Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.
In plasma cell neoplasms (PCNs), a genetically heterogeneous disease group with inherently low proliferation rate, it has been shown that aCGH is superior for disease risk stratification compared with conventional cytogenetic or FISH studies (7). Similarly, aCGH allows better characterization of the 13q14 deletion common in chronic lymphocytic leukemia (CLL). Deletions of 13q14 can be divided into 2 groups: low risk, which are lesions <2 Mb [tumor suppressor gene RB1 (retinoblastoma 1)  not deleted] and high risk, which are deletions [greater than or equal to]2 Mb (8).
In contrast to aCGH, FISH, and conventional cytogenetic studies, single nucleotide polymorphism (SNP) arrays can identify uniparental disomy (UPD) (1, 9). In neoplastic transformation, somatic cells acquire UPD through chromosomal segregation errors during mitosis (10, 11). UPD contributes to tumorigenesis when the affected region contains inactivated tumor suppressor genes or activated oncogenes (12). In myelodysplastic syndrome (MDS), UPD of chromosome 7 and 7q deletions have similar effects on patient outcome (13).
Although aCGH and SNP microarray analysis have numerous advantages, several technical and analytical limitations exist (14). Balanced structural rearrangements such as translocations and inversions are not detected, and assay sensitivity is limited to cases with a tumor burden >20%. Moreover, clonal heterogeneity may confound results. Microarray (aCGH and SNP array) analysis does identify clonal evolution by comparing sequential samples during the treatment course (15, 16). Unlike FISH and conventional cytogenetic studies, detection of clonal heterogeneity within a single sample by microarray analysis is limited and, to our knowledge, not commonly applied in a clinical setting.
Previous studies have theorized the presence of clonal subpopulations by assessing [log.sub.2] ratios or B-allele frequencies and postulating differences as potential indicators for clonal evolution (17-24). Because clonal evolution is associated with disease progression and adverse clinical outcome (25-27), detection and characterization of subclonal populations by microarray analysis could improve the clinical workup of hematopoietic malignancies.
Using a novel combination of both aCGH and SNP data, in this study, we established further indicators for identifying multiple related clonal populations. We applied an analytical approach called manual peak reassignment to individually adjust SNP data, allowing the characterization and, importantly, confirmation of genomic aberrations present in clonal subfractions. Proficiency of this algorithmic approach was evaluated by use of 16 neoplastic hematopoietic samples; results were compared with conventional FISH and/or cytogenetic analysis. Improved monitoring of clonal progression by combined SNP/aCGH analysis was also demonstrated by use of 3 selected case studies.
Materials and Methods
The sample cohort comprised 16 cases: 13 cases [test cohort: 2 CLL, 2 PCN, 1 suspected MDS, and 8 acute myeloid leukemia (AML)] were evaluated for clonal evolution by use of the manual peak reassignment approach; additionally, 3 MDS cases (monitoring cohort) with available follow-up material were evaluated for clonal evolution during disease progression. Sample handling was in compliance with institutional review board review exemption issued by the Western Institutional Review Board (Olympia, Washington). Genomic DNA was isolated from tissue, bone marrow aspirates, peripheral blood, and, in PCN, [CD138.sup.+]-enriched cell populations by use of the QIAmp DNA mini kit (Qiagen).
We processed sample DNA and sex-matched normal reference DNA using the SureTag Complete DNA Labeling Kit (Agilent Technologies) per the manufacturer's recommendations. We evaluated the samples for genomic aberrations using the Agilent SurePrint G3 Cancer CGH + SNP 4x180K Microarray. This chip, designed by the Cancer Cytogenomics Microarray Consortium, contains >180000 features, including approximately 20 000 cancer-associated CGH probes and approximately 60 000 SNP probes.
We used Agilent CytoGenomics and Nexus Copy Number (BioDiscovery) software programs for data analysis (see Supplemental Data, which accompanies the online version of this article at http://www. clinchem.org/content/vol60/issue12). We assessed the data quality using the derivative log ratio spread (DLRS) value (28). We observed DLRS values between 0.109 and 0.269 (mean 0.178), indicating good quality of the microarray data sets.
IDENTIFICATION OF CLONAL HETEROGENEITY
We used 4 parameters to identify clonal heterogeneity (Fig. 1): clonal fraction, discrepancy between CGH and SNP data, complex distribution of [log.sub.2] ratios, and peaks in the distribution plot not assigned a CN.
For the clonal fraction, we used the [log.sub.2] ratios to estimate the percentage of cells harboring a particular aberration. Because the [log.sub.2] ratio reflects the CN sample-to-reference ratio and both the tumor and the nondiseased counterpart of a heterogeneous sample contribute to the sample CN, we used the following formulas (21) to appraise the proportion of cells harboring a particular chromosome aberration:
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For the discrepancy between CGH and SNP data, by default the allele-specific copy number (ASCN) was calculated for the most aberrant clone. The presence of a subclone was consequently indicated if the [log.sub.2] ratio showed a significant deviation from the modal value of 0.0, indicating either a gain or loss for a particular genomic region, but the ASCN remained 2.
For the complex distribution of [log.sub.2] ratios, when plotting the distribution of [log.sub.2] ratios, we looked for bell-shaped peaks in the plot representing ratios associated with particular CNs. For example, a peak at [log.sub.2] of 0.0 corresponds with a CN of 2. The presence of multiple peaks within the distribution plot is suggestive of clonal heterogeneity.
For the peaks in the distribution plot not assigned a CN, although the software initially assigns CN states to peaks in the distribution plot, these assignments are based on aberrations present in the most prominent abnormal cell clone, omitting peaks originating from CN changes in minor clonal populations. Consequently, peaks without an assigned CN likely represent an aberration originating from a subclone.
An analysis algorithm called manual peak reassignment was evaluated and used to achieve improved resolution of clonal composition and confirm the presence of clonal subpopulations (29). For analysis of minor clones, peaks of the CGH probe distribution plot were manually reassigned. Peaks corresponding to the CGH [log.sub.2] ratios of abnormalities in the major clones were manually deleted and replaced by peaks putatively associated with a minor clonal population. Next, the clone fraction and ASCN were recalculated. The success of this manipulation was evaluated by reviewing the new SNP copy number calls. The presence and characteristics of a minor clone were accepted when new SNP plots (ASCN) became consistent with the corresponding CGH data.
FISH AND CONVENTIONAL CYTOGENETIC STUDIES
We performed interphase FISH studies as previously described (7) using probe panels that routinely identify common chromosome aberrations in hematologic neoplasms (Tables 1 and 2; online Supplemental Tables 1-3).
We performed cytogenetic studies in 12 of 13 samples of the test cohort. Cytogenetic studies performed on the monitoring cohort are listed in Table 2 and online Supplemental Table 3. All samples were processed by use of 24- and 48-h culture conditions. Samples were stimulated with interleukin (IL)-2 (Sigma-Aldrich Corp.) for PCN or with IL-2 and CpG oligonucleotide (DSP30, TIB MOLBIOL) for CLL. Typically, 20 metaphases were analyzed per case.
INDICATORS OF CLONAL HETEROGENEITY IDENTIFIED BY aCGH/SNP ANALYSIS
A total of 13 samples (test cohort) were evaluated for clonal heterogeneity with combined SNP/aCGH microarray analysis. The clonal fraction containing a particular genomic abnormality was calculated by use of the [log.sub.2] ratio. Clonal diversity was suspected if the clonal fraction between 2 or more aberrations identified within the same sample differed by >15% (valid for all cases) (Table 1; online Supplemental Table 2). The smallest difference in clonal fractions was observed in case AML-5, with a gain of 11q23.3q25 (15.7 Mb) and trisomy 19 in the major clone in approximately 41% of cells and a minor subclone carrying an additional deletion of 2p16.1p15 (1.7 Mb), 4p14p13 (3.3 Mb), and gain of 3p26.3p11.1 (90.2 Mb), 18q11.2q23 (55.7 Mb) and chromosomes 6 and 13 in approximately 23% of cells.
In addition to the [log.sub.2] ratio variance, other indicators of clonal heterogeneity were identified in each sample. Microarray data for all samples demonstrated discrepancies between calculated CGH and SNP results for certain abnormalities. Although CN changes were identified in these samples, the corresponding ASCN remained 2 at affected genomic regions, contradicting a CN gain or loss (Fig. 1B). This difference between CGH and SNP data is highly suggestive of minor clonal cell populations, since the ASCN is calculated by use of CGH data exclusively for major clone abnormalities, omitting CGH data originating from subclones.
A further indication of clonal heterogeneity, i.e., complex distributions of [log.sub.2] ratios, was observed in cases AML-6 (Fig. 2), AML-4, PCN-10, and PCN-12. Up to 7 peaks were identified in the distribution plots, indicating the presence of multiple clones with copy number aberrations (see online Supplemental Fig. 1).
Furthermore, the [log.sub.2] ratio distribution plots for cases AML-6 (Fig. 1D), AML-1, AML-2, AML-4, AML-8, and PCN-12 demonstrated peaks without assigned CNs, which putatively correspond to aberrations in a minor clone population.
MANUAL PEAK REASSIGNMENT ALLOWS FOR IMPROVED RESOLUTION OF CLONAL HETEROGENEITY
Separation of major and minor clone abnormalities according to manual peak reassignments was successfully performed in 10 of 13 cases by harmonizing copy number states independently calculated from CGH and SNP results (Table 1; online Supplemental Table 2).
Here, 1-8 (median 3.5) additional aberrations were verified in minor clonal populations revealing clonal evolution. Fig. 2 (AML-6) illustrates this. Initially, the software algorithm assigned the [log.sub.2] ratio of -0.9 to CN 1, corresponding to loss of 5q11.1q35.3 (131.1 Mb), 6p25p22.1 (27.9 Mb), and 20p13p11.22 (21.8 Mb) and gain of 5p15.33p11 (46.2 Mb) and loss of chromosome 18 (Fig. 3A). However, although a 55.2-Mb deletion of 13q12.3q31.1 ([log.sub.2] = -0.30) and gain of 8q11.21q24.3 ([log.sub.2] = 0.27) were also detected, they were not assigned in the [log.sub.2] ratio distribution plot. Consequently, the ASCN only concurred with aberrations on 5p, 5q, 6p, 20p, and chromosome 18. After manual peak reassignment and ASCN reanalysis, SNP data confirmed the 13q deletion and 8q gain as subclonal aberrations.
For 3 of 13 cases (AML-5, AML-8, MDS-9), clonal composition resolution was limited. Microarray demonstrated clonal heterogeneity, since variable clonal fractions (on the basis of [log.sub.2] ratios) and discrepancies between CGH copy number status and ASCN were observed. The CGH distribution plot for case AML-8 also contained unassigned peaks. However, even after manual copy number assignment, the recalculated SNP data for putative minor clones demonstrated CN states different from those obtained from CGH data (see online Supplemental Fig. 2).
COMPARISON TO CYTOGENETIC ANALYSIS
For all cases, cytogenetic studies revealed complex abnormalities and clonal evolution. A median of 3.5 related clones (range 3-7) were identified per sample (Table 1; online Supplemental Tables 1 and 2). In contrast, manual peak reassignment was able to identify only 1 subclone in most samples. In 8 of 12 cases, cytogenetic studies described aberrations undetected by aCGH/SNP analysis, a phenomenon particularly noticeable in cases with small subclones (e.g., AML-2, AML-7, CLL-11) or complex clonal compositions (PCN-10, CLL-13). The array algorithmic approach, on the other hand, mapped lesions at greater resolution than standard chromosome banding, revealing involvement of cancer or other disease-associated genes. For example, in cases CLL-11 and CLL-13, microarray analysis confirmed deletions of tumor suppressor genes RB1 and TP53 (tumor protein p53), respectively (online Supplemental Fig. 3).
Furthermore, cytogenetic analysis identified marker chromosomes of unknown origin in 7 of 12 cases (58%), providing incomplete characterization of all chromosome abnormalities present. In such cases, addition of array CGH can improve the delineation of deleted or gained chromosome segments.
COMPARISON TO FISH ANALYSIS
FISH studies were performed on 10 of 13 samples (Table 1; online Supplemental Table 2). For samples AML-1, AML-4, and AML-6, FISH studies identified additional genomic abnormalities not detected by microarray analysis in clonal subpopulations. Minor clone aberrations were identified in 23%, 21%, and 6% of nuclei examined, respectively. In contrast, microarray analysis detected clonal evolution affecting genomic regions not covered by standard FISH probe panels (Table 1; online Supplemental Table 2) in 9 of 10 cases. For example, a 55-Mb deletion of 13q (including RB1) originating from a subclone fraction was revealed exclusively by microarray analysis (sample AML-6). SNP/aCGH data revealed that aberrations were more complex than suggested by FISH studies in all but 1 sample exhibiting clonal evolution (exception: MDS-9). Moreover, in 3 of 10 cases (AML-3, AML-8, CLL-11), FISH studies did not reveal clonal heterogeneity.
Case studies best demonstrate comparisons of detection of clonal evolution with differing technologies.
TREATMENT MONITORING AND SAMPLES WITH LOW CELLULARITY
Microarray analysis for case AML-6, a 55-year-old woman with secondary AML, demonstrated a major clone characterized by gain of 5p15.33p11 (46.2 Mb) and loss of 5q11.1q35.3 (131.1 Mb), 6p25.3p22.1 (27.9 Mb), 20p13p11.22 (21.8 Mb), and chromosome 18. Additionally, a subpopulation with deletion of 13q12.3q31.1 (55.2 Mb) and gain of 8q11.21q24.3 (96.3 Mb) was identified, suggesting clonal evolution (Fig. 3A). FISH and cytogenetic findings correlated: FISH demonstrated deletion of 5q combined with gain of 5p, an extra copy of 8q22, and gain of 11q23 in 84.5%, 50%, and 6% of nuclei examined, respectively. Cytogenetic analysis revealed complex abnormal findings with isochromosome of 5p, rearrangement of chromosome 6, and loss of chromosomes 18 and 20 in all cells examined. Seven cells also showed loss of chromosome 13, a derivative chromosome resulting from a translocation with the long arm of chromosome 8, and 1-2 unidentified marker chromosomes, indicating clonal evolution (Fig. 3B). To evaluate discrepancies between aCGH findings and cytogenetic results (deletion of 13q12.3q31.1 vs monosomy 13), additional metaphase FISH studies were performed and revealed juxtaposition of 13q34 on the terminal end of chromosome 6 (Fig. 3C). This verified that the 13q34 region was present and an unbalanced rearrangement between chromosomes 6 and 13 was effectively causing a deletion of 13q as identified by aCGH analysis.
Sequential microarray data was available for this patient at 6.5 weeks and 4 months postdiagnosis. The 6.5-week bone marrow aspirate was low-positive for the major clone (+5p, -5q, -6p, -18, -20p) previously identified by aCGH analysis but not for minor aberrations (+8q, -13q) previously detected. No additional aberrations or further clonal evolution was identified. At 4 months, follow-up demonstrated continued presence of the major clone aberrations, indicating tumor persistence; FISH and cytogenetic studies failed due to low sample cellularity.
LOSS OF HETEROZYGOSITY DETECTION FOR IMPROVED MONITORING OF CLONAL EVOLUTION
In addition to identifying clonal heterogeneity/evolution within a single sample, in 3 MDS cases, we also used SNP/aCGH analysis to monitor clonal progression during the disease course (Table 2, online Supplemental Table 3).
Case MDS-14, an 88-year-old woman with pancytopenia and suspected MDS, was seen over a 1.5-year period including examination of 4 samples. Initial cytogenetic findings were normal. FISH studies 6 months later were negative for gains or losses of chromosomes 5q, 7q, 17p, and 20q. Concordantly, SNP/aCGH analysis was negative for numerical aberrations; however, a 52.2-Mb-long region of loss of heterozygosity (LOH) affecting 7q (7q22.3-7q36.3) was detected. At 2 later time points, FISH studies were normal but LOH of 7q was identified, indicating continued presence of the clonal population.
Similarly, cytogenetic and FISH studies for case MDS-15 were normal whereas microarray analysis detected LOH affecting 18q (18q11.2-18q23, 54 Mb). Six months later, another sample was negative for PML/ RARA (promyelocytic leukemia/retinoic acid receptor, a) and RUNX1T1/RUNX1 [runt-related transcription factor 1, translocated to, 1 (cyclin D-related) (formerly ETO)/runt-related transcription factor 1] translocations, mixed-lineage leukemia (MLL) and corebinding factor, [beta] subunit (CBFB) rearrangements, and numerical abnormalities affecting 5q, 7q, 17p, and 20q by FISH. SNP/aCGH revealed continued clonal presence characterized by a large LOH region on 18q; an additional region of LOH was detected on 21q, including (but not limited to) cancer-associated genes OLIG2 (oligodendrite lineage transcription factor 2), RUNX1, ERG (v-ets avian erythroblastosis virus E26 oncogene homolog), TMPRSS2 (transmembrane protease, serine 2), and U2AF1 (U2 small nuclear RNA auxiliary factor 1). Detection of the new abnormality may indicate clonal progression or evolution.
Cytogenetic studies for patient MDS-16 identified a deletion on chromosome 5q in all 20 cells examined, and FISH analysis revealed deletion of 5q in 56% of cells; SNP/aCGH studies were positive for loss of 5q from 5q14.2 to 5q34 (79 Mb).
A subsequent sample was received for follow-up at 9 weeks. Cytogenetic studies demonstrated continued presence of the isolated 5q deletion, as did FISH analysis (deletion of 5q in 5% of cells examined). SNP/ aCGH analysis, however, revealed evidence of clonal evolution. In addition to the loss of 5q from 5q14.2 to 5q34, a new region of LOH/UPD on 18q (18q21.33-18q22.2, 7.9 Mb), including BCL2 (B-cell CLL/lymphoma 2), was detected.
This study presents a novel analytical approach that capitalizes on the unique dual nature of new microarray platforms featuring aCGH and SNP probe sets on a single chip. By combining aCGH with SNP data and incorporating 2 independent measurements, we identified and confirmed clonal heterogeneity with increased certainty. The prognostic significance of complex cytogenetics and identification of clonal evolution in AML is well established (30-33). Microarray data has demonstrated that the presence of clonal heterogeneity is associated with poor prognosis in CLL (19) and mantle cell lymphoma (25). In PCN, the prognostic impact of clonal heterogeneity may still be underestimated owing to technical limitations in identifying clonal evolution. Conventional cytogenetic studies often fail to detect genomic aberrations in a significant number of PCN cases owing to the inherently low proliferation rate of plasma cells in vitro (34-36). Hence, in combination with plasma cell enrichment strategies, new prognostic information might emerge from microarray studies that use improved approaches to evaluate and assess clonal heterogeneity.
Despite the application of more sophisticated analytical approaches for improved characterization of major and minor clones, cell populations must be adequately ample to exceed the sensitivity limit of microarray analysis (approximately 15%-20%). We have demonstrated that when meeting this criterion, the technique can separate and characterize aberrations originating from a major clone and from subclonal populations; identification of genomic aberrations is possible even in cases of relatively small subclonal cell fractions. Still, in cases where the manual peak reassignment approach demonstrated that the size of clonal subpopulations differed by <30% from the main clone, limited separation of clonal subfractions was achieved (AML-5, AML-8, MDS-9). Therefore, we hypothesize that robust separation of major and minor clonal populations by use of manual peak reassignment requires a significant difference in [log.sub.2] ratios.
We detected several differences when comparing conventional cytogenetic results with microarray findings. Cytogenetic characterization of major and minor clone aberrations was generally more complex and did not fully match microarray results (e.g., identification of further subclones by cytogenetics, variations in breakpoints, or copy number status of entire chromosomes). Whereas cytogenetic studies are performed at a single-cell level and thereby identify differences between 2 or more metaphase cells within a sample, the resolution needed to detect subtle and cryptic chromosome abnormalities or precisely identify breakpoints is lacking. Additionally, cytogenetic studies can identify aberrations only in cells that proliferate in vitro, whereas microarray analysis is performed on DNA derived from cells in all phases of the cell cycle. Consequently, the major clone identified by cytogenetic analysis may not always reflect the prevalent clone in the uncultured sample or may not detect aberrant populations with low proliferation index. The number of analyzed cells might be another technical factor that contributes to discrepancies between cytogenetic and microarray studies. Cytogeneticists routinely evaluate 20 metaphases, and it is possible that this fraction does not always accurately reflect the true clonal composition of the sample. In contrast, thousands of cells are interrogated by the microarray approach, leading to a less random appraisal. However, cytogenetic analysis can examine subclonal populations present well below the detection sensitivity of aCGH/SNP studies. Therefore, differences between clonal fractions as determined by cytogenetic and microarray studies must be interpreted appropriately.
Cytogenetic studies can detect aberrations classified as marker chromosomes (genomic material not assigned a chromosomal origin due to lack of identifiable specific chromosome banding patterns); genomic material described as deleted by chromosome analysis could be located on a marker chromosome, resulting in an abnormal call by cytogenetic analysis but normal gene dosage by microarray analysis.
Case study AML-6 demonstrated the value of identification of clonal heterogeneity for monitoring treatment response. Although aCGH/SNP analysis at diagnosis demonstrated 2 clones, follow-up post-treatment samples identified continued presence of only the major clone, suggesting that it was less responsive to the administered chemotherapy. This case highlights another advantage of the SNP/aCGH technology. Whereas cytogenetic and FISH studies failed in follow-up samples owing to inadequate sample cellularity, microarray analysis demonstrated the continued presence of the major clone abnormalities. Therefore, in cases of insufficient sample quality (e.g., low proliferative index or low cellularity), SNP/aCGH analysis could be an alternate approach to provide valuable clinical information.
Regions of LOH are important genetic aberrations, particularly in myeloid disorders (MDS, AML), and can be detected only by SNP microarray analysis. Here, we demonstrate the importance of LOH detection to identify clonal evolution events not detectable by conventional cytogenetics or FISH techniques by outlining 3 MDS case studies. Interestingly, for 1 case (MDS-16), FISH analysis revealed a significant decrease in the extent of del(5q) as the sole abnormality compared to the diagnostic sample, suggesting a positive response to treatment. However, SNP/aCGH microarray studies demonstrated a previously undetected large region of LOH on chromosome 18q, indicating clonal evolution; therefore, SNP/aCGH microarray analysis may be able to reveal otherwise undetected clonal evolution and progression, thereby allowing earlier treatment interventions or changes in therapy.
In conclusion, the combined approach of SNP/ aCGH data analysis with manual peak reassignment algorithm improves characterization of genomic aberrations in clonal evolution in hematological malignancies. Advantages of microarray technology over conventional cytogenetic and FISH studies for documentation of clonal evolution include superior description of specific aberrations, evaluation of the entire genome in 1 assay, detection of LOH, and the ability to analyze nondividing cells. Microarray analysis confers additional benefits to be considered in a clinical laboratory setting. Standardized microarray analysis algorithms can offer increased resolution for detecting genomic gains and losses in comparison to conventional cytogenetics, since some of these are too small to be observed at the cytogenetic level. Detection of small or subtle cytogenetic aberrations can depend on the quality of chromosome resolution and morphology, which in hematopoietic neoplasms varies from 1 laboratory to another depending on culture systems used and banding techniques. Further, analysis and detection of subtle abnormalities can be subject to the expertise of cytogeneticist. However, microarray analysis should not be seen as a stand-alone technique in characterizing clonal evolution in hematopoietic malignancies, but rather as a complementary addition to established FISH and cytogenetic studies, since sensitivity is limited and balanced chromosome rearrangements cannot be detected.
Integrating cytogenetic, FISH, and microarray data allows greater confidence in detection and description of clonal aberrations, fostering improved, patient-specific management. To the best of our knowledge, all currently available microarray software packages assess the data assuming exclusive presence of a single clone. Although this is adequate for analysis of constitutional aberrations, uniclonal analysis does not meet the need for identifying and analyzing the clonal heterogeneity seen in oncology samples. Manual peak reassignment of data combining aCGH and SNP results from 1 microarray chip can distinguish aberrations originating from clonal subpopulations. In this study, we have demonstrated the clinical utility of this approach. Future software tools may become available to enhance and automate this feature, highlighting and detecting clonal heterogeneity and simplifying user analysis.
Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, oranalysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:
Employment or Leadership: None declared.
Consultant or Advisory Role: None declared.
Stock Ownership: M.R. Loken, HematoLogics Inc.; B.K. Zehentner, HematoLogics Inc.
Honoraria: None declared.
Research Funding: L. Hartmann, student stipend provided by HematoLogics during previous internship work partially represented in this study.
Expert Testimony: None declared.
Patents: None declared.
Role of Sponsor: No sponsor was declared.
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(36.) Hartmann L, Biggerstaff JS, Chapman DB, Scott JM, Johnson KR, Ghirardelli KM, et al. Detection of genomic abnormalities in multiple myeloma: the application of FISH analysis in combination with various plasma cell enrichment techniques. Am J Clin Pathol 2011;136:712-20.
(37.) American College of Medical Genetics. Standards and Guidelines for Clinical Genetics Laboratories. 2009 ed., revised 01/2010. Section E, Clinical cytogenetics. https://www.acmg.net/Static Content/SGs/Section_E_2011.pdf (Accessed October 2014).
Luise Hartmann,  Christine F. Stephenson,  Stephanie R. Verkamp,  Krystal R. Johnson,  Bettina Burnworth,  Kelle Hammock,  Lisa Eidenschink Brodersen,  Monica E. de Baca,  Denise A. Wells,  Michael R. Loken,  and Barbara K. Zehentner  *
 HematoLogics Inc., Seattle, WA.
* Address correspondence to this author at: HematoLogics Inc., 3161 Elliott Ave, Suite 200, Seattle, WA 98121. Fax 206-223-5550; e-mail firstname.lastname@example.org.
Received May 29, 2014; accepted September 12, 2014.
Previously published online at DOI: 10.1373/clinchem.2014.227785
 Nonstandard abbreviations: aCGH, array comparative genomic hybridization; CN, copy number; FISH, fluorescence in situ hybridization; PCN, plasma cell neoplasm; CLL, chronic lymphocytic leukemia; SNP, single nucleotide polymorphism; UPD, uniparental disomy; MDS, myelodysplastic syndrome; AML, acute myeloid leukemia; DLRS, derivative log ratio spread; ASCN, allele-specific copy number; IL, interleukin; MLL, mixed-lineage leukemia; CBFB, core-binding factor, [beta] subunit; LOH, loss of heterozygosity.
 Human genes: RB1, retinoblastoma 1; TP53, tumor protein p53; RUNX1T1, runt-related transcription factor 1, translocated to, 1 (cyclin D-related) (formerly ETO); RUNX1, runt-related transcription factor 1; OLIG2, oligodendrite lineage transcription factor 2; ERG, v-ets avian erythroblastosis virus E26 oncogene homolog; TMPRSS2, transmembrane protease, serine 2; U2AF1, U2 small nuclear RNA auxiliary factor 1; BCL2, B-cell CLL/lymphoma 2.
Table 1. Summary of results from CGH/SNP array, FISH, and conventional cytogenetic studies for 2 selected patients. (a) aCGH/SNP array findings Indicators Separation of clonal of subclones Patient heterogeneity possible AML-6 Discrepant ASCN; Yes unassigned peaks; complex log? distribution plot AML-7 Discrepant ASCN Yes aCGH/SNP array findings Major clone Minor clone aberrations aberrations Patient (clonal fraction) (clonal fraction) AML-6 + 5p15.3 3 p 11 (0.93); +8q11.21q24.3 (0.41); - 5q11.1q35.3 (0.88); - 13q12.3q31.1 (0.38) -6p2 5.3p22.1 (0.91); -18 (0.90); -20p13 p11.22 (0.88) AML-7 +8 (0.58) + 19 (0.30); +20p13 p11.1 (0.37); +20q11.21 q13.33 (0.28); +21 (0.35) FISH findings Number Major clone Minor clone of Patient aberrations (%) aberrations (%) clones AML-6 + 5p 1 5.2 (84.5); + 8q21.3 (50); 3 - 5 q 31 (84.5) +11q23 (6) AML-7 + 8 (42) + 20q12 (25.5) 3 Cytogenetics findings Identified aberrations [%] Patient Major clone Minor clone AML-6 i(5)(p10) ; -13 ; der(?) add(6)(p21) ; t(?;8)(?;q13) -18 ; ; +1-2mar ; -20  der(11)t(11;11)(p15; q13)  AML-7 t( 11; 17)(q23;q25) + 19 ; +20 ; ; +8 +21 ; -10 ;  der(11)t(10;11)(q22; q23) ; ins(12;?)(q 13;?) ; -17 ; +2mar  (a) Bold text indicates aberrations not identified by other technologies and present in >15% of analyzed cells. Table 2. Cytogenetic, FISH, and microarray results for 1 selected monitoring case (test results in International System for Chromosome Nomenclature). Case Date Cytogenetics FISH AML-6 July 2012 44, XX, nuc ish(EGR1x1, i(5)(p10), D5S721x3) [169/ add(6) (p21), 200]/(RUNX1 - 18, -20 T1x3) [100/ [cp10]/45, 200]/ idem, -13, (MLl_x3-4)[12/ der(?)t 200]/ (?;8)(?;q13), (D7S486x2), 2mar[cp7]/ (CEP8x2), 41 -44, idem, (CBFBx2), der(11 )t(11 (PMLx2), ;11 )(p15;q13) (RARAx2), (TP53x2), (D20S108x2), (RUNX1 x2) August 2012 44, XX, nuc ish(EGR1x1, i(5)(p10), D5S721x3)[14/ add(6)(p21), 200]/ -18, (D7S522x2), -20/46, (RUNX1T1), XX[11 ] (CEP8x2), (MLLx2), (PMLx2), (CBFBx2), (RARAx2), (TP53x2), (D20S108x2), (RUNX1x2) November Failed Failed 2012 Case Date aCGH/SNP AML-6 July 2012 arr 5p15.33p11 (120, 415-46, 365, 277)x3, 5q11.1 q 3 5.3 (49, 584, 189-180, 712, 263)x1, 6p25.3p22.1 (219, 055-28, 145, 142)x1, 8q11.21 q24.3(49, 895, 720-146, 196, 317)x3, 13q12.3q31.1 (30, 251, 591-85, 475, 499)x1, (18)x1, 20p13p11.22(67, 778-21, 850, 779)x1 August 2012 arr 5p15.33p12(0- 46, 365, 277)x3, 5q11, 2q15(53, 480, 705-172, 671, 177)x1, 6p25.3p22.3(0- 17, 145, 495)x1, (18)x1, 20p13p11.22(67, 778-21, 850, 779)x1 November arr 5p15.33p11 2012 (79, 146-46, 365, 277)x3, 5q11.1 q 3 5.3 (49, 584, 189-180, 712, 263)x1, 6p25.3p22.1 (219, 055-28, 145, 142)x1, (18)x1, 20p13p11.22(122, 610-21, 925, 972)x1 Table 3. Summary of advantages and disadvantages of FISH, cytogenetics, and aCGH/SNP arrays for the detection of clonal evolution. Criterion FISH Cytogenetics CGH/SNP array Detection of Good Detects Genome-wide abnormality sensitivity abnormalities analysis at to detect present in 10% superior minor or more of resolution cell cells based on populations 20 cell study (per standard cytogenetic testing guidelinesa) Detects Can detect Detection of abnormalities abnormalities amplification/ in >2%-8% of present <10% loss interphase but only if cells, more cells analysis analyzed by at least two ualified individuals and a minimum of 50-200 cells (a) Limited to May not be able Limitation: evaluation of to characterize cannot detect specific all detected balanced genomic loci material (e.g. rearrangements, marker tetraploidy chromosomes) Cannot detect LOH Detection of Good Ability to Analysis of a clonal sensitivity detect and composite cell hetero- to detect describe clonal population geneity minor cell heterogeneity possibleb populations at single cell (specific level sensitivity levels vary according to probe type used and laboratory specific reportable reference ranges) Limited to Can identify Limited ability evaluation of and to detect minor specific characterize clones present genomic loci stem and side in <20% of lines cells Limited to Can describe in resolution of detail chromosome abnormalities structure present in subclones that are amplifications or deletions Reproducibility Adequate for Adequate for High owing to and detection of overall standardized objectivity specific loci analysis of a analysis of interest cell's genetic algorithms complement Minor clones Subjectivity of Minor clones can be missed abnormality can be missed calls may vary with banding resolution Can be improved Limitation of by automated 20 cells means slide imaging minor clones and analysis can be missed platforms Improved by automated platforms Sample Sufficient cell Requires viable Sufficient requirements number and cells with amount of DNA sample capacity to (about 250-500 quality proliferate in ng, depending vitro on platform) Advantage over Low technical Genome-wide High-resolution the other effort detection of detail of analysis and time numerical and amplification/ methods requirement structural loss chromosome aberrations Can work with Detailed Detection of very small single-cell- LOH and sample level detection uniparental size/volumes of clonal disomy as a heterogeneity further hallmark of clonal evolution Dividing cells Whole genome not required, amplification can be can be performed on performed on interphase sparse samples nuclei (a) American College of Medical Genetics (37). (b) According to our data, detection of heterogeneity is possible if difference of clonal fractions is >15% (log2 ratio-based approach) to >30% (manual peak reassignment approach).
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|Author:||Hartmann, Luise; Stephenson, Christine F.; Verkamp, Stephanie R.; Johnson, Krystal R.; Burnworth, Be|
|Date:||Dec 1, 2014|
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