Gene Expression Signature for Prediction of Golimumab Response in a Phase 2a Open-Label Trial of Patients With Ulcerative Colitis.

Golimumab, a tumor necrosis factor antagonist, is an effective treatment for patients with moderate-to-severe ulcerative colitis (UC); however, more than 50% of initial responders lose their response to the drug within the first year of therapy. A gene expression signature identified in colon biopsies collected before treatment was associated with response to infliximab, and was subsequently refined to associate with mucosal healing in response to golimumab. We performed a phase 2a open-label study of 103 golimumab-treated patients with moderate-to-severe UC to test whether the baseline gene expression signature could be used to predict which patients would achieve mucosal healing, clinical response, and clinical remission at weeks 6 and 30 of treatment. The gene expression signature identified patients who went on to achieve mucosal healing at treatment week 6 with an area under the receiver operating characteristic curve (AUCROC) of 0.688 (P = .002) and at week 30 with an AUCROC of 0.671 (P = .006). The signature identified patients with mucosal healing with 87% sensitivity, but only 34% specificity, limiting its clinical utility. The baseline gene expression signature did not identify patients who went on to achieve clinical remission or clinical response with statistical significance. Further studies are needed to identify biomarkers that can be used to predict which patients with UC will respond to treatment with anti-tumor necrosis factor agents. ClinicalTrials.gov no: NCT01988961.

The Interdependency of the Morphological Variations of the Planktonic Foraminiferal Species Globigerina bulloides in Surface Sediments on the Environmental Parameters of the Southwestern Indian Ocean.

18 surface sediment samples collected from a north-south transect along the Indian Ocean have been analyzed for planktonic Foraminifera content. Among the other planktonic foraminiferal faunas, Globigerina bulloides was present substantially in all samples. Census data of G. bulloides were measured for different parameters (average size, mean proloculus size, coiling direction, and number of chambers) and a Q-mode cluster analysis was applied on these data. Samples were segregated into two homogeneous clusters, each reflecting particular environmental conditions. Two clusters are as follows: (1) Cluster A, comprised of 6 samples and characterized by the highest range of foraminiferal and ecological parameters, except sea surface temperature and salinity which shows the lowest range, and (2) Cluster B, comprised of 12 samples and characterized by the lowest range of foraminiferal parameters and ecological parameters, except sea surface temperature and salinity which shows the highest range. The study suggests that the ecological parameters are the governing factors for the morphological characteristics of planktonic foraminiferal species G. bulloides.

Quantifying factors for the success of stratified medicine.

Co-developing a drug with a diagnostic to create a stratified medicine - a therapy that is targeted to a specific patient population on the basis of a clinical characteristic such as a biomarker that predicts treatment response - presents challenges for product developers, regulators, payers and physicians. With the aim of developing a shared framework and tools for addressing these challenges, here we present an analysis using data from case studies in oncology and Alzheimer's disease, coupled with integrated computational modelling of clinical outcomes and developer economic value, to quantify the effects of decisions related to key issues such as the design of clinical trials. This illustrates how such analyses can aid the coordination of diagnostic and drug development, and the selection of optimal development and commercialization strategies. It also illustrates the impact of the interplay of these factors on the economic feasibility of stratified medicine, which has important implications for public policy makers.

Expressions of CK-19, NF-kappaB, E-cadherin, beta-catenin and EGFR as diagnostic and prognostic markers by immunohistochemical analysis in thyroid carcinoma.

Immunohistochemical markers have been proposed for thyroid cancer diagnosis and prognostic studies. Immunohistochemical analysis of CK-19, NF-kappaB, beta-catenin, E-cadherin and EGFR were done to evaluate their diagnostic and prognostic efficiencies in eighty eight cancer specimen (PTC-52, FTC-16, benign nodule-12 and MNG-8). CK-19 was positive in 91% (62/68) DTC, 98% (51/52) PTC, 69% (11/16) FTC and 15% (3/20) benign thyroid nodules. NF-kappaB was expressed 93% (63/68) DTC, in 96% (50/52) PTC, 81% (11/16) FTC and 15% (3/20) benign thyroid nodules. Both CK-19 and NF-kappaB were significantly differentiated DTC, PTC and FTC from benign thyroid nodule (p < 0.0001) with diagnostic accuracy of 89.74%, 94.4% and 77.4% for CK-19 and 91.0%, 90.5% and 83.5% respectively for NF-kappaB. Though CK-19 and NF-kappaB were equally sensitive but CK-19 was most specific in the diagnosis of DTC and PTC. The diagnostic accuracy of beta-catenin was 96% and 94% and accuracy of E-cadherin was 90.1% and 93.9% for the diagnosis of metastatic PTC and FTC respectively. EGFR showed 90% (18/20) of metastatic PTC (p < 0.0001) and sensitivity, specificity and accuracy were 90%, 71.8% and 78.85% respectively. CK-19 and NF-kappaB were accurately diagnosed in DTC, PTC and FTC whereas, NF-kappaB, E-cadherin, beta-catenin and EGFR were strongly expressed in invasive papillary thyroid cancers and FTC, thus can be important diagnostic and prognostic marker for FTC and metastatic PTC. This may be concluded that immunohistochemical expression of panel of markers CK-19, NF-kappaB, E-cadherin, beta-catenin and EGFR can be useful in diagnosis and prognosis of DTC.

Development of a clinically feasible molecular assay to predict recurrence of stage II colon cancer.

The 5-year survival rate for patients with Stage II colon cancer is approximately 75%. However, there is no clinical test available to identify the 25% of patients at high risk of recurrence. We have previously identified a 23-gene signature that predicts individual risk for recurrence. The present study tested this gene signature in an independent group of 123 Stage II patients, and the 23-gene signature was highly informative in identifying patients with distant recurrence in both univariate (hazard ratio [HR] 2.51) and multivariate analyses (HR, 2.40). The composition of this representative patient group also allowed us to refine the 23-gene signature to a 7-gene signature that exhibited a similar prognostic power in both univariate (HR, 2.77) and multivariate analyses (HR, 2.87). Furthermore, we developed this prognostic signature into a clinically feasible test with real-time quantitative PCR using standard fixed paraffin-embedded tumor tissues. When a 110-patient cohort was evaluated with the PCR assay, the 7-gene signature, demonstrated to be a strong prognostic factor in both univariate (HR, 6.89) and multivariate analyses (HR, 14.2). These results clearly show the prognostic value of the predefined gene signature for Stage II colon cancer patients. The ability to identify colon cancer patients with an unfavorable outcome may help patients at high risk for recurrence to seek more aggressive therapy.

Development of a multiplexed urine assay for prostate cancer diagnosis.

BACKGROUND: Several studies have demonstrated the value of DNA methylation in urine-based assays for prostate cancer diagnosis. However, a multicenter validation with a clinical prototype has not been published. METHODS: We developed a multiplexed, quantitative methylation-specific polymerase chain reaction (MSP) assay consisting of 3 methylation markers, GSTP1, RARB, and APC, and an endogenous control, ACTB, in a closed-tube, homogeneous assay format. We tested this format with urine samples collected after digital rectal examination from 234 patients with prostate-specific antigen (PSA) concentrations > or =2.5 microg/L in 2 independent patient cohorts from 9 clinical sites. RESULTS: In the first cohort of 121 patients, we demonstrated 55% sensitivity and 80% specificity, with area under the curve (AUC) 0.69. In the second independent cohort of 113 patients, we found a comparable sensitivity of 53% and specificity of 76% (AUC 0.65). In the first cohort, as well as in a combined cohort, the MSP assay in conjunction with total PSA, digital rectal examination status, and age improved the AUC without MSP, although the difference was not statistically significant. Importantly, the GSTP1 cycle threshold value demonstrated a good correlation (R = 0.84) with the number of cores found to contain prostate cancer or premalignant lesions on biopsy. Moreover, samples that exhibited methylation for either GSTP1 or RARB typically contained higher tumor volumes at prostatectomy than those samples that did not exhibit methylation. CONCLUSIONS: These data confirm and extend previously reported studies and demonstrate the performance of a clinical prototype assay that should aid urologists in identifying men who should undergo biopsy.

Quantitative, spatial resolution of the epigenetic field effect in prostate cancer.

BACKGROUND: Although a field effect in which transformed cells extend beyond morphologically evident tumor has been proposed in cancer, little direct evidence exists as to its magnitude and spatial resolution. We tested this hypothesis using molecular techniques to detect epigenetic changes in the primary tumor and surrounding tissues. METHODS: Ex vivo core biopsies, each spaced approximately 1 mm apart, were generated from 37 unique prostatectomy samples. The first core biopsy was confirmed to be histologically positive for cancer, and the subsequent biopsies were confirmed to be histologically negative. The methylation ratio of GSTP1, APC, RARbeta2, and RASSF1A were measured for all of the 159 cores. RESULTS: No field effect, defined as absence of epigenetically transformed cells, for GSTP1 was observed whereas APC, RARbeta2, and RASSF1A showed a field effect up to 3 mm from the malignant core in three prostatectomy samples. Furthermore, for each case, different patterns of the field effect were observed. The field effect appeared most pronounced with RARbeta2. In 11 prostatectomy samples in which a second focus of cancer was identified, cells harboring RARbeta2 methylation extended a large distance away from the primary tumor in one sample. Bisulfite sequencing of RARbeta2 confirmed the presence of epigenetic aberrations. CONCLUSIONS: This study quantifies previous observations of methylation in histologically negative samples and provides important assessment of field effects based on epigenetic events in cancer. These molecular approaches set the stage for consideration of such data in prospective trials for assessment of surgical margins and prediction of recurrence.

Gene-expression signatures in oncology diagnostics.

The advent of DNA microarray technologies has enabled the development of gene expression signatures that can be used for prognostic and predictive purposes. This new information can change the paradigm of how medicine is practiced, coupling physical examination, pathology and clinical tests with new molecular information. However, many unanswered questions regarding sample acquisition, platform development, signature validation and clinical trial design will need to be addressed before this new medical content will have an impact on the clinical setting. This article will examine some of these issues in greater detail, focusing on tissue type, platform comparison, biospecimen collection and signature validation.

A quantitative reverse transcriptase-polymerase chain reaction assay to identify metastatic carcinoma tissue of origin.

Identifying the primary site in patients with metastatic carcinoma of unknown primary origin can enable more specific therapeutic regimens and may prolong survival. Twenty-three putative tissue-specific markers for lung, colon, pancreatic, breast, prostate, and ovarian carcinomas were nominated by querying a gene expression profile database and by performing a literature search. Ten of these marker candidates were then selected based on validation by reverse transcriptase-polymerase chain reaction (RT-PCR) on 205 formalin-fixed, paraffin-embedded metastatic carcinoma specimens originating from these six and from other cancer types. Next, we optimized the RNA isolation and quantitative RT-PCR methods for these 10 markers and applied the quantitative RT-PCR assay to a set of 260 metastatic tumors. We then built a gene-based algorithm that predicted the tissue of origin of metastatic carcinomas with an overall leave-one-out cross-validation accuracy of 78%. Lastly, our assay demonstrated an accuracy of 76% when tested on an independent set of 48 metastatic samples, 37 of which were either a known primary or initially presented as carcinoma of unknown primary but were subsequently resolved.

Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.

Gene expression signatures have the ability to serve in both prognostic and predictive capacities in patient management. The use of RNA as the starting material and the lability of this analyte, however, dictate that tissues must be snap-frozen or stored in a solution that can maintain the integrity of the RNA. We compared pairs of snap-frozen and RNAlater preservative-suspended tissue from 30 such paired lymph node-negative breast tumors and 21 such paired Dukes' B colon tumors. We assessed the correlation of gene expression profiles and prediction of recurrence based on two prognostic algorithms. Tissues stored in RNAlater preservative generated expression profiles with excellent correlation (average Pearson correlation coefficients of 0.97 and 0.94 for the breast and colon tumor pairs, respectively) compared to those produced by tissues that were snap-frozen. The correlation in the prediction of recurrence was 97% and 95% for the breast and colon tumor pairs, respectively, between these two types of tissue handling protocols. This novel finding demonstrates that prognostic signatures can be obtained from RNAlater preservative-suspended tissues, an important step in bringing gene expression signatures to the clinic.

Molecular and cellular approaches to patient management in oncology.

Many of the techniques that are employed today by pathologists and oncologists to generate a diagnosis, prognosis or prediction of response have not changed over several decades. However, new molecular and cellular technologies will enable more precise and objective decision-making. This review will detail some of the more recent developments in these areas from Veridex, LLC, academic laboratories and other commercial entities. The discussion of molecular technologies will focus on breast sentinel lymph node biopsy, prostate biopsy, carcinoma of unknown primary, prediction of recurrence in lymph node negative colon and breast cancers and pharmacogenomics. The discussion of cellular technologies will focus on the use of circulating cells to serve in both prognostic and predictive capacities and on the use of molecular methods to interrogate the DNA and RNA isolated from these circulating cells.

Novel genes associated with malignant melanoma but not benign melanocytic lesions.

PURPOSE: Cutaneous melanoma is a common, aggressive cancer with increasing incidence. The identification of melanoma-specific deregulated genes could provide molecular markers for lymph node staging assays and further insight into melanoma tumorigenesis. EXPERIMENTAL DESIGN: Total RNA isolated from 45 primary melanoma, 18 benign skin nevi, and 7 normal skin tissue specimens were analyzed on an Affymetrix Hu133A microarray containing 22,000 probe sets. RESULTS: Hierarchical clustering revealed a distinct separation of the melanoma samples from the benign and normal specimens. Novel genes associated with malignant melanoma were identified. Differential gene expression of two melanoma-specific genes, PLAB and L1CAM, were tested by a one-step quantitative reverse transcription-PCR assay on primary malignant melanoma, benign nevi, and normal skin samples, as well as on malignant melanoma lymph node metastasis and melanoma-free lymph nodes. The performance of the markers was compared with conventional melanoma markers such as tyrosinase, gp100, and MART1. CONCLUSION: Our study systematically identified novel melanoma-specific genes and showed the feasibility of using a combination of PLAB and L1CAM in a reverse transcription-PCR assay to differentiate clinically relevant samples containing benign or malignant melanocytes.

Oligodeoxyribonucleotide probe accessibility on a three-dimensional DNA microarray surface and the effect of hybridization time on the accuracy of expression ratios.

BACKGROUND: DNA microarrays are now routinely used to monitor the transcript levels of thousands of genes simultaneously. However, the array fabrication method, hybridization conditions, and oligodeoxyribonucleotide probe length can impact the performance of a DNA microarray platform. RESULTS: We demonstrate solution-phase hybridization behavior of probe:target interactions by showing a strong correlation between the effect of mismatches in probes attached to a three dimensional matrix of a microarray and solution-based, thermodynamic duplex melting studies. The effects of mismatches in the probes attached to the microarray also demonstrate that most, if not all, of the oligodeoxyribonucleotide is available for hybridization. Kinetic parameters were also investigated. As anticipated, hybridization signals increased in a transcript concentration-dependent manner, and mismatch specificity increased with hybridization time. Unexpectedly, hybridization time increased the accuracy of fold changes by relieving the compression observed in expression ratios, and this effect may be more dramatic for larger fold changes. CONCLUSIONS: Taken together, these studies demonstrate that a three-dimensional surface may enable use of shorter oligodeoxyribonucleotide probes and that hybridization time may be critical in improving the accuracy of microarray data.

Expression profiling with oligonucleotide arrays: technologies and applications for neurobiology.

DNA microarrays have been used in applications ranging from the assignment of gene function to analytical uses in prognostics. However, the detection sensitivity, cross hybridization, and reproducibility of these arrays can affect experimental design and data interpretation. Moreover, several technologies are available for fabrication of oligonucleotide microarrays. We review these technologies and performance attributes and, with data sets generated from human brain RNA, present statistical tools and methods to analyze data quality and to mine and visualize the data. Our data show high reproducibility and should allow an investigator to discern biological and regional variability from differential expression. Although we have used brain RNA as a model system to illustrate some of these points, the oligonucleotide arrays and methods employed in this study can be used with cell lines, tissue sections, blood, and other fluids. To further demonstrate this point, we provide data generated from total RNA sample sizes of 200 ng.

Quantitative assessment of the use of modified nucleoside triphosphates in expression profiling: differential effects on signal intensities and impacts on expression ratios.

BACKGROUND: The power of DNA microarrays derives from their ability to monitor the expression levels of many genes in parallel. One of the limitations of such powerful analytical tools is the inability to detect certain transcripts in the target sample because of artifacts caused by background noise or poor hybridization kinetics. The use of base-modified analogs of nucleoside triphosphates has been shown to increase complementary duplex stability in other applications, and here we attempted to enhance microarray hybridization signal across a wide range of sequences and expression levels by incorporating these nucleotides into labeled cRNA targets. RESULTS: RNA samples containing 2-aminoadenosine showed increases in signal intensity for a majority of the sequences. These results were similar, and additive, to those seen with an increase in the hybridization time. In contrast, 5-methyluridine and 5-methylcytidine decreased signal intensities. Hybridization specificity, as assessed by mismatch controls, was dependent on both target sequence and extent of substitution with the modified nucleotide. Concurrent incorporation of modified and unmodified ATP in a 1:1 ratio resulted in significantly greater numbers of above-threshold ratio calls across tissues, while preserving ratio integrity and reproducibility. CONCLUSIONS: Incorporation of 2-aminoadenosine triphosphate into cRNA targets is a promising method for increasing signal detection in microarrays. Furthermore, this approach can be optimized to minimize impact on yield of amplified material and to increase the number of expression changes that can be detected.

A highly reproducible, linear, and automated sample preparation method for DNA microarrays.

DNA microarrays are powerful tools to detect changes in transcript abundance in multiple samples in parallel. However, detection of differential transcript levels requires a reproducible sample (target) preparation method in addition to a high-performance microarray. Therefore, we optimized a target-preparation method that converts the poly(A)(+) RNA fraction of total RNA into complementary DNA, then generates biotin-labeled complementary RNA from the cDNA. We measured the efficiency of incorporation of biotin-containing nucleotides by an enzymatic digestion, followed by resolution via analytical high-performance liquid chromatography (HPLC). When the target was hybridized to a sensitive and reproducible microarray platform, low coefficients of variation in both hybridization intensities and differential expression ratios across target preparations were observed. Nearly identical hybridization intensities and expression ratios are observed regardless of whether poly(A)(+)-enriched RNA or total RNA is used as the starting material. We show the ability to discern biological and production variability through the use of different lots of commercial samples as visualized by hierarchical clustering. Automation of the target-preparation procedure shows equivalence to the manual procedure, reproducible yields of target, and low variability as measured by hybridization to microarrays. Most importantly, RNA mixing experiments show a linear and quantitative amplification in probe hybridization signals for >6000 genes across the entire signal range.

An assessment of Motorola CodeLink microarray performance for gene expression profiling applications.

DNA microarrays enable users to obtain information on differences in transcript abundance on a massively parallel scale. Recently, however, data analyses have revealed potential pitfalls related to image acquisition, variability and misclassifications in replicate measurements, cross-hybridization and sensitivity limitations. We have generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. Together, we have used these tools to optimize performance in an expression profiling study. We demonstrate three significant advantages of the Motorola CodeLink platform: sensitivity of one copy per cell, coefficients of variation of 10% in the hybridization signals across slides and across target preparations, and specificity in distinguishing highly homologous sequences. Slides where oligonucleotide probes are spotted in 6-fold redundancy were used to demonstrate the effect of replication on data quality. Lastly, the differential expression ratios obtained with the CodeLink expression platform were validated against those obtained with quantitative reverse transcription-PCR assays for 54 genes.