Individual Patient Samples Research Articles

PTU-064 Increased Mucosal Expression Of Insoluble Keratins 8, 18 And 19 In Long-standing Ulcerative Colitis In Comparison To Recent-onset Ulcerative Colitis: Validation Of Mass Spectrometry Data

IntroductionIntermediate filaments (IF) are one of the main components of the human cell cytoskeleton with keratins (K) being the largest component. K8, K18 and K19 constitute the main keratins in...

Identification of druggable cancer driver genes amplified across TCGA datasets.

The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 14 cancer subtypes and identified 461 genes that were amplified in two or more datasets. The list was narrowed to 73 cancer-associated genes with potential “druggable” properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 40 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 40 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapter GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug targets and we further discuss potential novel opportunities for drug discovery efforts.

Analysis of serum haptoglobin fucosylation in hepatocellular carcinoma and liver cirrhosis of different etiologies.

We have developed herein a quantitative mass spectrometry-based approach to analyze the etiology-related alterations in fucosylation degree of serum haptoglobin in patients with liver cirrhosis and hepatocellular carcinoma (HCC). The three most common etiologies, including infection with hepatitis B virus (HBV), infection with hepatitis C virus (HCV), and heavy alcohol consumption (ALC), were investigated. Only 10 μL of serum was used in this assay in which haptoglobin was immunoprecipitated using a monoclonal antibody. The N-glycans of haptoglobin were released with PNGase F, desialylated, and permethylated prior to MALDI-QIT-TOF MS analysis. In total, N-glycan profiles derived from 104 individual patient samples were quantified (14 healthy controls, 40 cirrhosis, and 50 HCCs). A unique pattern of bifucosylated tetra-antennary glycan, with both core and antennary fucosylation, was identified in HCC patients. Quantitative analysis indicated that the increased fucosylation degree was highly associated with HBV- and ALC-related HCC patients compared to that of the corresponding cirrhosis patients. Notably, the bifucosylation degree was distinctly increased in HCC patients versus that in cirrhosis of all etiologies. The elevated bifucosylation degree of haptoglobin can discriminate early stage HCC patients from cirrhosis in each etiologic category, which may be used to provide a potential marker for early detection and to predict HCC in patients with cirrhosis.

Identification of a Subset of Human Non–Small Cell Lung Cancer Patients with High PI3Kβ and Low PTEN Expression, More Prevalent in Squamous Cell Carcinoma

The phosphoinositide 3-kinase (PI3K) pathway is a major oncogenic signaling pathway and an attractive target for therapeutic intervention. Signaling through the PI3K pathway is moderated by the tumor suppressor PTEN, which is deficient or mutated in many human cancers. Molecular characterization of the PI3K signaling network has not been well defined in lung cancer; in particular, the role of PI3Kβ and its relation to PTEN in non-small cell lung cancer NSCLC remain unclear. Antibodies directed against PI3Kβ and PTEN were validated and used to examine, by immunohistochemistry, expression in 240 NSCLC resection tissues [tissue microarray (TMA) set 1]. Preliminary observations were extended to an independent set of tissues (TMA set 2) comprising 820 NSCLC patient samples analyzed in a separate laboratory applying the same validated antibodies and staining protocols. The staining intensities for PI3Kβ and PTEN were explored and colocalization of these markers in individual tumor cores were correlated. PI3Kβ expression was elevated significantly in squamous cell carcinomas (SCC) compared with adenocarcinomas. In contrast, PTEN loss was greater in SCC than in adenocarcinoma. Detailed correlative analyses of individual patient samples revealed a significantly greater proportion of SCC in TMA set 1 with higher PI3Kβ and lower PTEN expression when compared with adenocarcinoma. These findings were reinforced following independent analyses of TMA set 2. We identify for the first time a subset of NSCLC more prevalent in SCC, with elevated expression of PI3Kβ accompanied by a reduction/loss of PTEN, for whom selective PI3Kβ inhibitors may be predicted to achieve greater clinical benefit.

A metabolic biosignature of early response to anti-tuberculosis treatment

BackgroundThe successful treatment of tuberculosis (TB) requires long-term multidrug chemotherapy. Clinical trials to evaluate new drugs and regimens for TB treatment are protracted due to the slow clearance of Mycobacterium tuberculosis (Mtb) infection and the lack of early biomarkers to predict treatment outcome. Advancements in the field of metabolomics make it possible to identify metabolic profiles that correlate with disease states or successful chemotherapy. However, proof-of-concept of this approach has not been provided for a TB-early treatment response biosignature (TB-ETRB).MethodsUrine samples collected at baseline and during treatment from 48 Ugandan and 39 South African HIV-seronegative adults with pulmonary TB were divided into discovery and qualification sets, normalized to creatinine concentration, and analyzed by liquid chromatography-mass spectrometry to identify small molecule molecular features (MFs) in individual patient samples. A biosignature that distinguished baseline and 1 month treatment samples was selected by pairwise t-test using data from two discovery sample sets. Hierarchical clustering and repeated measures analysis were applied to additional sample data to down select molecular features that behaved consistently between the two clinical sites and these were evaluated by logistic regression analysis.ResultsAnalysis of discovery samples identified 45 MFs that significantly changed in abundance at one month of treatment. Down selection using an extended set of discovery samples and qualification samples confirmed 23 MFs that consistently changed in abundance between baseline and 1, 2 and 6 months of therapy, with 12 MFs achieving statistical significance (p < 0.05). Six MFs classified the baseline and 1 month samples with an error rate of 11.8%.ConclusionsThese results define a urine based TB-early treatment response biosignature (TB-ETRB) applicable to different parts of Africa, and provide proof-of-concept for further evaluation of this technology in monitoring clinical responses to TB therapy.

Long‐term evaluation of analytical methods used in sirolimus therapeutic drug monitoring

Results of therapeutic monitoring of sirolimus blood concentrations are assay and laboratory dependent. This study compared performance over time of the IMx microparticle enzyme immunoassay (MEIA), Architect chemiluminescent microparticle immunoassay (CMIA), and liquid chromatography with mass spectrometric detection (LC/MS/MS) as part of a proficiency testing scheme. Pooled samples from sirolimus-treated patients and whole-blood samples spiked with known quantities of sirolimus were assayed monthly between 2004 and 2012. When results of pooled patient samples were compared with LC/MS/MS, the MEIA assay showed an overall mean percent bias of -2.3% ± 11.2% that, although initially positive, became increasingly negative from 2007 through 2009. The CMIA, which replaced the MEIA assay, had a mean percent bias of 21.9% ± 12.3%, remaining stable from 2007 through 2012. Similarly, for spiked samples, the MEIA showed an increasingly negative bias over time vs. LC/MS/MS, whereas CMIA maintained a stable positive bias. Based on comparison of immunoassay measurements on individual patient samples, CMIA values were more than 25% higher than MEIA values. These results highlight the importance of continued proficiency testing and regular monitoring of sirolimus assay performance. Clinicians must be aware of the methodology used and adjust target levels accordingly to avoid potential effects on efficacy and toxicity.

High variability in serum estradiol measurements in men and women

To reduce the variability in estradiol (E2) testing and to assure better patient care, standardization of E2 measurements has been recommended. This study aims to assess the accuracy and variability of E2 measurements performed by 11 routine immunological methods and 6 mass spectrometry methods using single donor serum materials and to compare the results to a reference method. The contribution of calibration bias, specificity or matrix effects, and imprecision on the overall variability of individual assays was evaluated.This study showed substantial variability in serum E2 measurements in samples from men and pre- and post-menopausal women. The mean bias across all samples, for each participant, ranged between −2.4% and 235%, with 3 participants having a mean bias of over 100%. The data suggest that calibration bias is the major contributor to the overall variability for nine assays.The analytical performances of most assays measuring E2 concentrations do not meet current needs in research and patient care. Three out of 17 assays would meet performance criteria derived from biological variability of ±12.5% bias at concentrations ⩾20pg/mL, and a maximum allowable bias of ±2.5pg/mL at concentrations <20pg/mL. The sensitivity differs highly between assays. Most assays are not able to measure E2 levels below 10pg/mL. Standardization, specifically calibration to a common standard by using panels of individual patient samples, can reduce the observed variability and improve the utility of E2 levels in clinical settings.

A Novel Automated Analysis Of Flow Cytometry Data Identifies Distinct Cell Signatures In The Immune System Of CLL Patients

IntroductionRecent developments of novel immunotherapeutic drugs have shown promising results for patients with hematologic malignancies, however, an unmet need for accurate and specific biomarkers persists. To address this need, we developed a novel integrative analysis procedure for the automated analysis of multidimensional flow cytometry data obtained from the peripheral blood of patients with chronic lymphocytic leukemia (CLL). State of the art flow cytometry analysis is accomplished by manual sequential segmentation, or gating, of cell populations based on similarities in fluorescence and light scatter characteristics through visualization of the data in one- or two-dimensional plots. This approach has a number of limitations, including the subjective nature of the gating and the inability to fully utilize the high-dimensional data. Recent efforts have produced sophisticated computational methods that overcome many of these limitations; however, these newer computational methods have not been rigorously tested in a clinical context and have focused on the rigorous and automated analysis of samples from individual patients, with substantially less effort towards the analysis of patient populations. The ultimate goal of our analysis is to develop computational approaches that will enable an identification of subsets of patients with distinct immunological markers. MethodsWe developed a novel analysis framework that facilitates automated identification of both common cell types and patient population subgroups, based on post-processing of individual sample analysis with the FLOCK program. FLOCK identifies clusters of putatively similar cells in an individual sample by multidimensional clustering of the fluorescence marker and light-scattering measurements. We developed a rigorous hierarchical clustering approach to identify common “cell signatures” across multiple patients. The cell signatures were then mapped back onto the individual patient samples and used in a second clustering that identified patient subgroups based on similar abundances of specific cell types. ResultsWe used our analytic framework to analyze multidimensional flow cytometry data (26 cell surface markers in 4 different antibody cocktails) from peripheral blood specimens of a heterogeneous group of 55 CLL patients and 13 healthy controls. Our analysis revealed distinct differences between controls and CLL patients. Analyzing the non-malignant peripheral blood cell types, we were furthermore able to differentiate between distinct clinical subpopulations of patients (e.g. identify treatment-naïve patients from those that had previously undergone chemotherapy). Conclusion/DiscussionUsing a novel integrative analysis procedure to analyze complex flow cytometry data of the peripheral blood from CLL patients, we are able to identify distinct cell type distributions. We propose that this information is a marker for the overall health/disease status of the corresponding patient, and could ultimately be used for diagnosis, prognosis, and selection of optimal treatment. In the context of multiple novel treatment options for CLL patients, such a tool will be crucial for defining individual patient prognosis, and defining an accurately matched treatment plan. Disclosures:No relevant conflicts of interest to declare.

α2Macroglobulin Fails To Compensate For Decreased Thrombin Decay In Severe Antithrombin Deficiency In Liver Cirrhosis Patients

IntroductionIn liver cirrhosis patients antithrombin (AT) decreases proportionally to the severity of the disease and in a part of the cases approaches the dangerous levels of heterozygous AT deficiency (50%) associated with thrombosis risk. Moreover, α2Macroglobulin (α2M) has been reported to increase up to fourfold. We investigated in how far the decrease of AT was compensated by the simultaneous increase of α2M. MethodsThrombin decay was characterized in plasma samples from healthy controls (n=32) and liver cirrhosis patients (n=29) by measuring AT, α2M and fibrinogen levels as well as the overall thrombin inhibitory capacity of the plasma. Functional AT, α2M and fibrinogen levels were measured with in-house chromogenic assays and the von Clauss method respectively. The overall inhibitory capacity of a plasma sample (total thrombin decay rate) was obtained by triggering thrombin generation (TG) with 50 pM tissue factor and analysis of thrombin decay after prothrombin conversion was over (t = 3 min). From the same TG curves, the rate of thrombin decay by α2M was calculated, and thrombin decay by antithrombin was calculated as the difference between total and α2M-dependent thrombin decay.In addition, we used a validated computer model to predict thrombin decay in time based on measured plasma levels of AT, α2M and fibrinogen. This allows us to predict thrombin decay under conditions that do not exist in real patient populations, such as liver cirrhosis patients with decreased AT levels, but normal α2M levels. In this way we can quantify the potential protective effect of α2M increase during liver cirrhosis. ResultsMean AT and α2M concentrations in the healthy control group were 2.01 μM (± 0.36 μM) and 3.34 μM (± 0.89 µM), respectively. In liver cirrhosis patients, the average AT level was significantly decreased (1.62 µM; p = 0.002) and the average α2M level was significantly increased (5.05 µM; p<0.001). In accordance, thrombin decay by α2M is significantly increased in liver cirrhosis patients (180% of control; p<0.001), whereas AT-dependent thrombin decay is significantly decreased (88% of control; p=0.009). The overall thrombin decay was not significantly altered in cirrhosis patients (95% of control; p=0.345), showing that α2M increase indeed compensates for AT decrease. However, in the subset of patients with AT<75% of normal, the rate of thrombin decay is significantly lower than in the control group (76%, p<0.001). Computer simulation of thrombin decay in this subset showed a similarity with the experimental curves to within the limit of experimental error. Replacing the values for the a2M concentration in individual liver cirrhosis patient samples by the average normal value reveals that the elevation in α2M levels increases the thrombin decay rate significantly (10%, p=0.016), but not enough to completely restore physiological thrombin decay rates (76%, p<0.001). ConclusionWe show that thrombin decay in liver cirrhosis is substantially reduced by the decrease of plasma antithrombin levels, and that a simultaneous increase in α2M levels counteracts this effect. In liver cirrhosis patients with moderate AT loss (<25%) α2M increase fully compensates for AT deficiency, but in patients with severe AT deficiency (<75% of normal levels) this compensation is only partial. In conclusion, the increase of the plasma α2M concentration in liver cirrhosis can be considered to be a (partial) protective mechanism. Disclosures:No relevant conflicts of interest to declare.

Population Pharmacological Profiles Of AML Treatments In Patient Samples By Automated Flow Cytometry; A Bridge To Individualized Medicine

BackgroundTo aid in the identification of effective treatments for individual patients, ex vivo assays for detecting cell death inducible by drugs for hematological malignancies have been in development for over 20 years. We have developed a novel approach incorporating 4 key innovations; incubating drugs in whole bone marrow sample without isolating leukocytes, using flow cytometry enables identification of the malignant cells selectively, an automated flow cytometry-based platform (ExviTech) decreases errors and enables full pharmacological characterization, and analyzing the data using pharmacodynamic population models. AimThe purpose of this study is to derive the ex vivo pharmacological profiles across the AML patient population of single drugs and combination treatments as a tool for individualized treatment selection. Patients and MethodsBone-marrow samples from 160 patients diagnosed with AML were sent to Vivia from 24 hospitals across Spain within 24 hrs. The plates were incubated for 48-hours prior to analysis with ExviTech, The percentage of leukemic cell death was determined via labeling with monoclonal antibodies and AnnexinV-FITC. A survival index is computed for each drug, the lower the survival index, the more effective the drug. Dose-response curves of cytarabine, idarubicin, daunorubicine, etoposide, mitoxantrone, fludarabine, clofarabine, and 6-thioguanine were measured in 160 patient samples. The added benefit of combining these drugs into 12 combination treatments was assessed by measuring their synergy in each individual patient. In 39 patients treated with CYT IDA we had clinical data of response, and then we performed a blinded interpretation of this in vitro test by an expert hematologist, to predict the clinical response based in this test result. ResultsThere was a large range of interpatient variability in the response to a single drug and even larger in the synergism between drugs. The Population Pharmacological Profiles for an individual patient is shown on the figure below. The relative drug potency in terms of their percentile ranking within the population is shown in the left panel from 0 (weakest) to 100 (most potent). Green lines represent the individual patient potency relative to the population ranking, with confidence intervals. Third column lists when a drug leaves a significant % of leukemic cells alive, potential resistant clones. The panel on the right side shows the synergism of the drug combinations treatments shown as box-plots at 10-25-75-90% to highlight their distribution. The synergism value for an individual patient in each combination is shown in green, with confidence interval as parallel dotted green lines. This representation of the Pharmacological Profile of an individual patient sample quickly identifies extreme values, when a drug or combination is very sensitive (rightward shift green lines, green boxes) or very resistant (leftward shift green lines, red boxes). This patient showed average sensitivities for most drugs though highly resistant to Clofarabine (red box) that leaves 45% alive. However this patient showed lack of synergism in multiple treatments (right, red boxes). CYT and IDA show average potencies but lack of synergism, suggesting CYT-DAU might be a more efficient treatment. These representations lead to clear guidelines in >90% samples, and based on hematologist's interpretation of these guidelines show a clinical correlation with clinical responses to CYT-IDA of 84%. ConclusionWe have developed an improved a methodology to measure the pharmacological activity of drugs and drug combinations in AML patient samples as well as modeling their pharmacological behavior. This information may be useful in selecting the optimal treatment for the individual patient, especially relapse/refractory patients in need of therapeutic alternatives. By testing the drugs used in the treatment protocols for AML directly on patient samples, a pharmacological based model has been developed to infer drug resistance or sensitivity, patient by patient.▪ Disclosures:Ballesteros:Vivia Biotech: Equity Ownership. Primo:Vivia Biotech: Employment. Hernandez-Campo:Vivia Biotech: Employment. Rojas:Vivia Biotech: Employment. Liebana:Vivia Biotech: Employment. Lopez:Vivia Biotech: Employment. Iñaki:Vivia Biotech: Consultancy. Bennett:Vivia Biotech: Employment.

Quantitative Liquid Chromatography-Mass Spectrometry-Multiple Reaction Monitoring (LC-MS-MRM) Analysis of Site-specific Glycoforms of Haptoglobin in Liver Disease

Development of liver disease is associated with the appearance of multiply fucosylated glycoforms of haptoglobin. To analyze the disease-related haptoglobin glycoforms in liver cirrhosis and hepatocellular carcinoma, we have optimized an LC-MS-multiple reaction monitoring (MRM) workflow for glycopeptide quantification. The final quantitative analysis included 24 site-specific glycoforms generated by treatment of a tryptic digest of haptoglobin with α(2-3,6,8)-neuraminidase and β(1-4)-galactosidase. The combination of LC-MS-MRM with exoglycosidase digests allowed resolution of isobaric glycoforms of the haptoglobin-T3 glycopeptide for quantification of the multiply fucosylated Lewis Y-containing glycoforms we have identified in the context of liver disease. Fourteen multiply fucosylated glycoforms of the 20 examined increased significantly in the liver disease group compared with healthy controls with an average 5-fold increase in intensity (p < 0.05). At the same time, two tri-antennary glycoforms without fucoses did not increase in the liver disease group, and two tetra-antennary glycoforms without fucoses showed a marginal increase (at most 40%) in intensity. Our analysis of 30 individual patient samples (10 healthy controls, 10 cirrhosis patients, and 10 hepatocellular carcinoma patients) showed that these glycoforms were substantially increased in a small subgroup of liver disease patients but did not significantly differ between the groups of hepatocellular carcinoma and cirrhosis patients. The tri- and tetra-antennary singly fucosylated glycoforms are associated with a MELD score and low platelet counts (p < 0.05). The exoglycosidase-assisted LC-MS-MRM workflow, optimized for the quantification of fucosylated glycoforms of haptoglobin, can be used for quantification of these glycoforms on other glycopeptides with appropriate analytical behavior.

Abstract LB-283: Prognostic significance of BRMS1 promoter methylation in operable breast cancer.

Abstract Introduction: Breast Cancer Metastasis Suppressor-1 (BRMS1) encodes a predominantly nuclear protein that differentially regulates expression of multiple genes, leading to suppression of metastasis without affecting orthotopic tumor growth. We examined the clinical relevance of BRMS1 promoter methylation in early breast cancer. Methods: We analyzed 118 formalin-fixed paraffin embedded samples: 5 pairs of breast tumors and adjacent non-cancerous tissues, 14 non-cancerous tissues, 10 benign fibroadenomas, and 84 primary breast tumors. Peripheral blood mononuclear cells were isolated from 39/84 of these patients and were fixed in cytospins. BRMS1 methylation status was investigated in all FFPE and cytospin stained circulating tumor cells using methylation specific PCR. BRMS1 expression was examined using double-immunofluorescence in isolated PBMC cytospins using anti-BRMS1 and pancytokeratin A45-B/B3 antibodies. Results: BRMS1 promoter methylation was observed in 0/19 noncancerous breast tissues, 0/10 benign fibroadenomas and 31/84(37.8%) breast tumors. During the follow-up period 27/84(32.1%) patients relapsed of which 19/84(22.6%) patients died as a consequence of disease progression. BRMS1 methylation was detected in 15/27(55.6%) patients that relapsed and in 10/19(52.6%) of patients that died. BRMS1 promoter methylation was associated with reduced disease-free interval (P=0.009) while a trend towards a reduced overall survival (OS) was also observed (P=0.071). Expression of BRMS1 on CTC was very heterogeneous: CTC with high BRMS1 expression were found in 7/13(53.8%) CTC positive samples while exclusively CTC with high BRMS1 were found in only 3 patients (23.0%). CTC with low BRMS1 expression were found in 3 patients. CTC negative for BRMS1 were found in 8/13(61.5%) patients. Exclusively CTC with low or negative BRMS1-expression were identified in 6/13(46.1%) patients. 4/13(30.8%) patients had both high and low or negative BRMS1 expression in their CTC. Conclusions: BRMS1 promoter methylation provides important prognostic information for disease free survival in early breast cancer patients. BRMS1 promoter methylation and protein expression were evaluated in primary tumors and corresponding CTC for the first time. BRMS1 expression in CTC was heterogeneous in individual patient samples. CTC expressing epithelial markers but no BRMS1 seem to define a worse prognosis group of patients. These results need to be further evaluated and validated in a larger cohort of breast cancer patients. Citation Format: Maria Chimonidou, Galatea Kallergi, Vasilis Georgoulias, Danny Welch, Evi Lianidou. Prognostic significance of BRMS1 promoter methylation in operable breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-283. doi:10.1158/1538-7445.AM2013-LB-283

Abstract 2495: Human proteome arrays for autoantibody identification in clinical cancer studies.

Abstract Early detection of cancer is a critical factor for successful treatment of cancer patients. Autoantibody signatures have value in the diagnosis and management of autoimmune disorders and may be valuable for detection of cancers. Previous groups have applied several techniques to identify cancer-specific autoimmune responses with varying degrees of success. A lack of high throughput methods to rapidly screen large numbers of patient samples and validate multiple antigens of interest is an important bottleneck in the development of autoantibodies as biomarkers for cancer diagnosis. We tested normal and cancer patient sera against protein arrays generated using a gene library capable of expressing full-length human proteins. Autoantibodies against proteins in these arrays were identified using electrochemiluminescence detection technology from MSD®, a proven technology for high-throughput, array-based measurements. This approach offers key advantages over existing array-based approaches by providing a high-throughput, sensitive, and specific assay platform, with large-scale protein arrays. This approach also enables a rapid transition from antigen discovery to clinical validation using small focused arrays on the same diagnostic platform. Protein arrays containing ∼7,000 unique (non-redundant) full-length human proteins were generated using a eukaryotic expression system. This set of proteins represents a significant portion (28-35%) of the human proteome. We estimate that greater than 80% of autoantibodies recognize unmodified epitopes on single protein antigens; the protein arrays, therefore, should be highly representative of the vast majority of autoantigens. These “proteome-scale” arrays were used to screen for cancer-specific autoantibodies in patient serum samples. Patient samples were initially screened as pools (n=5) followed by screening of individual patient samples. Initial screening was done using samples from patients with breast, lung, ovarian, prostate, colon, kidney, melanoma, and pancreatic cancers. Control samples included samples from normal patients as well as those with benign breast disease, bronchial dysplasia, benign ovarian disease, and benign prostate hyperplasia. Samples from patients with breast, lung, ovarian, and prostate cancers were sub-divided into additional groups based on clinical findings. In total we screened 22 different groups of patients. We validated this approach with the recovery of well-established tumor antigen p53 and additional antigens. Ovarian cancer yielded the highest percentage of positive autoantibody responses with 21% for p53, 8% for DEK, and 6% for GMPR2. Further evaluation of this approach using sets of molecularly classified patient samples may improve the discovery of diagnostic autoantigens in cancer, especially in combination with patient-specific protein arrays determined from tumor whole-genome sequencing data. Citation Format: John H. Kenten, Mikayla Higgins, Christopher Frye, Sudeep Kumar, John Joern, George B. Sigal, Eli N. Glezer, Jacob N. Wohlstadter. Human proteome arrays for autoantibody identification in clinical cancer studies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2495. doi:10.1158/1538-7445.AM2013-2495

Abstract 1466: Establishment of a multimarker gene panel for the characterization of circulating tumor cells in metastatic breast cancer.

Abstract Background: Improved treatment strategies for metastatic breast cancer (MBC) patients are urgently needed. Since metastatic tissue may be difficult to obtain for repeated analysis, circulating tumor cells (CTC) would be an ideal surrogate tissue to identify prognostic and predictive factors that will help to select the optimal therapeutic strategy for each individual patient. Assuming that the population of CTC contains epithelial-like, EMT (Epithelial-Mesenchymal-Transition)-like and stem cell-like cells, we established a multi-marker qPCR for the characterization of these cells.Materials and Methods: Establishment of a 16 gene qPCR panel was performed using various epithelial cancer cell lines for the markers: EpCAM, MUC1 (epithelial); PI3K, PTEN, TWIST, mTOR, KRAS, AKT2 (EMT); ALDH1, CD44, CD24L4 (stem cell); ER, PR, HER2 and EGFR (receptors) and CD45 as a leucocyte control. The prostate cancer cell line LNCAP, expressing most of these genes, was used for spiking experiments. 10 ml blood of eight healthy donors (HDs), five HDs spiked with 10 LNCAP cells and 25 MBC patients were selected for CTC using AdnaTest BreastCancerSelect (AdnaGen AG) resulting in cDNA1. Subsequently, the same sample (with removed target cells) was processed again using the same procedure resulting in cDNA2. cDNA1 and cDNA2 were gene specifically preamplified using TaqMan PreAmp Master Mix according to in house designed assays. qPCR was performed using Bio-Rad SYBR Green Mix. If the CD45 deltaCt was &amp;gt; zero, deltaCt value of a given gene was calculated as the difference between Ct (cDNA2) and Ct(cDNA1). A gene with a deltaCt &amp;gt; zero was considered positive.Results: When HDs were tested for all genes, no false positive findings were observed except for AKT2, CD24L4, CD44 (n=3 cases). All of the genes except for TWIST, ER and PR could be positively detected in samples spiked with 10 LNCAP cells. In patient samples, at least one of all studied markers was detected in 21/25 (84%) of the patients. The distribution of the markers across all patients was highly variable. However, PI3K expression was observed most frequently (n=8/21 patients), followed by the expression of CD44 (n=6/21 patients), HER2 (n=5/21 patients) and TWIST, KRAS, mTOR and EpCAM (4/21 patients), respectively. No expression was observed for MUC1, PR and CD45. In general, EMT- and stem cell-like CTC were predominantly detected. HER2 positive and epithelial-like CTC as well as CTC expressing ER, PR and EGFR were observed less frequently. Interestingly, some patients expressed only one CTC-subtype.Conclusion: Multi-gene expression profiling improves the characterization of CTC of an individual patient. Furthermore, it was possible to classify individual patient samples into CTC subtypes. Despite these promising preliminary findings, the method has to be further optimized and needs to be verified in a larger patient population. Citation Format: Maren Bredemeier, Bahriye Aktas, Rainer Kimmig, Sabine Kasimir-Bauer. Establishment of a multimarker gene panel for the characterization of circulating tumor cells in metastatic breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1466. doi:10.1158/1538-7445.AM2013-1466

Clonal diversity of recurrently mutated genes in myelodysplastic syndromes

Recent studies suggest that most cases of myelodysplastic syndrome (MDS) are clonally heterogeneous, with a founding clone and multiple subclones. It is not known whether specific gene mutations typically occur in founding clones or subclones. We screened a panel of 94 candidate genes in a cohort of 157 patients with MDS or secondary acute myeloid leukemia (sAML). This included 150 cases with samples obtained at MDS diagnosis and 15 cases with samples obtained at sAML transformation (8 were also analyzed at the MDS stage). We performed whole-genome sequencing (WGS) to define the clonal architecture in eight sAML genomes and identified the range of variant allele frequencies (VAFs) for founding clone mutations. At least one mutation or cytogenetic abnormality was detected in 83% of the 150 MDS patients and 17 genes were significantly mutated (false discovery rate ≤0.05). Individual genes and patient samples displayed a wide range of VAFs for recurrently mutated genes, indicating that no single gene is exclusively mutated in the founding clone. The VAFs of recurrently mutated genes did not fully recapitulate the clonal architecture defined by WGS, suggesting that comprehensive sequencing may be required to accurately assess the clonal status of recurrently mutated genes in MDS.

The JALA Special Issue on Novel Drug Development and Delivery

We are pleased to present this special issue of the Journal of Laboratory Automation that looks at novel drug development and delivery. How therapeutics are designed, developed, and delivered to patients is constantly evolving. With recent advances in molecular medicine and nanotechnology, this is an exceptionally exciting time in drug development. It is clear now that diseases such as cancer can benefit from more detailed diagnostic analysis of individual patient samples. This often involves a better understanding of genetic alterations and subsequent changes to other biological processes that are unique to the individual patient. In addition, with the identification of potential rare cancer stem cell populations that may escape traditional treatment, better methods for isolating, detecting, and analyzing these rare populations from cancer patients will prove integral to how medical professionals treat patients. This personal diagnostics approach has to be married with improved therapeutics that are specific to individual patients. Advances in microfluidics and nanotechnology provide the best chances at making this diagnostic/therapeutic paradigm shift a reality. In addition to improved and more detailed personal diagnostics of diseases, these fields of technology are leading to greater improvements in drug development and delivery. This includes the use of novel molecules, such as DNA/RNA, as therapeutics and the use of nanoparticles, such as lipids and carbon nanostructures, as drug-delivery platforms. As with any emerging field of medical technology, a greater understanding of the mechanisms of action and other properties of these novel drug-delivery modalities is necessary for clinical acceptance. Better techniques for analyzing drugs and drug development platforms will lead to highly optimized therapeutics and faster pathways to clinical approval. For this special issue, we have collected a set of original and review articles that we think highlight and exemplify many of these concepts as they relate to emerging technologies and approaches to drug development and drug delivery. The importance of cancer stem cells in cancer development and recurrence is becoming clearer and will need to be considered when developing novel diagnostic and therapeutic approaches to cancer. Methods that improve diagnostics through automated approaches to analyzing system biology programs such as the secretome to a variety of ways to isolate and analyze single cells are discussed here, including shear horizontal surface-acoustic-wave sensors and inductive-coupled plasma techniques.1Wetie A.G.N. Sokolowska I. Woods A.G. Wormwood K.L. Dao S. Patel S. Clarkson B.D. Darie C.C. Automated Mass Spectrometry–Based Functional Assay for the Routine Analysis of the Secretome.J. Lab. Autom. 2013; 18 (0–00)Google Scholar, 2Hao H.C. Chang H.Y. Wang T.P. Yao D.J. Detection of Cells Captured with Antigens on Shear Horizontal Surface-Acoustic-Wave Sensors.J. Lab. Autom. 2013; 18 (0–00)Google Scholar, 3Albanese A. Tsoi K.M. Chan W.C.W. Simultaneous Quantification of Cells and Nanomaterials by Inductive-Coupled Plasma Techniques.J. Lab. Autom. 2013; 18 (0–00)Google Scholar Novel approaches to drug development improve as our understanding and ability to modify genetic and protein molecules increases. This leads to work in the use and optimization of microRNAs and aptamers as new therapeutic approaches, both of which are highlighted here.4Yang J. Hao Y. Xi J. Therapeutic Application of MicroRNAs against Human Cancers.J. Lab. Autom. 2013; 18 (0–00)Google Scholar,5Na L. Reversible Regulation of Aptamer Activity with Effector-Responsive Hairpin Oligonucleotides.J. Lab. Autom. 2013; 18 (0–00)Google Scholar In particular, we feature as our cover article an original report on reversible regulated aptamer activity that may prove useful against many diseases. In addition, we have a number of review and original articles that cover some novel techniques for characterizing drug-delivery platforms. These include mathematical modeling of vesicle drug-delivery systems and fused deposition modeling for magnetic resonance imaging of solid dosage forms.6Mosley G.L. Yamanishi C.D. Kamei D.T. Mathematical Modeling of Vesicle Drug Delivery Systems 1: Vesicle Formation and Stability Along with Drug Loading and Release.J. Lab. Autom. 2013; 18 (0–00)Google Scholar, 7Ying C.T. Wang J. Lamm R.J. Kamei D.T. Mathematical Modeling of Vesicle Drug Delivery Systems 2: Targeted Vesicle Interactions with Cells, Tumors, and the Body.J. Lab. Autom. 2013; 18 (0–00)Google Scholar, 8Charest K. Mak-Jurkauskas M.L. Cinicola D. Clausen A.M. Fused Deposition Modeling Provides Solution for Magnetic Resonance Imaging of Solid Dosage Form by Advanced Design Quickly from Prototype to Final Product.J. Lab. Autom. 2013; 18 (0–00)Google Scholar This is important because as different modes of drug-delivery gain popularity as potential approaches to targeted and combinatorial drug delivery, better understanding of how drugs are loaded as well as how drug-delivery platforms deliver their payloads to cells and navigate the body will be key to optimization as well as to addressing any safety issues that may arise during the clinical approval process.

Molecular Analysis of HER2 Signaling in Human Breast Cancer by Functional Protein Pathway Activation Mapping

Targeting of the HER2 protein in human breast cancer represents a major advance in oncology but relies on measurements of total HER2 protein and not HER2 signaling network activation. We used reverse-phase protein microarrays (RPMA) to measure total and phosphorylated HER2 in the context of HER family signaling to understand correlations between phosphorylated and total levels of HER2 and downstream signaling activity. Three independent study sets, comprising a total of 415 individual patient samples from flash-frozen core biopsy samples and formalin-fixed and paraffin-embedded (FFPE) surgical and core samples, were analyzed via RPMA. The phosphorylation and total levels of the HER receptor family proteins and downstream signaling molecules were measured in laser capture microdissected (LCM) enriched tumor epithelium from 127 frozen pretreatment core biopsy samples and whole-tissue lysates from 288 FFPE samples and these results were compared with FISH and immunohistochemistry (IHC). RPMA measurements of total HER2 were highly concordant (>90% all sets) with FISH and/or IHC data, as was phosphorylation of HER2 in the FISH/IHC(+) population. Phosphorylation analysis of HER family signaling identified HER2 activation in some FISH/IHC(-) tumors and, identical to that seen with FISH/IHC(+) tumors, the HER2 activation was concordant with EGF receptor (EGFR) and HER3 phosphorylation and downstream signaling endpoint activation. Molecular profiling of HER2 signaling of a large cohort of human breast cancer specimens using a quantitative and sensitive functional pathway activation mapping technique reveals IHC(-)/FISH(-)/pHER2(+) tumors with HER2 pathway activation independent of total HER2 levels and functional signaling through HER3 and EGFR.

High-Throughput Ex Vivo Drug Sensitivity and Resistance Testing (DSRT) Integrated with Deep Genomic and Molecular Profiling Reveal New Therapy Options with Targeted Drugs in Subgroups of Relapsed Chemorefractory AML

AbstractAbstract 288 Introduction:Recent genomic analyses of acute myeloid leukemia (AML) patients have provided new information on mutations contributing to the disease onset and progression. However, the genomic changes are often complex and highly diverse from one patient to another and often not actionable in clinical care. To rapidly identify novel patient-specific therapies, we developed a high-throughput drug sensitivity and resistance testing (DSRT) platform to experimentally validate therapeutic options for individual patients with relapsed AML. By integrating the results with exome and transcriptome sequencing plus proteomic analysis, we were able to define specific drug-sensitive subgroups of patients and explore predictive biomarkers. Methods:Ex vivo DSRT was implemented for 29 samples from 16 adult AML patients at the time of relapse and chemoresistance and from 5 healthy donors. Fresh mononuclear cells from bone marrow aspirates (>50% blast count) were screened against a comprehensive collection of cytotoxic chemotherapy agents (n=103) and targeted preclinical and clinical drugs (n=100, later 170). The drugs were tested over a 10,000-fold concentration range resulting in a dose-response curve for each compound and each leukemia sample. A leukemia-specific drug sensitivity score (sDSS) was derived from the area under each dose response curve in relation to the total area, and comparing leukemia samples with normal bone marrow results. The turnaround time for the DSRT assay was 4 days. All samples also underwent deep exome (40–100×) and transcriptome sequencing to identify somatic mutations and fusion transcripts, as well as phosphoproteomic array analysis to uncover active cell signaling pathways. Results:The drug sensitivity profiles of AML patient samples differed markedly from healthy bone marrow controls, with leukemia-specific responses mostly observed for molecularly targeted drugs. Individual AML patient samples clustered into distinct subgroups based on their chemoresponse profiles, thus suggesting that the subgroups were driven by distinct signaling pathways. Similarly, compounds clustered based on the response across the samples revealing functional groups of compounds of both expected and unexpected composition. Furthermore, subsets of patient samples stood out as highly sensitive to different compounds. Specifically, dasatinib, rapalogs, MEK inhibitors, ruxolitinib, sunitinib, sorafenib, ponatinib, foretinib and quizartinib were found to be selectively active in 5 (31%), 5 (31%), 4 (25%), 4 (25%), 3 (19%), 3 (19%), 2 (13%), 2 (13%), and 1 (6%) of the AML patients ex vivo, respectively. DSRT assays of serial samples from the same patient at different stages of leukemia progression revealed patterns of resistance to the clinically applied drugs, in conjunction with evidence of dynamic changes in the clonal genomic architecture. Emergence of vulnerabilities to novel pathway inhibitors was seen at the time of drug resistance, suggesting potential combinatorial or successive cycles of drugs to achieve remissions in an increasingly chemorefractory disease.Genomic and molecular profiling of the same patient samples not only highlighted potential biomarkers reflecting the ex vivo DSRT response patterns, but also made it possible to follow in parallel the drug sensitivities and the clonal progression of the disease in serial samples from the same patients. Summary:The comprehensive analysis of drug responses by DSRT in samples from human chemorefractory AML patients revealed a complex pattern of sensitivities to distinct inhibitors. Thus, these results suggest tremendous heterogeneity in drug response patterns and underline the relevance of individual ex vivo drug testing in selecting optimal therapies for patients (personalized medicine). Together with genomic and molecular profiling, the DSRT analysis resulted in a comprehensive view of the drug response landscape and the underlying molecular changes in relapsed AML. These data can readily be translated into the clinic via biomarker-driven stratified clinical trials. [Display omitted] Disclosures:Mustjoki:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria. Kallioniemi:Roche: Research Funding; Medisapiens: Membership on an entity's Board of Directors or advisory committees. Porkka:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.

Cerebrospinal Fluid Proteome of Patients with Acute Lyme Disease

During acute Lyme disease, bacteria can disseminate to the central nervous system (CNS), leading to the development of meningitis and other neurologic symptoms. Here we have analyzed pooled cerebrospinal fluid (CSF) allowing a deep view into the proteome for patients diagnosed with early disseminated Lyme disease and CSF inflammation. Additionally, we analyzed individual patient samples and quantified differences in protein abundance employing label-free quantitative mass spectrometry-based methods. We identified 108 proteins that differ significantly in abundance in patients with acute Lyme disease from controls. Comparison between infected patients and control subjects revealed differences in proteins in the CSF associated with cell death localized to brain synapses and others that likely originate from brain parenchyma.

Abstract B72: Assessing specific biological mechanisms of drug resistance in adult and pediatric AML.

Abstract Background: Acute myeloid leukemias (AML) non-responsive to induction chemotherapy generally have poor prognoses. Understanding the biological mechanisms of drug resistance, or sensitivity, specific to each individual AML could inform biologically-based treatment selection in the salvage setting. The current study was undertaken to identify resistance mechanisms to commonly used AML drugs. Methods: Single Cell Network Profiling (SCNP) is a multiparametric flow cytometry-based assay that simultaneously measures, in a quantitative fashion and at the single cell level, both extracellular surface marker levels and changes in intracellular signaling proteins in response to extracellular modulators (Kornblau et al. Clin Cancer Res 2010). Herein we use SCNP to investigate biological mechanisms of in vitro resistance to chemotherapeutics relevant to AML treatment (Ara-C/Daunorubicin, Gemtuzumab Ozogamicin, Decitabine, Azacitidine and Clofarabine) by assessing in a quantitative fashion the induction of DNA Damage Responses (as measured by phospho-Chk2 and phospho-H2A.X levels) and apoptosis (as measured by cleaved PARP levels and loss of membrane integrity) in 6 pediatric and 6 elderly AML samples. In addition, SCF and FLT3L induced survival signaling (as measured by phospho-Akt and phospho-Erk levels) were simultaneously assessed. Results: Treatment with Ara-C/Dauno and GO revealed cross-resistance among AML samples and was associated with elevated SCF induced PI3K/Erk survival signaling. In vitro treatment of AML samples with the different genotoxic agents (Ara-C/Dauno, GO or CLO), resulted in three distinct profiles of DNA Damage and apoptosis responses: A) Samples with induced DNA Damage Response and apoptosis, B) Samples with induced DNA Damage response but no detectable apoptosis and C) Samples lacking significant induced DNA Damage response and apoptosis. In the latter group the presence of drug efflux activity in some samples, as measured by sensitization with an MDR1 (MultiDrug Resistance) inhibitor, may explain the observation. Of note, for each sample the drug response varied with the specific agent tested. Differential sensitivity among individual patient samples was also observed between treatment with two hypomethylating agents (Decitabine and Azacitidine). Additionally, distinct kinetics of DNA Damage and apoptosis were observed among drugs: genotoxic agents (CLO, Ara/Dauno, GO) induced DNA Damage prior to induction of apoptosis while hypomethylating agents (Decitabine and Azaciditine) induced DNA Damage coincident with induction of apoptosis. Conclusions: Using SCNP to dissect in vitro response to clinically used AML drugs reveals: 1) heterogeneity of individual patient biology characteristic of AML, 2) distinct resistance mechanisms present in unique samples and 3) mechanistic differences between distinct classes of agents. Studies are ongoing to assess the clinical relevance of these findings. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B72.