Mutational signatures in colon cancer.

ObjectiveRecently, many tumor sequencing studies have inferred and reported on mutational signatures, short nucleotide patterns at which particular somatic base substitutions appear more often. A number of signatures reflect biological processes in the patient and factors associated with cancer risk. Our goal is to infer mutational signatures appearing in colon cancer, a cancer for which environmental risk factors vary by cancer subtype, and compare the signatures to those in adult stem cells from normal colon. We also compare the mutational signatures to others in the literature.ResultsWe apply a probabilistic mutation signature model to somatic mutations previously reported for six adult normal colon stem cells and 431 colon adenocarcinomas. We infer six mutational signatures in colon cancer, four being specific to tumors with hypermutation. Just two signatures explained the majority of mutations in the small number of normal aging colon samples. All six signatures are independently identified in a series of 295 Chinese colorectal cancers

Human hair genealogies and stem cell latency

BACKGROUND: Stem cells divide to reproduce themselves and produce differentiated progeny. A fundamental problem in human biology has been the inability to measure how often stem cells divide. Although it is impossible to observe every division directly, one method for counting divisions is to count replication errors; the greater the number of divisions, the greater the numbers of errors. Stem cells with more divisions should produce progeny with more replication errors. METHODS: To test this approach, epigenetic errors (methylation) in CpG-rich molecular clocks were measured from human hairs. Hairs exhibit growth and replacement cycles and "new" hairs physically reappear even on "old" heads. Errors may accumulate in long-lived stem cells, or in their differentiated progeny that are eventually shed. RESULTS: Average hair errors increased until two years of age, and then were constant despite decades of replacement, consistent with new hairs arising from infrequently dividing bulge stem cells. Errors were significantly more frequent in longer hairs, consistent with long-lived but eventually shed mitotic follicle cells. CONCLUSION: Constant average hair methylation regardless of age contrasts with the age-related methylation observed in human intestine, suggesting that error accumulation and therefore stem cell latency differs among tissues. Epigenetic molecular clocks imply similar mitotic ages for hairs on young and old human heads, consistent with a restart with each new hair, and with genealogies surreptitiously written within somatic cell genomes

A stem cell niche dominance theorem

<p>Abstract</p> <p>Background</p> <p>Multilevelness is a defining characteristic of complex systems. For example, in the intestinal tissue the epithelial lining is organized into crypts that are maintained by a niche of stem cells. The behavior of the system 'as a whole' is considered to emerge from the functioning and interactions of its parts. What we are seeking here is a conceptual framework to demonstrate how the "fate" of intestinal crypts is an emergent property that inherently arises from the complex yet robust underlying biology of stem cells.</p> <p>Results</p> <p>We establish a conceptual framework in which to formalize cross-level principles in the context of tissue organization. To this end we provide a definition for stemness, which is the propensity of a cell lineage to contribute to a tissue fate. We do not consider stemness a property of a cell but link it to the process in which a cell lineage contributes towards tissue (mal)function. We furthermore show that the only logically feasible relationship between the stemness of cell lineages and the emergent fate of their tissue, which satisfies the given criteria, is one of dominance from a particular lineage.</p> <p>Conclusions</p> <p>The dominance theorem, conceived and proven in this paper, provides support for the concepts of niche succession and monoclonal conversion in intestinal crypts as bottom-up relations, while crypt fission is postulated to be a top-down principle.</p

Tissue Photolithography

Tissue lithography will enable physicians and researchers to obtain macromolecules with high purity (greater than 90 percent) from desired cells in conventionally processed, clinical tissues by simply annotating the desired cells on a computer screen. After identifying the desired cells, a suitable lithography mask will be generated to protect the contents of the desired cells while allowing destruction of all undesired cells by irradiation with ultraviolet light. The DNA from the protected cells can be used in a number of downstream applications including DNA sequencing. The purity (i.e., macromolecules isolated form specific cell types) of such specimens will greatly enhance the value and information of downstream applications. In this method, the specific cells are isolated on a microscope slide using photolithography, which will be faster, more specific, and less expensive than current methods. It relies on the fact that many biological molecules such as DNA are photosensitive and can be destroyed by ultraviolet irradiation. Therefore, it is possible to protect the contents of desired cells, yet destroy undesired cells. This approach leverages the technologies of the microelectronics industry, which can make features smaller than 1 micrometer with photolithography. A variety of ways has been created to achieve identification of the desired cell, and also to designate the other cells for destruction. This can be accomplished through chrome masks, direct laser writing, and also active masking using dynamic arrays. Image recognition is envisioned as one method for identifying cell nuclei and cell membranes. The pathologist can identify the cells of interest using a microscopic computerized image of the slide, and appropriate custom software. In one of the approaches described in this work, the software converts the selection into a digital mask that can be fed into a direct laser writer, e.g. the Heidelberg DWL66. Such a machine uses a metalized glass plate (with chrome metallization) on which there is a thin layer of photoresist. The laser transfers the digital mask onto the photoresist by direct writing, with typical best resolution of 2 micrometers. The plate is then developed to remove the exposed photoresist, which leaves the exposed areas susceptible to chemical chrome etch. The etch removes the unprotected chrome. The rest of the photoresist is then removed, by either ultraviolet organic solvent or over-development. The remaining chrome pattern is quickly oxidized by atmospheric exposure (typically within 30 seconds). The ready chrome mask is now applied to the tissue slide and aligned manually, or using automatic software and pre-designed alignment marks. The slide plate sandwich is then exposed to UV to destroy the DNA of the unwanted cells. The slide and plate are separated and the slide is processed in a standard way to prepare for polymerase chain reaction (PCR) and potential identification of cancer sequences

The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns

The analysis of methylation patterns is a promising approach to investigate the genealogy of cell populations in an organism. In a stem cell–niche scenario, sampled methylation patterns are the stochastic outcome of a complex interplay between niche structural features such as the number of stem cells within a niche and the niche succession time, the methylation/demethylation process, and the randomness due to sampling. As a consequence, methylation pattern studies can reveal niche characteristics but also require appropriate statistical methods. The analysis of methylation patterns sampled from colon crypts is a prototype of such a study. Previous analyses were based on forward simulation of the cell content of the whole crypt and subsequent comparisons between simulated and experimental data using a few statistics as a proxy to summarize the data. In this paper we develop a more powerful method to analyze these data based on coalescent modelling and Bayesian inference. Results support a scenario where the colon crypt is maintained by a high number of stem cells; the posterior indicates a number greater than eight and the posterior mode is between 15 and 20. The results also provide further evidence for synergistic effects in the methylation/demethylation process that could for the first time be quantitatively assessed through their long-term consequences such as the coexistence of hypermethylated and hypomethylated patterns in the same colon crypt

Principles, Techniques, and Applications of Tissue Microfluidics

The principle of tissue microfluidics and its resultant techniques has been applied to cell analysis. Building microfluidics to suit a particular tissue sample would allow the rapid, reliable, inexpensive, highly parallelized, selective extraction of chosen regions of tissue for purposes of further biochemical analysis. Furthermore, the applicability of the techniques ranges beyond the described pathology application. For example, they would also allow the posing and successful answering of new sets of questions in many areas of fundamental research. The proposed integration of microfluidic techniques and tissue slice samples is called tissue microfluidics because it molds the microfluidic architectures in accordance with each particular structure of each specific tissue sample. Thus, microfluidics can be built around the tissues, following the tissue structure, or alternatively, the microfluidics can be adapted to the specific geometry of particular tissues. By contrast, the traditional approach is that microfluidic devices are structured in accordance with engineering considerations, while the biological components in applied devices are forced to comply with these engineering presets. The proposed principles represent a paradigm shift in microfluidic technology in three important ways: Microfluidic devices are to be directly integrated with, onto, or around tissue samples, in contrast to the conventional method of off-chip sample extraction followed by sample insertion in microfluidic devices. Architectural and operational principles of microfluidic devices are to be subordinated to suit specific tissue structure and needs, in contrast to the conventional method of building devices according to fluidic function alone and without regard to tissue structure. Sample acquisition from tissue is to be performed on-chip and is to be integrated with the diagnostic measurement within the same device, in contrast to the conventional method of off-chip sample prep and subsequent insertion into a diagnostic device. A more advanced form of tissue integration with microfluidics is tissue encapsulation, wherein the sample is completely encapsulated within a microfluidic device, to allow for full surface access. The immediate applications of these approaches lie with diagnostics of tissue slices and biopsy samples e.g. for cancer but the approaches would also be very useful in comparative genomics and other areas of fundamental research involving heterogeneous tissue samples

Methods and Devices for Micro-Isolation, Extraction, and/or Analysis of Microscale Components

Provided herein are devices and methods for the micro-isolation of biological cellular material. A micro-isolation apparatus described can comprise a photomask that protects regions of interest against DNA-destroying illumination. The micro-isolation apparatus can further comprise photosensitive material defining access wells following illumination and subsequent developing of the photosensitive material. The micro-isolation apparatus can further comprise a chambered microfluidic device comprising channels providing access to wells defined in photosensitive material. The micro-isolation apparatus can comprise a chambered microfluidic device without access wells defined in photosensitive material where valves control the flow of gases or liquids through the channels of the microfluidic device. Also included are methods for selectively isolating cellular material using the apparatuses described herein, as are methods for biochemical analysis of individual regions of interest of cellular material using the devices described herein. Further included are methods of making masking arrays useful for the methods described herein

Numbers of mutations to different types of colorectal cancer

BACKGROUND: The numbers of oncogenic mutations required for transformation are uncertain but may be inferred from how cancer frequencies increase with aging. Cancers requiring more mutations will tend to appear later in life. This type of approach may be confounded by biologic heterogeneity because different cancer subtypes may require different numbers of mutations. For example, a sporadic cancer should require at least one more somatic mutation relative to its hereditary counterpart. METHODS: To better estimate numbers of mutations before transformation, 1,022 colorectal cancers were classified with respect to microsatellite instability (MSI) and germline DNA mismatch repair mutations characteristic of hereditary nonpolyposis colorectal cancer (HNPCC). MSI- cancers were also classified with respect to clinical stage. Ages at cancer and a Bayesian algorithm were used to estimate the numbers of oncogenic mutations required for transformation for each cancer subtype. RESULTS: Ages at MSI+ cancers were consistent with five or six oncogenic mutations for hereditary (HNPCC) cancers, and seven or eight mutations for its sporadic counterpart. Ages at cancer were consistent with seven mutations for sporadic MSI- cancers, and were similar (six to eight mutations) regardless of clinical cancer stage. CONCLUSION: Different biologic subtypes of colorectal cancer appear to require different numbers of oncogenic mutations before transformation. Sporadic MSI+ cancers may require more than a single additional somatic alteration compared to hereditary MSI+ cancers because the epigenetic inactivation of MLH1 commonly observed in sporadic MSI+ cancers may be a multistep process. Interestingly, estimated numbers of MSI- cancer mutations were similar (six to eight mutations) regardless of clinical cancer stage, suggesting a propensity to spread or metastasize does not require additional mutations after transformation. Estimates of oncogenic mutation numbers may help explain some of the biology underlying different cancer subtypes

Epigenetic Subgroups of Esophageal and Gastric Adenocarcinoma with Differential GATA5 DNA Methylation Associated with Clinical and Lifestyle Factors

BACKGROUND: Adenocarcinomas located near the gastroesophageal junction have unclear etiology and are difficult to classify. We used DNA methylation analysis to identify subtype-specific markers and new subgroups of gastroesophageal adenocarcinomas, and studied their association with epidemiological risk factors and clinical outcomes. METHODOLOGY/PRINCIPAL FINDINGS: We used logistic regression models and unsupervised hierarchical cluster analysis of 74 DNA methylation markers on 45 tumor samples (44 patients) of esophageal and gastric adenocarcinomas obtained from a population-based case-control study to uncover epigenetic markers and cluster groups of gastroesophageal adenocarcinomas. No distinct epigenetic differences were evident between subtypes of gastric and esophageal cancers. However, we identified two gastroesophageal adenocarcinoma subclusters based on DNA methylation profiles. Group membership was best predicted by GATA5 DNA methylation status. We analyzed the associations between these two epigenetic groups and exposure using logistic regression, and the associations with survival time using Cox regression in a larger set of 317 tumor samples (278 patients). There were more males with esophageal and gastric cardia cancers in Cluster Group 1 characterized by higher GATA5 DNA methylation values (all p<0.05). This group also showed associations of borderline statistical significance with having ever smoked (p-value = 0.07), high body mass index (p-value = 0.06), and symptoms of gastroesophageal reflux (p-value = 0.07). Subjects in cluster Group 1 showed better survival than those in Group 2 after adjusting for tumor differentiation grade, but this was not found to be independent of tumor stage. CONCLUSIONS/SIGNIFICANCE: DNA methylation profiling can be used in population-based studies to identify epigenetic subclasses of gastroesophageal adenocarcinomas and class-specific DNA methylation markers that can be linked to epidemiological data and clinical outcome. Two new epigenetic subgroups of gastroesophageal adenocarcinomas were identified that differ to some extent in their survival rates, risk factors of exposure, and GATA5 DNA methylation