A mouse to human search for plasma proteome changes associated with pancreatic tumor development

Plasma-to-tumour tissue integrated proteomics using nano-omics for biomarker discovery in glioblastoma

Glioblastoma (GB) is the most lethal brain cancer, with patient survival rates remaining largely unchanged over the past two decades. Here, we introduce the Nano-omics integrative workflow that links systemic (plasma) and localised (tumour tissue) protein changes associated with GB progression. Mass spectrometry analysis of the nanoparticle biomolecule corona in GL261-bearing mice at different stages of GB revealed plasma protein alterations, even at low tumour burden, with over 30% overlap between GB-specific plasma and tumour tissue proteomes. Analysis of matched plasma and surgically resected tumour samples from high-grade glioma patients demonstrates the clinical applicability of the Nano-omics pipeline. Cross-species correlation identified 48 potential GB biomarker candidates involved in actin cytoskeleton organisation, focal adhesion, platelet activation, leukocyte migration, amino acid biosynthesis, carbon metabolism, and phagosome pathways. The Nano-omics approach holds promise for the discovery of early detection and disease monitoring biomarkers of central nervous system conditions, paving the way for subsequent clinical validation.

Non-invasive biomarkers for early diagnosis of pancreatic cancer risk: metabolite genomewide association study based on the KCPS-II cohort

BACKGROUND

Pancreatic cancer is a lethal disease with a high mortality rate. The difficulty of early diagnosis is one of its primary causes. Therefore, we aimed to discover non-invasive biomarkers that facilitate the early diagnosis of pancreatic cancer risk.

METHODS

The study subjects were randomly selected from the Korean Cancer Prevention Study-II and matched by age, sex, and blood collection point [pancreatic cancer incidence (n = 128) vs. control (n = 256)]. The baseline serum samples were analyzed by non-targeted metabolomics, and XGBoost was used to select significant metabolites related to pancreatic cancer incidence. Genomewide association study for the selected metabolites discovered valuable single nucleotide polymorphisms (SNPs). Moderation and mediation analysis were conducted to explore the variables related to pancreatic cancer risk.

RESULTS

Eleven discriminant metabolites were selected by applying a cut-off of 4.0 in XGBoost. Five SNP presented significance in metabolite-GWAS (p ≤ 5 × 10-6) and logistic regression analysis. Among them, the pair metabolite of rs2370981, rs55870181, and rs72805402 displayed a different network pattern with clinical/biochemical indicators on comparison with allelic carrier and non-carrier. In addition, we demonstrated the indirect effect of rs59519100 on pancreatic cancer risk mediated by γ-glutamyl tyrosine, which affects the smoking status. The predictive ability for pancreatic cancer on the model using five SNPs and four pair metabolites with the conventional risk factors was the highest (AUC: 0.738 [0.661-0.815]).

CONCLUSIONS

Signatures involving metabolites and SNPs discovered in the present research may be closely associated with the pathogenesis of pancreatic cancer and for use as predictive biomarkers allowing early pancreatic cancer diagnosis and therapy.

Functional and Clinical Proteomic Exploration of Pancreatic Cancer

Pancreatic cancer, most cases being pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers with a median survival time of less than 6 months. Therapeutic options are very limited for PDAC patients, and surgery is still the most effective treatment, making improvements in early diagnosis critical. One typical characteristic of PDAC is the desmoplastic reaction of its stroma microenvironment, which actively interacts with cancer cells to orchestrate key components in tumorigenesis, metastasis, and chemoresistance. Global exploration of cancer-stroma crosstalk is essential to decipher PDAC biology and design intervention strategies. Over the past decade, the dramatic improvement of proteomics technologies has enabled profiling of proteins, post-translational modifications (PTMs), and their protein complexes at unprecedented sensitivity and dimensionality. Here, starting with our current understanding of PDAC characteristics, including precursor lesions, progression models, tumor microenvironment, and therapeutic advancements, we describe how proteomics contributes to the functional and clinical exploration of PDAC, providing insights into PDAC carcinogenesis, progression, and chemoresistance. We summarize recent achievements enabled by proteomics to systematically investigate PTMs-mediated intracellular signaling in PDAC, cancer-stroma interactions, and potential therapeutic targets revealed by these functional studies. We also highlight proteomic profiling of clinical tissue and plasma samples to discover and verify useful biomarkers that can aid early detection and molecular classification of patients. In addition, we introduce spatial proteomic technology and its applications in PDAC for deconvolving tumor heterogeneity. Finally, we discuss future prospects of applying new proteomic technologies in comprehensively understanding PDAC heterogeneity and intercellular signaling networks. Importantly, we expect advances in clinical functional proteomics for exploring mechanisms of cancer biology directly by high-sensitivity functional proteomic approaches starting from clinical samples.

An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next

Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

Multianalyte Serum Biomarker Panel for Early Detection of Pancreatic Adenocarcinoma

PURPOSE

We determined whether a large, multianalyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

We defined a biologically relevant subspace of blood analytes on the basis of previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, and 182 early-stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects on the basis of their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.

RESULTS

A classification model was trained on 669 subjects (358 healthy, 159 benign, and 152 early-stage PDAC). Model evaluation on a hold-out test set of 168 subjects (103 healthy, 35 benign, and 30 early-stage PDAC) yielded an area under the receiver operating characteristic curve (AUC) of 0.920 for classification of PDAC from non-PDAC (benign and healthy controls) and an AUC of 0.944 for PDAC versus healthy controls. The algorithm was then validated in 146 subsequent cases presenting with pancreatic disease (73 benign pancreatic disease and 73 early- and late-stage PDAC cases) and 40 healthy control subjects. The validation set yielded an AUC of 0.919 for classification of PDAC from non-PDAC and an AUC of 0.925 for PDAC versus healthy controls.

CONCLUSION

Individually weak serum biomarkers can be combined into a strong classification algorithm to develop a blood test to identify patients who may benefit from further testing.

Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly attributed to late diagnosis. We assessed the predictive performance of our previously reported urine biomarker panel for earlier detection of PDAC (LYVE1, REG1B and TFF1) in prediagnostic samples, alone and in combination with plasma CA19-9. This nested case-control study included 99 PDAC cases with urine samples prospectively collected up to 5 years prior to PDAC diagnosis and 198 matched controls. The samples were obtained from the Shanghai Women's Health Study (SWHS), the Shanghai Men's Health Studies (SMHS) and the Southern Community Cohort Study (SCCS). The urine biomarkers were measured by ELISA. Plasma CA19-9 was quantified by Luminex. Multiple logistic regression and Wilcoxon rank-sum and Mann-Whitney test were used for analysis. The internal validation approach was applied and the validated AUC estimators are reported on. The algorithm of urinary protein panel, urine creatinine and age named PancRISK, displayed similar AUC as CA19-9 up to 1 year before PDAC diagnosis (AUC = 0.79); however, the combination enhanced the AUCs to 0.89, and showed good discriminative ability (AUC = 0.77) up to 2 years. The combination showed sensitivity (SN) of 72% at 90% specificity (SP), and SP of 59% at 90% SN up to 1 year and 60% SN with 80% SP and 53% SP with 80% SN up to 2 years before PDAC diagnosis. Adding the clinical information on BMI value resulted in the overall improvement in performance of the PancRISK score. When combined with CA19-9, the urinary panel reached a workable model for detecting PDAC cases up to 2 years prior to diagnosis.

Diagnostic accuracy and added value of blood-based protein biomarkers for pancreatic cancer: A meta-analysis of aggregate and individual participant data

BACKGROUND

Novel blood-based protein biomarkers may be of value for efficient, accurate, and non-invasive diagnosis of pancreatic cancer. This study assesses the diagnostic accuracy of newly recognized blood-based protein biomarkers for detecting pancreatic cancer, and investigates their added value to CA19-9, the common blood-based biomarker in clinical use for pancreatic cancer.

METHODS

PubMed, Embase, Web of Science, and the Wiley/Cochrane Library were systematically searched from inception until June 2022. A meta-analysis of aggregate and individual participant data was conducted using frequentist and Bayesian hierarchical random-effects models. The added clinical utility of protein biomarkers was investigated using bootstrap bias-corrected decision curve analyses.

FINDINGS

Aggregate data from 28 primary studies (6127 participants) were included, of which 8 studies (1790 participants) provided individual participant data. CA19-9 was significantly more accurate than MIC-1 for distinguishing pancreatic cancer from benign disease (AUC, 0.83 vs 0.74; relative diagnostic odds ratio [rDOR], 2.10 [95% CI, 0.98-4.48]; p = 0.002), THBS2 (AUC, 0.87 vs 0.69; rDOR, 4.53 [2.16-9.39]; p < 0.0001), TIMP-1 (AUC, 0.91 vs 0.70; rDOR, 8.00 [3.81-16.9]; p < 0.0001), OPN (AUC, 0.89 vs 0.74; rDOR, 4.22 [1.13-15.6]; p < 0.0001), ICAM-1 (AUC, 0.91 vs 0.68; rDOR 9.30 [0.87-99.5]; p < 0.0001), and IGFBP2 (AUC, 0.91 vs 0.68; rDOR, 4.48 [0.78-24.3]; p < 0.0001). The addition of these novel protein biomarkers to CA19-9 did not significantly improve the AUC, and resulted in minor increases or limited decreases in clinical utility.

INTERPRETATION

Novel protein biomarkers have moderate diagnostic accuracy, do not outperform CA19-9 in differentiating pancreatic cancer from benign disease, and show limited added clinical value to CA19-9. We propose recommendations to aid the development of minimally invasive diagnostic tests with sufficient clinical utility to improve the management of patients with suspected pancreatic cancer.

FUNDING

Bennink Foundation, Dutch Cancer Foundation (KWF Kankerbestrijding), and AIRC.

Proteomic Analysis of Exudates from Chronic Ulcer of Diabetic Foot Treated with Scorpion Antimicrobial Peptide

Scorpion peptides have good therapeutic effect on chronic ulcer of diabetic foot, but the related pharmacological mechanism has remained unclear. The different proteins and bacteria present in ulcer exudates from chronic diabetic foot patients, treated with scorpion antimicrobial peptide at different stages, were analyzed using isobaric tags for quantification-labeled proteomics and bacteriological methods. According to the mass spectrometry data, a total of 1865 proteins were identified qualitatively, and the number of the different proteins was 130 (mid/early), 401 (late/early), and 310 (mid, late/early). In addition, functional annotation, cluster analysis of effects and the analysis of signal pathway, transcription regulation, and protein-protein interaction network were carried out. The results showed that the biochemical changes of wound microenvironment during the treatment involved activated biological functions such as protein synthesis, cell proliferation, differentiation, migration, movement, and survival. Inhibited biological functions such as cell death, inflammatory response, immune diseases, and bacterial growth were also involved. Bacteriological analysis showed that Burkholderia cepacia was the main bacteria in the early and middle stage of ulcer exudate and Staphylococcus epidermidis in the late stage. This study provides basic data for further elucidation of the molecular mechanism of diabetic foot.

Proceedings of the fifth international Molecular Pathological Epidemiology (MPE) meeting

Cancer heterogeneities hold the key to a deeper understanding of cancer etiology and progression and the discovery of more precise cancer therapy. Modern pathological and molecular technologies offer a powerful set of tools to profile tumor heterogeneities at multiple levels in large patient populations, from DNA to RNA, protein and epigenetics, and from tumor tissues to tumor microenvironment and liquid biopsy. When coupled with well-validated epidemiologic methodology and well-characterized epidemiologic resources, the rich tumor pathological and molecular tumor information provide new research opportunities at an unprecedented breadth and depth. This is the research space where Molecular Pathological Epidemiology (MPE) emerged over a decade ago and has been thriving since then. As a truly multidisciplinary field, MPE embraces collaborations from diverse fields including epidemiology, pathology, immunology, genetics, biostatistics, bioinformatics, and data science. Since first convened in 2013, the International MPE Meeting series has grown into a dynamic and dedicated platform for experts from these disciplines to communicate novel findings, discuss new research opportunities and challenges, build professional networks, and educate the next-generation scientists. Herein, we share the proceedings of the Fifth International MPE meeting, held virtually online, on May 24 and 25, 2021. The meeting consisted of 21 presentations organized into the three main themes, which were recent integrative MPE studies, novel cancer profiling technologies, and new statistical and data science approaches. Looking forward to the near future, the meeting attendees anticipated continuous expansion and fruition of MPE research in many research fronts, particularly immune-epidemiology, mutational signatures, liquid biopsy, and health disparities.

Oncogenic KRAS-Induced Protein Signature in the Tumor Secretome Identifies Laminin-C2 and Pentraxin-3 as Useful Biomarkers for the Early Diagnosis of Pancreatic Cancer

KRAS mutations characterize pancreatic cell transformation from the earliest stages of carcinogenesis, and are present in >95% of pancreatic ductal adenocarcinoma (PDAC) cases. In search of novel biomarkers for the early diagnosis of PDAC, we identified the proteins secreted by the normal human pancreatic cell line (HPDE) recently transformed by inducing the overexpression of the KRASG12V oncogene. We report a proteomic signature of KRAS-induced secreted proteins, which was confirmed in surgical tumor samples from resected PDAC patients. The putative diagnostic performance of three candidates, Laminin-C2 (LAMC2), Tenascin-C (TNC) and Pentraxin-3 (PTX3), was investigated by ELISA quantification in two cohorts of PDAC patients (n = 200) eligible for surgery. Circulating levels of LAMC2, TNC and PTX3 were significantly higher in PDAC patients compared to the healthy individuals (p < 0.0001). The Receiver Operating Characteristics (ROC) curve showed good sensitivity (1) and specificity (0.63 and 0.85) for LAMC2 and PTX3, respectively, but not for TNC, and patients with high levels of LAMC2 had significantly shorter overall survival (p = 0.0007). High levels of LAMC2 and PTX3 were detected at early stages (I−IIB) and in CA19-9-low PDAC patients. In conclusion, pancreatic tumors release LAMC2 and PTX3, which can be quantified in the systemic circulation, and may be useful in selecting patients for further diagnostic imaging.

Data-Independent Acquisition Enables Robust Quantification of 400 Proteins in Non-Depleted Canine Plasma

Mass spectrometry-based plasma proteomics offers a major advance for biomarker discovery in the veterinary field, which has traditionally been limited to quantification of a small number of proteins using biochemical assays. The development of foundational data and tools related to sequential window acquisition of all theoretical mass spectra (SWATH)-mass spectrometry has allowed for quantitative profiling of a significant number of plasma proteins in humans and several animal species. Enabling SWATH in dogs enhances human biomedical research as a model species, and significantly improves diagnostic and disease monitoring capability. In this study, a comprehensive peptide spectral library specific to canine plasma proteome was developed and evaluated using SWATH for protein quantification in non-depleted dog plasma. Specifically, plasma samples were subjected to various orthogonal fractionation and digestion techniques, and peptide fragmentation data corresponding to over 420 proteins was collected. Subsequently, a SWATH-based assay was introduced that leveraged the developed resource and that enabled reproducible quantification of 400 proteins in non-depleted plasma samples corresponding to various disease conditions. The ability to profile the abundance of such a significant number of plasma proteins using a single method in dogs has the potential to accelerate biomarker discovery studies in this species.

Liquid biopsy: the value of different bodily fluids

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?

Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).

Expanding the Spectrum of Pancreatic Cancers Responsive to Vesicular Stomatitis Virus-Based Oncolytic Virotherapy: Challenges and Solutions

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignancy with poor prognosis and a dismal survival rate, expected to become the second leading cause of cancer-related deaths in the United States. Oncolytic virus (OV) is an anticancer approach that utilizes replication-competent viruses to preferentially infect and kill tumor cells. Vesicular stomatitis virus (VSV), one such OV, is already in several phase I clinical trials against different malignancies. VSV-based recombinant viruses are effective OVs against a majority of tested PDAC cell lines. However, some PDAC cell lines are resistant to VSV. Upregulated type I IFN signaling and constitutive expression of a subset of interferon-simulated genes (ISGs) play a major role in such resistance, while other mechanisms, such as inefficient viral attachment and resistance to VSV-mediated apoptosis, also play a role in some PDACs. Several alternative approaches have been shown to break the resistance of PDACs to VSV without compromising VSV oncoselectivity, including (i) combinations of VSV with JAK1/2 inhibitors (such as ruxolitinib); (ii) triple combinations of VSV with ruxolitinib and polycations improving both VSV replication and attachment; (iii) combinations of VSV with chemotherapeutic drugs (such as paclitaxel) arresting cells in the G2/M phase; (iv) arming VSV with p53 transgenes; (v) directed evolution approach producing more effective OVs. The latter study demonstrated impressive long-term genomic stability of complex VSV recombinants encoding large transgenes, supporting further clinical development of VSV as safe therapeutics for PDAC.

Recent progress in surface plasmon resonance based sensors: A comprehensive review

In the recent years, researchers have contributed substantially in the field of Surface Plasmon Resonance (SPR) sensors and its applications. SPR sensors show the salient features, such as label-free detection, real-time monitoring, small sample size, furnish accurate outcomes at low cost, and smooth handling. Moreover, the SPR sensors are also well-known because of its quantitative and qualitative excellent performance in real-time applications, including drug discovery, environment monitoring, food safety, medical diagnosis, clinical diagnosis, biological studies, and biomolecule interactions. This paper exhibits a comprehensive review of SPR based sensors, such as prism-based SPR with the applications (e.g., biomolecule interaction, medical diagnostic, etc.), fiber-based SPR, and waveguide-based SPR. Furthermore, we summarized the modern designs and techniques with their limitations and challenges in detail. The erudition outlined in this paper can be given an exceptional benefit for the researchers and industry people in the field of SPR based sensors.

ImmunoPET/NIRF/Cerenkov multimodality imaging of ICAM-1 in pancreatic ductal adenocarcinoma

PURPOSE

We dual-labeled an intercellular adhesion molecule-1 (ICAM-1) monoclonal antibody (mAb) and evaluated its effectiveness for lesion detection and surgical navigation in pancreatic ductal adenocarcinoma (PDAC) via multiple noninvasive imaging approaches, including positron emission tomography (PET), near-infrared fluorescence (NIRF), and Cerenkov luminescence imaging (CLI).

METHODS

ICAM-1 expression in PDAC cell lines (BxPC-3 and AsPC-1) was assessed via flow cytometry and immunofluorescent staining. An ICAM-1 mAb labeled by IRDye 800CW and radionuclide zirconium-89 (denoted as [⁸⁹Zr]Zr-DFO-ICAM-1-IR800) was synthesized. Its performance was validated via in vivo comparative PET/NIRF/CLI and biodistribution (Bio-D) studies in nude mice bearing subcutaneous BxPC-3/AsPC-1 tumors or orthotopic BxPC-3 tumor models using nonspecific IgG as an isotype control tracer.

RESULTS

ICAM-1 expression was strong in the BxPC-3 and minimal in the AsPC-1 cell line. Both multimodality imaging and Bio-D data exhibited more prominent uptake of [⁸⁹Zr]Zr-DFO-ICAM-1-IR800 in BxPC-3 tumors than in AsPC-1 tumors. The uptake of [⁸⁹Zr]Zr-DFO-IgG-IR800 in BxPC-3 tumors was similar to that of [⁸⁹Zr]Zr-DFO-ICAM-1-IR800 in AsPC-1 tumors. These results demonstrate the desirable affinity and specificity of [⁸⁹Zr]Zr-DFO-ICAM-1-IR800 compared to [⁸⁹Zr]Zr-DFO-IgG-IR800. Orthotopic BxPC-3 tumor foci could also be clearly delineated by [⁸⁹Zr]Zr-DFO-ICAM-1-IR800. An intermodal match was achieved in the ICAM-1-targeted immunoPET/NIRF/CLI. The positive expression levels of ICAM-1 in BxPC-3 tumor tissue were further confirmed by immunohistopathology.

CONCLUSION

We successfully developed a dual-labeled ICAM-1-targeted tracer for PET/NIRF/CLI of PDAC that can facilitate better diagnosis and intervention of PDAC upon clinical translation.

Biomarkers and Strategy to Detect Preinvasive and Early Pancreatic Cancer: State of the Field and the Impact of the EDRN

Patients afflicted with pancreatic ductal adenocarcinoma (PDAC) face a dismal prognosis, but headway could be made if physicians could identify the disease earlier. A compelling strategy to broaden the use of surveillance for PDAC is to incorporate molecular biomarkers in combination with clinical analysis and imaging tools. This article summarizes the components involved in accomplishing biomarker validation and an analysis of the requirements of molecular biomarkers for disease surveillance. We highlight the significance of consortia for this research and highlight resources and infrastructure of the Early Detection Research Network (EDRN). The EDRN brings together the multifaceted expertise and resources needed for biomarker validation, such as study design, clinical care, biospecimen collection and handling, molecular technologies, and biostatistical analysis, and studies coming out of the EDRN have yielded biomarkers that are moving forward in validation. We close the article with an overview of the current investigational biomarkers, an analysis of their performance relative to the established benchmarks, and an outlook on the current needs in the field. The outlook for improving the early detection of PDAC looks promising, and the pace of further research should be quickened through the resources and expertise of the EDRN and other consortia.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Systemic Proteome Alterations Linked to Early Stage Pancreatic Cancer in Diabetic Patients

BACKGROUND

Diabetes is a risk factor associated with pancreatic ductal adenocarcinoma (PDAC), and new adult-onset diabetes can be an early sign of pancreatic malignancy. Development of blood-based biomarkers to identify diabetic patients who warrant imaging tests for cancer detection may represent a realistic approach to facilitate earlier diagnosis of PDAC in a risk population.

METHODS

A spectral library-based proteomic platform was applied to interrogate biomarker candidates in plasma samples from clinically well-defined diabetic cohorts with and without PDAC. Random forest algorithm was used for prediction model building and receiver operating characteristic (ROC) curve analysis was applied to evaluate the prediction probability of potential biomarker panels.

RESULTS

Several biomarker panels were cross-validated in the context of detection of PDAC within a diabetic background. In combination with carbohydrate antigen 19-9 (CA19-9), the panel, which consisted of apolipoprotein A-IV (APOA4), monocyte differentiation antigen CD14 (CD14), tetranectin (CLEC3B), gelsolin (GSN), histidine-rich glycoprotein (HRG), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), plasma kallikrein (KLKB1), leucine-rich alpha-2-glycoprotein (LRG1), pigment epithelium-derived factor (SERPINF1), plasma protease C1 inhibitor (SERPING1), and metalloproteinase inhibitor 1 (TIMP1), demonstrated an area under curve (AUC) of 0.85 and a two-fold increase in detection accuracy compared to CA19-9 alone. The study further evaluated the correlations of protein candidates and their influences on the performance of biomarker panels.

CONCLUSIONS

Proteomics-based multiplex biomarker panels improved the detection accuracy for diagnosis of early stage PDAC in diabetic patients.

Proteins and Molecular Pathways Relevant for the Malignant Properties of Tumor-Initiating Pancreatic Cancer Cells

Cancer stem cells (CSCs), a small subset of the tumor bulk with highly malignant properties, are deemed responsible for tumor initiation, growth, metastasis, and relapse. In order to reveal molecular markers and determinants of their tumor-initiating properties, we enriched rare stem-like pancreatic tumor-initiating cells (TICs) by harnessing their clonogenic growth capacity in three-dimensional multicellular spheroid cultures. We compared pancreatic TICs isolated from three-dimensional tumor spheroid cultures with nontumor-initiating cells (non-TICs) enriched in planar cultures. Employing differential proteomics (PTX), we identified more than 400 proteins with significantly different expression in pancreatic TICs and the non-TIC population. By combining the unbiased PTX with mRNA expression analysis and literature-based predictions of pro-malignant functions, we nominated the two calcium-binding proteins S100A8 (MRP8) and S100A9 (MRP14) as well as galactin-3-binding protein LGALS3BP (MAC-2-BP) as putative determinants of pancreatic TICs. In silico pathway analysis followed by candidate-based RNA interference mediated loss-of-function analysis revealed a critical role of S100A8, S100A9, and LGALS3BP as molecular determinants of TIC proliferation, migration, and in vivo tumor growth. Our study highlights the power of combining unbiased proteomics with focused gene expression and functional analyses for the identification of novel key regulators of TICs, an approach that warrants further application to identify proteins and pathways amenable to drug targeting.

Patient-Derived Xenograft Models of Pancreatic Cancer: Overview and Comparison with Other Types of Models

Pancreatic cancer (PC) is anticipated to be second only to lung cancer as the leading cause of cancer-related deaths in the United States by 2030. Surgery remains the only potentially curative treatment for patients with pancreatic ductal adenocarcinoma (PDAC), the most common form of PC. Multiple recent preclinical studies focus on identifying effective treatments for PDAC, but the models available for these studies often fail to reproduce the heterogeneity of this tumor type. Data generated with such models are of unknown clinical relevance. Patient-derived xenograft (PDX) models offer several advantages over human cell line-based in vitro and in vivo models and models of non-human origin. PDX models retain genetic characteristics of the human tumor specimens from which they were derived, have intact stromal components, and are more predictive of patient response than traditional models. This review briefly describes the advantages and disadvantages of 2D cultures, organoids and genetically engineered mouse (GEM) models of PDAC, and focuses on the applications, characteristics, advantages, limitations, and the future potential of PDX models for improving the management of PDAC.

Characterization of genetic subclonal evolution in pancreatic cancer mouse models

The KPC mouse model, driven by the Kras and Trp53 transgenes, is well regarded for faithful recapitulation of human pancreatic cancer biology. However, the extent that this model recapitulates the subclonal evolution of this tumor type is unknown. Here we report evidence of continuing subclonal evolution after tumor initiation that largely reflect copy number alterations that target cellular processes of established significance in human pancreatic cancer. The evolutionary trajectories of the mouse tumors show both linear and branching patterns as well as clonal mixing. We propose the KPC model and derivatives have unexplored utility as a functional system to model the mechanisms and modifiers of tumor evolution.

In pancreatic cancer the Kras and Trp53 transgene driven KPC mouse model is used to experimentally study disease processes. Here, the authors analyse tumour evolution within the KPC model, finding both linear and branched evolution and highlighting the utility of this model in mechanistic research of tumour evolution.

[Development of a Pancreatic Cancer Specific Binding Peptide Using Phage Display]

Background/Aims

Pancreatic cancer has a very poor prognosis, and early diagnosis is a way to increase the survival rate of patients. The purpose of this study was to develop pancreatic cancer-specific peptides for imaging studies.

Methods

Three pancreatic cancer cell lines, MIA PaCa-2, UACC-462, and BxPC-3, and a control cell line, CCD841, were used. Biopannings were performed on MIA PaCa-2 using a phage display library. After this, the peptides were synthesized and labeled with fluorescein isothiocyanate (FITC). Immunocytochemistry (ICC), enzyme-linked immunosorbent assay (ELISA), and fluorescence- activated cell sorter (FACS) were performed to examine the specific binding. To examine its therapeutic applications, a photosensitizer, chlorin e6 (Ce6), was conjugated on the peptide and photodynamic therapy was performed. Cell survival was investigated using a [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide] assay.

Results

After three biopannings, the phages were amplified from 1.4×10⁴ to 3.2×10⁵ plaque-forming units. The most strongly binding phage was selected from the ELISA and ICC results. FITC-labeled peptide, M5, in the three pancreatic cancer cell lines showed significantly higher immunofluorescence in the ICC experiments than that of CCD841. The higher binding ability to MIA PaCa-2 cells was confirmed from FACS analysis, which showed a right shift compared to CCD841. M5 bound to Ce6 showed a significantly lower cell survival rate than that of Ce6 alone in photodynamic therapy, which was observed consistently as a change in the tumor size and fluorescence intensity in MIA PaCa-2 cell-implanted animal models.

Conclusions

This study showed that the noble peptide, M5, binds specifically to the pancreatic cancer cell line, MIA PaCa-2. The M5 peptide has potential use in future optical diagnostic and therapeutic purposes.

Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer that is characterized by its poor prognosis, rapid progression and development of drug resistance. Chemotherapy is a vital treatment option for most of PDAC patients. Stratification of PDAC patients, who would have a higher likelihood of responding to chemotherapy, could facilitate treatment selection and patient management.

METHODS

A quantitative proteomic study was performed to characterize the protein profiles in the plasma of PDAC patients undergoing chemotherapy to determine if specific biomarkers could be used to predict likelihood of therapeutic response.

RESULTS

By comparing the plasma proteome of the PDAC patients with positive therapeutic response and longer overall survival (Good-responders) to those who did not respond as well with shorter survival time (Limited-responders), we identified differential proteins and protein variants that could effectively segregate Good-responders from Limited-responders. Functional clustering and pathway analysis further suggested that many of these differential proteins were involved in pancreatic tumorigenesis. Four proteins, including vitamin-K dependent protein Z (PZ), sex hormone-binding globulin (SHBG), von Willebrand factor (VWF) and zinc-alpha-2-glycoprotein (AZGP1), were further evaluated as single or composite predictive biomarker with/without inclusion of CA 19-9. A composite biomarker panel that consists of PZ, SHBG, VWF and CA 19-9 demonstrated the best performance in distinguishing Good-responders from Limited-responders.

CONCLUSION

Based on the cohort investigated, our data suggested that systemic proteome alterations involved in pathways associated with inflammation, immunoresponse, coagulation and complement cascades may be reporters of chemo-treatment outcome in PDAC patients. For the majority of the patients involved, the panel consisting of PZ, SHBG, VWF and CA 19-9 was able to segregate Good-responders from Limited-responders effectively. Our data also showed that dramatic fluctuations of biomarker concentration in the circulating system of a PDAC patient, which might result from biological heterogeneity or confounding complications, could diminish the performance of a biomarker. Categorization of PDAC patients in terms of their tumor stages and histological types could potentially facilitate patient stratification for treatment.

MicroRNA-7 directly targets Reg1 in pancreatic cells

Regenerating islet-derived (Reg) proteins, which were first discovered in the pancreas, are associated with increased proliferation, prevention of apoptosis, and enhanced differentiation in normal and disease states, but very little is known about the regulation of their expression. We hypothesized that Reg expression is influenced by microRNAs. Bioinformatic analysis predicted Reg1 to be a target of microRNA-7 (miR-7), which influences pancreatic β-cell function. To this end, we investigated the effects of miR-7 on Reg1 expression in pancreatic acinar and islet β-cells. High levels of Reg1 were noted by immunostaining and Western blotting in acinar cells in contrast to islet cells. A reciprocal expression pattern was observed for miR-7. Overexpression of miR-7 resulted in Reg1 mRNA suppression and reduction of secreted Reg1 protein. Conversely, miR-7 knockdown led to increases in Reg1. Targeting of Reg1 by miR-7 was confirmed via luciferase activity assays. In contrast, miR-7 did not directly repress the human ortholog of Reg1 REG1A as well as REG1B indicating species differences in the regulation of Reg expression. This is the first account of microRNA modulation of any Reg member warranting studies to fill gaps in our knowledge of Reg protein biology, particularly in disease contexts.

Soluble stroma-related biomarkers of pancreatic cancer

The clinical management of pancreatic ductal adenocarcinoma (PDAC) is hampered by the lack of reliable biomarkers. This study investigated the value of soluble stroma‐related molecules as PDAC biomarkers. In the first exploratory phase, 12 out of 38 molecules were associated with PDAC in a cohort of 25 PDAC patients and 16 healthy subjects. A second confirmatory phase on an independent cohort of 131 PDAC patients, 30 chronic pancreatitis patients, and 131 healthy subjects confirmed the PDAC association for MMP7, CCN2, IGFBP2, TSP2, sICAM1, TIMP1, and PLG. Multivariable logistic regression model identified biomarker panels discriminating respectively PDAC versus healthy subjects (MMP7 + CA19.9, AUC = 0.99, 99% CI = 0.98–1.00) (CCN2 + CA19.9, AUC = 0.96, 99% CI = 0.92–0.99) and PDAC versus chronic pancreatitis (CCN2 + PLG+FN+Col4 + CA19.9, AUC = 0.94, 99% CI = 0.88–0.99). Five molecules were associated with PanIN development in two GEM models of PDAC (PdxCre/LSL‐Kras^G12D and PdxCre/LSL‐Kras^G12D/+/LSL‐Trp53^R172H/+), suggesting their potential for detecting early disease. These markers were also elevated in patient‐derived orthotopic PDAC xenografts and associated with response to chemotherapy. The identified stroma‐related soluble biomarkers represent potential tools for PDAC diagnosis and for monitoring treatment response of PDAC patients.

Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment

The immense costs in both financial terms and preclinical research effort that occur in the development of anticancer drugs are unfortunately not matched by a substantial increase in improved clinical therapies due to the high rate of failure during clinical trials. This may be due to issues with toxicity or lack of clinical effectiveness when the drug is evaluated in patients. Currently, much cancer research is driven by the need to develop therapies that can exploit cancer cell adaptations to conditions in the tumor microenvironment such as acidosis and hypoxia, the requirement for more-specific, targeted treatments, or the exploitation of 'precision medicine' that can target known genomic changes in patient DNA. The high attrition rate for novel anticancer therapies suggests that the preclinical methods used in screening anticancer drugs need improvement. This chapter considers the advantages and disadvantages of 3D organotypic models in both cancer research and cancer drug screening, particularly in the areas of targeted drugs and the exploitation of genomic changes that can be used for therapeutic advantage in precision medicine.

Molecular phenotyping of laboratory mouse strains using 500 multiple reaction monitoring mass spectrometry plasma assays

Mouse is the predominant experimental model for the study of human disease due, in part, to phylogenetic relationship, ease of breeding, and the availability of molecular tools for genetic manipulation. Advances in genome-editing methodologies, such as CRISPR-Cas9, enable the rapid production of new transgenic mouse strains, necessitating complementary high-throughput and systematic phenotyping technologies. In contrast to traditional protein phenotyping techniques, multiple reaction monitoring (MRM) mass spectrometry can be highly multiplexed without forgoing specificity or quantitative precision. Here we present MRM assays for the quantitation of 500 proteins and subsequently determine reference concentration values for plasma proteins across five laboratory mouse strains that are typically used in biomedical research, revealing inter-strain and intra-strain phenotypic differences. These 500 MRM assays will have a broad range of research applications including high-throughput phenotypic validation of novel transgenic mice, identification of candidate biomarkers, and general research applications requiring multiplexed and precise protein quantification.

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary cooperation within the PDAC community is poised to confront it.

Circulating biomarkers for early diagnosis of pancreatic cancer: facts and hopes

Pancreatic cancer (PC) is characterized by extremely high mortality and poor prognosis, which are largely ascribed to difficulties in early diagnosis and limited therapeutics. Although there is a sufficient window for intervention before preneoplastic lesions progress to invasive disease, effective early detection of PC remains difficult using current biomarkers and imaging techniques. Biomarkers with satisfactory diagnostic efficacy and convenient analysis methods are urgently required. In this review, we summarized recent advances in the identification of biomarkers in circulation for early detection of PC. A number of novel circulating biomarkers, such as metabolites, cell-free DNA (cfDNA), noncoding RNA, and exosomes, that show promising diagnostic value have been discovered using advances in sequencing techniques and "omics" analyses. Panels comprising several biomarkers may also exhibit better diagnostic performance. In the future, we need more efficient circulating biomarkers for the identification of noninvasive precursor lesions and early disease. Collaborative large-scale studies are also required to show the clinical validity and applicability of potential biomarkers.

Evidence of Altered Glycosylation of Serum Proteins Prior to Pancreatic Cancer Diagnosis

Biomarkers for the early detection of pancreatic cancer are urgently needed. The aim of this pilot study was to evaluate changes in serum N-glycoproteins and their glycosylation status prior to clinical presentation of pancreatic cancer that may be potential biomarkers. Prediagnosis serum samples pooled according to five time-to-diagnosis groups and a non-cancer control pool were digested with trypsin, labelled with mass tags, and subjected to titanium dioxide capture, deglycosylation, and 2D-LC-MS/MS profiling. Unbound peptides were profiled in parallel. Across the sample groups, 703 proteins were quantified and 426 putative sites of N-glycosylation were identified with evidence of several novel sites. Altered proteins with biomarker potential were predominantly abundant inflammatory response, coagulation, and immune-related proteins. Whilst glycopeptide profiles largely paralleled those of their parent proteins, there was evidence of altered N-glycosylation site occupancy or sialic acid content prior to diagnosis for some proteins, most notably of immunoglobulin gamma chains. α-1-Antitrypsin was tested as a biomarker, but found not to complement carbohydrate antigen 19-9 (CA19-9) in early detection of cancer. In conclusion, we provide preliminary evidence of altered glycosylation of several serum proteins prior to pancreatic cancer diagnosis, warranting further investigation of these proteins as early biomarkers. These changes may be largely driven by inflammatory processes that occur in response to tumour formation and progression.

Gut microbial profile analysis by MiSeq sequencing of pancreatic carcinoma patients in China

Pancreatic carcinoma (PC) is a lethal cancer. Gut microbiota is associated with some risk factors of PC, e.g. obesity and types II diabetes. However, the specific gut microbial profile in clinical PC in China has never been reported. This prospective study collected 85 PC and 57 matched healthy controls (HC) to analyze microbial characteristics by MiSeq sequencing. The results showed that gut microbial diversity was decreased in PC with an unique microbial profile, which partly attributed to its decrease of alpha diversity. Microbial alterations in PC featured by the increase of certain pathogens and lipopolysaccharides-producing bacteria, and the decrease of probiotics and butyrate-producing bacteria. Microbial community in obstruction cases was separated from the un-obstructed cases. Streptococcus was associated with the bile. Furthermore, 23 microbial functions e.g. Leucine and LPS biosynthesis were enriched, while 13 functions were reduced in PC. Importantly, based on 40 genera associated with PC, microbial markers achieves a high classification power with AUC of 0.842. In conclusion, gut microbial profile was unique in PC, providing a microbial marker for non-invasive PC diagnosis.

Elevated TIMP-1 expression is associated with a prometastatic phenotype, disease relapse, and poor survival in neuroblastoma

Approximately two-thirds of patients with neuroblastoma are found to have metastatic disease at time of diagnosis with frequent skeletal, lymph node, central nervous system, and liver involvement. Using a serial in vivo splenic injection model, we have isolated an aggressive subclone (BE(2)-C/LM2) from MYCN-amplified neuroblastomas that demonstrate an enhanced propensity to develop metastatic liver lesions. BE(2)-C/LM2 subclone cells demonstrate increased adherent, soft agar colony and tumorsphere growth in vitro. Components of the tumor microenvironment regulate cancer progression, via networks of cytokines and growth factors. Cytokine array analysis identified increased TIMP-1 in the plasma of mice injected with BE(2)-C/LM2 subclone cells, leading us to hypothesize that TIMP-1 may play a role in our observed prometastatic phenotype. Immunoblotting and ELISA demonstrated enhanced endogenous TIMP-1 expression in our isolated neuroblastoma subclone. Silencing endogenous TIMP-1 successfully blocked in vitro proliferation, soft agar colony formation and tumorsphere formation by BE(2)-C/LM2 cells. Stable RNA interference of endogenous TIMP-1 failed to reverse the prometastatic phenotype of our BE(2)-C/LM2 subclone in our liver metastasis model, suggesting that endogenous TIMP-1 levels may not be an essential component of this in vivo behavior. Notably, tissue microarray analysis and Kaplan-Meier by gene expression demonstrates that elevated TIMP-1 expression is correlated with increased disease relapse and mortality in patients with neuroblastoma. Taken together, our study identifies TIMP-1 as a novel soluble factor that is associated with a prometastatic phenotype in our in vivo model and adverse outcomes in patients with neuroblastoma.

Multiparametric plasma EV profiling facilitates diagnosis of pancreatic malignancy

Pancreatic ductal adenocarcinoma (PDAC) is usually detected late in the disease process. Clinical workup through imaging and tissue biopsies is often complex and expensive due to a paucity of reliable biomarkers. We used an advanced multiplexed plasmonic assay to analyze circulating tumor-derived extracellular vesicles (tEVs) in more than 100 clinical populations. Using EV-based protein marker profiling, we identified a signature of five markers (PDACEV signature) for PDAC detection. In our prospective cohort, the accuracy for the PDACEV signature was 84% [95% confidence interval (CI), 69 to 93%] but only 63 to 72% for single-marker screening. One of the best markers, GPC1 alone, had a sensitivity of 82% (CI, 60 to 95%) and a specificity of 52% (CI, 30 to 74%), whereas the PDACEV signature showed a sensitivity of 86% (CI, 65 to 97%) and a specificity of 81% (CI, 58 to 95%). The PDACEV signature of tEVs offered higher sensitivity, specificity, and accuracy than the existing serum marker (CA 19-9) or single-tEV marker analyses. This approach should improve the diagnosis of pancreatic cancer.

Sequential Validation of Blood-Based Protein Biomarker Candidates for Early-Stage Pancreatic Cancer

Background

CA19-9, which is currently in clinical use as a pancreatic ductal adenocarcinoma (PDAC) biomarker, has limited performance in detecting early-stage disease. We and others have identified protein biomarker candidates that have the potential to complement CA19-9. We have carried out sequential validations starting with 17 protein biomarker candidates to determine which markers and marker combination would improve detection of early-stage disease compared with CA19-9 alone.

Methods

Candidate biomarkers were subjected to enzyme-linked immunosorbent assay based sequential validation using independent multiple sample cohorts consisting of PDAC cases (n = 187), benign pancreatic disease (n = 93), and healthy controls (n = 169). A biomarker panel for early-stage PDAC was developed based on a logistic regression model. All statistical tests for the results presented below were one-sided.

Results

Six out of the 17 biomarker candidates and CA19-9 were validated in a sample set consisting of 75 PDAC patients, 27 healthy subjects, and 19 chronic pancreatitis patients. A second independent set of 73 early-stage PDAC patients, 60 healthy subjects, and 74 benign pancreatic disease patients (combined validation set) yielded a model that consisted of TIMP1, LRG1, and CA19-9. Additional blinded testing of the model was done using an independent set of plasma samples from 39 resectable PDAC patients and 82 matched healthy subjects (test set). The model yielded areas under the curve (AUCs) of 0.949 (95% confidence interval [CI] = 0.917 to 0.981) and 0.887 (95% CI = 0.817 to 0.957) with sensitivities of 0.849 and 0.667 at 95% specificity in discriminating early-stage PDAC vs healthy subjects in the combined validation and test sets, respectively. The performance of the biomarker panel was statistically significantly improved compared with CA19-9 alone (P < .001, combined validation set; P = .008, test set).

Conclusion

The addition of TIMP1 and LRG1 immunoassays to CA19-9 statistically significantly improves the detection of early-stage PDAC.

Inflammatory cytokines and angiogenic factors as potential biomarkers in South African pancreatic ductal adenocarcinoma patients: A preliminary report

BACKGROUND/OBJECTIVES

Several studies have investigated the association of differentially expressed cytokines with pancreatic ductal adenocarcinoma (PDAC), but none in African countries. This study aimed at investigating T-helper (Th) cell and angiogenic markers as diagnostic or prognostic biomarkers for PDAC in Black South Africans.

METHODS

We conducted a prospective, case-control study comprising of 34 PDAC patients and 27 control participants with either critical limb ischemia, abdominal aortic aneurysm or other abdominal pathology from causes other than pancreatic disease. Plasma levels of IL-2, IL-4, IL-6, IL-10, TNF, IFN-γ, IL-17A, VEGF, sVEGF-R1, FGF, PIGF, PDGF and P-selectin were measured using commercially available cytometric bead array, ELISA and multi-analyte Luminex kits.

RESULTS

Significantly higher levels of IFN-γ (p < 0.001), TNF (p < 0.001), IL-2 (p = 0.001), IL-4 (p < 0.01), IL-10 (p < 0.01), IL-17A (p < 0.01), PlGF (p < 0.0001) and basic FGF (p < 0.0001) were found in cases compared to control participants. PDAC patients with irresectable tumours had higher levels of VEGF (p = 0.02) and IL-6 (p = 0.01). A univariate analysis showed significant associations between IFN-γ, TNF, IL-10, -4, -2, basic FGF, PlGF and PDAC. In a multivariate logistic regression model, basic FGF (p = 0.002) and PlGF (p = 0.007) were independent risk factors for PDAC with a combined sensitivity of 71% and specificity of 100%.

CONCLUSION

Our preliminary data suggests a potential role for basic FGF and PlGF as diagnostic, and VEGF and IL-6 as prognostic biomarkers of PDAC in Black South African patients.

Biomarkers in pancreatic adenocarcinoma: current perspectives

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of 7.7%. Most patients are diagnosed at an advanced stage not amenable to potentially curative resection. A substantial portion of this review is dedicated to reviewing the current literature on carbohydrate antigen (CA 19-9), which is currently the only guideline-recommended biomarker for PDAC. It provides valuable prognostic information, can predict resectability, and is useful in decision making about neoadjuvant therapy. We also discuss carcinoembryonic antigen (CEA), CA 125, serum biomarker panels, circulating tumor cells, and cell-free nucleic acids. Although many biomarkers have now been studied in relation to PDAC, significant work still needs to be done to validate their usefulness in the early detection of PDAC and management of patients with PDAC.

A Proteogenomic Approach to Understanding MYC Function in Metastatic Medulloblastoma Tumors

Brain tumors are the leading cause of cancer-related deaths in children, and medulloblastoma is the most prevalent malignant childhood/pediatric brain tumor. Providing effective treatment for these cancers, with minimal damage to the still-developing brain, remains one of the greatest challenges faced by clinicians. Understanding the diverse events driving tumor formation, maintenance, progression, and recurrence is necessary for identifying novel targeted therapeutics and improving survival of patients with this disease. Genomic copy number alteration data, together with clinical studies, identifies c-MYC amplification as an important risk factor associated with the most aggressive forms of medulloblastoma with marked metastatic potential. Yet despite this, very little is known regarding the impact of such genomic abnormalities upon the functional biology of the tumor cell. We discuss here how recent advances in quantitative proteomic techniques are now providing new insights into the functional biology of these aggressive tumors, as illustrated by the use of proteomics to bridge the gap between the genotype and phenotype in the case of c-MYC-amplified/associated medulloblastoma. These integrated proteogenomic approaches now provide a new platform for understanding cancer biology by providing a functional context to frame genomic abnormalities.

Proteomic analysis of ovarian cancer cells during epithelial-mesenchymal transition (EMT) induced by epidermal growth factor (EGF) reveals mechanisms of cell cycle control

Epithelial to mesenchymal transition (EMT) is a well-orchestrated process that culminates with loss of epithelial phenotype and gain of a mesenchymal and migratory phenotype. EMT enhances cancer cell invasiveness and drug resistance, favoring metastasis. Dysregulation of transcription factors, signaling pathways, miRNAs and growth factors including EGF, TGF-beta and HGF can trigger EMT. In ovarian cancer, overexpression of the EGFR family is associated with more aggressive clinical behavior. Here, the ovarian adenocarcinoma cell line Caov-3 was induced to EMT with EGF in order to identify specific mechanisms controlled by this process. Caov-3 cells induced to EMT were thoroughly validated and a combination of subcellular proteome enrichment, GEL-LC-MS/MS and SILAC strategy allowed consistent proteome identification and quantitation. Protein network analysis of differentially expressed proteins highlighted regulation of metabolism and cell cycle. Activation of relevant signaling pathways, such as PI3K/Akt/mTOR and Ras/Erk MAPK, in response to EGF-induced EMT was validated. Also, EMT did not affected the proliferation rate of Caov-3 cells, but led to cell cycle arrest in G1 phase regulated by increased levels of p21Waf1/Cip1, independently of p53. Furthermore, a decrease in G1 and G2 checkpoint proteins was observed, supporting the involvement of EGF-induced EMT in cell cycle control.

BIOLOGICAL SIGNIFICANCE

Cancer is a complex multistep process characterized by accumulation of several hallmarks including epithelial to mesenchymal transition (EMT), which promotes cellular and microenvironmental changes resulting in invasion and migration to distant sites, favoring metastasis. EMT can be triggered by different extracellular stimuli, including growth factors such as EGF. In ovarian cancer, the most lethal gynecological cancer, overexpression of the EGFR family is associated with more aggressive clinical behavior, increasing mortality rate caused by metastasis. Our proteomic data, together with specific validation of specific cellular mechanisms demonstrated that EGF-induced EMT in Caov-3 cells leads to important alterations in metabolic process (protein synthesis) and cell cycle control, supporting the implication of EGF/EMT in cancer metastasis, cancer stem cell generation and, therefore, poor prognosis for the disease.

Genetics and biology of pancreatic ductal adenocarcinoma

Ying et al. review pancreatic ductal adenocarcinoma (PDAC) genetics and biology, particularly altered cancer cell metabolism, the complexity of immune regulation in the tumor microenvironment, and impaired DNA repair processes.

With 5-year survival rates remaining constant at 6% and rising incidences associated with an epidemic in obesity and metabolic syndrome, pancreatic ductal adenocarcinoma (PDAC) is on track to become the second most common cause of cancer-related deaths by 2030. The high mortality rate of PDAC stems primarily from the lack of early diagnosis and ineffective treatment for advanced tumors. During the past decade, the comprehensive atlas of genomic alterations, the prominence of specific pathways, the preclinical validation of such emerging targets, sophisticated preclinical model systems, and the molecular classification of PDAC into specific disease subtypes have all converged to illuminate drug discovery programs with clearer clinical path hypotheses. A deeper understanding of cancer cell biology, particularly altered cancer cell metabolism and impaired DNA repair processes, is providing novel therapeutic strategies that show strong preclinical activity. Elucidation of tumor biology principles, most notably a deeper understanding of the complexity of immune regulation in the tumor microenvironment, has provided an exciting framework to reawaken the immune system to attack PDAC cancer cells. While the long road of translation lies ahead, the path to meaningful clinical progress has never been clearer to improve PDAC patient survival.

Genetically Engineered Mouse Models of Pancreatic Cancer: The KPC Model (LSL-Kras(G12D/+) ;LSL-Trp53(R172H/+) ;Pdx-1-Cre), Its Variants, and Their Application in Immuno-oncology Drug Discovery

Pancreatic ductal adenocarcinoma (PDAC) ranks fourth among cancer-related deaths in the United States. For patients with unresectable disease, treatment options are limited and lack curative potential. Preclinical mouse models of PDAC that recapitulate the biology of human pancreatic cancer offer an opportunity for the rational development of novel treatment approaches that may improve patient outcomes. With the recent success of immunotherapy for subsets of patients with solid malignancies, interest is mounting in the possible use of immunotherapy for the treatment of PDAC. Considered in this unit is the value of genetic mouse models for characterizing the immunobiology of PDAC and for investigating novel immunotherapeutics. Several variants of these models are described, all of which may be used in drug development and for providing information on unique aspects of disease biology and therapeutic responsiveness. © 2016 by John Wiley & Sons, Inc.

Pancreatic cancer

Pancreatic cancer is a major cause of cancer-associated mortality, with a dismal overall prognosis that has remained virtually unchanged for many decades. Currently, prevention or early diagnosis at a curable stage is exceedingly difficult; patients rarely exhibit symptoms and tumours do not display sensitive and specific markers to aid detection. Pancreatic cancers also have few prevalent genetic mutations; the most commonly mutated genes are KRAS, CDKN2A (encoding p16), TP53 and SMAD4 - none of which are currently druggable. Indeed, therapeutic options are limited and progress in drug development is impeded because most pancreatic cancers are complex at the genomic, epigenetic and metabolic levels, with multiple activated pathways and crosstalk evident. Furthermore, the multilayered interplay between neoplastic and stromal cells in the tumour microenvironment challenges medical treatment. Fewer than 20% of patients have surgically resectable disease; however, neoadjuvant therapies might shift tumours towards resectability. Although newer drug combinations and multimodal regimens in this setting, as well as the adjuvant setting, appreciably extend survival, ∼80% of patients will relapse after surgery and ultimately die of their disease. Thus, consideration of quality of life and overall survival is important. In this Primer, we summarize the current understanding of the salient pathophysiological, molecular, translational and clinical aspects of this disease. In addition, we present an outline of potential future directions for pancreatic cancer research and patient management.

Improved Pancreatic Adenocarcinoma Diagnosis in Jaundiced and Non-Jaundiced Pancreatic Adenocarcinoma Patients through the Combination of Routine Clinical Markers Associated to Pancreatic Adenocarcinoma Pathophysiology

BACKGROUND

There is still no reliable biomarker for the diagnosis of pancreatic adenocarcinoma. Carbohydrate antigen 19-9 (CA 19-9) is a tumor marker only recommended for pancreatic adenocarcinoma follow-up. One of the clinical problems lies in distinguishing between this cancer and other benign pancreatic diseases such as chronic pancreatitis. In this study we will assess the value of panels of serum molecules related to pancreatic cancer physiopathology to determine whether alone or in combination could help to discriminate between these two pathologies.

METHODS

CA 19-9, carcinoembryonic antigen (CEA), C-reactive protein, albumin, insulin growth factor-1 (IGF-1) and IGF binding protein-3 were measured using routine clinical analyzers in a cohort of 47 pancreatic adenocarcinoma, 20 chronic pancreatitis and 15 healthy controls.

RESULTS

The combination of CA 19-9, IGF-1 and albumin resulted in a combined area under the curve (AUC) of 0.959 with 93.6% sensitivity and 95% specificity, much higher than CA 19-9 alone. An algorithm was defined to classify the patients as chronic pancreatitis or pancreatic cancer with the above specificity and sensitivity. In an independent validation group of 20 pancreatic adenocarcinoma and 13 chronic pancreatitis patients, the combination of the four molecules classified correctly all pancreatic adenocarcinoma and 12 out of 13 chronic pancreatitis patients.

CONCLUSIONS

Although this panel of markers should be validated in larger cohorts, the high sensitivity and specificity values and the convenience to measure these parameters in clinical laboratories shows great promise for improving pancreatic adenocarcinoma diagnosis.