Cancer biomarker development from basic science to clinical practice

The amount of published literature on biomarkers has exponentially increased over the last two decades. Cancer biomarkers are molecules that are either part of tumour cells or secreted by tumour cells. Biomarkers can be used for diagnosing cancer (tumour versus normal and differentiation of subtypes), prognosticating patients (progression free survival and overall survival) and predicting response to therapy. However, very few biomarkers are currently used in clinical practice compared to the unprecedented discovery rate. Some of the examples are: carcino-embryonic antigen (CEA) for colon cancer; prostate specific antigen (PSA) for prostate; and estrogen receptor (ER), progesterone receptor (PR) and HER2 for breast cancer. Cancer biomarkers passes through a series of phases before they are used in clinical practice. First phase in biomarker development is identification of biomarkers which involve discovery, demonstration and qualification. This is followed by validation phase, which includes verification, prioritisation and initial validation. More large-scale and outcome-oriented validation studies expedite the clinical translation of biomarkers by providing a strong ‘evidence base’. The final phase in biomarker development is the routine clinical use of biomarker. In summary, careful identification of biomarkers and then validation in well-designed retrospective and prospective studies is a systematic strategy for developing clinically useful biomarkers

Neutrophil-to-lymphocyte ratio as a bladder cancer biomarker: assessing prognostic and predictive value in SWOG 8710

No abstract available

New generation of electrochemical immunoassay based on polymeric nanoparticles for early detection of breast cancer

Screening and early diagnosis are the key factors for the reduction of mortality rate and treatment cost of cancer. Therefore, sensitive and selective methods that can reveal the low abundance of cancer biomarkers in a biological sample are always desired. Here, we report the development of a novel electrochemical biosensor for early detection of breast cancer by using bioconjugated self-assembled pH-responsive polymeric micelles. The micelles were loaded with ferrocene molecules as "tracers" to specifically target cell surface-associated epithelial mucin (MUC1), a biomarker for breast and other solid carcinoma. The synthesis of target-specific, ferrocene-loaded polymeric micelles was confirmed, and the resulting sensor was capable of detecting the presence of MUC1 in a sample containing about 10 cells/mL. Such a high sensitivity was achieved by maximizing the loading capacity of ferrocene inside the polymeric micelles. Every single event of binding between the antibody and antigen was represented by the signal of hundreds of thousands of ferrocene molecules that were released from the polymeric micelles. This resulted in a significant increase in the intensity of the ferrocene signal detected by cyclic voltammetry

Predicting Prostate Cancer Aggressiveness through a Nanoparticle Test

Prostate cancer (PCa) is the most common malignancy and the second leading cause of cancer death in American men. Due to the lack of accurate tests to distinguish aggressive cancer from indolent tumor, prostate cancer is often over-treated. Post-surgery pathology analysis revealed that 30% of tumors removed by radical prostatectomy are deemed clinically insignificant and would not have required such invasive treatment.^1^ Over-diagnosis and treatment of low-risk prostate cancer has serious and long-lasting side effect: as high as 70% of the patients who receive radical prostatectomy treatment will suffer a loss of sexual potency that cannot be remedied by drugs such as sildenafil citrate.^2^ We herein report a simple nanoparticle-serum protein adsorption test that not only can distinguish prostate cancer from normal and benign conditions, but also is capable of predicting the aggressiveness of prostate cancer quantitatively. This new test could potentially deliver the long-expected and very much needed solution for better individualization of prostate cancer treatment

Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer

PURPOSE: Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers. EXPERIMENTAL DESIGN: Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples. RESULTS: We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting. CONCLUSIONS AND CLINICAL RELEVANCE: We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening

Hybrid inorganic/organic photonic crystal biochips for cancer biomarkers detection

We report on hybrid inorganic/organic one-dimensional photonic crystal biochips sustaining Bloch surface waves. The biochips were used, together with an optical platform operating in a label-free and fluorescence configuration simultaneously, to detect the cancer biomarker Angiopoietin 2 in a protein base buffer. The hybrid photonic crystals embed in their geometry a thin functionalization poly-acrylic acid layer deposited by plasma polymerization, which is used to immobilize a monoclonal antibody for highly specific biological recognition. The fluorescence operation mode is described in detail, putting into evidence the role of field enhancement and localization at the photonic crystal surface in the shaping and intensification of the angular fluorescence pattern. In the fluorescence operation mode, the hybrid biochips can attain the limit of detection 6 ng/ml.We report on hybrid inorganic/organic one-dimensional photonic crystal biochips sustaining Bloch surface waves. The biochips were used, together with an optical platform operating in a label-free and fluorescence configuration simultaneously, to detect the cancer biomarker Angiopoietin 2 in a protein base buffer. The hybrid photonic crystals embed in their geometry a thin functionalization poly-acrylic acid layer deposited by plasma polymerization, which is used to immobilize a monoclonal antibody for highly specific biological recognition. The fluorescence operation mode is described in detail, putting into evidence the role of field enhancement and localization at the photonic crystal surface in the shaping and intensification of the angular fluorescence pattern. In the fluorescence operation mode, the hybrid biochips can attain the limit of detection 6 ng/ml

Exploring the Evidence, Cracking the Case

How nanotechnology is helping researchers clue into pathogen, cancer biomarker detectio

Biosensing platform combining label-free and labelled analysis using Bloch surface waves

Bloch surface waves (BSW) propagating at the boundary of truncated photonic crystals (1D-PC) have emerged as an attractive approach for label-free sensing in plasmon-like sensor configurations. Due to the very low losses in such dielectric thin film stacks, BSW feature very low angular resonance widths compared to the surface plasmon resonance (SPR) case. Besides label-free operation, the large field enhancement and the absence of quenching allow utilizing BSW coupled fluorescence detection to additionally sense the presence of fluorescent labels. This approach can be adapted to the case of angularly resolved resonance detection, thus giving rise to a combined label-free / labelled biosensor platform. It features a parallel analysis of multiple spots arranged as a one-dimensional array inside a microfluidic channel of a disposable chip. Application of such a combined biosensing approach to the detection of the Angiopoietin-2 cancer biomarker in buffer solutions is reported

Proteomics for cancer biomarker discovery

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 51-54).Background: If we are to successfully treat cancer, we must understand the biologic underpinnings in conjunction with early diagnosis. Genome-wide expression studies have advanced the research of many cancers. Nevertheless, understanding which genes are expressed in a tumor is not equivalent to knowing which proteins are being produced. Proteomics hold great promise for careful examination of the proteins in complex biologic fluids and tissues, and it may be possible to detect disease from a patient's serum, long before it would otherwise be clinically evident. Although there have been steady advances in all the steps of a proteomic analysis, much remains to be standardized. Because of some high-profile problems with the initial analysis of ovarian cancer proteomic data, early exuberance has now been tempered and replaced by a more methodical approach to these studies. Hypothesis: My hypothesis in this thesis is that proteomics is a valuable tool in the diagnosis and study of cancer, as will be demonstrated in several steps. Methods: First, I describe the current field of proteomics, specifically as it applies to early detection of cancer and biomarker discovery.(cont.) I lay out the current state-of-the-art technologies for preparing samples and enumerating the proteins in complex fluids and tissues, giving special treatment to the main threats to validity-chance and bias. I also describe the bioinformatic tools necessary for analyzing the large amounts of data produced. Through the example of a mouse model of colorectal carcinoma, I demonstrate the steps involved in a proteomic study, from procuring samples to peptide and protein determination to bioinformatic analysis. Finally, I discuss these findings in light of the proteomic considerations discussed earlier. Results: From this work, I discovered that proteomic profiling can describe the proteins in serum from mice both with and without colon cancer. Furthermore, I developed a naive Bayes classifier that could distinguish between the serum of mice with colorectal carcinoma and their normal litter-mates. Contributions: Through this work, I have contributed the following. I described the field of proteomics with special emphasis on cancer biomarker discovery and early detection. I enumerated the challenges and pitfalls to developing early detection schemes for cancer based on high-dimensional proteomic analyses.(cont.) I described a set of experiments on mice harboring a gene mutation that predisposes them to colorectal carcinoma. I detailed the bioinformatic analysis of this data, including the development of a naive Bayes classifier to differentiate the cancerous state from the normal state. Finally, I discussed the caveats of the current work, in reference to the initial discussion on the challenges and pitfalls of early detection schemes and cancer biomarker discovery.by Samuel Louis Volchenboum.S.M

Bioinformatics advances in saliva diagnostics

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva diagnostics made possible by the Saliva Ontology and SDxMart