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Digital information reflecting an individual's karyotype From Wikipedia, the free encyclopedia
In genetics, virtual karyotype is the digital information reflecting a karyotype, resulting from the analysis of short sequences of DNA from specific loci all over the genome, which are isolated and enumerated.[1] It detects genomic copy number variations at a higher resolution for level than conventional karyotyping or chromosome-based comparative genomic hybridization (CGH).[2] The main methods used for creating virtual karyotypes are array-comparative genomic hybridization and SNP arrays.
A karyotype (Fig 1) is the characteristic chromosome complement of a eukaryote species.[3][4] A karyotype is typically presented as an image of the chromosomes from a single cell arranged from largest (chromosome 1) to smallest (chromosome 22), with the sex chromosomes (X and Y) shown last. Historically, karyotypes have been obtained by staining cells after they have been chemically arrested during cell division. Karyotypes have been used for several decades to identify chromosomal abnormalities in both germline and cancer cells. Conventional karyotypes can assess the entire genome for changes in chromosome structure and number, but the resolution is relatively coarse, with a detection limit of 5-10Mb.[citation needed]
Recently, platforms for generating high-resolution karyotypes in silico from disrupted DNA have emerged, such as array comparative genomic hybridization (arrayCGH) and SNP arrays. Conceptually, the arrays are composed of hundreds to millions of probes which are complementary to a region of interest in the genome. The disrupted DNA from the test sample is fragmented, labeled, and hybridized to the array. The hybridization signal intensities for each probe are used by specialized software to generate a log2ratio of test/normal for each probe on the array. [citation needed]
Knowing the address of each probe on the array and the address of each probe in the genome, the software lines up the probes in chromosomal order and reconstructs the genome in silico (Fig 2 and 3).
Virtual karyotypes have dramatically higher resolution than conventional cytogenetics. The actual resolution will depend on the density of probes on the array. Currently, the Affymetrix SNP6.0 is the highest density commercially available array for virtual karyotyping applications. It contains 1.8 million polymorphic and non-polymorphic markers for a practical resolution of 10-20kb—about the size of a gene. This is approximately 1000-fold greater resolution than karyotypes obtained from conventional cytogenetics.[citation needed]
Virtual karyotypes can be performed on germline samples for constitutional disorders,[5][6] and clinical testing is available from dozens of CLIA certified laboratories (genetests.org). Virtual karyotyping can also be done on fresh or formalin-fixed paraffin-embedded tumors.[7][8][9] CLIA-certified laboratories offering testing on tumors include Creighton Medical Laboratories (fresh and paraffin embedded tumor samples) and CombiMatrix Molecular Diagnostics (fresh tumor samples).
Array-based karyotyping can be done with several different platforms, both laboratory-developed and commercial. The arrays themselves can be genome-wide (probes distributed over the entire genome) or targeted (probes for genomic regions known to be involved in a specific disease) or a combination of both. Further, arrays used for karyotyping may use non-polymorphic probes, polymorphic probes (i.e., SNP-containing), or a combination of both. Non-polymorphic probes can provide only copy number information, while SNP arrays can provide both copy number and loss-of-heterozygosity (LOH) status in one assay. The probe types used for non-polymorphic arrays include cDNA, BAC clones (e.g., BlueGnome), and oligonucleotides (e.g., Agilent, Santa Clara, CA, USA or Nimblegen, Madison, WI, USA). Commercially available oligonucleotide SNP arrays can be solid phase (Affymetrix, Santa Clara, CA, USA) or bead-based (Illumina, San Diego, CA, USA). Despite the diversity of platforms, ultimately they all use genomic DNA from disrupted cells to recreate a high resolution karyotype in silico. The end product does not yet have a consistent name, and has been called virtual karyotyping,[8][10] digital karyotyping,[11] molecular allelokaryotyping,[12] and molecular karyotyping.[13] Other terms used to describe the arrays used for karyotyping include SOMA (SNP oligonucleotide microarrays)[14] and CMA (chromosome microarray).[15][16] Some consider all platforms to be a type of array comparative genomic hybridization (arrayCGH), while others reserve that term for two-dye methods, and still others segregate SNP arrays because they generate more and different information than two-dye arrayCGH methods.[citation needed]
Copy number changes can be seen in both germline and tumor samples. Copy number changes can be detected by arrays with non-polymorphic probes, such as arrayCGH, and by SNP-based arrays. Human beings are diploid, so a normal copy number is always two for the non-sex chromosomes.[citation needed]
Autozygous segments and uniparental disomy (UPD) are diploid/'copy neutral' genetic findings and therefore are only detectable by SNP-based arrays. Both autozygous segments and UPD will show loss of heterozygosity (LOH) with a copy number of two by SNP array karyotyping. The term Runs of Homozgygosity (ROH), is a generic term that can be used for either autozygous segments or UPD.[citation needed]
Figure 7 is a SNP array virtual karyotype from a colorectal carcinoma demonstrating deletions, gains, amplifications, and acquired UPD (copy neutral LOH).
A virtual karyotype can be generated from nearly any tumor, but the clinical meaning of the genomic aberrations identified are different for each tumor type. Clinical utility varies and appropriateness is best determined by an oncologist or pathologist in consultation with the laboratory director of the lab performing the virtual karyotype. Below are examples of types of cancers where the clinical implications of specific genomic aberrations are well established. This list is representative, not exhaustive. The web site for the Cytogenetics Laboratory at Wisconsin State Laboratory of Hygiene has additional examples of clinically relevant genetic changes that are readily detectable by virtual karyotyping.
Based on a series of 493 neuroblastoma samples, it has been reported that overall genomic pattern, as tested by array-based karyotyping, is a predictor of outcome in neuroblastoma:[24]
Earlier publications categorized neuroblastomas into three major subtypes based on cytogenetic profiles:[25]
Tumor-specific loss-of-heterozygosity (LOH) for chromosomes 1p and 16q identifies a subset of Wilms' tumor patients who have a significantly increased risk of relapse and death. LOH for these chromosomal regions can now be used as an independent prognostic factor together with disease stage to target intensity of treatment to risk of treatment failure.[26][27]
Renal epithelial neoplasms have characteristic cytogenetic aberrations that can aid in classification.[28] See also Atlas of Genetics and Cytogenetics in Oncology and Haematology.
Array-based karyotyping can be used to identify characteristic chromosomal aberrations in renal tumors with challenging morphology.[8][10] Array-based karyotyping performs well on paraffin embedded tumors[29] and is amenable to routine clinical use.
In addition, recent literature indicates that certain chromosomal aberrations are associated with outcome in specific subtypes of renal epithelial tumors.[30]
Clear cell renal carcinoma: del 9p and del 14q are poor prognostic indicators.[31][32]
Papillary renal cell carcinoma: duplication of 1q marks fatal progression.[33]
Array-based karyotyping is a cost-effective alternative to FISH for detecting chromosomal abnormalities in chronic lymphocytic leukemia (CLL). Several clinical validation studies have shown >95% concordance with the standard CLL FISH panel.[12][34][35][36][37] In addition, many studies using array-based karyotyping have identified 'atypical deletions' missed by the standard FISH probes and acquired uniparental disomy at key loci for prognostic risk in CLL.[38][39]
Four main genetic aberrations are recognized in CLL cells that have a major impact on disease behavior.[40]
Avet-Loiseau, et al. in Journal of Clinical Oncology, used SNP array karyotyping of 192 multiple myeloma (MM) samples to identify genetic lesions associated with prognosis, which were then validated in a separate cohort (n = 273).[41] In MM, lack of a proliferative clone makes conventional cytogenetics informative in only ~30% of cases. FISH panels are useful in MM, but standard panels would not detect several key genetic abnormalities reported in this study.[citation needed]
Array-based karyotyping cannot detect balanced translocations, such as t(4;14) seen in ~15% of MM. Therefore, FISH for this translocation should also be performed if using SNP arrays to detect genome-wide copy number alterations of prognostic significance in MM.[citation needed]
Array-based karyotyping of 260 medulloblastomas by Pfister S, et al. resulted in the following clinical subgroups based on cytogenetic profiles:[42]
The 1p/19q co-deletion is considered a "genetic signature" of oligodendroglioma. Allelic losses on 1p and 19q, either separately or combined, are more common in classic oligodendrogliomas than in either astrocytomas or oligoastrocytomas.[43] In one study, classic oligodendrogliomas showed 1p loss in 35 of 42 (83%) cases, 19q loss in 28 of 39 (72%), and these were combined in 27 of 39 (69%) cases; there was no significant difference in 1p/19q loss of heterozygosity status between low-grade and anaplastic oligodendrogliomas.[43] 1p/19q co-deletion has been correlated with both chemosensitivity and improved prognosis in oligodendrogliomas.[44][45] Most larger cancer treatment centers routinely check for the deletion of 1p/19q as part of the pathology report for oligodendrogliomas. The status of the 1p/19q loci can be detected by FISH or virtual karyotyping. Virtual karyotyping has the advantage of assessing the entire genome in one assay, as well as the 1p/19q loci. This allows assessment of other key loci in glial tumors, such as EGFR and TP53 copy number status.[citation needed]
Whereas the prognostic relevance of 1p and 19q deletions is well established for anaplastic oligodendrogliomas and mixed oligoastrocytomas, the prognostic relevance of the deletions for low-grade gliomas is more controversial. In terms of low-grade gliomas, a recent study also suggests that 1p/19q co-deletion may be associated with a (1;19)(q10;p10) translocation which, like the combined 1p/19q deletion, is associated with superior overall survival and progression-free survival in low-grade glioma patients.[46] Oligodendrogliomas show only rarely mutations in the p53 gene, which is in contrast to other gliomas.[47] Epidermal growth factor receptor amplification and whole 1p/19q codeletion are mutually exclusive and predictive of completely different outcomes, with EGFR amplification predicting poor prognosis.[48]
Yin et al.[49] studied 55 glioblastoma and 6 GBM cell lines using SNP array karyotyping. Acquired UPD was identified at 17p in 13/61 cases. A significantly shortened survival time was found in patients with 13q14 (RB) deletion or 17p13.1 (p53) deletion/acquired UPD. Taken together, these results suggest that this technique is a rapid, robust, and inexpensive method to profile genome-wide abnormalities in GBM. Because SNP array karyotyping can be performed on paraffin embedded tumors, it is an attractive option when tumor cells fail to grow in culture for metaphase cytogenetics or when the desire for karyotyping arises after the specimen has been formalin fixed.[citation needed]
The importance of detecting acquired UPD (copy neutral LOH) in glioblastoma:[citation needed]
In addition, in cases with uncertain grade by morphology, genomic profiling can assist in diagnosis.
Cytogenetics, the study of characteristic large changes in the chromosomes of cancer cells, has been increasingly recognized as an important predictor of outcome in acute lymphoblastic leukemia (ALL).[52]
NB: Balanced translocations cannot be detected by array-based karyotyping (see Limitations below).
Some cytogenetic subtypes have a worse prognosis than others. These include:
Cytogenetic change | Risk category |
---|---|
Philadelphia chromosome | Poor prognosis |
t(4;11)(q21;q23) | Poor prognosis |
t(8;14)(q24.1;q32) | Poor prognosis |
Complex karyotype (more than four abnormalities) | Poor prognosis |
Low hypodiploidy or near triploidy | Poor prognosis |
High hyperdiploidy | Good prognosis |
del(9p) | Good prognosis |
Correlation of prognosis with bone marrow cytogenetic finding in acute lymphoblastic leukemia
Prognosis | Cytogenetic findings |
---|---|
Favorable | Hyperdiploidy > 50 ; t (12;21) |
Intermediate | Hyperdioloidy 47 -50; Normal(diploidy); del (6q); Rearrangements of 8q24 |
Unfavorable | Hypodiploidy-near haploidy; Near tetraploidy; del (17p); t (9;22); t (11q23) |
Unclassified ALL is considered to have an intermediate prognosis.[56]
Myelodysplastic syndrome (MDS) has remarkable clinical, morphological, and genetic heterogeneity. Cytogenetics play a decisive role in the World Health Organization's classification-based International Prognostic Scoring System (IPSS) for MDS.[57][58]
In a comparison of metaphase cytogenetics, FISH panel, and SNP array karyotyping for MDS, it was found that each technique provided a similar diagnostic yield. No single method detected all defects, and detection rates improved by ~5% when all three methods were used.[59]
Acquired UPD, which is not detectable by FISH or cytogenetics, has been reported at several key loci in MDS using SNP array karyotyping, including deletion of 7/7q.[60][61]
Philadelphia chromosome–negative myeloproliferative neoplasms (MPNs) including polycythemia vera, essential thrombocythemia, and primary myelofibrosis show an inherent tendency for transformation into leukemia (MPN-blast phase), which is accompanied by acquisition of additional genomic lesions. In a study of 159 cases,[62] SNP-array analysis was able to capture practically all cytogenetic abnormalities and to uncover additional lesions with potentially important clinical implications.[citation needed]
Identification of biomarkers in colorectal cancer is particularly important for patients with stage II disease, where less than 20% have tumor recurrence. 18q LOH is an established biomarker associated with high risk of tumor recurrence in stage II colon cancer.[63] Figure 7 shows a SNP array karyotype of a colorectal carcinoma (whole genome view).
Colorectal cancers are classified into specific tumor phenotypes based on molecular profiles[63] which can be integrated with the results of other ancillary tests, such as microsatellite instability testing, IHC, and KRAS mutation status:
Malignant rhabdoid tumors are rare, highly aggressive neoplasms found most commonly in infants and young children. Due to their heterogenous histologic features, diagnosis can often be difficult and misclassifications can occur. In these tumors, the INI1 gene (SMARCB1)on chromosome 22q functions as a classic tumor suppressor gene. Inactivation of INI1 can occur via deletion, mutation, or acquired UPD.[64]
In a recent study,[64] SNP array karyotyping identified deletions or LOH of 22q in 49/51 rhabdoid tumors. Of these, 14 were copy neutral LOH (or acquired UPD), which is detectable by SNP array karyotyping, but not by FISH, cytogenetics, or arrayCGH. MLPA detected a single exon homozygous deletion in one sample that was below the resolution of the SNP array.[citation needed]
SNP array karyotyping can be used to distinguish, for example, a medulloblastoma with an isochromosome 17q from a primary rhabdoid tumor with loss of 22q11.2. When indicated, molecular analysis of INI1 using MLPA and direct sequencing may then be employed. Once the tumor-associated changes are found, an analysis of germline DNA from the patient and the parents can be done to rule out an inherited or de novo germline mutation or deletion of INI1, so that appropriate recurrence risk assessments can be made.[64]
The most important genetic alteration associated with poor prognosis in uveal melanoma is loss of an entire copy of Chromosome 3 (Monosomy 3), which is strongly correlated with metastatic spread.[65] Gains on chromosomes 6 and 8 are often used to refine the predictive value of the Monosomy 3 screen, with gain of 6p indicating a better prognosis and gain of 8q indicating a worse prognosis in disomy 3 tumors.[66] In rare instances, monosomy 3 tumors may duplicate the remaining copy of the chromosome to return to a disomic state referred to as isodisomy.[67] Isodisomy 3 is prognostically equivalent to monosomy 3, and both can be detected by tests for chromosome 3 loss of heterozygosity.[68]
Unlike karyotypes obtained from conventional cytogenetics, virtual karyotypes are reconstructed by computer programs using signals obtained from disrupted DNA. In essence, the computer program will correct translocations when it lines up the signals in chromosomal order. Therefore, virtual karyotypes cannot detect balanced translocations and inversions. They also can only detect genetic aberrations in regions of the genome that are represented by probes on the array. In addition, virtual karyotypes generate a relative copy number normalized against a diploid genome, so tetraploid genomes will be condensed into a diploid space unless renormalization is performed. Renormalization requires an ancillary cell-based assay, such as FISH, if one is using arrayCGH. For karyotypes obtained from SNP-based arrays, tetraploidy can often be inferred from the maintenance of heterozygosity within a region of apparent copy number loss.[22] Low-level mosaicism or small subclones may not be detected by virtual karyotypes because the presence of normal cells in the sample will dampen the signal from the abnormal clone. The exact point of failure, in terms of the minimal percentage of neoplastic cells, will depend on the particular platform and algorithms used. Many copy number analysis software programs used to generate array-based karyotypes will falter with less than 25–30% tumor/abnormal cells in the sample. However, in oncology applications this limitation can be minimized by tumor enrichment strategies and software optimized for use with oncology samples. The analysis algorithms are evolving rapidly, and some are even designed to thrive on 'normal clone contamination',[69] so it is anticipated that this limitation will continue to dissipate.
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