Search

Intrahepatic cholangiocarcinoma (iCCA) presents a challenging diagnosis due to its nonspecific early clinical manifestations, often resulting in late-stage detection and high mortality. Diagnosing iCCA is further complicated by its limited accuracy, often necessitating multiple invasive procedures for precise identification. Despite carbohydrate antigen 19-9 (CA19-9) having been investigated and employed for iCCA diagnosis, it demonstrates modest diagnostic performance. Consequently, the identification of novel biomarkers with improved sensitivity and specificity remains an imperative yet formidable task. Autoantibodies, as early indicators of the immune response against cancer, offer a promising avenue for enhancing diagnostic accuracy. Our study aimed to identify non-invasive blood-based autoantibody biomarkers capable of distinguishing iCCA patients from healthy individuals (CTRs). We profiled autoantibodies in 26 serum samples (16 iCCAs and 10 CTRs) using protein microarrays containing 1622 functional proteins. Leveraging machine learning techniques, we identified a signature composed of three autoantibody biomarkers (NDE1, PYCR1, and VIM) in conjunction with CA19-9 for iCCA detection. This combined signature demonstrated superior diagnostic performance with an AUC of 96.9%, outperforming CA19-9 alone (AUC: 83.8%). These results suggest the potential of autoantibody biomarkers to develop a complementary non-invasive diagnostic utility for routine iCCA screening., (© 2024. The Author(s).)

Background: Lung cancer is the leading cause of cancer-related death worldwide. Surgical resection remains the definitive curative treatment for early-stage disease offering an overall 5-year survival rate of 62%. Despite careful case selection, a significant proportion of early-stage cancers relapse aggressively within the first year post-operatively. Identification of these patients is key to accurate prognostication and understanding the biology that drives early relapse might open up potential novel adjuvant therapies., Methods: We performed an unsupervised interrogation of >1600 serum-based autoantibody biomarkers using an iterative machine-learning algorithm., Results: We identified a 13 biomarker signature that was highly predictive for survivorship in post-operative early-stage lung cancer; this outperforms currently used autoantibody biomarkers in solid cancers. Our results demonstrate significantly poor survivorship in high expressers of this biomarker signature with an overall 5-year survival rate of 7.6%., Conclusions: We anticipate that the data will lead to the development of an off-the-shelf prognostic panel and further that the oncogenic relevance of the proteins recognised in the panel may be a starting point for a new adjuvant therapy., (© 2021. The Author(s).)

Objective: To study the association between insulin receptors (isoforms α and β), insulin growth factor-1 (IGF1) and serine/arginine splicing factor 1 (SRSF-1) in patients with prostate cancer (PC) and diabetes., Materials and Methods: We retrospectively analyzed data from 368 patients who underwent surgery for PC or benign prostatic hyperplasia (BPH) between 2010 and 2020 at the Department of Urology, University of Catania. Tissue microarray slides were constructed and they were stained for androgen receptor (AR), insulin receptor-α and -β, IGF1 (IGF1-R), Ki-67, and prostate specific membrane antigen (PSMA) expression using validated score., Results: The final cohort was represented by 100 patients with BPH and 268 with PC, with a median age of 68 years. We found that SRSF-1 expression was associated with AR (odds ratio [OR]: 1.66), PSMA (OR: 2.13), Ki-67 (OR: 5.99), insulin receptor (IR)-α (OR: 2.38), IR-β (OR: 3.48), IGF1-R (OR: 1.53), and microvascular density (MVD) was associated with PSMA (OR: 3.44), Ki-67 (OR: 2.23), IR-α (OR: 2.91), IR-β (OR: 3.02), IGF1-R (OR: 2.95), and SRSF-1 (OR: 2.21). In the sub cohort of PC patients, we found that SRSF-1 expression was associated with AR (OR: 2.34), Ki-67 (OR: 6.77), IR-α (OR: 2.7), and MVD (OR: 1.98). At the Kaplan-Meier analysis, SRSF-1 + patients had worse 5- and 9-year biochemical recurrence (36% and 6%) respect to SRSF-1 - (67% and 7%; p < .01) and similarly MVD + patients (44% and 7%) respect to MVD - (64% and 8%; p < .01). Restricting the analysis only in patients with PC and diabetes, we found that SRSF-1 + was associated with Ki-67 + (OR: 8.75; p < .05) and MVD + (OR: 7.5; p < .05)., Conclusions: PC exhibits widespread heterogeneity in protein expression. In particular, the expressions of the SRSF-1 protein and of the MVD are associated with a worse prognosis and in particular with a greater cell proliferation. These results, although preliminary, may offer new future scientific insights with the aim of highlighting possible genetic alterations linked to a greater expression of SRSF-1 and associated with a worse prognosis., (© 2021 The Authors. The Prostate published by Wiley Periodicals LLC.)

The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor-associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti-TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme-linked immunosorbent assay (ELISA) was used to detect the content of candidate anti-TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti-TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls (P < .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti-TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti-TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti-TAA autoantibodies could be a good tool in immunodiagnosis of OC., (© 2020 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Electrochemistry is a multidisciplinary field encompassing the study of analytes in solution for detection and quantification. For the medical field, this brings opportunities to the clinical practice of disease detection through measurements of disease biomarkers. Specifically, panels of biomarkers offer an important future option that can enable physicians' access to blood, saliva, or urine bioassays for screening diseases, as well as monitoring the progression and response to therapy. Here, we describe the simultaneous detection of eight protein cancer biomarkers in a 30-min assay by a microfluidic electrochemical immunoarray.

Introduction: Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC)., Methods: Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group., Results: A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888-0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852-0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852-0.919) in the training cohort and 0.884 (95% CI: 0.842-0.925) in the validation cohort., Discussion: Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)

Gene expression data obtained in large studies hold great promises for discovering disease signatures or subtypes through data analysis. It is also prone to technical variation, whose removal is essential to avoid spurious discoveries. Because this variation is not always known and can be confounded with biological signals, its removal is a challenging task. Here we provide a step-wise procedure and comprehensive analysis of the MINDACT microarray dataset. The MINDACT trial enrolled 6693 breast cancer patients and prospectively validated the gene expression signature MammaPrint for outcome prediction. The study also yielded a full-transcriptome microarray for each tumor. We show for the first time in such a large dataset how technical variation can be removed while retaining expected biological signals. Because of its unprecedented size, we hope the resulting adjusted dataset will be an invaluable tool to discover or test gene expression signatures and to advance our understanding of breast cancer.

Purpose: Diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin lymphoma, is a heterogeneous lymphoma with different clinical manifestations and molecular alterations, and several markers are currently being measured routinely for its diagnosis, subtyping, or prognostication by immunohistochemistry (IHC). Here, the utility of a reverse-phase-protein-array (RPPA) as a novel supportive tool to measure multiple biomarkers for DLBCL diagnosis is validated., Experimental Design: The expression of seven markers (CD5, CD10, BCL2, BCL6, MUM1, Ki-67, and C-MYC) is analyzed by RPPA and IHC using 37 DLBCL tissues, and the correlation between the two methods is determined. To normalize tumor content ratio in the tissues, the raw RPPA values of each marker are adjusted by that of CD20 or PAX-5., Results: The CD20-adjusted data for CD5, MUM1, BCL2, Ki-67, and C-MYC has better correlation with IHC results than PAX-5-adjusted data. Receiver operating characteristic (ROC) analysis reveals that CD5, MUM1, BCL2, and C-MYC exhibit a better sensitivity and specificity >0.750. Furthermore, the CD20-adjusted C-MYC value strongly correlates with that of IHC, and has a particularly high specificity (0.882)., Conclusions and Clinical Relevance: Although further investigation using a large number of DLBCL specimens needs to be conducted, these results suggest that RPPA could be applicable as a supportive tool for determining lymphoma prognosis., (© 2019 The Authors. Proteomics - Clinical Application published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The exact biological mechanism governing the radioresistant phenotype of prostate tumours at a high risk of recurrence despite the delivery of advanced radiotherapy protocols remains unclear. This study analysed the protein expression profiles of a previously generated isogenic 22Rv1 prostate cancer model of radioresistance using DigiWest multiplex protein profiling for a selection of 90 signalling proteins. Comparative analysis of the profiles identified a substantial change in the expression of 43 proteins. Differential PARP-1, AR, p53, Notch-3 and YB-1 protein levels were independently validated using Western Blotting. Pharmacological targeting of these proteins was associated with a mild but significant radiosensitisation effect at 4Gy. This study supports the clinical relevance of isogenic in vitro models of radioresistance and clarifies the molecular radiation response of prostate cancer cells.

Background: Previous studies have shown that miR-144-3p might be a potential biomarker in non-small cell lung cancer (NSCLC). Nevertheless, the comprehensive mechanism behind the effects of miR-144-3p on the origin, differentiation, and apoptosis of NSCLC, as well as the relationship between miR-144-3p and clinical parameters, has been rarely reported., Methods: We investigated the correlations between miR-144-3p expression and clinical characteristics through data collected from Gene Expression Omnibus (GEO) microarrays, the relevant literature, The Cancer Genome Atlas (TCGA), and real-time quantitative real-time PCR (RT-qPCR) analyses to determine the clinical role of miR-144-3p in NSCLC. Furthermore, we investigated the biological function of miR-144-3p by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Protein-protein interaction (PPI) network was created to identify the hub genes., Results: From the comprehensive meta-analysis, the combined SMD of miR-144-3p was - 0.95 with 95% CI of (- 1.37, - 0.52), indicating that less miR-144-3p was expressed in the NSCLC tissue than in the normal tissue. MiR-144-3p expression was significantly correlated with stage, lymph node metastasis and vascular invasion (all P <  0.05). As for the bioinformatics analyses, a total of 37 genes were chosen as the potential targets of miR-144-3p in NSCLC. These promising target genes were highly enriched in various key pathways such as the protein digestion and absorption and the thyroid hormone signaling pathways. Additionally, PPI revealed five genes-C12orf5, CEP55, E2F8, STIL, and TOP2A-as hub genes with the threshold value of 6., Conclusions: The current study validated that miR-144-3p was lowly expressed in NSCLC. More importantly, miR-144-3p might function as a latent tumor biomarker in the prognosis prediction for NSCLC. The results of bioinformatics analyses may present a new method for investigating the pathogenesis of NSCLC.

Objectives This study aimed to examine a simple, effective, time-saving, and low-cost protein microarray method for detecting serum alpha-fetoprotein (AFP) and AFP-L3 levels. Methods Serum samples from patients with hepatocellular carcinoma (HCC) (n = 33) and control subjects (n = 39) were collected and evaluated for the presence of AFP using a novel protein microarray. Glycoprotein (including AFP-L3) was enriched from crude samples by a Hotgen Biotech glycosyl capture spin column and then detected by protein microarray. An electrochemiluminescence immunoassay (ECLIA) was used to validate the measured values. Results Neither AFP levels lower than 20 ng/mL in the HCC group nor AFP levels higher than 20 ng/mL in the control group were found when tested by the ECLIA and protein microarray. The kappa test showed good consistency in the diagnostic performance of measuring serum AFP levels and the percentage of AFP-L3 in total AFP by the ECLIA and protein microarray. Protein microarray had advantages of smaller sample size required, low cost, and convenience compared with the ECLIA. Conclusion The protein microarray assay that was developed in the present study shows potential as an economic and convenient technique for detecting AFP and AFP-L3 levels in serum samples from patients with HCC.

Background: The early diagnostic of lung cancer plays an important role in the prognosis of surgical treatment among lung cancer patients. To evaluate the clinical application of multi-tumor markers protein biochip in the diagnosis of lung cancer, 12 tumor markers were detected in patients with different stages of lung cancer., Methods: Serum CA125, CA19-9, Ferritin, CA15-3, CA242, CEA, AFP, NSE, PSA, f-PSA, HGH, and β-HGH were assessed in 506 patients, with 224 patients with lung cancer (including 123 cases of adenocarcinoma, 30 squamous cell carcinoma, 54 small-cell carcinoma, and 17 non classification), 159 patients with benign lung disease and 90 healthy people control by the C-12 multiple tumor protein-chip detective system., Results: The positive rate of C-12 (77.23%) in lung cancer was significantly higher than that of benign lung disease (13.84%) and healthy people (9.76%) (P < .01). In lung cancer, the positive rate of CA199, NSE, CEA, CA242, Ferritin, f-PSA, and CA125 were significantly higher than that of benign lung disease and healthy people. In adenocarcinoma, the positive rate of CA125 (73.53%) was significantly higher than that of squamous cell carcinoma (36.67%) and small-cell carcinoma (56.62%)., Conclusion: The C-12 multiple tumor protein-chip detective system has acceptable sensitivity in the diagnostic of lung cancer., (© 2018 Wiley Periodicals, Inc.)

Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 "CRC genes." These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology., (Copyright © 2018 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Production and hosting by Elsevier B.V. All rights reserved.)

Glycan-binding proteins (GBPs) play critical roles in diverse cellular functions such as cell adhesion, signal transduction and immune response. Studies of the interaction between GBPs and glycans have been hampered by the availability of high throughput and high-content technologies. Here we report multiplex glycan bead array (MGBA) that allows simultaneous analyses of 384 samples and up to 500 glycans in a single assay. The specificity, sensitivity and reproducibility of MGBA are evaluated using 39 plant lectins, 13 recombinant anti-glycan antibodies, and mammalian GBPs. We demonstrate the utility of this platform by the analyses of natural anti-glycan IgM and IgG antibodies in 961 human serum samples and the discovery of anti-glycan antibody biomarkers for ovarian cancer. Our data indicate that the MGBA platform is particularly suited for large population-based studies that require the analyses of large numbers of samples and glycans.

The technique of surface-enhanced laser desorption/ionization time-of-flight SELDI-TOF mass spectrometry could be used to establish serum or plasma proteomic profiles in esophageal adenocarcinoma. The protein profiles in patients may be used to predict survival and monitor response to chemotherapy in patients with esophageal adenocarcinoma. Here, a protocol for sample preparation from esophageal adenocarcinoma, analysis of proteomic profiles, and collection of protein fractions for identification of significant peaks is presented.

Aim: Here, a multiplex surface-enhanced Raman scattering (SERS) based assay for simultaneous quantitation of carcinoembryonic antigen (CEA) and α-fetoprotein (AFP) was developed., Methods: SERS tags of nanostars and SERS substrates of nanobowl arrays were functionalized with labeling and capturing antibodies, respectively. In presence of antigens, SERS tags, antigens and SERS substrates formed sandwich structure., Results: The SERS-based technique showed a wide linear range from 0.5 to 100 ng/ml and detection limits were 0.41 and 0.35 ng/ml for CEA and AFP in phosphate-buffered saline buffer, respectively. Analysis results of clinical serum samples using this technique were similar to that shown in phosphate-buffered saline buffer. The LODs were 0.44 and 0.40 ng/ml for CEA and AFP, respectively. Conclusion: The precision and stability of this analysis technique were satisfactory, meanwhile, no obvious cross-reactivity could be found. What's more, it also suggested that this novel multiplex SERS-based technique could be a simple, specific, reliable, sensitive and multiplexed tool for important diagnostic and prognostic applications.

Background: Both common and rare genetic variants may contribute to risk of developing prostate cancer. Genome-wide association studies (GWASs) have identified ∼100 independent, common variants associated with prostate cancer risk. However, little is known about the association of rare variants (minor allele frequency [MAF] <1%) in the genome with prostate cancer risk., Methods: A two-stage study was used to test the association of rare, deleterious coding variants, annotated using predictive algorithms, with prostate cancer risk in Chinese men. Predicted rare, deleterious coding variants in the Illumina HumanExome-12 v1.1 beadchip were first evaluated in 1343 prostate cancer patients and 1008 controls. Significant variants were then validated in an additional 1816 prostate cancer patients and 1549 controls., Results: In the discovery stage, 14 predicted rare, deleterious coding variants were significantly associated with prostate cancer risk (P < 0.01). In the confirmation stage, Q1631H in TEX15 (rs142485241), a DNA repair gene, was significantly associated with prostate cancer risk (P = 0.0069). The estimated odds ratio (OR) of the variant in the combined analysis was 3.24 (95% Confidence Interval 1.85-6.06), P = 8.81 × 10 -5 . Additionally, rs28756990 (V741F) at MLH3 (P = 0.06) and rs2961144 (I126V) at OR2A5 (P = 0.065) were marginally associated with prostate cancer risk in the replication stage., Conclusions: Our study provided preliminary evidence that the rare variant Q1631H in DNA repair gene TEX15 is associated with prostate cancer risk. This finding complements known common prostate cancer risk-associated variants and suggests the possible role of DNA repair genes in prostate cancer development., (© 2017 Wiley Periodicals, Inc.)

Biomarkers are deemed to be potential tools in early diagnosis, therapeutic monitoring, and prognosis evaluation for cancer, with simplicity as well as economic advantages compared with computed tomography and biopsy. However, most of the current cancer biomarkers present insufficient sensitivity as well as specificity. Therefore, there is urgent requirement for the discovery of biomarkers for cancer. As one of the most exciting emerging technologies, protein array provides a versatile and robust platform in cancer proteomics research because it shows tremendous advantages of miniaturized features, high throughput, and sensitive detections in last decades. Here, we will present a relatively complete picture on the characteristics and advance of different types of protein arrays in application for biomarker discovery in cancer, and give the future perspectives in this area of research., (Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.)

Purpose: Reverse Phase Protein Array (RPPA) is a high-throughput antibody-based technique to assess cellular protein activity. The goal of this study was to assess protein marker changes by RPPA in tumor tissue from a pre-surgical metformin trial in women with operable breast cancer (BC)., Methods: In an open-label trial, metformin 1500-mg PO daily was administered prior to resection in 35 non-diabetic patients with stage 0-III BC, body mass index ≥25 kg/m 2 . For RPPA, formalin-fixed paraffin-embedded (FFPE) samples were probed with 160 antibodies. Paired and two-sample t-tests were performed (p ≤ 0.05). Multiple comparisons were adjusted for by fixing the false discovery rate at 25 %. We evaluated whether pre- and post-metformin changes of select markers by RPPA were identified by immunohistochemistry (IHC) in these samples. We also assessed for these changes by western blot in metformin-treated BC cell lines., Results: After adjusting for multiple comparisons in the 32 tumors from metformin-treated patients vs. 34 untreated historical controls, 11 proteins were significantly different between cases vs., Controls: increases in Raptor, C-Raf, Cyclin B1, Cyclin D1, TRFC, and Syk; and reductions in pMAPK pT202,Y204 , JNK pT183,pT185 , Bad pS112 , PKC.alpha pS657 , and Src pY416 . Cyclin D1 change after metformin by IHC was not observed. In cell lines, reductions in JNK pT183 and Bad pS112 were seen, with no change in Cyclin D1 or Raptor., Conclusions: These results suggest that metformin modulates apoptosis/cell cycle, cell signaling, and invasion/motility. These findings should be assessed in larger metformin trials. If confirmed, associations between these changes and BC clinical outcome should be evaluated. CLINICALTRIALS., Gov Identifier: NCT00930579.

We present here an experimental approach for exploring a new class of tumor biomarkers that are overexpressed by circulating tumor cells (CTCs) and are likely targetable in immunotherapy against tumor metastasis. Using carbohydrate microarrays, anti-tumor monoclonal antibodies (mAbs) were scanned against a large panel of carbohydrate antigens to identify potential tumor glycan markers. Subsequently, flow cytometry and fiber-optic array scanning technology (FAST) were applied to determine whether the identified targets are tumor-specific cell-surface markers and are, therefore, likely suitable for targeted immunotherapy. Finally, the tumor glycan-specific antibodies identified were validated using cancer patients' blood samples for their performance in CTC-detection and immunotyping analysis. In this article, identifying breast CTC-specific glycan markers and targeting mAbs serve as examples to illustrate this tumor biomarker discovery strategy.

Carcinoma progression is influenced by interactions between epithelial tumor cells and components of their microenvironment. In particular, cell-extracellular matrix (ECM) interactions are known to drive tumor growth, metastatic potential, and sensitivity or resistance to therapy. Yet the intrinsic complexity of ECM composition within the tumor microenvironment remains a barrier to comprehensive investigation of these interactions. We present here a high-throughput cell microarray-based approach to study the impact of defined combinations of ECM proteins on tumor cell drug responses. Using this approach, we quantitatively evaluated the effects of 55 different ECM environments representing all single and two-factor combinations of 10 ECM proteins on the responses of lung adenocarcinoma cells to a selection of cancer-relevant small molecule drugs. This drug panel consisted of an alkylating agent and five receptor tyrosine kinase inhibitors. We further determined that expression of the neuroendocrine transcription factor ASCL1, which has been previously associated with poor patient outcome when co-expressed with the RET oncogene, altered cell responses to drugs and modulated cleavage of the pro-apoptotic protein caspase-3 depending on ECM context. Our results suggest that co-expression of specific ECM proteins with known genetic drivers in lung adenocarcinoma may impact therapeutic efficacy. Furthermore, this approach could be utilized to define the molecular mechanisms by which cell-matrix interactions drive drug resistance through integration with clinical cell samples and genomics data.

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

The majority of the targeted therapeutic agents in clinical use target proteins and protein function. Although DNA and RNA analyses have been used extensively to identify novel targets and patients likely to benefit from targeted therapies, these are indirect measures of the levels and functions of most therapeutic targets. More importantly, DNA and RNA analysis is ill-suited for determining the pharmacodynamic effects of target inhibition. Assessing changes in protein levels and function is the most efficient way to evaluate the mechanisms underlying sensitivity and resistance to targeted agents. Understanding these mechanisms is necessary to identify patients likely to benefit from treatment and to develop rational drug combinations to prevent or bypass therapeutic resistance. There is an urgent need for a robust approach to assess protein levels and protein function in model systems and across patient samples. While "shot gun" mass spectrometry can provide in-depth analysis of proteins across a limited number of samples, and emerging approaches such as multiple reaction monitoring have the potential to analyze candidate markers, mass spectrometry has not entered into general use because of the high cost, requirement of extensive analysis and support, and relatively large amount of material needed for analysis. Rather, antibody-based technologies, including immunohistochemistry, radioimmunoassays, enzyme-linked immunosorbent assays (ELISAs), and more recently protein arrays, remain the most common approaches for multiplexed protein analysis. Reverse-phase protein array (RPPA) technology has emerged as a robust, sensitive, cost-effective approach to the analysis of large numbers of samples for quantitative assessment of key members of functional pathways that are affected by tumor-targeting therapeutics. The RPPA platform is a powerful approach for identifying and validating targets, classifying tumor subsets, assessing pharmacodynamics, and identifying prognostic and predictive markers, adaptive responses and rational drug combinations in model systems and patient samples. Its greatest utility has been realized through integration with other analytic platforms such as DNA sequencing, transcriptional profiling, epigenomics, mass spectrometry, and metabolomics. The power of the technology is becoming apparent through its use in pathology laboratories and integration into trial design and implementation., Competing Interests: The authors report no conflict of interest related to this manuscript., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Multiplex pharmacodynamic (PD) assays have the potential to increase sensitivity of biomarker-based reporting for new targeted agents, as well as revealing significantly more information about target and pathway activation than single-biomarker PD assays. Stringent methodology is required to ensure reliable and reproducible results. Common to all PD assays is the importance of reagent validation, assay and instrument calibration, and the determination of suitable response calibrators; however, multiplex assays, particularly those performed on paraffin specimens from tissue blocks, bring format-specific challenges adding a layer of complexity to assay development. We discuss existing multiplex approaches and the development of a multiplex immunofluorescence assay measuring DNA damage and DNA repair enzymes in response to anti-cancer therapeutics and describe how our novel method addresses known issues., Competing Interests: None, (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The increasingly complex programs of contemporary cancer therapy emphasize the need for biological indicators of both therapeutic response and adverse effects. One example is combined-modality treatment aimed at improving long-term outcome in patients with locally advanced rectal cancer, which commonly comes at the price of extended limits of patient tolerance., Methods: In a prospective study with intensified neoadjuvant treatment of rectal cancer patients, using an antibody array, the profiling of approximately 500 proteins was performed in serial serum samples collected at different stages of the treatment course., Results: The small number of proteins whose levels significantly changed after induction neoadjuvant chemotherapy (NACT) expanded substantially following the sequential chemoradiotherapy (CRT) and persisted four weeks later at treatment evaluation before pelvic surgery. Serum levels of proteins selected for validation of the experimental design, lipocalin-2 and matrix metalloproteinase-9, declined after NACT and gradually reverted to baseline values during the remaining neoadjuvant course. Of note, the greater the decline in post-NACT and post-CRT matrix metalloproteinase-9 levels, the more favorable progression-free survival. No correlation was found, however, with diarrhea scores, the clinical correlate of adverse therapeutic effects., Conclusions: Even though the findings were indicative of only tumor and not normal tissue effects, multiplex immunoassay analysis of circulating proteins in patients undergoing combined-modality therapy may in principle dissect the contribution of the individual modalities to overall systemic responses in patient outcome and tolerance., Trial Registration: ClinicalTrials.gov NCT00278694 ; registration date: January 16, 2006, retrospective to enrollment of the first 10 patients of the current report.

Colorectal cancer (CRC) is the third most common malignancy in industrialized countries. Despite the advances in diagnostics and development of new drugs, the 5-year survival remains only 60-65%. Our approach to early diagnostics of CRC is based on the determination of serological signatures with an array of hemispherical hydrogel cells containing immobilized proteins and oligosaccharides (glycochip). The compounds immobilized on the glycochip include tumor-associated glycans (SiaTn, Tn, TF, Le(C) , Le(Y) , SiaLe(A) , and Manβ1-4GlcNAcβ) and antibodies against human immunoglobulins IgG, IgA, and IgM. The glycochip detects antibodies against tumor-associated glycans in patients' sera. The simultaneous measurement of the levels of immunoglobulins enhances the diagnostic impact of the signatures. In this work, we found previously unreported increase in antibodies against oligosaccharide Manβ1-4GlcNAcβ in patients with CRC. In parallel with these experiments, we determined the levels of oncomarkers carcinoembryonic antigen (CEA), cancer antigen (CA) 19-9, CA 125, CA 15-3, human chorionic gonadotropin (HCG), and alpha-fetoprotein (AFP) using another gel-based biochip with immobilized antibodies (oncochip) developed earlier in our laboratory. In total, 69 samples from healthy donors, 33 from patients with colorectal carcinoma, and 27 from patients with inflammatory bowel diseases were studied. The use of combined signatures of antiglycan antibodies and oncomarkers provides much better predictive value than the conventional measurement of oncomarkers CEA and CA 19-9. Positive predictive value of CRC diagnoses using together glycochip and oncochip reached 95% with the sensitivity and specificity 88% and 98%, respectively. Thus, the combination of antibody profiling with detection of conventional oncomarkers proved to be a promising tool in diagnostics of CRC., (© 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Heat shock proteins (HSPs) are over-expressed in a wide range of human cancers. It results in the stimulation of the immune system and consequently in elevated concentration of anti-HSP autoantibodies. Elevated anti-HSP autoantibodies were found in breast cancer patients, and they are associated with tumor metastasis. Therefore, screening these autoantibodies could be of diagnostic and prognostic values. Protein microarrays have already demonstrated their great potential as a diagnostic tool. However, protein diversity requires optimization of the microarray fabrication to achieve high sensitivity and specificity. In this study, seven HSPs were immobilized on six different surface chemistries. After evaluation and optimization with purified antibodies of the six surface chemistries, two surfaces were selected to detect anti-HSP autoantibodies in breast cancer sera. Multiplex detection of anti-HSP autoantibodies allowed discrimination of breast cancer patients (50) from healthy controls (26) with a sensitivity of 86% and a specificity of 100%.

To develop sero-diagnostic markers for lung cancer, we generated monoclonal antibodies using lung adenocarcinoma (AC)-derived A549 cells as antigens by employing the random immunization method. Hybridoma supernatants were immunohistochemically screened for antibodies with AMeX-fixed and paraffin-embedded A549 cell preparations. Positive clones were monocloned twice through limiting dilutions. From the obtained monoclonal antibodies, one designated as KU-Lad-001 was recognized as calnexin (CANX) based on immunoprecipitation and MADLI TOF/TOF-MS analysis. To evaluate the utility of this antibody as a sero-diagnostic marker for lung cancer, we performed reverse-phase protein array analysis with samples of 195 lung cancer patients and 100 healthy controls. The CANX expression levels were significantly higher in lung cancer patients than in healthy controls (P<0.0001), and the area under the curve of ROC was 0.980, with 96.9% specificity and 99.0% sensitivity. Furthermore, since CANX was also detected in stage I disease, the serum CANX levels should be applicable markers discriminating lung cancer patients from healthy controls and possibly used in the detection of early lung cancer. To our knowledge, the present results provide evidence that CANX may be a novel sero-diagnostic marker for lung cancer., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Aims: To compare serum levels of 17 cytokines and 5 adhesion molecules in patients with newly diagnosed acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) using biochip array technology., Methods: A total of 15 AML and 15 ALL patients were studied. Serum samples were taken prior to anticancer therapy and were analyzed by biochip based immunoassays on the Evidence Investigator analyzer. This approach allows simultaneous detection of multiple analytes from a single sample. T-tests were used for statistical analysis., Results: Comparing cytokine and adhesion molecules levels in newly diagnosed AML and ALL patients, we found significant increase in AML in serum IL-4 (P < 0.0001), IL-2 (P < 0.01), IL-3 (P < 0.05), and significant decrease (P < 0.05) in serum VEGF and VCAM-1., Discussion: Our results indicate that serum profile of cytokines and adhesion molecules differs in newly diagnosed AML and ALL patients. Further studies are needed to establish if these alterations could be used as a clinically relevant biomarker for acute leukemias.

Bladder cancer (BCa) is a serious malignancy of the urinary tract worldwide and also prominent for its high rate of recurrence incorporating 50% of all treated patients. To reduce relapse of BCa, lifelong surveillance of patients is essential leading to high treatment costs. The gold standard for the diagnosis of bladder cancer is cystoscopy. It is very sensitive, but due to high costs and its invasive nature this method for routine diagnosis of bladder cancer remains questionable. Because of this and the required surveillance of patients suffering from bladder cancer, urine based markers represent a new potential field of investigation. Literature at the National Center of Biological Information (NCBI) was retrieved for a potential marker panel offering specific protein signatures and used to develop a sensitive and accurate chip assay to monitor BCa. Discovery of possible bladder cancer protein markers is compiled by extensive literature search including 1077 recently (15.01.2008-20.03.2014) published research articles. Validation of this literature is done by selection based on prior defined inclusion and exclusion criteria. A set of six putative biomarkers (VEGF, IL-8, MMP-9, MMP-7, survivin and Cyfra 21.1) was identified and a non-invasive microarray developed to be used for further clinical validation. Investigation regarding optimized urine preparation and assay development, to enhance assay sensitivity for the marker panel, was carried out. This protein based BCa chip enables the fast (within 5 h), simultaneous, easy to operate, cheap, early and non-invasive determination of BCa and is ready for clinical evaluation.

We evaluated the clinical benefits of novel predictive markers for distant recurrence with colorectal cancer using lectin microarray analysis of cell surface glycan modifications. Glycoproteins were extracted from formalin-fixed, paraffin-embedded tumor specimens and normal epithelium from 53 consecutive curatively resected stage I-III colorectal cancer cases and then subjected to lectin microarray to obtain lectin-glycan interaction (LGI) values. In addition, clinicopathological factors associated with distant recurrence were identified. LGI values that were associated with distant recurrence were validated with an additional 55 curatively resected stage II colorectal cancer cases. LGI values for Agaricus bisporus (ABA) lectin, prominent in cancer tissues, were statistically associated with distant recurrence. ABA lectin staining exhibited strikingly intense signals in the cytoplasm and apical surfaces of cancer cells, while weak staining was observed in the supranuclear regions of normal epithelium. This ABA tumor/normal LGI ratio may be a new predictive biomarker for distant recurrence of curatively resected colorectal cancer., (© 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: The clinical stage of the disease at diagnosis often determines the prognosis and survival rate of a patient with pancreatic cancer. Early symptoms of pancreatic cancer are often not obvious on imaging (ultrasound, computed tomography (CT), and so on), and when patients present with weight loss, jaundice and abdominal pain and other symptoms, they are usually already in the advanced stages of pancreatic cancer. However, the examination of combined tumor markers might improve their sensitivity or specificity in aiding diagnosis., Methods: Twelve tumor markers including AFP, CEA, NSE, CA125, CA15-3, CA242, CA19-9, PSA, f-PSA, FER, β-HCG and HGH were measured by the protein biochip detection in serum in 235 pancreatic cancer patients, 230 benign pancreatic disease patients and 240 healthy people., Results: Positive detection rates of tumor markers were: CA19-9 (49.3%), CA125 (45.1%), FER (44.2%), CA242 (42.5%), CEA (38.6%), CA15-3 (36.7%), β-HCG (29.6%), AFP (24.5%), NSE (18.2%), PSA (19.5%), f-PSA (9.4%) and HGH (8.7%) respectively. There was significant difference in CA19-9, NSE, CEA, CA242 and CA125 by multi-tumor marker protein biochip detection among patients with cancer, benign disease and healthy people (P<0.05). The positive rate of 5 tumor markers was 94.9%, and this was much higher than that of any single marker., Conclusion: The detection of CA19-9, NSE, CEA, CA242 and CA125 in the multi-tumor marker protein biochip system is helpful in the diagnosis of pancreatic cancer.

Although the search for disease biomarkers continues, the clinical return has thus far been disappointing. The complexity of the body's response to disease makes it difficult to represent this response with only a few biomarkers, particularly when many are present at low levels. An alternative to the typical reductionist biomarker paradigm is an assay we call an "immunosignature." This approach leverages the response of antibodies to disease-related changes, as well as the inherent signal amplification associated with antigen-stimulated B-cell proliferation. To perform an immunosignature assay, the antibodies in diluted blood are incubated with a microarray of thousands of random sequence peptides. The pattern of binding to these peptides is the immunosignature. Because the peptide sequences are completely random, the assay is effectively disease-agnostic, potentially providing a comprehensive diagnostic on multiple diseases simultaneously. To explore the ability of an immunosignature to detect and identify multiple diseases simultaneously, 20 samples from each of five cancer cohorts collected from multiple sites and 20 noncancer samples (120 total) were used as a training set to develop a reference immunosignature. A blinded evaluation of 120 blinded samples covering the same diseases gave 95% classification accuracy. To investigate the breadth of the approach and test sensitivity to biological diversity further, immunosignatures of >1,500 historical samples comprising 14 different diseases were examined by training with 75% of the samples and testing the remaining 25%. The average accuracy was >98%. These results demonstrate the potential power of the immunosignature approach in the accurate, simultaneous classification of disease.

Epithelial mesenchymal transition (EMT), as defined by loss of epithelial characteristics and gain of a mesenchymal phenotype, has been reported in vivo although the occurrence of events remains unclear. This study aims at exploration of EMT portraits of breast cancer (BC) with relevance to different molecular pathways, especially potential EMT triggers and BC molecular subtypes. Immunohistochemical (IHC) expression of markers/triggers of EMT was studied on a well-defined cohort of invasive non-lobular BC (n = 1,035), prepared as tissue microarrays. IHC panel of biomarkers included cadherins (cad; E-cad and N-cad), TGFβ1, PIK3CA, pAkt, and others. Reverse phase protein array (RPPA) was performed for quantitative analysis of proteins extracted from formalin fixed paraffin embedded tissues of a subset of cases from this cohort. Four combinatorial phenotypic groups representing cadherin switch were defined, including E-cad(+)/N-cad(-), E-cad(-)/N-cad(-), E-cad(+)/N-cad(+), and E-cad(-)/N-cad(+). Statistically significant association was noticed between these phenotypes and histological tumour grade, tumour type and size and NPI staging classes. The E-cad/N-cad switch occurred more frequently in the triple negative molecular class, both basal and non-basal, and in the HER2(+) subtype than in luminal BC. Significant outcome differences were observed between cadherin switch combinatorial groups regarding BCSS and DMFS (p < 0.001). Results of RPPA confirm those observed using IHC regarding differential expressions of EMT markers/triggers. EMT/cadherin switch programs in BC appear to occur in synergy with TGFβ1 and PIK3/Akt pathways activation. These data explain, at translational proteomic level, the molecular heterogeneity and in turn the varied clinical behaviour of BC molecular subtypes. RPPA is a promising high-throughput technique in monitoring subtle quantitative changes in protein expression in archival material.

It is very challenging to make a highly sensitive protein microarray because of its lack of a universal signal amplification method like PCR used in DNA microarray. The current strategies to improve the sensitivity mainly rely on a unique nanostructured substrate or enzymatically catalyzed signal amplification, of which the former requires a complicated and time-consuming fabrication process while the latter suffers from high cost and poor stability of enzymes as well as downstream biochemical reactions. In this work, an inexpensive ZnO nanomulberry (NMB) decorated glass slide is investigated as a superior substrate to nonenzymatically amplify the signal of protein microarray for sensitive detection, accomplishing a limit of detection (LOD) of 1 pg mL(-1) and a broad dynamic range of 1 pg mL(-1) to 1 μg mL(-1) to detect an important cancer biomarker, carcinoembryonic antigen (CEA) in 10% human serum. The excellent performance is attributed to ZnO NMB possessing high-density loading of capture antibody and intrinsic enhancement of fluorescence emission. The substrate preparation is simple without using any expensive equipment and complicated technique while offering advantages of low autofluorescence, versatility for various fluorophores, and excellent compatibility with existing microarray fabrication techniques. Thus, a ZnO NMB based protein microarray holds great promise for developing a low cost, sensitive, and high throughput protein assay platform for broad applications in both fundamental research and clinical diagnosis.

Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. The high mortality rate of patients with pancreatic cancer is primarily due to the difficulty of early diagnosis and a lack of effective therapies. There is an urgent need to discover novel molecular targets for early diagnosis and new therapeutic approaches to improve the clinical outcome of this deadly disease., Aim: We utilized the reverse-phase protein assay (RPPA) to identify differentially expressed biomarker proteins in tumors and matched adjacent, normal-appearing tissue samples from 15 pancreatic cancer patients., Methods: The antibody panel used for the RPPA included 130 key proteins involved in various cancer-related pathways. The paired t test was used to determine the significant differences between matched pairs, and the false discovery rate-adjusted p values were calculated to take into account the effect of multiple comparisons., Results: After correcting for multiple comparisons, we found 19 proteins that had statistically significant differences in expression between matched pairs. However, only four (AKT, β-catenin, GAB2, and PAI-1) of them met the conservative criteria (both a q value <0.05 and a fold-change of ≥3/2 or ≤2/3) to be considered differentially expressed. Overexpression of AKT, β-catenin, and GAB2 in pancreatic cancer tissues identified by RPPA has also been further confirmed by western blot analysis. Further analysis identified several significantly associated canonical pathways and overrepresented network functions., Conclusion: GAB2, a newly identified protein in pancreatic cancer, may provide additional insight into this cancer's pathogenesis. Future studies in a larger population are warranted to further confirm our results.

The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Background: The ability to accurately measure multiple proteins simultaneously in a single assay has the potential to markedly improve the efficiency of a myriad of clinical assays. Here, we tested the performance of a new, multiplex protein array platform to quantitate three bladder cancer-associated proteins in urine samples. The following analytes, interleukin 8 (IL8), matrix metallopeptidase 9 (MMP9), and vascular endothelial growth factor A (VEGFA) were monitored using Q-plex, a customized multiplex ELISA system from Quansys Biosciences, and individual target commercial ELISA kits. The performance of the two approaches was compared by evaluating the diagnostic accuracy of the biomarker assays in samples from a cohort of 73 subjects of known bladder cancer status., Results: The combination biomarker panel analyses revealed an AUROC value of 0.9476 for the Q-plex assay, and 0.9119 for the combination of the single-target ELISA assays. The Q-plex assay achieved an overall diagnostic sensitivity of 0.93 and specificity of 0.81, and the individual target ELISA assays achieved an overall sensitivity of 0.77 and specificity of 0.91., Conclusion: Based on these encouraging preliminary data, we believe that the Q-Plex technology is a viable platform that can be exploited as an efficient, highly accurate tool to quantitate multiplex panels of diagnostic proteins in biologic specimens.

Aim: Evaluation of serum levels of 17 cytokines and 5 adhesion molecules in patients with newly diagnosed acute myeloid leukemia (AML) and in healthy subjects using biochip array technology., Methods: A total of 15 AML patients and 15 healthy subjects (blood donors) were studied. Serum samples were analyzed by biochip based immunoassays on the Evidence Investigator analyzer. This approach allows multi-analytical determination from a single sample. T-tests were used for statistical analysis., Results: In newly diagnosed AML patients, we found significant increase (p < 0.01) in serum VCAM-1, ICAM-1, E-selectin, L-selectin, and significant increase (p < 0.05) in serum IL-6, IL-8. No significant differences were found in the levels of other evaluated cytokines and adhesion molecules., Conclusion: Our results indicate that serum levels of specific cytokines and adhesion molecules (VCAM-1, ICAM-1, E-selectin, L-selectin, IL-6, IL-8) are significantly altered in patients with newly diagnosed AML, showing activity of the disease. Whether these alterations could serve as a prognostic marker for AML is not known. Further studies will be needed to define the potential role of these and additional markers in the risk stratification of AML.

Purpose: To assess the value of multi-tumor marker protein chips in the diagnosis and treatment of ovarian cancer., Materials and Methods: Twelve tumor markers (CA19-9, NSE, CEA, CA242, CK19, β-HCG, AFP, SCC, c-PSA, CA125, CA724 and CA15-3) were detected by protein biochip in 220 patients with ovarian carcinomas, 205 with benign ovarian tumors and 200 healthy subjects., Results: The positivity rate was obviously higher in ovarian cancer (77.7%), than that in the benign cases (26.3%, p<0.01) and healthy subjects (4.5%, p<0.01). Serum levels of tumor markers were furthermore significantly higher in cases with lymph node metastasis (86.8%) than those without metastasis (44.7%), p<0.01., Conclusions: Multi-tumor marker protein chips provide important assistance in the diagnosis and treatment evaluation in ovarian cancers.

Purpose: To determine pretreatment serum protein levels for generally applicable measurement to predict chemoradiation treatment outcomes in patients with locally advanced squamous cell cervical carcinoma (CC)., Methods and Materials: In a screening study, measurements were conducted twice. At first, 6 serum samples from CC patients (3 with no evidence of disease [NED] and 3 with cancer-caused death [CD]) and 2 from healthy controls were tested. Next, 12 serum samples from different CC patients (8 NED, 4 CD) and 4 from healthy controls were examined. Subsequently, 28 different CC patients (18 NED, 10 CD) and 9 controls were analyzed in the validation study. Protein chips were treated with the sample sera, and the serum protein pattern was detected by surface-enhanced laser desorption and ionization-time-of-flight mass spectrometry (SELDI-TOF MS). Then, single MS-based peptide mass fingerprinting (PMF) and tandem MS (MS/MS)-based peptide/protein identification methods, were used to identify protein corresponding to the detected peak. And then, turbidimetric assay was used to measure the levels of a protein that indicated the best match with this peptide peak., Results: The same peak 8918 m/z was identified in both screening studies. Neither the screening study nor the validation study had significant differences in the appearance of this peak in the controls and NED. However, the intensity of the peak in CD was significantly lower than that of controls and NED in both pilot studies (P=.02, P=.04) and validation study (P=.01, P=.001). The protein indicated the best match with this peptide peak at 8918 m/z was identified as apolipoprotein C-II (ApoC-II) using PMF and MS/MS methods. Turbidimetric assay showed that the mean serum levels of ApoC-II tended to decrease in CD group when compared with NED group (P=.078)., Conclusion: ApoC-II could be used as a biomarker for detection in predicting and estimating the radiation treatment outcome of patients with CC., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Objective: To identify potential biomarkers of azoospermia to determine a particular stage of spermatogenetic differentiation., Design: GeneChip Human Gene 1.0 ST microarray with validation at mRNA and protein levels., Setting: Basic research laboratory., Patient(s): Men with various types of nonobstructive azoospermia (n = 18) and with normal spermatogenesis (n = 4)., Intervention(s): Obtaining 31 testicular biopsy samples., Main Outcome Measure(s): Gene expression analysis using the Affymetrix Human Gene 1.0 ST microarrays on 14 selected genes according to the highest fold change, verified with quantitative polymerase chain reaction and on independent set of microarray samples. Western blot and immunohistochemistry were additionally performed., Result(s): The comparative analysis of gene expression profiles in the infertile and control groups resulted in the selection of 4,946 differentially expressed genes. AKAP4, UBQLN3, CAPN11, GGN, SPACA4, SPATA3, and FAM71F1 were the most significantly down-regulated genes in infertile patients. Global analysis also led to identification of up-regulated genes-WBSCR28, ADCY10, TMEM225, SPATS1, FSCN3, GTSF1L, and GSG1-in men with late maturation arrest. Moreover, the results from quantitative polymerase chain reaction and Western blot largely confirmed the microarray data., Conclusion(s): The set of selected genes can be used to create a molecular diagnostic tool to determine the degree of spermatogenic impairment for men with idiopathic nonobstructive azoospermia., (Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.)

Hepatocellular carcinoma (HCC) is a malignant disease that is prevalent all around the world, especially in Asia. The combined detection of four common HCC markers, alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125) and 19-9 (CA19-9), can significantly improve the accuracy of early screening and diagnosis of this disease, which is very important for its effective treatment in a curable stage. In this article, hierarchical ZnO column arrays with core-shell structure were prepared, and specific antibodies of HCC markers were successfully conjugated onto ZnO arrays via the carbodiimide chemistry. The photoluminescence (PL) intensity of antibody-ZnO increased after HCC markers were bound. In the range of 0.5-15 ng/mL for AFP or CEA (or 0.5-15 U/mL for CA125 or CA19-9), the apparent linear relations between the PL enhancements and the concentrations of HCC markers offered simple standard curve for HCC detection in serum samples, indicating that the PL-enhanced antibody-ZnO arrays could be utilized in early clinical screening. A preliminary mechanism of PL intensity enhancement can be established based on this work.

Background: Lysine acetylation is a reversible and dynamic post-translational modification on proteins, and plays an important role in diverse biological processes. Technological limitations have so far prevented comparative quantification of lysine acetylation in different samples., Results: We developed a method to efficiently study lysine acetylation on individual proteins from complex mixtures, using antibody microarrays to capture individual proteins followed by detection with lysine acetyl antibody. By profiling both protein and acetylation variations in multiple samples using this microarray, we found cancer-associated lysine acetylation alteration on VEGF in the serum of hepatocellular carcinoma patients., Conclusion: Microarrays of lysine acetylation are highly effective for detecting acetylation, and should be useful in identifying and validating disease-associated acetylation alterations as biomarkers under both normal and pathological circumstances.