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• W1504229479 abstract "Rhabdomyosarcoma (RMS) in children occurs as two major histological subtypes, embryonal (ERMS) and alveolar (ARMS). ERMS is associated with an 11p15.5 loss of heterozygosity (LOH) and may be confused with nonmyogenic, non-RMS soft tissue sarcomas. ARMS expresses the product of a genomic translocation that fuses FOXO1 (FKHR) with either PAX3 or PAX7 (P-F); however, at least 25% of cases lack these translocations. Here, we describe a genomic-based classification scheme that is derived from the combined gene expression profiling and LOH analysis of 160 cases of RMS and non-RMS soft tissue sarcomas that is at variance with conventional histopathological schemes. We found that gene expression profiles and patterns of LOH of ARMS cases lacking P-F translocations are indistinguishable from conventional ERMS cases. A subset of tumors that has been histologically classified as RMS lack myogenic gene expression. However, classification based on gene expression is possible using as few as five genes with an estimated error rate of less than 5%. Using immunohistochemistry, we characterized two markers, HMGA2 and TFAP2ß, which facilitate the differential diagnoses of ERMS and P-F RMS, respectively, using clinical material. These objectively derived molecular classes are based solely on genomic analysis at the time of diagnosis and are highly reproducible. Adoption of these molecular criteria may offer a more clinically relevant diagnostic scheme, thus potentially improving patient management and therapeutic RMS outcomes. Rhabdomyosarcoma (RMS) in children occurs as two major histological subtypes, embryonal (ERMS) and alveolar (ARMS). ERMS is associated with an 11p15.5 loss of heterozygosity (LOH) and may be confused with nonmyogenic, non-RMS soft tissue sarcomas. ARMS expresses the product of a genomic translocation that fuses FOXO1 (FKHR) with either PAX3 or PAX7 (P-F); however, at least 25% of cases lack these translocations. Here, we describe a genomic-based classification scheme that is derived from the combined gene expression profiling and LOH analysis of 160 cases of RMS and non-RMS soft tissue sarcomas that is at variance with conventional histopathological schemes. We found that gene expression profiles and patterns of LOH of ARMS cases lacking P-F translocations are indistinguishable from conventional ERMS cases. A subset of tumors that has been histologically classified as RMS lack myogenic gene expression. However, classification based on gene expression is possible using as few as five genes with an estimated error rate of less than 5%. Using immunohistochemistry, we characterized two markers, HMGA2 and TFAP2ß, which facilitate the differential diagnoses of ERMS and P-F RMS, respectively, using clinical material. These objectively derived molecular classes are based solely on genomic analysis at the time of diagnosis and are highly reproducible. Adoption of these molecular criteria may offer a more clinically relevant diagnostic scheme, thus potentially improving patient management and therapeutic RMS outcomes. Rhabdomyosarcoma (RMS) defines a group of histologically and genetically heterogeneous sarcomas that are the single most common soft tissue sarcomas affecting children and young adults. Two major forms of the disease are described,1Asmar L Gehan EA Newton WA Webber BL Marsden HB van Unnik AJ Hamoudi AB Shimada H Tsokos M Harms D Agreement among and within groups of pathologists in the classification of rhabdomyosarcoma and related childhood sarcomas. Report of an international study of four pathology classifications.Cancer. 1994; 74: 2579-2588Crossref PubMed Scopus (79) Google Scholar, 2Enterline HT Horn Jr, RC Alveolar rhabdomyosarcoma; a distinctive tumor type.Am J Clin Pathol. 1958; 29: 356-366PubMed Google Scholar, 3Newton Jr, WA Gehan EA Webber BL Marsden HB van Unnik AJ Hamoudi AB Tsokos MG Shimada H Harms D Schmidt D Classification of rhabdomyosarcomas and related sarcomas. Pathologic aspects and proposal for a new classification—an Intergroup Rhabdomyosarcoma Study.Cancer. 1995; 76: 1073-1085Crossref PubMed Scopus (459) Google Scholar, 4Riopelle JL Thériault JP Sur une forme méconnue de sarcome des parties molles: le rhabdomyosarcome alvéolaire.Ann Anat Pathol (Paris). 1956; 1: 88-111PubMed Google Scholar, 5Tsokos M Webber BL Parham DM Wesley RA Miser A Miser JS Etcubanas E Kinsella T Grayson J Glatstein E Rhabdomyosarcoma: a new classification scheme related to prognosis.Arch Pathol Lab Med. 1992; 116: 847-855PubMed Google Scholar conventionally termed embryonal RMS (ERMS) and alveolar RMS (ARMS), reflecting morphological similarities to fetal muscle or pulmonary alveoli, respectively. These distinctions are clinically relevant because the embryonal form typically shows less aggressive clinical behavior and a better prognosis and morphological embryonal variants such as spindle/botryoid tumors5Tsokos M Webber BL Parham DM Wesley RA Miser A Miser JS Etcubanas E Kinsella T Grayson J Glatstein E Rhabdomyosarcoma: a new classification scheme related to prognosis.Arch Pathol Lab Med. 1992; 116: 847-855PubMed Google Scholar, 6Leuschner I Newton Jr, WA Schmidt D Sachs N Asmar L Hamoudi A Harms D Maurer HM Spindle cell variants of embryonal rhabdomyosarcoma in the paratesticular region. A report of the Intergroup Rhabdomyosarcoma Study.Am J Surg Pathol. 1993; 17: 221-230Crossref PubMed Scopus (140) Google Scholar, 7Newton Jr, WA Soule EH Hamoudi AB Reiman HM Shimada H Beltangady M Maurer H Histopathology of childhood sarcomas. Intergroup Rhabdomyosarcoma Studies I and II: clinicopathologic correlation.J Clin Oncol. 1988; 6: 67-75Crossref PubMed Scopus (225) Google Scholar are highly curable. When clinical stage and other variables are taken into account, survival rates range from 20% for patients with metastatic alveolar histology tumors to more than 95% for some localized forms of ERMS.8Breneman JC Lyden E Pappo AS Link MP Anderson JR Parham DM Qualman SJ Wharam MD Donaldson SS Maurer HM Meyer WH Baker KS Paidas CN Crist WM Prognostic factors and clinical outcomes in children and adolescents with metastatic rhabdomyosarcoma—a report from the Intergroup Rhabdomyosarcoma Study IV.J Clin Oncol. 2003; 21: 78-84Crossref PubMed Scopus (346) Google Scholar, 9Crist WM Anderson JR Meza JL Fryer C Raney RB Ruymann FB Breneman J Qualman SJ Wiener E Wharam M Lobe T Webber B Maurer HM Donaldson SS Intergroup rhabdomyosarcoma study-IV: results for patients with nonmetastatic disease.J Clin Oncol. 2001; 19: 3091-3102PubMed Google Scholar Recurrent chromosomal translocations10Barr FG Fusions involving paired box and fork head family transcription factors in the pediatric cancer alveolar rhabdomyosarcoma.Curr Top Microbiol Immunol. 1997; 220: 113-129PubMed Google Scholar, 11Barr FG Gene fusions involving PAX and FOX family members in alveolar rhabdomyosarcoma.Oncogene. 2001; 20: 5736-5746Crossref PubMed Scopus (297) Google Scholar that result in the expression of the chimeric transcription factors, PAX3-FOXO1 or PAX7-FOXO1 (henceforth, P-F or PAX-FKHR), and that can be detected by molecular genetic techniques, are found exclusively in ARMS. Initially this was thought to provide an objective basis for distinguishing the two major forms of the disease.10Barr FG Fusions involving paired box and fork head family transcription factors in the pediatric cancer alveolar rhabdomyosarcoma.Curr Top Microbiol Immunol. 1997; 220: 113-129PubMed Google Scholar However, analysis of a large series of cases consistently fails to show an absolute association of P-F translocations with ARMS; at least 25% of these tumors possess classic alveolar histology but lack a translocation.12Barr FG Qualman SJ Macris MH Melnyk N Lawlor ER Strzelecki DM Triche TJ Bridge JA Sorensen PH Genetic heterogeneity in the alveolar rhabdomyosarcoma subset without typical gene fusions.Cancer Res. 2002; 62: 4704-4710PubMed Google Scholar, 13Sorensen PH Lynch JC Qualman SJ Tirabosco R Lim JF Maurer HM Bridge JA Crist WM Triche TJ Barr FG PAX3-FKHR and PAX7-FKHR gene fusions are prognostic indicators in alveolar rhabdomyosarcoma: a report from the children's oncology group.J Clin Oncol. 2002; 20: 2672-2679Crossref PubMed Scopus (605) Google Scholar The most recent work from the Children's Oncology Group (COG) cites a figure as high as 45% for ARMS histology cases lacking known P-F fusions.14Parham DM Qualman SJ Teot L Barr FG Morotti R Sorensen PH Triche TJ Meyer WH Correlation between histology and PAX/FKHR fusion status in alveolar rhabdomyosarcoma: a report from the Children's Oncology Group.Am J Surg Pathol. 2007; 31: 895-901Crossref PubMed Scopus (58) Google Scholar In contrast, ERMS do not demonstrate recurrent chromosomal translocations (ie, P-F-negative). Instead, they show greater genomic instability (manifested as highly variable karyotypes) and recurring allelic imbalances such as loss of heterozygosity (LOH) at chromosome 11p15.5.15Besnard-Guérin C Newsham I Winqvist R Cavenee WK A common region of loss of heterozygosity in Wilms' tumor and embryonal rhabdomyosarcoma distal to the D11S988 locus on chromosome 11p15.5.Hum Genet. 1996; 97: 163-170Crossref PubMed Scopus (74) Google Scholar, 16Visser M Sijmons C Bras J Arceci RJ Godfried M Valentijn LJ Voute PA Baas F Allelotype of pediatric rhabdomyosarcoma.Oncogene. 1997; 15: 1309-1314Crossref PubMed Scopus (86) Google Scholar RMS is defined as demonstrating at least minimal evidence of rhabdomyogenesis, or skeletal muscle differentiation. However, in a large proportion of cases, morphological evidence of myogenesis is limited to a small percentage of tumor cells or may be extremely difficult to detect. The use of antibodies for immunohistochemical (IHC) detection of myogenesis-associated proteins such as desmin, myogenin (MYOG), and MyoD (MYOD1) have aided the diagnostic workup of such cases,17Cessna MH Zhou H Perkins SL Tripp SR Layfield L Daines C Coffin CM Are myogenin and myoD1 expression specific for rhabdomyosarcoma? A study of 150 cases, with emphasis on spindle cell mimics.Am J Surg Pathol. 2001; 25: 1150-1157Crossref PubMed Scopus (224) Google Scholar, 18Tsokos M The role of immunocytochemistry in the diagnosis of rhabdomyosarcoma.Arch Pathol Lab Med. 1986; 110: 776-778PubMed Google Scholar and when combined myogenin and MyoD have ∼97% sensitivity to detect RMS.19Qualman SJ Coffin CM Newton WA Hojo H Triche TJ Parham DM Crist WM Intergroup Rhabdomyosarcoma Study: update for pathologists.Pediatr Dev Pathol. 1998; 1: 550-561Crossref PubMed Scopus (192) Google Scholar, 20Morotti RA Nicol KK Parham DM Teot LA Moore J Hayes J Meyer W Qualman SJ An immunohistochemical algorithm to facilitate diagnosis and subtyping of rhabdomyosarcoma: the Children's Oncology Group experience.Am J Surg Pathol. 2006; 30: 962-968Crossref PubMed Scopus (153) Google Scholar The identification of muscle related differentiation is key and clinically relevant because some RMS cases can be virtually indistinguishable from the group of so-called undifferentiated or nonrhabdomyosarcoma soft-tissue sarcomas (UDS/NRSTS). The latter lack any morphological or ultrastructural evidence of myogenesis and have a poor outcome compared with RMS.21Raney RB Anderson JR Barr FG Donaldson SS Pappo AS Qualman SJ Wiener ES Maurer HM Crist WM Rhabdomyosarcoma and undifferentiated sarcoma in the first two decades of life: a selective review of intergroup rhabdomyosarcoma study group experience and rationale for Intergroup Rhabdomyosarcoma Study V.J Pediatr Hematol Oncol. 2001; 23: 215-220Crossref PubMed Scopus (317) Google Scholar, 22Schmidt D Reimann O Treuner J Harms D Cellular differentiation and prognosis in embryonal rhabdomyosarcoma. A report from the Cooperative Soft Tissue Sarcoma Study 1981 (CWS 81).Virchows Arch A Pathol Anat Histopathol. 1986; 409: 183-194Crossref PubMed Scopus (38) Google Scholar Formerly, UDS/NRSTS was considered a diagnosis of exclusion but on current COG protocols (eg, D9902) these patients are not eligible for RMS clinical trials. The Intergroup Rhabdomyosarcoma Study Group (IRSG) was formed as a multi-institutional cooperative effort to better understand the biology of RMS and to improve the outcome of this disease.7Newton Jr, WA Soule EH Hamoudi AB Reiman HM Shimada H Beltangady M Maurer H Histopathology of childhood sarcomas. Intergroup Rhabdomyosarcoma Studies I and II: clinicopathologic correlation.J Clin Oncol. 1988; 6: 67-75Crossref PubMed Scopus (225) Google Scholar Such cooperative efforts have resulted in dramatic improvement of RMS patient overall survival from 25% before the first IRSG-I protocol to ∼71% on IRSG-IV.9Crist WM Anderson JR Meza JL Fryer C Raney RB Ruymann FB Breneman J Qualman SJ Wiener E Wharam M Lobe T Webber B Maurer HM Donaldson SS Intergroup rhabdomyosarcoma study-IV: results for patients with nonmetastatic disease.J Clin Oncol. 2001; 19: 3091-3102PubMed Google Scholar, 23Crist WM Garnsey L Beltangady MS Gehan E Ruymann F Webber B Hays DM Wharam M Maurer HM Prognosis in children with rhabdomyosarcoma: a report of the intergroup rhabdomyosarcoma studies I and II. Intergroup Rhabdomyosarcoma Committee.J Clin Oncol. 1990; 8: 443-452Crossref PubMed Scopus (231) Google Scholar, 24Meyer WH Spunt SL Soft tissue sarcomas of childhood.Cancer Treat Rev. 2004; 30: 269-280Abstract Full Text Full Text PDF PubMed Scopus (106) Google Scholar The recognition that patient outcome is highly variable and dependent on numerous clinicopathological risk factors resulted in the development of a risk-based algorithm for treatment assignment, which combines a histological classification scheme with presurgical stage and postsurgical clinical group. A cornerstone of this risk-based assignment is the histological diagnosis, criteria for which were developed throughout several decades by numerous investigators and culminating in the International Classification of Rhabdomyosarcoma (ICR).3Newton Jr, WA Gehan EA Webber BL Marsden HB van Unnik AJ Hamoudi AB Tsokos MG Shimada H Harms D Schmidt D Classification of rhabdomyosarcomas and related sarcomas. Pathologic aspects and proposal for a new classification—an Intergroup Rhabdomyosarcoma Study.Cancer. 1995; 76: 1073-1085Crossref PubMed Scopus (459) Google Scholar, 25Quackenbush J Microarray analysis and tumor classification.N Engl J Med. 2006; 354: 2463-2472Crossref PubMed Scopus (378) Google Scholar ICR criteria, based mainly on the morphological and cytological examination of hematoxylin and eosin-stained histology sections, resulted in remarkable improvements in the reproducibility of diagnosis and provided a platform for survival models that are predictive of patient outcome.1Asmar L Gehan EA Newton WA Webber BL Marsden HB van Unnik AJ Hamoudi AB Shimada H Tsokos M Harms D Agreement among and within groups of pathologists in the classification of rhabdomyosarcoma and related childhood sarcomas. Report of an international study of four pathology classifications.Cancer. 1994; 74: 2579-2588Crossref PubMed Scopus (79) Google Scholar, 3Newton Jr, WA Gehan EA Webber BL Marsden HB van Unnik AJ Hamoudi AB Tsokos MG Shimada H Harms D Schmidt D Classification of rhabdomyosarcomas and related sarcomas. Pathologic aspects and proposal for a new classification—an Intergroup Rhabdomyosarcoma Study.Cancer. 1995; 76: 1073-1085Crossref PubMed Scopus (459) Google Scholar However, despite exhaustive efforts to establish consensus for these diagnostic criteria, as many as a third of patients could be incorrectly assigned to treatment protocols because of inconsistency and uncertainty as determined by institutional pathology diagnosis—and is the primary reason for mandatory central pathology review process at the COG.19Qualman SJ Coffin CM Newton WA Hojo H Triche TJ Parham DM Crist WM Intergroup Rhabdomyosarcoma Study: update for pathologists.Pediatr Dev Pathol. 1998; 1: 550-561Crossref PubMed Scopus (192) Google Scholar Genomic analysis of human tumor specimens is having a significant impact on the field of tumor pathology,25Quackenbush J Microarray analysis and tumor classification.N Engl J Med. 2006; 354: 2463-2472Crossref PubMed Scopus (378) Google Scholar, 26Lakhani SR Ashworth A Microarray and histopathological analysis of tumours: the future and the past?.Nat Rev Cancer. 2001; 1: 151-157Crossref PubMed Scopus (125) Google Scholar redefining tumor classes based on molecular features27Greer BT Khan J Diagnostic classification of cancer using DNA microarrays and artificial intelligence.Ann NY Acad Sci. 2004; 1020: 49-66Crossref PubMed Scopus (37) Google Scholar, 28Khan J Wei JS Ringner M Saal LH Ladanyi M Westermann F Berthold F Schwab M Antonescu CR Peterson C Meltzer PS Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks.Nat Med. 2001; 7: 673-679Crossref PubMed Scopus (2146) Google Scholar and identifying new subclasses previously unrecognized by conventional histology or cytogenetics.29Ebert BL Golub TR Genomic approaches to hematologic malignancies.Blood. 2004; 104: 923-932Crossref PubMed Scopus (120) Google Scholar We therefore sought to determine whether a new molecular-based classification scheme derived from analysis of gene expression profiles and whole-genome patterns of LOH might be better suited to define a heterogeneous disease such as RMS than conventional histological methods. Analysis was performed on initial diagnostic biopsy specimens from 160 cases of RMS drawn primarily from (IRSG)-IV and (IRSG)-V RMS studies conducted by the COG.8Breneman JC Lyden E Pappo AS Link MP Anderson JR Parham DM Qualman SJ Wharam MD Donaldson SS Maurer HM Meyer WH Baker KS Paidas CN Crist WM Prognostic factors and clinical outcomes in children and adolescents with metastatic rhabdomyosarcoma—a report from the Intergroup Rhabdomyosarcoma Study IV.J Clin Oncol. 2003; 21: 78-84Crossref PubMed Scopus (346) Google Scholar, 9Crist WM Anderson JR Meza JL Fryer C Raney RB Ruymann FB Breneman J Qualman SJ Wiener E Wharam M Lobe T Webber B Maurer HM Donaldson SS Intergroup rhabdomyosarcoma study-IV: results for patients with nonmetastatic disease.J Clin Oncol. 2001; 19: 3091-3102PubMed Google Scholar, 21Raney RB Anderson JR Barr FG Donaldson SS Pappo AS Qualman SJ Wiener ES Maurer HM Crist WM Rhabdomyosarcoma and undifferentiated sarcoma in the first two decades of life: a selective review of intergroup rhabdomyosarcoma study group experience and rationale for Intergroup Rhabdomyosarcoma Study V.J Pediatr Hematol Oncol. 2001; 23: 215-220Crossref PubMed Scopus (317) Google Scholar These samples were analyzed using Affymetrix (Santa Clara, CA) 22,000 gene U133A expression arrays and 10,000 SNP mapping arrays, and results were validated by reverse transcriptase-polymerase chain reaction (RT-PCR) and IHC of primary tumor material. Based on our studies we have identified classes of RMS that differ markedly from those of conventional classification schemes including the ICR. These molecularly defined classes are highly reproducible and can be objectively defined, thus providing several advantages over those of current histopathological classification schemes. Moreover, molecular classification imparts prognostically relevant information that may be useful in optimizing risk-adapted therapy. Tumor specimens were obtained from the Intergroup Rhabdomyosarcoma Study Group/Pediatric Cooperative Human Tissue Network (Columbus, OH) and Children's Hospital Los Angeles institutional tumor banks from 160 patients that were enrolled in IRSG IV and V COG clinical trials. Frozen tumor samples were sectioned and representative sections were examined. Only samples with tumor cell content of at least 80% were included for analysis. Clinical covariates were obtained from the COG Research Data Center (Arcadia, CA). For clinical characteristics of the data set see Table 1 and Supplemental Table S1 available at for individual sample covariate data.Table 1Clinical Characteristics of Gene Expression Microarray Data SetNo.%Histology Alveolar6641.3 Mixed alveolar/embryonal42.5 Embryonal6943.1 Botryoid31.9 Spindle63.8 Undifferentiated or NRSTS*Review diagnosis of undifferentiated sarcoma or non-rhabdomyosarcoma soft-tissue sarcoma.127.5Clinical groups IA & IB3220.0 IIA & IIB138.1 III4427.5 IV2616.3 Unknown4528.1Alive/Dead Alive10565.6 Dead5333.1 Unknown21.3Sex Male9861.3 Female5232.5 Unknown106.3Primary site Orbit53.1 Head/Neck127.5 Paramenigeal2213.8 Bladder/prostate138.1 Genitourinary Other†Non-bladder/prostate genitourinary tumors.2817.5 Extremity3924.4 Other3421.3 Unknown74.4Age groups <1 year74.4 1–4 years5031.3 5–9 years5936.9 10–14 years2213.8 >15 years138.1 Unknown95.6* Review diagnosis of undifferentiated sarcoma or non-rhabdomyosarcoma soft-tissue sarcoma.† Non-bladder/prostate genitourinary tumors. Open table in a new tab Centrally reviewed (IRSG/Cooperative Human Tissue Network) histological diagnoses were based on the International Classification of Rhabdomyosarcoma criteria, in accordance with IRSG protocols.3Newton Jr, WA Gehan EA Webber BL Marsden HB van Unnik AJ Hamoudi AB Tsokos MG Shimada H Harms D Schmidt D Classification of rhabdomyosarcomas and related sarcomas. Pathologic aspects and proposal for a new classification—an Intergroup Rhabdomyosarcoma Study.Cancer. 1995; 76: 1073-1085Crossref PubMed Scopus (459) Google Scholar, 19Qualman SJ Coffin CM Newton WA Hojo H Triche TJ Parham DM Crist WM Intergroup Rhabdomyosarcoma Study: update for pathologists.Pediatr Dev Pathol. 1998; 1: 550-561Crossref PubMed Scopus (192) Google Scholar Mixed alveolar/embryonal tumors or tumors with any evidence of alveolar histology, classical, or solid variant were classified as the alveolar subtype (ARMS, n = 70). Embryonal tumors were all of classical histology, botryoid or spindle cell variants (Table 1) or not-otherwise specified (ERMS, n = 78). Undifferentiated sarcomas or those sarcomas designated as other because of indeterminate/uncertain diagnosis (eg, non-RMS histology) but placed on RMS treatment protocols were also evaluated (UDS/NRSTS, n = 12). RT-PCR using total RNA extracted from frozen tissue was performed on all tumors with alveolar or mixed alveolar/embryonal histology for detection of PAX3-FKHR and PAX7-FKHR fusion transcripts.12Barr FG Qualman SJ Macris MH Melnyk N Lawlor ER Strzelecki DM Triche TJ Bridge JA Sorensen PH Genetic heterogeneity in the alveolar rhabdomyosarcoma subset without typical gene fusions.Cancer Res. 2002; 62: 4704-4710PubMed Google Scholar Additionally, 45 of the ERMS and 8 of the UDS/NRSTS tumors were also assayed for PAX-FKHR transcripts and all were found to be P-F-negative in accordance with previously reported data from IRSG-IV cases.12Barr FG Qualman SJ Macris MH Melnyk N Lawlor ER Strzelecki DM Triche TJ Bridge JA Sorensen PH Genetic heterogeneity in the alveolar rhabdomyosarcoma subset without typical gene fusions.Cancer Res. 2002; 62: 4704-4710PubMed Google Scholar, 13Sorensen PH Lynch JC Qualman SJ Tirabosco R Lim JF Maurer HM Bridge JA Crist WM Triche TJ Barr FG PAX3-FKHR and PAX7-FKHR gene fusions are prognostic indicators in alveolar rhabdomyosarcoma: a report from the children's oncology group.J Clin Oncol. 2002; 20: 2672-2679Crossref PubMed Scopus (605) Google Scholar DNA and RNA were extracted from frozen tissues with DNA STAT and RNA STAT-60, respectively (Tel-Test Inc., Friendswood, TX). RNA was purified with the RNeasy protect kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. Biotin-labeled cRNA was prepared from total RNA and hybridized to Affymetrix GeneChip human U133A expression arrays performed according to the manufacturer's instructions (Affymetrix). Genomic DNA was digested with XbaI, PCR amplified, and hybridized to Affymetrix GeneChip 10K mapping arrays performed according to the manufacturer's instructions (Affymetrix). All data management and analyses were conducted using the Genetrix suite of tools for microarray analysis (Epicenter Software, Pasadena, CA). Estimates of relative mRNA abundances for each of the 22,215 probe sets on the Affymetrix U133A expression microarray were derived using the ProbeProfiler algorithm (Corimbia, Berkeley, CA), which weights individual probes in each probe set according to a principal components model.30James AC Veitch JG Zareh AR Triche T Sensitivity and specificity of five abundance estimators for high-density oligonucleotide microarrays.Bioinformatics. 2004; 20: 1060-1065Crossref PubMed Scopus (11) Google Scholar Probe set filtering was used to remove genes whose SD was less than 40 Affymetrix average difference intensity units across all of the samples reducing the number of useable probe sets to 11,694 (henceforth, genes).31Davicioni E Finckenstein FG Shahbazian V Buckley JD Triche TJ Anderson MJ Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas.Cancer Res. 2006; 66: 6936-6946Crossref PubMed Scopus (252) Google Scholar Probe set average difference intensity values were truncated at 1 and log transformed. The complete tumor microarray data set can be found on the National Cancer Institute Cancer Array Database at . Semisupervised clustering was performed using a k-means algorithm. Because the k-means method converges to a local minimum, with the final clusters being dependent on the starting position of the cluster centroids, a metaclustering approach was used in which the clustering was repeated 2000 times and the cluster membership information from each run was aggregated. For each metaclustering run, i) the genes used for classification were independently selected based on the significance level for each gene in a Kruskal-Wallis H test of homogeneity of the expression means values in each of the three ICR histological groups, ii) the initial positions of the k centroid means were randomly selected, iii) a random selection of n (test) samples were separated for cross validation (leave-n-out sampling), where n was set to 10% of the sample set, iv) the k-means algorithm was applied to the remaining (training) samples, v) the membership of each of the n out-of-sample cases was based on the closest training set centroid, vi) a pairwise similarity matrix was cumulated across all metacluster runs, based on the proportion of all runs in which both members of the pair were present in the same test set that placed both members in the same class, and vii) a multidimensional scaling analysis based on the final cumulative similarity matrix was used to generate two-way hierarchical clustering dendrogram. Probe set selection criteria for Kruskal-Wallis H test used a false discovery correction with a P value set to <0.00001 to provide an estimated false discovery rate of 0.1%. Cluster centroids discovery for P-F RMS tumors was done as described above except a t-test was used to select for differentially expressed genes between PAX3-FKHR and PAX7-FKHR ARMS. The multidimensional scaling analysis showing the relative proximities of each sample based on the final cumulative similarity matrix of this first metaclustering round can be seen in Supplemental Figure S1A available at . Two clusters of P-F RMS are apparent, the colored circles denote the new tumor classes that were used to select for differentially expressed genes in a second round of metaclustering. For fusion-negative tumors the same procedure was applied except using Kruskal-Wallis H test to initially select for genes differentially expressed between spindle/botryoid, embryonal, fusion-negative alveolar, and UDS/NRSTS tumor groups. Clusters identified by this round of metaclustering were used to select for genes and derive the clustering in a second round of metaclustering. Samples and genes were optimally ordered by complete-linkage hierarchical clustering using Pearson's correlation metrics. The nearest shrunken centroids algorithm, a derivative of SAM (significance analysis of microarrays), developed by Tibshirani and colleagues,32Tibshirani R Hastie T Narasimhan B Chu G Diagnosis of multiple cancer types by shrunken centroids of gene expression.Proc Natl Acad Sci USA. 2002; 99: 6567-6572Crossref PubMed Scopus (2145) Google Scholar and implemented within Genetrix, was evaluated as a classification tool by calculation of the centroids for each of the three major tumor classes (P-F RMS, F RMS, and UDS/NRSTS) as determined by our semisupervised metaclustering analyses. Our objective was to define a minimal discriminatory gene signature for RMS tumors and to determine whether the consensus molecular classes observed with analysis of the expression patterns of hundreds of genes (ie, P-F RMS, P-F-negative RMS, and UDS/NRSTS), are reliably identified with a shrunken subset of less than 20 genes. Such a minimal expression signature would be more suited than whole-genome arrays for routine clinical practice (eg, through the use of quantitative RT-PCR or other low-density multiplex assays). Samples evaluated for this analysis consisted of the 55 P-F-positive ARMS histology tumors, 93 P-F-negative tumors (embryonal, spindle, botryoid, and alveolar) and 12 UDS/NRSTS histology tumors (undifferentiated or other) (Figure 1). This combines the accepted or consensus molecular genetic classifiers (ie, P-F-positive or -negative) with the ICR histological classification scheme, and permits closer comparison of a putative expression-based scheme to a purely histological classification scheme. Classes were based on a training set of samples and allocation of members of a test set to the nearest centroid. The training and test sets were created through a leave-n-out cross validation procedure (with n = 16). The initial gene set for classification was the 609 genes that were selected in the all metaclustering analyses, and the centroids w" @default.
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• W1504229479 title "Molecular Classification of Rhabdomyosarcoma—Genotypic and Phenotypic Determinants of Diagnosis" @default.
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