Emerging concepts in biomarker discovery; the US-Japan Workshop on Immunological Molecular Markers in Oncology

Inframe insertion and splice site variants in MFGE8 associate with protection against coronary atherosclerosis

Cardiovascular diseases are the leading cause of premature death and disability worldwide, with both genetic and environmental determinants. While genome-wide association studies have identified multiple genetic loci associated with cardiovascular diseases, exact genes driving these associations remain mostly uncovered. Due to Finland’s population history, many deleterious and high-impact variants are enriched in the Finnish population giving a possibility to find genetic associations for protein-truncating variants that likely tie the association to a gene and that would not be detected elsewhere. In a large Finnish biobank study FinnGen, we identified an association between an inframe insertion rs534125149 in MFGE8 (encoding lactadherin) and protection against coronary atherosclerosis. This variant is highly enriched in Finland, and the protective association was replicated in meta-analysis of BioBank Japan and Estonian biobank. Additionally, we identified a protective association between splice acceptor variant rs201988637 in MFGE8 and coronary atherosclerosis, independent of the rs534125149, with no significant risk-increasing associations. This variant was also associated with lower pulse pressure, pointing towards a function of MFGE8 in arterial aging also in humans in addition to previous evidence in mice. In conclusion, our results suggest that inhibiting the production of lactadherin could lower the risk for coronary heart disease substantially.

A genome-wide association study identifies MFGE8 as protective against coronary atherosclerosis in European and East Asian populations.

Biomarkers of metabolic disorders and neurobehavioral diseases in a PCB- exposed population: What we learned and the implications for future research

Polychlorinated biphenyls (PCBs) are one of the original twelve classes of toxic chemicals covered by the Stockholm Convention on Persistent Organic Pollutants (POP), an international environmental treaty signed in 2001. PCBs are present in the environment as mixtures of multiple isomers at different degree of chlorination. These compounds are manmade and possess useful industrial properties including extreme longevity under harsh conditions, heat absorbance, and the ability to form an oily liquid at room temperature that is useful for electrical utilities and in other industrial applications. They have been widely used for a wide range of industrial purposes over the decades. Despite a ban in production in 1979 in the US and many other countries, they remain persistent and ubiquitous in environment as contaminants due to their improper disposal. Humans, independent of where they live, are therefore exposed to PCBs, which are routinely found in random surveys of human and animal tissues. The prolonged exposures to PCBs have been associated with the development of different diseases and disorders, and they are classified as endocrine disruptors. Due to its ability to interact with thyroid hormone, metabolism and function, they are thought to be implicated in the global rise of obesity diabetes, and their potential toxicity for neurodevelopment and disorders, an example of gene by environmental interaction (GxE). The current review is primarily intended to summarize the evidence for the association of PCB exposures with increased risks for metabolic dysfunctions and neurobehavioral disorders. In particular, we present evidence of gene expression alterations in PCB-exposed populations to construct the underlying pathways that may lead to those diseases and disorders in course of life. We conclude the review with future perspectives on biomarker-based research to identify susceptible individuals and populations.

The Society for Immunotherapy of Cancer Biomarkers Task Force recommendations review

The clinical successes in cancer immunotherapy have led to a critical need for biomarkers in cancer immunotherapy. It is of the utmost importance to know who is most likely to benefit from these therapies (predictive biomarkers) but also who is starting to respond (prognostic biomarkers) and how the therapy functions in order to make rational combination choices (mechanism of action biomarkers). The Society for Immunotherapy of Cancer (SITC) Biomarkers Task Force addressed the state of the art and made a series of recommendations for the field, which is summarized here.

Beyond PD-L1 testing-emerging biomarkers for immunotherapy in non-small cell lung cancer

Recently, a firmer understanding of tumor immunology and tumor escape mechanisms has led to the development of immune checkpoint inhibitors, antibodies against programmed death-1 (PD-1) and its ligand (PD-L1). Nivolumab, pembrolizumab, and atezolizumab have dramatically altered the treatment paradigm in non-small cell lung cancer (NSCLC) and have each demonstrated improvements in outcomes and quality of life when compared to chemotherapy. Enrichment strategies to better select those patients more likely to respond have identified PD-L1 staining by immunohistochemistry (IHC) to be a predictive biomarker in both treatment naïve and refractory patients. Unfortunately, many challenges exist with this strategy and underscore the need for further exploration for more reliable biomarkers. Multiple tissue and plasma-based enrichment strategies have been identified in the hope of identifying patients more likely to benefit from checkpoint inhibitors. These include tumor mutational load; the "inflamed phenotype" including tumor infiltrating lymphocytes (TILS) and immunoscore; T-cell receptor clonality; gene signatures, and several plasma biomarkers. Several studies have revealed many of these biomarkers to be reliable predictors of response to immune checkpoint inhibitors across multiple tumor types. Given the small nature of these studies, additional prospective studies are warranted to formalize and validate each of these enrichment strategies.

A Phase II randomized study of galunisertib monotherapy or galunisertib plus lomustine compared with lomustine monotherapy in patients with recurrent glioblastoma

BACKGROUND

The combination of galunisertib, a transforming growth factor (TGF)-β receptor (R)1 kinase inhibitor, and lomustine was found to have antitumor activity in murine models of glioblastoma.

METHODS

Galunisertib (300 mg/day) was given orally 14 days on/14 days off (intermittent dosing). Lomustine was given as approved. Patients were randomized in a 2:1:1 ratio to galunisertib + lomustine, galunisertib monotherapy, or placebo + lomustine. The primary objective was overall survival (OS); secondary objectives were safety, pharmacokinetics (PKs), and antitumor activity.

RESULTS

One hundred fifty-eight patients were randomized: galunisertib + lomustine (N = 79), galunisertib (N = 39), and placebo + lomustine (N = 40). Baseline characteristics were: male (64.6%), white (75.3%), median age 58 years, ECOG performance status (PS) 1 (63.3%), and primary glioblastoma (93.7%). The PKs of galunisertib were not altered with lomustine, and galunisertib had a median half-life of ∼8 hours. Median OS in months (95% credible interval [CrI]) for galunisertib + lomustine was 6.7 (range: 5.3-8.5), 8.0 (range: 5.7-11.7) for galunisertib alone, and 7.5 (range: 5.6-10.3) for placebo + lomustine. There was no difference in OS for patients treated with galunisertib + lomustine compared with placebo + lomustine [P (HR < 1) = 26%]. Median progression-free survival of ∼2 months was observed in all 3 arms. Among 8 patients with IDH1 mutation, 7 patients were treated with galunisertib (monotherapy or with lomustine); OS ranged from 4 to 17 months. Patients treated with galunisertib alone had fewer drug-related grade 3/4 adverse events (n = 34) compared with lomustine-treated patients (10% vs 26%). Baseline PS, post-discontinuation of bevacizumab, tumor size, and baseline levels of MDC/CCL22 were correlated with OS.

CONCLUSIONS

Galunisertib + lomustine failed to demonstrate improved OS relative to placebo + lomustine. Efficacy outcomes were similar in all 3 arms.

CLINICAL TRIAL REGISTRATION

NCT01582269, ClinicalTrials.gov.

Enhancing the discovery and development of immunotherapies for cancer using quantitative and systems pharmacology: Interleukin-12 as a case study

Recent clinical successes of immune checkpoint modulators have unleashed a wave of enthusiasm associated with cancer immunotherapy. However, this enthusiasm is dampened by persistent translational hurdles associated with cancer immunotherapy that mirror the broader pharmaceutical industry. Specifically, the challenges associated with drug discovery and development stem from an incomplete understanding of the biological mechanisms in humans that are targeted by a potential drug and the financial implications of clinical failures. Sustaining progress in expanding the clinical benefit provided by cancer immunotherapy requires reliably identifying new mechanisms of action. Along these lines, quantitative and systems pharmacology (QSP) has been proposed as a means to invigorate the drug discovery and development process. In this review, I discuss two central themes of QSP as applied in the context of cancer immunotherapy. The first theme focuses on a network-centric view of biology as a contrast to a "one-gene, one-receptor, one-mechanism" paradigm prevalent in contemporary drug discovery and development. This theme has been enabled by the advances in wet-lab capabilities to assay biological systems at increasing breadth and resolution. The second theme focuses on integrating mechanistic modeling and simulation with quantitative wet-lab studies. Drawing from recent QSP examples, large-scale mechanistic models that integrate phenotypic signaling-, cellular-, and tissue-level behaviors have the potential to lower many of the translational hurdles associated with cancer immunotherapy. These include prioritizing immunotherapies, developing mechanistic biomarkers that stratify patient populations and that reflect the underlying strength and dynamics of a protective host immune response, and facilitate explicit sharing of our understanding of the underlying biology using mechanistic models as vehicles for dialogue. However, creating such models require a modular approach that assumes that the biological networks remain similar in health and disease. As oncogenesis is associated with re-wiring of these biological networks, I also describe an approach that combines mechanistic modeling with quantitative wet-lab experiments to identify ways in which malignant cells alter these networks, using Interleukin-12 as an example. Collectively, QSP represents a new holistic approach that may have profound implications for how translational science is performed.

Impacts of a biobank: Bridging the gap in translational cancer medicine

The prevalence of people affected by cancer has been steadily increasing. More and more people are being offered the chance of increased longevity. This has been possible due to advances not only in medicines and techniques but also because of the gain in understanding of cancer biology through Translational Cancer Medicine. A significant step towards obtaining this success was the establishment of successful biobanking practise. In this review we discuss about the importance of a Biobank and the various impacts that a biobank can have not only in the field of cancer but also on many other aspects. Later we discuss a method of quantitative evaluation of these impacts of a biobank.

Molecular markers to predict clinical outcome and radiation induced toxicity in lung cancer

The elucidation of driver mutations involved in the molecular pathogenesis of cancer has led to a surge in the application of novel targeted therapeutics in lung cancer. Novel oncologic research continues to lead investigators towards targeting personalized tumor characteristics rather than applying targeted therapy to broad patient populations. Several driver genes, in particular epidermal growth factor receptor (EGFR) and ALK fusions, are the earliest to have made their way into clinical trials. The avant-garde role of genomic profiling has led to important clinical challenges when adapting current standard treatments to personalized oncologic care. This new frontier of medicine requires newer biomarkers for toxicity that will identify patients at risk, as well as, new molecular markers to predict and assess clinical outcomes. Thus far, several signature genes have been developed to predict outcome as well as genetic factors related to inflammation to predict toxicity.

Milk fat globule epidermal growth factor VIII signaling in arterial wall remodeling

Arterial inflammation and remodeling, important sequellae of advancing age, are linked to the pathogenesis of age-associated arterial diseases e.g. hypertension, atherosclerosis, and metabolic disorders. Recently, high-throughput proteomic screening has identified milk fat globule epidermal growth factor VIII (MFG-E8) as a novel local biomarker for aging arterial walls. Additional studies have shown that MFG-E8 is also an element of the arterial inflammatory signaling network. The transcription, translation, and signaling levels of MFG-E8 are increased in aged, atherosclerotic, hypertensive, and diabetic arterial walls in vivo as well as activated vascular smooth muscle cells (VSMC) and a subset of macrophages in vitro. In VSMC, MFG-E8 increases proliferation and invasion as well as the secretion of inflammatory molecules. In endothelial cells (EC), MFG-E8 facilitates apoptosis. In addition, MFG-E8 has been found to be an essential component of the endothelial-derived microparticles that relay biosignals and modulate arterial wall phenotypes. This review mainly focuses upon the landscape of MFG-E8 expression and signaling in adverse arterial remodeling. Recent discoveries have suggested that MFG-E8 associated interventions are novel approaches for the retardation of the enhanced rates of VSMC proliferation and EC apoptosis that accompany arterial wall inflammation and remodeling during aging and age-associated arterial disease.

Local immune response predicts survival in patients with thick (t4) melanomas

BACKGROUND

Tumor infiltrating lymphocytes (TIL) and histological regression in primary melanoma are generally considered indicators of the local immune response but their roles as prognostic factors have been variably reported. We examined the prognostic role of these variables in patients with high risk (T4) primary melanomas in a large series of patients with long-term follow-up.

METHODS

From a prospectively maintained cohort of patients diagnosed between 1971 and 2004, 161 patients were retrospectively identified with primary thick melanomas (>4 mm), no clinical evidence of regional nodal disease (RND) at diagnosis and complete histopathologic data. Univariate and multivariate Cox regression models were performed to identify clinical and histopathologic predictors of disease-specific survival (DSS) and to identify subgroups with differential survival.

RESULTS

Factors significantly associated with decreased DSS by univariate analysis included male gender, age ≥ 60 years, axial anatomic location, presence of ulceration, RND, absence of TIL, and presence of regression. In the final multivariate model, TIL and regression, as interacting variables, and RND status remained significantly associated with DSS. In the presence of TIL, concomitant regression was associated with significantly worse survival (p ≤ 0.0001). In the absence of TIL, there was no effect of regression on survival (p = 0.324).

CONCLUSIONS

Primary TIL and regression status and RND status are independently associated with melanoma-specific survival in patients with T4 melanomas; presence of TIL in the primary melanoma with concomitant radial growth phase regression is associated with a poor prognosis and may reflect an ineffective local regional immune response.

Quality controls in cellular immunotherapies: rapid assessment of clinical grade dendritic cells by gene expression profiling

Cell-based immunotherapies are among the most promising approaches for developing effective and targeted immune response. However, their clinical usefulness and the evaluation of their efficacy rely heavily on complex quality control assessment. Therefore, rapid systematic methods are urgently needed for the in-depth characterization of relevant factors affecting newly developed cell product consistency and the identification of reliable markers for quality control. Using dendritic cells (DCs) as a model, we present a strategy to comprehensively characterize manufactured cellular products in order to define factors affecting their variability, quality and function. After generating clinical grade human monocyte-derived mature DCs (mDCs), we tested by gene expression profiling the degrees of product consistency related to the manufacturing process and variability due to intra- and interdonor factors, and how each factor affects single gene variation. Then, by calculating for each gene an index of variation we selected candidate markers for identity testing, and defined a set of genes that may be useful comparability and potency markers. Subsequently, we confirmed the observed gene index of variation in a larger clinical data set. In conclusion, using high-throughput technology we developed a method for the characterization of cellular therapies and the discovery of novel candidate quality assurance markers.

Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Immunotherapy of cancer in 2012

The immunotherapy of cancer has made significant strides in the past few years due to improved understanding of the underlying principles of tumor biology and immunology. These principles have been critical in the development of immunotherapy in the laboratory and in the implementation of immunotherapy in the clinic. This improved understanding of immunotherapy, enhanced by increased insights into the mechanism of tumor immune response and its evasion by tumors, now permits manipulation of this interaction and elucidates the therapeutic role of immunity in cancer. Also important, this improved understanding of immunotherapy and the mechanisms underlying immunity in cancer has fueled an expanding array of new therapeutic agents for a variety of cancers. Pegylated interferon-α2b as an adjuvant therapy and ipilimumab as therapy for advanced disease, both of which were approved by the United States Food and Drug Administration for melanoma in March 2011, are 2 prime examples of how an increased understanding of the principles of tumor biology and immunology have been translated successfully from the laboratory to the clinical setting. Principles that guide the development and application of immunotherapy include antibodies, cytokines, vaccines, and cellular therapies. The identification and further elucidation of the role of immunotherapy in different tumor types, and the development of strategies for combining immunotherapy with cytotoxic and molecularly targeted agents for future multimodal therapy for cancer will enable even greater progress and ultimately lead to improved outcomes for patients receiving cancer immunotherapy.

The immune score as a new possible approach for the classification of cancer

The outcome prediction in cancer is usually achieved by evaluating tissue samples obtained during surgical removal of the primary tumor focusing on their histopathological characteristics. Tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N), and evidence for metastases (M). However, this classification provides limited prognostic information in estimating the outcome in cancer and does not predict response to therapy. It is recognized that cancer outcomes can vary significantly among patients within the same stage. Recently, many reports suggest that cancer development is controlled by the host's immune system underlying the importance of including immunological biomarkers for the prediction of prognosis and response to therapy. Data collected from large cohorts of human cancers demonstrated that the immune-classification has a prognostic value that may be superior to the AJCC/UICC TNM-classification. Thus, it is imperative to begin incorporating immune scoring as a prognostic factor and to introduce this parameter as a marker to classify cancers, as part of the routine diagnostic and prognostic assessment of tumors. At the same time, the inherent complexity of quantitative immunohistochemistry, in conjunction with variable assay protocols across laboratories, the different immune cell types analyzed, different region selection criteria, and variable ways to quantify immune infiltration underscore the urgent need to reach assay harmonization. In an effort to promote the immunoscore in routine clinical settings worldwide, the Society for Immunotherapy of Cancer (SITC), the European Academy of Tumor Immunology, the Cancer and Inflammation Program, the National Cancer Institute, National Institutes of Health, USA and "La Fondazione Melanoma" will jointly initiate a task force on Immunoscoring as a New Possible Approach for the Classification of Cancer that will take place in Naples, Italy, February 13^th, 2012. The expected outcome will include a concept manuscript that will be distributed to all interested participants for their contribution before publication outlining the goal and strategy to achieve this effort; a preliminary summary to be presented during the "Workshop on Tumor Microenvironment" prior to the SITC annual meeting on October 24^th - 25^th 2012 in Bethesda, Maryland, USA and finally a "Workshop on Immune Scoring" to be held in Naples in December of 2012 leading to the preparation of a summary document providing recommendations for the harmonization and implementation of the Immune Score as a new component for the classification of cancer.

Multiplex serum biomarker assessments: technical and biostatistical issues

BACKGROUND

Identification of predictive and prognostic biomarkers for patients with disease and undergoing different therapeutic options is a very active area of investigation. Many of these studies seek biomarkers among circulating proteins accessed in blood. Many levels of standardization in materials and procedures have been identified which can impact the resulting data.

METHODS

Here, we have observed unexpected variability in levels of commonly tested analytes in serum which were processed and stored under standardized conditions. We have identified apparent changes in cytokine, chemokine and growth factor levels detected by multiplex Luminex assay in melanoma patient and healthy donor serum samples, over storage time at -80°C. Controls included Luminex kit standards, multiplexed cytokine standards and WHO cytokine controls. Data were analyzed by Wilcoxon rank-sum testing and Spearman's test for correlations.

RESULTS

The interpretation of these changes is confounded by lot-to-lot kit standard curve reagent changes made by a single manufacturer of Luminex kits.

CONCLUSIONS

This study identifies previously unknown sources of variation in a commonly used biomarker assay, and suggests additional levels of controls needed for identification of true changes in circulating protein levels.

Biomarkers in T cell therapy clinical trials

T cell therapy represents an emerging and promising modality for the treatment of both infectious disease and cancer. Data from recent clinical trials have highlighted the potential for this therapeutic modality to effect potent anti-tumor activity. Biomarkers, operationally defined as biological parameters measured from patients that provide information about treatment impact, play a central role in the development of novel therapeutic agents. In the absence of information about primary clinical endpoints, biomarkers can provide critical insights that allow investigators to guide the clinical development of the candidate product. In the context of cell therapy trials, the definition of biomarkers can be extended to include a description of parameters of the cell product that are important for product bioactivity.

This review will focus on biomarker studies as they relate to T cell therapy trials, and more specifically: i. An overview and description of categories and classes of biomarkers that are specifically relevant to T cell therapy trials, and ii. Insights into future directions and challenges for the appropriate development of biomarkers to evaluate both product bioactivity and treatment efficacy of T cell therapy trials.

Multiplexed protein analysis using encoded antibody-conjugated microbeads

We describe a method for multiplexed analysis of proteins using fluorescently encoded microbeads. The sensitivity of our method is comparable to the sensitivity obtained by enzyme-linked immunosorbent assay while only 5 µl sample volumes are needed. Streptavidin-coated, 1 µm beads are encoded with a combination of fluorophores at different intensity levels. As a proof of concept, we demonstrate that 27 microbead populations can be readily encoded by affinity conjugation using three intensity levels for each of three different biotinylated fluorescent dyes. Four populations of encoded microbeads are further conjugated with biotinylated capture antibodies and then combined and immobilized in a microfluidic flow cell for multiplexed protein analysis. Using four uniquely encoded microbead populations, we show that a cancer biomarker and three cytokine proteins can be analysed quantitatively in the picogram per millilitre range by fluorescence microscopy in a single assay. Our method will allow for the fabrication of high density, bead-based antibody arrays for multiplexed protein analysis using integrated microfluidic devices and automated sample processing.

Translational Medicine is developing in China: a new venue for collaboration

Translational Medicine is an emerging area comprising multidisciplinary Research from basic sciences to medical applications well summarized by the Bench-to-Beside concept; this entails close collaboration between clinicians and basic scientists across institutes. We further clarified that Translational Medicine should be regarded as a two-way road: Bench-to-Bedside and Bedside-to-Bench, to complement testing of novel therapeutic strategies in humans with feedback understanding of how they respond to them. It is, therefore, critical and important to define and promote Translational Medicine among clinicians, basic Researchers, biotechnologists, politicians, ethicists, sociologists, investors and coordinate these efforts among different Countries, fostering aspects germane only to this type of Research such as, as recently discussed, biotechnology entrepreneurship. Translational Medicine as an inter-disciplinary science is developing rapidly and widely and, in this article, we will place a special emphasis on China.

Immuno-oncology biomarkers 2010 and beyond: perspectives from the iSBTc/SITC biomarker task force

The International Society for Biological Therapy of Cancer (iSBTc, recently renamed the Society for Immunotherapy of Cancer, SITC) hosted a one-day symposium at the National Institutes of Health on September 30, 2010 to address development and application of biomarkers in cancer immunotherapy. The symposium, titled Immuno-Oncology Biomarkers 2010 and Beyond: Perspectives from the iSBTc/SITC Biomarker Task Force, gathered approximately 230 investigators equally from academia, industry and governmental/regulatory agencies from around the globe for panel discussions and presentations on the following topics: 1) immunologic monitoring: standardization and validation of assays; 2) correlation of immunity to biologic activity, clinical response and potency assays; 3) novel methodologies for assessing the immune landscape: clinical utility of novel technologies; and 4) recommendations on incorporation of biomarkers into the clinical arena. The presentations are summarized in this report; additional program information and slides are available online at the iSBTc/SITC website.

What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema

A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term "biomarker". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of "biomarker" and either "discovery", "genomics", "proteomics" or "metabolomics" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in "biomarker" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.

Proteomic strategies and challenges in tumor metastasis research

The rapidly evolving field of proteomics offers new approaches to understanding the pathogenesis of cancer and metastatic disease. Although numerous tumor markers have been identified with different genomic methods in the past, most are either not specific or sensitive enough to be used in routine clinical setting. The rationale for proteomic profiling is based on the fact that proteins represent the dynamic state of the cells, reflecting pathophysiological changes in the disease more accurately than genomic and epigenetic alterations. Emerging proteomic techniques allow simultaneous assessment of a large number of proteins at one time. The study of protein profiles in complex systems, such as plasma, serum or tissues of cancer patients is likely to become valuable for monitoring the response of patients during treatment or for detecting recurrence of the disease.

Dendritic cells: are they clinically relevant?

Cancer vaccines have undergone a renaissance because of recent clinical trials showing promising immunologic data and some clinical benefit to patients. Current trials exploiting dendritic cells (DCs) as vaccines have shown durable tumor regressions in a fraction of patients. Clinical efficacy of current vaccines is hampered by myeloid-derived suppressor cells, inflammatory type 2 T cells, and regulatory T cells, all of which prevent the generation of effector cells. To improve the clinical efficacy of DC vaccines, we need to design novel and improved strategies that can boost adaptive immunity to cancer, help overcome regulatory T cells and allow the breakdown of the immunosuppressive tumor microenvironment. This can be achieved by exploiting the fast increasing knowledge about the DC system, including the existence of distinct DC subsets. Critical to the design of better vaccines is the concept of distinct DC subsets and distinct DC activation pathways, all contributing to the generation of unique adaptive immune responses. Such novel DC vaccines will be used as monotherapy in patients with resected disease and in combination with antibodies and/or drugs targeting suppressor pathways and modulation of the tumor environment in patients with metastatic disease.

Gene-expression profiling in vaccine therapy and immunotherapy for cancer

The identification of tumor antigens recognized by T cells led to the design of therapeutic strategies aimed at eliciting adaptive immune responses. The last decade of experience has shown that, although active immunization can induce enhancement of anticancer T-cell precursors (easily detectable in standard assays), most often they are unable to induce tumor regression and, consequently, have scarcely any impact on overall survival. Moreover, in the few occasions when tumor rejection occurs, the mechanisms determining this phenomenon remain poorly understood, and data derived from in vivo human observations are rare. The advent of high-throughput gene-expression analysis (microarrays) has cast new light on unrecognized mechanisms that are now deemed to be central for the development of efficient immune-mediated tumor rejection. The aim of this article is to review the data on the molecular signature associated with this process. We believe that the description of how the mechanism of immune-mediated tissue destruction occurs would contribute to our understanding of why it happens, thereby allowing us to develop more effective immune therapeutic strategies.

Dendritic cell subsets as vectors and targets for improved cancer therapy

Current active immunotherapy trials have shown durable tumor regressions in a fraction of patients. However, the clinical efficacy of current vaccines is limited, possibly because tumors skew the immune system by means of myeloid-derived suppressor cells, inflammatory Type 2 T cells and regulatory T cells (Tregs), all of which prevent the generation of effector cells. To improve the clinical efficacy of cancer vaccines in patients with metastatic disease, we need to design novel and improved strategies that can boost adaptive immunity to cancer, help overcome Tregs and allow the breakdown of the immunosuppressive tumor microenvironment. This can be achieved by exploiting the fast increasing knowledge about the dendritic cell (DC) system, including the existence of distinct DC subsets. Critical to the design of better vaccines is the concept of distinct DC subsets and distinct DC activation pathways, all contributing to the generation of unique adaptive immune responses. Such novel DC vaccines will be used as monotherapy in patients with resected disease and in combination with antibodies and/or drugs targeting suppressor pathways and modulation of the tumor environment in patients with metastatic disease.

Harnessing dendritic cells to generate cancer vaccines

Passive immunotherapy of cancer (i.e., transfer of T cells or antibodies) can lead to some objective clinical responses, thus demonstrating that the immune system can reject tumors. However, passive immunotherapy is not expected to yield memory T cells that might control tumor outgrowth. Active immunotherapy with dendritic cell (DC) vaccines has the potential to induce tumor-specific effector and memory T cells. Clinical trials testing first-generation DC vaccines pulsed with tumor antigens provided a proof-of-principle that therapeutic immunity can be elicited. Newer generation DC vaccines are built on the increased knowledge of the DC system, including the existence of distinct DC subsets and their plasticity all leading to the generation of distinct types of immunity. Rather than the quantity of IFN-gamma-secreting CD8(+) T cells, we should aim at generating high-quality, high-avidity, polyfunctional effector CD8(+) T cells able to reject tumors and long-lived memory CD8(+) T cells able to prevent relapse.

Turning laboratory findings into therapy: a marathon goal that has to be reached

The mission of translational research involves difficult tasks to be accomplished for its ultimate goal, i.e., the introduction of novel, effective therapeutic strategies in the clinic to diminish human suffering and cure life-threatening diseases. Translational research (also referred to as translational medicine) facilitates the translation of investment in biomedical research into successful medical treatment. This includes the transfer of diagnostic and therapeutic advances by proving their efficacy in large evidence-based trials. Through the study of humans novel insights about disease are brought back to the laboratory to identify new, observation-based strategies. This "two-way road" ("bench to bedside and bedside to bench") process includes formulating guidelines for drug development and principles for new therapeutic strategies; initiating clinical investigations that provide the biological basis for new therapies, and related clinical trials; defining therapeutic targets and clinical endpoints. It requires a systematic approach beginning with specimen sampling, patient data collection, laboratory investigations, data analysis, preclinical testing, clinical trials, treatment efficacy monitoring, and finally the evaluation of therapeutic result. The marathon well symbolizes the enormous efforts undertaken by clinicians, scientists, regulators, ethicists, patient advocates, drug developers, and others, coordinately attempting to overcome obstacles along this road toward the final "marathon goal in medicine".