Serum CA 19-9 as a Biomarker for Pancreatic Cancer-A Comprehensive Review

Recent advances in surface plasmon resonance for the detection of ovarian cancer biomarkers: a thorough review

Early detection of ovarian cancer (OC) is crucial for effective management and treatment, as well as reducing mortality rates. However, the current diagnostic methods for OC are time-consuming and have low accuracy. Surface plasmon resonance (SPR) biosensors offer a promising alternative to conventional techniques, as they enable rapid and less invasive screening of various circulating indicators. These biosensors are widely used for biomolecular interaction analysis and detecting tumor markers, and they are currently being investigated as a rapid diagnostic tool for early-stage cancer detection. Our main focus is on the fundamental concepts and performance characteristics of SPR biosensors. We also discuss the latest advancements in SPR biosensors that enhance their sensitivity and enable high-throughput quantification of OC biomarkers, including CA125, HE4, CEA, and CA19-9. Finally, we address the future challenges that need to be overcome to advance SPR biosensors from research to clinical applications. The ultimate goal is to facilitate the translation of SPR biosensors into routine clinical practice for the early detection and management of OC.

Identification of miR-6794-3p as a suppressor in pancreatic cancer metastasis

Metastasis is a major cause of treatment failure in patients with pancreatic cancer, highlighting the urgent need for effective therapeutic strategies. Here, we focused on identifying novel miRNAs with key roles in metastasis of pancreatic cancer. Microarray analysis of miRNA expression in metastatic and non-metastatic pancreatic cancer samples revealed significantly lower expression of miR-6794-3p in the metastatic tumor group. Gain- and loss-of-function approaches using the pancreatic cancer cell lines MIA-PaCa-2 and HPAF-II expressing low and high levels of miR-6794-3p, respectively, indicated a role of miR-6794-3p in suppression of cell invasion, migration, and EMT signaling. Importantly, our results showed that miR-6794-3p exerts its effects by inhibiting expression of the chromatin remodeling factor, RBBP4. The resulting suppression of RBBP4 induced an increase in the levels of GRHL2 involved in regulating invasion, migration, and EMT signaling in metastatic pancreatic cancer cells. Consistent with these findings, low miR-6794-3p expression levels correlate with poor pancreatic cancer patient survival. Additional preclinical experiments on nude mice clearly demonstrated inhibitory effects of miR-6794-3p on pancreatic cancer cell metastasis. The collective results highlight the functional significance of miR-6794-3p as a suppressor of metastasis and support its predictive utility as a prognostic biomarker and therapeutic target in pancreatic cancer.

The Five Periampullary Cancers, not Just Different Siblings but Different Families: An International Multicenter Cohort Study

BACKGROUND

Cancer arising in the periampullary region can be anatomically classified in pancreatic ductal adenocarcinoma (PDAC), distal cholangiocarcinoma (dCCA), duodenal adenocarcinoma (DAC), and ampullary carcinoma. Based on histopathology, ampullary carcinoma is currently subdivided in intestinal (AmpIT), pancreatobiliary (AmpPB), and mixed subtypes. Despite close anatomical resemblance, it is unclear how ampullary subtypes relate to the remaining periampullary cancers in tumor characteristics and behavior.

METHODS

This international cohort study included patients after curative intent resection for periampullary cancer retrieved from 44 centers (from Europe, United States, Asia, Australia, and Canada) between 2010 and 2021. Preoperative CA19-9, pathology outcomes and 8-year overall survival were compared between DAC, AmpIT, AmpPB, dCCA, and PDAC.

RESULTS

Overall, 3809 patients were analyzed, including 348 DAC, 774 AmpIT, 848 AmpPB, 1,036 dCCA, and 803 PDAC. The highest 8-year overall survival was found in patients with AmpIT and DAC (49.8% and 47.9%), followed by AmpPB (34.9%, P < 0.001), dCCA (26.4%, P  =  0.020), and finally PDAC (12.9%, P < 0.001). A better survival was correlated with lower CA19-9 levels but not with tumor size, as DAC lesions showed the largest size.

CONCLUSIONS

Despite close anatomic relations of the five periampullary cancers, this study revealed differences in preoperative blood markers, pathology, and long-term survival. More tumor characteristics are shared between DAC and AmpIT and between AmpPB and dCCA than between the two ampullary subtypes. Instead of using collective definitions for "periampullary cancers" or anatomical classification, this study emphasizes the importance of individual evaluation of each histopathological subtype with the ampullary subtypes as individual entities in future studies.

Potential of Carbohydrate Antigen 19-9 and Serum Apolipoprotein A2-Isoforms in the Diagnosis of Stage 0 and IA Pancreatic Cancer

Apolipoprotein A2-ATQ/AT (apoA2-ATQ/AT) is a new biomarker for diagnosing pancreatic cancer (PC). In this study, the value of blood carbohydrate antigen 19-9 (CA19-9) and apoA2-ATQ/AT levels in diagnosing stage 0 and IA PC was evaluated. During 2014-2021, 12 patients with stage 0 PC and 12 patients with IA PC (average age: 73.8 years) underwent resection at JA Onomichi General Hospital. In addition, the data of 200 healthy controls were collected from a community-based cohort study. Levels of two apoA2-isoforms were measured using enzyme-linked immunosorbent assay (ELISA) with specific antibodies to calculate the apoA2-i Index as a surrogate value for apoA2-ATQ/AT. The cutoff value for the apoA2-i Index was determined to be 62.9 μg/mL. CA19-9 levels were also measured through ELISA. Among all 24 patients with PC, the positivity rates for apoA2-i and CA19-9 were 33.3% and 25.0%, respectively. The positivity rates for apoA2-i and CA19-9 were 16.7% and 8.3% in patients with stage 0 PC and 50.0% and 41.7% in those with stage IA, respectively. For CA19-9-negative patients, the apoA2-i positivity rate was 9.1% in stage 0 and 42.9% in stage IA. The combined positivity rate for both markers was 16.7% in stage 0 and 66.7% in stage IA. Imaging findings in apoA2-i- and CA19-9-positive patients included pancreatic duct dilatation (87.5%/100%), duct stenosis (75.0%/50%), and atrophy (87.5%/66.7%). The imaging findings of this study suggest that apoA2-i may enhance the sensitivity for detecting CA19-9-negative stage 0 and IA PC, and complementary measurements with CA19-9 may be valuable for diagnosing early-stage PC. Therefore, minute PC with pancreatic duct dilation, duct stenosis, and atrophy may exhibit a high positivity rate, aiding differential diagnosis.

Expression of the laminin genes family and its relationship to prognosis in pancreatic carcinoma

BACKGROUND AND STUDY AIMS

Laminin is an extracellular matrix molecule that is the major component of the basement membrane and plays a key role in regulating various processes. However, the association between the laminin gene family and the prognosis of pancreatic carcinoma has not been systematically investigated.

PATIENTS AND METHODS

The role of the laminin gene family in pancreatic cancer was evaluated using data from the TCGA database. The effects of different expressions of members of the laminin gene family on pancreatic cancer survival were compared, and their primary cellular roles were examined. The effects of different expressions of positive family genes on proliferation, metastasis, and invasion, as well as EMT and ferroptosis in pancreatic cancer, were also examined.

RESULTS

Based on univariate and multifactorial analysis of pancreatic cancer patients, LAMA3 was identified as an independent prognostic factor for overall survival in pancreatic cancer. LAMA3 was found to be enriched in the actin cytoskeleton, P53 signaling pathway, adhesion molecule junctions, pentose phosphate pathway, and regulatory differences in the cell cycle and focal adhesion. Additionally, high expression of LAMA3 was found to promote cancer proliferation, invasion, and metastasis, facilitate the EMT process, and inhibit ferroptosis.

CONCLUSIONS

Our results identified LAMA3 was associated with the prognosis of patients with pancreatic cancer and may serve as a prognostic biomarker for pancreatic cancer.

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.

Can preoperative Carbohydrate Antigen 19-9 predict metastatic pancreatic cancer? Results of a systematic review and meta-analysis

BACKGROUND

To investigate the relationship between preoperative Carbohydrate Antigen19-9(CA19-9)and pancreatic cancer occult metastasis.

METHODS

Systematic search of MEDLINE, CENTRAL, Web of Science and bibliographic reference lists were conducted. All comparative observational studies investigating the predictive ability of preoperative CA 19-9 in patients with pancreatic cancer were considered. Mean CA-19-9 value in the pancreatic cancer patients with and without metastasis were evaluated. Best cut-off value of CA 19-9 for metastasis was determined using ROC analysis.

RESULTS

Ten comparative observational studies reporting a total of 1431 pancreatic cancer patients with (n = 496) and without (n = 935) metastasis were included. Subsequent meta-analysis demonstrated that mean preoperative CA 19-9 level was significantly higher in patients with metastases compared to those without (MD: 904.4; 95 % CI, 642.08-1166.74, P < 0.0001). The between-study heterogeneity was significant (I2: 99 %, P < 0.00001). ROC analysis yielded a cut-off CA 19-9 level of 336 with a sensitivity and specificity for predicting metastasis of 90 % and 80 %, respectively (AUC = 0.90).

CONCLUSIONS

CA 19-9 level is significantly higher in patients with metastatic pancreatic cancer. A preoperative CA 19-9 value of 336 should be considered as an acceptable cut-off value to design prospective studies.

Circulating tumor DNA and its role in detection, prognosis and therapeutics of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is considered the fifth most prevalent cancer among all types of cancers and has the third most morbidity value. It has the most frequent duplication time and a high recurrence rate. Recently, the most unique technique used is liquid biopsies, which carry many markers; the most prominent is circulating tumor DNA (ctDNA). Varied methods are used to investigate ctDNA, including various forms of polymerase chain reaction (PCR) [emulsion PCR (ePCR), digital PCR (dPCR), and bead, emulsion, amplification, magnetic (BEAMing) PCR]. Hence ctDNA is being recognized as a potential biomarker that permits early cancer detection, treatment monitoring, and predictive data on tumor burden are subjective to therapy or surgery. Numerous ctDNA biomarkers have been investigated based on their alterations such as 1) single nucleotide variations (either insertion or deletion of a nucleotide) markers including TP53, KRAS, and CCND1; 2) copy number variations which include markers such as CDK6, EFGR, MYC and BRAF; 3) DNA methylation (RASSF1A, SEPT9, KMT2C and CCNA2); 4) homozygous mutation includes ctDNA markers as CDKN2A, AXIN1; and 5) gain or loss of function of the genes, particularly for HCC. Various researchers have conducted many studies and gotten fruitful results. Still, there are some drawbacks to ctDNA namely low quantity, fragment heterogeneity, less stability, limited mutant copies and standards, and differential sensitivity. However, plenty of investigations demonstrate ctDNA's significance as a polyvalent biomarker for cancer and can be viewed as a future diagnostic, prognostic and therapeutic agent. This article overviews many conditions in genetic changes linked to the onset and development of HCC, such as dysregulated signaling pathways, somatic mutations, single-nucleotide polymorphisms, and genomic instability. Additionally, efforts are also made to develop treatments for HCC that are molecularly targeted and to unravel some of the genetic pathways that facilitate its early identification.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

Innate and adaptive immune-directed tumour microenvironment in pancreatic ductal adenocarcinoma

One of the most deadly and aggressive cancers in the world, pancreatic ductal adenocarcinoma (PDAC), typically manifests at an advanced stage. PDAC is becoming more common, and by the year 2030, it is expected to overtake lung cancer as the second greatest cause of cancer-related death. The poor prognosis can be attributed to a number of factors, including difficulties in early identification, a poor probability of curative radical resection, limited response to chemotherapy and radiotherapy, and its immunotherapy resistance. Furthermore, an extensive desmoplastic stroma that surrounds PDAC forms a mechanical barrier that prevents vascularization and promotes poor immune cell penetration. Phenotypic heterogeneity, drug resistance, and immunosuppressive tumor microenvironment are the main causes of PDAC aggressiveness. There is a complex and dynamic interaction between tumor cells in PDAC with stromal cells within the tumour immune microenvironment. The immune suppressive microenvironment that promotes PDAC aggressiveness is contributed by a range of cellular and humoral factors, which itself are modulated by the cancer. In this review, we describe the role of innate and adaptive immune cells, complex tumor microenvironment in PDAC, humoral factors, innate immune-mediated therapeutic advances, and recent clinical trials in PDAC.

CA19-9 and CEA biosensors in pancreatic cancer

Cancer is a complex pathophysiological condition causing millions of deaths each year. Early diagnosis is essential especially for pancreatic cancer. Existing diagnostic tools rely on circulating biomarkers such as Carbohydrate Antigen 19-9 (CA19-9) and Carcinoembryonic Antigen (CEA). Unfortunately, these markers are nonspecific and may be increased in a variety of disorders. Accordingly, diagnosis of pancreatic cancer generally involves more invasive approaches such as biopsy as well as imaging studies. Recent advances in biosensor technology have allowed the development of precise diagnostic tools having enhanced analytical sensitivity and specificity. Herein we examine these advances in the detection of cancer in general and in pancreatic cancer specifically. Furthermore, we highlight novel technologies in the measurement of CA19-9 and CEA and explore their future application in the early detection of pancreatic cancer.

Unusual Presentation of a Hepatic Neuroendocrine Tumor With Elevated CEA and CA 19-9: A Case Report

Neuroendocrine tumors (NETs) of the gastrointestinal tract (GIT) are rare malignancies, which may have unique presentations. The diagnostic process predominantly relies on immunohistochemical analysis. While tumor markers are extensively utilized in diagnosing and monitoring GI malignancies, their specific role in NETs has not been fully explored. This case describes an 83-year-old male presenting with jaundice and general weakness. Diagnostic imaging through MRI and CT angiography (CTA) revealed a nodular texture on the liver's surface suggesting cirrhosis. The presence of elevated tumor markers, specifically carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA 19-9), raised suspicions of malignancy. A subsequent liver biopsy confirmed the diagnosis of small-cell high-grade neuroendocrine carcinoma accompanied by reactive fibrosis. As per our knowledge, this case is the first recorded instance of a liver neuroendocrine tumor (NET) exhibiting elevated levels of both CEA and CA 19-9, with no abnormalities detected in the gallbladder, biliary tree, and bowel in the MRI with magnetic resonance cholangiopancreatography (MRCP) and CTA. This is an atypical presentation of a liver NET, mimicking cirrhotic liver morphology, and underscores the potential diagnostic relevance of tumor markers CEA and CA 19-9 in such cases.

Integrating a microRNA signature as a liquid biopsy-based tool for the early diagnosis and prediction of potential therapeutic targets in pancreatic cancer

INTRODUCTION

Pancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies.

MATERIALS AND METHODS

The analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved.

RESULTS

Our multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients.

CONCLUSION

A panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1) and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

A highly specific antibody against the core fucose of the N-glycan in IgG identifies the pulmonary diseases and its regulation by CCL2

Glycan structure is often modulated in disease or predisease states, suggesting that such changes might serve as biomarkers. Here, we generated a monoclonal antibody (mAb) against the core fucose of the N-glycan in human IgG. Notably, this mAb can be used in Western blotting and ELISA. ELISA using this mAb revealed a low level of the core fucose of the N-glycan in IgG, suggesting that the level of acore fucosylated (noncore fucosylated) IgG was increased in the sera of the patients with lung cancer, chronic obstructive pulmonary disease, and interstitial pneumonia compared to healthy subjects. In a coculture analysis using human lung adenocarcinoma A549 cells and antibody-secreting B cells, the downregulation of the FUT8 (α1,6 fucosyltransferase) gene and a low level of core fucose of the N-glycan in IgG in antibody-secreting B cells were observed after coculture. A dramatic alteration in gene expression profiles for cytokines, chemokines, and their receptors were also observed after coculturing, and we found that the identified C-C motif chemokine 2 was partially involved in the downregulation of the FUT8 gene and the low level of core fucose of the N-glycan in IgG in antibody-secreting B cells. We also developed a latex turbidimetric immunoassay using this mAb. These results suggest that communication with C-C motif chemokine 2 between lung cells and antibody-secreting B cells downregulate the level of core fucose of the N-glycan in IgG, i.e., the increased level of acore fucosylated (noncore fucosylated) IgG, which would be a novel biomarker for the diagnosis of patients with pulmonary diseases.

Albumin-Bilirubin (ALBI) Score and Systemic Immune-Inflammation Indexes Used As Pretreatment Outcome Predictors in Patients With Pancreatic Ductal Adenocarcinoma Undergoing Robotic or Open Whipple Procedures: A Logistic Regression Analysis

Background Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer (PC) in the United States. In patients with resectable PC, identification of pretreatment biomarkers before surgery can help in the decision-making process by weighing the benefits of neo-adjuvant therapy, surgical procedure, and adjuvant therapy. The purpose of this study was to determine if the albumin-bilirubin (ALBI) score and immune-inflammatory marker levels can be used in combination as pretreatment predictors of mortality risk in patients undergoing the Whipple procedure (alternatively, pancreatoduodenectomy (PD)) for PDAC. Methods This retrospective study included 115 patients with PDAC who underwent open or robotic Whipple procedures between January 2013 and December 2022 at a single tertiary medical center. Logistic regression analysis was used to find the association between predictors and mortality. Machine learning algorithms were used to calculate the performance of the different models. Results Bivariate analysis showed that the variables "sex" and "body mass index (BMI)" had a potential association with mortality, although statistical significance was not achieved for sex (p = 0.07). Patients with BMIs >25 kg/m2 had a higher risk of mortality compared to patients with BMIs ≤24.9 kg/m2 (odds ratio (OR) = 2.2, 95% CI = 1.03-4.8, p = 0.04). Higher (more positive) ALBI scores (>-2.24) were also associated with increased mortality risk (OR = 4.6, 95% CI = 2-10.5, p = 0.0003). When the cutoff values of the inflammatory markers were used to categorize these variables, values greater than the cutoff values were associated with an increased risk of mortality. In the multivariate logistic regression model, an ALBI score >-2.24 (OR = 4.3, 95% CI = 1.8-10.3, p = 0.0008), neutrophil-to-lymphocyte ratio (NLR) >3.5 (OR = 3.3, 95% CI = 1.4-7.9, p = 0.007), and being a woman (OR = 2.6, 95% CI = 1.1-6.4, p = 0.03) remained influential predictors of increased mortality (c value = 0.77). Conclusion The ALBI score and the NLR are easily accessible markers; their use, combined with a patient's sex, can provide useful pre-surgical information regarding mortality risk after PD. This can aid in treatment planning as well as expedite decisions about the type of Whipple procedure, adjuvant therapy, and surveillance, which can subsequently improve a patient's outcomes and survival.

Circulating Tumor DNA: Towards More Individualized Treatment for Patients with Resectable Colorectal Cancer

PURPOSE

Despite curative-intent treatment, recurrence is common for patients with colorectal cancer (CRC).  Currently, prediction of disease recurrence and prognostication following surgery is based upon vague clinical factors and more precise and dynamic biomarkers for risk stratification and treatment decisions are urgently needed.  Circulating tumor DNA (ctDNA) is a promising biomarker for patients undergoing treatment for resectable CRC.

METHODS

In this review, we provide an overview of the data supporting current uses of ctDNA for CRC, including localized CRC and resectable colorectal liver metastases (CLM), as well as descriptions of important ongoing clinical trials using ctDNA in the care of patients with CRC.

RESULTS

The detection of ctDNA following curative-intent therapy is associated with disease recurrence, and multiple trials are investigating its role in determining need and duration for adjuvant therapy for localized CRC. In addition, ctDNA reliably predicts prognosis for patients with CLM, with trials underway studying ctDNA-guided treatment sequencing and intensity.

CONCLUSION

The detection of ctDNA is a sensitive and dynamic biomarker for disease recurrence in CRC. Many investigations are underway into ctDNA's potential role in surveillance and treatment algorithms, and it has the potential to become a critical biomarker to determine individualized strategies for treatment sequencing, choice, and duration of therapies.

Case Report: Overcoming challenges in pancreatic cancer with liver metastases: a personalized therapeutic odyssey of TACE, ablation, and immunotherapy

Pancreatic cancer represents a malignant neoplasm originating from pancreatic cells. The optimal approach to cancer treatment remains uncertain, lacking a definitive consensus. Here, we present a compelling case of a 49-year-old female with pancreatic head cancer with liver metastases, as identified by CT and confirmed by biopsy. PET-CT indicated widespread metastatic involvement. TACE therapy with gemcitabine and cisplatin was initiated, yielding a stable disease response. The patient's high PD-L1 expression prompted TACE-PD-1 monoclonal antibody combination therapy. Subsequent treatments, including ablation, sustained PD-1 immunotherapy, and consolidation TACE, culminated in a complete response, as evidenced by imaging and tumor marker dynamics. Our case underscores the potential of multifaceted strategies in managing aggressive pancreatic cancer.

Aquaporins Transcripts with Potential Prognostic Value in Pancreatic Cancer

Pancreatic cancer is anticipated to be the second leading cause of cancer-related death by 2030. Aquaporins (AQPs), a family of water channel proteins, have been linked to carcinogenesis. The aim of this study was to determine AQP gene expression in pancreatic cancer tissues and to validate aquaporins as possible diagnosis and/or prognosis genes. The relative gene expression levels of AQP1, AQP3, AQP5, and AQP9 were analyzed using real-time quantitative PCR (RT-qPCR) in 24 paired pancreatic tumors and adjacent healthy tissues according to variables such as age, gender, and tumor invasiveness and aggressiveness. AQPs transcripts were detected in both healthy and tumor tissues. While AQP1 was downregulated in the tumor samples, AQP3 was particularly overexpressed in low-grade invasive tumors. Interestingly, most of the strong positive Pearson correlation coefficients found between AQPs in healthy tissues were lost when analyzing the tumor tissues, suggesting disruption of the coordinated AQP-gene expression in pancreatic cancer.

CA 19-9 but Not IGF-1/IGFBP-2 Is a Useful Biomarker for Pancreatic Ductal Adenocarcinoma (PDAC) and Chronic Pancreatitis (CP) Differentiation

INTRODUCTION

There are still no effective diagnostic and prognostic biomarkers in pancreatic ductal adenocarcinoma (PDAC). The differentiation between PDAC and chronic pancreatitis (CP) is often challenging. The inflammatory mass in the course of CP causes diagnostic difficulties in differentiating them from neoplastic lesions and, thus, delays the initiation of radical treatment. Insulin-like growth factor 1 (IGF-1) and insulin-like growth factor-binding protein 2 (IGFBP-2) form a network involved in PDAC development. The role of IGFs in promoting pancreatic cancer cell proliferation, survival, and migration is well established, and their ability to stimulate tumor growth and metastasis is well documented. The aim of the study was to evaluate the usability of IGF-1, IGFBP-2, and IGF-1/IGFBP-2 ratio in PDAC and CP differentiation.

MATERIAL AND METHODS

The study included 137 patients: 89 patients with PDAC and 48 patients with CP. All subjects were tested for the levels of IGF-1 and IGFBP-2 using the ELISA method (Corgenix UK Ltd. R&D Systems), along with the level of CA 19-9 in serum. Additionally, the IGF-1/IGFBP-2 ratio was calculated. Further analyses used logit and probit models with varying determinants in order to discern between PDAC and CP patients. The models served as a basis for AUROC calculation.

RESULTS

The mean IGF-1 serum level was equal to 52.12 ± 33.13 ng/mL in PDAC vs. 74.23 ± 48.98 ng/mL in CP (p = 0.0053). The mean level of IGFBP-2 was equal to 305.95 ± 194.58 ng/mL in PDAC vs. 485.43 ± 299 ng/mL in CP (p = 0.0002). The mean CA 19-9 serum concentration was 434.95 ± 419.98 U/mL in PDAC vs. 78.07 ± 182.36 U/mL in CP (p = 0.0000). The mean IGF-1/IGFBP-2 ratio was 0.213 ± 0.14 in PDAC vs. 0.277 ± 0.33 in CP (p = 0.1914). The diagnostic usefulness of indicators for the purpose of PDAC and CP differentiation was assessed by means of AUROC comparison. The AUROCs of IGF-1, IGFBP-2, and IGF-1/IGFBP-2 ratio ranged below 0.7, being lower than the AUROC of CA 19-9 (0.7953; 0.719 within 95% CI). Together, the CA 19-9 and IGFBP-2 AUROCs also ranged below 0.8. When age was included, the AUROC increased to 0.8632, and its 95% confidence interval held above the 0.8 limit. The sensitivity of the used markers was not correlated to the stage of pancreatic PDAC.

CONCLUSIONS

The presented results indicate that CA 19-9 is a marker demonstrating high potential for PDAC and CP differentiation. The inclusion of additional variables into the model, such as the serum level of IGF-1 or IGFBP-2, slightly increased the sensitivity in differentiating CP from PDAC. The IGF-1/IGFBP-2 ratio turned out to be a good marker of pancreatic diseases, but insufficient for the purpose of CP and PDAC differentiation.

Measuring blood cell DNA damage using the PIG-A mutation and CBMN assay in pancreatic cancer patients: a pilot study

Pancreatic cancer still has one of the worst prognoses of all solid malignancies, despite developments in cancer knowledge and care. Research into pancreatic cancer has not fully translated into clinical improvements and as a result, fewer than 1% of patients survive 10 years post-diagnosis. This bleak outlook for patients could be improved by earlier diagnosis. The human erythrocyte phosphatidylinositol glycan class A (PIG-A) assay monitors the mutation status of the X-linked PIG-A gene by measuring glycosyl phosphatidylinositol (GPI)-anchored proteins on the extracellular surface. We have previously identified an elevated PIG-A mutant frequency in oesophageal adenocarcinoma patients and here investigate whether this could be seen in a pancreatic cancer cohort, given the urgent need for novel pancreatic cancer biomarkers. In our pilot study, an elevated PIG-A mutant frequency (5.775 × 10-6 (95% CI 4.777-10) mutants per million) was seen in pancreatic cancer patients (n = 30) when compared to the non-cancer control group (n = 14) who had an erythrocyte mutant frequency of 4.211 × 10-6 (95% CI 1.39-5.16) mutants per million (p = 0.0052). A cut-off value of 4.7 mutants per million provided an AUROC of 0.7595 with a sensitivity of 70% and specificity of 78.57%. A secondary measure of DNA damage in an alternative blood cell population also showed an increase in peripheral lymphocytes using the cytokinesis-block micronucleus assay (p = 0.0164) (AUROC = 0.77, sensitivity = 72.22%, specificity = 72.73%). The micronucleus frequency and PIG-A status show some potential as blood-based biomarkers of pancreatic cancer, but further investigations of these DNA damage tests are required to assess their utility in pancreatic cancer diagnosis.

Sensitive amplified luminescent proximity homogeneous assay for the quantitative detection of CA242

We here developed a sensitive and stable amplified luminescent proximity homogeneous assay (AlphaLISA) method for fast quantification of CA242 in human serum. Donor and acceptor beads modified with carboxyl groups could be coupled with CA242 antibodies after activation in the AlphaLISA method. CA242 was rapidly detected by the double antibody sandwich immunoassay. The method yielded good linearity (>0.996) and detection range (0.16-400 U/mL). The intra-assay precisions of CA242-AlphaLISA were between 3.43% and 6.81% (< 10%), and the inter-assay precisions were between 4.06% and 9.56% (< 15%). The relative recoveries ranged from 89.61% to 107.29%. Detection time for the CA242-AlphaLISA method was only 20 min. Moreover, results of CA242-AlphaLISA and time-resolved fluorescence immunoassay had satisfactory correlation and consistency (ρ = 0.9852). The method was successfully applied to the analysis of human serum samples. Meanwhile, serum CA242 has a good detection value in the identification and diagnosis of pancreatic cancer and the monitoring of disease degree. Furthermore, the proposed AlphaLISA method is expected to be an alternative to traditional detection methods, laying a good foundation for the further development of kits to detect other biomarkers in future studies.

Prediction of Pathologic Change Development in the Pancreas Associated with Diabetes Mellitus Assessed by NMR Metabolomics

Nuclear magnetic resonance (NMR) metabolomics was used for identification of metabolic changes in pancreatic cancer (PC) blood plasma samples when compared to healthy controls or diabetes mellitus patients. An increased number of PC samples enabled a subdivision of the group according to individual PC stages and the construction of predictive models for finer classification of at-risk individuals recruited from patients with recently diagnosed diabetes mellitus. High-performance values of orthogonal partial least squares (OPLS) discriminant analysis were found for discrimination between individual PC stages and both control groups. The discrimination between early and metastatic stages was achieved with only 71.5% accuracy. A predictive model based on discriminant analyses between individual PC stages and the diabetes mellitus group identified 12 individuals out of 59 as at-risk of development of pathological changes in the pancreas, and four of them were classified as at moderate risk.

Surface Plasmon Resonance (SPR) Sensor for Cancer Biomarker Detection

A biomarker is a physiological observable marker that acts as a stand-in and, in the best-case scenario, forecasts a clinically significant outcome. Diagnostic biomarkers are more convenient and cost-effective than directly measuring the ultimate clinical outcome. Cancer is among the most prominent global health problems and a major cause of morbidity and death globally. Therefore, cancer biomarker assays that are trustworthy, consistent, precise, and verified are desperately needed. Biomarker-based tumor detection holds a lot of promise for improving disease knowledge at the molecular scale and early detection and surveillance. In contrast to conventional approaches, surface plasmon resonance (SPR) allows for the quick and less invasive screening of a variety of circulating indicators, such as circulating tumor DNA (ctDNA), microRNA (miRNA), circulating tumor cells (CTCs), lipids, and proteins. With several advantages, the SPR technique is a particularly beneficial choice for the point-of-care identification of biomarkers. As a result, it enables the timely detection of tumor markers, which could be used to track cancer development and suppress the relapse of malignant tumors. This review emphasizes advancements in SPR biosensing technologies for cancer detection.

Combination of serum human satellite RNA and miR-21-5p levels as a biomarker for pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis due to the difficulty of its diagnosis. Because human satellite II (HSATII) RNA, a satellite repeat RNA, is highly and specifically expressed in human PDAC, the serum HSATII RNA level may be a biomarker of PDAC. To measure the serum HSATII RNA level with high sensitivity and reproducibility, we previously developed a convenient method, tandem repeat amplification by nuclease protection (TRAP) combined with droplet digital PCR (ddPCR). Here, we refined the original method by simultaneously measuring the serum miR-21-5p level to enhance the detection of PDAC. The resulting PDAC-Index, constructed using serum HSATII RNA and miR-21-5p levels, discriminated patients with PDAC with high accuracy. We verified the clinical usefulness of the PDAC-Index as a supportive test in difficult-to-diagnose cases. The PDAC-Index has satisfactory diagnostic performance and may routinely be applied for detecting PDAC.

Pancreatic Mass Characterization Using IVIM-DKI MRI and Machine Learning-Based Multi-Parametric Texture Analysis

Non-invasive characterization of pancreatic masses aids in the management of pancreatic lesions. Intravoxel incoherent motion-diffusion kurtosis imaging (IVIM-DKI) and machine learning-based texture analysis was used to differentiate pancreatic masses such as pancreatic ductal adenocarcinoma (PDAC), pancreatic neuroendocrine tumor (pNET), solid pseudopapillary epithelial neoplasm (SPEN), and mass-forming chronic pancreatitis (MFCP). A total of forty-eight biopsy-proven patients with pancreatic masses were recruited and classified into pNET (n = 13), MFCP (n = 6), SPEN (n = 4), and PDAC (n = 25) groups. All patients were scanned for IVIM-DKI sequences acquired with 14 b-values (0 to 2500 s/mm2) on a 1.5T MRI. An IVIM-DKI model with a 3D total variation (TV) penalty function was implemented to estimate the precise IVIM-DKI parametric maps. Texture analysis (TA) of the apparent diffusion coefficient (ADC) and IVIM-DKI parametric map was performed and reduced using the chi-square test. These features were fed to an artificial neural network (ANN) for characterization of pancreatic mass subtypes and validated by 5-fold cross-validation. Receiver operator characteristics (ROC) analyses were used to compute the area under curve (AUC). Perfusion fraction (f) was significantly higher (p < 0.05) in pNET than PDAC. The f showed better diagnostic performance for PDAC vs. MFCP with AUC:0.77. Both pseudo-diffusion coefficient (D*) and f for PDAC vs. pNET showed an AUC of 0.73. ADC and diffusion coefficient (D) showed good diagnostic performance for pNET vs. MFCP with AUC: 0.79 and 0.76, respectively. In the TA of PDAC vs. non-PDAC, f and combined IVIM-DKI parameters showed high accuracy ≥ 84.3% and AUC ≥ 0.84. Mean f and combined IVIM-DKI parameters estimated that the IVIM-DKI model with TV texture features has the potential to be helpful in characterizing pancreatic masses.

Epigenetic reprogramming in pancreatic premalignancy and clinical implications

Pancreatic cancer (PC) is the most lethal human cancer, with less than 10% 5-year survival. Pancreatic premalignancy is a genetic and epigenomic disease and is linked to PC initiation. Pancreatic premalignant lesions include pancreatic intraepithelial neoplasia (PanIN), intraductal papillary mucinous neoplasm (IPMN), and mucinous cystic neoplasm (MCN), with pancreatic acinar-to-ductal metaplasia (ADM) as the major source of pancreatic premalignant lesions. Emerging evidence reveals that an epigenetic dysregulation is an early event in pancreatic tumorigenesis. The molecular mechanisms of epigenetic inheritance include chromatin remodeling; modifications in histone, DNA, and RNA; non-coding RNA expression; and alternative splicing of RNA. Changes in those epigenetic modifications contribute to the most notable alterations in chromatin structure and promoter accessibility, thus leading to the silence of tumor suppressor genes and/or activation of oncogenes. The expression profiles of various epigenetic molecules provide a promising opportunity for biomarker development for early diagnosis of PC and novel targeted treatment strategies. However, how the alterations in epigenetic regulatory machinery regulate epigenetic reprogramming in pancreatic premalignant lesions and the different stages of their initiation needs further investigation. This review will summarize the current knowledge of epigenetic reprogramming in pancreatic premalignant initiation and progression, and its clinical applications as detection and diagnostic biomarkers and therapeutic targets in PC.

Pharmacotherapeutic options for pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy projected to be the 2^nd leading cause of cancer related death in the USA by 2030. This manuscript discusses current and evolving treatment approaches in patients with pancreatic cancer.

AREAS COVERED

PDAC is classified as: a) resectable, b) borderline resectable, c) unresectable (locally advanced and metastatic). The standard of care for patients who present with resectable pancreatic adenocarcinoma is six months of adjuvant modified (m) FOLFIRINOX, gemcitabine plus capecitabine, or single agent gemcitabine. For many reasons, there has been a paradigm shift to employing neoadjuvant chemotherapy. For resectable and borderline resectable patients, we generally start with systemic therapy and reevaluate resectability with subsequent scans specifically when the tumor is located in the head or body of the pancreas. Combined chemoradiation therapy can be employed in select patients. The standard of care for metastatic PDAC is FOLFIRINOX or gemcitabine and nab-paclitaxel. Germline and somatic genomic profiling should be obtained in all patients. Patients with a germline BRCA mutation can receive upfront gemcitabine and cisplatin.

EXPERT OPINION

Thorough understanding of molecular pathogenesis in PDAC has opened various therapeutic avenues. We remain optimistic that future treatment modalities such as targeted therapies, cellular therapies and immunotherapy will further improve survival in PDAC.

Understanding the cross-talk between human microbiota and gastrointestinal cancer for developing potential diagnostic and prognostic biomarkers

The interaction between gut microbes and gastrointestinal (GI) tract carcinogenesis has always attracted researchers' attention to identify therapeutic targets or potential prognostic biomarkers. Various studies have suggested that the microbiota do show inflammation and immune dysregulation, which led to carcinogenesis in GI tract. In this review, we have focused on the role of microbes present in the gut, intestine, or faeces in GI tract cancers, including esophageal cancer, gastric cancer, and colorectal cancer. Herein, we have discussed the importance of the microbes and their metabolites, which could serve as diagnostic biomarkers for cancer detection, especially in the early stage, and prognostic markers. To maximize the effect of the treatment strategies, an accurate evaluation of the prognosis is imperative for clinicians. There is a vast difference in the microbiota profiles within a population and across the populations depending upon age, diet, lifestyle, genetic makeup, use of antibiotics, and environmental factors. Therefore, the diagnostic efficiency of the microbial markers needs to be further validated. A deeper understanding of the GI cancer and the host microbiota is needed to acquire pivotal information about disease status.

Heterogeneity of metabolic adaptive capacity affects the prognosis among pancreatic ductal adenocarcinomas

BACKGROUND

Evolutionary cancer has a supply mechanism to satisfy higher energy demands even in poor-nutrient conditions. Metabolic reprogramming is essential to supply sufficient energy. The relationship between metabolic reprogramming and the clinical course of pancreatic ductal adenocarcinoma (PDAC) remains unclear. We aimed to clarify the differences in metabolic status among PDAC patients.

METHODS

We collected clinical data from 128 cases of resectable PDAC patients undergoing surgery. Sixty-three resected tissues, 15 tissues from the low carbohydrate antigen 19-9 (CA19-9), 38-100 U/mL, and high CA19-9, > 500 U/mL groups, and 33 non-tumor control parts, were subjected to tandem mass spectrometry workflow to systematically explore metabolic status. Clinical and proteomic data were compared on the most used PDAC biomarker, preoperative CA19-9 value.

RESULTS

Higher CA19-9 levels were clearly associated with higher early recurrence (p < 0.001), decreased RFS (p < 0.001), and decreased DSS (p = 0.025). From proteomic analysis, we discovered that cancer evolution-related as well as various metabolism-related pathways were more notable in the high group. Using resected tissue immunohistochemical staining, we learned that high CA19-9 PDAC demonstrated aerobic glycolysis enhancement, yet no decrease in protein synthesis. We found a heterogeneity of various metabolic processes, including carbohydrates, proteins, amino acids, lipids, and nucleic acids, between the low and the high groups, suggesting differences in metabolic adaptive capacity.

CONCLUSIONS

Our study found metabolic adaptation differences among PDAC cases, pertaining to both cancer evolution and the prognosis. CA19-9 can help estimate the metabolic adaptive capacity of energy supply for PDAC evolution.

Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy

Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer's detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.

Nanomedicine for overcoming therapeutic and diagnostic challenges associated with pancreatic cancer

Pancreatic cancer is the second leading cause of cancer-related death in the USA. The 5-year survival rate for pancreatic cancer is as low as 10%, making it one of the most deadly cancers. This dismal prognosis is caused, in part, by the lack of early detection and screening options, leading to late-stage detection of the disease, at a point at which chemotherapy is no longer effective. However, nanoparticle (NP) drug delivery systems have increased the efficacy of chemotherapeutics by improving the targeting ability of drugs to the tumor site, while also decreasing the risk of local and systemic toxicity. Such efforts can contribute to the development of early diagnosis and routine screening tests, which will drastically improve the survival rates and prognosis of patients with pancreatic cancer.

Combined multiagent chemotherapy and radiotherapy is associated with prolonged overall survival in patients with non-operatively managed stage II-III pancreatic adenocarcinoma

BACKGROUND

Most patients with pancreatic adenocarcinoma (PDAC) do not undergo surgical resection. The role of radiotherapy (RT) in non-operatively managed localized pancreatic adenocarcinoma is unclear.

METHODS

The National Cancer Database (2010-2016) was queried for patients with clinical stage II-III PDAC treated with multiagent systemic chemotherapy (CT) +/- RT but not surgery. Factors associated with the receipt of RT and overall survival were compared after adjusting for patient demographics and clinical characteristics.

RESULTS

A total of 14,921 patients were included, of whom 9279 received CT and 5382 received CT + RT. Patients treated with CT + RT were more likely to be younger (65vs66yrs), treated at non-academic facilities (48.8%vs46.7%), have private insurance (40.3%vs36.5%), and have clinical T4 tumors (53.6%vs48.7%). Most patients who were treated with RT received external beam radiotherapy (89.3%), and the median dose was 5,000 cGy. Median time to start of RT was 129 days. CT + RT was associated with longer overall survival (15.9vs11.8mos,p < 0.001), and remained associated with survival on multivariable analysis (HR 0.74, 95%CI 0.70-0.78). On a 4-month conditional survival analysis, combined CT + RT remained associated with improved survival compared to CT alone (16.0vs13.1mos,p < 0.001).

CONCLUSIONS

In patients with non-operatively managed localized pancreatic adenocarcinoma, combined radiotherapy and multiagent systemic chemotherapy is associated with improved overall survival compared to chemotherapy alone.

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.

On Demand Biosensors for Early Diagnosis of Cancer and Immune Checkpoints Blockade Therapy Monitoring from Liquid Biopsy

Recently, considerable interest has emerged in the development of biosensors to detect biomarkers and immune checkpoints to identify and measure cancer through liquid biopsies. The detection of cancer biomarkers from a small volume of blood is relatively fast compared to the gold standard of tissue biopsies. Traditional immuno-histochemistry (IHC) requires tissue samples obtained using invasive procedures and specific expertise as well as sophisticated instruments. Furthermore, the turnaround for IHC assays is usually several days. To overcome these challenges, on-demand biosensor-based assays were developed to provide more immediate prognostic information for clinicians. Novel rapid, highly precise, and sensitive approaches have been under investigation using physical and biochemical methods to sense biomarkers. Additionally, interest in understanding immune checkpoints has facilitated the rapid detection of cancer prognosis from liquid biopsies. Typically, these devices combine various classes of detectors with digital outputs for the measurement of soluble cancer or immune checkpoint (IC) markers from liquid biopsy samples. These sensor devices have two key advantages: (a) a small volume of blood drawn from the patient is sufficient for analysis, and (b) it could aid physicians in quickly selecting and deciding the appropriate therapy regime for the patients (e.g., immune checkpoint blockade (ICB) therapy). In this review, we will provide updates on potential cancer markers, various biosensors in cancer diagnosis, and the corresponding limits of detection, while focusing on biosensor development for IC marker detection.

Retroperitoneal Bronchogenic Cyst Mimicking a Pancreatic Cystic Lesion with Extremely High Level of Intralesional Fluid CA-19.9 Antigen: Benign in Disguise

Bronchogenic cysts are congenital benign tumors resulting from abnormal budding of the primitive foregut. Usually presented on the posterior mediastinum, its presence on the retroperitoneum is extremely rare. We present an asymptomatic lady patient with a retroperitoneal cystic lesion that was submitted to endoscopic ultrasound-guided biopsies and intracystic fluid aspiration with histology excluding malignance despite intracystic fluid biochemical analysis that disclosed extremely high carbohydrate antigen 19-9. Definite diagnosis of bronchogenic cyst was only possible after complete surgical resection of the lesion. Furthermore, we discuss the use of this antigen as a tumor marker in this situation and its relevance to the preoperative diagnosis of such lesions.

An Immunohistochemical Evaluation of Tumor-Associated Glycans and Mucins as Targets for Molecular Imaging of Pancreatic Ductal Adenocarcinoma

Simple Summary

Distinguishing pancreatic cancer from healthy tissue before and during surgery can be enhanced by using molecular tracers directed at molecules on tumor cells allowing high-contrast visualization of tumor tissue, eventually improving diagnosis and surgical removal. Albeit sugar molecules and proteins carrying a large amount of sugars-mucins- have gained significant interest as tumor-specific targets, their relative presence on structures surrounding tumor tissues and lymph node metastases is unknown. The current study shows that the presence of several, but not all, investigated sugar molecules and mucins on pancreatic cancer cells is higher compared to surrounding tissues. Moreover, given their abundance on tumor cells in lymph nodes and their absence on normal lymph nodes, all investigated targets are high-potential targets for visualization of lymph node metastases. This study paves the way for the development of molecular tracers against the targets evaluated herein to allow improvement of pancreatic cancer treatment.

Abstract

Targeted molecular imaging may overcome current challenges in the preoperative and intraoperative delineation of pancreatic ductal adenocarcinoma (PDAC). Tumor-associated glycans Le^a/c/x, sdi-Le^a, sLe^a, sLe^x, sTn as well as mucin-1 (MUC1) and mucin-5AC (MU5AC) have gained significant interest as targets for PDAC imaging. To evaluate their PDAC molecular imaging potential, biomarker expression was determined using immunohistochemistry on PDAC, (surrounding) chronic pancreatitis (CP), healthy pancreatic, duodenum, positive (LN⁺) and negative lymph node (LN⁻) tissues, and quantified using a semi-automated digital image analysis workflow. Positive expression on PDAC tissues was found on 83% for Le^a/c/x, 94% for sdi-Le^a, 98% for sLe^a, 90% for sLe^x, 88% for sTn, 96% for MUC1 and 67% for MUC5AC, where all were not affected by the application of neoadjuvant therapy. Compared to PDAC, all biomarkers were significantly lower expressed on CP, healthy pancreatic and duodenal tissues, except for sTn and MUC1, which showed a strong expression on duodenum (sTn tumor:duodenum ratio: 0.6, p < 0.0001) and healthy pancreatic tissues (MUC1 tumor:pancreas ratio: 1.0, p > 0.9999), respectively. All biomarkers are suitable targets for correct identification of LN⁺, as well as the distinction of LN⁺ from LN⁻ tissues. To conclude, this study paves the way for the development and evaluation of Le^a/c/x-, sdi-Le^a-, sLe^a-, sLe^x- and MUC5AC-specific tracers for molecular imaging of PDAC imaging and their subsequent introduction into the clinic.

The Association of Real-World CA 19-9 Level Monitoring Patterns and Clinical Outcomes Among Patients With Metastatic Pancreatic Ductal Adenocarcinoma

Background

Pancreatic cancer is expected to be the third deadliest cancer in the US in 2021. Evaluation of treatment response in patients with mPDAC necessitates scheduled clinical and radiographic assessments along with monitoring serum CA 19-9 levels. Currently available single-institution data examining the importance of CA 19-9 monitoring cannot be generalized to real-world settings. We investigated the impact of serum CA 19-9 monitoring and its association with clinical outcomes in patients with mPDAC in a population-based setting.

Methods

Data were extracted from the Flatiron Health electronic health record (EHR)-derived de-identified database for patients diagnosed with mPDAC between January 1, 2015, and June 30, 2020. Serum CA 19-9 levels at baseline – defined as the values obtained ≤ 60 days prior to treatment initiation - and during treatment were extracted. CA 19-9 levels > 40 IU/mL were considered elevated. Survival outcomes were compared based on testing frequency, baseline CA 19-9 levels, and change in CA 19-9.

Results

6,118 patients with mPDAC who received treatment were included in the analysis. The median age at diagnosis was 68 years (IQR: 61-75). Patients with normal baseline CA 19-9 experienced longer median survival than patients with elevated levels [1L: 8.8 months (95% CI: 7.9 - 10) vs. 7.2 months (6.8 – 7.5), p < 0.001; 2L: 7.2 months (6.1 – 9.2) vs. 5.2 months (4.9 – 5.6), p < 0.001; 3L: 6.1 months (5.4 – 9.1) vs. 3.9 months (3.4 – 4.3), p < 0.001]. Patients with decreasing/stable CA 19-9 during treatment experienced longer survival than patients who experienced an increase in CA 19-9 levels [1L: 10.9 months (10.5 – 11.3) vs. 5.4 months (5.1 – 5.9), p < 0.0001; 2L: 8.2 months (7.7 – 8.5) vs. 4.3 months (4.1 – 4.7), p < 0.001; 3L: 7.5 months (6.6 – 9.2) vs. 3.7 months (3.4 – 4.3), p < 0.001].

Conclusions

In one of the largest, contemporary, real-world studies of patients with mPDAC, elevated CA 19-9 level at treatment initiation demonstrated a prognostic impact. Routine serial monitoring of CA 19-9 levels during treatment may be warranted, in addition to clinical and radiographic assessment, and may translate into better patient outcomes. Further validation studies are needed to understand the generalizability of these results.

Exploiting the MUC5AC Antigen for Noninvasive Identification of Pancreatic Cancer

Pancreatic cancer (PC) remains the fourth leading cause of cancer death; therefore, there is a clinically unmet need for novel therapeutics and diagnostic markers to treat this devastating disease. Physicians often rely on biopsy or CT for diagnosis, but more specific protein biomarkers are highly desired to assess the stage and severity of PC in a noninvasive manner. Serum biomarkers such as carbohydrate antigen 19-9 are of particular interest as they are commonly elevated in PC but have exhibited suboptimal performance in the clinic. MUC5AC has emerged as a useful serum biomarker that is specific for PC versus inflammation. We developed RA96, an anti-MUC5AC antibody, to gauge its utility in PC diagnosis through immunohistochemical analysis and whole-body PET in PC. Methods: In this study, extensive biochemical characterization determined MUC5AC as the antigen for RA96. We then determined the utility of RA96 for MUC5AC immunohistochemistry on clinical PC and preclinical PC. Finally, we radiolabeled RA96 with 89Zr to assess its application as a whole-body PET radiotracer for MUC5AC quantification in PC. Results: Immunohistochemical staining with RA96 distinguished chronic pancreatitis, pancreatic intraepithelial neoplasia, and varying grades of pancreatic ductal adenocarcinoma in clinical samples. 89Zr-desferrioxamine-RA96 was able to detect MUC5AC with high specificity in mice bearing capan-2 xenografts. Conclusion: Our study demonstrated that RA96 can differentiate between inflammation and PC, improving the fidelity of PC diagnosis. Our immuno-PET tracer 89Zr-desferrioxamine-RA96 shows specific detection of MUC5AC-positive tumors in vivo, highlighting the utility of MUC5AC targeting for diagnosis of PC.

Infection Masquerading as Recurrence of Pancreatic Ductal Adenocarcinoma: A Cautionary Tale

We present a case of a 59-year-old male undergoing adjuvant chemotherapy for his pancreatic adenocarcinoma post-surgical resection. He had an acute rise in carbohydrate antigen (CA) 19-9 level, which raised suspicion of metastatic disease. Instead, the patient was diagnosed to have a liver abscess, the treatment of which brought the CA 19-9 level back to normal. Unfortunately, although CA 19-9 is Food and Drug Administration (FDA)-approved tumor marker for pancreatic cancer, it is also elevated in several benign conditions, causing fear of cancer and unnecessary diagnostic workup. Hence, caution is necessary for interpreting the significance of its elevation.

Surgical Resection or Ablation for Recurrent Pancreatic Ductal Adenocarcinoma: An Analysis of Oncologic Outcomes According to the Recurrence Type

Objective

To evaluate the survival benefits of curative-intent treatment (CIT, including surgery or ablation) for recurrent pancreatic ductal adenocarcinoma (PDAC) depending on the recurrence type and compared the survival outcomes with other treatment modalities.

Background

The treatment for recurrent PDAC is mostly chemotherapy or best supportive care (BSC). Still, the role of CIT for recurrent PDAC is not well established.

Methods

PDAC patients who underwent pancreatectomy between 2004 and 2019 were included. Recurrences were categorized as locoregional (LR), distant, or disseminated. Recurrent PDAC management was classified as CIT, chemotherapy ± radiation therapy (CTX ± RTX), or BSC. The survival after recurrence (SAR) rate was measured from the first day of recurrence to the date of death or last follow-up.

Results

Two hundred eighteen patients had recurrent PDAC and were analyzed (27 CIT, 128 CTX ± RTX, 63 BSC). The 1-, 3-, and 5-year SAR rates were 65.4%, 11.5%, and 11.5% for CIT, 42.1%, 4.0%, and 0% for CTX ± RTX, and 15.9%, 1.6%, and 0% for BSC, respectively. Subgroup analysis indicated the SAR rate was significantly better in the CIT group than in the CTX ± RTX and BSC groups in LR type (P = 0.027) and distant type (P < 0.001). In multivariate analysis, the albumin level at recurrence (hazard ratio, 2.14; 95% confidence interval, 1.15-18.3, P = 0.038) and operation time of the second operation (hazard ratio, 0.98; 95% confidence interval, 0.97-0.99, P = 0.021) were associated with a favorable prognosis of SAR in the CIT group.

Conclusions

CIT should be considered in recurrent PDAC for LR and distant metastases in selected patients.

MicroRNAs as biomarkers and perspectives in the therapy of pancreatic cancer

Pancreatic cancer is considered as one of the most aggressive tumor types, representing over 45,750 mortality cases annually in the USA solely. The aggressive nature and late identification of pancreatic cancer, combined with the restrictions of existing chemotherapeutics, present the mandatory need for the advancement of novel treatment systems. Ongoing reports have shown an important role of microRNAs (miRNAs) in the initiation, migration, and metastasis of malignancies. Besides, abnormal transcriptional levels of miRNAs have regularly been related with etiopathogenesis of pancreatic malignancy, underlining the conceivable utilization of miRNAs in the management of pancreatic disease patients. In this review article, we give a concise outline of molecular pathways involved in etiopathogenesis of pancreatic cancer patients as well as miRNA implications in pancreatic cancer patients. Ensuing sections describe the involvement of miRNAs in the diagnosis, prognosis, and therapy of pancreatic cancer patients. The involvement of miRNAs in the chemoresistance of pancreatic cancers was also discussed. End area portrays the substance of survey with future headings.

Lactoferrin and Its Detection Methods: A Review

Lactoferrin (LF) is one of the major functional proteins in maintaining human health due to its antioxidant, antibacterial, antiviral, and anti-inflammatory activities. Abnormal levels of LF in the human body are related to some serious diseases, such as inflammatory bowel disease, Alzheimer’s disease and dry eye disease. Recent studies indicate that LF can be used as a biomarker for diagnosis of these diseases. Many methods have been developed to detect the level of LF. In this review, the biofunctions of LF and its potential to work as a biomarker are introduced. In addition, the current methods of detecting lactoferrin have been presented and discussed. We hope that this review will inspire efforts in the development of new sensing systems for LF detection.

Exosomal microRNA in Pancreatic Cancer Diagnosis, Prognosis, and Treatment: From Bench to Bedside

Simple Summary

Pancreatic cancer is the fourth leading cause of cancer death in the United States and over 90% of the patients suffer from pancreatic ductal adenocarcinoma (PDAC). PDAC is the most lethal gastrointestinal malignancies and only 10% of the people survive more than 5 years, therefore, novel diagnostic, prognostic, and therapeutic strategies are an immediate necessity. Studies have demonstrated microRNAs in bodily fluids that are bound with membranes (exosomes) can act as stable biomarkers both for disease development and metastasis. The diagnostic, prognostic, as well as therapeutic roles of exosomal microRNAs in pancreatic cancer have been discussed in this review.

Abstract

Pancreatic cancer is the fourth leading cause of cancer death among men and women in the United States, and pancreatic ductal adenocarcinoma (PDAC) accounts for more than 90% of pancreatic cancer cases. PDAC is one of the most lethal gastrointestinal malignancies with an overall five-year survival rate of ~10%. Developing effective therapeutic strategies against pancreatic cancer is a great challenge. Novel diagnostic, prognostic, and therapeutic strategies are an immediate necessity to increase the survival of pancreatic cancer patients. So far, studies have demonstrated microRNAs (miRNAs) as sensitive biomarkers because of their significant correlation with disease development and metastasis. The miRNAs have been shown to be more stable inside membrane-bound vesicles in the extracellular environment called exosomes. Varieties of miRNAs are released into the body fluids via exosomes depending on the normal physiological or pathological conditions of the body. In this review, we discuss the recent findings on the diagnostic, prognostic, and therapeutic roles of exosomal miRNAs in pancreatic cancer.

Diagnosis of malignant versus tuberculous ascites using tumor markers and globulin ratios in serum and ascites: A Fisher discriminant model

BACKGROUND AND STUDY AIMS

This study was conducted to investigate the significance of tumor and biochemical markers in serum and ascitic fluid in the differential diagnosis of tuberculous and malignant ascites.

PATIENTS AND METHODS

Based on findings from natural orifice transluminal endoscopic surgery and postoperative pathology or cytology of 63 patients, they were divided into the malignant group (31 patients) and the tuberculous group (32 patients). Levels of tumor markers, albumin, globulin, and lactate dehydrogenase were measured simultaneously. Data were statistically analyzed, and a Fisher discriminant model was established. The receiver operating characteristic curve was constructed to confirm the discriminant value.

RESULTS

The levels of carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), cancer antigen 19-9 (CA 19-9), and globulin in serum and ascitic fluid were different between the tuberculous and malignant ascites groups (P < .05). The ratios of ascites-to-serum levels of CEA, CA125, and CA 19-9, as well as the ratio of serum-to-ascites of globulin levels, were different between the two groups (P < .05). The Fisher discriminant model was established based on the ascites-to-serum ratios of CEA, CA125, and CA 19-9 levels and the serum-to-ascites ratio of globulin levels. The area under the curve was 0.908, the sensitivity was 0.838 (26/31), and the specificity was 0.875 (28/32).

CONCLUSION

A Fisher discriminant model can be established using serum and ascites tumor markers and globulin ratios, which is valuable in the differential diagnosis of tuberculous versus malignant ascites.