Candidate Protein Biomarkers Research Articles

Proteomic Profiling Change and Its Implies in the Early Mycosis Fungoides (MF) Using Isobaric Tags for Relative and Absolute Quantification (iTRAQ).

Purpose Mycosis fungoides (MF) is the most common T-cell lymphoma, with indolent biologic behavior in the early stage and features of invasive in the tumor stage. The diagnosis of MF is still ambiguous and difficult. We focused on the proteomic profiling change in the pathogenesis of early MF and identified candidate biomarkers for early diagnosis. Methods We collected peripheral blood samples of MF patients and healthy individuals (HI) performed proteomic profiling analysis using isobaric tags for relative and absolute quantification (iTRAQ) platform. Differently expressed proteins (DEPs) were filtered, and involved biological functions were analyzed through Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software. Results We identified 78 DEPs including fifty proteins were upregulated and 28 proteins were downregulated in the MF group with HI as a control. Total DEPs were analyzed according to the biological regulation and metabolic process through GO analysis. The pathways of LXR/RXR activation and FXR/RXR activation were significantly activated, in which APOH, CLU, and ITIH4 were involved. The top annotated disease and function network was (Cancer, Organismal Injury and Abnormalities, Reproductive System Disease), with a key node CLU. These DEPs were involved in cancer, including thyroid carcinoma, head and neck carcinoma, and cancer of secretory structure, in which CLU, GNAS, and PKM played an indirect role in the occurrence and development of cancer. Relevant causal network was IL12 (family), which is related to GNAS, PKM, and other DEPs. Conclusion Proteomic profiling of early-stage MF provided candidate protein biomarkers such as CLU, GNAS, and PKM, which benefit the early diagnosis and understanding of the mechanism of MF development. Besides, lipid metabolism may be one of the pathogenesis of MF, and IL12 was a potential marker for the diagnosis and treatment of early MF.

Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer.

Simple SummaryIn-time diagnosing ovarian cancer, intractable cancer that has no symptoms can increase the survival of women. The aim of this study was to discover biomarkers from liquid biopsy samples using multi-omics approach, metabolomics and proteomics for the diagnosis of ovarian cancer. To verify our biomarker candidates, we conducted comparative analysis with other previous published studies. Despite the limitations of non-invasive samples, our findings are able to discover emerging properties through the interplay between metabolites and proteins and mechanism-based biomarkers through integrated protein and metabolite analysis.The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified.

Definition and Independent Validation of a Proteomic-Classifier in Ovarian Cancer.

Simple SummaryThe heterogeneity of epithelial ovarian cancer and its associated molecular biological characteristics are continuously integrated in the development of therapy guidelines. In a next step, future therapy recommendations might also be able to focus on the patient’s systemic status, not only the tumor’s molecular pattern. Therefore, new methods to identify and validate host-related biomarkers need to be established. Using mass spectrometry, we developed and independently validated a blood-based proteomic classifier, stratifying epithelial ovarian cancer patients into good and poor survival groups. We also determined an age dependence of the prognostic performance of this classifier and its association with important biological processes. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response and could therefore be integrated into future processes of therapy planning.Mass-spectrometry-based analyses have identified a variety of candidate protein biomarkers that might be crucial for epithelial ovarian cancer (EOC) development and therapy response. Comprehensive validation studies of the biological and clinical implications of proteomics are needed to advance them toward clinical use. Using the Deep MALDI method of mass spectrometry, we developed and independently validated (development cohort: n = 199, validation cohort: n = 135) a blood-based proteomic classifier, stratifying EOC patients into good and poor survival groups. We also determined an age dependency of the prognostic performance of this classifier, and our protein set enrichment analysis showed that the good and poor proteomic phenotypes were associated with, respectively, lower and higher levels of complement activation, inflammatory response, and acute phase reactants. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response in a subset of ovarian cancer patients and could therefore be integrated into future processes of therapy planning.

Abstract 1200: Associations between genetically predicted blood protein biomarkers and pancreatic ductal adenocarcinoma risk

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of most lethal malignancies with few known risk factors and biomarkers. Identification of disease biomarkers is critical for understanding the pathogenesis of this cancer and identifying high risk individuals for close surveillance. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers usually in small samples. To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, by using genetic instruments. Protein quantitative trait loci (pQTLs) for 1,226 plasma proteins identified in a large INTERVAL study of 3,301 healthy European descendants were used as instruments to evaluate associations between genetically predicted protein levels and PDAC. For proteins showing a significant association, we further conducted conditional analysis with adjustments for previously identified risk variants to assess whether the observed associations between genetically predicted protein concentrations and PDAC risk were independent of the risk variants identified in genome-wide association studies (GWAS). Furthermore, for the proteins that were associated with PDAC risk, we performed an enrichment analysis of the genes encoding these proteins to examine whether they are enriched in specific pathways, functions or networks. We observed associations between predicted concentrations of 38 proteins and PDAC risk at a false discovery rate of < 0.05, including those of 23 proteins that showed a significant association even after Bonferroni correction (4.08 × 10−5). These include Histo-blood group ABO system transferase encoded by ABO, which has been previously implicated as a potential target gene of PDAC risk variant identified in GWAS. Eight of the identified proteins (Beta-crystallin B2, Dedicator of cytokinesis protein 9, VIP36-like protein, Erythrocyte band 7 integral membrane protein, Tensin-2, Transmembrane protease serine 11D, Alcohol dehydrogenase 1B, and C-X-C motif chemokine 10) were associated with PDAC risk after conditioning on previously reported pancreatic cancer risk variants (odds ratios ranged from 0.79 to 1.52, P-values from 1.28 × 10−3 to 6.47 × 10−4). Pathway enrichment analysis showed that the encoding genes for the implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL-15 production. In conclusion, we identified 38 protein biomarker candidates for PDAC risk, which if validated by additional studies, may contribute to the etiological understanding of PDAC tumor development. Citation Format: Jingjing Zhu, Xiang Shu, Xingyi Guo, Duo Liu, Jiandong bao, Roger Milne, Graham G Giles, Chong Wu, Mengmeng Du, Emily White, Harvey A Risch, Nuria Malats, Eric J. Duell, Phyllis J. Goodman, Donghui Li, Paige Bracci, Verena Katzke, Rachel E Neale, Steven Gallinger, Stephen Van Den Eeden, Alan Arslan, Federico Canzian, Charles Kooperberg, Brian Wolpin, Laura Beane-Freeman, Ghislaine Scelo, Kala Visvanatha, Christopher A. Haiman, Loïc Le Marchand, Herbert Yu, Gloria M Petersen, Rachael Stolzenberg-Solomon, Alison P Klein, Laufey T Amundadottir, Qiuyin Cai, Jirong Long, Xiao-Ou Shu, Wei Zheng, Lang Wu. Associations between genetically predicted blood protein biomarkers and pancreatic ductal adenocarcinoma risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1200.

Diagnostic and therapeutic potential of exosomes in Alzheimer’s disease

Exosomes are small extracellular vesicles released by almost all cell types in physiological and pathological conditions. The exosomal potential to unravel disease mechanisms, or to be used as a source of biomarkers, is being explored, in particularly in the field of neurodegenerative diseases. Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in the world and exosomes appear to have a relevant role in disease pathogenesis. This review summarizes the current knowledge on exosome contributions to AD as well as their use as disease biomarker resources or therapeutic targets. The most recent findings with respect to both protein and miRNA biomarker candidates for AD, herein described, highlight the state of the art in this field and encourage the use of exosomes derived from biofluids in clinical practice in the near future.

Detection of Head and Neck Cancer Based on Longitudinal Changes in Serum Protein Abundance.

Approximately 85% of the U.S. military active duty population is male and less than 50 years of age, with elevated levels of known risk factors for oropharyngeal squamous cell carcinoma (OPSCC), including smoking, excessive use of alcohol, and greater numbers of sexual partners, and elevated prevalence of human papilloma virus (HPV). Given the recent rise in incidence of OPSCC related to the HPV, the Department of Defense Serum Repository provides an unparalleled resource for longitudinal studies of OPSCC in the military for the identification of early detection biomarkers. We identified 175 patients diagnosed with OPSCC with 175 matched healthy controls and retrieved a total of 978 serum samples drawn at the time of diagnosis, 2 and 4 years prior to diagnosis, and 2 years after diagnosis. Following immunoaffinity depletion, serum samples were analyzed by targeted proteomics assays for multiplexed quantification of a panel of 146 candidate protein biomarkers from the curated literature. Using a Random Forest machine learning approach, we derived a 13-protein signature that distinguishes cases versus controls based on longitudinal changes in serum protein concentration. The abundances of each of the 13 proteins remain constant over time in control subjects. The AUC for the derived Random Forest classifier was 0.90. This 13-protein classifier is highly promising for detection of OPSCC prior to overt symptoms. Use of longitudinal samples has significant potential to identify biomarkers for detection and risk stratification.

Associations between Genetically Predicted Blood Protein Biomarkers and Pancreatic Cancer Risk.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of < 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. We identified 38 candidates of protein biomarkers for PDAC risk. This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.

Candidate protein biomarkers in pancreatic neuroendocrine neoplasms grade 3

Pancreatic neuroendocrine neoplasms (PanNENs) are rare tumours that compose 1–2% of all pancreatic tumours.Patients with metastatic grade 3 neoplasia are usually treated with chemotherapy but have a poor progression-free and overall survival. According to the WHO 2017 classification, they are divided into neuroendocrine tumours (NETs) G3 and neuroendocrine carcinomas (NECs). Despite the new classification, new diagnostic and prognostic biomarkers are needed to sub-categorise the patients and to help guide therapy decisions. Blood from 42 patients and 42 healthy controls were screened for the presence of 92 proteins with the Immuno-Oncology panel using the Proximity Extension Assay provided by Olink Biosciences. Immunohistochemical staining of FAS ligand (FASLG) was performed on 16 patient tumour specimens using a commercial antibody. Fifty-four out of 87 evaluable proteins differed significantly in concentration between blood from patients and blood from healthy controls. FASLG was the only protein for which the concentration in blood was significantly lower in patients compared to controls and the levels correlated negatively to Ki-67 index. Seven of 14 evaluable PanNEN G3 specimens showed FASLG immunoreactivity in the tumour cells while there was scattered immunoreactivity in immune cells. Positive FASLG immunoreactivity correlated to well-differentiated morphology.FASLG concentration in blood was significantly lower in patients with pancreatic NENs G3 compared to controls, and the expression in tumour tissue was variable. Furthermore, FASLG was negatively correlated to Ki-67 and was more frequently expressed in well-differentiated tumours. Taken together, these results may suggest a role of FASLG in PanNENs.

A novel urinary biomarker protein panel to identify children with ureteropelvic junction obstruction – A pilot study

Reliable urinary biomarker proteins would be invaluable in identifying children with ureteropelvic junction obstruction (UPJO) as the existing biomarker proteins are inconsistent in their predictive ability. Therefore, the aim of this study was to identify consistent and reliable urinary biomarker proteins in children with UPJO. To identify candidate biomarker proteins, total protein from age-restricted (<2 years) and sex-matched (males) control (n=22) and UPJO (n=21) urine samples was analyzed by mass spectrometry. Proteins that were preferentially identified in UPJO samples were selected (2-step process) and ranked according to their diagnostic odds ratio value. The top ten proteins with highest odds ratio values were selected and tested individually by ELISA. The total amount of each protein was normalized to urine creatinine and the median with interquartile ranges for control and UPJO samples was determined. Additionally, fold change (UPJO/Control) of medians of the final panel of 5 proteins was also determined. Finally, we calculated the average+3(SD) and average+4(SD) values of each of the 5 proteins in the control samples and used it as an arbitrary cutoff to classify individual control and UPJO samples. In the first step of our selection process, we identified 171 proteins in UPJO samples that were not detected in the majority of the control samples (16/22 samples, or 72.7%). Of the 171 proteins, only 50 proteins were detected in at least 11/21 (52.4%) of the UPJO samples and hence were selected in the second step. Subsequently, these 50 proteins were ranked according to the odds ratio value and the top 10 ranked proteins were validated by ELISA. Five of the 10 proteins - prostaglandin-reductase-1, ficolin-2, nicotinate-nucleotide pyrophosphorylase [carboxylating], immunoglobulin superfamily-containing leucine-rich-repeat-protein and vascular cell adhesion molecule-1 were present at higher levels in the UPJO samples (fold-change of the median protein concentrations ranging from 2.9 to 9.4) and emerged as a panel of biomarkers to identify obstructive uropathy. Finally, the order of prevalence of the 5 proteins in UPJO samples is PTGR1>FCN2>QPRT>ISLR>VCAM1. In summary, this unique screening strategy led to the identification of previously unknown biomarker proteins that when screened collectively, may reliably distinguish between obstructed vs. non-obstructed infants and may prove useful in identifying informative biomarker panels for biological samples from many diseases.

Abstract A073: TGF-beta receptor type-2 expression regulates breast cancer progression and is a prognostic marker for racial disparities

Abstract Transforming growth factor β (TGFβ) is one of the most important signaling pathways associated with cellular proliferation, and its dysregulation can lead to tumor development. TGFβ can act as either a tumor suppressor or a tumor promoter depending upon the cellular context and genetic alterations. TGFβ receptor type-2 (TGFβR2) is the ligand-binding receptor, and data shows that the aberration of TGFβR2 is associated with many different cancers including colon, gastric, biliary, pulmonary, and ovarian cancers. In this study, we focused on uncovering the functional role of TGFβR2 in regulating breast cancer (BrCa) progression. First, we analyzed the genomic alterations of TGFβR2 in a sample set from The Cancer Genome Atlas (TCGA, n=1084) on the cBioprotal platform. We focused on obtaining genetic modifications, including mutations and copy number alteration. Data indicated that almost 25% of the patient’s samples having TGFβ amplified copy number; however, only less than one percent patients have amplified copy of TGFβR2 and other TGFβ receptors, within across this sample set. Next, we have screened the level of TGFβR2 protein expression in different BrCa cell-lines. We found that the elevated level of TGFβR2 is associated with the most aggressive triple-negative MDA-MB-231 cells. It is also found that the TGFβR2 is secreted into extracellular space. Therefore, we next evaluated the expression level of TGFβR2 in patient’s serum samples. We have well defined and categorized BrCa patients serum samples (n=240) from the Clinical Breast Care Project led by Walter Reed National Military Medical Center, Bethesda. The differential expression level of TGFβR2 in serum indicated that the elevated level of TGFβR2 is associated with BrCa patients compared with healthy individuals. Furthermore, the serum level of TGFβR2 is higher in the African American patient population when compared to Caucasian patients, and most significant differences were found within Luminal B1 sub-type BrCa cases. To better understand the mechanism of the higher level of TGFβR2 protein expression, in association with aggressiveness, we hypothesized that increased levels of TGFβ ligand are inducing the expression of the receptor (TGFβR2) and eventually stimulating the oncogenic pathway. We have used a series of BrCa cell lines and incubated them with different concentrations of TGFβ ligand. The level of TGFβR2 protein was increased in BrCa cell lines after TGFβ ligand treatment. Increased levels of TGFβ2 ligand induces the expression of the relevant receptor. In summary, we quantified the expression levels of TGFβR2 in patients’ serum samples, which can be used to create a set of stage and race-specific candidate protein biomarkers for BrCa. We also found that the increased level of TGFβ ligand-induced the expression of the TGFβR2 receptor. We can also conclude that TGFβR2 is an important biomarker and possibly plays a role in racial disparities in breast cancer progression. Citation Format: Alakesh Bera, John Karaian, Harvey B Pollard, Hai Hu, Craig D Shriver, Meera Srivastava. TGF-beta receptor type-2 expression regulates breast cancer progression and is a prognostic marker for racial disparities [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A073.

Proteomics of Sentinel Lymph Nodes in Early Breast Cancer for Identification of Thymidylate Synthase as a Potential Biomarker to Flag Metastasis: A Preliminary Study.

IntroductionBreast cancer is the second most common cancer in women across the world. Some of the patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and its diagnosis is crucial for the staging of cancer thereby dictating the type of surgical therapy. Therefore, the sentinel lymph node status provides the most relevant information to the surgeon and patient prognosis. The expanded utilization of breast conservation surgery has declined the morbidity associated with mastectomy and axillary lymph node surgery. Recent interest is, therefore, centered on techniques that allow accurate assessment of the sentinel lymph node metastasis. A current procedure such as sentinel lymph node biopsy (SLNB) that is used to assess axillary lymph node metastasis is neither specific nor sensitive, and besides, it is time-consuming.ObjectiveTo compare the protein profiles between metastatic and non-metastatic lymph nodes to identify a biomarker that can flag lymph node metastasis.Materials and MethodsWomen with early breast cancer were screened using mammography imaging and recruited to the study. Surgical resection was done to remove the breast tissue, and sentinel lymph node was identified using fluorescein and methylene blue tracer. Lymph node was sliced, and one set was sent for histopathology, which was considered the gold standard to assess the metastatic status of the lymph node. One set of slices was taken for proteomic experiments. Proteins were labelled with fluorescent cyanine tags and were subjected to difference gel electrophoresis experiment. Differentially expressed spots that had at least a twofold relative ratio and consistent pattern across three sets of biological replicate experiments were marked. Gel spots were trypsin digested and identified on mass spectrometry machine. Validation study was done by Western blot experiment on the same set of samples.ResultsThymidylate synthase has a twofold higher expression in the metastatic sentinel lymph nodes as compared to non-metastatic lymph nodes in early breast cancer patients.ConclusionDifferential in gel expression proteomics is an ideal platform for the identification of potential protein biomarker candidates that can differentiate metastatic from non-metastatic lymph nodes in early breast cancer. The identification of thymidylate synthase offers a scope to develop an on-table diagnostic kit to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical management of axillary lymph nodes in early breast cancer.

Proteomics-Based Identification of Diagnostic Biomarkers Related to Risk Factors and Pathogenesis of Ischemic Stroke.

Ischemic stroke is caused by blood clot formation and consequent vessel blockage. Proteomic approaches provide a cost-effective alternative to current diagnostic methods, including computerized tomography (CT) scans and magnetic resonance imaging (MRI). To identify diagnostic biomarkers associated with ischemic stroke risk factors, we performed individual proteomic analysis of serum taken from 20 healthy controls and 20 ischemic stroke patients. We then performed SWATH analysis, a data-independent method, to assess quantitative changes in protein expression between the two experimental conditions. Our analysis identified several candidate protein biomarkers, 11 of which were validated by multiple reaction monitoring (MRM) analysis as novel diagnostic biomarkers associated with ischemic stroke risk factors. Our study identifies new biomarkers associated with the risk factors and pathogenesis of ischemic stroke which, to the best of our knowledge, were previously unknown. These markers may be effective in not only the diagnosis but also the prevention and management of ischemic stroke.

SAT-LB136 A Proteomic Approach to Identify Circulating Glucocorticoid Responsive Proteins in Humans

Glucocorticoids used in pharmacological doses for the treatment of a variety of medical conditions, and endogenous glucocorticoid excess - Cushing’s syndrome, may result in several adverse effects, but currently there is no clinically useful biomarker of glucocorticoid activity. We have applied a proteomic approach to the discovery of glucocorticoid-responsive proteins potentially measurable in human serum samples. To minimise the masking by abundant serum proteins, we conducted discovery proteomics on the secretome of ex vivo-stimulated peripheral blood mononuclear cells (PBMC) isolated from 12 volunteers. The PBMC were divided into 4 treatment groups; +/- dexamethasone 100 ng/mL (dex) for 4h, or +/- dex for 24h. In all treatment groups, media was changed to serum free for 3h before collection. Media samples were processed for proteomics, with 561 and 273 proteins analysed by label-free quantification (LFQ) for the 4h and 24h secretome, respectively. Paired statistical analysis at the 2 time points generated a shortlist of 43 candidate biomarker proteins, which was verified using a multiple reaction monitoring (MRM) assay, confirming the differential secretion of 12 proteins at both 4h and 24 h. Five proteins were selected for validation using enzyme linked immunosorbent assay (ELISA) in an independent cohort: β2 microglobulin (B2M), lysozyme C (LYZ), high-mobility group protein 2 (HMG2), nucleophosmin (NPM1) and nucleolin (NCL). Twenty new volunteers (10M and 10F) had venous blood drawn at baseline and 12h after 4 mg oral dex. Four proteins were detectable by ELISA, three of which showed statistically significant change in concentration. Serum LYZ and NPM1 significantly decreased following dex: LYZ - 101 ± 5.5 vs 67 ± 4.4 ng/mL, (P<0.0001); NPM1 - 17.4 ± 1.0 vs 14.3 ± 0.9 ng/mL, (P<0.01), while HMG2 significantly increased - 819 ± 34 vs 984 ± 60 pg/mL (P<0.01). These results demonstrate that an ex vivo proteomic approach using PBMC in conditioned media can identify glucocorticoid-responsive proteins measurable in human serum.

Spatially-resolved quantification of proteins in triple negative breast cancers reveals differences in the immune microenvironment associated with prognosis

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype. Recent studies have shown that MHC class II (MHCII) expression and tumor infiltrating lymphocytes are important prognostic factors in patients with TNBC, although the relative importance of lymphocyte subsets and associated protein expression is incompletely understood. NanoString Digital Spatial Profiling (DSP) allows for spatially resolved, highly multiplexed quantification of proteins in clinical samples. In this study, we sought to determine if DSP could be used to characterize expression of MHCII and other immune related proteins in tumor epithelial versus stromal compartments of patient-derived TNBCs (N = 10) using a panel of 39 markers. We confirmed that a subset of TNBCs have elevated expression of HLA-DR in tumor epithelial cells; HLA-DR expression was also significantly higher in the tumors of patients with long-term disease-free survival when compared to patients that relapsed. HLA-DR expression in the epithelial compartment was correlated with high expression of CD4 and ICOS in the stromal compartment of the same tumors. We also identified candidate protein biomarkers with significant differential expression between patients that relapsed versus those that did not. In conclusion, DSP is a powerful method that allows for quantification of proteins in the immune microenvironment of TNBCs.

Different CSF protein profiles in amyotrophic lateral sclerosis and frontotemporal dementia with C9orf72 hexanucleotide repeat expansion

ObjectivesThe hexanucleotide repeat expansion in the C9orf72 gene is the most common mutation associated with amyotrophic lateral sclerosis (C9-ALS) and frontotemporal dementia (C9-FTD). Until now, it is unknown which factors...

Proteomics Analysis of Brain Tissue in a Rat Model of Ischemic Stroke in the Acute Phase.

Background: Stroke is a leading health issue, with high morbidity and mortality rates worldwide. Of all strokes, approximately 80% of cases are ischemic stroke (IS). However, the underlying mechanisms of the occurrence of acute IS remain poorly understood because of heterogeneous and multiple factors. More potential biomarkers are urgently needed to reveal the deeper pathogenesis of IS.Methods: We identified potential biomarkers in rat brain tissues of IS using an iTRAQ labeling approach coupled with LC-MS/MS. Furthermore, bioinformatrics analyses including GO, KEGG, DAVID, and Cytoscape were used to present proteomic profiles and to explore the disease mechanisms. Additionally, Western blotting for target proteins was conducted for further verification.Results: We identified 4,578 proteins using the iTRAQ-based proteomics method. Of these proteins, 282 differentiated proteins, comprising 73 upregulated and 209 downregulated proteins, were observed. Further bioinformatics analysis suggested that the candidate proteins were mainly involved in energy liberation, intracellular protein transport, and synaptic plasticity regulation during the acute period. KEGG pathway enrichment analysis indicated a series of representative pathological pathways, including energy metabolite, long-term potentiation (LTP), and neurodegenerative disease-related pathways. Moreover, Western blotting confirmed the associated candidate proteins, which refer to oxidative responses and synaptic plasticity.Conclusions: Our findings highlight the identification of candidate protein biomarkers and provide insight into the biological processes involved in acute IS.

Diagnostic and prognostic values of PBMC proteins in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which there are no validated biomarkers. Previous exploratory studies have identified a panel of candidate protein biomarkers in peripheral blood mononuclear cells (PBMCs) that include peptidyl-prolyl cis-trans isomerase A (PPIA), heat shock cognate protein 71 kDa (HSC70), heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2B1) and TDP-43. It has also been found that PPIA plays a key role in the assembly and dynamics of ribonucleoprotein (RNP) complexes and interacts with TDP-43. Its absence accelerates disease progression in a SOD1 mouse model of ALS, and low levels of PPIA in PBMCs are associated with early-onset ALS. However, the diagnostic and prognostic values of PPIA and the other candidate protein biomarkers have not been established. We analyzed the PBMC proteins in a well-characterized cohort of ALS patients (n=93), healthy individuals (n=104) and disease controls (n=111). We used a highly controlled sample processing procedure that implies two-step differential detergent fractionation. We found that the levels of the selected PBMC proteins in the soluble and insoluble fraction, combined, have a high discriminatory power for distinguishing ALS from controls, with PPIA, hnRNPA2B1 and TDP-43 being the proteins most closely associated with ALS. We also found a shift toward increased protein partitioning in the insoluble fraction in ALS and this correlated with a worse disease phenotype. In particular, low PPIA soluble levels were associated with six months earlier death. In conclusion, PPIA is a disease modifier with prognostic potential. PBMC proteins indicative of alterations in protein and RNA homeostasis are promising biomarkers of ALS, for diagnosis, prognosis and patient stratification.

Alteration of retinal metabolism and oxidative stress may implicate myopic eye growth: Evidence from discovery and targeted proteomics in an animal model

Myopia, the most common cause of impaired vision, may induce sight- threatening diseases or ocular complications due to axial elongation. The exact mechanisms underlying myopia development have received much attention and understanding of these is necessary for clinical prevention or therapeutics. In this study, quantitative proteomics using Isotope Coded Protein Label (ICPL) was applied to identify differentially regulated proteins in the retinas of myopic chicks and, from their presence, infer the possible pathogenesis of excessive ocular elongation. Newly hatched white leghorn chicks (n = 15) wore -10D and + 10D lenses bilaterally for 3 and 7 days, respectively, to develop progressive lens-induced myopia (LIM) and hyperopia (LIH). Retinal proteins were quantified with nano-liquid chromatography electrospray ionization coupled with tandem mass spectrometry (nanoLC-ESI-MS/MS). Bioinformatics analysis of differentially regulated proteins revealed that the majority originated from the cytoplasmic region and were related to various metabolic, glycolytic, or oxidative processes. The fold changes of four proteins of interest (vimentin, apolipoprotein A1, interphotoreceptor retinoid binding protein, and glutathione S-transferase) were further confirmed by a novel high-resolution multiple reaction monitoring mass spectrometry (MRM-HR) using a label-free approach. SignificanceDiscovery of effective protein biomarkers of myopia has been extensively studied to inhibit myopia progression. This study first applied lens-induced hyperopia and myopia in the same chick to maximize the inter-ocular differences, aiming to discover more protein biomarker candidates. The findings provided new evidence that myopia was metabolism related, accompanied by altered energy generation and oxidative stress at retinal protein levels. The results in the retina were also compared to our previous study in vitreous using ICPL quantitative technology. We have now presented the protein changes in these two adjacent tissues, which may provide extra information of protein changes during ocular growth in myopia.

Protein biomarkers for incident deep venous thrombosis in critically ill adolescents: An exploratory study.

There are no tests to identify critically ill children at high risk of deep venous thrombosis (DVT). In this exploratory study, we aimed to identify proteins that are associated with incident DVT in critically ill adolescents. Plasma samples were obtained from critically ill adolescents within 24hours after initiation of cardiopulmonary support. The adolescents were followed with ultrasound to detect the development of DVT of the lower extremity and clinically for bleeding. Thrombin-antithrombin complex and prothrombin fragment 1+2 were measured using immunosorbent assays, whereas procoagulation and anticoagulation factors were measured using multiplex assays. Plasma samples were also analyzed using SOMAscan, an aptamer-based capture assay. The associations between DVT and the log-transformed level of the proteins were assessed using logistic regression adjusting for the presence of femoral venous catheter and severity of illness. Associations were expressed as odds ratio (OR) for every log-fold increase in level of the protein with 95% confidence interval (CI). Plasma from 59 critically ill adolescents, of whom 9 developed incident DVT, was analyzed. The median age of the adolescents was 15.1 years (interquartile range, 14.0-16.7 years). Higher levels of thrombin-antithrombin complex (OR: 31.54; 95% CI: 2.09-475.92) and lower levels of factor XIII (OR: 0.03; 95% CI: 0.002-0.44) were associated with DVT. CD36, MIC-1, and EpoR were marginally associated with DVT. Only factor XIII was associated with clinically relevant bleeding (OR: 0.27; 95% CI: 0.08-0.97). We identified candidate protein biomarkers for incident DVT. We plan to validate our findings in adequately powered studies.

Exosome Biomarkers Revolutionize Preclinical Diagnosis of Neurodegenerative Diseases and Assessment of Treatment Responses in Clinical Trials.

Alzheimer's disease and other neurodegenerative diseases have long preclinical phases with active and progressively irreversible pathology. Therefore, biomarkers are essential for identifying patients early in the course of these diseases, when they may benefit the most from disease-modifying interventions. A limitation of biomarkers measured in the soluble phase of blood is their tenuous link to brain pathology. A new approach to biomarker discovery that addresses this limitation is deriving extracellular vesicles (EVs) enriched for neuronal and astrocytic origin from peripheral blood. EVs are membranous particles (subdivided into smaller exosomes and larger microvesicles) that are shed by all cells and found in all biofluids. Neuronal and astrocytic EVs have been implicated in the pathogenesis of several neurodegenerative diseases. Given their origin, neuronal and astrocytic enriched EVs harvested from blood can be used to interrogate brain pathologic processes previously inaccessible in vivo. In a long series of case control studies based on these EV subpopulations, we have identified candidate protein biomarkers for Alzheimer's disease and other neurodegenerative diseases. In GeNeDis 2018, an update of these studies and results from a validation study of these biomarkers in preclinical Alzheimer's disease will be presented. In addition, we will present results from studies demonstrating EV biomarker responses to experimental interventions. EV-based biomarkers are a valuable new tool that will enable researchers to test hypotheses in proof of concept studies with carefully selected participants at the preclinical phase, spearheading therapeutic discovery in neurodegenerative disease.