A suite of DNA methylation markers that can detect most common human cancers

Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available—TCGA Illumina HumanMethylation450 data with over 8,500 tumors—in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC >0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, SEPT9 and GSTP1, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is MIR129-2. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.     

New molecular tumor markers for endometrial cancer

Although the International Federation of Gynecology and Obstetrics officially changed the classification system of endometrial cancer from a clinically staged to a surgically staged disease in 1988, optimal management of patients with endometrial cancer is still controversial. Gynecologists happen to experience that patients with tumors that are identical in grade and stage often have significantly different clinical outcomes or responses to therapy. In order to identify an objective biological factor correlating with tumor aggressiveness, many tumor markers have been investigated. So far, CA125 is one of the most reliable tumor marker for adenocarcinoma of the uterus and frequently used in a clinical setting. Recently, with the advent of molecular biological techniques, many genes and regions of the genome related to endometrial cancer have been identified. We undertook a genome-wide screening to detect genetic changes by comparative genomic hybridization (CGH) in primary endometrioid cancers, since CGH analysis provides comprehensive information concerning relative chromosomal losses and gains in tumors by a single hybridization. In this paper, the usefulness of serum tumor markers and the new promising molecular tumor markers for endometrial cancer are discussed.     

Southern and fluorescent in situ hybridization detect three RAPD-generated PCR products useful as introgression markers in Petunia

 Fluorescent in situ hybridization (FISH) was used to reveal the intrachromosomal organization of 11 RAPD markers localized on the genetic map of Petunia hybrida. The cloned RAPD markers were analyzed by means of Southern hybridization to determine their level of sequence repetition and their specificity in different Petunia species with 2n=14 and 18 chromosomes. The same probes were then used in FISH experiments. Most of the RAPD clones studied showed high sequence repetition and no species specificity. Moreover, FISH analysis showed that these probes could belong to multilocus families as evidenced by the multiple FISH signals dispersed throughout the genome and present on every chromosome. Only 3 RAPD clones revealed species specificity at the chromosome level. Clones OPJ18-250 and V20-350 were only detected by FISH in the white-flowered species and clone OPV08-600 only in species with colored flowers. They were localized at one two or three pairs of fluorescent sites. The localization of OPJ18-250 at a unique site on chromosome VI give us the opportunity to compare genetic and physical distances. Received: 19 June 1998 / Accepted: 15 July 1998     

Generating molecular markers from zooxanthellate cnidarians

Genetic techniques are providing tools that are necessary to answer questions concerning the ecology and evolution of cnidarians that, until recently, could not be easily addressed. In developing molecular markers for cnidarians with algal symbionts (zooxanthellae), however, caution must be used to ensure the markers in question are derived from the cnidarian host and not zooxanthellae. Unless the DNA template is from asymbiotic tissue, both host and symbiont genomes are present in the DNA template and zooxanthella-specific markers are often inadvertently generated. Steps should be taken to minimize the contamination by zooxanthella DNA in the template, and the origin of the molecular marker (host or symbiont) must be verified. Including zooxanthella-specific markers in analyses for cnidarians will confound interpretations of the results as biogeographic and phylogeographic patterns of zooxanthellae do not necessarily reflect those of the host.     

Multiple target-specific molecular imaging agents detect liver cancer in a preclinical model

Liver cancer is the fifth most common cause of cancer deaths worldwide. Noninvasive diagnosis is difficult and the disease heterogeneity reduces the accuracy of pathological assays. Improvement in diagnostic imaging of specific molecular disease markers has provided hope for accurate and early noninvasive detection of liver cancer. However, all current imaging technologies, including ultrasonography, computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging, are not specific targets for detection of liver cancer. The aim of this study was to test the feasibility of injecting a cocktail of specific molecular imaging agents to noninvasively image liver cancer. The target-specific cocktail contained agents for imaging the neovasculature (RGD peptide), matrix metalloproteinase (MMP), and glucose transport (18F-fluorodeoxyglucose [18F-FDG]). Imaging studies were performed in liver cancer cells and xenograft models. The distribution of MMP at the intracellular level was imaged by confocal microscopy. RGD, MMP, and 18F-FDG were imaged on tumor-bearing mice using PET, CT, X-ray, and multi-wavelength optical imaging modalities. Image data demonstrated that each agent bound to a specific disease target component. The same liver cancer xenograft contained multiple disease markers. Those disease markers were heterogenetically distributed in the same tumor nodule. The molecular imaging agents had different distributions in the whole body and inside the tumor nodule. All target-specific agents yielded high tumor-to-background ratios after injection. In conclusion, target-specific molecular imaging agents can be used to study liver cancer in vitro and in vivo. Noninvasive multimodal/multi-target-specific molecular imaging agents could provide tools to simultaneously study multiple liver cancer components.     

Multiple species‐specific molecular markers using nanofluidic array as a tool to detect prey DNA from carnivore scats

Large carnivore feeding ecology plays a crucial role for management and conservation for predators and their prey. One of the keys to this kind of research is to identify the species composition in the predator diet, for example, prey determination from scat content. DNA‐based methods applied to detect prey in predators’ scats are viable alternatives to traditional macroscopic approaches, showing an increased reliability and higher prey detection rate. Here, we developed a molecular method for prey species identification in wolf (Canis lupus) scats using multiple species‐specific marker loci on the cytochrome b gene for 18 target species. The final panel consisted of 80 assays, with a minimum of four markers per target species, and that amplified specifically when using a high‐throughput Nanofluidic array technology (Fluidigm Inc.). As a practical example, we applied the method to identify target prey species DNA in 80 wolf scats collected in Sweden. Depending on the number of amplifying markers required to obtain a positive species call in a scat, the success in determining at least one prey species from the scats ranged from 44% to 92%. Although we highlight the need to evaluate the optimal number of markers for sensitive target species detection, the developed method is a fast and cost‐efficient tool for prey identification in wolf scats and it also has the potential to be further developed and applied to other areas and large carnivores as well.     

The molecular markers of cancer stem cells in head and neck tumors

Head and neck cancer (HNC) is the six most common malignancy worldwide leading to more than 350,000 deaths annually. Despite recent advances in treatment modalities for these patients, there has been only a slight improvement of prognosis. As cancer stem cells (CSCs) have been implicated in tumor cell survival, progression, and response to therapy, the identification of this tumor subpopulation would have important therapeutic and prognostic implications. In this structured appraisal of the literature, Embase, PubMed, and Ovid were searched for publications that investigated CSC markers of HNC in humans. The search was conducted under the PRISMA guidelines with clear inclusion and exclusion criteria for articles published in the last two decades. The review process resulted in the identification of some key CSC-associated molecules such as CD44, ALDH1, CD133, Oct3/4, Nanog, and Sox2, although a single common CSC sorting marker could not be found. These biomarkers were identified in a range of HNCs but the most common one was squamous cell carcinoma (SCC), predominantly oral SCC. Patient cohorts were of variable size (3–195 individuals) and the most common technique used for detection was immunohistochemistry. Some of the molecules were associated with poor prognosis and may be able to inform the choice of appropriate treatment for these patients.     

FLOTAC can detect parasitic and pseudoparasitic elements in reptiles

Reptiles have increased in popularity worldwide; snakes and lizards are frequently used as pets. As a consequence of their popularity, the interest of the scientific community in these animals has increased. In order to acquire epidemiological data on the parasitic infections affecting reptiles in Italy a survey was carried out in 125 snakes and 25 lizards bred in the Campania region of southern Italy. Individual fecal samples were collected and FLOTAC was used for copromicroscopic diagnosis. Eimeriidae, oxyurids, strongylids, other gastro-intestinal nematodes and pulmonary nematodes were the most representative parasites found. Eggs of pseudoparasites (mites, oxyurids and trichurids affecting rodents) were also found. The use of FLOTAC for diagnosis of parasitic infections in reptiles has demonstrated to be a rapid and sensitive test to improve diagnosis and acquire new information on the parasitological fauna of reptiles.     

Nonlinear ultrasound can detect accumulated damage in human bone

Bone micro-damage is commonly accepted as a relevant parameter for fracture risk assessment, but there is no available technique for its non-invasive characterization. The objective of this work is to study the potential of nonlinear ultrasound for damage detection in human bone. Ultrasound is particularly desirable due to its non-invasive and non-ionizing characteristics. We show results illustrating the correlation of progressive fatigue of human bone samples to their nonlinear dynamical response. In our experiments, damage was induced in 30 samples of diaphyseal human femur using fatigue cycling. At intervals in the cycling, the nonlinear response of the samples was assessed applying Nonlinear Resonant Ultrasound Spectroscopy (NRUS). The nonlinear parameter alpha, which in other materials correlates with the quantity of damage, dramatically increased with the number of mechanical testing cycles. We find a large spread in alpha in the pristine samples and infer that the spread is due to damage differences in the sample population. As damage accumulates during cycling, we find that alpha is much more sensitive to damage than other quantities measured, including the slope and hysteresis of the load/displacement curve, and the dynamic wavespeed. To our knowledge, this study represents the first application of the concept of nonlinear dynamic elasticity to human bone. The results are promising, suggesting the value of further work on this topic. Ultimately, the approach may have merit for in vivo bone damage characterization.     

Equivalence of single- and multilocus markers: power to detect linkage with composite markers derived from biallelic loci

The reintroduction of biallelic markers, now in the form of single-nucleotide polymorphisms (SNPs), has again raised concerns about the practicality of the use of markers with low heterozygosity for genomic screening for complex traits, even if thousands of such markers are available. Like the early blood-group markers (e.g., Rh and MNS), tightly linked biallelic SNPs can be combined into composite markers with heterozygosity similar to that of short-tandem-repeat polymorphisms. The assumptions that underlie the equivalence between single-locus multiallelic and composite markers are presented. We used computer simulation to determine the power of the Haseman-Elston test for linkage with composite markers when not all of these assumptions hold. The Genometric Analysis Simulation Program was used to simulate continuous and discrete traits, one single-locus four-allele marker, and six biallelic markers. We studied composite markers created from pairs, trios, and quartets of biallelic markers in nuclear families and in independent sib pairs. The power to detect linkage with a two-point approach for composite markers and with a multipoint approach that incorporated all six biallelic markers was compared with that for a single-locus, four-allele reference marker. Although the power to detect linkage with a single biallelic marker was considerably less than that of the reference marker, the power to detect linkage with two- and three-locus composite markers was quite similar to that of the reference marker. The power to detect linkage with four-locus composite markers was similar to that of a multipoint approach.     

Extinction can be estimated from moderately sized molecular phylogenies

Hundreds of studies have been dedicated to estimating speciation and extinction from phylogenies of extant species. Although it has long been known that estimates of extinction rates using trees of extant organisms are often uncertain, an influential paper by Rabosky (2010) suggested that when birth rates vary continuously across the tree, estimates of the extinction fraction (i.e., extinction rate/speciation rate) will appear strongly bimodal, with a peak suggesting no extinction and a peak implying speciation and extinction rates are approaching equality. On the basis of these results, and the realistic nature of this form of rate variation, it is now generally assumed by many practitioners that extinction cannot be understood from molecular phylogenies alone. Here, we reevaluated and extended the analyses of Rabosky (2010) and come to the opposite conclusion—namely, that it is possible to estimate extinction from molecular phylogenies, even with model violations due to heritable variation in diversification rate. Note that while it may be tempting to interpret our study as advocating the application of simple birth–death models, our goal here is to show how a particular model violation does not necessitate the abandonment of an entire field: use prudent caution, but do not abandon all hope.     

Genetic spatial autocorrelation can readily detect sex-biased dispersal

Sex-biased dispersal is expected to generate differences in the fine-scale genetic structure of males and females. Therefore, spatial analyses of multilocus genotypes may offer a powerful approach for detecting sex-biased dispersal in natural populations. However, the effects of sex-biased dispersal on fine-scale genetic structure have not been explored. We used simulations and multilocus spatial autocorrelation analysis to investigate how sex-biased dispersal influences fine-scale genetic structure. We evaluated three statistical tests for detecting sex-biased dispersal: bootstrap confidence intervals about autocorrelation r values and recently developed heterogeneity tests at the distance class and whole correlogram levels. Even modest sex bias in dispersal resulted in significantly different fine-scale spatial autocorrelation patterns between the sexes. This was particularly evident when dispersal was strongly restricted in the less-dispersing sex (mean distance <200 m), when differences between the sexes were readily detected over short distances. All tests had high power to detect sex-biased dispersal with large sample sizes (n ≥ 250). However, there was variation in type I error rates among the tests, for which we offer specific recommendations. We found congruence between simulation predictions and empirical data from the agile antechinus, a species that exhibits male-biased dispersal, confirming the power of individual-based genetic analysis to provide insights into asymmetries in male and female dispersal. Our key recommendations for using multilocus spatial autocorrelation analyses to test for sex-biased dispersal are: (i) maximize sample size, not locus number; (ii) concentrate sampling within the scale of positive structure; (iii) evaluate several distance class sizes; (iv) use appropriate methods when combining data from multiple populations; (v) compare the appropriate groups of individuals.     

A new method to estimate relatedness from molecular markers

Four major problems can affect the efficiency of methods developed to estimate relatedness between individuals from information of molecular markers: (i) some of them are dependent on the knowledge of the true allelic frequencies in the base population; (ii) they assume that all loci are unlinked and in Hardy-Weinberg and linkage equilibrium; (iii) pairwise methods can lead to incongruous assignations because they take into account only two individuals at a time; (iv) most are usually constructed for particular structured populations (only consider a few relationship classes, e.g. full-sibs vs. unrelated). We have developed a new approach to estimate relatedness that is free from the above limitations. The method uses a 'blind search algorithm' (actually simulated annealing) to find the genealogy that yield a co-ancestry matrix with the highest correlation with the molecular co-ancestry matrix calculated using the markers. Thus (i and ii) it makes no direct assumptions about allelic frequencies or Hardy-Weinberg and linkage equilibrium; (iii) it always provide congruent relationships, as it considers all individuals at a time; (iv) degrees of relatedness can be as complex as desired just increasing the 'depth' (i.e. number of generations) of the proposed genealogies. Computer simulations have shown that the accuracy and robustness against genotyping errors of this new approach is comparable to that of other proposed methods in those particular situations they were developed for, but it is more flexible and can cope with more complex situations.     

The influence of HER2 genotypes as molecular markers in ovarian cancer outcome

A relevant clinical problem in the treatment of ovarian cancer (OC) is the development of resistance to chemotherapy, frequently due to genetic variations in enzymes and receptors. Changes in the HER2 receptor have been associated with breast and ovarian cancers. The role of a polymorphism in the HER2 gene in the clinical outcome of OC patients was investigated in this study. We characterized DNA samples from 111 patients with OC treated with cisplatin and paclitaxel, using PCR-RFLP. Our results indicate that patients carrying the valine homozygotic genotype present a lower overall survival mean, suggesting a role for this polymorphism in the outcome of ovarian cancer patients. The G allele has been implicated in the formation of active HER2 receptors, with a more aggressive phenotype. We hypothesize that HER2 genotypes can be predictive biomarkers in ovarian cancer, contributing to a genetic individual profile of great interest in clinical oncology.