Assays to measure DNA methylation, which are important in epigenetic research and clinical diagnostics, typically rely on conversion of unmethylated cytosine to uracil by sodium bisulfite. However, no study has comprehensively evaluated the precision and performance characteristics of sodium bisulfite conversion and subsequent quantitative methylation assay. We developed quantitative real-time polymerase chain reaction (MethyLight) to measure percentage of methylated reference (PMR, ie, degree of methylation) for the MGMT, MLH1, and CDKN2A (p16) promoters. To measure the precision of bisulfite conversion, we bisulfite-treated seven different aliquots of DNA from each of four paraffin-embedded colon cancer samples. To assess run-to-run variation, we repeated MethyLight five times. Bisulfite-to-bisulfite coefficient of variation (CV) of PMR ranged from 0.10 to 0.38 (mean, 0.21), and run-to-run CV of PMR ranged from 0.046 to 0.60 (mean, 0.31). Interclass correlation coefficients were 0.74 to 0.84 for the three loci, indicating good reproducibility. DNA mixing study with methylated and unmethylated DNA showed good linearity of the assay. Of 272 colorectal cancers evaluated, most showed PMR either <1 or >10, and promoter methylation (PMR >4) was tightly associated with loss of respective protein expression (P < 10 ؊16 ). In conclusion, sodium bisulfite conversion and quantitative MethyLight assays have good precision and linearity and can be effectively used for high-throughput DNA methylation analysis on paraffin-embedded tissue.

PCR is widely employed as the initial DNA amplification step for genetic testing. However, a key limitation of PCR-based methods is the inability to selectively amplify low levels of mutations in a wild-type background. As a result, downstream assays are limited in their ability to identify subtle genetic changes that can have a profound impact in clinical decision-making and outcome. Here we describe co-amplification at lower denaturation temperature PCR (COLD-PCR), a novel form of PCR that amplifies minority alleles selectively from mixtures of wild-type and mutation-containing sequences irrespective of the mutation type or position on the sequence. We replaced regular PCR with COLD-PCR before sequencing or genotyping assays to improve mutation detection sensitivity by up to 100-fold and identified new mutations in the genes encoding p53, KRAS and epidermal growth factor in heterogeneous cancer samples that had been missed by the currently used methods. For clinically relevant microdeletions, COLD-PCR enabled exclusive amplification and isolation of the mutants. COLD-PCR will transform the capabilities of PCR-based genetic testing, including applications in cancer, infectious diseases and prenatal identification of fetal alleles in maternal blood.

Tumors are characterized by somatic mutations that drive biological processes ultimately reflected in tumor phenotype. With regard to radiographic phenotypes, generally unconnected through present understanding to the presence of specific mutations, artificial intelligence methods can automatically quantify phenotypic characters by using predefined, engineered algorithms or automatic deep-learning methods, a process also known as radiomics. Here we demonstrate how imaging phenotypes can be connected to somatic mutations through an integrated analysis of independent datasets of 763 lung adenocarcinoma patients with somatic mutation testing and engineered CT image analytics. We developed radiomic signatures capable of distinguishing between tumor genotypes in a discovery cohort (n ¼ 353) and verified them in an independent validation cohort (n ¼ 352). All radiomic signatures significantly outperformed conventional radiographic predictors (tumor volume and maximum diameter).We found a radiomic signature related to radiographic heterogeneity that successfully discriminated between EGFR þ and EGFR Our results argue that somatic mutations drive distinct radiographic phenotypes that can be predicted by radiomics. This work has implications for the use of imaging-based biomarkers in the clinic, as applied noninvasively, repeatedly, and at low cost.

Radiation therapy (RT) is the treatment of cancer and other diseases with ionizing radiation. The ultimate goal of RT is to destroy all the disease cells while sparing healthy tissue. Towards this goal, RT has advanced significantly over the past few decades in part due to new technologies including: multileaf collimator-assisted modulation of radiation beams, improved computer-assisted inverse treatment planning, image guidance, robotics with more precision, better motion management strategies, stereotactic treatments and hypofractionation. With recent advances in nanotechnology, targeted RT with gold nanoparticles (GNPs) is actively being investigated as a means to further increase the RT therapeutic ratio. In this review, we summarize the current status of research and development towards the use of GNPs to enhance RT. We highlight the promising emerging modalities for targeted RT with GNPs and the corresponding preclinical evidence supporting such promise towards potential clinical translation. Future prospects and perspectives are discussed.

BACKGROUND:The ability to identify low-level somatic DNA mutations and minority alleles within an excess wild-type sample is becoming essential for characterizing early and posttreatment tumor status in cancer patients. Over the past 2 decades, much research has focused on improving the selectivity of PCR-based technologies for enhancing the detection of minority (mutant) alleles in clinical samples. Routine application in clinical and diagnostic settings requires that these techniques be accurate and cost-effective and require little effort to optimize, perform, and analyze.CONTENT: Enrichment methods typically segregate by their ability to enrich for, and detect, either known or unknown mutations. Although there are several robust approaches for detecting known mutations within a high background of wild-type DNA, there are few techniques capable of enriching and detecting low-level unknown mutations. One promising development is COLD-PCR (coamplification at lower denaturation temperature), which enables enrichment of PCR amplicons containing unknown mutations at any position, such that they can be subsequently sequenced to identify the exact nucleotide change.

Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing. Experimental Design: We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ERþ/HER2À metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples. Results: Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median ¼ 57; range ¼ 2-346). Clinical sensitivity was 81% (n ¼ 13/16) in newly diagnosed MBC, 23% (n ¼ 7/30) at postoperative and 19% (n ¼ 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR ¼ 20.8; 95% confidence interval, 7.3-58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range ¼ 3.4-39.2 months). Conclusions: Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track.

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, and (iii) the overall radiation dose deposited by radiolabeled cells in the unlabeled cells within the growing tumor is <10 cGy, we conclude that the results obtained are a consequence of a bystander effect that is generated in vivo by factor(s) present within and͞or released from the 125 IUdR-labeled cells. These in vivo findings significantly impact the current dogma for assessing the therapeutic potential of internally administered radionuclides. They also call for reevaluation of the approaches currently used for estimating the risks to individuals and populations inadvertently exposed internally to radioactivity as well as to patients undergoing routine diagnostic nuclear medical procedures. Studies in recent years have demonstrated that a radiobiologic phenomenon termed the ''bystander effect'' can be observed in mammalian cells grown in vitro. Bystander damage describes biologic effects, originating from irradiated cells, that occur in unirradiated neighboring cells. Several investigators have reported that when ␣-particles traverse a small fraction of a cell population in vitro, lower rates of survival and higher rates of genetic change are observed than those predicted from directionization-only models (1-6). These changes include increased levels of sister chromatid exchanges, mutations, and micronuclei formation, changes in gene expression, and oncogenic transformation. Cell survival is likewise compromised when cells are cocultured with tritiated thymidine-labeled cells (7, 8) and iodine-125 (9). Similarly, the bystander effect has been reported for microcolonies that have been ␥ irradiated (10) and for cells exposed to media from ␥-irradiated cells (10, 11). Evidence from these reports challenges the past half-century's tenet that radiation produces effects only in cells whose DNA has been damaged either through direct ionization or indirectly (for example, through hydroxyl radicals produced in water molecules in the immediate vicinity of the DNA).Whether radiation-induced bystander effects represent a phenomenon that occurs only ex vivo, i.e., are a byproduct of in vitro conditions and manipulations, or whether they are factual in vivo events has not been fully examined. Consequently, the extension of conclusions derived from in vitro studies to the in vivo situation is uncertain. The demonstration of a bystander effect with an in vivo system and the elucidation of the underlying mechanisms of an in vivo bystander effect would go a long way in translating its implications for humans.Recently, Watson et al. (12) demonstrated chromosomal instability in the progeny of unirradiated bone marrow cells mixed with cells exposed ex vivo to neutrons and transplanted into recipient mice. In this novel system, a sex-mismatch transplantation protocol provides a three-way marker system and allows the investigators to distinguish not only host-derived cells from donor-derived cells, but also irradiated donor stemcell-derived cells from nonirradiated donor stem-cell-derived cells. These studies thus provide the...