Neoadjuvant Trebananib plus Paclitaxel-based Chemotherapy for Stage II/III Breast Cancer in the Adaptively Randomized I-SPY2 Trial-Efficacy and Biomarker Discovery.

PURPOSE: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial. PATIENTS AND METHODS: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy "graduates" if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction. RESULTS: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%-99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease. CONCLUSIONS: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority >90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.

Safety and efficacy of HSP90 inhibitor ganetespib for neoadjuvant treatment of stage II/III breast cancer.

HSP90 inhibitors destabilize oncoproteins associated with cell cycle, angiogenesis, RAS-MAPK activity, histone modification, kinases and growth factors. We evaluated the HSP90-inhibitor ganetespib in combination with standard chemotherapy in patients with high-risk early-stage breast cancer. I-SPY2 is a multicenter, phase II adaptively randomized neoadjuvant (NAC) clinical trial enrolling patients with stage II-III breast cancer with tumors 2.5 cm or larger on the basis of hormone receptors (HR), HER2 and Mammaprint status. Multiple novel investigational agents plus standard chemotherapy are evaluated in parallel for the primary endpoint of pathologic complete response (pCR). Patients with HER2-negative breast cancer were eligible for randomization to ganetespib from October 2014 to October 2015. Of 233 women included in the final analysis, 140 were randomized to the standard NAC control; 93 were randomized to receive 150 mg/m2 ganetespib every 3 weeks with weekly paclitaxel over 12 weeks, followed by AC. Arms were balanced for hormone receptor status (51-52% HR-positive). Ganetespib did not graduate in any of the biomarker signatures studied before reaching maximum enrollment. Final estimated pCR rates were 26% vs. 18% HER2-negative, 38% vs. 22% HR-negative/HER2-negative, and 15% vs. 14% HR-positive/HER2-negative for ganetespib vs control, respectively. The predicted probability of success in phase 3 testing was 47% HER2-negative, 72% HR-negative/HER2-negative, and 19% HR-positive/HER2-negative. Ganetespib added to standard therapy is unlikely to yield substantially higher pCR rates in HER2-negative breast cancer compared to standard NAC, and neither HSP90 pathway nor replicative stress expression markers predicted response. HSP90 inhibitors remain of limited clinical interest in breast cancer, potentially in other clinical settings such as HER2-positive disease or in combination with anti-PD1 neoadjuvant chemotherapy in triple negative breast cancer.Trial registration: www.clinicaltrials.gov/ct2/show/NCT01042379.

I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations.

INTRODUCTION: The COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalised with severe COVID-19. The Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis (ISPY COVID-19 trial) was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation and challenges of the ISPY COVID-19 trial during the first phase of trial activity from April 2020 until December 2021. METHODS AND ANALYSIS: The ISPY COVID-19 Trial is a multicentre open-label phase 2 platform trial in the USA designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID-19 Trial network includes academic and community hospitals with significant geographical diversity across the country. Enrolled patients are randomised to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes-time to recovery and mortality. The statistical design uses a Bayesian model with 'stopping' and 'graduation' criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrols to a maximum of 125 patients per arm and is compared with concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrolment and adaptation of the trial design are ongoing. ETHICS AND DISSEMINATION: ISPY COVID-19 operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer-reviewed medical journals. TRIAL REGISTRATION NUMBER: NCT04488081.

Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial.

HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms 'graduate' in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome.

Ganitumab and metformin plus standard neoadjuvant therapy in stage 2/3 breast cancer.

I-SPY2 is an adaptively randomized phase 2 clinical trial evaluating novel agents in combination with standard-of-care paclitaxel followed by doxorubicin and cyclophosphamide in the neoadjuvant treatment of breast cancer. Ganitumab is a monoclonal antibody designed to bind and inhibit function of the type I insulin-like growth factor receptor (IGF-1R). Ganitumab was tested in combination with metformin and paclitaxel (PGM) followed by AC compared to standard-of-care alone. While pathologic complete response (pCR) rates were numerically higher in the PGM treatment arm for hormone receptor-negative, HER2-negative breast cancer (32% versus 21%), this small increase did not meet I-SPY's prespecified threshold for graduation. PGM was associated with increased hyperglycemia and elevated hemoglobin A1c (HbA1c), despite the use of metformin in combination with ganitumab. We evaluated several putative predictive biomarkers of ganitumab response (e.g., IGF-1 ligand score, IGF-1R signature, IGFBP5 expression, baseline HbA1c). None were specific predictors of response to PGM, although several signatures were associated with pCR in both arms. Any further development of anti-IGF-1R therapy will require better control of anti-IGF-1R drug-induced hyperglycemia and the development of more predictive biomarkers.

Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial.

The combination of PD-L1 inhibitor durvalumab and PARP inhibitor olaparib added to standard paclitaxel neoadjuvant chemotherapy (durvalumab/olaparib/paclitaxel [DOP]) was investigated in the phase II I-SPY2 trial of stage II/III HER2-negative breast cancer. Seventy-three participants were randomized to DOP and 299 to standard of care (paclitaxel) control. DOP increased pathologic complete response (pCR) rates in all HER2-negative (20%-37%), hormone receptor (HR)-positive/HER2-negative (14%-28%), and triple-negative breast cancer (TNBC) (27%-47%). In HR-positive/HER2-negative cancers, MammaPrint ultra-high (MP2) cases benefited selectively from DOP (pCR 64% versus 22%), no benefit was seen in MP1 cancers (pCR 9% versus 10%). Overall, 12.3% of patients in the DOP arm experienced immune-related grade 3 adverse events versus 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has superior efficacy over standard neoadjuvant chemotherapy in HER2-negative breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

PRoBE the cloud toolkit: finding the best biomarkers of drug response within a breast cancer clinical trial.

OBJECTIVES: In this paper, we discuss leveraging cloud-based platforms to collect, visualize, analyze, and share data in the context of a clinical trial. Our cloud-based infrastructure, Patient Repository of Biomolecular Entities (PRoBE), has given us the opportunity for uniform data structure, more efficient analysis of valuable data, and increased collaboration between researchers. MATERIALS AND METHODS: We utilize a multi-cloud platform to manage and analyze data generated from the clinical Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2 (I-SPY 2 TRIAL). A collaboration with the Institute for Systems Biology Cancer Gateway in the Cloud has additionally given us access to public genomic databases. Applications to I-SPY 2 data have been built using R Shiny, while leveraging Google's BigQuery tables and SQL commands for data mining. RESULTS: We highlight the implementation of PRoBE in several unique case studies including prediction of biomarkers associated with clinical response, access to the Pan-Cancer Atlas, and integrating pathology images within the cloud. Our data integration pipelines, documentation, and all codebase will be placed in a Github repository. DISCUSSION AND CONCLUSION: We are hoping to develop risk stratification diagnostics by integrating additional molecular, magnetic resonance imaging, and pathology markers into PRoBE to better predict drug response. A robust cloud infrastructure and tool set can help integrate these large datasets to make valuable predictions of response to multiple agents. For that reason, we are continuously improving PRoBE to advance the way data is stored, accessed, and analyzed in the I-SPY 2 clinical trial.

Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial.

Importance: Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed. Objective: To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial. Design, Setting, and Participants: The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016. Interventions: Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery. Main Outcomes and Measures: The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial. Results: Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years' median follow-up). Conclusions and Relevance: When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature. Trial Registration: ClinicalTrials.gov Identifier: NCT01042379.

Neutrophil-Related Gene Expression and Low-Density Granulocytes Associated With Disease Activity and Response to Treatment in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis.

OBJECTIVE: To discover biomarkers involved in the pathophysiology of antineutrophil cytoplasmic antibody-associated vasculitis (AAV) and to determine whether low-density granulocytes (LDGs) contribute to gene expression signatures in AAV. METHODS: The source of clinical data and linked biologic specimens was a randomized controlled treatment trial in AAV. RNA sequencing of whole blood from patients with AAV was performed during active disease at the baseline visit and during remission 6 months later. Gene expression was compared between patients who met versus those who did not meet the primary trial outcome of clinical remission at 6 months (responders versus nonresponders). Measurement of neutrophil-related gene expression was confirmed in peripheral blood mononuclear cells (PBMCs) to validate the findings in whole blood. A negative-selection strategy isolated LDGs from PBMC fractions. RESULTS: Differential expression between responders (n = 77) and nonresponders (n = 35) was detected in 2,346 transcripts at the baseline visit (P < 0.05). Unsupervised hierarchical clustering demonstrated a cluster of granulocyte-related genes, including myeloperoxidase (MPO) and proteinase 3 (PR3). A granulocyte multigene composite score was significantly higher in nonresponders than in responders (P < 0.01) and during active disease than during remission (P < 0.01). This signature strongly overlapped an LDG signature identified previously in lupus (false discovery rate by gene set enrichment analysis <0.01). Transcription of PR3 measured in PBMCs was associated with active disease and treatment response (P < 0.01). LDGs isolated from patients with AAV spontaneously formed neutrophil extracellular traps containing PR3 and MPO. CONCLUSION: In AAV, increased expression of a granulocyte gene signature is associated with disease activity and decreased response to treatment. The source of this signature is likely LDGs, a potentially pathogenic cell type in AAV.

Peripheral CD5+ B cells in antineutrophil cytoplasmic antibody-associated vasculitis.

OBJECTIVE: CD5+ B cells have been conceptualized as a possible surrogate for Breg cells. The aim of the present study was to determine the utility of CD5+ B cells as biomarkers in antineutrophil cytoplasmic antibody-associated vasculitis (AAV). METHODS: The absolute and relative numbers (percentages) of CD5+ B cells (explanatory variables) were measured longitudinally during 18 months in 197 patients randomized to receive either rituximab (RTX) or cyclophosphamide (CYC) followed by azathioprine (AZA) for the treatment of AAV (Rituximab in ANCA-Associated Vasculitis [RAVE] trial). Outcome variables included disease activity (status of active disease versus complete remission), responsiveness to induction therapy, disease relapse, disease severity, and, in RTX-treated patients, relapse-free survival according to the percentage of CD5+ B cells detected upon B cell repopulation. RESULTS: CD5+ B cell numbers were comparable between the treatment groups at baseline. After an initial decline, absolute CD5+ B cell numbers progressively increased in patients in the RTX treatment arm, but remained low in CYC/AZA-treated patients. In both groups, the percentage of CD5+ B cells increased during remission induction and slowly declined thereafter. During relapse, the percentage of CD5+ B cells correlated inversely with disease activity in RTX-treated patients, but not in patients who received CYC/AZA. No significant association was observed between the numbers of CD5+ B cells and induction treatment failure or disease severity. The dynamics of the CD5+ B cell compartment did not anticipate disease relapse. Following B cell repopulation, the percentage of CD5+ B cells was not predictive of time to flare in RTX-treated patients. CONCLUSION: The percentage of peripheral CD5+ B cells might reflect disease activity in RTX-treated patients. However, sole staining for CD5 as a putative surrogate marker for Breg cells did not identify a subpopulation of B cells with clear potential for meaningful clinical use. Adequate phenotyping of Breg cells is required to further explore the value of these cells as biomarkers in AAV.

High-throughput flow cytometry data normalization for clinical trials.

Flow cytometry datasets from clinical trials generate very large datasets and are usually highly standardized, focusing on endpoints that are well defined apriori. Staining variability of individual makers is not uncommon and complicates manual gating, requiring the analyst to adapt gates for each sample, which is unwieldy for large datasets. It can lead to unreliable measurements, especially if a template-gating approach is used without further correction to the gates. In this article, a computational framework is presented for normalizing the fluorescence intensity of multiple markers in specific cell populations across samples that is suitable for high-throughput processing of large clinical trial datasets. Previous approaches to normalization have been global and applied to all cells or data with debris removed. They provided no mechanism to handle specific cell subsets. This approach integrates tightly with the gating process so that normalization is performed during gating and is local to the specific cell subsets exhibiting variability. This improves peak alignment and the performance of the algorithm. The performance of this algorithm is demonstrated on two clinical trial datasets from the HIV Vaccine Trials Network (HVTN) and the Immune Tolerance Network (ITN). In the ITN data set we show that local normalization combined with template gating can account for sample-to-sample variability as effectively as manual gating. In the HVTN dataset, it is shown that local normalization mitigates false-positive vaccine response calls in an intracellular cytokine staining assay. In both datasets, local normalization performs better than global normalization. The normalization framework allows the use of template gates even in the presence of sample-to-sample staining variability, mitigates the subjectivity and bias of manual gating, and decreases the time necessary to analyze large datasets.

Efficacy of remission-induction regimens for ANCA-associated vasculitis.

BACKGROUND: The 18-month efficacy of a single course of rituximab as compared with conventional immunosuppression with cyclophosphamide followed by azathioprine in patients with severe (organ-threatening) antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis is unknown. METHODS: In a multicenter, randomized, double-blind, double-dummy, noninferiority trial, we compared rituximab (375 mg per square meter of body-surface area administered once a week for 4 weeks) followed by placebo with cyclophosphamide administered for 3 to 6 months followed by azathioprine for 12 to 15 months. The primary outcome measure was complete remission of disease by 6 months, with the remission maintained through 18 months. RESULTS: A total of 197 patients were enrolled. As reported previously, 64% of the patients in the rituximab group, as compared with 53% of the patients in the cyclophosphamide-azathioprine group, had a complete remission by 6 months. At 12 and 18 months, 48% and 39%, respectively, of the patients in the rituximab group had maintained the complete remissions, as compared with 39% and 33%, respectively, in the comparison group. Rituximab met the prespecified criteria for noninferiority (P<0.001, with a noninferiority margin of 20%). There was no significant difference between the groups in any efficacy measure, including the duration of complete remission and the frequency or severity of relapses. Among the 101 patients who had relapsing disease at baseline, rituximab was superior to conventional immunosuppression at 6 months (P=0.01) and at 12 months (P=0.009) but not at 18 months (P=0.06), at which time most patients in the rituximab group had reconstituted B cells. There was no significant between-group difference in adverse events. CONCLUSIONS: In patients with severe ANCA-associated vasculitis, a single course of rituximab was as effective as continuous conventional immunosuppressive therapy for the induction and maintenance of remissions over the course of 18 months. (Funded by the National Institute of Allergy and Infectious Diseases and others; RAVE ClinicalTrials.gov number, NCT00104299.)

Ancillary study management systems: a review of needs.

BACKGROUND: The valuable clinical data, specimens, and assay results collected during a primary clinical trial or observational study can enable researchers to answer additional, pressing questions with relatively small investments in new measurements. However, management of such follow-on, "ancillary" studies is complex. It requires coordinating across institutions, sites, repositories, and approval boards, as well as distributing, integrating, and analyzing diverse data types. General-purpose software systems that simplify the management of ancillary studies have not yet been explored in the research literature. METHODS: We have identified requirements for ancillary study management primarily as part of our ongoing work with a number of large research consortia. These organizations include the Center for HIV/AIDS Vaccine Immunology (CHAVI), the Immune Tolerance Network (ITN), the HIV Vaccine Trials Network (HVTN), the U.S. Military HIV Research Program (MHRP), and the Network for Pancreatic Organ Donors with Diabetes (nPOD). We also consulted with researchers at a range of other disease research organizations regarding their workflows and data management strategies. Lastly, to enhance breadth, we reviewed process documents for ancillary study management from other organizations. RESULTS: By exploring characteristics of ancillary studies, we identify differentiating requirements and scenarios for ancillary study management systems (ASMSs). Distinguishing characteristics of ancillary studies may include the collection of additional measurements (particularly new analyses of existing specimens); the initiation of studies by investigators unaffiliated with the original study; cross-protocol data pooling and analysis; pre-existing participant consent; and pre-existing data context and provenance. For an ASMS to address these characteristics, it would need to address both operational requirements (e.g., allocating existing specimens) and data management requirements (e.g., securely distributing and integrating primary and ancillary data). CONCLUSIONS: The scenarios and requirements we describe can help guide the development of systems that make conducting ancillary studies easier, less expensive, and less error-prone. Given the relatively consistent characteristics and challenges of ancillary study management, general-purpose ASMSs are likely to be useful to a wide range of organizations. Using the requirements identified in this paper, we are currently developing an open-source, general-purpose ASMS based on LabKey Server (http://www.labkey.org) in collaboration with CHAVI, the ITN and nPOD.

QUAliFiER: an automated pipeline for quality assessment of gated flow cytometry data.

BACKGROUND: Effective quality assessment is an important part of any high-throughput flow cytometry data analysis pipeline, especially when considering the complex designs of the typical flow experiments applied in clinical trials. Technical issues like instrument variation, problematic antibody staining, or reagent lot changes can lead to biases in the extracted cell subpopulation statistics. These biases can manifest themselves in non-obvious ways that can be difficult to detect without leveraging information about the study design or other experimental metadata. Consequently, a systematic and integrated approach to quality assessment of flow cytometry data is necessary to effectively identify technical errors that impact multiple samples over time. Gated cell populations and their statistics must be monitored within the context of the experimental run, assay, and the overall study. RESULTS: We have developed two new packages, flowWorkspace and QUAliFiER to construct a pipeline for quality assessment of gated flow cytometry data. flowWorkspace makes manually gated data accessible to BioConductor's computational flow tools by importing pre-processed and gated data from the widely used manual gating tool, FlowJo (Tree Star Inc, Ashland OR). The QUAliFiER package takes advantage of the manual gates to perform an extensive series of statistical quality assessment checks on the gated cell sub-populations while taking into account the structure of the data and the study design to monitor the consistency of population statistics across staining panels, subject, aliquots, channels, or other experimental variables. QUAliFiER implements SVG-based interactive visualization methods, allowing investigators to examine quality assessment results across different views of the data, and it has a flexible interface allowing users to tailor quality checks and outlier detection routines to suit their data analysis needs. CONCLUSION: We present a pipeline constructed from two new R packages for importing manually gated flow cytometry data and performing flexible and robust quality assessment checks. The pipeline addresses the increasing demand for tools capable of performing quality checks on large flow data sets generated in typical clinical trials. The QUAliFiER tool objectively, efficiently, and reproducibly identifies outlier samples in an automated manner by monitoring cell population statistics from gated or ungated flow data conditioned on experiment-level metadata.

Increased T cell proliferative responses to islet antigens identify clinical responders to anti-CD20 monoclonal antibody (rituximab) therapy in type 1 diabetes.

Type 1 diabetes mellitus is believed to be due to the autoimmune destruction of ß-cells by T lymphocytes, but a single course of rituximab, a monoclonal anti-CD20 B lymphocyte Ab, can attenuate C-peptide loss over the first year of disease. The effects of B cell depletion on disease-associated T cell responses have not been studied. We compare changes in lymphocyte subsets, T cell proliferative responses to disease-associated target Ags, and C-peptide levels of participants who did (responders) or did not (nonresponders) show signs of ß-cell preservation 1 y after rituximab therapy in a placebo-controlled TrialNet trial. Rituximab decreased B lymphocyte levels after four weekly doses of mAb. T cell proliferative responses to diabetes-associated Ags were present at baseline in 75% of anti-CD20- and 82% of placebo-treated subjects and were not different over time. However, in rituximab-treated subjects with significant C-peptide preservation at 6 mo (58%), the proliferative responses to diabetes-associated total (p = 0.032), islet-specific (p = 0.048), and neuronal autoantigens (p = 0.005) increased over the 12-mo observation period. This relationship was not seen in placebo-treated patients. We conclude that in patients with type 1 diabetes mellitus, anti-B cell mAb causes increased proliferative responses to diabetes Ags and attenuated ß-cell loss. The way in which these responses affect the disease course remains unknown.

Identification of a B cell signature associated with renal transplant tolerance in humans.

Establishing long-term allograft acceptance without the requirement for continuous immunosuppression, a condition known as allograft tolerance, is a highly desirable therapeutic goal in solid organ transplantation. Determining which recipients would benefit from withdrawal or minimization of immunosuppression would be greatly facilitated by biomarkers predictive of tolerance. In this study, we identified the largest reported cohort to our knowledge of tolerant renal transplant recipients, as defined by stable graft function and receiving no immunosuppression for more than 1 year, and compared their gene expression profiles and peripheral blood lymphocyte subsets with those of subjects with stable graft function who are receiving immunosuppressive drugs as well as healthy controls. In addition to being associated with clinical and phenotypic parameters, renal allograft tolerance was strongly associated with a B cell signature using several assays. Tolerant subjects showed increased expression of multiple B cell differentiation genes, and a set of just 3 of these genes distinguished tolerant from nontolerant recipients in a unique test set of samples. This B cell signature was associated with upregulation of CD20 mRNA in urine sediment cells and elevated numbers of peripheral blood naive and transitional B cells in tolerant participants compared with those receiving immunosuppression. These results point to a critical role for B cells in regulating alloimmunity and provide a candidate set of genes for wider-scale screening of renal transplant recipients.

Per-channel basis normalization methods for flow cytometry data.

Between-sample variation in high-throughput flow cytometry data poses a significant challenge for analysis of large-scale data sets, such as those derived from multicenter clinical trials. It is often hard to match biologically relevant cell populations across samples because of technical variation in sample acquisition and instrumentation differences. Thus, normalization of data is a critical step before analysis, particularly in large-scale data sets from clinical trials, where group-specific differences may be subtle and patient-to-patient variation common. We have developed two normalization methods that remove technical between-sample variation by aligning prominent features (landmarks) in the raw data on a per-channel basis. These algorithms were tested on two independent flow cytometry data sets by comparing manually gated data, either individually for each sample or using static gating templates, before and after normalization. Our results show a marked improvement in the overlap between manual and static gating when the data are normalized, thereby facilitating the use of automated analyses on large flow cytometry data sets. Such automated analyses are essential for high-throughput flow cytometry.

Power enhancement via multivariate outlier testing with gene expression arrays.

MOTIVATION: As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing. RESULTS: We applied our approach to several data resources. First, as a negative control, we found that the Affymetrix and Illumina contributions to MAQC data were free from outliers at a nominal outlier flagging rate of alpha=0.01. Second, we created a tunable framework for artificially corrupting intensity data from the Affymetrix Latin Square spike-in experiment to allow investigation of sensitivity and specificity of quality assurance (QA) criteria. Third, we applied the procedure to 507 Affymetrix microarray GeneChips processed with RNA from human peripheral blood samples. We show that exclusion of arrays by this approach substantially increases inferential power, or the ability to detect differential expression, in large clinical studies. AVAILABILITY: http://bioconductor.org/packages/2.3/bioc/html/arrayMvout.html and http://bioconductor.org/packages/2.3/bioc/html/affyContam.html affyContam (credentials: readonly/readonly)