Decreased Mitochondrial DNA Mutagenesis in Human Colorectal Cancer

Genome instability is regarded as a hallmark of cancer. Human tumors frequently carry clonally expanded mutations in their mitochondrial DNA (mtDNA), some of which may drive cancer progression and metastasis. The high prevalence of clonal mutations in tumor mtDNA has commonly led to the assumption that the mitochondrial genome in cancer is genetically unstable, yet this hypothesis has not been experimentally tested. In this study, we directly measured the frequency of non-clonal (random) de novo single base substitutions in the mtDNA of human colorectal cancers. Remarkably, tumor tissue exhibited a decreased prevalence of these mutations relative to adjacent non-tumor tissue. The difference in mutation burden was attributable to a reduction in C∶G to T∶A transitions, which are associated with oxidative damage. We demonstrate that the lower random mutation frequency in tumor tissue was also coupled with a shift in glucose metabolism from oxidative phosphorylation to anaerobic glycolysis, as compared to non-neoplastic colon. Together these findings raise the intriguing possibility that fidelity of mitochondrial genome is, in fact, increased in cancer as a result of a decrease in reactive oxygen species-mediated mtDNA damage

Quantitative evaluation of oligonucleotide surface concentrations using polymerization-based amplification

Quantitative evaluation of minimal polynucleotide concentrations has become a critical analysis among a myriad of applications found in molecular diagnostic technology. Development of high-throughput, nonenzymatic assays that are sensitive, quantitative and yet feasible for point-of-care testing are thus beneficial for routine implementation. Here, we develop a nonenzymatic method for quantifying surface concentrations of labeled DNA targets by coupling regulated amounts of polymer growth to complementary biomolecular binding on array-based biochips. Polymer film thickness measurements in the 20–220 nm range vary logarithmically with labeled DNA surface concentrations over two orders of magnitude with a lower limit of quantitation at 60 molecules/μm2 (∼106 target molecules). In an effort to develop this amplification method towards compatibility with fluorescence-based methods of characterization, incorporation of fluorescent nanoparticles into the polymer films is also evaluated. The resulting gains in fluorescent signal enable quantification using detection instrumentation amenable to point-of-care settings

Bmi1 Is Down-Regulated in the Aging Brain and Displays Antioxidant and Protective Activities in Neurons

Aging increases the risk to develop several neurodegenerative diseases, although the underlying mechanisms are poorly understood. Inactivation of the Polycomb group gene Bmi1 in mice results in growth retardation, cerebellar degeneration, and development of a premature aging-like phenotype. This progeroid phenotype is characterized by formation of lens cataracts, apoptosis of cortical neurons, and increase of reactive oxygen species (ROS) concentrations, owing to p53-mediated repression of antioxidant response (AOR) genes. Herein we report that Bmi1 expression progressively declines in the neurons of aging mouse and human brains. In old brains, p53 accumulates at the promoter of AOR genes, correlating with a repressed chromatin state, down-regulation of AOR genes, and increased oxidative damages to lipids and DNA. Comparative gene expression analysis further revealed that aging brains display an up-regulation of the senescence-associated genes IL-6, p19Arf and p16Ink4a, along with the pro-apoptotic gene Noxa, as seen in Bmi1-null mice. Increasing Bmi1 expression in cortical neurons conferred robust protection against DNA damage-induced cell death or mitochondrial poisoning, and resulted in suppression of ROS through activation of AOR genes. These observations unveil that Bmi1 genetic deficiency recapitulates aspects of physiological brain aging and that Bmi1 over-expression is a potential therapeutic modality against neurodegeneration

Frequent Heterogeneous Missense Mutations of GGAP2 in Prostate Cancer: Implications for Tumor Biology, Clonality and Mutation Analysis

Prostate cancer is the most common visceral malignancy in Western men and a major cause of cancer deaths. Increased activation of the AKT and NFkB pathways have been identified as critical steps in prostate cancer initiation and progression. GGAP2 (GTP-binding and GTPase activating protein 2) is a multidomain protein that contains an N-terminal Ras homology domain (GTPase), followed by a PH domain, a C-terminal GAP domain and an ankyrin repeat domain. GGAP2 can directly activate signaling via both the AKT and NFkB pathways and acts as a node of crosstalk between these pathways. Increased GGAP2 expression is present in three quarters of prostate cancers. Mutations of GGAP2 have been reported in cell lines from other malignancies. We therefore analyzed 84 prostate cancer tissues and 43 benign prostate tissues for somatic mutations in GGAP2 by direct sequencing of individual clones derived from the GAP and GTPase domains of normal and tumor tissue. Overall, half of cancers contained mutant GAP domain clones and in 20% of cancers, 30% or more of clones were mutant in the GAP domain. Surprisingly, the mutations were heterogeneous and nonclonal, with multiple different mutations being present in many tumors. Similar findings were observed in the analysis of the GTPase domain. Mutant GGAP2 proteins had significantly higher transcriptional activity using AP-1 responsive reporter constructs when compared to wild-type protein. Furthermore, the presence of these mutations was associated with aggressive clinical behavior. The presence of high frequency nonclonal mutations of a single gene is novel and represents a new mode of genetic alteration that can promote tumor progression. Analysis of mutations in cancer has been used to predict outcome and guide therapeutic target identification but such analysis has focused on clonal mutations. Our studies indicate that in some cases high frequency nonclonal mutations may need to be assessed as well

Epidemiology of Doublet/Multiplet Mutations in Lung Cancers: Evidence that a Subset Arises by Chronocoordinate Events

BACKGROUND: Evidence strongly suggests that spontaneous doublet mutations in normal mouse tissues generally arise from chronocoordinate events. These chronocoordinate mutations sometimes reflect "mutation showers", which are multiple chronocoordinate mutations spanning many kilobases. However, little is known about mutagenesis of doublet and multiplet mutations (domuplets) in human cancer. Lung cancer accounts for about 25% of all cancer deaths. Herein, we analyze the epidemiology of domuplets in the EGFR and TP53 genes in lung cancer. The EGFR gene is an oncogene in which doublets are generally driver plus driver mutations, while the TP53 gene is a tumor suppressor gene with a more typical situation in which doublets derive from a driver and passenger mutation. METHODOLOGY/PRINCIPAL FINDINGS: EGFR mutations identified by sequencing were collected from 66 published papers and our updated EGFR mutation database (www.egfr.org). TP53 mutations were collected from IARC version 12 (www-p53.iarc.fr). For EGFR and TP53 doublets, no clearly significant differences in race, ethnicity, gender and smoking status were observed. Doublets in the EGFR and TP53 genes in human lung cancer are elevated about eight- and three-fold, respectively, relative to spontaneous doublets in mouse (6% and 2.3% versus 0.7%). CONCLUSIONS/SIGNIFICANCE: Although no one characteristic is definitive, the aggregate properties of doublet and multiplet mutations in lung cancer are consistent with a subset derived from chronocoordinate events in the EGFR gene: i) the eight frameshift doublets (present in 0.5% of all patients with EGFR mutations) are clustered and produce a net in-frame change; ii) about 32% of doublets are very closely spaced (< or =30 nt); and iii) multiplets contain two or more closely spaced mutations. TP53 mutations in lung cancer are very closely spaced (< or =30 nt) in 33% of doublets, and multiplets generally contain two or more very closely spaced mutations. Work in model systems is necessary to confirm the significance of chronocoordinate events in lung and other cancers

Evidence of Genetic Instability in Tumors and Normal Nearby Tissues

We have analyzed the sequence heterogeneity of the transcripts of the human HPRT and G6PD single copy genes that are not considered tumor markers. Analyses have been performed on different colon cancers and on the nearby histologically normal tissues of two male patients. Several copies of each cDNA, which were produced by cloning the RT-PCR-amplified fragments of the specific mRNA, have been sequenced. Similar analyses have been performed on blood samples of two ostensibly healthy males as reference controls. The sequence heterogeneity of the HPRT and G6PD genes was also determined on DNA from tumor tissues. The employed analytical approach revealed the presence of low-frequency mutations not detectable by other procedures. The results show that genetic heterogeneity is detectable in HPRT and G6PD transcripts in both tumors and nearby healthy tissues of the two studied colon tumors. Similar frequencies of mutations are observed in patient genomic DNA, indicating that mutations have a somatic origin. HPRT transcripts show genetic heterogeneity also in healthy individuals, in agreement with previous results on human T-cells, while G6PD transcript heterogeneity is a characteristic of the patient tissues. Interestingly, data on TP53 show little, if any, heterogeneity in the same tissues. CONCLUSIONS/SIGNIFICANCE: These findings show that genetic heterogeneity is a peculiarity not only of cancer cells but also of the normal tissue where a tumor arises

The dynamics of E1A in regulating networks and canonical pathways in quiescent cells

<p>Abstract</p> <p>Background</p> <p>Adenoviruses force quiescent cells to re-enter the cell cycle to replicate their DNA, and for the most part, this is accomplished after they express the E1A protein immediately after infection. In this context, E1A is believed to inactivate cellular proteins (e.g., p130) that are known to be involved in the silencing of E2F-dependent genes that are required for cell cycle entry. However, the potential perturbation of these types of genes by E1A relative to their functions in regulatory networks and canonical pathways remains poorly understood.</p> <p>Findings</p> <p>We have used DNA microarrays analyzed with Bayesian ANOVA for microarray (BAM) to assess changes in gene expression after E1A alone was introduced into quiescent cells from a regulated promoter. Approximately 2,401 genes were significantly modulated by E1A, and of these, 385 and 1033 met the criteria for generating networks and functional and canonical pathway analysis respectively, as determined by using Ingenuity Pathway Analysis software. After focusing on the highest-ranking cellular processes and regulatory networks that were responsive to E1A in quiescent cells, we observed that many of the up-regulated genes were associated with DNA replication, the cell cycle and cellular compromise. We also identified a cadre of up regulated genes with no previous connection to E1A; including genes that encode components of global DNA repair systems and DNA damage checkpoints. Among the down-regulated genes, we found that many were involved in cell signalling, cell movement, and cellular proliferation. Remarkably, a subset of these was also associated with p53-independent apoptosis, and the putative suppression of this pathway may be necessary in the viral life cycle until sufficient progeny have been produced.</p> <p>Conclusions</p> <p>These studies have identified for the first time a large number of genes that are relevant to E1A's activities in promoting quiescent cells to re-enter the cell cycle in order to create an optimum environment for adenoviral replication.</p

Clonal mutations in primary human glial tumors: evidence in support of the mutator hypothesis

<p>Abstract</p> <p>Background</p> <p>A verifiable consequence of the mutator hypothesis is that even low grade neoplasms would accumulate a large number of mutations that do not influence the tumor phenotype (clonal mutations). In this study, we have attempted to quantify the number of clonal mutations in primary human gliomas of astrocytic cell origin. These alterations were identified in tumor tissue, microscopically confirmed to have over 70% neoplastic cells.</p> <p>Methods</p> <p>Random Amplified Polymorphic DNA (RAPD) analysis was performed using a set of fifteen 10-mer primers of arbitrary but definite sequences in 17 WHO grade II astrocytomas (low grade diffuse astrocytoma or DA) and 16 WHO grade IV astrocytomas (Glioblastoma Multiforme or GBM). The RAPD profile of the tumor tissue was compared with that of the leucocyte DNA of the same patient and alteration(s) scored. A quantitative estimate of the overall genomic changes in these tumors was obtained by 2 different modes of calculation.</p> <p>Results</p> <p>The overall change in the tumors was estimated to be 4.24% in DA and 2.29% in GBM by one method and 11.96% and 6.03% in DA and GBM respectively by the other. The difference between high and lower grade tumors was statistically significant by both methods.</p> <p>Conclusion</p> <p>This study demonstrates the presence of extensive clonal mutations in gliomas, more in lower grade. This is consistent with our earlier work demonstrating that technique like RAPD analysis, unbiased for locus, is able to demonstrate more intra-tumor genetic heterogeneity in lower grade gliomas compared to higher grade. The results support the mutator hypothesis proposed by Loeb.</p

Analysis of Cancer Mutation Signatures in Blood by a Novel Ultra-Sensitive Assay: Monitoring of Therapy or Recurrence in Non-Metastatic Breast Cancer

BACKGROUND: Tumor DNA has been shown to be present both in circulating tumor cells in blood and as fragments in the plasma of metastatic cancer patients. The identification of ultra-rare tumor-specific mutations in blood would be the ultimate marker to measure efficacy of cancer therapy and/or early recurrence. Herein we present a method for detecting microinsertions/deletions/indels (MIDIs) at ultra-high analytical selectivity. MIDIs comprise about 15% of mutations. METHODS AND FINDINGS: We describe MIDI-Activated Pyrophosphorolysis (MAP), a method of ultra-high analytical selectivity for detecting MIDIs. The high analytical selectivity of MAP is putatively due to serial coupling of two rare events: heteroduplex slippage and mis-pyrophosphorolysis. MAP generally has an analytical selectivity of one mutant molecule per >1 billion wild type molecules and an analytical sensitivity of one mutant molecule per reaction. The analytical selectivity of MAP is about 100,000-fold better than that of our previously described method of Pyrophosphorolysis Activated Polymerization-Allele specific amplification (PAP-A) for detecting MIDIs. The utility of this method is illustrated in two ways. 1) We demonstrate that two EGFR deletions commonly found in lung cancers are not present in tissue from four normal human lungs (10(7) copies of gDNA each) or in blood samples from 10 healthy individuals (10(7) copies of gDNA each). This is inconsistent, at least at an analytical sensitivity of 10(-7), with the hypotheses of (a) hypermutation or (b) strong selection of these growth factor-mutated cells during normal lung development leads to accumulation of pre-neoplastic cells with these EGFR mutations, which sometimes can lead to lung cancer in late adulthood. Moreover, MAP was used for large scale, high throughput "gene pool" analysis. No germline or early embryonic somatic mosaic mutation was detected (at a frequency of >0.3%) for the 15/18 bp EGFR deletion mutations in 6,400 individuals, suggesting that early embryonic EGFR somatic mutation is very rare, inconsistent with hypermutation or strong selection of these deletions in the embryo. 2) The second illustration of MAP utility is in personalized monitoring of therapy and early recurrence in cancer. Tumor-specific p53 mutations identified at diagnosis in the plasma of six patients with stage II and III breast cancer were undetectable after therapy in four women, consistent with clinical remission, and continued to be detected after treatment in two others, reflecting tumor progression. CONCLUSIONS: MAP has an analytical selectivity of one part per billion for detection of MIDIs and an analytical sensitivity of one molecule. MAP provides a general tool for monitoring ultra-rare mutations in tissues and blood. As an example, we show that the personalized cancer signature in six out of six patients with non-metastatic breast cancer can be detected and that levels over time are correlated with the clinical course of disease

Predicting cancer involvement of genes from heterogeneous data

<p>Abstract</p> <p>Background</p> <p>Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data.</p> <p>Results</p> <p>We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature.</p> <p>Conclusion</p> <p>Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks. </p