Biomarker For Pancreatic Cancer Research Articles

Fluorescent Anti-MUC5AC Brightly Targets Pancreatic Cancer in a Patient-derived Orthotopic Xenograft.

Overexpression of mucin-5AC (MUC5AC) makes it a targetable biomarker in pancreatic cancer. The present study evaluated tumor targeting with a MUC5AC antibody conjugated to a near-infrared dye in a patient-derived orthotopic xenograft (PDOX) mouse model. MUC5AC monoclonal antibody was conjugated to the near-infrared dye IRDye800CW to synthesize MUC5AC-IR800. PDOX models were established by implanting a high-MUC5AC-expressing patient-derived pancreatic tumor on the pancreas of nude mice. After 4 weeks of PDOX tumor growth, mice were imaged after receiving MUC5AC-IR800 (75 μg) intravenously. In the PDOX models, MUC5AC-IR800 selectively and brightly targeted the pancreatic tumor (tumor to background ratio: 2.46±0.465). MUC5AC-IR800 provides distinct visualization of pancreatic tumors. MUC5AC-IR800 may be used clinically in the future to improve pancreatic cancer resection. This novel fluorescent probe is also promising for targeting of pre-malignant pancreatic lesions with subsequent resection under fluorescence guidance.

Imaging-based Machine-learning Models to Predict Clinical Outcomes and Identify Biomarkers in Pancreatic Cancer: A Scoping Review.

To perform a scoping review of imaging-based machine-learning models to predict clinical outcomes and identify biomarkers in patients with PDAC. Patients with PDAC could benefit from better selection for systemic and surgical therapy. Imaging-based machine-learning models may improve treatment selection. A scoping review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses-scoping review guidelines in the PubMed and Embase databases (inception-October 2020). The review protocol was prospectively registered (open science framework registration: m4cyx). Included were studies on imaging-based machine-learning models for predicting clinical outcomes and identifying biomarkers for PDAC. The primary outcome was model performance. An area under the curve (AUC) of ≥0.75, or a P-value of ≤0.05, was considered adequate model performance. Methodological study quality was assessed using the modified radiomics quality score. After screening 1619 studies, 25 studies with 2305 patients fulfilled the eligibility criteria. All but 1 study was published in 2019 and 2020. Overall, 23/25 studies created models using radiomics features, 1 study quantified vascular invasion on computed tomography, and one used histopathological data. Nine models predicted clinical outcomes with AUC measures of 0.78-0.95, and C-indices of 0.65-0.76. Seventeen models identified biomarkers with AUC measures of 0.68-0.95. Adequate model performance was reported in 23/25 studies. The methodological quality of the included studies was suboptimal, with a median modified radiomics quality score score of 7/36. The use of imaging-based machine-learning models to predict clinical outcomes and identify biomarkers in patients with PDAC is increasingly rapidly. Although these models mostly have good performance scores, their methodological quality should be improved.

Review of Immunohistochemistry Biomarkers in Pancreatic Cancer Diagnosis

Pancreatic cancer is one of the cancer types with poor prognosis and high rate of mortality. Diagnostic modalities for early detection of pancreatic cancer have been among the academic concerns. On account of the potential role of immunohistochemistry (IHC) biomarkers in overcoming certain limitations of imaging diagnostic tools in discriminating pancreatic cancer tissues from benign ones, a growing scholarly attention has been given to the diagnostic efficacy of IHC biomarkers for pancreatic cancer. This review will analyze and synthesize published articles to provide an insight into potential IHC biomarkers for pancreatic cancer diagnosis.

Comprehensive Analysis of Myoferlin in Human Pancreatic Cancer via Bioinformatics.

Pancreatic cancer is the fourth leading cause of cancer-related death and urgently needs biomarkers for clinical diagnosis and prognosis. It has been reported that myoferlin (MYOF) is implicated in the regulation of proliferation, invasion, and migration of tumor cells in many cancers including pancreatic cancer. To confirm the prognostic value of MYOF in pancreatic cancer, a comprehensive cancer versus healthy people analysis was conducted using public data. MYOF mRNA expression levels were compared in many kinds of cancers including pancreatic cancer via the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The results have shown that MYOF mRNA expression levels were upregulated in most types of cancers, especially in pancreatic cancer, compared with healthy people's tissues. Data from the Cancer Cell Line Encyclopedia (CCLE) and European Bioinformatics Institute (EMBL-EML) database also revealed that MYOF mRNA is highly expressed in most cancer cells, particularly in pancreatic cancer cell lines. Furthermore, the prognostic value of MYOF was evaluated using GEPIA and Long-term Outcome and Gene Expression Profiling Database of pan-cancers (LOGpc) database. Higher expression of MYOF was associated with poorer overall survival, especially in the lower stage and lower grade. Coexpressed genes, possible regulators, and the correlation between MYOF expressions were analyzed via the GEPIA and LinkedOmics database. Nineteen coexpressed genes were identified, and most of these genes were related to cancer. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the correlation between MYOF and immune response. Notably, we found that MYOF might have a potential novel immune regulatory role in tumor immunity. These results support that MYOF is a candidate prognostic biomarker for pancreatic cancer, which calls for further genomics research of pancreatic cancer and deeply functional studies on MYOF.

TNFSF9 promotes metastasis of pancreatic cancer by regulating M2 polarization of macrophages through Src/FAK/p-Akt/IL-1β signaling

The effect of tumor necrosis factor superfamily member 9 (TNFSF9) on the metastasis of pancreatic cancer (PC) and the underlying mechanism remain unclear. We studied the expression of TNFSF9 in pancreatic cancer and its relationship with immune cells. We further explored the effect of TNFSF9 on pancreatic cancer metastasis by inducing macrophage polarization, and evaluated the expression of Src/FAK/p-Akt/IL-1β signals in macrophages after knocking down TNFSF9. The data shows that TNFSF9 expression is elevated in pancreatic cancer and is related to the poor prognosis of patients with pancreatic cancer. In addition, TNFSF9 may induce the M2 polarization of macrophages through Src/FAK/p-Akt/IL-1β signals, thereby promoting the migration of pancreatic cancer cells. In conclusion, our data reveals that TNFSF9 may become a predictive biomarker of pancreatic cancer and provides a new intervention target for the immunotherapy of pancreatic cancer.

Metabolomics study reveals systematic metabolic dysregulation and early detection markers associated with incident pancreatic cancer.

Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n=192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-Five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.

Diagnostic biomarkers for pancreatic cancer: An update.

Pancreatic ductal adenocarcinoma accounts for the primary type of pancreatic cancer (PC) with a 5-year survival rate of only about 10% in the United States. Early diagnosis will improve chances for curative treatment. To date, a broadly used serum marker for PC diagnosis is carbohydrate antigen 19-9, which is the only approved biomarker currently by the United States Food and Drug Administration. However, it has low specificity; therefore, development of novel biomarkers is urgently needed. Clinical trials are ongoing to evaluate candidate biomarkers for PC diagnosis, and the use of a multi-biomarker panel with current PC diagnostic biomarkers appears promising.

Circulating Tumor Cells Enumeration from the Portal Vein for Risk Stratification in Early Pancreatic Cancer Patients.

Simple SummaryEffective biomarkers are needed to enable personalized medicine for pancreatic cancer patients. This study analyzes the prognostic value, in early pancreatic cancer, of circulating tumor cells and clusters from the central venous catheter and portal blood. Circulating tumor cells were isolated using an immunomagnetic selection and were detected by microscopy using immunocytochemistry staining. In conclusion, the circulating tumor cell number in portal blood identifies a death risk in patients with early pancreatic cancer.Background. Effective biomarkers are needed to enable personalized medicine for pancreatic cancer patients. This study analyzes the prognostic value, in early pancreatic cancer, of single circulating tumor cell (CTC) and CTC clusters from the central venous catheter (CVC) and portal blood (PV). Methods. In total, 7 mL of PV and CVC blood from 35 patients with early pancreatic cancer were analyzed. CTC were isolated using a positive immunomagnetic selection. The detection and identification of CTC were performed by immunocytochemistry (ICC) and were analyzed by Epi-fluorescence and confocal microscopy. Results. CTC and the clusters were detected both in PV and CVC. In both samples, the CTC number per cluster was higher in patients with grade three or poorly differentiated tumors (G3) than in patients with well (G1) or moderately (G2) differentiated. Patients with fewer than 185 CTC in PV exhibited a longer OS than patients with more than 185 CTC (24.5 vs. 10.0 months; p = 0.018). Similarly, patients with fewer than 15 clusters in PV showed a longer OS than patients with more than 15 clusters (19 vs. 10 months; p = 0.004). These significant correlations were not observed in CVC analyses. Conclusions. CTC presence in PV could be an important prognostic factor to predict poor prognosis in early pancreatic cancer. In addition, the number of clustered-CTC correlate to a tumor negative differentiation degree and, therefore, could be used as a diagnostic biomarker for pancreatic cancer.

Comprehensive analysis of prognostic value and immune infiltration of calpains in pancreatic cancer.

Calpains (CAPNs) are intracellular calcium-activated neutral cysteine proteinases involved in cancer initiation, progression, and metastasis. However, its role in pancreatic cancer (PC) is still unclear. This study aims to identify the prognostic value and immune infiltration of CAPNs for PC patients using comprehensive bioinformatics analyzes. We analyzed the transcription levels of CAPNs in different cancers from Oncomine, differential gene expression in tumor/normal tissues and pathological stage through GEPIA database, the prognostic value of the mRNA expression of CAPNs by Kaplan-Meier plotter, the protein expression comparison of different CAPNs in human tumor/normal tissues from The Human Protein Atla, the CAPNs gene alterations through cBioPortal, the prediction of protein-protein interactions by STRING and GeneMANIA, the functional enrichment of discrepant CAPNs by GO and KEGG, and the immune infiltration of CAPNs by ssGSEA. Our results showed that CAPN1, 2, 4, 5, 6, 8, 9, 10, and 12 were highly expressed in PC. CAPN1, 5, 8, and 12 expression levels were positively correlated with individual cancer stages. Furthermore, CAPN1, 2, 5, and 8 expression levels were negatively correlated with overall survival (OS) and recurrence-free survival (RFS), while CAPN10 was positively correlated with OS and RFS. We found that CAPN1, 2, 5, and 8 were correlated with tumor-infiltrating T follicular helper cells and CAPN10 with tumor-infiltrating T helper 2 cells. Functional enrichment analysis showed that differentially expressed CAPNs (CAPN1, 2, 5, 8, and 10) are involved in axonogenesis, cell-substrate adhesion, immune response-activating cell surface receptor signaling pathway, and cell junction organization in PC. These results suggested that CAPN1, 2, 5, 8, and 10 could be used as prognostic biomarkers in PC and improve individualized treatment strategies.

ALKBH5-mediated m6A demethylation of KCNK15-AS1 inhibits pancreatic cancer progression via regulating KCNK15 and PTEN/AKT signaling

Long noncoding RNAs (lncRNAs) are regarded as crucial regulators in tumor progression. Potassium two pore domain channel subfamily K member 15 and WISP2 antisense RNA 1 (KCNK15-AS1) has been confirmed to inhibit the migration and invasion of pancreatic cancer (PC) cells. However, its downstream mechanism and effect on other cellular functions in PC remain unknown. This study probed the function and potential mechanism of KCNK15-AS1 in PC cell growth. RT-qPCR and western blot were employed to measure gene expression in PC cells. ISH was applied to analyze KCNK15-AS1 expression in PC tissues. Functional assays were utilized to evaluate PC cell proliferation, apoptosis, migration and EMT. Mechanical experiments were adopted to detect gene interaction in PC cells. The obtained data indicated that KCNK15-AS1 was down-regulated in PC cells and tissues. Overexpressing KCNK15-AS1 hindered cell proliferation, migration and EMT while facilitated cell apoptosis in PC. Mechanically, alkylation repair homolog protein 5 (ALKBH5) was verified to induce m6A demethylation of KCNK15-AS1 to mediate KCNK15-AS1 up-regulation. KCNK15-AS1 combined with KCNK15 5’UTR to inhibit KCNK15 translation. Moreover, KCNK15-AS1 recruited MDM2 proto-oncogene (MDM2) to promote RE1 silencing transcription factor (REST) ubiquitination, thus transcriptionally upregulating phosphatase and tensin homolog (PTEN) to inactivate AKT pathway. In conclusion, our study first confirmed that KCNK15-AS1 hinders PC cell growth by regulating KCNK15 and PTEN, suggesting KCNK15-AS1 as a potential biomarker of PC.

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

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

HIST3H2A is a potential biomarker for pancreatic cancer: A study based on TCGA data.

The family of histone H2A proved that there are a lot of variants associated with cancer development. The link between HIST3H2A and pancreatic cancer has never been noted before. Our research suggests that HIST3H2A affects pancreatic tumor immune process and prognosis of patients, through the JAK STAT pathway, so it is expected to become the biomarker of pancreatic cancer.Gene expression profiles and clinical data of pancreatic cancer patients were downloaded from The Cancer Genome Atlas database (TCGA) and The Genotype Tissue Expression (GETx) project. R software (Rx64 3.6.0) was utilized to analyze. Gene set enrichment analysis (GSEA) was used to analyze HIST3H2A related signaling pathways in pancreatic cancer. CIBERSORT is applied to estimate the compositional patterns of the 22 types of immune cell fraction based on bulk expression data.HIST3H2A was expressed at higher in pancreatic cancer tissues than normal pancreatic tissues. Kaplan–Meier survival analysis suggested that the level of HIST3H2A expression affect prognosis of pancreatic cancer patients. Univariate Cox analysis and Multivariate Cox analysis suggested that HIST3H2A expression is a prognostic factor of pancreatic cancer. Cor expression analysis indicated that the genes positively correlated with HIST3H2A expression trend were DCST1-AS1, HIST1H2BD, SLC12A9-AS1. GSEA showed that the JAK-STAT signaling pathway was enriched in the HIST3H2A high expression phenotype, whereas intestinal network for IgA production, Asthma and Chemokine signaling pathway were enriched in the HIST3H2A low expression phenotype. In additional, results showed that CD8 T cells (P = .007), activated CD4 memory T cells (P = .001), and monocytes (P = .002) were more abundant in lower HIST3H2A expression groups.HIST3H2A is a promising biomarker for predicting prognosis of pancreatic cancer, and it could be a potential therapeutic target. HIST3H2A might regulate the progression of tumor immune in pancreatic cancer through modulating the JAK-STAT pathway. In addition, the role HIST3H2A in pancreatic cancer may be related to DCST1-AS1, HIST1H2B, SLC12A9-AS1. However, more research is necessary to validate findings.

Systems biomarker characteristics of circulating alkaline phosphatase activities for 48 types of human diseases

Background Most human diseases are accompanied by systems changes. Systems biomarkers should reflect such changes. The phosphorylation and dephosphorylation of biomolecules maintain human homeostasis. However, the systems biomarker characteristics of circulating alkaline phosphatase, a routine blood test conducted for many human diseases, have never been investigated. Method This study retrieved the circulating alkaline phosphatase (ALP) activities from patients with 48 clinically confirmed diseases and healthy individuals from the database of our hospital during the past five years. A detailed analysis of the statistical characteristics of ALP was conducted, including quantiles, receiving operator curve (ROC), and principal component analysis. Results Among the 48 diseases, 45 had increased, and three had decreased median levels of ALP activities compared to the healthy control. Preeclampsia, hepatic encephalopathy, pancreatic cancer, and liver cancer had the highest median values, whereas nephrotic syndrome, lupus erythematosus, and nephritis had decreased median values compared to the healthy control. Further, area under curve (AUC) values were ranged between 0.61 and 0.87 for 19 diseases, and the ALP activities were the best systems biomarker for preeclampsia (AUC 0.87), hepatic encephalopathy (AUC 0.87), liver cancer (AUC 0.81), and pancreatic cancer (AUC 0.81). Conclusions Alkaline phosphatase was a decent systems biomarker for 19 different types of human diseases. Understanding the molecular mechanisms of over-up-and-down-regulation of ALP activities might be the key to understanding the whole-body systems' reactions during specific disease progression.

LncRNAs: Novel Biomarkers for Pancreatic Cancer.

Pancreatic cancer is one of the most deadly neoplasms and the seventh major cause of cancer-related deaths among both males and females. This cancer has a poor prognosis due to the lack of appropriate methods for early detection of cancer. Long non-coding RNAs (lncRNAs) have been recently found to influence the progression and initiation of pancreatic cancer. MACC1-AS1, LINC00976, LINC00462, LINC01559, HOXA-AS2, LINC00152, TP73-AS1, XIST, SNHG12, LUCAT1, and UCA1 are among the oncogenic lncRNAs in pancreatic cancer. On the other hand, LINC01111, LINC01963, DGCR5, MEG3, GAS5, and LINC00261 are among tumor suppressor lncRNAs in this tissue. In the current review, we summarize the roles of these two classes of lncRNAs in pancreatic cancer and discuss their potential as attractive diagnostic and prognostic biomarkers for pancreatic cancer. We also identified that the low expression of MEG3, LINC01963, and LINC00261 and the high expression of MACC1-AS1, LINC00462, LINC01559, and UCA1 were significantly correlated with worse survival in pancreatic cancer patients. Further research on these lncRNAs will provide new clues that could potentially improve the early diagnosis, prognostic prediction, and personalized treatments of patients with pancreatic cancer.

Rapid sample preparation workflow based on enzymatic nanoreactors for potential serum biomarker discovery in pancreatic cancer

Mass spectrometry (MS)-based proteomics have been extensively applied in clinical practice to discover potential protein and peptide biomarkers. However, the traditional sample pretreatment workflow remains labor-intensive and time-consuming, which limits the application of MS-based proteomic biomarker discovery studies in a high throughput manner. In the current work, we improved the previously reported procedure of the simple and rapid sample preparation methods (RSP) by introducing macroporous ordered siliceous foams (MOSF), namely RSP-MOSF. With the aid of MOSF, we further reduced the digestion time to 10 min, facilitating the whole sample handling process within 30 min. Combining with 30 min direct data independent acquisition (DIA) of LC-MS/MS, we accomplished a serum sample analysis in 1 h. Comparing with the RSP method, the performance of protein and peptide identification, quantitation, as well as the reproducibility of RSP-MOSF is comparable or even outperformed the RSP method. We further applied this workflow to analyze serum samples for potential candidate biomarker discovery of pancreatic cancer. Overall, 576 serum proteins were detected with 41 proteins significantly changed, which could serve as potential biomarkers for pancreatic cancer. Additionally, we evaluated the performance of RSP-MOSF method in a 96-well plate format which demonstrated an excellent reproducibility of the analysis. These results indicated that RSP-MOSF method had the potential to be applied on an automatic platform for further scaled analysis.

Circulating Tumor DNA as a Potential Prognostic Marker in Patients with Borderline-Resectable Pancreatic Cancer Undergoing Neoadjuvant Chemotherapy Followed by Pancreatectomy.

Circulating tumor DNA (ctDNA) might be a promising biomarker for pancreatic cancer in liquid biopsy. This study aimed to evaluate the usefulness of liquid biopsy for patients with borderline-resectable pancreatic cancer (BR-PC). Patients with BR-PC according to the National Comprehensive Cancer Network guidelines (2017) and eligible for neoadjuvant chemotherapy (NAC) followed by pancreatectomy were recruited at Wakayama Medical University Hospital (UMIN000026647) between March 2017 and April 2020. The study enrolled 55 patients with locally advanced PC, and each patient consented to inclusion in the study. The study investigated the relationship between KRAS status in ctDNA and clinicopathologic features, analyzing ctDNA at three time points: pretreatment, post-NAC, and post-operation. Of the 55 enrolled patients with a diagnosis of BR-PC, 34 were scheduled to undergo pancreatectomy. From 27 patients with resected BR-PC, 81 blood samples were analyzed in triplicate for ctDNA. The patients with positive pretreatment and post-NAC ctDNA status had no significant decrease in median relapse-free survival (RFS) or overall survival (OS). However, the patients with positive postoperation ctDNA status had a significantly shorter median OS (723 days) than the patients with negative ctDNA results (not reached; P = 0.0148). A combined analysis of postoperative ctDNA and CA19-9 values showed the cumulative effect on both RFS (P = 0.0066) and OS (P = 0.0046). The adjusted hazard ratio for risk of survival computed for the patients carrying risk factors (either detectable ctDNA or CA19-9 > 37U/ml) increased from 4.13-fold to 17.71-fold (both P = 0.0055) compared with the patients who had no risk factors. Positive ctDNA predicts poor survival for patients with BR-PC who undergo NAC followed by pancreatectomy.

IL-6 is associated with expansion of myeloid-derived suppressor cells and enhanced immunosuppression in pancreatic adenocarcinoma patients.

Chronic inflammation favours the expansion of myeloid-derived suppressor cells (MDSCs) by secreting pro-inflammatory mediators. The role of MDSCs in mediating immunosuppression in pancreatic adenocarcinoma and in defining a premalignant route from chronic pancreatitis remains unclear. We aimed to study the immunosuppressive potential of all subsets of MDSCs and their correlation with inflammatory cytokines in pancreatic adenocarcinoma and chronic pancreatitis. Relative frequencies of MDSCs, immunosuppressive markers arginase-1 (ARG-1), programmed death-ligand 1 (PD-L1), reactive oxygen species (ROS) and cytokines in circulation and surgically resected local pancreatic tissue of chronic pancreatitis and pancreatic adenocarcinoma patients were analysed by multicolour flow cytometry and cytokine bead array, respectively. Levels of cytokines involved in MDSCs activation were analysed by ELISA, and the immunosuppressive nature of MDSCs was confirmed by T-cell suppression assay. Frequencies of circulating MDSCs and ARG-1, PD-L1, and ROS were significantly higher in pancreatic adenocarcinoma than healthy controls and showed a significant positive correlation with MDSCs burden in cancer tissue. Serum levels of cytokines IL-6, IL-8 and IL-10 were significantly elevated in pancreatic adenocarcinoma. IL-6 serum levels showed a significant positive correlation with frequencies of circulating MDSCs in pancreatic adenocarcinoma patients, and MDSCs mediated suppression of T-cell proliferation in vitro was associated with elevated IL-6 levels in the cell culture medium. Collectively, our results suggest that IL-6 plays a crucial role in the expansion of MDSCs and activating their immunosuppressive nature in pancreatic adenocarcinoma. The relative frequency of MDSCs in circulation can be used as a potential diagnostic biomarker for pancreatic cancer.

Liquid biopsy approach to pancreatic cancer.

Pancreatic cancer (PC) continues to pose a major clinical challenge. There has been little improvement in patient survival over the past few decades, and it is projected to become the second leading cause of cancer mortality by 2030. The dismal 5-year survival rate of less than 10% after the diagnosis is attributable to the lack of early symptoms, the absence of specific biomarkers for an early diagnosis, and the inadequacy of available chemotherapies. Most patients are diagnosed when the disease has already metastasized and cannot be treated. Cancer interception is vital, actively intervening in the malignization process before the development of a full-blown advanced tumor. An early diagnosis of PC has a dramatic impact on the survival of patients, and improved techniques are urgently needed to detect and evaluate this disease at an early stage. It is difficult to obtain tissue biopsies from the pancreas due to its anatomical position; however, liquid biopsies are readily available and can provide useful information for the diagnosis, prognosis, stratification, and follow-up of patients with PC and for the design of individually tailored treatments. The aim of this review was to provide an update of the latest advances in knowledge on the application of carbohydrates, proteins, cell-free nucleic acids, circulating tumor cells, metabolome compounds, exosomes, and platelets in blood as potential biomarkers for PC, focusing on their clinical relevance and potential for improving patient outcomes.

Identification of Candidate Biomarker ASXL2 and Its Predictive Value in Pancreatic Carcinoma.

Pancreatic adenocarcinoma is one of the most lethal diseases with a 5-year survival rate of about 8%. ASXL2 is an epigenetic regulator associated with various tumors including colorectal cancer, breast cancer, and myeloid leukemia. However, the role of ASXL2 in pancreatic cancer remains unclear. This is the first research focusing on the prognostic value of ASXL2 in pancreatic cancer. In this research, we aimed to explore the correlation between ASXL2 and the prognosis, as well as other features in PAAD. We obtained gene expression profiles of PAAD and normal tissues from TCGA, GEO, and Xena databases. TIMER and CIBERSORT algorithms were employed to investigate the effect of ASXL2 on tumor microenvironment. GSEA along with GO and KEGG enrichment analyses were conducted to uncover the biological functions of ASXL2. The response to various chemotherapeutic drugs was estimated by algorithms in R package “pRRophetic”, while the sensitivity to immunotherapy was quantified by TIDE score. We found that ASXL2 was upregulated in the PAAD samples and elevated expression of ASXL2 was linked to poor overall survival. ASXL2 DNA methylation contributed to ASXL2 expression. Functional annotation indicated that ASXL2 was mainly involved in inflammatory response and epithelial mesenchymal transition. Patients with high ASXL2 expression were more likely to benefit from immune checkpoint blockade, gemcitabine, and mitomycin-C. Finally, external datasets and biospecimens were used and the results further validated the aberrant expression of ASXL2 in PAAD samples. In summary, our results highlight that ASXL2 is a potential prognostic and predictive biomarker in pancreatic cancer.

RUNX2 and LAMC2: promising pancreatic cancer biomarkers identified by an integrative data mining of pancreatic adenocarcinoma tissues.

Pancreatic carcinoma (PC) is a severe disease associated with high mortality. Although strategies for cancer therapy have made great progress, outcomes of pancreatic carcinoma patients remain extremely poor. Therefore, it is urgent to find novel biomarkers and therapeutic targets. To identify biomarkers for early diagnosis and therapy, three mRNA microarray datasets and two miRNA datasets were selected, and combinative analysis was performed by GEO2R. Functional and pathway enrichment analysis were performed using DAVID database. MiRTarBase, miRWalk and Diana Tools were used to get key genes. TCGA, HPA and western blotting were used to verify diagnostic and prognostic value of key genes. By integrating mRNA and miRNA expression profiles, we identified 114 differentially expressed genes and 114 differentially expressed miRNAs, respectively. Then, three overlapping key genes, RUNX2, LAMC2 and FBXO32, were found. Their protein levels in pancreatic tissue from PC patients and normal people were analyzed by immunohistochemical staining and western blotting. RUNX2 showed a potential property to identify PC. Aberrant over-expression of LAMC2 was associated with poor prognosis of PC patients, tumor status and subtypes. In summary, our current study identified that RUNX2 and LAMC2 may be promising targets for early diagnosis and therapy of PC patients.