MicroRNA-26a Is Strongly Downregulated in Melanoma and Induces Cell Death through Repression of Silencer of Death Domains (SODD)

Melanoma is an aggressive cancer that metastasizes rapidly and is refractory to conventional chemotherapies. Identifying microRNAs (miRNAs) that are responsible for this pathogenesis is therefore a promising means of developing new therapies. We identified miR-26a through microarray and quantitative reverse-transcription–PCR (qRT-PCR) experiments as an miRNA that is strongly downregulated in melanoma cell lines as compared with primary melanocytes. Treatment of cell lines with miR-26a mimic caused significant and rapid cell death compared with a negative control in most melanoma cell lines tested. In surveying targets of miR-26a, we found that protein levels of SMAD1 (mothers against decapentaplegic homolog 1) and BAG-4/SODD were strongly decreased in sensitive cells treated with miR-26a mimic as compared with the control. The luciferase reporter assays further demonstrated that miR-26a can repress gene expression through the binding site in the 3′ untranslated region (3′UTR) of SODD (silencer of death domains). Knockdown of these proteins with small interfering RNA (siRNA) showed that SODD has an important role in protecting melanoma cells from apoptosis in most cell lines sensitive to miR-26a, whereas SMAD1 may have a minor role. Furthermore, transfecting cells with a miR-26a inhibitor increased SODD expression. Our findings indicate that miR-26a replacement is a potential therapeutic strategy for metastatic melanoma, and that SODD, in particular, is a potentially useful therapeutic target

Directive 02-14: Tax Obligations of Persons Purchasing Cigarettes in Interstate Commerce for which the Massachusetts Cigarette Excise Has Not Been Paid

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications.</p

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

The Combination of BH3-Mimetic ABT-737 with the Alkylating Agent Temozolomide Induces Strong Synergistic Killing of Melanoma Cells Independent of p53

Metastatic melanoma has poor prognosis and is refractory to most conventional chemotherapies. The alkylating agent temozolomide (TMZ) is commonly used in treating melanoma but has a disappointing response rate. Agents that can act cooperatively with TMZ and improve its efficacy are thus highly sought after. The BH3 mimetic ABT-737, which can induce apoptosis by targeting pro-survival Bcl-2 family members, has been found to enhance the efficacy of many conventional chemotherapeutic agents in multiple cancers. We found that combining TMZ and ABT-737 induced strong synergistic apoptosis in multiple human melanoma cell lines. When the drugs were used in combination in a mouse xenograft model, they drastically reduced tumor growth at concentrations where each individual drug had no significant effect. We found that TMZ treatment elevated p53 levels, and that the pro-apoptotic protein Noxa was elevated in TMZ/ABT-737 treated cells. Experiments with shRNA demonstrated that the synergistic effect of TMZ and ABT-737 was largely dependent on Noxa. Experiments with nutlin-3, a p53 inducer, demonstrated that p53 induction was sufficient for synergistic cell death with ABT-737 in a Noxa-dependent fashion. However, p53 was not necessary for TMZ/ABT-737 synergy as demonstrated by a p53-null line, indicating that TMZ and ABT-737 together induce Noxa in a p53-independent fashion. These results demonstrate that targeting anti-apoptotic Bcl-2 members is a promising method for treating metastatic melanoma, and that clinical trials with TMZ and Bcl-2 inhibitors are warranted

Enhanced Discrimination of Malignant from Benign Pancreatic Disease by Measuring the CA 19-9 Antigen on Specific Protein Carriers

The CA 19-9 assay detects a carbohydrate antigen on multiple protein carriers, some of which may be preferential carriers of the antigen in cancer. We tested the hypothesis that the measurement of the CA 19-9 antigen on individual proteins could improve performance over the standard CA 19-9 assay. We used antibody arrays to measure the levels of the CA 19-9 antigen on multiple proteins in serum or plasma samples from patients with pancreatic adenocarcinoma or pancreatitis. Sample sets from three different institutions were examined, comprising 531 individual samples. The measurement of the CA 19-9 antigen on any individual protein did not improve upon the performance of the standard CA 19-9 assay (82% sensitivity at 75% specificity for early-stage cancer), owing to diversity among patients in their CA 19-9 protein carriers. However, a subset of cancer patients with no elevation in the standard CA 19-9 assay showed elevations of the CA 19-9 antigen specifically on the proteins MUC5AC or MUC16 in all sample sets. By combining measurements of the standard CA 19-9 assay with detection of CA 19-9 on MUC5AC and MUC16, the sensitivity of cancer detection was improved relative to CA 19-9 alone in each sample set, achieving 67–80% sensitivity at 98% specificity. This finding demonstrates the value of measuring glycans on specific proteins for improving biomarker performance. Diagnostic tests with improved sensitivity for detecting pancreatic cancer could have important applications for improving the treatment and management of patients suffering from this disease

Definitive characterization of CA 19-9 in resectable pancreatic cancer using a reference set of serum and plasma specimens

The validation of candidate biomarkers often is hampered by the lack of a reliable means of assessing and comparing performance. We present here a reference set of serum and plasma samples to facilitate the validation of biomarkers for resectable pancreatic cancer. The reference set includes a large cohort of stage I-II pancreatic cancer patients, recruited from 5 different institutions, and relevant control groups. We characterized the performance of the current best serological biomarker for pancreatic cancer, CA 19-9, using plasma samples from the reference set to provide a benchmark for future biomarker studies and to further our knowledge of CA 19-9 in early-stage pancreatic cancer and the control groups. CA 19-9 distinguished pancreatic cancers from the healthy and chronic pancreatitis groups with an average sensitivity and specificity of 70-74%, similar to previous studies using all stages of pancreatic cancer. Chronic pancreatitis patients did not show CA 19-9 elevations, but patients with benign biliary obstruction had elevations nearly as high as the cancer patients. We gained additional information about the biomarker by comparing two distinct assays. The two CA 9-9 assays agreed well in overall performance but diverged in measurements of individual samples, potentially due to subtle differences in antibody specificity as revealed by glycan array analysis. Thus, the reference set promises be a valuable resource for biomarker validation and comparison, and the CA 19-9 data presented here will be useful for benchmarking and for exploring relationships to CA 19-9

P-33 Comparison of the tissue staining of CA19-9 versus sialic acids (using Avian and Human Haemagglutinin (HA)) within microtissue array samples

The early detection of cancer is the primary determinant of increasing the 5-year survivability of the patient following its diagnosis. Pancreatic cancer has the lowest 5-year survivability of all common cancers. Developing early detection methods for that disease is crucial to increasing its survival rate. Changes in glycoprotein structures in the blood and serum have been detected that correlate strongly with cancer prognosis, specifically, the concentration of the carbohydrate moiety known as CA19-9. Cancer victims with high levels of CA19-9 glycoproteins circulating in their system are known to have significantly shorter prognosis. Using lectins that bind to CA19-9 and HA which binds to α 2-3 sialic acid bonds and α 2-6 sialic acid bonds in microarray tissue slides, the resulting trends in binding gave disappointing results and lowered the confidence that HA can be used as an early detection marker

Glycans Related to the CA19-9 Antigen Are Increased in Distinct Subsets of Pancreatic Cancers and Improve Diagnostic Accuracy Over CA19-9Summary

Background & Aims: The cancer antigen 19-9 (CA19-9) is the current best biomarker for pancreatic cancer, but it is not increased in approximately 25% of pancreatic cancer patients at a cut-off value that provides a 25% false-positive rate. We hypothesized that antigens related to the CA19-9 antigen, which is a glycan called sialyl-Lewis A (sLeA), are increased in distinct subsets of pancreatic cancers. Methods: We profiled the levels of multiple glycans and mucin glycoforms in plasma from 200 subjects with either pancreatic cancer or benign pancreatic disease, and we validated selected findings in additional cohorts of 116 and 100 subjects, the latter run with the investigators blinded to diagnoses and including cancers that exclusively were early stage. Results: We found significant increases in 2 glycans: an isomer of sLeA called sialyl-Lewis X, present both in sulfated and nonsulfated forms, and the sialylated form of a marker for pluripotent stem cells, type 1 N-acetyl-lactosamine. The glycans performed as well as sLeA as individual markers and were increased in distinct groups of patients, resulting in a 3-marker panel that significantly improved upon any individual biomarker. The panel showed 85% sensitivity and 90% specificity in the combined discovery and validation cohorts, relative to 54% sensitivity and 86% specificity for sLeA; and it showed 80% sensitivity and 84% specificity in the independent test cohort, as opposed to 66% sensitivity and 72% specificity for sLeA. Conclusions: Glycans related to sLeA are increased in distinct subsets of pancreatic cancers and yield improved diagnostic accuracy compared with CA19-9. Keywords: Biomarkers, Sialyl-Lewis A, Antibody Arrays, Lectin