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• W3025831237 abstract "Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness. Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness. Breast cancer is the most frequently diagnosed cancer and has the highest cancer-related mortality among women worldwide.1Bray F. Ferlay J. Soerjomataram I. Siegel R.L. Torre L.A. Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J Clin. 2018; 68: 394-424Crossref PubMed Scopus (51204) Google Scholar Individuals diagnosed at a young age (<40 years) usually have tumors that are more advanced and more aggressive, resulting in higher recurrence rates and shorter survival, when compared to older patients.2Adami H.O. Malker B. Holmberg L. Persson I. Stone B. The relation between survival and age at diagnosis in breast cancer.N Engl J Med. 1986; 315: 559-563Crossref PubMed Scopus (451) Google Scholar, 3Nixon A.J. Neuberg D. Hayes D.F. Gelman R. Connolly J.L. Schnitt S. Abner A. Recht A. Vicini F. Harris J.R. Relationship of patient age to pathologic features of the tumor and prognosis for patients with stage I or II breast cancer.J Clin Oncol. 1994; 12: 888-894Crossref PubMed Scopus (477) Google Scholar, 4El Saghir N.S. Seoud M. Khalil M.K. Charafeddine M. Salem Z.K. Geara F.B. Shamseddine A.I. Effects of young age at presentation on survival in breast cancer.BMC Cancer. 2006; 6: 194Crossref PubMed Scopus (175) Google Scholar However, the underlying biological and genetic characteristics associated with less favorable outcomes are not generally agreed upon. Moreover, there is no consensus as to whether young patients should receive different treatments, including more radical surgery.5Sariego J. Breast cancer in the young patient.Am Surg. 2010; 76: 1397-1400PubMed Google Scholar,6Azim Jr., H.A. Partridge A.H. Biology of breast cancer in young women.Breast Cancer Res. 2014; 16: 427Crossref PubMed Scopus (230) Google Scholar Extensive studies using gene expression profiling to characterize breast cancers have revealed four distinct molecular subtypes: i) luminal A, ii) luminal B [with either positive or negative erb-b2 receptor tyrosine kinase 2 (ERBB2; alias HER2) status], iii) HER2 enriched, and iv) triple-negative/basal-like.7Perou C.M. Sorlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnsen H. Akslen L.A. Fluge O. Pergamenschikov A. Williams C. Zhu S.X. Lonning P.E. Borresen-Dale A.L. Brown P.O. Botstein D. Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (11701) Google Scholar,8Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Lonning P.E. Borresen-Dale A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc Natl Acad Sci U S A. 2001; 98: 10869-10874Crossref PubMed Scopus (8540) Google Scholar These subgroups are clinically categorized into three basic therapeutic groups: i) luminal/estrogen receptor (ER) positive, ii) HER2 amplified, and iii) triple negative/basal like. The ER-positive group is the most common and diverse; patients in this group benefit in particular from endocrine therapy.9van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7784) Google Scholar,10Paik S. Shak S. Tang G. Kim C. Baker J. Cronin M. Baehner F.L. Walker M.G. Watson D. Park T. Hiller W. Fisher E.R. Wickerham D.L. Bryant J. Wolmark N. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.N Engl J Med. 2004; 351: 2817-2826Crossref PubMed Scopus (4852) Google Scholar The HER2-amplified group is associated with a poor prognosis; however, the introduction of trastuzumab, a monoclonal antibody targeting this growth factor receptor, has dramatically improved treatment and survival.11Slamon D.J. Clark G.M. Wong S.G. Levin W.J. Ullrich A. McGuire W.L. Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene.Science. 1987; 235: 177-182Crossref PubMed Scopus (9936) Google Scholar, 12Bergamaschi A. Kim Y.H. Wang P. Sorlie T. Hernandez-Boussard T. Lonning P.E. Tibshirani R. Borresen-Dale A.L. Pollack J.R. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer.Genes Chromosomes Cancer. 2006; 45: 1033-1040Crossref PubMed Scopus (408) Google Scholar, 13Chin K. DeVries S. Fridlyand J. Spellman P.T. Roydasgupta R. Kuo W.L. Lapuk A. Neve R.M. Qian Z. Ryder T. Chen F. Feiler H. Tokuyasu T. Kingsley C. Dairkee S. Meng Z. Chew K. Pinkel D. Jain A. Ljung B.M. Esserman L. Albertson D.G. Waldman F.M. Gray J.W. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies.Cancer Cell. 2006; 10: 529-541Abstract Full Text Full Text PDF PubMed Scopus (1022) Google Scholar Triple-negative/basal-like breast cancers are more common in patients with germline BRCA1 or BRCA2 mutations. Adjuvant treatment options are restricted to chemotherapy.14Perou C.M. Molecular stratification of triple-negative breast cancers.Oncologist. 2010; 15 Suppl 5: 39-48Crossref PubMed Scopus (182) Google Scholar Recent studies have reported that the prevalence of aggressive, triple-negative/basal-like cancers is higher among young women compared to older patients.15Bauer K.R. Brown M. Cress R.D. Parise C.A. Caggiano V. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California Cancer Registry.Cancer. 2007; 109: 1721-1728Crossref PubMed Scopus (1630) Google Scholar, 16Cancello G. Maisonneuve P. Rotmensz N. Viale G. Mastropasqua M.G. Pruneri G. Veronesi P. Torrisi R. Montagna E. Luini A. Intra M. Gentilini O. Ghisini R. Goldhirsch A. Colleoni M. Prognosis and adjuvant treatment effects in selected breast cancer subtypes of very young women (<35 years) with operable breast cancer.Ann Oncol. 2010; 21: 1974-1981Abstract Full Text Full Text PDF PubMed Scopus (179) Google Scholar, 17Anders C.K. Fan C. Parker J.S. Carey L.A. Blackwell K.L. Klauber-DeMore N. Perou C.M. Breast carcinomas arising at a young age: unique biology or a surrogate for aggressive intrinsic subtypes?.J Clin Oncol. 2011; 29: e18-e20Crossref PubMed Scopus (164) Google Scholar These findings raise the question of whether breast cancers diagnosed at a young age are biologically and genetically unique and should thus be considered as a distinct disease entity, or whether young age is simply associated with a higher prevalence of aggressive molecular subtypes.17Anders C.K. Fan C. Parker J.S. Carey L.A. Blackwell K.L. Klauber-DeMore N. Perou C.M. Breast carcinomas arising at a young age: unique biology or a surrogate for aggressive intrinsic subtypes?.J Clin Oncol. 2011; 29: e18-e20Crossref PubMed Scopus (164) Google Scholar,18Partridge A.H. Hughes M.E. Warner E.T. Ottesen R.A. Wong Y.N. Edge S.B. Theriault R.L. Blayney D.W. Niland J.C. Winer E.P. Weeks J.C. Tamimi R.M. Subtype-dependent relationship between young age at diagnosis and breast cancer survival.J Clin Oncol. 2016; 34: 3308-3314Crossref PubMed Scopus (227) Google Scholar The use of gene expression profiling has contributed to the development of molecular signatures for improved prognostication when used in addition to conventional clinicopathologic parameters.10Paik S. Shak S. Tang G. Kim C. Baker J. Cronin M. Baehner F.L. Walker M.G. Watson D. Park T. Hiller W. Fisher E.R. Wickerham D.L. Bryant J. Wolmark N. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.N Engl J Med. 2004; 351: 2817-2826Crossref PubMed Scopus (4852) Google Scholar,19van de Vijver M.J. He Y.D. van't Veer L.J. Dai H. Hart A.A. Voskuil D.W. Schreiber G.J. Peterse J.L. Roberts C. Marton M.J. Parrish M. Atsma D. Witteveen A. Glas A. Delahaye L. van der Velde T. Bartelink H. Rodenhuis S. Rutgers E.T. Friend S.H. Bernards R. A gene-expression signature as a predictor of survival in breast cancer.N Engl J Med. 2002; 347: 1999-2009Crossref PubMed Scopus (5271) Google Scholar,20Sotiriou C. Wirapati P. Loi S. Harris A. Fox S. Smeds J. Nordgren H. Farmer P. Praz V. Haibe-Kains B. Desmedt C. Larsimont D. Cardoso F. Peterse H. Nuyten D. Buyse M. Van de Vijver M.J. Bergh J. Piccart M. Delorenzi M. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.J Natl Cancer Inst. 2006; 98: 262-272Crossref PubMed Scopus (1571) Google Scholar Tests for some of these signatures are currently commercially available, such as OncotypeDX (Genomic Health, Redwood City, CA), which is included in the American Society of Clinical Oncology's breast cancer guideline on risk stratification of early stage, node-negative, hormone-receptor–positive and HER2-negative breast cancer.21Andre F. Ismaila N. Henry N.L. Somerfield M.R. Bast R.C. Barlow W. Collyar D.E. Hammond M.E. Kuderer N.M. Liu M.C. Van Poznak C. Wolff A.C. Stearns V. Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: ASCO clinical practice guideline update-integration of results From TAILORx.J Clin Oncol. 2019; 37: 1956-1964Crossref PubMed Scopus (137) Google Scholar, 22Cardoso F. van't Veer L. Rutgers E. Loi S. Mook S. Piccart-Gebhart M.J. Clinical application of the 70-gene profile: the MINDACT trial.J Clin Oncol. 2008; 26: 729-735Crossref PubMed Scopus (389) Google Scholar, 23Sparano J.A. Paik S. Development of the 21-gene assay and its application in clinical practice and clinical trials.J Clin Oncol. 2008; 26: 721-728Crossref PubMed Scopus (465) Google Scholar In addition, extensive studies measuring nuclear DNA content by either flow cytometry or image cytometry have shown that the degree of gross aneuploidy, that is, genomic instability, determines disease outcome.24Auer G. Eriksson E. Azavedo E. Caspersson T. Wallgren A. Prognostic significance of nuclear DNA content in mammary adenocarcinomas in humans.Cancer Res. 1984; 44: 394-396PubMed Google Scholar, 25Cornelisse C.J. van de Velde C.J. Caspers R.J. Moolenaar A.J. Hermans J. DNA ploidy and survival in breast cancer patients.Cytometry. 1987; 8: 225-234Crossref PubMed Scopus (216) Google Scholar, 26Fallenius A.G. Auer G.U. Carstensen J.M. Prognostic significance of DNA measurements in 409 consecutive breast cancer patients.Cancer. 1988; 62: 331-341Crossref PubMed Scopus (145) Google Scholar, 27Kronenwett U. Huwendiek S. Ostring C. Portwood N. Roblick U.J. Pawitan Y. Alaiya A. Sennerstam R. Zetterberg A. Auer G. Improved grading of breast adenocarcinomas based on genomic instability.Cancer Res. 2004; 64: 904-909Crossref PubMed Scopus (71) Google Scholar, 28Habermann J.K. Doering J. Hautaniemi S. Roblick U.J. Bundgen N.K. Nicorici D. Kronenwett U. Rathnagiriswaran S. Mettu R.K. Ma Y. Kruger S. Bruch H.P. Auer G. Guo N.L. Ried T. The gene expression signature of genomic instability in breast cancer is an independent predictor of clinical outcome.Int J Cancer. 2009; 124: 1552-1564Crossref PubMed Scopus (94) Google Scholar Patients with diploid tumors have a significantly better prognosis compared to patients with aneuploid tumors.24Auer G. Eriksson E. Azavedo E. Caspersson T. Wallgren A. Prognostic significance of nuclear DNA content in mammary adenocarcinomas in humans.Cancer Res. 1984; 44: 394-396PubMed Google Scholar, 25Cornelisse C.J. van de Velde C.J. Caspers R.J. Moolenaar A.J. Hermans J. DNA ploidy and survival in breast cancer patients.Cytometry. 1987; 8: 225-234Crossref PubMed Scopus (216) Google Scholar, 26Fallenius A.G. Auer G.U. Carstensen J.M. Prognostic significance of DNA measurements in 409 consecutive breast cancer patients.Cancer. 1988; 62: 331-341Crossref PubMed Scopus (145) Google Scholar, 27Kronenwett U. Huwendiek S. Ostring C. Portwood N. Roblick U.J. Pawitan Y. Alaiya A. Sennerstam R. Zetterberg A. Auer G. Improved grading of breast adenocarcinomas based on genomic instability.Cancer Res. 2004; 64: 904-909Crossref PubMed Scopus (71) Google Scholar Habermann et al28Habermann J.K. Doering J. Hautaniemi S. Roblick U.J. Bundgen N.K. Nicorici D. Kronenwett U. Rathnagiriswaran S. Mettu R.K. Ma Y. Kruger S. Bruch H.P. Auer G. Guo N.L. Ried T. The gene expression signature of genomic instability in breast cancer is an independent predictor of clinical outcome.Int J Cancer. 2009; 124: 1552-1564Crossref PubMed Scopus (94) Google Scholar previously established a gene expression signature of chromosomal instability that overlapped substantially with established prognostic gene expression signatures. The investigators concluded that the biological basis for prognostic molecular signatures is reflected in the degree of genomic instability as the defining biological property. The relationship between the degree of genomic instability and levels of intratumor heterogeneity (ITH) remains largely elusive. To understand the interplay between ITH, gross aneuploidy, gene mutations, and disease outcome, we conducted a single-cell genetic analysis by multiplex interphase fluorescence in situ hybridization (miFISH), accompanied by DNA cytometry and targeted sequencing of breast cancers from younger patients with profoundly different clinical outcomes. Our study was motivated by the desire to elucidate biological and genetic features that could explain the generally aggressive nature of breast cancer in younger women. This study analyzed 34 formalin-fixed, paraffin-embedded tumor specimens from a group of younger breast cancer patients with a mean age of 40 years (range, 31 to 59) at diagnosis and a minimum follow-up of 16.7 years. Samples were selected from a cohort of 5618 breast cancer patients who were treated at the Karolinska University Hospital, the Vällingby Clinical Center, as well as other outpatient clinics, in Stockholm, Sweden, between 1986 and 2001. Two equal-sized groups were formed, consisting of 17 patients with short disease-specific survival (DSS; mean survival, 3.6 years; range, 0.7 to 10.3 years) and 17 patients with long DSS (mean survival, 19.1 years; range, 16.7 to 20.9 years). None of the patients in the long survival group died during follow-up. The distribution of aneuploid and diploid tumors (defined in the subsequent paragraph) within the two groups was similar: the short survival group comprised 9 aneuploid cases (52.9%) and 8 diploid cases (47.1%), whereas the long survival group consisted of 6 aneuploid tumors (35.3%) and 11 diploid tumors (64.7%). ER and progesterone receptor (PR) positivity were determined by isoelectric focusing because this was the standard procedure during 1986 to 2001, when the samples were collected.29Wrange O. Isoelectric focusing of steroid hormone receptors in slabs of polyacrylamide gel.Breast Cancer Res Treat. 1983; 3: 97-102Crossref PubMed Scopus (5) Google Scholar Isoelectric focusing is a technique for separating proteins based on their isoelectric point; ER and PR are subsequently detected based on incubation of the gel with radioactively labeled estradiol or promegestrone, respectively, without the use of antibodies.30Wrange O. Humla S. Ramberg I. Nordenskjold B. Gustafsson J.A. Estrogen and progestin receptor analysis in human breast cancer by isoelectric focusing in slabs of polyacrylamide gel.Recent Results Cancer Res. 1984; 91: 32-40Crossref PubMed Scopus (3) Google Scholar The thresholds for ER and PR positivity were set at ≥0.05 fmol/ng DNA.31Wrange O. Nordenskjold B. Gustafsson J.A. Cytosol estradiol receptor in human mammary carcinoma: an assay based on isoelectric focusing in polyacrylamide gel.Anal Biochem. 1978; 85: 461-475Crossref PubMed Scopus (121) Google Scholar HER2 and Ki-67 status were determined by immunohistochemistry.32Lebeau A. Denkert C. Sinn P. Schmidt M. Wockel A. [Update of the German S3 breast cancer guideline: what is new for pathologists?].Pathologe. 2019; 40: 185-198Crossref PubMed Scopus (8) Google Scholar The molecular subtypes were determined by applying the criteria specified in Table 1.Table 1Molecular Subtypes of Breast Cancer and Definition of Surrogate ParametersMolecular subtypeSubgroupDefinitionLuminal AER/PR+, HER2−, Ki-67 <20%Luminal BHER2–ER/PR+, HER2−, Ki-67 ≥20%HER2+ER/PR+, HER2+, any Ki-67HER2-enrichedER/PR−, HER2+, any Ki-67Triple negative/basal-likeER/PR−, HER2−, any Ki-67Molecular subtypes of breast cancer and definition of surrogate parameters.ER, estrogen receptor; PR, progesterone receptor.The threshold for estrogen and progesterone receptor positivity (+) is set at ≥10% positive tumor cells assessed immunohistochemistry. Hormone receptor negativity is defined as ER–/PR–expression of 0% to 9%.HER2 positivity (+) is defined as a protein overexpression (HER2-score 3+) assessed by immunohistochemistry or a gene amplification assessed by fluorescence in situ hybridization.32Lebeau A. Denkert C. Sinn P. Schmidt M. Wockel A. [Update of the German S3 breast cancer guideline: what is new for pathologists?].Pathologe. 2019; 40: 185-198Crossref PubMed Scopus (8) Google Scholar Open table in a new tab Molecular subtypes of breast cancer and definition of surrogate parameters. ER, estrogen receptor; PR, progesterone receptor. The threshold for estrogen and progesterone receptor positivity (+) is set at ≥10% positive tumor cells assessed immunohistochemistry. Hormone receptor negativity is defined as ER–/PR–expression of 0% to 9%. HER2 positivity (+) is defined as a protein overexpression (HER2-score 3+) assessed by immunohistochemistry or a gene amplification assessed by fluorescence in situ hybridization.32Lebeau A. Denkert C. Sinn P. Schmidt M. Wockel A. [Update of the German S3 breast cancer guideline: what is new for pathologists?].Pathologe. 2019; 40: 185-198Crossref PubMed Scopus (8) Google Scholar The clinicopathologic data are presented in Figure 1 and Supplemental Table S1. Samples assigned to either of the groups were labeled A for short survivors and B for long survivors. The local Swedish ethics committee approved the use of samples and data for this study (document case number 2013/707-31/3; Office of Human Subjects Research 12758). Fine-needle aspirates of all tumors were Feulgen stained, and nuclear DNA content was measured quantitatively using static image analysis, which converts the computer-aided extinction coefficient of the stained cells into a ploidy degree, as described by Kronenwett et al.27Kronenwett U. Huwendiek S. Ostring C. Portwood N. Roblick U.J. Pawitan Y. Alaiya A. Sennerstam R. Zetterberg A. Auer G. Improved grading of breast adenocarcinomas based on genomic instability.Cancer Res. 2004; 64: 904-909Crossref PubMed Scopus (71) Google Scholar The ploidy is visualized as a histogram reflecting the measured tumor cell population. Between 100 and 200 tumor cells and 10 to 20 lymphocytes (serving as a corresponding staining control with a diploid value of 2c) were measured per case. The DNA histograms (Figure 2, C and G ; Figure 3, C and G ; and Supplemental Figure S1) were then classified according to Auer et al24Auer G. Eriksson E. Azavedo E. Caspersson T. Wallgren A. Prognostic significance of nuclear DNA content in mammary adenocarcinomas in humans.Cancer Res. 1984; 44: 394-396PubMed Google Scholar into diploid (types I and III) and aneuploid (type IV).Figure 3Patients with long survival. Multiplex interphase fluorescence in situ hybridization (miFISH) results (A and E), histology (B and F), image cytometry (C and G), and imbalance clone plots (D and H) for case B3 (A–D) and case B15 (E–H). A and E: Color display of miFISH analysis with eight gene-specific probes. Copy number counts for each nucleus are displayed as gains (green), losses (red), and neutral (blue). Markers are plotted horizontally with the Locus column depicting the specific chromosome arm for each probe on the left of the plot, and the corresponding gene name on the right. Nuclei are plotted vertically by pattern frequency. Each vertical line discerns specific gain and loss patterns and the prevalence of these clones in the population. The Gain and Loss columns refer to the percentage of nuclei in which a gain or loss was observed. The ASN column denotes the mean signal number. Color-labeled percentages indicate a 15% threshold of gain or loss. The Instability Index and the mean ploidy were calculated as described in Materials and Methods. B and F: Hematoxylin and eosin–stained sections showing the histomorphology of the respective breast cancer that has been analyzed. C and G: Histograms of the quantitative measurements of the nuclear DNA content. The DNA histograms show the quantitative measurements of the nuclear DNA content (x axis) of the tumor cells given in c units. Based on the 2c stemline, the percentages of cells in the G1, S phase and exceeding the G2/M phase of the cell cycle are determined. The brackets visualize the area of the corresponding cells in the G2/M phase. The y axis represents the total cell count: between 100 and 200 tumor cells were measured per case. D and H: Imbalance clone plots visualizing the clonal composition and their putative evolutionary trajectory. The areas of the circles reflect the percentages with which these clones are present. Clones derived by a single gain or loss change are connected by arrows. The arrows indicate the clonal evolution according to gain and loss patterns in the color charts. Clones that are not connected by arrows must have undergone > one gain or loss. Color coding allows for the assignment of the individual clones to the corresponding clones in the color displays in A and E. Scale bars = 200 μm (B and F).View Large Image Figure ViewerDownload Hi-res image Download (PPT) To develop miFISH probes that sensitively and specifically hybridize to certain human gene loci, bacterial artificial chromosome contigs were assembled using three to four overlapping clones. Breast cancer–specific probe selection was based on findings from prior analyses of breast cancers using comparative genomic hybridization.33Kallioniemi A. Kallioniemi O.P. Piper J. Tanner M. Stokke T. Chen L. Smith H.S. Pinkel D. Gray J.W. Waldman F.M. Detection and mapping of amplified DNA sequences in breast cancer by comparative genomic hybridization.Proc Natl Acad Sci U S A. 1994; 91: 2156-2160Crossref PubMed Scopus (701) Google Scholar,34Ried T. Just K.E. Holtgreve-Grez H. du Manoir S. Speicher M.R. Schrock E. Latham C. Blegen H. Zetterberg A. Cremer T. Auer G. Comparative genomic hybridization of formalin-fixed, paraffin-embedded breast tumors reveals different patterns of chromosomal gains and losses in fibroadenomas and diploid and aneuploid carcinomas.Cancer Res. 1995; 55: 5415-5423PubMed Google Scholar The following probes were included: COX2/MT-CO2 (1q31.1), DBC2/RHOBTB2 (8p21.3), MYC (8q24.21), CCND1 (11q13.3), CDH1 (16q22.1), TP53 (17p13.1), HER2/ERBB2 (17q12), and ZNF217 (20q13.2). Centromere probes CEP4 and CEP10 were used as ploidy references. Clone DNA was extracted, labeled with fluorophores by nick translation, and precipitated as previously published.35Oltmann J. Heselmeyer-Haddad K. Hernandez L.S. Meyer R. Torres I. Hu Y. Doberstein N. Killian J.K. Petersen D. Zhu Y.J. Edelman D.C. Meltzer P.S. Schwartz R. Gertz E.M. Schaffer A.A. Auer G. Habermann J.K. Ried T. Aneuploidy, TP53 mutation, and amplification of MYC correlate with increased intratumor heterogeneity and poor prognosis of breast cancer patients.Genes Chromosomes Cancer. 2018; 57: 165-175Crossref PubMed Scopus (22) Google Scholar,36Fiedler D. Heselmeyer-Haddad K. Hirsch D. Hernandez L.S. Torres I. Wangsa D. Hu Y. Zapata L. Rueschoff J. Belle S. Ried T. Gaiser T. Single-cell genetic analysis of clonal dynamics in colorectal adenomas indicates CDX2 gain as a predictor of recurrence.Int J Cancer. 2019; 144: 1561-1573Crossref PubMed Scopus (12) Google Scholar Cytospin slides containing single-layered interphase nuclei from two 50-μm–thick unstained formalin-fixed, paraffin-embedded tissue sections per sample were prepared using a modified Hedley method as described.37Heselmeyer-Haddad K. Berroa Garcia L.Y. Bradley A. Ortiz-Melendez C. Lee W.J. Christensen R. Prindiville S.A. Calzone K.A. Soballe P.W. Hu Y. Chowdhury S.A. Schwartz R. Schaffer A.A. Ried T. Single-cell genetic analysis of ductal carcinoma in situ and invasive breast cancer reveals enormous tumor heterogeneity yet conserved genomic imbalances and gain of MYC during progression.Am J Pathol. 2012; 181: 1807-1822Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar Two probe panels consisting of four gene-specific probes and one centromere probe each were consecutively hybridized onto the same cytospin and imaged by the DUET scanning imaging workstation software version 3.6.0.15 (BioView Ltd., Rehovot, Israel). Images were automatically overlaid, so that signal counts of all 10 probes could be enumerated concurrently within each nucleus. All signals were manually counted and reviewed for accuracy using the SOLO workstation (BioView Ltd.) applying the following exclusion criteria: i) overlap with other nuclei, ii) visibly damaged or incomplete nuclei, or iii) insufficient hybridization quality, such as one or more non–clearly discernible probe signals. A mean of 250 nuclei per case (range, 81 to 310) were evaluated. The processing of raw data for the determination of clonal signal patterns was performed as previously described.35Oltmann J. Heselmeyer-Haddad K. Hernandez L.S. Meyer R. Torres I. Hu Y. Doberstein N. Killian J.K. Petersen D. Zhu Y.J. Edelman D.C. Meltzer P.S. Schwartz R. Gertz E.M. Schaffer A.A. Auer G. Habermann J.K. Ried T. Aneuploidy, TP53 mutation, and amplification of MYC correlate with increased intratumor heterogeneity and poor prognosis of breast cancer patients.Genes Chromosomes Cancer. 2018; 57: 165-175Crossref PubMed Scopus (22) Google Scholar The most common signal pattern in each cell population was defined as the major signal pattern clone. Cellular ploidy was assigned to each signal pattern by integrating mean signal counts of the centromere probes and the eight gene probes, leaving out markers with amplifications to avoid bias of the mean. Gain and loss patterns were determined in relation to the ploidy of the respective nucleus. When we mention that a gene was gained or lost in a sample (Results), or that statistical analyses are reported on gains or losses, only probes for which the respective abe" @default.
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• W3025831237 title "High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients" @default.
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• W3025831237 doi "https://doi.org/10.1016/j.ajpath.2020.04.015" @default.
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