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10.1245/ASO.2005.03.522
Annals of Surgical Oncology 12:1054-1060 (2005)
© 2005 Society of Surgical Oncology
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Original Article

Timing of Critical Genetic Changes in Human Breast Disease

Rachel E. Ellsworth, PhD1, Darrell L. Ellsworth, PhD1, Brenda Deyarmin, HT(ASCP)1, Laurel R. Hoffman, BS1, Brad Love, PhD2, Jeffrey A. Hooke, MD3 and Craig D. Shriver, MD3

1 Clinical Breast Care Project, Windber Research Institute, 620 Seventh Street, Windber, Pennsylvania 15963
2 Invitrogen Bioinformatics, 1600 Faraday Avenue, PO Box 6482, Carlsbad, California 92008
3 Clinical Breast Care Project, Walter Reed Army Medical Center, 6900 Georgia Avenue NW, Washington, DC 20307

Correspondence: Address correspondence and reprint requests to: Rachel E. Ellsworth, PhD; E-mail: r.ellsworth{at}wriwindber.org.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Breast cancer development has been characterized as a nonobligatory sequence of histological changes from normal epithelium through invasive malignancy. Although genetic alterations are thought to accumulate stochastically during tumorigenesis, little is known about the timing of critical mutations. This study examined allelic imbalance (AI) in tissue samples representing a continuum of breast cancer development to examine the evolution of genomic instability.

Methods: Laser-microdissected DNA samples were collected from histologically normal breast specimens (n = 25), atypical ductal hyperplasia (ADH, n = 16), ductal carcinoma-in-situ (DCIS, n = 37), and stage I to III invasive carcinomas (n = 72). Fifty-two microsatellite markers representing 26 chromosomal regions commonly deleted in breast cancer were used to assess patterns of AI.

Results: AI frequencies were <5% in histologically normal and ADH specimens, 20% in DCIS lesions, and approximately 25% in invasive tumors. Mann-Whitney tests showed (1) that levels of AI in ADH samples did not differ significantly from those in histologically normal tissues and (2) that AI frequencies in DCIS lesions were not significantly different from those in invasive carcinomas. ADH and DCIS samples, however, differed significantly (P < .0001).

Conclusions: DCIS lesions contain levels of genomic instability that are characteristic of advanced invasive tumors, and this suggests that the biology of a developing carcinoma may already be predetermined by the in situ stage. Observations that levels of AI in ADH lesions are similar to those in disease-free tissues provide a genomic rationale for why prevention strategies at the ADH level are successful and why cases with ADH involving surgical margins do not require further resection.

Key Words: Allelic imbalance • Atypical ductal hyperplasia • Ductal carcinoma-in-situ • Breast cancer • Tumor progression


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
A recognized (although not obligatory) sequence of histological changes from normal epithelium through atypical hyperplasia, in situ carcinoma, and, finally, invasive malignancy has been used to define breast cancer progression. Genetic changes are known to accumulate during tumorigenesis in a highly variable manner, with certain changes linked to specific stages of development and other alterations apparently unlinked to tumor progression.1,2 Although some genetic alterations may be shared between successive stages, thus supporting obligate progression,3 little is known about the timing of genetic aberrations in breast cancer evolution.

Clinical diagnoses of breast disease are currently derived by pathologic characterization of diseased tissues, but tissue histological characteristics alone cannot accurately predict tumor behavior and progression. As a result, numerous studies have attempted to use molecular profiling as a supplement to pathologic diagnosis to refine breast disease classification and improve prediction of clinical outcomes. Allelic imbalance (AI) studies have shown that atypical ductal hyperplasia (ADH) lesions, associated with a 4- to 5-fold increased risk for subsequent carcinoma, may contain precursor mutations that aFect neoplastic potential.4,5 High-grade ductal carcinoma-in-situ (DCIS) lesions, 40% of which progress to invasive cancer, may show chromosomal alterations that are also seen in the synchronous invasive carcinomas,3 but the importance of critical genomic alterations in genetic predetermination of breast cancer progression remains unknown.

To examine the evolution of genomic instability in breast cancer development, we assayed patterns of AI in breast tissues representing a continuum of histological characteristics from histologically normal samples to stage IIIC invasive carcinomas. We surveyed 52 microsatellite markers defining 26 chromosomal regions throughout the genome to (1) identify altered chromosomal regions associated with specific stages of breast disease and (2) establish a timeline in which these alterations accumulate. Information on the timing of critical genetic changes in breast cancer progression has potential utility in guiding surgical procedures and developing prevention strategies in patients with preinvasive disease.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
ParaGn-embedded normal and diseased breast tissues from 150 patients were obtained from the Windber Medical Center and Memorial Medical Center pathology departments or from the Clinical Breast Care Project (CBCP) Pathology Laboratory. Samples from Windber Medical Center and Memorial Medical Center (n = 65) were archival in nature and were anonymized, with no links between the assigned research number and patient identifiers. Clinical information, including age at diagnosis, estrogen receptor (ER)/progesterone receptor (PR) status, and pathologic details, was provided anonymously by the Memorial Medical Center Cancer Registry. Tissue and blood samples from CBCP patients (n = 85) were collected with approval from the Walter Reed Army Medical Center Human Use Committee and Institutional Review Board. All subjects enrolled in the CBCP voluntarily agreed to participate and gave written informed consent. Demographic and clinical information was provided for all CBCP samples by using questionnaires designed by and administered under the auspices of the CBCP.

Diagnoses of all samples were made by the CBCP pathologist (J.A.H.) from hematoxylin and eosin–stained slides. Invasive carcinomas were staged by using guidelines defined by the 6th edition of the AJCC Cancer Staging Manual.6 DCIS was categorized according to nuclear grade as recommended by the 1997 Consensus Conference,7 and a diagnosis of ADH was rendered when cells cytologically similar to low-grade DCIS cells coexisted with patterns of usual ductal hyperplasia or when there was partial involvement of the terminal duct lobular unit by characteristic morphology. Selected clinical information for all samples is listed in Table 1Go.


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  		TABLE 1. Clinical characteristics of 150 patients examined in this study
 
DNA was obtained from homogeneous populations of breast lesion or tumor cells after laser-assisted microdissection on an ASLMD laser microdissection system8 (Leica Microsystems, Wetzlar, Germany; Fig. 1Go). All microdissected sections were examined by the CBCP pathologist, who identified and marked regions of disease before micro-dissection. The integrity of multiple serial sections was established by pathologic verification of the first and last sections stained with hematoxylin and eosin. DNA was isolated from 25-mg sections from disease-free samples by using the QIAamp DNA Mini Kit (Qiagen, Valencia, CA). Referent DNA was obtained from blood clots by using Clotspin and Puregene DNA purification kits (Gentra, Minneapolis, MN) or from microdissected disease-free skin (nipple) or negative lymph node tissues.


Figure 1
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  		FIG. 1. Hematoxylin and eosin–stained sections showing the specificity of laser microdissection in obtaining homogenous populations of diseased cells. (A and B) Atypical ductal hyperplasia. (C and D) Grade 3 ductal carcinoma-in-situ. (E and F) Stage IIB infiltrating ductal carcinoma.

 
A panel of 52 microsatellite markers was amplified and genotyped as previously described.9 Genotypes were determined by using Genetic Profiler version 2.0 software (Amersham Biosciences, Piscataway, NJ) with alphabetical bin labels that facilitated accurate allele calling. AI was detected by using the formula (t1/t2)/(n1/n2), where t1 and n1 represent the peak heights of the less intense alleles and t2 and n2 represent the peak heights of the more intense alleles in the tumor and referent samples, respectively10 (Fig. 2Go). Samples with a normalized ratio of ≤.35 were considered to show genomic instability;11 this indicates that a substantial proportion of cells in that sample contained the same chromosomal aberration compared with normal somatic cells. A normalized ratio of ≤.35 can result from a deletion (loss of heterozygosity) or increase in copy number (allelic amplification) at a chromosomal region. Because each chromosomal region was represented by two polymorphic markers, genomic instability in each region was classified according to the following criteria: (1) when at least one marker for a given region showed an allelic ratio ≤.35, the region was considered to show AI; (2) when neither marker had an allelic ratio ≤.35 and at least one marker was informative, the region was considered normal; and (3) when both markers were homozygous, the region was considered uninformative.


Figure 2
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  		FIG. 2. Detection of allelic imbalance in breast disease with fluorescence-based genotyping. Alleles for marker D11S901 on chromosome 11q13.1 were detected as fluorescent peaks (arrows) in referent DNA (A) and microdissected breast tumor DNA (B). A normalized peak height ratio of .28 was calculated for the tumor sample by using the following peak heights in relative fluorescence units (rfu): referent DNA, 28,678 rfu and 16,287 rfu; tumor DNA, 2002 rfu and 4056 rfu.

 
Comparisons of overall AI frequencies with age at diagnosis and menopausal, hormonal, and lymph node status were performed with Student’s t-test. Analyses of AI frequency by chromosomal region used exact unconditional homogeneity/independence tests for 2 x 2 tables (http://www.stat.ncsu.edu/exact/tables.html). Analysis of variance was used to test for homogeneity in AI frequencies among disease stages. Mann-Whitney tests using median frequencies were then used in pairwise comparisons to identify significant differences in AI frequencies between histological classifications. A significance value of P < .05 was used for all analyses.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Overall AI Frequencies
Within the 125 diseased samples studied, 616 AI events were detected. The frequency of AI at each locus varied widely, with the most frequent AI (39%) seen on chromosome 17p13.3 and the least frequent AI (5%) seen on chromosome 7q31. The extent of AI per sample ranged from 0 to 17 chromosomal regions. In the disease-free samples, 9 of 25 specimens had a single AI event; all others had no detectable AI. In the diseased tissues, six ADH, three DCIS, and two stage I tumors had no AI events. The tumor sample with the highest levels of AI was a stage IIIa invasive ductal carcinoma from a postmenopausal woman with positive ER/PR status and 8 of 11 positive lymph nodes.

Relationships Between AI Frequency and Clinical Parameters
Data were stratified by several clinical parameters to identify associations between genomic instability and prognostic factors. No significant associations were identified between levels of genomic instability and menopausal status, young (<40 years) age at diagnosis, or lymph node or hormonal status (Table 2Go). When hormonal status was further stratified by ER and PR status, positive receptor status was not associated with AI frequency.


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  		TABLE 2. Comparison of AI frequencies by clinical/pathologic factor
 
Observed AI frequencies were 1.5% in histologically normal specimens, 3.3% in ADH lesions, 20.9% in DCIS, and approximately 25% in invasive tumors (Fig. 3Go). Analysis of variance indicated a significant difference in AI frequencies (P < .0001) across the spectrum of breast histopathological categories. Mann-Whitney tests showed that levels of AI in ADH samples did not differ significantly from those in histologically normal tissues. Likewise, AI frequencies in DCIS lesions were not significantly different from those in invasive carcinomas. In the continuum of histological progression, only atypical hyperplastic lesions (ADH) differed significantly from preinvasive (DCIS) lesions in overall levels of genomic instability (P < .0001).


Figure 3
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  		FIG. 3. Levels of genomic instability (percentage of informative markers showing allelic imbalance) across a continuum of histological diagnoses in the development of breast cancer.

 
Frequency of AI by Chromosomal Region
To investigate whether specific genetic alterations were associated with disease stage, AI data were stratified by chromosomal location (Table 3Go). AI frequencies were similar between DCIS and invasive carcinomas at all 26 chromosomal regions. When AI frequencies were compared between ADH and DCIS, the frequency of AI was significantly lower in the ADH samples (similar to those seen in histologically normal samples) at all chromosomal regions except 8q24, which showed significantly higher levels of AI compared with histologically normal tissues (P < .004).


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  		TABLE 3. Frequency of AI at each chromosomal region by disease stage
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The genomic locations of chromosomal alterations in tumor specimens were initially used in the field of molecular genetics to identify genes promoting cancer development (oncogenes) and genes that inhibit tumor formation (tumor-suppressor genes). Because patterns of chromosomal aberrations may be associated with important pathologic characteristics, such as mitotic activity and hormone-receptor status,12,13 recent attention has focused on the clinical utility of genomic changes in predicting patient outcomes and distinguishing primary breast cancer from recurrent disease.14 Molecular models of breast cancer progression have been developed to supplement histological evidence in predicting disease progression and improving patient care,15–17 but because of extensive heterogeneity in the timing of key genetic changes, a consistent model of molecular progression in breast cancer has not yet emerged.

One explanation for the diGculty in assigning specific chromosomal changes to disease stage may be the rapid accumulation of critical genetic changes in the transition from ADH to DCIS. In agreement with data presented here, previous studies have shown that many genetic alterations detected in invasive tumors may be present in DCIS,18–21 whereas AI in hyperplastic lesions is relatively uncommon.3,22 For example, over-expression of HER2/neu is rarely detected in ADH but ranges from 10% to 60% in DCIS, and this suggests that HER2/neu plays a role in the progression to invasive carcinoma.23 Similarly, alterations of p53 are rarely seen in ADH but increase with increasing grade in DCIS.24 The low levels of genetic changes observed in ADH samples concur with histological classifications, thus suggesting that ADH may be a marker of increased risk for cancer development but that ADH is not an obligate precursor lesion.

Our observations that levels of genomic instability in hyperplastic (ADH) lesions are significantly less than levels commonly seen in in situ carcinomas may partially explain several clinically relevant characteristics of preinvasive lesions. Standard treatments for ADH, such as surgical resection without chemotherapy or radiotherapy, have been extremely eFective in reducing the risk for recurrence. Similarly, patients presenting with ADH have shown high proportional risk reduction (86%) when tamoxifen is used as a chemopreventive agent, whereas risk reduction using similar therapies in women with DCIS is only approximately 40%.25,26 Numerous studies have shown that the risk of recurrence does not increase when ADH is excised with positive margins; however, re-excision is warranted with margin involvement in patients with DCIS. Levels of genomic instability in preinvasive lesions may thus play an important role in dictating clinical approaches to treatment and in patient response to chemopreventive therapies.

Alterations of specific chromosomal regions may be associated with disease progression in ADH lesions, despite relatively low overall levels of genomic instability. For example, the frequency of AI events at chromosome 8q24 in ADH lesions (35%) was similar to that seen in DCIS and invasive tumors but was significantly higher than that in histologically normal tissues. Chromosomal changes at 8q24 may contribute to a more aggressive phenotype because AI in this region has been detected in DCIS but has not previously been associated with ADH. Of note, the metastasis suppressor 1 (MTSS1; gene accession number NM_014751) and v-myc myelocytomatosis viral oncogene homologue (MYC; gene accession number NM_002467) genes map within this region. Deletion of MTSS1 has been observed in metastatic cell lines, and amplification of MYC inappropriately promotes cellular proliferation and has been associated with an unfavorable tumor phenotype.27

The similarity in levels of genomic instability between ADH and histologically normal tissue may partially explain why ADH can be easily managed by standard interventions. Our findings that DCIS lesions share similar levels of genomic instability with invasive tumors underscore the diGculty in developing standardized practices of care for treating DCIS. Currently, treatment for DCIS requires complete excision of known lesions followed by hormone therapy and radiation treatment or, in some cases, mastectomy. Histological grading of DCIS may influence treatment options, because the rate of recurrence increases from 10% in low-grade DCIS to 40% in high-grade DCIS. Focused studies of preinvasive in situ lesions stratified by histological grade are needed to determine whether frequencies and patterns of AI correlate with grading based on pathologic criteria and whether AI events can improve the prediction of progression of in situ lesions to invasive carcinomas.

Because of extensive variation in the timing of key genetic alterations and rapid accumulation of genomic changes in preinvasive disease, both ADH and DCIS lesions vary considerably in levels and patterns of AI. For example, 1 of the 16 ADH cases had increased levels of AI, which may indicate that although pathologic examination did not reveal any features indicating aggressiveness, this lesion may be at higher risk for progression. Conversely, some in situ carcinomas have significantly lower levels of genomic change than the "average" DCIS lesion. In this study, most DCIS with low levels of AI (83%) were low-grade (grade 1 and 2) carcinomas; this suggests that low-grade DCIS may represent a genetic intermediary between ADH and high-grade DCIS. Because breast cancer progression seems to be driven by critical genetic changes, functionally significant genomic changes (changes that directly aFect tumor behavior and drive disease progression) need to be identified and distinguished from alterations with a minimal eFect on disease etiology.

In conclusion, the frequency of AI suggests that the transition from ADH to DCIS is a critical event in the development of breast cancer. Because DCIS lesions share similar overall frequencies of AI, as well as specific chromosomal changes, with invasive tumors, behavior and clinical outcome may be predetermined in in situ carcinomas. The low levels of genomic instability in ADH lesions (1) suggest that, unlike DCIS, the behavior of atypical hyperplasias may not yet be predetermined and (2) emphasize the need for early detection of precursor lesions.


   ACKNOWLEDGMENTS
 
The authors thank Dennis Meyers for assistance in genotyping, Tyson Becker, MD, for critical review of the manuscript, and F. Nicholas Jacobs for his support of this research program.

Received for publication March 4, 2005. Accepted for publication July 27, 2005.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Couch FJ, Weber BL. Breast cancer. In: Vogelstein B, Kinzler K, eds. The Genetic Basis of Human Cancer. New York: McGraw-Hill, 2002:549–81.
  2. Devilee P, Cornelisse CJ. Somatic genetic changes in human breast cancer. Biochim Biophys Acta 1994;1198:113–30.[Medline]
  3. O’Connell P, Pekkel V, Fuqua SAW, Osborne CK, Allred DC. Analysis of loss of heterozygosity in 399 premalignant breast lesions at 15 genetic loci. J Natl Cancer Inst 1998;90:697–703.[Abstract/Free Full Text]
  4. Euhus DM, Cler L, Shivapurkar N, et al. Loss of heterozygosity in benign breast epithelium in relation to breast cancer risk. J Natl Cancer Inst 2002;94:858–60.[Abstract/Free Full Text]
  5. Kaneko M, Arihiro K, Takeshima Y, Fujii S, Inai K. Loss of heterozygosity and microsatellite instability in epithelial hyperplasia of the breast. J Exp Ther Oncol 2002;2:9–18.[CrossRef][Medline]
  6. American Joint Committee on Cancer. AJCC Cancer Staging Manual. New York: Springer, 2002.
  7. The Consensus Conference CommitteeConsensus conference on the classification of ductal carcinoma in situ. Hum Pathol 1997;28:1221–5.[CrossRef][Medline]
  8. Ellsworth DL, Shriver CD, Ellsworth RE, Deyarmin B, Somiari RI. Laser capture microdissection of paraffin-embedded tissues. Biotechniques 2003;34:42–6.[Medline]
  9. Ellsworth RE, Ellsworth DL, Lubert SM, Hooke J, Somiari RI, Shriver CD. High-throughput loss of heterozygosity mapping in 26 commonly deleted regions in breast cancer. Cancer Epidemiol Biomarkers Prev 2003;12:915–9.[Abstract/Free Full Text]
  10. Medintz IL, Lee C-CR, Wong WW, Pirkola K, Sidransky D, Mathies RA. Loss of heterozygosity assay for molecular detection of cancer using energy-transfer primers and capillary array electrophoresis. Genome Res 2000;10:1211–8.[Abstract/Free Full Text]
  11. Ellsworth DL, Ellsworth RE, Love B, et al. Outer breast quadrants demonstrate increased levels of genomic instability. Ann Surg Oncol 2004;11:861–8.[Abstract/Free Full Text]
  12. Janssen EA, Baak JP, Guervos MA, van Diest PJ, Jiwa M, Hermsen MA. In lymph node-negative invasive breast carcinomas, specific chromosomal aberrations are strongly associated with high mitotic activity and predict outcome more accurately than grade, tumour diameter, and oestrogen receptor. J Pathol 2003;201:555–61.[CrossRef][Medline]
  13. Leighton X, Srikantan V, Pollard HB, Sukumar S, Srivastava M. Significant allelic loss of ANX7 region (10q21) in hormone receptor negative breast carcinomas. Cancer Lett 2004;210:239–44.[CrossRef][Medline]
  14. Schlechter BL, Yang Q, Larson PS, et al. Quantitative DNA fingerprinting may distinguish new primary breast cancer from disease recurrence. J Clin Oncol 2004;22:1830–8.[Abstract/Free Full Text]
  15. Lichy JH, Zavar M, Tsai MM, O’Leary TJ, Taubenberger JK. Loss of heterozygosity on chromosome 11p15 during histological progression in microdissected ductal carcinoma of the breast. Am J Pathol 1998;153:271–8.[Abstract/Free Full Text]
  16. Radford DM, Phillips NJ, Fair KL, Ritter JH, Holt M, Donis-Keller H. Allelic loss and the progression of breast cancer. Cancer Res 1995;55:5180–3.[Abstract/Free Full Text]
  17. Watatani M, Inui H, Nagayama K, et al. Identification of high-risk breast cancer patients from genetic changes of their tumors. Surg Today 2000;30:516–22.[Medline]
  18. Champeme MH, Bieche I, Beuzelin M, Lidereau R. Loss of heterozygosity on 7q31 occurs early during breast tumorigenesis. Genes Chromosomes Cancer 1995;12:304–6.[Medline]
  19. Ingvarsson S. Molecular genetics of breast cancer progression. Cancer Biol 1999;9:277–88.
  20. Radford DM, Fair KL, Phillips TJ, et al. Allelotyping of ductal carcinoma in situ of the breast: deletion of loci on 8p, 13q, 16q, 17p and 17q. Cancer Res 1995;55:3399–405.[Abstract/Free Full Text]
  21. Yaremko ML, Recant WM, Westbrook CA. Loss of heterozygosity from the short arm of chromosome 8 is an early event in breast cancers. Genes Chromosomes Cancer 1995;13:186–91.[Medline]
  22. Allred DC, Mohsin SK, Fuqua SAW. Histological and biological evolution of human premalignant breast disease. Endocr Relat Cancer 2001;8:47–61.[Abstract]
  23. Allred DC, Clark GM, Molina R, et al. Overexpression of HER-2/neu and its relationship with other prognostic factors change during the progression of in situ to invasive breast cancer. Hum Pathol 1992;23:974–9.[CrossRef][Medline]
  24. Chitemerere M, Andersen TI, Holm R, Karlsen F, Borresen AL, Nesland JM. P53 alterations in atypical ductal hyperplasia and ductal carcinoma in situ of the breast. Br Cancer Res Treat 1996;41:103–9.[CrossRef][Medline]
  25. Fisher B, Costantino JP, Wickerham DL, et al. Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 Study. J Natl Cancer Inst 1998;90:1371–88.[Abstract/Free Full Text]
  26. Fisher B, Dignam J, Wolmark N, et al. Tamoxifen in treatment of intraductal breast cancer: National Surgical Adjuvant Breast and Bowel Project B-24 randomised controlled trial. Lancet 1999;353:1993–2000.[CrossRef][Medline]
  27. Deming SL, Nass SJ, Dickson RB, Trock BJ. C-myc amplification in breast cancer: a meta-analysis of its occurrence and prognostic relevance. Br J Cancer 2000;83:1688–95.[CrossRef][Medline]



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