Tumor-Associated Antigens and Biomarkers in Cancer and Immune Therapy

Anti-α-enolase is a prognostic marker in postoperative lung cancer patients

Our previous studies suggest that antibodies against ENO1 (anti-ENO1 Ab) have a protective role in patients with non-small cell lung carcinoma. In this study, we evaluated the prognostic value of anti-ENO1 Ab levels in non-small cell lung carcinoma patients undergoing surgery. Circulating levels of anti-ENO1 Ab were assessed in 85 non-small cell lung carcinoma patients before and after surgery, and were correlated with clinical outcome. After surgery, patients with a higher increase of anti-ENO1 Ab had a lower hazard ratio and a better progression-free survival. Using animal models, we demonstrated that tumor cells reduce the circulating levels of anti-ENO1 Ab through physical absorption and neutralization of anti-ENO1 Ab with surface-expressed and secreted ENO1, respectively. Mice transplanted with ENO1-overexpressing tumors generated ENO1-specific regulatory T cells to suppress the production of anti-ENO1 Ab. Our results suggest that the increase of anti-ENO1 Ab may reflect anti-tumor immune responses and serve as a prognostic marker in postoperative lung cancer patients.

Analysis of serum metabolic profile by ultra-performance liquid chromatography-mass spectrometry for biomarkers discovery: application in a pilot study to discriminate patients with tuberculosis

BACKGROUND

Tuberculosis (TB) is a chronic wasting inflammatory disease characterized by multisystem involvement, which can cause metabolic derangements in afflicted patients. Metabolic signatures have been exploited in the study of several diseases. However, the serum that is successfully used in TB diagnosis on the basis of metabolic profiling is not by much.

METHODS

Orthogonal partial least-squares discriminant analysis was capable of distinguishing TB patients from both healthy subjects and patients with conditions other than TB. Therefore, TB-specific metabolic profiling was established. Clusters of potential biomarkers for differentiating TB active from non-TB diseases were identified using Mann-Whitney U-test. Multiple logistic regression analysis of metabolites was calculated to determine the suitable biomarker group that allows the efficient differentiation of patients with TB active from the control subjects.

RESULTS

From among 271 participants, 12 metabolites were found to contribute to the distinction between the TB active group and the control groups. These metabolites were mainly involved in the metabolic pathways of the following three biomolecules: Fatty acids, amino acids, and lipids. The receiver operating characteristic curves of 3D, 7D, and 11D-phytanic acid, behenic acid, and threoninyl-γ-glutamate exhibited excellent efficiency with area under the curve (AUC) values of 0.904 (95% confidence interval [CI]: 0863-0.944), 0.93 (95% CI: 0.893-0.966), and 0.964 (95% CI: 00.941-0.988), respectively. The largest and smallest resulting AUCs were 0.964 and 0.720, indicating that these biomarkers may be involved in the disease mechanisms. The combination of lysophosphatidylcholine (18:0), behenic acid, threoninyl-γ-glutamate, and presqualene diphosphate was used to represent the most suitable biomarker group for the differentiation of patients with TB active from the control subjects, with an AUC value of 0.991.

CONCLUSION

The metabolic analysis results identified new serum biomarkers that can distinguish TB from non-TB diseases. The metabolomics-based analysis provides specific insights into the biology of TB and may offer new avenues for TB diagnosis.

Green fluorescent-conjugated anti-CEA single chain antibody for the detection of CEA-positive cancer cells

According to World Health Organization (WHO), cancer is a leading cause of death worldwide, accounting for 7.4 million deaths (around 13% of all deaths) in 2004. Monoclonal/recombinant antibodies, which specifically target clinical biomarkers of disease, have increasingly been applied as powerful tools in cancer imaging and therapy, a fact that is highlighted by some nine FDA-approved monoclonal antibodies (MAbs) or their immunoconjugates (as of December 2008) for use in cancer treatment. In this study, five monoclonal antibodies (MAbs) were generated and characterized against carcinoembryonic antigen (CEA), which is widely used clinically as both a blood and tissue tumor marker of epithelial malignancy. Variable domains (VH and VL) of one the stable MAbs with highest affinity were PCR-amplified and assembled as single-chain antibody fragment (scFv). Following the cloning and expression of scFv antibody fragments in Escherichia coli, the functional binding and specificity of the recombinant antibody were confirmed by ELISA. To develop a direct in vitro detection of CEA-positive cancer cells, scFv DNA was genetically fused to enhanced green fluorescent protein (EGFP) gene and expressed in bacteria. The chimeric fluorescent protein is able to specifically detect CEA-positive cell lines; no cross-reactivity was observed with a negative control cell line. This strategy will likely allow the establishment of a rapid, single-step detection assay of CEA, which is considered to be one of the best predictors of malignancy among all other tumor markers.

Bispecific antibodies engage T cells for antitumor immunotherapy

INTRODUCTION

Although considerable evidence supports the hypothesis that T cells play a critical role in the immune response against cancer, the ability to mount and sustain tumor-specific cellular responses in vivo remains a challenge. A strategy that harnesses the cytotoxic advantage of T cell therapy is the use of bispecific antibodies designed to engage and activate endogenous polyclonal T cell populations via the CD3 complex, but only in the presence of a tumor antigen. While antibody constructs with dual specificity were first described as anticancer therapeutics over 25 years ago, it was not until recently that one subclass of bispecific single-chain antibody, the bispecific T cell engager (BiTE), emerged as superior to previous iterations in achieving efficacy in animal models and early clinical trials.

AREAS COVERED

The evolution of bispecific antibodies in antitumor immunotherapy is reviewed and the greatest hurdles impeding their clinical translation are discussed, specifically in the context of immunoprivileged sites as is the case for intracerebral malignancy.

EXPERT OPINION

The BiTE platform has great potential in the treatment of malignant disease. Despite burgeoning interest in bispecific antibodies and permutations thereof, the issues of stability and cost-effective production persist as obstacles.

Immunotherapy can reject intracranial tumor cells without damaging the brain despite sharing the target antigen

Although vaccines targeting tissue differentiation Ags represent a promising strategy for cancer immunotherapy, the risk of triggering autoimmune damage to normal tissues remains to be determined. Immunizing against a melanoma-associated Ag, dopachrome tautomerase (DCT), which normal melanocytes and glial cells also express, allowed concurrent analysis of autoimmune consequences in multiple tissues. We show that vaccination with recombinant adenovirus expressing DCT elicited a strong CTL response in C57BL/6 mice, leading to protection against intracranial challenge with B16-F10 melanoma cells. Both histological analysis and behavioral testing indicated that there was no evidence of neuropathology in vaccinated animals and long-term survivors. Although vitiligo or demyelination could be induced by additional stimuli (i.e., surgery or inflammation) in DCT-vaccinated mice, it did not extend beyond the inflammatory area, suggesting that there is self-regulatory negative feedback in normal tissues. These results demonstrate that it is possible to vaccinate against a tumor embedded in a vital organ that shares the target Ag.

Current advances in tumor proteomics and candidate biomarkers for hepatic cancer

Tumor proteomics apply proteomics techniques to tumor biological research, mainly by screening candidate biomarkers for early tumor diagnosis, prognosis and treatment. Hepatocellular carcinoma (HCC) is a type of malignant tumor with one of the highest death rates in the world. With the advent of the post-genomic age, tumor biological research developing the technology of proteomics has become a major focus of researchers. The discovery of novel candidate biomarkers is one of crucial problems for the early diagnosis of HCC. In general, there are three distinct types of candidate biomarkers for HCC based on different areas: biochemical biomarkers, antigenic biomarkers and epigenetic biomarkers. This review mainly discusses current advances in the problems and prospects of candidate biomarker for the early diagnosis of HCC, discovered by technologies of tumor proteomics.

RHAMM (CD168) is overexpressed at the protein level and may constitute an immunogenic antigen in advanced prostate cancer disease

Localized prostate cancer (CaP) can be cured using several strategies. However, the need to identify active substances in advanced tumor stages is tremendous, as the outcome in such cases is still disappointing. One approach is to deliver human tumor antigen-targeted therapy, which is recognized by T cells or antibodies. We used data mining of the Cancer Immunome Database (CID), which comprises potential immunologic targets identified by serological screening of expression libraries. Candidate antigens were screened by DNA microarrays. Genes were then validated at the protein level by tissue microarrays, representing various stages of CaP disease. Of 43 targets identified by CID, 10 showed an overexpression on the complementary DNA array in CaP metastases. The RHAMM (CD168) gene, earlier identified by our group as an immunogenic antigen in acute and chronic leukemia, also showed highly significant overexpression in CaP metastases compared with localized disease and benign prostatic hyperplasia. At the protein level, RHAMM was highest in metastatic tissue samples and significantly higher in neoplastic localized disease compared with benign tissue. High RHAMM expression was associated with clinical parameters known to be linked to better clinical outcome. Patients with high RHAMM expression in the primaries had a significantly lower risk of biochemical failure. The number of viable cells in cell cultures was reduced in blocking experiments using hormone-sensitive and hormone-insensitive metastatic CaP cell lines. Acknowledging the proven immunogenic effects of RHAMM in leukemia, this antigen is intriguing as a therapeutic target in far-advanced CaP.

[Recent development of metabonomics and its applications in clinical research]

In the post-genomic era, systems biology is central to the biological sciences. Functional genomics such as transcriptomics and proteomics can simultaneous determine massive gene or protein expression changes following drug treatment or other intervention. However, these changes can't be coupled directly to changes in biological function. As a result, metabonomics and its many pseudonyms (metabolomics, metabolic profiling, etc.) have exploded onto the scientific scene in the past several years. Metabonomics is a rapidly growing research area and a system approach for comprehensive and quantitative analysis of the global metabolites in a biological matrix. Analytical chemistry approach is necessary for the development of comprehensive metabonomics investigations. Fundamentally, there are two types of metabonomics approaches: mass-spectrometry (MS) based and nuclear magnetic resonance (NMR) methodologies. Metabonomics measurements provide a wealth of data information and interpretation of these data relies mainly on chemometrics approaches to perform large-scale data analysis and data visualization, such as principal and independent component analysis, multidimensional scaling, a variety of clustering techniques, and discriminant function analysis, among many others. In this review, the recent development of analytical and statistical techniques used in metabonomics is summarized. Major applications of metabonomics relevant to clinical and preclinical study are then reviewed. The applications of metabonomics in study of liver diseases, cancers and other diseases have proved useful both as an experimental tool for pathogenesis mechanism re-search and ultimately a tool for diagnosis and monitoring treatment response of these diseases. Next, the applications of metabonomics in preclinical toxicology are discussed and the role that metabonomics might do in pharmaceutical research and development is explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology (COMET), and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Finally, the role of metabonomics in elucidating the function of the unknown or novel enzyme is mentioned.

Spontaneous and treatment-induced cancer rejection in humans

BACKGROUND

Experimental observations suggest that human cancer cells actively interact with normal host cells and this cross-talk results, in most instances, in an increased potential of cancer cells to survive. On the other hand, it is also well documented that on rare occasions tumors can be dramatically destroyed by the host's immune response.

OBJECTIVE

In this review, we argue that understanding the mechanisms that bring about the immune response and lead to cancer destruction is of paramount importance for the design of future rational therapies.

METHODS

Here we summarize the present understanding of the phenomenology leading to cancer regression in humans and propose novel strategies for a more efficient study of human cancer under natural conditions and during therapy.

CONCLUSION

The understanding of tumor/host interactions within the tumor microenvironment is a key component of the study of tumor immunology in humans, much can be learned by a dynamic study of such interactions at time points related to the natural history of the disease or its response to therapy. Such understanding will eventually lead to novel and more effective therapies.

Metabolomics in biomarker discovery: future uses for cancer prevention

Metabolomics is the systematic study of small-molecular-weight substances in cells, tissues and/or whole organisms as influenced by multiple factors including genetics, diet, lifestyle and pharmaceutical interventions. These substances may directly or indirectly interact with molecular targets and thereby influence the risk and complications associated with various diseases, including cancer. Since the interaction between metabolites and specific targets is dynamic, knowledge regarding genetics, susceptibility factors, timing, and degree of exposure to an agent (drug or food component) is fundamental to understanding the metabolome and its potential use for predicting and preventing early phenotypic changes. The future of metabolomics rests with its ability to monitor subtle changes in the metabolome that occur prior to the detection of a gross phenotypic change reflecting disease. The integrated analysis of metabolomics and other 'omics' may provide more sensitive ways to detect changes related to disease and discover novel biomarkers. Knowledge regarding these multivariant characteristics is critical for establishing validated and predictive metabolomic models for cancer prevention. Understanding the metabolome will not only provide insights into the critical sites of regulation in health promotion, but will also assist in identifying intermediate or surrogate cancer biomarkers for establishing preemptive/preventative or therapeutic approaches for health. While unraveling the metabolome will not be simple, the societal implications are enormous.

Neutrophils in antibody-based immunotherapy of cancer

Monoclonal antibodies (mAb) are presently considered key therapeutic drugs for the treatment of malignancies. They can be designed to specifically target tumour-associated antigens and initiate several effector mechanisms, which potentially leads to elimination of the tumour. Through their Fc tail mAbs interact with Fc receptors (FcR) that are expressed on immune cells. Neutrophils are the most abundant circulating FcR-expressing white blood cells with potent cytotoxic ability that is enhanced in the presence of antitumour mAbs. They furthermore play a role in regulating adaptive immunity, which may lead to the initiation of antitumour immune responses. Yet, neutrophils receive surprisingly little attention as potential effector cell population. This article reviews the scientific data that supports the possibility of exploiting neutrophils for mAb-based immunotherapy of cancer. An increasing awareness and understanding of this topic may allow for future development of new anticancer therapies.