Pancreatic Cancer Biomarkers: Oncogenic Mutations, Tissue and Liquid Biopsies, and Radiomics-A Review

Urinary biomarkers analysis as a diagnostic tool for early detection of pancreatic adenocarcinoma: Molecular quantification approach

BACKGROUND AND AIMS

Pancreatic ductal adenocarcinoma (PDAC) is infrequent. Currently, non-invasive biomarkers for early detection of PDAC are not accessible. Here, we intended to identify a set of urine markers able to discriminate patients with early-stage PDAC from healthy individuals.

PATIENTS AND METHODS

Seventy-five urine samples from PDAC patients and 50 healthy controls were assayed using quantitative real-time PCR (qPCR). The chosen biomarkers were lymphatic vessel endothelial HA receptor (LYVE-1), regenerating islet-derived 1 alpha (REG1A), and trefoil factor family (TFF1).

RESULTS

LYVE-1, REG1A, and TFF1 expression in PDAC proved to be significantly elevated compared to healthy individuals (p < 0.05). Determination of these markers' expression might be useful for early tumor diagnosis with a sensitivity of 96 %, 100 %, and 73.33 % respectively, and a specificity of 100 %, 82 %, and 100 % respectively.

CONCLUSION

We have recognized three diagnostic biomarkers REG1A, TFF1, and LYVE1 that can detect patients with early-stage pancreatic cancer in non-invasive urine specimens with improved sensitivity and specificity. To the best of our knowledge, there have been no prior investigations examining the mRNA expression levels of them in urine within the Egyptian population.

GDF15 and LCN2 for early detection and prognosis of pancreatic cancer

BACKGROUND

The prognosis of pancreatic ductal adenocarcinomas (PDAC) remains very poor, emphasizing the critical importance of early detection, where biomarkers offer unique potential. Although growth differentiation factor 15 (GDF15) and Lipocalin 2 (LCN2) have been linked to PDAC, their precise roles as biomarkers are uncertain.

METHODS

Circulating levels of GDF15 and LCN2 were examined in human PDAC patients, heathy controls, and individuals with benign pancreatic diseases. Circulating levels of IL-6, CA19-9, and neutrophil-to-lymphocyte ratio (NLR) were measured for comparisons. Correlations between PDAC progression and overall survival were assessed. A mouse PDAC model was employed for comprehensive analyses, complementing the human studies by exploring associations with various metabolic and inflammatory parameters. Sensitivity and specificity of the biomarkers were evaluated.

FINDINGS

Our results demonstrated elevated levels of circulating GDF15 and LCN2 in PDAC patients compared to both healthy controls and individuals with benign pancreatic diseases, with higher GDF15 levels associated with disease progression and increased mortality. In PDAC mice, circulating GDF15 and LCN2 progressively increased, correlating with tumor growth, behavioral manifestations, tissue and molecular pathology, and cachexia development. GDF15 exhibited highly sensitive and specific for PDAC patients compared to CA19-9, IL-6, or NLR, while LCN2 showed even greater sensitivity and specificity in PDAC mice. Combining GDF15 and LCN2, or GDF15 and CA19-9, enhanced sensitivity and specificity.

INTERPRETATION

Our findings indicate that GDF15 holds promise as a biomarker for early detection and prognosis of PDAC, while LCN2 could strengthen diagnostic panels.

Radiogenomic analysis for predicting lymph node metastasis and molecular annotation of radiomic features in pancreatic cancer

BACKGROUND

To provide a preoperative prediction model for lymph node metastasis in pancreatic cancer patients and provide molecular information of key radiomic features.

METHODS

Two cohorts comprising 151 and 54 pancreatic cancer patients were included in the analysis. Radiomic features from the tumor region of interests were extracted by using PyRadiomics software. We used a framework that incorporated 10 machine learning algorithms and generated 77 combinations to construct radiomics-based models for lymph node metastasis prediction. Weighted gene coexpression network analysis (WGCNA) was subsequently performed to determine the relationships between gene expression levels and radiomic features. Molecular pathways enrichment analysis was performed to uncover the underlying molecular features.

RESULTS

Patients in the in-house cohort (mean age, 61.3 years ± 9.6 [SD]; 91 men [60%]) were separated into training (n = 105, 70%) and validation (n = 46, 30%) cohorts. A total of 1,239 features were extracted and subjected to machine learning algorithms. The 77 radiomic models showed moderate performance for predicting lymph node metastasis, and the combination of the StepGBM and Enet algorithms had the best performance in the training (AUC = 0.84, 95% CI = 0.77-0.91) and validation (AUC = 0.85, 95% CI = 0.73-0.98) cohorts. We determined that 15 features were core variables for lymph node metastasis. Proliferation-related processes may respond to the main molecular alterations underlying these features.

CONCLUSIONS

Machine learning-based radiomics could predict the status of lymph node metastasis in pancreatic cancer, which is associated with proliferation-related alterations.

New Function Annotation of PROSER2 in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to the absence of diagnostic markers and molecular targets. Here, we took an unconventional approach to identify new molecular targets for pancreatic cancer. We chose uncharacterized protein evidence level 1 without function annotation from extensive proteomic research on pancreatic cancer and focused on proline and serine-rich 2 (PROSER2), which ranked high in the cell membrane and cytoplasm. In our study using cell lines and patient-derived orthotopic xenograft cells, PROSER2 exhibited a higher expression in cells derived from primary tumors than in those from metastatic tissues. PROSER2 was localized in the cell membrane and cytosol by immunocytochemistry. PROSER2 overexpression significantly reduced the metastatic ability of cancer cells, whereas its suppression had the opposite effect. Proteomic analysis revealed that PROSER2 interacts with STK25 and PDCD10, and their binding was confirmed by immunoprecipitation and immunocytochemistry. STK25 knockdown enhanced metastasis by decreasing p-AMPK levels, whereas PROSER2-overexpressing cells increased the level of p-AMPK, indicating that PROSER2 suppresses invasion via the AMPK pathway by interacting with STK25. This is the first demonstration of the novel role of PROSER2 in antagonizing tumor progression via the STK25-AMPK pathway in PDAC. LC-MS/MS data are available at MassIVE (MSV000092953) and ProteomeXchange (PXD045646).

Echoendoscopic ultrasound pancreatic adenocarcinoma diagnosis and theranostic approach: should KRAS mutation research be recommended in everyday practice?

Background

The impact of KRAS mutation testing on pancreatic ductal adenocarcinoma (PDAC) samples by endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) for reducing the need to repeat EUS-FNA has been demonstrated. Such testing however is not part of standard practice for endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB).

Objectives

We aim to analyse the proportion of non-contributive samples by EUS-FNB and to evaluate the impact of KRAS mutation testing on the diagnosis, theranostics and survival.

Design

In this retrospective study, the impact on diagnosis and survival of KRAS testing for contributive and non-contributive samples by EUS-FNB was analysed.

Methods

The EUS-FNB samples, combined with KRAS testing using the Idylla® technique on liquid-based cytology from patients with PDAC between February 2019 and May 2023, were retrospectively reviewed. The cytology results were classified according to the guidelines of the World Health Organization System for Reporting Pancreaticobiliary Cytopathology (WHOSRPC).

Results

A total of 85 EUS-FNB specimens were reviewed. In all, 25 EUS-FNB samples did not lead to a formal diagnosis of PDAC according to the WHOSRPC (30.2%). Out of these 25, 11 (44%) could have been considered positive for a PDAC diagnosis thanks to the KRAS mutation test without carrying out further diagnosis procedures. The sensitivity of KRAS mutation testing using the Idylla technique was 98.6%. According to the available data, survival rates were not statistically different depending on the type of mutation.

Conclusion

KRAS mutation testing on liquid-based cytology using the Idylla or equivalent technique, combined with the PDAC EUS-FNB sample, should become a standard for diagnosis to avoid delaying treatment by doing another biopsy. Furthermore, knowledge of the KRAS status from treatment initiation could be used to isolate mutations requiring targeted treatments or inclusion in clinical research trials, especially for wild-type KRAS PDAC.

New Analogues of the Nicotinamide Phosphoribosyltransferase Inhibitor FK866 as Potential Anti-Pancreatic Cancer Agents

BACKGROUND

During the past two decades, many nicotinamide phosphoribosyltransferase (NAMPT) inhibitors were prepared and tested because this enzyme is overexpressed in pancreatic cancer. Although FK866 is a well-known, strong NAMPT inhibitor, it suffers severe drawbacks.

OBJECTIVE

Our work aimed to synthesize efficient NAMPT inhibitors featuring better pharmacokinetic properties than the pyridine-containing FK866. To this aim, the new anticancer agents were based on benzene, pyridazine, or benzothiazole moieties as a cap group instead of the pyridine unit found in FK866 and other NAMPT inhibitors.

METHODS

The new compounds, prepared exploiting standard heterocycle chemistry and coupling reactions (e.g., formation of amides, ureas, and cyanoguanidines, copper-mediated azide-alkyne cycloaddition), have been fully characterized using NMR and HRMS analyses. Their activity has been evaluated using cytotoxicity and intracellular NAD depletion assays in the human pancreatic cancer cell line MiaPaCa-2.

RESULTS

Among the 14 products obtained, compound 28, bearing a pyridazine unit as the cap group and a thiophene moiety as the tail group, showed 6.7 nanomolar inhibition activity in the intracellular NAD depletion assay and 43 nanomolar inhibition in the MiaPaCa-2 cells cytotoxicity assay, comparable to that observed for FK866.

CONCLUSION

The positive results observed for some newly synthesized molecules, particularly those carrying a thiophene unit as a tail group, indicate that they could act as in vivo anti-pancreatic cancer agents.

Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN)

Intraductal papillary mucinous neoplasms (IPMNs) are a very common incidental finding during patient radiological assessment. These lesions may progress from low-grade dysplasia (LGD) to high-grade dysplasia (HGD) and even pancreatic cancer. The IPMN progression risk grows with time, so discontinuation of surveillance is not recommended. It is very important to identify imaging features that suggest LGD of IPMNs, and thus, distinguish lesions that only require careful surveillance from those that need surgical resection. It is important to know the management guidelines and especially the indications for surgery, to be able to point out in the report the findings that suggest malignant degeneration. The imaging tools employed for diagnosis and risk assessment are Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) with contrast medium. According to the latest European guidelines, MRI is the method of choice for the diagnosis and follow-up of patients with IPMN since this tool has a highest sensitivity in detecting mural nodules and intra-cystic septa. It plays a key role in the diagnosis of worrisome features and high-risk stigmata, which are associated with IPMNs malignant degeneration. Nowadays, the main limit of diagnostic tools is the ability to identify the precursor of pancreatic cancer. In this context, increasing attention is being given to artificial intelligence (AI) and radiomics analysis. However, these tools remain in an exploratory phase, considering the limitations of currently published studies. Key limits include noncompliance with AI best practices, radiomics workflow standardization, and clear reporting of study methodology, including segmentation and data balancing. In the radiological report it is useful to note the type of IPMN so as the morphological features, size, rate growth, wall, septa and mural nodules, on which the indications for surveillance and surgery are based. These features should be reported so as the surveillance time should be suggested according to guidelines.

3D Printing for Cancer Diagnosis: What Unique Advantages Are Gained?

Cancer is a complex disease with global significance, necessitating continuous advancements in diagnostics and treatment. 3D printing technology has emerged as a revolutionary tool in cancer diagnostics, offering immense potential in detection and monitoring. Traditional diagnostic methods have limitations in providing molecular and genetic tumor information that is crucial for personalized treatment decisions. Biomarkers have become invaluable in cancer diagnostics, but their detection often requires specialized facilities and resources. 3D printing technology enables the fabrication of customized sensor arrays, enhancing the detection of multiple biomarkers specific to different types of cancer. These 3D-printed arrays offer improved sensitivity, allowing the detection of low levels of biomarkers, even in complex samples. Moreover, their specificity can be fine-tuned, reducing false-positive and false-negative results. The streamlined and cost-effective fabrication process of 3D printing makes these sensor arrays accessible, potentially improving cancer diagnostics on a global scale. By harnessing 3D printing, researchers and clinicians can enhance early detection, monitor treatment response, and improve patient outcomes. The integration of 3D printing in cancer diagnostics holds significant promise for the future of personalized cancer care.

Pancreatic Cancer Health Disparity: Pharmacologic Anthropology

Pancreatic cancer (PCa) remains a formidable global health challenge, with high mortality rates and limited treatment options. While advancements in pharmacology have led to improved outcomes for various cancers, PCa continues to exhibit significant health disparities, disproportionately affecting certain populations. This paper explores the intersection of pharmacology and anthropology in understanding the health disparities associated with PCa. By considering the socio-cultural, economic, and behavioral factors that influence the development, diagnosis, treatment, and outcomes of PCa, pharmacologic anthropology provides a comprehensive framework to address these disparities and improve patient care.

Liquid biopsy techniques and pancreatic cancer: diagnosis, monitoring, and evaluation

Pancreatic cancer (PC) is one of the most common malignancies. Surgical resection is a potential curative approach for PC, but most patients are unsuitable for operations when at the time of diagnosis. Even with surgery, some patients may still experience tumour metastasis during the operation or shortly after surgery, as precise prognosis evaluation is not always possible. If patients miss the opportunity for surgery and resort to chemotherapy, they may face the challenging issue of chemotherapy resistance. In recent years, liquid biopsy has shown promising prospects in disease diagnosis, treatment monitoring, and prognosis assessment. As a noninvasive detection method, liquid biopsy offers advantages over traditional diagnostic procedures, such as tissue biopsy, in terms of both cost-effectiveness and convenience. The information provided by liquid biopsy helps clinical practitioners understand the molecular mechanisms underlying tumour occurrence and development, enabling the formulation of more precise and personalized treatment decisions for each patient. This review introduces molecular biomarkers and detection methods in liquid biopsy for PC, including circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), noncoding RNAs (ncRNAs), and extracellular vesicles (EVs) or exosomes. Additionally, we summarize the applications of liquid biopsy in the early diagnosis, treatment response, resistance assessment, and prognostic evaluation of PC.

Liquid biopsy analysis of lipometabolic exosomes in pancreatic cancer

Pancreatic cancer is characterized by its high malignancy, insidious onset and poor prognosis. Most patients with pancreatic cancer are usually diagnosed at advanced stage or with the distant metastasis due to the lack of an effective early screening method. Liquid biopsy technology is promising in studying the occurrence, progression, and early metastasis of pancreatic cancer. In particular, exosomes are pivotal biomarkers in lipid metabolism and liquid biopsy of blood exosomes is valuable for the evaluation of pancreatic cancer. Lipid metabolism is crucial for the formation and activity of exosomes in the extracellular environment. Exosomes and lipids have a complex relationship of mutual influence. Furthermore, spatial metabolomics can quantify the levels and spatial locations of individual metabolites in cancer tissue, cancer stroma, and para-cancerous tissue in pancreatic cancer. However, the relationship among exosomes, lipid metabolism, and pancreatic cancer is also worth considering. This study mainly updates the research progress of metabolomics in pancreatic cancer, their relationship with exosomes, an important part of liquid biopsy, and their lipometabolic roles in pancreatic cancer. We also discuss the mechanisms by which possible metabolites, especially lipid metabolites through exosome transport and other processes, contribute to the recurrence and metastasis of pancreatic cancer.