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WO2010019588A1 - Procédé de détection ou de diagnostic d'une instabilité génomique - Google Patents

Procédé de détection ou de diagnostic d'une instabilité génomique Download PDF

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WO2010019588A1
WO2010019588A1 PCT/US2009/053423 US2009053423W WO2010019588A1 WO 2010019588 A1 WO2010019588 A1 WO 2010019588A1 US 2009053423 W US2009053423 W US 2009053423W WO 2010019588 A1 WO2010019588 A1 WO 2010019588A1
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ucr
region
conserved
genomic
frequency
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Francesca Ciccarelli
Anna De Grassi
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Istituto Europeo di Oncologia SRL IEO
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/156—Polymorphic or mutational markers

Definitions

  • the invention relates to molecular markers for hereditary cancers and methods for determining genomic instability and the presence of cancer or predisposition to develop cancer.
  • Genomic instability is a common trait of cancer cells and plays a pivotal role in promoting carcinogenesis in several hereditary tumors.
  • MMR mismatch repair
  • One of the best-known examples is the Lynch syndrome, an autosomal dominant condition associated to heterozygous mutations in mismatch repair (MMR) genes (Peltomaki et al . , 1997) .
  • MMR mismatch repair
  • individuals affected by the Lynch syndrome undergo somatic inactivation of the second allele that causes the impairment of the MMR machinery and the onset of the "mutator phenotype" (Loeb, 1991) .
  • the tumorigenic process starts when mutations hit oncogenes and/or tumor suppressors, often in actively renovating tissues such as endometrium, ovary, and colon.
  • the genetic condition is known as Hereditary Non-Polyposis Colorectal Cancer (HNPCC) , which represents the most common form of inherited colorectal cancer (Lynch et al . ,
  • MMR deficiency A hallmark of MMR deficiency is microsatellite instability (MSI) that measures replication errors at repeated regions of the genome. Since more than 90% of HNPCC show MSI (Aaltonen et al . , 1994; Soreide, 2007), this has become a common diagnostic marker of MMR deficiency. MSI detects clonal mutations at specific repeats of the cancer genome that are particularly prone to accumulate mutations, and therefore it provides only indirect evidence of a widespread genomic instability. Recently, large-scale mutational screenings returned the first estimations of the mutation frequency, which is the number of mutations per genome unit, associated to coding and non- coding sequences of cancer genomes (Greenman et al . , 2007; Wood et al .
  • the returned picture is a "static snapshot" of the cancer genome, where only the tip of the iceberg (i.e., clonal mutations) is captured.
  • next -generation sequencing technologies could offer a valid solution, as they rely on amplification and sequencing of distinct DNA filaments. Because sensitivity of these methods increases with coverage, rare mutations should become detectable by performing an ultra-deep re- sequencing of a given DNA region. The obvious drawback is connected with specificity: at deep coverage, low frequency substitutions are an indistinguishable mixture of technical errors and true mutations, which makes it hard to distinguish true signal from noise.
  • the present invention solves the drawbacks and problems encountered in the prior art and provides a method for detecting or diagnosing genomic instability in a subject, which involves determining in the subject the difference in mutation frequency between a genomic region that is not conserved among species (i.e., not under evolutionary constraints) and another genomic region that is under strong evolutionary constraints, such as an ultra-conserved genomic region (UCR) .
  • a statistically significant increase in mutation frequency in the non-conserved region as compared to the region under strong evolutionary constraints establishes a likelihood of genomic instability in the subject.
  • Figures IA and IB show the features of eUCR41.
  • the genomic coordinates refer to the hg!8 assembly of the human genome.
  • the two grey bars correspond to the extremely conserved sequence (Visel et al . , 2008) , and to the genomic region tested for enhancer activity (Pennacchio et al . , 2006) , respectively.
  • Black bars indicate the eleven overlapping segments used for the amplification.
  • Fig. IB the base composition and percentage of homopolymers over the total length of the three regions (eUCR41, ultraconserved core, and flanking segments) are shown.
  • Figure 2 shows the depth of coverage reached with the sequencing screenings. For each sample, the coverage of sequencing (reads/bp) was measured. The average coverage is 49,150 in sample CC; 45,370 in sample NC; 52,530 in sample PBL; and 48,380 in sample H-PBL. Regions in which the coverage almost doubles correspond to overlapping segments between contiguous amplicons (see Materials and Methods in the Example and Figure IA) . The gradient in gray shading corresponds to the degree of sequence conservation, as reported in Fig. IA. UCR41 is highlighted.
  • Figures 3A-3D show examples of high frequency errors. For each of the four hot spot regions described in Table 7, a different example of high frequency errors derived from sample CC is shown. In all cases, the errors are due to indels that cause misalignments between the reads and the reference sequence. In three cases, the misaligned region corresponds to the end of the reads (*) .
  • Fig. 3A Reference position 1050-1061, frequency 0.1%; SEQ ID NOs: 23 and 24.
  • Fig. 3B Reference position 633- 652, frequency 0.6%; SEQ ID NOs: 25 and 26.
  • Fig. 3C Reference position 1071-1094, frequency 0.1%; SEQ ID NOs:27 and 28.
  • Fig. 3D Reference position 29-45 frequency 0.1%; SEQ ID NOs: 29 and 30.
  • Figures 4A and 4B shows graphs of mutation spectrum of eUCR41 in Sample CC.
  • Fig. 4A all detected substitutions are mapped on the corresponding positions of eUCR41.
  • Two range of substitution frequency are shown: 40.5%-2.5% and ⁇ 1.0%, since no substitution was detected in the range 1.0%-2.5%. All substitutions reported in the range 1.0%-0.1% were manually checked and excluded as sequencing errors. The range of frequency highlighted in grey (2.5%-0.1%) was used to estimate the mutation rate of cancer genome in the simulation model.
  • Fig. 4B mutability was calculated using sliding windows of the same length as UCR41. Values corresponding to the middle point of each window are reported. Mutability increases with the decrease of sequence conservation: it is always below average for sequence identity > 50%, while it is above average for non-conserved segments. Similar trends were observed for all samples deriving from HNPCC (data not shown) .
  • Figure 5 is a schematic illustration of a model for the progressive acquisition of mutations during clonal expansion.
  • the mutation frequency of each mutation in the final population reflects the timing of its appearance.
  • the formula to calculate the mutation frequency is described in Table 8.
  • CD cell division.
  • Figures 6A-6D are graphs showing observed and expected mutability outside and inside UCR41. The expected distribution of mutability ratios are shown for each sample, after 1,000,000 random reassignments of positions with low substitution frequency. Arrows correspond to the experimentally observed ratio.
  • CC neoplastic colon mucosa
  • NC non-neoplastic colon mucosa
  • PBL peripheral blood leukocytes
  • H-PBL Fig. 6C
  • Figure 7 is a graph showing the variation of the mutability ratio for decreasing contribution of random errors.
  • the mutability ratio outside and inside UCR41 increases in all samples from HNPCC patients.
  • errors overcome true mutations inside and outside UCR41 at any value of frequency cutoff.
  • the corresponding mutability ratio is therefore always around 1.
  • Values on the Y axis correspond to the observed ratio for each sample.
  • Figure 8 is a graph showing sensitivity in detecting rare mutations.
  • the linear regression curve was calculated by plotting the observed frequency of the mutated allele G for a series of dilutions into the corresponding A wild-type allele.
  • a strict linear correlation is maintained between observed and expected substitution frequency also for allele frequency of 0.01% (dilution 1:10,000) .
  • UCRs Ultraconserved regions of the human genome constitute a possible repository of such immutable segments.
  • UCRs are genomic elements longer than 200 base pairs (bp) , 100% identical between human, mouse and rat (Bejerano et al . , 2004) , almost utterly depleted in polymorphisms within the human population (Derti et al .
  • the present invention provides a method for detecting" or diagnosing genomic instability in a subject.
  • This method involves sequencing both a genomic region that is under strong evolutionary constraints (e.g., an ultra-conserved genomic region (UCR) ) and a genomic region that is not conserved among species (i.e., not under evolutionary constraints) from DNA obtained from cells of the subject, and determining the difference in mutation frequency ( (mutated sequenced alleles/total sequenced alleles) xlOO) between the two regions.
  • the genomic region under strong evolutionary constraints e.g., UCR serves as an internal control to detect an increase in mutations in the non-conserved region.
  • a statistically significant increase in mutation frequency in the non-conserved genomic region as compared to the genomic region under strong evolutionary constraints establishes a likelihood of genomic instability in the subject.
  • Detecting or diagnosing genomic instability in a subject provides an indication of the likelihood that the subject already has or is predisposed to developing hereditary cancers/tumors and genetic diseases in which there is an increase in the mutation rate or mutation frequency.
  • a preferred embodiment is detecting or diagnosing genomic instability associated with Lynch Syndrome.
  • Lynch Syndrome refers to a number of hereditary tumors that can affect at least eight organs (colon, stomach, endometrium, ovaries, small bowel, hepatobiliary epithelium, brain, uroepithelial epithelium) and which are characterized by widespread increase of genome instability known as "mutator" "phenotype" due to loss of heterozygosis in one of the genes of the mismatch repair (MMR) .
  • mutator phenotype
  • MMR mismatch repair
  • Molecular markers currently used for the diagnosis of Lynch Syndrome rely either on the presence of microsatellite instability (MSI) or on the loss of immunohistochemical staining for MMR proteins.
  • the method according to the present invention applied ultra-deep, single molecule sequencing to detect the difference in mutation frequency between a UCR of the cancer genome and its flanking regions (non-conserved regions) .
  • the well-known hypomutability of UCRs in healthy genomes was found to also be preserved in cancer cells. Therefore, an ultraconserved region can serve as an "internal control" for detecting an increase in mutations
  • HNPCC a well-known form of Lynch Syndrome. This difference in mutation frequency, which is also detectable in non-cancerous tissues of the same HNPCC patients, however completely disappears in DNA obtained from the blood of healthy patients. Thus, the whole genome of an individual affected by HNPCC (and not only the genome derived from cancer cells of the individual) has a statistically significant increased mutation frequency as compared to the genome of a healthy individual .
  • hereditary cancer in which the increased mutation frequency of a non-conserved region as compared to an ultraconserved region can be used to detect the presence of the cancer or the predisposition of the subject to develop the cancer is hereditary MYH colorectal cancer, where mutations in the MYH gene have been found to be associated with a recessive form of polyposis.
  • the genomic region that is under strong evolutionary constraints is a region of at least 200 base pairs that are ultraconserved (100% identity with no insertions or deletions) between homologous regions of the human, rat and mouse genomes (Bejeranos et al . , 2004) .
  • these ultraconserved regions are genomic regions 100% conserved during mammal evolution (Bejeranos et al . , 2004) and within the human population (Drake et al., 2006; Katzman et al . , 2007) . Bejeranos et al .
  • the genomic region that is not conserved among mammalian species (i.e., not under evolutionary constraints to be conserved) which is used to compare its mutational frequency with that of a UCR internal control in the method of the present invention, may be immediately adjacent to the UCR (or in the sequence flanking either or both sides of the UCR) , or it can be located far away from the UCR.
  • the non- conserved genomic region used in the method of the present invention is located in the DNA immediately flanking the UCR on one or both sides, more preferably within about 600 to 700 base pairs from the UCR.
  • the non-conserved region flanking the UCR to form an extended UCR provides the advantage that both regions used for determining a difference of mutation frequency are physically located near each other on the same segment of DNA. This however is only preferred and not an absolute requirement .
  • the non-conserved region preferably has no more than 60% conservation (sequence homology or identity) between mammalian species, in contrast with the 100% conservation of the UCRs .
  • the length of the UCR and the non-conserved region sequenced in the method according to the present invention are preferably at least 400 base pairs each, more preferably at least 200 base pairs each.
  • the larger the UCR region to be sequenced the larger the flanking sequence that should be sequenced.
  • the length of the non-conserved genomic region sequenced is at least twice as long as the length of the UCR.
  • UCR41 which can be covered by a single amplicon, as can be seen in Figure IA.
  • the -1,500 bp eUCR41 selected as a molecular marker for detecting genomic instability according to the present invention is also shown in Fig. IA, with the criteria for selecting eUCR41 for ultra-deep sequencing and use as the molecular marker presented in Table 1 of the Example hereinbelow .
  • UCR41 is certainly a preferred UCR, with eUCR41 a particularly preferred combination of UCR41 and a non- conserved region in the flanking sequences of UCR41.
  • the non-conserved region and the UCR to be sequenced as part of the method of the present invention are sequenced at a high depth (ultra deep) of coverage, most preferably using an emulsion method for DNA amplification and an instrument for sequencing by synthesis using a pyrosequencing protocol optimized for solid support and picoliter-scale volumes.
  • This single molecule sequencing technology was developed by company 454 (Margulies et al., Nature 437:376-380, 2005 and US Patent 7,211,390, both of which are herein incorporated by reference for the sequencing technology) and currently commercialized by Roche (www.454.com) .
  • the output of the sequencing at a high depth of coverage i.e., more than 10,000 reads, allowed the detection of rare mutations present in a very small portion of the cell population.
  • the high depth of coverage is at least 20,000 reads, i.e., between 20,000 and 40,000 reads. While higher numbers of reads provides increasing better coverage, generally no more than about 40,000 reads is considered necessary. Lower coverage, e.g., lower number of reads, considerably reduces the costs of this analysis.
  • a statistically significant increase in mutation frequency between the non- conserved region and the UCR, as determined by ultra-deep sequencing in the present method, is one where the statistical parameter p (probability) ⁇ 0.01, more preferably P ⁇ 0.001.
  • the method of the present invention can be used to provide a simple highly sensitive analysis for diagnosing Lynch Syndrome.
  • This method is non-invasive; a blood sample from a subject is all that is needed.
  • the application of this method can be extended to testing predisposition for Lynch syndrome, e.g., HPNCC, in members of families with the hereditary forms of cancer.
  • HPNCC as a preferred embodiment, such a testing for predisposition in individuals with a family history of HPNCC is currently not possible with molecular markers so it is done through annual colonoscopy.
  • This method of the present invention as used for testing of predisposition, is a one time test and does not require periodical testing. This allows particular vigilance in the form of annual colonoscopy and prophylactic/therapeutic treatments to prevent cancer development in those individuals with a family history of HPNCC and who are determined to be heterozygous for MMR.
  • eUCR41 as the best candidate for ultra-deep sequencing was done as shown in Table 1.
  • Table 1 The entire sequence of eUCR41 was divided into eleven overlapping segments (amplicons) , each around 200 bp long.
  • amplicons a pair of forward and reverse primers was designed with 40%-60% of GC content and a melting temperature of 58-60 0 C.
  • the UCSC in silico PCR tool was used to check that selected primers did not have spurious additional matches on the human genome. All primers were fused with ad-hoc 5' overhangs to allow emulsion PCR and sequencing.
  • dCNE duplicated conserved non coding elements
  • CEU Utah residents with ancestry from northern and western Europe
  • MAF minor allele frequency
  • HNPCC carriers were selected from the Registry of Hereditary Colorectal Cancer at the Istituto Nazionale Tumori (Milan, Italy) . Heterozygous MLHl and MSH2 mutations were detected on genomic DNA purified from peripheral blood leukocytes (Blasi et al . , 2006) . Nine healthy controls more than 50 years old (four males and five females) were selected among blood donors with Italian ancestry and no personal history of cancer. Tumors (six adenocarcinomas and three adenomas) and normal colonic mucosa were surgical removed and cryoconserved.
  • Tumor and matched normal DNAs were amplified by PCR using fluorescent primers followed by gel electrophoresis on a 3130 DNA Sequencer (Applied Biosystems, Foster City, CA) and fragments were analyzed using GeneScan and Genotyper softwares (Canzian et al . , 1996) . All tumor samples used for the analysis showed altered electrophoretic pattern in tumor DNA compared with normal DNA for at least two microsatellites of the NCI recommended panel (Boland et al . , 1998) .
  • Genomic DNA was extracted from frozen tumors and normal mucosa using the QIAmp ® DNA Mini Kit and from peripheral blood leukocytes using the QIAmp ® DNA Blood Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. Genomic DNA was amplified by PCR using the high fidelity Pwo SuperYield DNA Polymerase (Roche) . The PCR products were individually checked on agarose gel and purified using the AGENCOURT AMPure kit (Beckman Coulter) according to the manufacturers' protocol.
  • n is the number of reads differing from the reference and t is the total number of reads for position j.
  • Positions with high substitution frequency (>0.1%) in all four samples were manually checked to reject possible false positives.
  • positions with low substitution frequency ( ⁇ 0.1%) only base substitutions and no indels were considered to reduce the probability of pyrosequencing artifacts associated with insertions and deletions.
  • PCR errors The number of possible errors introduced by the DNA polymerase during the polymerase chain reaction (PCR errors) , was first estimated and then removed from experimental data. PCR errors were quantified using two different approaches. The first one was based on the binomial probability distribution, in which the number of PCR errors X was considered a random variable that follows a binomial distribution:
  • the number n of single stranded DNA sequences was taken from the number of reads of each sample (49,194; 45,383; 53,212; and 49,005 in CC, NC, PBL and H-PBL, respectively) .
  • the cycles of PCR amplifications were simulated in silico using a model similar to that used for the mutation rate. Starting from one DNA double strand of length L 1 errors were randomly introduced at a rate r in each position of the strand at each of the d PCR cycles. Once introduced, errors were retained in all the daughter strands. At the end of the amplification, the number of PCR errors present in the n single strands of DNA sequences was derived. The procedure was re-iterated 1,000 times to generate a distribution of N values. The number of estimated PCR errors returned by the two approaches is identical and is shown in Table 3 below.
  • Dilution experiments were performed using the 157 bp long segment of eUCR41 corresponding to amplicon 9, which bears a single nucleotide polymorphism in position 1204 (SNP A/G; Figure IA) .
  • This segment was amplified from the peripheral blood leukocytes of two healthy donors showing homozygous AA and GG genotypes, respectively (Samples 13 and 14, Table 4) . After amplification, the regions were purified as described above and pooled in different relative amounts. Four final dilutions were obtained with decreasing G:A ratios (1:1,000; 1:2,000; 1:5,000; and 1:10,000; respectively) .
  • DNA quantifications of the two alleles were performed using the Victor PicoGreen fluorometer (PerkinElmer Life Sciences) . The obtained values were used to calibrate the successive dilution.
  • the DNA samples corresponding to the four dilutions were sequenced using four distinct lanes using a four-lane gasket for 70x75 PicoTiterPlate device on the GS FLX Sequencer at BMR Genomics (Padua, Italy) . Specificity was measured as TN/ (TN+FP) . The number of true negatives (TN) was calculated as the number of sequence positions showing errors at a frequency lower than the frequency of the diluted allele.
  • eUCRs extended UCRs
  • All 307 eUCRs were screened for genomic and functional properties that would favor the detection of a difference in mutability between the ultraconserved core and the flanking segments (Table 1) .
  • the best candidate was identified as eUCR41, a 1493 bp long region centered on a 217 bp (654-870) long ultraconserved core ( Figure IA) .
  • This region bears two known SNPs at 286 and 1204, has no coding activity and is located in a gene desert. It acts as a developmental enhancer in the mouse forebrain (Pennacchio et al .
  • MSI microsatellite instability
  • CC colon cancer
  • NC non-neoplastic mucosa
  • PBL peripheral blood leukocytes
  • H- PBL healthy peripheral blood leukocytes.
  • the Minor Allele Frequency (MAF) in all samples is reported, as derived from 454 and Sanger sequencing.
  • MAF was calculated as the percentage of reads bearing the minor allele in each sample.
  • the Sanger screening it corresponds to the fraction of minor alleles detected in the nine patients and in the nine healthy donors.
  • Sanger genotyping confirmed that the two clonal mutations in sample CC are heterozygous mutations present in two different patients. Combining this information with the frequency in the 454 screening, it is possible to infer that they are present in about 74% and 47% of the cells of the two patients, respectively.
  • CC colon cancer
  • NC non-neoplastic mucosa
  • PBL peripheral blood leukocytes
  • H-PBL healthy peripheral blood leukocytes.
  • the mutation frequency allows for roughly assigning an "age" to each mutation detected in sample CC ( Figures 5A and 6) .
  • the present inventors refer to "mutation frequency" and not to "substitution frequency” because the present inventors consider only true mutations and not errors.
  • Clonal mutations which are present in the vast majority of the neoplastic cell population, likely arose at early stages of clonal proliferation. Mutations with lower frequency, and therefore present only in a smaller fraction of the cell population, were instead introduced later. This inverse correlation allows to estimate the mutation rate, defined as the number of mutations per sequenced nucleotide introduced at each cell division (muts/bp/cd) .
  • To derive the mutation rate of HNPCC we simulated a model of cell proliferation that reproduces the progressive accumulation of mutations during cancer clonal expansion ( Figure 5) .
  • the numbers of founder cells and cell divisions were derived from the experimental data of sample CC. At each cell division, the mutation frequency at each sequence position, was measured. This allowed obtaining a final number of expected mutations with frequency 2.6%-0.1% to be compared to the experimentally observed one.
  • the present inventors developed an algorithm that simulates cell proliferation and the progressive inclusion of mutations.
  • the algorithm is based on three steps: (1) Each simulation starts from nine founder cells, resembling the nine HNPCC carriers. The genome of each cell corresponds to a numerical string as long as eUCR41. All positions of the string were initially set to zero; (2) Eleven cycles of cell division are simulated to generate 36,864 final alleles. This number approximates the number of distinct DNA filaments that were experimentally sequenced; (3) At each cell division, mutations are introduced at a given mutation rate. Each mutation corresponded to a 0 to 1 transition in a random position of the string and was propagated to all daughter cells.
  • the mutations frequency defined as the number of mutations divided by the number of final alleles, was calculated for each position of the string ( Figure 5) .
  • the resulting mutation frequency was multiplied by 0.7. This value approximates a reliable content of tumoral cells in the initial samples ( ⁇ 70%) , as estimated using histological analysis (Thomas et al . , 2006; Thomas et al . , 2007) and confirmed by the frequency of clonal mutation at position 871 (74%) .
  • the HNPCC genome acquires mutations at a rate ⁇ 6xlO-6 mutations per base pair at each cell division (muts/bp/cd) .
  • This estimation represents the first measure of mutation rate inferred directly from sequencing data and is compatible with the estimated frequency of fixed mutations in MMR deficient cancers (3.2x10-5 muts/bp) (Greenman et al. , 2007) .
  • the frequency was calculated as the number of times that the substitution was observed divided by the number of times that that position was read.
  • the data confirm our initial assumption that UCR41 is also maintained as ultraconserved in somatic cells and it can therefore be used to normalize the experimental errors.
  • the mutation rate of the HNPCC genome allows detecting an increased occurrence of mutations in the flanking segments when compared to the ultraconserved core. No increase is detectable in the sample H-PBL, although UCR41 is very likely to also be conserved here as well.
  • the mutation rate of healthy human genome is so low that sequencing errors overcome true mutations in the entire region. The different behavior between HNPCC and healthy samples becomes more evident when the contribution of random errors decreases.
  • predisposition testing in family members with the Lynch syndrome consists of genetic screening of the MMR genes to identify germline mutations (Lynch, 2007; Vasen et al . , 2007) .
  • Our strategy here constitutes an alternative test for diagnosing cancer predisposition without any a priori knowledge of the mutated genes.
  • Genome Res 14 (4) : 708-715 (2004) Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res 14 (4) : 708-715.
  • Flaman JM Frevier T, Moreau V, Charbonnier F, Martin C et al .
  • Pennacchio LA Ahituv N
  • Moses AM Ahituv N
  • Prabhakar S Nobrega MA et al .

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Abstract

L'invention porte sur un procédé de détection ou de diagnostic d'une instabilité génomique chez un individu par la détermination de la différence de fréquence de mutation entre une région génomique non conservée et une région génomique ultraconservée (UCR), où une augmentation statistiquement significative de la fréquence de mutation dans la région non conservée, par comparaison avec l’UCR établit une probabilité d'instabilité génomique chez l'individu.
PCT/US2009/053423 2008-08-11 2009-08-11 Procédé de détection ou de diagnostic d'une instabilité génomique Ceased WO2010019588A1 (fr)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011101744A3 (fr) * 2010-02-22 2011-12-08 Population Genetics Technologies Ltd. Procédés d'extraction et de normalisation de régions à étudier
US20120178077A1 (en) * 2010-08-31 2012-07-12 Canon U.S. Life Sciences, Inc. Thermal calibration
US20140011184A1 (en) * 2010-08-31 2014-01-09 Canon U.S. Life Sciences, Inc. Positive Controls
US20220213561A1 (en) * 2014-04-21 2022-07-07 Natera, Inc. Detecting mutations and ploidy in chromosomal segments
US12494267B2 (en) 2010-05-18 2025-12-09 Natera, Inc. Methods for non-invasive prenatal ploidy calling
US12492429B2 (en) 2014-04-21 2025-12-09 Natera, Inc. Detecting mutations and ploidy in chromosomal segments

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7078168B2 (en) * 2001-02-27 2006-07-18 Biotage Ab Method for determining allele frequencies
US20070037185A1 (en) * 2005-05-11 2007-02-15 The Board Of Regents Of The University Of Texas System Estimating allele frequencies by small pool PCR

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7078168B2 (en) * 2001-02-27 2006-07-18 Biotage Ab Method for determining allele frequencies
US20070037185A1 (en) * 2005-05-11 2007-02-15 The Board Of Regents Of The University Of Texas System Estimating allele frequencies by small pool PCR

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BEJERANO ET AL.: "Ultraconserved elements in the human genome.", SCIENCE, vol. 304, no. 5675, 2004, pages 1321 - 1325 *
SIMONS ET AL.: "Transposon-free regions in mammalian genomes.", GENOME RESEARCH, vol. 16, no. 2, 2006, pages 164 - 172 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011101744A3 (fr) * 2010-02-22 2011-12-08 Population Genetics Technologies Ltd. Procédés d'extraction et de normalisation de régions à étudier
US12494267B2 (en) 2010-05-18 2025-12-09 Natera, Inc. Methods for non-invasive prenatal ploidy calling
US20120178077A1 (en) * 2010-08-31 2012-07-12 Canon U.S. Life Sciences, Inc. Thermal calibration
US20140011184A1 (en) * 2010-08-31 2014-01-09 Canon U.S. Life Sciences, Inc. Positive Controls
US10591364B2 (en) * 2010-08-31 2020-03-17 Canon U.S.A., Inc. Thermal calibration
US11022573B2 (en) * 2010-08-31 2021-06-01 Canon U.S.A., Inc. Positive controls
US20220213561A1 (en) * 2014-04-21 2022-07-07 Natera, Inc. Detecting mutations and ploidy in chromosomal segments
US12492429B2 (en) 2014-04-21 2025-12-09 Natera, Inc. Detecting mutations and ploidy in chromosomal segments

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