Fred Immermann

Proteomic Changes in Cerebrospinal Fluid of Presymptomatic and Affected Persons Carrying Familial Alzheimer Disease Mutations

OBJECTIVE To identify cerebrospinal fluid (CSF) protein changes in persons who will develop familial Alzheimer disease (FAD) due to PSEN1 and APP mutations, using unbiased proteomics. DESIGN We compared proteomic profiles of CSF from individuals with FAD who were mutation carriers (MCs) and related noncarriers (NCs). Abundant proteins were depleted and samples were analyzed using liquid chromatography-electrospray ionization-mass spectrometry on a high-resolution time-of-flight instrument. Tryptic peptides were identified by tandem mass spectrometry. Proteins differing in concentration between the MCs and NCs were identified. SETTING A tertiary dementia referral center and a proteomic biomarker discovery laboratory. PARTICIPANTS Fourteen FAD MCs (mean age, 34.2 years; 10 are asymptomatic, 12 have presenilin-1 [PSEN1 ] gene mutations, and 2 have amyloid precursor protein [APP ] gene mutations) and 5 related NCs (mean age, 37.6 years). RESULTS Fifty-six proteins were identified, represented by multiple tryptic peptides showing significant differences between MCs and NCs (46 upregulated and 10 downregulated); 40 of these proteins differed when the analysis was restricted to asymptomatic individuals. Fourteen proteins have been reported in prior proteomic studies in late-onset AD, including amyloid precursor protein, transferrin, α(1)β-glycoprotein, complement components, afamin precursor, spondin 1, plasminogen, hemopexin, and neuronal pentraxin receptor. Many other proteins were unique to our study, including calsyntenin 3, AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) 4 glutamate receptor, CD99 antigen, di- N-acetyl-chitobiase, and secreted phosphoprotein 1. CONCLUSIONS We found much overlap in CSF protein changes between individuals with presymptomatic and symptomatic FAD and those with late-onset AD. Our results are consistent with inflammation and synaptic loss early in FAD and suggest new presymptomatic biomarkers of potential usefulness in drug development.

The Biomarkers of Lupus Disease Study: A Bold Approach May Mitigate Interference of Background Immunosuppressants in Clinical Trials

Molecular medicine raised expectations for strategically targeted biologic agents in systemic lupus erythematosus (SLE), but clinical trial results have been disappointing and difficult to interpret. Most studies add investigational agents to various, often effective, standard therapy immunosuppressants used at baseline, with unknown treatment interactions. Eliminating polypharmacy in trials of active lupus remains controversial. We undertook the Biomarkers of Lupus Disease study to test withdrawal of immunosuppressants as a novel approach to rendering SLE trials interpretable.

Cerebrospinal fluid (CSF) vs. plasma-based biomarkers in Alzheimer's disease (AD), mild cognitive impaired (MCI) and age-matched healthy controls (HC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort

P1-320 CEREBROSPINAL FLUID (CSF) VS. PLASMABASED BIOMARKERS IN ALZHEIMER’S DISEASE (AD), MILD COGNITIVE IMPAIRED (MCI) AND AGE-MATCHED HEALTHY CONTROLS (HC) FROM THE ALZHEIMER’S DISEASE NEUROIMAGING INITIATIVE (ADNI) COHORT William Potter, Eve H. Pickering, Fred Immermann, Max Kuhn, Judith Siuciak, Leslie Shaw, Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Foundation for NIH Biomarkers Consortium CSF Proteomics Project Team, Foundation for the National Institutes of Health, Bethesda, Maryland, United States; 2 Pfizer Worldwide Research and Development, Groton, Connecticut, United States; Foundation for the NIH, Bethesda, Maryland, United States; University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, United States; 5 ADNI, Bethesda, Maryland, United States; 6 FNIH, Bethesda, Maryland, United States.

FRI0003 Determination of interferon (IFN) signatures for sle patients may be critical for optimal treatment selection but depends on the genes chosen: report from the bold (biomarkers of lupus disease) study

Background Elevated expression of IFN pathway genes, known as the IFN signature (IS) is found in roughly half of SLE patients1. Various studies have used different IFN genes to define the IS, and different methods to assign patients to “IFN high” or “low” expression groups. Importantly a recent report from the Genentech ROSE study found higher responsiveness to an interferon antagonist in patients with lower IFN expression using a 7 gene set (G-7), suggesting that IS might inform optimal selection of treatments in the future2. Objectives As a step toward understanding the clinical relevance and molecular drivers of the IS, we used data from the BOLD study to test the difference between IS-derived patient groupings derived from different sets of IFN genes. Methods The BOLD study enrolled SLE patients with active disease (minimum SLEDAI of 6 or two BILAG B scores). 41 patients had background immune suppressives withdrawn, were given brief steroids until improvement, then followed with serial samples until disease flare. 62 additional active SLE patients were evaluated only once. RNA expression levels for 329 genes were assayed using TaqMan® Low Density Arrays. 238 SLE patient-visits were partitioned into two groups by unsupervised hierarchical clustering of the expression levels of IFN-related genes. Results Clustering was done separately for 5 gene sets, denoted B-30, P-11, M-20, G-7, and O-3. Two of the gene sets (M-20 and G-7) were 95% and 100% matched to sets used in clinical trials of IFN-inhibiting treatments. Consistent with previous reports, all of the gene sets assigned about 40-50% of visits (96 to 118 patient-visits) to an “IFN high” group characterized by IFN pathway expression that was higher than healthy volunteers. In a cross-sectional analysis using the P-11 gene set, membership in the IFN high group was associated with higher SLEDAI score than IFN low assignment (9.73 vs. 7.70, p<0.0001) and higher TNFSF13B (BLYS/BAFF) gene expression (2.4 fold increase, p=0.0005). Most of the patients followed longitudinally remained in the same group over the course of the study, despite changes of gene expression with disease improvement and flare. IFN group assignments were similar for the B-30 and P-11 gene sets, and also similar among the M-20, G-7, and O-3 gene sets, but differed more across these groups. For instance, 21 patient-visits (9%) were assigned to the IFN high group by the G-7 gene set, but placed in the IFN low group by the P-11 gene set. Conclusions The comparison of IFN group assignments for the same samples, derived using different IFN gene sets, highlights the need for more investigation of the molecular and cellular drivers of IFN gene expression in SLE blood. An optimal IFN gene set, once determined, might improve how patients are selected for targeted therapies in the future. References Baechler et al., PNAS 100(5) 2610-2615 (2003); Kalunian et al., ACR 2012 Washington D.C, Abstract 2622. Disclosure of Interest None Declared

Changes in plasma based biomarkers in Alzheimer's disease, mild cognitively impaired and aged matched normal controls from the ADNI cohort

and others recently discovered that BACE1 activity was significantly increased in sporadic AD brains and that the concentrations of both CSF BACE1 enzymatic activity and protein were significantly increased in subjects with amnestic mild cognitive impairment (MCI).We have hypothesized that by using BACE1 as a biomarker candidate in CSF, it may aid in early detection and prediction of AD in the at-risk predementia MCI stage. Lumbar punctures, however, are considered an invasive procedure. It may be difficult to obtain the sample size necessary for biomarker validation studies, or for a broad clinical screening with a diagnostic indicator. Therefore, potential biomarkers from a more accessible source, such as blood plasma, are critical for advancement. In this study,wewanted to understandwhetherBACE in the blood fromMCI andADpatients would be changed.Methods: Therewere at least 100 patients in each group. Clinically, the MCI subjects met Petersen criteria for amnestic MCI and the AD subjects met NINDS-ADRDA criteria for the diagnosis. Control group is composed by age-matched healthy individuals. We used BACE enzymatic activity assay, BACE ELISA, Ab1-x and sAPPb tomeasure BACE enzyme activity, expression levels and reaction product.Results: Both BACE enzyme activity and expression levels are significantly changed in MCI and AD patients compared to healthy agematched controls.Conclusions:To our knowledge, this is the first time blood from MCI and AD patients has been systematically examined for BACE1 functional proteins and enzyme activity, as well as the enzymatic product, sAPPb and total Ab1-x. Here, we report significant changes of BACE1 functional proteins in the blood among subjects with MCI or AD compared to age-matched cognitively normal controls. These finding are highly relevant for the improved hypothesis-driven generation of biomarkers for AD, regarding early detection and prediction, as well as for assessment of mechanisms for amyloid lowering compounds currently in phase II-III clinical trials.

Abstract 1469: Patient derived xenograft (PDX) models: improving predictability of experimental cancer therapies

Clinical development of cancer therapies is associated with attrition rates as high as 80-95%. This high attrition suggests that standard preclinical pharmacology models do not accurately reflect clinical responses. The development of more predictive preclinical models requires several considerations; the relevance of the in vivo model, the administration of test agent, and the interpretation of efficacy data. PDX are cancer models developed from the direct transfer of patient tumor tissue into immunocompromised mice. A collection of PDX models, by retaining the genetic and histologic characteristics of the patients from which they were derived, represents the complexity and heterogeneity of human cancer. To minimize the clinical attrition rates of oncology compounds, we are developing hundreds of PDX models in seven major cancer indications. The collection is being molecularly profiled by RNAseq, WES, and proteomics. Profiling has identified models with robust expression of target proteins or mutant oncogenes that are likely to respond in preclinical efficacy tests. Conversely, the PDX models may provide an understanding of resistance, for example evaluating models with good target expression that fail to respond to therapy. Patient and tumor information, if known, has been collected for each PDX model including age, sex, cancer stage and grade, diagnosis, primary or metastatic site, and prior treatments. In addition to the improvements provided by the PDX models, a preclinical paradigm shift away from treatment with maximally tolerated dose towards clinically relevant dose (CRD), taking into consideration such aspects as exposure, formulation, route and schedule, is critical when attempting to predict clinical outcome from preclinical data. Also essential is the incorporation of clinically meaningful endpoints (regression) when assessing preclinical activity. We have initiated studies on cohorts of non small cell lung and breast PDX models to predict the likely clinical efficacy of candidate compounds for clinical development and to determine the CRD for standard of care (SOC) regimens required to define the most promising Phase II/III combination therapies. Anti-tumor activities were characterized using RECIST criteria of progressive disease (PD), stable disease (SD), partial response (PR), and complete response (CR). Target expression was evaluated by RNA, proteomics and immunohistochemistry. Preliminary results demonstrate a spectrum of responses against experimental therapeutics, including Phase I ADCs and are defining the CRD required for combination treatments with SOC. Identification of the most critical parameters of PDX models predicting clinical outcome will help in validating the utility of ‘n of 1′ studies with the PDX collection, inform patient enrollment strategies, guide combination therapies, and provide insight for identifying new tumor indications. Citation Format: Edward Rosfjord, Xin Han, Danielle Leahy, Erik Upeslacis, Justin Lucas, Jonathon Golas, Andrea Hooper, Fred Immermann, Bingwen Lu, Jeremy Myers, Zhengyan Kan, James Hardwick, Eric Powell, Puja Sapra, Paul Rejto, Hans-Peter Gerber, Judy Lucas. Patient derived xenograft (PDX) models: improving predictability of experimental cancer therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1469. doi:10.1158/1538-7445.AM2015-1469

FRI0318 Comparison of lupus trial endpoints to a physician-weighted definition of improvement in the biomarkers of lupus disease (BOLD) study suggests improved discrimination using bicla (bilag based composite lupus assessment) vs sri (sle responder index)

Background The choice of composite clinical assessment tools in lupus clinical trials is expanding, but it is important to understand the differences between what these endpoints measure. The SLE Responder Index (SRI) was developed for the successful Phase III belimumab (BLISS) program which defines response as ≥ 4 (SRI-4) or 5 (SRI-5) point decrease in SLEDAI, no new BILAG A (severe disease) or 2 new B (moderate disease) organ scores plus increase in PGA of < 0.3 points (10% of scale). The best treatment corrected difference achieved with SRI-4 were 9.8% (1), and 14.4% (2) in the two phase III BLISS trials. The BICLA was tested in a Phase II study of epratuzumab (EMBLEM) with response defined by at least one grade improvement in all BILAG moderate or severe scores, no new BILAG A or 2 new B scores, no increase in SLEDAI, <10% worsening in PGA and no off-protocol treatment. Optimal treatment corrected differences in this trial was 24.8% (3). A comparison of BICLA and SRI has been reported using EMBLEM data (4), but was complicated by scoring of many 8 point features on SLEDAI which are not common in lupus. BICLA data from the BLISS studies have not been reported. Objectives To compare the SRI and BICLA to a physician-weighted definition of improvement in the BOLD study Methods The BOLD study was designed to test the impact of clinical, biologic and background treatment variables on lupus trials and scoring of 8 point SLEDAI features were rare. 41 patients entered with active disease (minimum SLEDAI of 6 or two BILAG B scores) in a single study center, then background immune suppressives were withdrawn, brief intramuscular steroids given until improvement, and patients followed until they flared. BOLD improvement was defined as either a 4 point drop in SLEDAI or one grade improvement in BILAG and required physician determination of clinically significant improvement. This allowed for simpler quantitative criteria, anchored by clinician judgment. Results At the improving visit, the mean decrease from baseline in PGA was 1.06 ± 0.38 (scale 0-3). Count of responders by SRI and BICLA are shown in the table below with McNemar’s test p-value for comparisons to the BOLD (physician-weighted) definition of improvement. Conclusions The BICLA was more likely to agree with a physician weighted definition of improvement than SRI, and less likely to score a physician designated flare visit as improvement. Differences in treatment efficacy, clinical trial design, and adjudication of trial endpoints may have accounted for the improved discrimination seen between treatment groups in the EMBLEM study (using BICLA) compared to the BLISS studies (using SRI). However, if further validated, these observations from BOLD may be helpful in optimizing the choice of clinical endpoints for future lupus trials. References Navarra SV, et al. Lancet. 2011;377:721–731. Furie R, et al. Arthritis Rheum. 2011;63:3918–3930. Wallace DJ, et al. Ann Rheum Dis 2013;00:1–8. Petri M, et al. ACR 2011; 1378. Disclosure of Interest: None Declared