Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.

Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics.

Visualizing disease associations: graphic analysis of frequency distributions as a function of age using moving average plots (MAP) with application to Alzheimer's and Parkinson's disease.

Age-related variation in marker frequency can be a confounder in association studies, leading to both false-positive and false-negative findings and subsequently to inconsistent reproducibility. We have developed a simple method, based on a novel extension of moving average plots (MAP), which allows investigators to inspect the frequency data for hidden age-related variations. MAP uses the standard case-control association data and generates a birds-eye view of the frequency distributions across the age spectrum; a picture in which one can see if, how, and when the marker frequencies in cases differ from that in controls. The marker can be specified as an allele, genotype, haplotype, or environmental factor; and age can be age-at-onset, age when subject was last known to be unaffected, or duration of exposure. Signature patterns that emerge can help distinguish true disease associations from spurious associations due to age effects, age-varying associations from associations that are uniform across all ages, and associations with risk from associations with age-at-onset. Utility of MAP is illustrated by application to genetic and epidemiological association data for Alzheimer's and Parkinson's disease. MAP is intended as a descriptive method, to complement standard statistical techniques. Although originally developed for age patterns, MAP is equally useful for visualizing any quantitative trait.

Genetic versus chemoprotective activation of Nrf2 signaling: overlapping yet distinct gene expression profiles between Keap1 knockout and triterpenoid-treated mice.

Loss of NF-E2-related factor 2 (Nrf2) signaling increases susceptibility to acute toxicity, inflammation and carcinogenesis in mice due to the inability to mount adaptive responses. In contrast, disruption of Keap1 (a cytoplasmic modifier of Nrf2 turnover) protects against these stresses in mice, although inactivating mutations in Keap1 have been identified recently in some human cancers. Global characterization of Nrf2 activation is important to exploit this pathway for chemoprevention in healthy, yet at-risk individuals and also to elucidate the consequences of hijacking the pathway in Keap1-mutant human cancers. Liver-targeted conditional Keap1-null, Albumin-Cre:Keap1((flox/-)) (CKO) mice provide a model of genetic activation of Nrf2 signaling. By coupling global gene expression analysis of CKO mice with analysis of pharmacologic activation using the synthetic oleanane triterpenoid 1-[2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oyl]imidazole (CDDO-Im), we are able to gain insight into pathways affected by Nrf2 activation. CDDO-Im is an extremely potent activator of Nrf2 signaling. CKO mice were used to identify genes modulated by genetic activation of Nrf2 signaling. The CKO response was compared with hepatic global gene expression changes in wild-type mice treated with CDDO-Im at a maximal Nrf2 activating dose. The results show that genetic and pharmacologic activation of Nrf2 signaling modulates pathways beyond detoxication and cytoprotection, with the largest cluster of genes associated with lipid metabolism. Genetic activation of Nrf2 results in much larger numbers of detoxication and lipid metabolism gene changes. Additionally, analysis of pharmacologic activation suggests that Nrf2 is the primary mediator of CDDO-Im activity, though other cell-signaling targets are also modulated following an oral dose of 30 micromol/kg.

Prospectively gated transverse coronary CT angiography versus retrospectively gated helical technique: improved image quality and reduced radiation dose.

PURPOSE: To retrospectively compare image quality, radiation dose, and blood vessel assessability for coronary artery computed tomographic (CT) angiograms obtained with a prospectively gated transverse (PGT) CT technique and a retrospectively gated helical (RGH) CT technique. MATERIALS AND METHODS: This HIPAA-compliant study received a waiver for approval from the institutional review board, including one for informed consent. Coronary CT angiograms obtained with 64-detector row CT were retrospectively evaluated in 203 clinical patients. A routine RGH technique was evaluated in 82 consecutive patients (44 males, 38 females; mean age, 55.6 years). The PGT technique was then evaluated in 121 additional patients (71 males, 50 females; mean age, 56.7 years). All images were evaluated for image quality, estimated radiation dose, and coronary artery segment assessability. Differences in image quality score were evaluated by using a proportional odds logistic regression model, with main effects for three readers, two techniques, and four arteries. RESULTS: The mean effective dose for the group with the PGT technique was 2.8 mSv; this represents an 83% reduction as compared with that for the group with the RGH technique (mean, 18.4 mSv; P < .001). The image quality score for each of the arteries, as well as the overall combined score, was significantly greater for images obtained with PGT technique than for images obtained with RGH technique. The combined mean image quality score was 4.791 for images obtained with PGT technique versus 4.514 for images obtained with RGH technique (proportional odds model odds ratio, 2.8; 95% confidence interval: 1.7, 4.8). The percentage of assessable coronary artery segments was 98.6% (1196 of 1213) for images obtained with PGT technique versus 97.9% (1741 of 1778) for images obtained with RGH technique (P = .83). CONCLUSION: PGT coronary CT angiography offers improved image quality and substantially reduced effective radiation dose compared with traditional RGH coronary CT angiography.

Exploring gene-environment interactions in Parkinson's disease.

The objective of this study was to explore combined effects of four candidate susceptibility genes and two exposures on Parkinson's disease (PD) risk; namely, alpha-synuclein (SNCA) promoter polymorphism REP1, microtubule-associated protein tau (MAPT) H1/H2 haplotypes, apolipoprotein E (APOE) epsilon2/epsilon3/epsilon4 polymorphism, ubiquitin carboxy-terminal esterase L1 (UCHL1) S18Y variant, cigarette smoking and caffeinated coffee consumption. 932 PD patients and 664 control subjects from the NeuroGenetics Research Consortium, with complete data on all six factors, were studied. Uniform protocols were used for diagnosis, recruitment, data collection and genotyping. A logistic regression model which included gene-exposure interactions was applied. Likelihood ratio tests (LRTs) were used for significance testing and Bayesian inference was used to estimate odds ratios (ORs). MAPT (P = 0.007), SNCA REP1 (P = 0.012), smoking (P = 0.001), and coffee (P = 0.011) were associated with PD risk. Two novel interactions were detected: APOE with coffee (P = 0.005), and REP1 with smoking (P = 0.021). While the individual main effects were modest, each yielding OR < 1.6, the effects were cumulative, with some combinations reaching OR = 12.6 (95% CI: 5.9-26.8). This study provides evidence for the long-held notion that PD risk is modulated by cumulative and interactive effects of genes and exposures. Furthermore, the study demonstrates that while interaction studies are useful for exploring risk relationships that might otherwise go undetected, results should be interpreted with caution because of the inherent loss of power due to multiple testing. The novel findings of this study that warrant replication are the evidence for interaction of coffee with APOE, and of smoking with REP1 on PD risk.

One step closer to fixing association studies: evidence for age- and gender-specific allele frequency variations and deviations from Hardy-Weinberg expectations in controls.

Association studies are the most powerful method available for identifying modest gene effects in complex disorders, but they often produce inconsistent results. With the rapidly growing SNP databases, haplotype maps and high throughput genotyping, the use of association studies is expected to increase; therefore, it is critical and timely that the problems with study design are identified and fixed. We questioned if unrecognized allele and genotype frequency variations in controls could be responsible for some of the inconsistent association findings. We performed a population genetic study of apolipoprotein E (APOE) and cytochrome P450 2D6 (CYP2D6) in 1,748 individuals ranging in age from newborns to centenarians. Although APOE and CYP2D6 are two of the most commonly used candidate genes, this is the first study to examine age- and gender-specific frequency distributions over the entire age spectrum, using a large, ethnically and geographically uniform population. We found significant, previously unrecognized variations in APOE allele frequencies, and deviations from Hardy-Weinberg expectations in CYP2D6 genotype frequencies starting at birth. The allele frequency variations within controls were larger than some reported case-control differences. We demonstrate that unrecognized frequency fluctuations in controls are a serious and potentially common confounder whose impact on association studies has not been appreciated, and one that can be addressed with proper study design. We recommend that population genetic studies be performed on commonly used candidate markers and that rigorous standards be applied for case-control matching.

Model-based detection of lung nodules in computed tomography exams. Thoracic computer-aided diagnosis.

RATIONALE AND OBJECTIVES: In this study, we developed a prototype model-based computer aided detection (CAD) system designed to automatically detect both solid and subsolid pulmonary nodules in computed tomography (CT) images. By using this CAD algorithm, along with the radiologist's initial interpretation, we aim to improve the sensitivity of radiologic readings of CT lung exams. MATERIALS AND METHODS: We have developed a model-based CAD algorithm through the use of precise mathematic models that capture scanner physics and anatomic information. Our model-based CAD algorithm uses multiple segmentation algorithms to extract noteworthy structures in the lungs and a Bayesian statistical model selection framework to determine the probability of various anatomical events throughout the lung. We tested this algorithm on 50 low-dose CT lung cancer screening cases in which ground truth was produced through readings by three expert chest radiologists. RESULTS: Using this model-based CAD algorithm on 50 low-dose CT cases, we measured potential sensitivity improvements of 7% and 5% in two radiologists with respect to all noncalcified nodules, solid and subsolid, greater than 5 mm in diameter. The third radiologist did not miss any nodules in the ground truth set. The CAD algorithm produced 8.3 false positives per case. CONCLUSION: Our prototype CAD system demonstrates promising results as a tool to improve the quality of radiologic readings by increasing radiologist sensitivity. A significant advantage of this model-based approach is that it can be easily extended to support additional anatomic models as clinical understanding and scanning practices improve.