Discriminating patients with early-stage pancreatic cancer or chronic pancreatitis using serum electrospray mass profiling

Sera Protein Signatures of Endometrial Cancer Lymph Node Metastases

The presence of lymph node metastases in endometrial cancer patients is a critical factor guiding treatment decisions; however, surgical and imaging methods for their detection are limited by morbidity and inaccuracy. To determine if sera can predict the presence of positive lymph nodes, sera collected from endometrial cancer patients with or without lymph node metastases, and benign gynecology surgical patients (N = 20 per group) were subjected to electron spray ionization mass spectrometry (ES-MS). Peaks that were significantly different among the groups were evaluated by leave one out cross validation (LOOCV) for their ability to differentiation between the groups. Proteins in the peaks were identified by MS/MS of five specimens in each group. Ingenuity Pathway Analysis was used to predict pathways regulated by the protein profiles. LOOCV of sera protein discriminated between each of the group comparisons and predicted positive lymph nodes. Pathways implicated in metastases included loss of PTEN activation and PI3K, AKT and PKA activation, leading to calcium signaling, oxidative phosphorylation and estrogen receptor-induced transcription, leading to platelet activation, epithelial-to-mesenchymal transition and senescence. Upstream activators implicated in these events included neurostimulation and inflammation, activation of G-Protein-Coupled Receptor Gβγ, loss of HER-2 activation and upregulation of the insulin receptor.

Giant obscurin regulates migration and metastasis via RhoA-dependent cytoskeletal remodeling in pancreatic cancer

Obscurins, encoded by the OBSCN gene, are giant cytoskeletal proteins with structural and regulatory roles. Large scale omics analyses reveal that OBSCN is highly mutated across different types of cancer, exhibiting a 5-8% mutation frequency in pancreatic cancer. Yet, the functional role of OBSCN in pancreatic cancer progression and metastasis has to be delineated. We herein show that giant obscurins are highly expressed in normal pancreatic tissues, but their levels are markedly reduced in pancreatic ductal adenocarcinomas. Silencing of giant obscurins in non-tumorigenic Human Pancreatic Ductal Epithelial (HPDE) cells and obscurin-expressing Panc5.04 pancreatic cancer cells induces an elongated, spindle-like morphology and faster cell migration via cytoskeletal remodeling. Specifically, depletion of giant obscurins downregulates RhoA activity, which in turn results in reduced focal adhesion density, increased microtubule growth rate and faster actin dynamics. Although OBSCN knockdown is not sufficient to induce de novo tumorigenesis, it potentiates tumor growth in a subcutaneous implantation model and exacerbates metastasis in a hemispleen murine model of pancreatic cancer metastasis, thereby shortening survival. Collectively, these findings reveal a critical role of giant obscurins as tumor suppressors in normal pancreatic epithelium whose loss of function induces RhoA-dependent cytoskeletal remodeling, and promotes cell migration, tumor growth and metastasis.

OKN-007 Alters Protein Expression Profiles in High-Grade Gliomas: Mass Spectral Analysis of Blood Sera

Current therapies for high-grade gliomas, particularly glioblastomas (GBM), do not extend patient survival beyond 16–22 months. OKN-007 (OKlahoma Nitrone 007), which is currently in phase II (multi-institutional) clinical trials for GBM patients, and has demonstrated efficacy in several rodent and human xenograft glioma models, shows some promise as an anti-glioma therapeutic, as it affects most aspects of tumorigenesis (tumor cell proliferation, angiogenesis, migration, and apoptosis). Combined with the chemotherapeutic agent temozolomide (TMZ), OKN-007 is even more effective by affecting chemo-resistant tumor cells. In this study, mass spectrometry (MS) methodology ESI-MS, mass peak analysis (Leave One Out Cross Validation (LOOCV) and tandem MS peptide sequence analyses), and bioinformatics analyses (Ingenuity^® Pathway Analysis (IPA^®)), were used to identify up- or down-regulated proteins in the blood sera of F98 glioma-bearing rats, that were either untreated or treated with OKN-007. Proteins of interest identified by tandem MS-MS that were decreased in sera from tumor-bearing rats that were either OKN-007-treated or untreated included ABCA2, ATP5B, CNTN2, ITGA3, KMT2D, MYCBP2, NOTCH3, and VCAN. Conversely, proteins of interest in tumor-bearing rats that were elevated following OKN-007 treatment included ABCA6, ADAMTS18, VWA8, MACF1, and LAMA5. These findings, in general, support our previous gene analysis, indicating that OKN-007 may be effective against the ECM. These findings also surmise that OKN-007 may be more effective against oligodendrogliomas, other brain tumors such as medulloblastoma, and possibly other types of cancers.

Obscurin: A multitasking giant in the fight against cancer

Giant obscurins (720-870 kDa), encoded by OBSCN, were originally discovered in striated muscles as cytoskeletal proteins with scaffolding and regulatory roles. Recently though, they have risen to the spotlight as key players in cancer development and progression. Herein, we provide a timely prudent synopsis of the expanse of OBSCN mutations across 16 cancer types. Given the extensive work on OBSCN's role in breast epithelium, we summarize functional studies implicating obscurins as potent tumor suppressors in breast cancer and delve into an in silico analysis of its mutational profile and epigenetic (de)regulation using different dataset platforms and sophisticated computational tools. Lastly, we formally describe the OBSCN-Antisense-RNA-1 gene, which belongs to the long non-coding RNA family and discuss its potential role in modulating OBSCN expression in breast cancer. Collectively, we highlight the escalating involvement of obscurins in cancer biology and outline novel potential mechanisms of OBSCN (de)regulation that warrant further investigation.

A comparative analysis of CT and MRI in differentiating pancreatic cancer from mass pancreatitis

AIM

This paper aims to explore the practical value of CT signs combined with magnetic resonance imaging with diffusion-weighted imaging (MRI-DWI) and magnetic resonance cholangiopancreatography (MRCP) in the differential diagnosis of pancreatic carcinoma and mass-forming pancreatitis.

METHODS

We carried out a retrospective analysis of the imaging data of 61 patients with pancreatic mass lesions who were diagnosed based on postoperative pathology in our hospital from May 2013 to May 2020 and analyzed the image diagnostic value of the combination of 128-slice CT and 1.5T MRI-DWI.

RESULTS

There were no significant differences in the pancreatic duct dilatation, the bile duct dilatation, or the peripancreatic and retroperitoneal lymph node enlargement between the patients with pancreatic carcinoma and the patients with mass-forming pancreatitis (P > 0.05). Both the incidences of lobulation signs and peripancreatic vascular invasion in the patients with pancreatic carcinoma were higher than they were in the patients with mass-forming pancreatitis, and the mass calcification, pseudocyst, and pancreatic duct stone rates, the net enhanced CT values in the arterial and pancreatic parenchyma phases, and the ADC values in pancreatic carcinoma patients were lower than they were in the patients with mass-forming pancreatitis (P < 0.05). The pancreatic duct stone and right prerenal fascial thickening rates in the patients with pancreatic carcinoma were lower than they were in the patients with mass-forming pancreatitis (P < 0.05).

CONCLUSION

CT signs combined with the MRI-DWI technique and MRCP can improve clinical pancreatic cancer diagnostic sensitivity.

Biomarkers of Chronic Pancreatitis: A systematic literature review

BACKGROUND

Chronic pancreatitis (CP) does not have diagnostic or prognostic biomarkers. CP is the end stage of a progressive inflammatory syndrome that is diagnosed at late stages by morphologic features. To diagnose earlier stages of the disease, a new mechanistic definition was established based on identifying underlying pathogenic processes and biomarker evidence of disease activity and stage. Although multiple risk factors are known, the corresponding biomarkers needed to make a highly accurate diagnosis of earlier disease stages have not been established. The goal of this study is to systematically analyze the literature to identify the most likely candidates for development into biomarkers of CP.

METHODS

We conducted a systematic review of candidate analytes from easily accessible biological fluids and identified 67 studies that compared CP to nonpancreatic-disease controls. We then ranked candidate biomarkers for sensitivity and specificity by area under the receiver operator curves (AUROCs).

RESULTS

Five biomarkers had a large effect size (an AUROC > 0.96), whereas 30 biomarkers had a moderate effect size (an AUROC between 0.96 and 0.83) for distinguishing CP cases from controls or other diseases. However, the studies reviewed had marked variability in design, enrollment criteria, and biospecimen sample handling and collection.

CONCLUSIONS

Several biomarkers have the potential for evaluation in prospective cohort studies and should be correlated with risk factors, clinical features, imaging studies and outcomes. The Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreas Cancer provides recommendations for avoiding design biases and heterogeneity in sample collection and handling in future studies.

The future of Extracellular Vesicles as Theranostics - an ISEV meeting report

The utilization of extracellular vesicles (EVs) in clinical theranostics has rapidly advanced in the past decade. In November 2018, the International Society for Extracellular Vesicles (ISEV) held a workshop on “EVs in Clinical Theranostic”. Here, we report the conclusions of roundtable discussions on the current advancement in the analysis technologies and we provide some guidelines to researchers in the field to consider the use of EVs in clinical application. The main challenges and the requirements for EV separation and characterization strategies, quality control and clinical investigation were discussed to promote the application of EVs in future clinical studies.

Distinguishing patients with idiopathic epilepsy from solitary cysticercus granuloma epilepsy and biochemical phenotype assessment using a serum biomolecule profiling platform

A major source of epilepsy is Neurocysticercosis (NCC), caused by Taenia solium infection. Solitary cysticercus granuloma (SCG), a sub-group of NCC induced epilepsy, is the most common form of NCC in India. Current diagnostic criteria for SCG epilepsy require brain imaging which may not be available in communities where the disease is endemic. Identification of serum changes and potential biomolecules that could distinguish SCG epilepsy from idiopathic generalized epilepsy (IE), without the initial need for imaging, could assist in disease identification, understanding, and treatment. The objective here was to investigate, using mass spectrometry (MS), sera biomolecule differences between patients with SCG epilepsy or IE to help distinguish these disorders based on physiological differences, to understand underlying phenotypes and mechanisms, and to lay ground work for future therapeutic and biomarker analyses. Sera were obtained from patients with SCG or IE (N = 29 each group). Serum mass peak profiling was performed with electrospray ionization (ESI) MS, and mass peak area means in the two groups were compared using leave one [serum sample] out cross validation (LOOCV). Serum LOOCV analysis identified significant differences between SCG and IE patient groups (p = 10-20), which became non-significant (p = 0.074) when the samples were randomly allocated to the groups and reanalyzed. Tandem MS/MS peptide analysis of serum mass peaks from SCG or IE patients was performed to help identify potential peptide/protein biochemical and phenotypic changes involving these two forms of epilepsy. Bioinformatic analysis of these peptide/protein changes suggested neurological, inflammatory, seizure, blood brain barrier, cognition, ion channel, cell death, and behavior related biochemical systems were being altered in these disease states. This study provides groundwork for aiding in distinguishing SCG and IE patients in minimally invasive, lower-cost manners, for improving understanding of underlying epilepsy mechanisms, and for further identifying discriminatory biomarkers and potential therapeutic targets.

Serum discrimination and phenotype assessment of coronary artery disease patents with and without type 2 diabetes prior to coronary artery bypass graft surgery

Diabetes Mellitus (DM) accelerates coronary artery disease (CAD) and atherosclerosis, the causes of most heart attacks. The biomolecules involved in these inter-related disease processes are not well understood. This study analyzes biomolecules in the sera of patients with CAD, with and without type (T) 2DM, who are about to undergo coronary artery bypass graft (CABG) surgery. The goal is to develop methodology to help identify and monitor CAD patients with and without T2DM, in order to better understand these phenotypes and to glean relationships through analysis of serum biomolecules. Aorta, fat, muscle, and vein tissues from CAD T2DM patients display diabetic-related histologic changes (e.g., lipid accumulation, fibrosis, loss of cellularity) when compared to non-diabetic CAD patients. The patient discriminatory methodology utilized is serum biomolecule mass profiling. This mass spectrometry (MS) approach is able to distinguish the sera of a group of CAD patients from controls (p value 10⁻¹⁵), with the CAD group containing both T2DM and non-diabetic patients. This result indicates the T2DM phenotype does not interfere appreciably with the CAD determination versus control individuals. Sera from a group of T2DM CAD patients however are distinguishable from non-T2DM CAD patients (p value 10⁻⁸), indicating it may be possible to examine the T2DM phenotype within the CAD disease state with this MS methodology. The same serum samples used in the CAD T2DM versus non-T2DM binary group comparison were subjected to MS/MS peptide structure analysis to help identify potential biochemical and phenotypic changes associated with CAD and T2DM. Such peptide/protein identifications could lead to improved understanding of underlying mechanisms, additional biomarkers for discriminating and monitoring these disease conditions, and potential therapeutic targets. Bioinformatics/systems biology analysis of the peptide/protein changes associated with CAD and T2DM suggested cell pathways/systems affected include atherosclerosis, DM, fibrosis, lipogenesis, loss of cellularity (apoptosis), and inflammation.

Distinguishing and Biochemical Phenotype Analysis of Epilepsy Patients Using a Novel Serum Profiling Platform

Diagnosis of non-symptomatic epilepsy includes a history of two or more seizures and brain imaging to rule out structural changes like trauma, tumor, infection. Such analysis can be problematic. It is important to develop capabilities to help identify non-symptomatic epilepsy in order to better monitor and understand the condition. This understanding could lead to improved diagnostics and therapeutics. Serum mass peak profiling was performed using electrospray ionization mass spectrometry (ESI-MS). A comparison of sera mass peaks between epilepsy and control groups was performed via leave one [serum sample] out cross-validation (LOOCV). MS/MS peptide analysis was performed on serum mass peaks to compare epilepsy patient and control groups. LOOCV identified significant differences between the epilepsy patient group and control group (p = 10⁻²²). This value became non-significant (p = 0.10) when the samples were randomly allocated between the groups and reanalyzed by LOOCV. LOOCV was thus able to distinguish a non-symptomatic epilepsy patient group from a control group based on physiological differences and underlying phenotype. MS/MS was able to identify potential peptide/protein changes involved in this epilepsy versus control comparison, with 70% of the top 100 proteins indicating overall neurologic function. Specifically, peptide/protein sera changes suggested neuro-inflammatory, seizure, ion-channel, synapse, and autoimmune pathways changing between epilepsy patients and controls.

Potential biomarkers for early detection of pancreatic ductal adenocarcinoma

Pancreatic cancer has the highest mortality amongst all major organ cancers. Early detection is key to reduce deaths related to pancreatic cancer. However, early detection has been challenged by the lack of non-invasive biomarkers with enough sensitivity and specificity to allow for screening. The gold standard is still carbohydrate antigen (CA 19-9), against which all new biomarkers must be evaluated. In this paper, we describe recent progress in the development of new pancreatic cancer biomarkers, focusing on proteins, metabolites, and genetic and epigenetic biomarkers. Although several promising biomarkers have been identified, they are all derived from retrospective studies and additional prospective studies are needed to confirm their clinical validity.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Distinguishing and phenotype monitoring of traumatic brain injury and post-concussion syndrome including chronic migraine in serum of Iraq and Afghanistan war veterans

Traumatic Brain Injury (TBI) and persistent post-concussion syndrome (PCS) including chronic migraine (CM) are major health issues for civilians and the military. It is important to understand underlying biochemical mechanisms of these conditions, and be able to monitor them in an accurate and minimally invasive manner. This study describes the initial use of a novel serum analytical platform to help distinguish TBI patients, including those with post-traumatic headache (PTH), and to help identify phenotypes at play in these disorders. The hypothesis is that physiological responses to disease states like TBI and PTH and related bodily stresses are reflected in biomolecules in the blood in disease-specific manner. Leave one out (serum sample) cross validations (LOOCV) and sample randomizations were utilized to distinguished serum samples from the following TBI patient groups: TBI +PTSD + CM + severe depression (TBI "most affected" group) vs healthy controls, TBI "most affected" vs TBI, TBI vs controls, TBI + CM vs controls, and TBI + CM vs TBI. Inter-group discriminatory p values were ≤ 10-10, and sample group randomizations resulted in p non-significant values. Peptide/protein identifications of discriminatory mass peaks from the TBI "most affected" vs controls and from the TBI plus vs TBI minus CM groups yielded information of the cellular/molecular effects of these disorders (immune responses, amyloidosis/Alzheimer's disease/dementia, neuronal development). More specific biochemical disease effects appear to involve blood brain barrier, depression, migraine headache, autoimmunity, and autophagy pathways. This study demonstrated the ability for the first time of a novel, accurate, biomarker platform to monitor these conditions in serum, and help identify biochemical relationships leading to better understanding of these disorders and to potential therapeutic approaches.

Distinguishing neurocysticercosis epilepsy from epilepsy of unknown etiology using a minimal serum mass profiling platform

Neurocysticercosis is associated with epilepsy in pig-raising communities with poor sanitation. Current internationally recognized diagnostic guidelines for neurocysticercosis rely on brain imaging, a technology that is frequently not available or not accessible in areas endemic for neurocysticercosis. Minimally invasive and low-cost aids for diagnosing neurocysticercosis epilepsy could improve treatment of neurocysticercosis. The goal of this study was to test the extent to which patients with neurocysticercosis epilepsy, epilepsy of unknown etiology, idiopathic headaches and among different types of neurocysticercosis lesions could be distinguished from each other based on serum mass profiling. For this, we collected sera from patients with neurocysticercosis-associated epilepsy, epilepsy of unknown etiology, recovered neurocysticercosis, and idiopathic headaches then performed binary group comparisons among them using electrospray ionization mass spectrometry. A leave one [serum sample] out cross validation procedure was employed to analyze spectral data. Sera from neurocysticercosis patients was distinguished from epilepsy of unknown etiology patients with a p-value of 10^-28. This distinction was lost when samples were randomized to either group (p-value = 0.22). Similarly, binary comparisons of patients with neurocysticercosis who has different types of lesions showed that different forms of this disease were also distinguishable from one another. These results suggest neurocysticercosis epilepsy can be distinguished from epilepsy of unknown etiology based on biomolecular differences in sera detected by mass profiling.

Recent advances in proteomic profiling of pancreatic ductal adenocarcinoma and the road ahead

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide. However, there remain many unmet clinical needs, from diagnosis to treatment strategies. The inherent complexity of the molecular characteristics of PDAC has made it difficult to meet these challenges, rendering proteomic profiling of PDAC a critical area of research. Area covered: In this review, we present recent advances in mass spectrometry (MS) and its current application in proteomic studies on PDAC. In addition, we discuss future directions for research that can efficiently incorporate current MS-based technologies that address key issues of PDAC proteomics. Expert commentary: Compared with other cancer studies, little progress has been made in PDAC proteomics, perhaps attributed to the difficulty in performing in-depth and large-scale clinical studies on PDAC. However, recent advances in mass spectrometry can advance PDAC proteomics past the fundamental research stage.

Serum Monitoring and Phenotype Identification of Stage I Non-Small Cell Lung Cancer Patients

A stage I non-small cell lung cancer (NSCLC) serum profiling platform is presented which is highly efficient and accurate. Test sensitivity (0.95) for stage I NSCLC is the highest reported so far. Test metrics are reported for discriminating stage I adenocarcinoma vs squamous cell carcinoma subtypes. Blinded analysis identified 23 out of 24 stage I NSCLC and control serum samples. Group-discriminating mass peaks were targeted for tandem mass spectrometry peptide/protein identification, and yielded a lung cancer phenotype. Bioinformatic analysis revealed a novel lymphocyte adhesion pathway involved with early-stage lung cancer.

Actual long-term outcome of T1 and T2 pancreatic ductal adenocarcinoma after surgical resection

BACKGROUND

The prognosis for patients with pancreatic cancer is extremely poor. The diagnosis of pancreatic ductal adenocarcinoma at an early stage is uncommon. The purpose of this study was to analyze the clinicopathological characteristics of patients with pathologically proven pancreatic ductal adenocarcinoma following surgical resection and their actual 5 year survival rates, especially for those with T1 and T2 early stage cancer.

METHODS

Retrospective analysis was performed for 433 patients with pancreatic ductal adenocarcinoma who underwent resection at Samsung medical center between May 1995 and December 2010. The actual 5 year survival rates and prognostic factors were analyzed.

RESULTS

Multivariate analysis showed that positive resection margin, poor differentiation, large tumor size, large amount of blood loss, and T3/T4 were independent prognostic factors on overall survival. The median survival for T1/T2 stage was 71.7 months compared to 16.1 months for those with T3/T4 stage. The actual 5 year survival rates for T1/T2 and T3/T4 stages were 66.7% and 18.4%, respectively.

CONCLUSIONS

T stage is one of the strongest independent prognostic factor for overall survival of patients with pancreatic cancer. T1/T2 pancreatic ductal adenocarcinoma showed good survival outcome. Therefore, additional efforts are needed to improve the screening for early detection.

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.