed the NRDC expression profile in pancreatic ductal adenocarcinoma by enzyme-linked immunosorbent assay (ELISA) and identified NRDC as a circulating biomarker in the serum of 112 pancreatic ductal adenocarcinoma patients. The diagnostic value of NRDC was analyzed by the area under the curve (AUC) and the receiver operating characteristic (ROC) test. Results: Our results demonstrated that the clinical prognosis significance of NRDC with the clinical characteristics in pancreatic ductal adenocarcinoma (PDAC). NRDC was notably decreased in PDAC patient serum compared with the control group (p < 0.001). Furthermore, the present study found that the NRDC expression level was correlated with T grade (p < 0.001), metastasis(p < 0.001), differentiation(p < 0.001), and TNM stage (p = 0.011). Further bioinformatics analysis revealed that NRDC correlated with proliferation and migration pathways; in particular, it mediated cell-matrix adhesion-dependent activation in pancreatic ductal adenocarcinoma. Conclusions: Serum NRDC may play a useful diagnostic biomarker to evaluate the aggressive clinical features in PAAD patients.

Clinical Applications of Classical and Novel Biological Markers of Pancreatic Cancer

The incidence and prevalence of pancreatic adenocarcinoma have increased in recent years. Pancreatic cancer is the seventh leading cause of cancer death, but it is projected to become the second leading cause of cancer-related mortality by 2040. Most patients are diagnosed in an advanced stage of the disease, with very limited 5-year survival. The discovery of different tissue markers has elucidated the underlying pathophysiology of pancreatic adenocarcinoma and allowed stratification of patient risk at different stages and assessment of tumour recurrence. Due to the invasive capacity of this tumour and the absence of screening markers, new immunohistochemical and serological markers may be used as prognostic markers for recurrence and in the study of possible new therapeutic targets because the survival of these patients is low in most cases. The present article reviews the currently used main histopathological and serological markers and discusses the main characteristics of markers under development.

Dielectrophoresis-Based Biosensor for Detection of the Cancer Biomarkers CEA and CA 242 in Serum

We show that dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism for detection of the concentration levels of the pancreatic cancer biomarkers cancer antigen (CA) 242 and carcinoembryonic antigen (CEA) in serum. We noticed a frequency dependence of the negative DEP force applied by interdigitated electrodes on functionalized polystyrene microspheres (PM) with respect to changes in the number of these cancer antigens bound to the PM. An electrode array with a well-defined gradient of the electric field was designed and used, which enabled the automation of the signal processing and reproducibility of the signal acquired by the biosensor.

The Impact of Biomarkers in Pancreatic Ductal Adenocarcinoma on Diagnosis, Surveillance and Therapy

Simple Summary

Pancreatic ductal adenocarcinoma is a leading cause of cancer death worldwide. Due to the frequently late diagnosis, early metastasis and high therapy resistance curation is rare and prognosis remains poor overall. To provide early diagnostic and therapeutic predictors, various molecules from blood, tissue and other origin e.g., saliva, urine and stool, have been identified as biomarkers. This review summarizes current trends in biomarkers for diagnosis and therapy of pancreatic ductal adenocarcinoma.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is still difficult to treat due to insufficient methods for early diagnosis and prediction of therapy response. Furthermore, surveillance after curatively intended surgery lacks adequate methods for timely detection of recurrence. Therefore, several molecules have been analyzed as predictors of recurrence or early detection of PDAC. Enhanced understanding of molecular tumorigenesis and treatment response triggered the identification of novel biomarkers as predictors for response to conventional chemotherapy or targeted therapy. In conclusion, progress has been made especially in the prediction of therapy response with biomarkers. The use of molecules for early detection and recurrence of PDAC is still at an early stage, but there are promising approaches in noninvasive biomarkers, composite panels and scores that can already ameliorate the current clinical practice. The present review summarizes the current state of research on biomarkers for diagnosis and therapy of pancreatic cancer.

A Label-Free Electrochemical Immunosensor for CEA Detection on a Novel Signal Amplification Platform of Cu2S/Pd/CuO Nanocomposites

Carcinoembryonic antigen (CEA) is regarded as one of the crucial tumor markers for colorectal cancer. In this study, we developed the snowflake Cu₂S/Pd/CuO nanocomposite to construct an original label-free electrochemical immunosensor for the ultrasensitive detection of CEA levels. The nanocomposite of cuprous sulfide (Cu₂S) with Pd nanoparticles (Pd NPs) was synthesized through an in situ formation of Pd NPs on the Cu₂S. Cuprous sulfide (Cu₂S) and CuO can not only be used as a carrier to increase the reaction area but also catalyze the substrate to generate current signal. Palladium nanoparticles (Pd NPs) have excellent catalytic properties and good biocompatibility, as well as the ability of excellent electron transfer. The immunosensor was designed using 5 mmol/L H₂O₂ as the active substrate by optimizing the conditions with a detection range from 100 fg/ml to 100 ng/ml and a minimum detection limit of 33.11 fg/ml. The human serum was detected by electrochemical immunoassay, and the results were consistent with those of the commercial electrochemical immunosensor. Therefore, the electrochemical immunosensor can be used for the detection of human serum samples and have potential value for clinical application.

Humoral Predictors of Malignancy in IPMN: A Review of the Literature

Pancreatic cystic lesions are increasingly detected in cross-sectional imaging. Intraductal papillary mucinous neoplasm (IPMN) is a mucin-producing subtype of the pancreatic cyst lesions arising from the pancreatic duct system. IPMN is a potential precursor of pancreatic cancer. The transformation of IPMN in pancreatic cancer is progressive and requires the occurrence of low-grade dysplasia, high-grade dysplasia, and ultimately invasive cancer. Jaundice, enhancing mural nodule >5 mm, main pancreatic duct diameter >10 mm, and positive cytology for high-grade dysplasia are considered high-risk stigmata of malignancy. While increased levels of carbohydrate antigen 19-9 (CA 19-9) (>37 U/mL), main pancreatic duct diameter 5-9.9 mm, cyst diameter >40 mm, enhancing mural nodules <5 mm, IPMN-induced acute pancreatitis, new onset of diabetes, cyst grow-rate >5 mm/year are considered worrisome features of malignancy. However, cross-sectional imaging is often inadequate in the prediction of high-grade dysplasia and invasive cancer. Several studies evaluated the role of humoral and intra-cystic biomarkers in the prediction of malignancy in IPMN. Carcinoembryonic antigen (CEA), CA 19-9, intra-cystic CEA, intra-cystic glucose, and cystic fluid cytology are widely used in clinical practice to distinguish between mucinous and non-mucinous cysts and to predict the presence of invasive cancer. Other biomarkers such as cystic fluid DNA sequencing, microRNA (mi-RNA), circulating microvesicles, and liquid biopsy are the new options for the mini-invasive diagnosis of degenerated IPMN. The aim of this study is to review the literature to assess the role of humoral and intracystic biomarkers in the prediction of advanced IPMN with high-grade dysplasia or invasive carcinoma.

Limits of serum carcinoembryonic antigen and carbohydrate antigen 19-9 as the diagnosis of gallbladder cancer

Purpose

Although serum CEA and CA 19-9 have been widely utilized for the diagnosis of gallbladder cancer (GBC), few studies have examined the diagnostic performance of them. This study aimed to investigate the diagnostic performance of these 2 biomarkers and demonstrate their clinical usefulness in diagnosing GBC.

Methods

Between January 2000 and March 2020, a total of 751 GBC patients and 2,310 normal controls were included. Serum CEA and CA 19-9 were measured preoperatively. Receiver operating characteristic curves were obtained, and the sensitivity and specificity of each biomarker were evaluated.

Results

In terms of differentiating GBC from the control, the sensitivity and specificity of serum CEA at 5 ng/mL was 12.1% and 99.1%, respectively, and those of serum CA 19-9 at 37 IU/mL were 28.7% and 94.5%, respectively. The optimal cutoff values of CEA and CA 19-9 were set to 2.1 ng/mL and 26 IU/mL in the receiver operating characteristic curves, respectively. The sensitivities of CEA and CA 19-9 at new cutoff values slightly increased but remained low (CEA, 42.9%; CA 19-9, 38.2%). When differentiating early-stage GBC from advanced tumor, the sensitivity and specificity, were 14.2% and 96.1% for CEA (cutoff value, 5 ng/mL) and 33.6% and 90.1% for CA 19-9 (cutoff value, 37 IU/mL), respectively.

Conclusion

Serum CEA and CA 19-9 levels are not suitable for screening GBC patients from controls. New promising biomarkers with higher sensitivity should be explored.

Tips and tricks for the diagnosis and management of biliary stenosis-state of the art review

Biliary stenosis may represent a diagnostic and therapeutic challenge resulting in a delay in diagnosis and initiation of therapy due to the frequent difficulty in distinguishing a benign from a malignant stricture. In such cases, the diagnostic flowchart includes the sequential execution of imaging techniques, such as magnetic resonance, magnetic resonance cholangiopancreatography, and endoscopic ultrasound, while endoscopic retrograde cholangiopancreatography is performed to collect tissue for histopathological/cytological diagnosis or to treat the stenosis by insertion of stent. The execution of percutaneous transhepatic drainage with subsequent biopsy has been shown to increase the possibility of tissue diagnosis after failure of the above techniques. Although the diagnostic yield of histopathology and imaging has increased with improvements in endoscopic ultrasound and peroral cholangioscopy, differential diagnosis between malignant and benign stenosis may not be easy in some patients, and strictures are classified as indeterminate. In these cases, a multidisciplinary workup including biochemical marker assays and advanced technologies available may speed up a diagnosis of malignancy or avoid unnecessary surgery in the event of a benign stricture. Here, we review recent advancements in the diagnosis and management of biliary strictures and describe tips and tricks to increase diagnostic yields in clinical routine.

Neoadjuvant Treatment for Pancreatic Adenocarcinoma: A False Promise or an Opportunity to Improve Outcome?

Simple Summary

Pancreatic cancer usually presents late when it has spread to distant sites. In a small proportion of patients, the cancer can be removed by surgery. Surgery is usually followed by chemotherapy, as studies have shown that this improves survival. However, due to complications after surgery and a decline in fitness, some patients do not start their chemotherapy and many do not complete the planned course. The cancer returns in the majority of patients. Chemotherapy or a combination of chemotherapy and radiotherapy before surgery are being investigated to improve survival. The best treatment regime and patient selection for different treatment strategies remains to be defined and is discussed here.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) has an aggressive tumor biology and is associated with poor survival outcomes. Most patients present with metastatic or locally advanced disease. In the 10–20% of patients with upfront resectable disease, surgery offers the only chance of cure, with the addition of adjuvant chemotherapy representing an established standard of care for improving outcomes. Despite resection followed by adjuvant chemotherapy, at best, 3-year survival reaches 63.4%. Post-operative complications and poor performance mean that around 50% of the patients do not commence adjuvant chemotherapy, and a significant proportion do not complete the intended treatment course. These factors, along with the advantages of early treatment of micrometastatic disease, the ability to downstage tumors, and the increase in R0 resection rates, have increased interest in neo-adjuvant treatment strategies. Here we review biomarkers for early diagnosis of PDAC and patient selection for a neo-adjuvant approach. We also review the current evidence for different chemotherapy regimens in this setting, as well as the role of chemoradiotherapy and immunotherapy, and we discuss ongoing trials.

Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review

Pancreatic cancer is a highly malignant digestive system tumor with a poor prognosis. Most pancreatic cancer patients are diagnosed at an advanced stage or even metastasis due to its highly aggressive characteristics and lack of typical early symptoms. Thus, an early diagnosis of pancreatic cancer is crucial for improving its prognosis. Currently, screening is often applied in high‐risk individuals to achieve the early diagnosis of pancreatic cancer. Fully understanding the risk factors of pancreatic cancer and pathogenesis could help us identify the high‐risk population and achieve early diagnosis and timely treatment of pancreatic cancer. Notably, accumulating studies have been undertaken to improve the detection rate of different imaging methods and the diagnostic accuracy of endoscopic ultrasound‐guided fine‐needle aspiration (EUS‐FNA) which is the golden standard for pancreatic cancer diagnosis. In addition, there are currently no biomarkers with sufficient sensitivity and specificity for the diagnosis of pancreatic cancer to be applied in the clinic. As the only serum biomarker approved by the United States Food and Drug Administration, carbohydrate antigen 19‐9 (CA19‐9) is not recommended to be used in the early screening of pancreatic cancer because of its limited specificity. Recently, increasing numbers of studies focused on the discovering of novel serum biomarkers and exploring their combination with CA19‐9 in the detection of pancreatic cancer. Besides, the application of liquid biopsy involving circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), microRNAs (miRNAs), and exosomes in blood and biomarkers in urine, and saliva in pancreatic cancer diagnosis are drawing more and more attention. Furthermore, many innovative technologies such as artificial intelligence, computer‐aided diagnosis system, metabolomics technology, ion mobility spectrometry (IMS) associated technologies, and novel nanomaterials have been tested for the early diagnosis of pancreatic cancer and have shown promising prospects. Hence, this review aims to summarize the recent progress in the development of early screening and diagnostic methods, including imaging, pathological examination, serological examination, liquid biopsy, as well as other potential diagnostic strategies for pancreatic cancer.

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).

Pancreatic Cancer Insights: Optimization of the Diagnostic Capacity of Tumor Biomarkers

OBJECTIVE

Pancreatic cancer (PC) is one of the deadliest malignancies. The aim of this study was to determine the usefulness of the carbohydrate antigen 19.9 (CA19.9)/ carcinoembryonic antigen (CEA) ratio as a diagnostic tool.

METHODS

This was a retrospective observational study (2015-2019), including laboratory requests with increased CA19.9 and CEA but no previous neoplasia. Receiver operating characteristic (ROC) curve analyses were performed for the CA19.9/CEA ratio and for CA19.9 and CEA alone for the detection of PC, and cutoff values for all strategies were selected separately and in combination.

RESULTS

A total of 373 individuals were included. The area under the curve (AUC) for CA19.9/CEA was 0.872, whereas the AUC for CA19.9 was 0.847 and for CEA was 0.554. Cutoff values with the greatest diagnostic power were CA19.9/CEA >40, CA19.9 >1130 U/mL, and CEA > 14.5 U/mL. The combination of CA19.9/CEA > 40 with CA19.9 > 550 U/mL maximized the diagnostic accuracy for PC.

CONCLUSION

Our results highlight the relevance of the measurement of serum CA19.9 and CEA in the detection of PC.

Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Background: Accumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. Methods: Univariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan–Meier (K–M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC. Results: Univariate analysis, K–M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8⁺ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways. Conclusion: Our study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

Label-Free SERS Analysis of Urine Using a 3D-Stacked AgNW-Glass Fiber Filter Sensor for the Diagnosis of Pancreatic Cancer and Prostate Cancer

Metabolomics shows tremendous potential for the early diagnosis and screening of cancer. For clinical application as an effective diagnostic tool, however, improved analytical methods for complex biological fluids are required. Here, we developed a reliable rapid urine analysis system based on surface-enhanced Raman spectroscopy (SERS) using 3D-stacked silver nanowires (AgNWs) on a glass fiber filter (GFF) sensor and applied it to the diagnosis of pancreatic cancer and prostate cancer. Urine samples were pretreated with centrifugation to remove large debris and with calcium ion addition to improve the binding of metabolites to AgNWs. The label-free urine-SERS detection using the AgNW-GFF SERS sensor showed different spectral patterns and distinguishable specific peaks in three groups: normal control (n = 30), pancreatic cancer (n = 22), and prostate cancer (n = 22). Multivariate analyses of SERS spectra using unsupervised principal component analysis and supervised orthogonal partial least-squares discriminant analysis showed excellent discrimination between the pancreatic cancer group and the prostate cancer group as well as between the normal control group and the combined cancer groups. The results demonstrate the great potential of the urine-SERS analysis system using the AgNW-GFF SERS sensor for the noninvasive diagnosis and screening of cancers.

Radiological evaluation of pancreatic cancer: What is the significance of arterial encasement >180° after neoadjuvant treatment?

PURPOSE

This study aimed to evaluate contrast-enhanced computed tomography (CE-CT) features for prediction of arterial tumor invasion in pancreatic cancer (PDAC) patients in the event of arterial encasement >180° after neoadjuvant (radio-)chemotherapy (NAT).

METHODS

Seventy PDAC patients with seventy-five arteries showing encasement >180° after completion of NAT were analyzed. All patients underwent surgical exploration with either tumor resection including arterial resection, periadventitial dissection (arterial divestment) or confirmation of locally irresectable disease. CE-CT scans were assessed regarding tumor extent and artery-specific imaging features. The results were analyzed on a per-artery basis. Based on the intraoperative and histopathological findings, encased arteries were classified as either invaded or non-invaded.

RESULTS

Eighteen radiologically encased arteries were resected; of these, nine had pathologic evidence for tumor invasion. In 42 encased arteries, the tumor could be removed by arterial divestment. In 13 patients with 15 encased arteries, the tumor was deemed technically irresectable. Median tumor size, length of solid soft tissue contact, and degree of circumferential contiguity by solid soft tissue along the artery in CE-CT were significantly lower in the non-invaded than in the invaded artery group (p ≤ 0.017). Imaging features showed moderate accuracies for prediction of arterial invasion (≤72.0 %). The thresholds ≤26 mm for post-NAT solid soft tissue contact and ≤270° for circumferential contiguity by solid soft tissue had high negative predictive values (≥87.5 %).

CONCLUSION

Although post-NAT prediction of arterial invasion remains difficult, arteries with ≤270° contiguity by soft tissue and arteries with ≤26 mm length of solid soft tissue contact are unlikely to be invaded, with possible implications for surgical planning.

Non-coding RNA biomarkers in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, which is usually diagnosed at an advanced stage. The late disease diagnosis, the limited availability of effective therapeutic interventions and lack of robust diagnostic biomarkers, are some of the primary reasons for the dismal 5-year survival rates (∼8%) in patients with PDAC. The pancreatic cancer develops through accumulation of a series of genomic and epigenomic alterations which lead to the transformation of normal pancreatic epithelium into an invasive carcinoma - a process that can take up to 15-20 years to develop, from the occurrence of first initiating mutational event. These facts highlight a unique window of opportunity for the earlier detection of PDAC, which could allow timely disease interception and improvement in the overall survival outcomes in patients suffering from this fatal malignancy. Non-coding RNAs (ncRNAs) have been recognized to play a central role in PDAC pathogenesis and are emerging as attractive candidates for biomarker development in various cancers, including PDAC. More specifically, the ncRNAs play a pivotal role in PDAC biology as they affect tumor growth, migration, and invasion by regulating cellular processes including cell cycle, apoptosis, and epithelial-mesenchymal transition. In this review, we focus on three types of well-established ncRNAs - microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) - and discuss their potential as diagnostic, prognostic and predictive biomarkers in PDAC.

Challenging biliary strictures: pathophysiological features, differential diagnosis, diagnostic algorithms, and new clinically relevant biomarkers - part 1

It is frequently challenging to make the correct diagnosis in patients with biliary strictures. This is particularly important as errors may have disastrous consequences. Benign-appearing strictures treated with stents may later be revealed to be malignant and unnecessary surgery for benign strictures carries a high morbidity rate. In the first part of the review, the essential information that clinicians need to know about diseases responsible for biliary strictures is presented, with a focus on the most recent data. Then, the characteristics and pitfalls of the methods used to make the diagnosis are summarized. These include serum biomarkers, imaging studies, and endoscopic modalities. As tissue diagnosis is the only 100% specific tool, it is described in detail, including techniques for tissue acquisition and their yields, how to prepare samples, and what to expect from the pathologist. Tricks to increase diagnostic yields are described. Clues are then presented for the differential diagnosis between primary and secondary sclerosing cholangitis, IgG4-related sclerosing cholangitis, cholangiocarcinoma, pancreatic cancer, autoimmune pancreatitis, and less frequent diseases. Finally, algorithms that will help to achieve the correct diagnosis are proposed.