Advances in biomarkers and techniques for pancreatic cancer diagnosis

Targeted Nanoparticle-Based Diagnostic and Treatment Options for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest cancers, presents significant challenges in diagnosis and treatment due to its aggressive, metastatic nature and lack of early detection methods. A key obstacle in PDAC treatment is the highly complex tumor environment characterized by dense stroma surrounding the tumor, which hinders effective drug delivery. Nanotechnology can offer innovative solutions to these challenges, particularly in creating novel drug delivery systems for existing anticancer drugs for PDAC, such as gemcitabine and paclitaxel. By using customization methods such as incorporating conjugated targeting ligands, tumor-penetrating peptides, and therapeutic nucleic acids, these nanoparticle-based systems enhance drug solubility, extend circulation time, improve tumor targeting, and control drug release, thereby minimizing side effects and toxicity in healthy tissues. Moreover, nanoparticles have also shown potential in precise diagnostic methods for PDAC. This literature review will delve into targeted mechanisms, pathways, and approaches in treating pancreatic cancer. Additional emphasis is placed on the study of nanoparticle-based delivery systems, with a brief mention of those in clinical trials. Overall, the overview illustrates the significant advances in nanomedicine, underscoring its role in transcending the constraints of conventional PDAC therapies and diagnostics.

Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

The high FKBP1A expression in WBCs as a potential screening biomarker for pancreatic cancer

Given the limitation of current routine approaches for pancreatic cancer screening and detection, the mortality rate of pancreatic cancer cases is still critical. The development of blood-based molecular biomarkers for pancreatic cancer screening and early detection which provide less-invasive, high-sensitivity, and cost-effective, is urgently needed. The goal of this study is to identify and validate the potential molecular biomarkers in white blood cells (WBCs) of pancreatic cancer patients. Gene expression profiles of pancreatic cancer patients from NCBI GEO database were analyzed by CU-DREAM. Then, mRNA expression levels of three candidate genes were determined by quantitative RT-PCR in WBCs of pancreatic cancer patients (N = 27) and healthy controls (N = 51). ROC analysis was performed to assess the performance of each candidate gene. A total of 29 upregulated genes were identified and three selected genes were performed gene expression analysis. Our results revealed high mRNA expression levels in WBCs of pancreatic cancer patients in all selected genes, including FKBP1A (p < 0.0001), PLD1 (p < 0.0001), and PSMA4 (p = 0.0002). Among candidate genes, FKBP1A mRNA expression level was remarkably increased in the pancreatic cancer samples and also in the early stage (p < 0.0001). Moreover, FKBP1A showed the greatest performance to discriminate patients with pancreatic cancer from healthy individuals than other genes with the 88.9% sensitivity, 84.3% specificity, and 90.1% accuracy. Our findings demonstrated that the alteration of FKBP1A gene in WBCs serves as a novel valuable biomarker for patients with pancreatic cancer. Detection of FKBP1A mRNA expression level in circulating WBCs, providing high-sensitive, less-invasive, and cost-effective, is simple and feasible for routine clinical setting that can be applied for pancreatic cancer screening and early detection.

A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach.

METHODS

Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed.

RESULTS

Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFX-IPEP signature outperformed the conventional CA19-9 tumor marker.

CONCLUSIONS

Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.

Clinical value of endoscopic ultrasound sound speed in differential diagnosis of pancreatic solid lesion and prognosis of pancreatic cancer

BACKGROUND

Differential diagnosis of pancreatic solid lesion (PSL) and prognosis of pancreatic cancer (PC) is a clinical challenge. We aimed to explore the differential diagnostic value of sound speed (SS) obtained from endoscopic ultrasonography (EUS) in PSL and the prognostic value of SS in PC.

METHODS

Patients with PSL in The Third Xiangya Hospital of Central South University from March 2019 to October 2019 were prospectively enrolled, who obtained SS from PSL. Patients were divided into the PC group and the pancreatic benign lesion (PBL) group. SS1 is the SS of lesions and SS2 is the SS of normal tissues adjacent to lesions. Ratio1 is equal to SS1 divided by SS2 of PSL (ratio1 = SS1/SS2).

RESULTS

Eighty patients were enrolled (24 PBL patients, 56 PC patients). SS1 and ratio1 in PC group were higher compared with PBL group (SS1:1568.00 vs. 1550.00, Z = -2.066, p = 0.039; ratio1: 1.0110 vs. 1.0051, Z = -3.391, p = 0.001). The SS1 in PC (Z = -6.503, p < 0.001) was higher compared to SS2. In the nonsurgical group of PC, low ratio1 predicted high overall survival (OS) (7.000 months vs. 4.000 months; p = 0.039). In the surgical group of PC, low SS1 was associated with low median OS (4.000 months vs. 12.000 months; p = 0.033).

CONCLUSIONS

SS plays a vital role in distinguishing between PBL and PC. Higher SS1 and ratio1 obtained by EUS are more related to PC than PBL. In PC patients, high SS1 may predict pancreatic lesions. In the nonsurgical group of PC, low ratio1 may predict high OS. However, in the surgical group of PC, low SS1 may predict low OS.

[Early detection of sporadic pancreatic cancer]

The incidence of pancreatic cancer is rising. At present, pancreatic cancer is the third most common cancer-causing death in Germany, but it is expected to become the second in 2030 and finally the leading cause of cancer death in 2050. Pancreatic ductal adenocarcinoma (PC) is generally diagnosed at advanced stages, and 5-year-survival has remained poor. Early detection of sporadic PC at stage IA, however, can yield a 5-year-survival rate of about 80%. Early detection initiatives aim at identifying persons at high risk. People with new-onset diabetes at age 50 or older have attracted much interest. Novel strategies regarding how to detect sporadic PC at an early stage are being discussed.

Biomarker discovery and validation for gastrointestinal tumors: A comprehensive review of colorectal, gastric, and liver cancers

Gastrointestinal (GI) malignancies, encompassing gastric, hepatic, colonic, and rectal cancers, are prevalent forms of cancer globally and contribute substantially to cancer-related mortality. Although there have been improvements in methods for diagnosing and treating GI cancers, the chances of survival for these types of cancers are still extremely low. According to the World Cancer Research International Fund's most recent figures, stomach cancer was responsible for roughly one million deaths worldwide in 2020. This emphasizes the importance of developing more effective tools for detecting, diagnosing, and predicting the outcome of these cancers at an early stage. Biomarkers, quantitative indications of biological processes or disease states, have emerged as promising techniques for enhancing the diagnosis and prognosis of GI malignancies. Recently, there has been a considerable endeavor to discover and authenticate biomarkers for various GI cancers by the utilization of diverse methodologies, including genomics, proteomics, and metabolomics. This review provides a thorough examination of the current state of biomarker research in the field of gastrointestinal malignancies, with a specific emphasis on colorectal, stomach, and liver cancers. A thorough literature search was performed on prominent databases such as PubMed, Scopus, and Web of Science to find pertinent papers published until November, 2023 for the purpose of compiling this review. The diverse categories of biomarkers, encompassing genetic, epigenetic, and protein-based biomarkers, and their potential utility in the fields of diagnosis, prognosis, and treatment selection, are explored. Recent progress in identifying and confirming biomarkers, as well as the obstacles that persist in employing biomarkers in clinical settings are emphasized. The utilization of biomarkers in GI cancers has significant potential in enhancing patient outcomes. Ongoing research is expected to uncover more efficient biomarkers for the diagnosis and prognosis of these cancers.

Unveiling the potential of galectin-3 as a diagnostic biomarker for pancreatic cancer: a review

Early detection of pancreatic cancer is crucial for improving patient outcomes, and identifying reliable biomarkers is a critical research area in this field. Galectin-3 (Gal-3) is a promising candidate for utilisation as a diagnostic biomarker in early-stage pancreatic cancer. This review aims to explore the potential of Gal-3 in pancreatic cancer diagnosis and its implications for precision medicine. Rigorous validation studies are essential to establish the clinical utility of Gal-3, including large-scale investigations to assess its sensitivity, specificity, and predictive value. Combining Gal-3 with existing biomarkers and advanced imaging techniques may enhance the accuracy of early detection. Moreover, Gal-3 holds promise for risk stratification, enabling the identification of high-risk individuals who could benefit from intensified surveillance and early interventions. However, challenges in standardised testing protocols, establishing reference ranges, assay reliability, workflow integration, cost-effectiveness, and healthcare provider education must be addressed for successful implementation. Despite these challenges, Gal-3 presents significant implications for precision medicine in pancreatic cancer management. By unravelling its potential and overcoming the hurdles, Gal-3 could revolutionise early detection, risk stratification, and personalised approaches in pancreatic cancer care. Collaborative efforts and continued research will be crucial in harnessing the full potential of Gal-3 as a diagnostic biomarker for early-stage pancreatic cancer.

A pancreatic adenocarcinoma mimicking hepatoid carcinoma of uncertain histogenesis: A case report and literature review

In rare cases, metastatic adenocarcinomas of different origin may exhibit the features of hepatoid carcinoma (HC), a rare malignant epithelial tumor, most commonly occurring in the ovaries and stomach, as well as in the pancreas and biliary ducts. A case of a 72-year-old female patient who developed a highly aggressive, poorly differentiated pancreatic ductal adenocarcinoma with peritoneal carcinomatosis, demonstrating hepatoid differentiation upon conventional hematoxylin and eosin staining is reported in the present study. The patient presented with severe abdominal pain, and the radiological investigations performed revealed ovarian and hepatic tumor masses and peritoneal lesions, which were surgically removed. The gross examination of the peritoneum and omentum revealed multiple solid, firm, grey-white nodules, diffusely infiltrating the adipose tissue. The microscopic examination revealed a malignant epithelial proliferation, composed of polygonal cells with abundant eosinophilic cytoplasm and irregular, pleomorphic nuclei. Certain cells presented with intracytoplasmic mucus inclusions, raising suspicion of a HC with an uncertain histogenesis. Immunohistochemical staining was performed, and the tumor cells were found to be positive for cytokeratin (CK)7, CK18 and mucin 5AC, whereas negative staining for CK20, caudal-type homeobox transcription factor 2, α-fetoprotein, paired box gene 8, GATA-binding protein 3 and Wilms tumor 1 were documented. Thus, the diagnosis of metastatic pancreatic adenocarcinoma was established. The main aim of the present study was to provide further knowledge concerning poorly differentiated metastatic adenocarcinoma resembling HC, emphasizing the histopathological and immunohistochemical features of these malignant lesions and raising awareness of the diagnostic difficulties that may arise, as well as the importance of the use immunohistochemistry in differentiating carcinomas of uncertain histogenesis.

Prospective of Pancreatic Cancer Diagnosis Using Cardiac Sensing

Pancreatic carcinoma (Ca Pancreas) is the third leading cause of cancer-related deaths in the world. The malignancies of the pancreas can be diagnosed with the help of various imaging modalities. An endoscopic ultrasound with a tissue biopsy is so far considered to be the gold standard in terms of the detection of Ca Pancreas, especially for lesions <2 mm. However, other methods, like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), are also conventionally used. Moreover, newer techniques, like proteomics, radiomics, metabolomics, and artificial intelligence (AI), are slowly being introduced for diagnosing pancreatic cancer. Regardless, it is still a challenge to diagnose pancreatic carcinoma non-invasively at an early stage due to its delayed presentation. Similarly, this also makes it difficult to demonstrate an association between Ca Pancreas and other vital organs of the body, such as the heart. A number of studies have proven a correlation between the heart and pancreatic cancer. The tumor of the pancreas affects the heart at the physiological, as well as the molecular, level. An overexpression of the SMAD4 gene; a disruption in biomolecules, such as IGF, MAPK, and ApoE; and increased CA19-9 markers are a few of the many factors that are noted to affect cardiovascular systems with pancreatic malignancies. A comprehensive review of this correlation will aid researchers in conducting studies to help establish a definite relation between the two organs and discover ways to use it for the early detection of Ca Pancreas.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks

BACKGROUND

Early diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is the main key to surviving cancer patients. Urine proteomic biomarkers which are creatinine, LYVE1, REG1B, and TFF1 present a promising non-invasive and inexpensive diagnostic method of the PDAC. Recent utilization of both microfluidics technology and artificial intelligence techniques enables accurate detection and analysis of these biomarkers. This paper proposes a new deep-learning model to identify urine biomarkers for the automated diagnosis of pancreatic cancers. The proposed model is composed of one-dimensional convolutional neural networks (1D-CNNs) and long short-term memory (LSTM). It can categorize patients into healthy pancreas, benign hepatobiliary disease, and PDAC cases automatically.

RESULTS

Experiments and evaluations have been successfully done on a public dataset of 590 urine samples of three classes, which are 183 healthy pancreas samples, 208 benign hepatobiliary disease samples, and 199 PDAC samples. The results demonstrated that our proposed 1-D CNN + LSTM model achieved the best accuracy score of 97% and the area under curve (AUC) of 98% versus the state-of-the-art models to diagnose pancreatic cancers using urine biomarkers.

CONCLUSION

A new efficient 1D CNN-LSTM model has been successfully developed for early PDAC diagnosis using four proteomic urine biomarkers of creatinine, LYVE1, REG1B, and TFF1. This developed model showed superior performance on other machine learning classifiers in previous studies. The main prospect of this study is the laboratory realization of our proposed deep classifier on urinary biomarker panels for assisting diagnostic procedures of pancreatic cancer patients.

Pancreatic Cancer: Genetic Conditions and Epigenetic Alterations

BACKGROUND

Pancreatic cancer is a lethal proliferative disease driven by multiple genetic and epigenetic alterations. Microarrays and omics-based sequencing techniques are potent tools that have facilitated a broader understanding of the complex biological processes that drive pancreatic ductal adenocarcinoma (PDAC). In turn, these tools have resulted in the identification of novel disease markers, prognostic factors, and therapeutic targets. Herein, we provide a review of the genetic and epigenetic drivers of PDAC relative to recent discoveries that impact patient management.

METHODS

A review of PubMed, Medline, Clinical Key, and Index Medicus was conducted to identify literature from January 1995 to July 2022 that is related to PDAC genetics and epigenetics. Articles in Spanish and English were considered during selection.

RESULTS

Molecular, genetic, and epigenetic diagnostic tools, novel biomarkers, and promising therapeutic targets have emerged in the treatment of pancreatic cancer. The implementation of microarray technology and application of large omics-based data repositories have facilitated recent discoveries in PDAC. Multiple molecular analyses based on RNA interference have been instrumental in the identification of novel therapeutic targets for patients with PDAC. Moreover, microarrays and next-generation omics-based discoveries have been instrumental in the characterization of subtypes of pancreatic cancer, thereby improving prognostication and refining patient selection for available targeted therapies.

CONCLUSION

Advances in molecular biology, genetics, and epigenetics have ushered in a new era of discovery in the pathobiology of PDAC. Current efforts are underway to translate these findings into clinical tools and therapies to improve outcomes in patients with PDAC.

Updated epidemiology of gastrointestinal cancers in East Asia

Globally, gastrointestinal cancers represent more than one-fourth of all cancer incidence and one-third of cancer-related mortality. Although there has been much progress in screening colorectal cancer, the prognosis of other gastrointestinal cancers tends to be poor. The highest burden of gastrointestinal cancers, including stomach, liver, oesophageal and gallbladder cancers, was observed in regions in East Asia. The increasing burden of gastrointestinal cancers in East Asian regions is related to population growth, ageing and the westernization of lifestyle habits in this region. Furthermore, the rising incidence of young-onset colorectal cancer is an emerging trend in East Asia. This Review provides a comprehensive and updated summary of the epidemiology of gastrointestinal cancers in East Asia, with emphasis on comparing their epidemiology in East Asia with that in Western regions, and highlights the major risk factors and implications for prevention. Overall, to optimally reduce the disease burden incurred by gastrointestinal cancers in East Asian regions, a concerted effort will be needed to modify unhealthy lifestyles, promote vaccination against the hepatitis virus, control Helicobacter pylori, liver fluke and hepatitis virus infections, increase the uptake rate of colorectal cancer screening, enhance detection of early cancers and their precursors, and improve cancer survivorship through an organized rehabilitation programme.

Early Diagnosis of Pancreatic Cancer: Clinical Premonitions, Timely Precursor Detection and Increased Curative-Intent Surgery

BACKGROUND

The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis.

ANALYSIS AND RESULTS

Currently, there are no designated diagnostic or screening tests for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of 'omics' technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection.

CONCLUSIONS

Early detection may come from analytics of various body fluids (eg 'liquid biopsies' from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.

Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer

Pancreatic cancer is among the most challenging forms of cancer to treat, owing to its late diagnosis and aggressive nature that reduces the survival rate drastically. Pancreatic cancer diagnosis has been primarily based on imaging, but the current state-of-the-art imaging provides a poor prognosis, thus limiting clinicians' treatment options. The advancement of a cancer diagnosis has been enhanced through the integration of artificial intelligence and imaging modalities to make better clinical decisions. In this review, we examine how AI models can improve the diagnosis of pancreatic cancer using different imaging modalities along with a discussion on the emerging trends in an AI-driven diagnosis, based on cytopathology and serological markers. Ethical concerns regarding the use of these tools have also been discussed.

LINC00941 promotes pancreatic cancer malignancy by interacting with ANXA2 and suppressing NEDD4L-mediated degradation of ANXA2

Recently, long non-coding RNAs (lncRNA) have been proven to regulate pancreatic cancer (PC) progression. We aimed to explore the pathogenesis of LINC00941 in PC regarding protein binding. By using PCR analysis, we found that LINC00941 was overexpressed in PC tissues and was higher in patients with liver metastasis than in patients without liver metastasis. In addition, high LINC00941 expression was associated with a poor prognosis. Functional experiments and mice models were respectively used to evaluate PC cell proliferation and migration in vitro and in vivo. The results suggested that LINC00941 overexpression promoted PC proliferation and metastasis. Subsequently, RNA pull-down, mass spectrometry (MS), and RNA-binding protein immunoprecipitation (RIP) were performed to identify LINC00941-interacting proteins. The results suggested that ANXA2 was the potential LINC00941-interacting protein. Nucleotides 500-1390 of LINC00941 could bind to the Annexin 1 domain of ANXA2. LINC00941-mediated malignant phenotype of PC was reversed by ANXA2 depletion. Co-immunoprecipitation (Co-IP) followed by MS was conducted to determine the potential interacting protein of LINC00941. The results illustrated that NEDD4L, an E3 ligase involved in ubiquitin-mediated protein degradation, bound to the Annexin 1 domain of ANXA2 and promoted its degradation. Mechanically, LINC00941 functioned as a decoy to bind to ANXA2 and suppressed its degradation by enclosing the domain that binds to NEDD4L. Eventually, LINC00941 upregulated ANXA2 and activated FAK/AKT signaling, increasing PC cell proliferation and metastasis. This study indicates that LINC00941 promotes PC proliferation and metastasis by binding ANXA2 and potentiating its stability, leading to the activation of FAK/AKT signaling. Our data demonstrate that LINC00941 may serve as a novel target for prognosis and therapy.