Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes.

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

Demonstration of DSI-semen--A novel DNA methylation-based forensic semen identification assay.

Determining whether the source tissue of biological material is semen is important in confirming sexual assaults, which account for a considerable percentage of crime cases. The gold standard for confirming the presence of semen is microscopic identification of sperm cells, however, this method is labor intensive and operator-dependent. Protein-based immunologic assays, such as PSA, are highly sensitive and relatively fast, but suffer from low specificity in some situations. In addition, proteins are less stable than DNA under most environmental insults. Recently, forensic tissue identification advanced with the development of several approaches based on mRNA and miRNA for identification of various body fluids. Herein is described DNA source identifier (DSI)-semen, a DNA-based assay that determines whether the source tissue of a sample is semen based on detection of semen-specific methylation patterns in five genomic loci. The assay is comprised of a simple single tube biochemical procedure, similar to DNA profiling, followed by automatic software analysis, yielding the identification (semen/non-semen) accompanied by a statistical confidence level. Three additional internal control loci are used to ascertain the reliability of the results. The assay, which aims to replace microscopic examination, can easily be integrated by forensic laboratories and is automatable. The kit was tested on 135 samples of semen, saliva, venous blood, menstrual blood, urine, and vaginal swabs and the identification of semen vs. non-semen was correct in all cases. In order to test the assay's applicability in "real-life" situations, 33 actual casework samples from the forensic biological lab of the Israeli police were analyzed, and the results were compared with microscopic examination performed by Israeli police personnel. There was complete concordance between both analyses except for one sample, in which the assay identified semen whereas no sperm was seen in the microscope. This sample likely represents true semen because sperm cells were detected from an adjacent sample from the same garment, therefore in this case the assay appears to be more sensitive than the microscopic examination. These results demonstrate that this assay is a bona fide confirmatory test for semen.

Cell lineage analysis of the mammalian female germline.

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote). We show that, in the reconstructed mouse cell lineage trees, oocytes form clusters that are separate from hematopoietic and mesenchymal stem cells, both in young and old mice, indicating that these populations belong to distinct lineages. Furthermore, while cumulus cells sampled from different ovarian follicles are distinctly clustered on the reconstructed trees, oocytes from the left and right ovaries are not, suggesting a mixing of their progenitor pools. We also observed an increase in oocyte depth with mouse age, which can be explained either by depth-guided selection of oocytes for ovulation or by post-natal renewal. Overall, our study sheds light on substantial novel aspects of female germline preservation and development.

DNA methylation-based forensic tissue identification.

Identifying the source tissue of biological material found at crime scenes can be very informative in a number of cases. Despite their usefulness, current visual, catalytic, enzymatic, and immunologic tests for presumptive and confirmatory tissue identification are applicable only to a subset of samples, might suffer limitations such as low specificity, lack of sensitivity, and are substantially impacted by environmental insults. Moreover these assays are incompatible and thus cannot be multiplexed. Thus they are less amenable to automation. In addition their results are operator-dependent. A better alternative approach is tissue identification based on messenger RNA (mRNA) or microRNA (miRNA); however, RNA is not as stable as DNA, and requires the use of non-standard procedures by forensic laboratories. Herein a DNA-based assay is described that enables tissue identification based on detection of tissue-specific methylation patterns. DNA samples are subjected to digestion by a methylation-sensitive restriction endonuclease followed by multiplex amplification of specific genomic targets with fluorescent-labeled primers, capillary electrophoresis of amplification products, and automatic signal analysis by dedicated software, yielding the source tissue of the sample. The single tube assay was designed for easy integration by forensic laboratories (as the assay utilizes the same platforms as current forensic STR profiling). The system is fully automatable, provides operator-independent results, and allows combining tissue identification with profiling in a single procedure. The assay was tested on 50 DNA samples from blood, saliva, semen, and skin epidermis, and the source tissue was successfully identified in all cases. Detection of semen and DNA profiling were combined into one assay and the ability to detect mixtures of semen and saliva in various ratios was demonstrated. The assay correctly detected semen in all samples where it was present, and the calculated percentage of semen was comparable to the fraction of semen in the samples. The results demonstrate that methylation-based tissue identification is more than a proof-of-concept. The methodology holds promise as another viable forensic DNA analysis tool for characterization of biological materials.

Authentication of forensic DNA samples.

Over the past twenty years, DNA analysis has revolutionized forensic science, and has become a dominant tool in law enforcement. Today, DNA evidence is key to the conviction or exoneration of suspects of various types of crime, from theft to rape and murder. However, the disturbing possibility that DNA evidence can be faked has been overlooked. It turns out that standard molecular biology techniques such as PCR, molecular cloning, and recently developed whole genome amplification (WGA), enable anyone with basic equipment and know-how to produce practically unlimited amounts of in vitro synthesized (artificial) DNA with any desired genetic profile. This artificial DNA can then be applied to surfaces of objects or incorporated into genuine human tissues and planted in crime scenes. Here we show that the current forensic procedure fails to distinguish between such samples of blood, saliva, and touched surfaces with artificial DNA, and corresponding samples with in vivo generated (natural) DNA. Furthermore, genotyping of both artificial and natural samples with Profiler Plus((R)) yielded full profiles with no anomalies. In order to effectively deal with this problem, we developed an authentication assay, which distinguishes between natural and artificial DNA based on methylation analysis of a set of genomic loci: in natural DNA, some loci are methylated and others are unmethylated, while in artificial DNA all loci are unmethylated. The assay was tested on natural and artificial samples of blood, saliva, and touched surfaces, with complete success. Adopting an authentication assay for casework samples as part of the forensic procedure is necessary for maintaining the high credibility of DNA evidence in the judiciary system.

Cell lineage analysis of a mouse tumor.

Revealing the lineage relations among cancer cells can shed light on tumor growth patterns and metastasis formation, yet cell lineages have been difficult to come by in the absence of a suitable method. We previously developed a method for reconstructing cell lineage trees from genomic variability caused by somatic mutations. Here, we apply the method to cancer and reconstruct, for the first time, a lineage tree of neoplastic and adjacent normal cells obtained by laser microdissection from tissue sections of a mouse lymphoma. Analysis of the reconstructed tree reveals that the tumor initiated from a single founder cell, approximately 5 months before diagnosis, that the tumor grew in a physically coherent manner, and that the average number of cell divisions accumulated in cancerous cells was almost twice than in adjacent normal lung epithelial cells but slightly less than the expected figure for normal B lymphocytes. The cells were also genotyped at the TP53 locus, and neoplastic cells were found to share a common mutation, which was most likely present in a heterozygous state. Our work shows that the ability to obtain data regarding the physical appearance, precise anatomic position, genotypic profile, and lineage position of single cells may be useful for investigating cancer development, progression, and interaction with the microenvironment.

Reconstruction of cell lineage trees in mice.

The cell lineage tree of a multicellular organism represents its history of cell divisions from the very first cell, the zygote. A new method for high-resolution reconstruction of parts of such cell lineage trees was recently developed based on phylogenetic analysis of somatic mutations accumulated during normal development of an organism. In this study we apply this method in mice to reconstruct the lineage trees of distinct cell types. We address for the first time basic questions in developmental biology of higher organisms, namely what is the correlation between the lineage relation among cells and their (1) function, (2) physical proximity and (3) anatomical proximity. We analyzed B-cells, kidney-, mesenchymal- and hematopoietic-stem cells, as well as satellite cells, which are adult skeletal muscle stem cells isolated from their niche on the muscle fibers (myofibers) from various skeletal muscles. Our results demonstrate that all analyzed cell types are intermingled in the lineage tree, indicating that none of these cell types are single exclusive clones. We also show a significant correlation between the physical proximity of satellite cells within muscles and their lineage. Furthermore, we show that satellite cells obtained from a single myofiber are significantly clustered in the lineage tree, reflecting their common developmental origin. Lineage analysis based on somatic mutations enables performing high resolution reconstruction of lineage trees in mice and humans, which can provide fundamental insights to many aspects of their development and tissue maintenance.

Estimating cell depth from somatic mutations.

The depth of a cell of a multicellular organism is the number of cell divisions it underwent since the zygote, and knowing this basic cell property would help address fundamental problems in several areas of biology. At present, the depths of the vast majority of human and mouse cell types are unknown. Here, we show a method for estimating the depth of a cell by analyzing somatic mutations in its microsatellites, and provide to our knowledge for the first time reliable depth estimates for several cells types in mice. According to our estimates, the average depth of oocytes is 29, consistent with previous estimates. The average depth of B cells ranges from 34 to 79, linearly related to the mouse age, suggesting a rate of one cell division per day. In contrast, various types of adult stem cells underwent on average fewer cell divisions, supporting the notion that adult stem cells are relatively quiescent. Our method for depth estimation opens a window for revealing tissue turnover rates in animals, including humans, which has important implications for our knowledge of the body under physiological and pathological conditions.

Amplification of multiple genomic loci from single cells isolated by laser micro-dissection of tissues.

BACKGROUND: Whole genome amplification (WGA) and laser assisted micro-dissection represent two recently developed technologies that can greatly advance biological and medical research. WGA allows the analysis of multiple genomic loci from a single genome and has been performed on single cells from cell suspensions and from enzymatically-digested tissues. Laser micro-dissection makes it possible to isolate specific single cells from heterogeneous tissues. RESULTS: Here we applied for the first time WGA on laser micro-dissected single cells from stained tissue sections, and developed a protocol for sequentially performing the two procedures. The combined procedure allows correlating the cell's genome with its natural morphology and precise anatomical position. From each cell we amplified 122 genomic and mitochondrial loci. In cells obtained from fresh tissue sections, 64.5% of alleles successfully amplified to approximately 700000 copies each, and mitochondrial DNA was amplified successfully in all cells. Multiplex PCR amplification and analysis of cells from pre-stored sections yielded significantly poorer results. Sequencing and capillary electrophoresis of WGA products allowed detection of slippage mutations in microsatellites (MS), and point mutations in P53. CONCLUSION: Comprehensive genomic analysis of single cells from stained tissue sections opens new research opportunities for cell lineage and depth analyses, genome-wide mutation surveys, and other single cell assays.

Genomic variability within an organism exposes its cell lineage tree.

What is the lineage relation among the cells of an organism? The answer is sought by developmental biology, immunology, stem cell research, brain research, and cancer research, yet complete cell lineage trees have been reconstructed only for simple organisms such as Caenorhabditis elegans. We discovered that somatic mutations accumulated during normal development of a higher organism implicitly encode its entire cell lineage tree with very high precision. Our mathematical analysis of known mutation rates in microsatellites (MSs) shows that the entire cell lineage tree of a human embryo, or a mouse, in which no cell is a descendent of more than 40 divisions, can be reconstructed from information on somatic MS mutations alone with no errors, with probability greater than 99.95%. Analyzing all approximately 1.5 million MSs of each cell of an organism may not be practical at present, but we also show that in a genetically unstable organism, analyzing only a few hundred MSs may suffice to reconstruct portions of its cell lineage tree. We demonstrate the utility of the approach by reconstructing cell lineage trees from DNA samples of a human cell line displaying MS instability. Our discovery and its associated procedure, which we have automated, may point the way to a future "Human Cell Lineage Project" that would aim to resolve fundamental open questions in biology and medicine by reconstructing ever larger portions of the human cell lineage tree.