Gokhan Demirkan

Next-generation high-density self-assembling functional protein arrays

We developed a high-density self-assembling protein microarray, based on the nucleic acid programmable protein array (NAPPA) concept, to display thousands of proteins that are produced and captured in situ from immobilized cDNA templates. We arrayed up to 1,000 unique human cDNAs and obtained high yields of protein expression and capture with minimal variation and good reproducibility. This method will enable various experimental approaches to study protein function in high throughput.

Application of Protein Microarrays for Multiplexed Detection of Antibodies to Tumor Antigens in Breast Cancer

There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum; may exist in greater concentrations than their cognate antigens; and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies.

Copper-catalyzed azide-alkyne cycloaddition (click chemistry)-based Detection of Global Pathogen-host AMPylation on Self-assembled Human Protein Microarrays

AMPylation (adenylylation) is a recently discovered mechanism employed by infectious bacteria to regulate host cell signaling. However, despite significant effort, only a few host targets have been identified, limiting our understanding of how these pathogens exploit this mechanism to control host cells. Accordingly, we developed a novel nonradioactive AMPylation screening platform using high-density cell-free protein microarrays displaying human proteins produced by human translational machinery. We screened 10,000 unique human proteins with Vibrio parahaemolyticus VopS and Histophilus somni IbpAFic2, and identified many new AMPylation substrates. Two of these, Rac2, and Rac3, were confirmed in vivo as bona fide substrates during infection with Vibrio parahaemolyticus. We also mapped the site of AMPylation of a non-GTPase substrate, LyGDI, to threonine 51, in a region regulated by Src kinase, and demonstrated that AMPylation prevented its phosphorylation by Src. Our results greatly expanded the repertoire of potential host substrates for bacterial AMPylators, determined their recognition motif, and revealed the first pathogen-host interaction AMPylation network. This approach can be extended to identify novel substrates of AMPylators with different domains or in different species and readily adapted for other post-translational modifications.

On-Chip Protein Synthesis for Making Microarrays

Protein microarrays are a miniaturized format for displaying in close spatial density hundreds or thousands of purified proteins that provide a powerful platform for the high-throughput assay of protein function. The traditional method of producing them requires the high-throughput production and printing of proteins, a laborious method that raises concerns about the stability of the proteins and the shelf life of the arrays. A novel method of producing protein microarrays, called nucleic acid programmable protein array (NAPPA), overcomes these limitations by synthesizing proteins in situ. NAPPA entails spotting plasmid DNA encoding the relevant proteins, which are then simultaneously transcribed and translated by a cell-free system. The expressed proteins are captured and oriented at the site of expression by a capture reagent that targets a fusion protein on either the N- or C-terminus of the protein. Using a mammalian extract, NAPPA expresses and captures 1000-fold more protein per feature than conventional protein-printing arrays. Moreover, this approach minimizes concerns about protein stability and integrity, because proteins are produced just in time for assaying. NAPPA has already proven to be a robust tool for protein functional assays.

Plasma Autoantibodies Associated with Basal-like Breast Cancers

Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detecting and managing this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case–control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified 13 AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (P = 0.009) in BLBC patients. In addition, MN1 and TP53 AAbs were associated with worse survival [MN1 AAb marker HR = 2.25, 95% confidence interval (CI), 1.03–4.91; P = 0.04; TP53, HR = 2.02, 95% CI, 1.06–3.85; P = 0.03]. We found limited evidence that AAb levels differed by demographic characteristics. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. Impact: Our study identifies 13 AAb markers associated specifically with BLBC and may improve detection or management of this deadly disease. Cancer Epidemiol Biomarkers Prev; 24(9); 1332–40. ©2015 AACR.

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Identification of antibody against SNRPB, small nuclear ribonucleoprotein-associated proteins B and B', as an autoantibody marker in Crohn's disease using an immunoproteomics approach

Background Current non-invasive biomarkers for Crohns disease are limited in their utility. Progress in identifying individual autoantigens and autoantibodies in Crohns disease has been challenging due to limitations of available immunoassays. Aims Our aim was to identify autoantibodies associated with Crohns disease that may be useful in diagnosis and management using an innovative protein array technology, namely nucleic acid programmable protein arrays [NAPPA]. Methods Serum samples of 96 patients with established Crohns disease and 96 healthy controls were included and evenly split into discovery and validation sets randomly. Autoantibodies of both IgG and IgA classes were profiled against ~1900 human proteins in the discovery set on NAPPA. Autoantibodies discovered to be Crohns disease-specific were further validated in the independent validation set by enzyme-linked immunosorbent assay. Results Overall, reactivity of IgG autoantibodies was stronger than that of IgA autoantibodies; however, IgA autoantibodies showed greater differential reactivity between cases and controls. Four IgA autoantibodies against SNRPB, PRPH, PTTG1 and SNAI1 were newly identified with sensitivities above 15% at 95% specificity, among which anti-SNRPB-IgA had the highest sensitivity of 24.0%. Autoantibodies associated with specific disease subtypes were also found. Conclusions As one of the first studies to use immunoproteomics for the identification of autoantibodies in Crohns disease, our results support the utility of NAPPA in implementing future expanded studies with better coverage of the human proteome and microbial proteomes relevant to Crohns disease and identifying antibody markers that may have clinical impact in diagnosis and management.

Abstract 2441: NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein

Introduction: Development of improved cancer diagnostics and therapeutics requires detailed understanding of the genomic, transcriptomic, and proteomic profiles in the tumor microenvironment. Current technologies can excel at measuring a single analyte, but it remains challenging to simultaneously collect high-throughput DNA, RNA, and protein data from small samples. We have developed an approach that uses optical barcodes to simultaneously profile DNA, RNA, and protein from as little as 5ng DNA, 25ng RNA, and 250ng protein or just 2 5µm FFPE slides, and simplifies data analysis by generating digital counts for each analyte. Methods: The approach uses paired capture and reporter oligonucleotide probes and optical barcodes to enumerate up to 800 targets. The platform was initially developed to measure RNA, and we have adapted it to measure DNA single nucleotide variants (SNVs), proteins, and phospho-proteins. SNVs are detected by direct hybridization of sequence discriminating probes to the wild-type and mutant sequence of interest. Proteins are detected via binding of oligonucleotide-conjugated antibodies. Results: Combinations of DNA, RNA, and protein in biological and experimental contexts. SNV probes are able to detect variant alleles down to 5% abundance within a wild type population and can discriminate variants within mutation hotspots. It was >96% accurate at identifying variants from samples displaying a range of allele frequencies and DNA integrity when benchmarked against next-generation sequencing. Protein detection has been developed for cell surface, cytosolic, and nuclear proteins, as well as phospho-proteins. It was validated against flow cytometry, western blot, and mass spectrometry using cell lines with ectopic target expression and primary cells. To demonstrate concurrent measurement of DNA, RNA, and protein from a single system, BRAFWT or BRAFV600E cell lines were treated with the BRAFV600E inhibitor vemurafenib and the MEK inhibitor trametinib. We measured the allele usage at the BRAFV600 locus, as well as BRAFV600E dependent changes in mRNA expression, protein expression and protein phosphorylation in a single experiment. Conclusions: 3D Biology has several advantages over other analytical approaches. Direct, single-molecule digital counting allows detection over a broad dynamic range with high reproducibility, often over 98% concordance between technical replicates. The simultaneous interrogation of DNA, RNA, and protein maximizes the amount of data obtained from precious samples and minimizes instrumentation demands by leveraging a single detection platform. The 3D Biology approach allows holistic, digital analysis of biological samples with high specificity and precision. This technology is currently available for research use, but may also have clinical application in the future. Citation Format: Chris Lausted, Yong Zhou, Jinho Lee, Christopher Vellano, Karina A. Eterovic, Ping Song, Lin-ya Tang, Gloria Fawcett, Tae-Beom Kim, Ken Chen, Gary Geiss, Gavin Meredith, Qian Mei, Gokhan Demirkan, Dwayne Dunaway, Dae Kim, P. Martin Ross, Elizabeth Manrao, Nathan Elliott, Sarah Warren, Christina Bailey, Chung-Ying Huang, Joseph Beechem, Gordon Mills, Leroy Hood. NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2441. doi:10.1158/1538-7445.AM2017-2441

Abstract P5-02-04: Plasma autoantibodies associated with basal-like breast cancers

Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detecting and managing this deadly disease. Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed. Results: We identified a 13-AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (p=0.009) in BLBC patients. In addition, MN1 and TP53 AAbs were associated with worse survival (MN1 AAb marker HR=2.25 95%CI= 1.03-4.91 p=0.04; TP53, HR=2.02, 95%CI 1.06-3.85, p=0.03). We found limited evidence that AAb levels differed by demographic characteristics. Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection. Currently, they are also being tested in a large national blind validation trial using a well characterized independent sample set. Citation Format: Wang (Student) J, Figueroa JD, Wallstrom G, Barker K, Park JG, Demirkan G, Lissowska J, Anderson K, Qiu J, LaBaer J. Plasma autoantibodies associated with basal-like breast cancers. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-02-04.

Abstract 887: Proteome scale identification of autoantibody biomarkers in colorectal cancer

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA It is widely appreciated that early detection is the key to making inroads in the fight against cancers. Despite the availability of endoscopic screening, compliance is poor. The diagnosis of CRC is often made in advanced stages, and the consequence is a dismal 50% five year survival across all CRC. There is urgent need for biomarkers with performance that can meet the need of early diagnosis. Like most cancers, colorectal cancers (CRCs) express tumor antigens that can induce humoral immune response. The identification of the autoantibodies against tumor antigens may facilitate early diagnosis of CRC. The goal for this pilot project was to demonstrate the feasibility of discovering autoantibody biomarkers for colorectal cancer using Nucleic Acid Programmable Protein Arrays (NAPPA). Autoantibodies in serum samples collected from 40 patients with DNA mismatch repair proficient colorectal cancer who had died of their cancer within 18 months of their blood draw and from 40 age-gender matched healthy controls were profiled on NAPPA arrays with randomly selected 2000 human protein. The fact that p53, a tumor antigen that has been previously reported to be related to various cancers including CRC, was one of the top candidates based on the statistical analysis demonstrates the validity of our discovery platform. Besides p53, thirty-one candidate antigens were identified to have sensitivity greater than or equal to 25% at 95% specificity and fifty-one candidate antigens had an area under the ROC curve (AUC) equal to or greater than 0.6. Validation of the combined 83 unique genes selected based on these two different data analysis methods in an independent sample set in a blind fashion is on-going. This pilot study using late stage cancer samples demonstrates the feasibility and power of an immunoproteomics study using protein arrays. This approach may rapidly lead to identification of markers that could have relevance in monitoring disease progression as well as in early cancer detection. Citation Format: Gokhan Demirkan, Leah Soderberg, Garrick Wallstrom, Emily Szeto, Kristi Barker, Jie Wang, Joshua LaBaer, Noralane M. Lindor, Ji Qiu. Proteome scale identification of autoantibody biomarkers in colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 887. doi:10.1158/1538-7445.AM2014-887