Levine Study Summary

[Marylouise Colleen]

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Comparisons of 66 SMGs between traditional histological subtypes are provided (Supplementary Methods 3), and SMGs across other subcohorts can be found in Supplementary Data 3.2. The spectrum of PIK3CA and PTEN mutations in endometrial cancer also differed from other solid tumours (Supplementary Methods 3). Integrated analysis may be useful for identifying histologically misclassified cases. For example, a single serous case was identified without a TP53 mutation or extensive SCNAs and with a KRAS mutation and high mutation rate. After re-review of the histological section, the case was deemed consistent with a grade 3 endometrioid tumour, demonstrating how molecular analysis could reclassify tumour histology and potentially affect treatment decisions.

Integrative clustering using the iCluster framework returned two major clusters split primarily on serous and endometrioid histology highlighting TP53 mutations, lack of PTEN mutation and encompassing almost exclusively copy-number high tumours23 (Supplementary Fig. 8.1). We developed a new clustering algorithm, called SuperCluster, to derive overall subtypes based on sample cluster memberships across all data types (Supplementary Fig. 9.1). SuperCluster identified four clusters that generally confirmed the contributions of individual platforms to the overall integrated clusters. No major batch effects were identified for any platform (Supplementary Methods 10).

Multiple platform data were integrated to identify recurrently altered pathways in the four endometrial cancer integrated subgroups. Because of the high background mutation rate and small sample size, we excluded the POLE subgroup from this analysis. Considering all recurrently mutated, homozygously deleted, and amplified genes, we used MEMo25 to identify gene networks with mutually exclusive alteration patterns in each subgroup. The most significant module was found in the copy-number low group and contained CTNNB1, KRAS and SOX17 (Fig. 4a). The very strong mutual exclusivity between mutations in these three genes suggests that alternative mechanisms activate WNT signalling in endometrioid endometrial cancer. Activating KRAS mutations have been shown to increase the stability of β-catenin via glycogen synthase kinase 3β (GSK-3β), leading to an alternative mechanism of β-catenin activation other than adenomatous polyposis coli degradation26. SOX17, which mediates proteasomal degradation of β-catenin27,28, is mutated exclusively in the copy-number low group (8%) at recurrent positions (Ala96Gly and Ser403Ile) not previously described. Other genes with mutually exclusive alteration patterns in this module were FBXW7, FGFR2 and ERBB2 (ref. 29). ERBB2 was focally amplified with protein overexpression in 25% of the serous or serous-like tumours, suggesting a potential role for human epidermal growth factor receptor 2 (HER2)-targeted inhibitors. A small clinical trial of trastuzumab found no activity in endometrial carcinoma, but accrued few HER2 fluorescence in situ hybridization (FISH)-amplified serous carcinomas30.

a, The RTK/RAS/β-catenin pathway is altered through several mechanisms that exhibit mutually exclusive patterns. Alteration frequencies are expressed as a percentage of all cases. The right panel shows patterns of occurrence. b, The PI(3)K pathway has mutually exclusive PIK3CA and PIK3R1 alterations that frequently co-occur with PTEN alterations in the MSI and copy-number low subgroups. c, Heat map display of top 1,000 varying pathway features within PARADIGM consensus clusters. Samples were arranged in order of their consensus cluster membership. The genomic subtype for each sample is displayed below the consensus clusters.

PIK3CA and PIK3R1 mutations were frequent and showed a strong tendency for mutual exclusivity in all subgroups, but unlike other tumour types, they co-occurred with PTEN mutations in the MSI and copy-number low subgroups as previously reported5,9 (Fig. 4b). The copy-number high subgroup showed mutual exclusivity between alterations of all three genes. Overall, 93% of endometrioid tumours had mutations that suggested potential for targeted therapy with PI(3)K/AKT pathway inhibitors.

Consensus clustering of copy number, mRNA expression and pathway interaction data for 324 samples yielded five PARADIGM clusters with distinct pathway activation patterns31 (Fig. 4c and Supplementary Methods 11). PARADIGM cluster 1 had the lowest level of MYC pathway activation and highest level of WNT pathway activation, consistent with its composition of copy-number low cases having frequent CTNNB1 mutations. PARADIGM cluster 3 was composed predominantly of the copy-number high cases, with relatively high MYC/MAX signalling but low oestrogen receptor/FOXA1 signalling and p53 activity. Only TP53 truncation and not missense mutations were implicated as loss-of-function mutations, suggesting different classes of p53 mutations may have distinct signalling consequences. PARADIGM cluster 5 was enriched for hormone receptor expression.

The clinical and pathologic features of uterine serous carcinoma and high-grade serous ovarian carcinoma (HGSOC) are quite similar. HGSOC shares many similar molecular features with basal-like breast carcinoma32. Focal SCNA patterns were similar between these three tumour subtypes and unsupervised clustering identified relatedness (Fig. 5a and Supplementary Fig. 12.1). Supervised analysis of transcriptome data sets showed high correlation between tumour subtypes (Supplementary Fig. 12.2). The MC3 DNA methylation subtype with minimal DNA methylation changes was also similar to basal-like breast and HGSOCs (Supplementary Fig. 12.3). A high frequency of TP53 mutations is shared across these tumour subtypes (uterine serous, 91%; HGSOC, 96%; basal-like breast, 84%)33,34, as is the very low frequency of PTEN mutations (uterine serous, 2%; HGSOC, 1%; basal-like breast, 1%). Differences included a higher frequency of FBXW7, PPP2R1A and PIK3CA mutations in uterine serous compared to basal-like breast and HGSOCs (Fig. 5b). We showed that uterine serous carcinomas share many molecular features with both HGSOCs and basal-like breast carcinomas, despite more frequent mutations, suggesting new opportunities for overlapping treatment paradigms.

Biospecimens were obtained from 373 patients after Institutional Review Board-approved consents. DNA and RNA were co-isolated using a modified AllPrep kit (Qiagen). We used Affymetrix SNP 6.0 microarrays to detect SCNAs in 363 samples and GISTIC analysis to identify recurrent events37. The exomes of 248 tumours were sequenced to a read-depth of at least 20. We performed low-pass whole-genome sequencing on 107 tumours to a mean depth of 6. Consensus clustering was used to analyse mRNA, miRNA, RPPA and methylation data with methods previously described38,39,40. Integrated cross-platform analyses were performed using MEMo, iCluster and PARADIGM25,31.

The TCGA Research Network contributed collectively to this study. Biospecimens were provided by the tissue source sites and processed by the biospecimen core resource. Data generation and analyses were performed by the genome sequencing centres, cancer genome characterization centres and genome data analysis centres. All data were released through the data coordinating centre. The National Cancer Institute and National Human Genome Research Institute project teams coordinated project activities. We also acknowledge the following TCGA investigators who made substantial contributions to the project: N.S. (manuscript coordinator); J. Gao (data coordinator); C.K. and L. Ding (DNA sequence analysis); W.Z. and Y.L. (mRNA sequence analysis); H.S. and P.W.L. (DNA methylation analysis); A.D.C. and I.P. (copy number analysis); S.L. and A. Hadjipanayis (translocations); N.S., N.W. G.C., C.C.B. and C.Y. (pathway analysis); Andy C. and A.G.R. (miRNA sequence analysis); R. Broaddus, P.J.G., G.B.M. and R.A.S. (pathology and clinical expertise); G.B.M., H.L. and R.A. (reverse phase protein arrays); P.J.G. and R.B. (disease experts); G.B.M. and R.K. (manuscript editing); D.A.L. and E.R.M. (project chairs).

The primary and processed data used to generate the analyses presented here are deposited at the Data Coordinating Center ( -data.nci.nih.gov/tcga/tcgaDownload.jsp); all of the primary sequence files are deposited in CGHub ( ). Sample lists, data matrices and supporting data can be found at: ( -data.nci.nih.gov/docs/publications/ucec_2013/). The data can be explored via the cBio Cancer Genomics Portal ( ). Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to D.A.L. (lev...@mskcc.org).

This paper from The Cancer Genome Atlas Research Network presents an in-depth genome-wide analysis of endometrial (uterine) carcinomas from more than 350 patients. Based on a series of genomic features including newly identified hotspot mutations in the DNA polymerase gene POLE, and novel mutations in the ARID5B DNA-binding protein, the authors propose a reclassification of endometrial tumours into four distinct types. This might have clinical relevance for post-surgical adjuvant treatment of women with aggressive tumours.

Ella Enchanted Summary & Study Guide includes comprehensive information and analysis tohelp you understand the book. This study guide contains the following sections:Plot SummaryChaptersCharactersObjects/PlacesThemesStyleQuotes This detailed literature summary also contains Topics for Discussion and a Free Quiz onElla Enchanted by Gail Carson Levine.When Ella is born, a fairy gives her the gift of obedience. As a result, Ella is always under the power of everyone who tells her what to do, no matter what strange commands she receives.

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