Radiogenomics of clear cell renal cell carcinoma: preliminary findings of The Cancer Genome Atlas–Renal Cell Carcinoma (TCGA–RCC) Imaging Research Group

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• 作者：Atul B. Shinagare ; Raghu Vikram ; Carl Jaffe ; Oguz Akin ; Justin Kirby…
• 关键词：Clear cell renal cell carcinoma ; CT ; MRI ; Mutational status ; Radiogenomics
• 刊名：Abdominal Imaging
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：40
• 期：6
• 页码：1684-1692
• 全文大小：1,391 KB
• 参考文献：1.Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65(1):5-9PubMed View Article
  2.Lam JS, Shvarts O, Leppert JT, Figlin RA, Belldegrun AS (2005) Renal cell carcinoma 2005: new frontiers in staging, prognostication and targeted molecular therapy. J Urol 173(6):1853-862PubMed View Article
  3.Gerlinger M, Rowan AJ, Horswell S, et al. (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366(10):883-92PubMed View Article
  4.Cancer Genome Atlas Research Network (2013) Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499(7456):43-9View Article
  5.Pe?a-Llopis S, Vega-Rubín-de-Celis S, Liao A, et al. (2012) BAP1 loss defines a new class of renal cell carcinoma. Nat Genet 44(7):751-59PubMed Central PubMed View Article
  6.Dalgliesh GL, Furge K, Greenman C, et al. (2010) Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes. Nature 463(7279):360-63PubMed Central PubMed View Article
  7.Varela I, Tarpey P, Raine K, et al. (2011) Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature 469(7331):539-42PubMed Central PubMed View Article
  8.Guo G, Gui Y, Gao S, et al. (2012) Frequent mutations of genes encoding ubiquitin-mediated proteolysis pathway components in clear cell renal cell carcinoma. Nat Genet 44(1):17-9View Article
  9.Duns G, van den Berg E, van Duivenbode I, et al. (2010) Histone methyltransferase gene SETD2 is a novel tumor suppressor gene in clear cell renal cell carcinoma. Cancer Res 70(11):4287-291PubMed View Article
  10.Shinagare AB, Giardino AA, Jagannathan JP, Van den Abbeele AD, Ramaiya NH (2011) Hereditary cancer syndromes: a radiologist’s perspective. Am J Roentgenol 197(6):W1001–W1007View Article
  11.Kim WY, Kaelin WG (2004) Role of VHL gene mutation in human cancer. J Clin Oncol 22(24):4991-004PubMed View Article
  12.Shuin T, Kondo K, Torigoe S, et al. (1994) Frequent somatic mutations and loss of heterozygosity of the von Hippel-Lindau tumor suppressor gene in primary human renal cell carcinomas. Cancer Res 54(11):2852-855PubMed
  13.Kapur P, Pe?a-Llopis S, Christie A, et al. (2013) Effects on survival of BAP1 and PBRM1 mutations in sporadic clear-cell renal-cell carcinoma: a retrospective analysis with independent validation. Lancet Oncol 14(2):159-67PubMed View Article
  14.Hakimi AA, Chen Y-B, Wren J, et al. (2013) Clinical and pathologic impact of select chromatin-modulating tumor suppressors in clear cell renal cell carcinoma. Eur Urol 63(5):848-54PubMed Central PubMed View Article
  15.cBioPortal for Cancer Genomics: Results [Internet]. http://?www.?cbioportal.?org/?public-portal/?index.?do??cancer_?study_?id=?kirc_?tcga_?pub&?genetic_?profile_?ids_?PROFILE_?MUTATION_?EXTENDED=?kirc_?tcga_?pub_?mutations&?genetic_?profile_?ids_?PROFILE_?COPY_?NUMBER_?ALTERATION=?kirc_?tcga_?pub_?gistic&?Z_?SCORE_?THRESHOLD=-.-&?RPPA_?SCORE_?THRESHOLD=-.-&?data_?priority=-&?case_?set_?id=?kirc_?tcga_?pub_?cnaseq&?case_?ids=-?gene_?set_?choice=?user-defined-list&?gene_?list=?MUC4&?clinical_?param_?selection=?null&?tab_?index=?tab_?visualize&?Action=?Submit . Accessed 22 Jul 2014
  16.Brugarolas J (2014) Molecular genetics of clear-cell renal cell carcinoma. J Clin Oncol 32(18):1968-976PubMed Central PubMed View Article
  17.Kuo MD, Jamshidi N (2014) Behind the numbers: decoding molecular phenotypes with radiogenomics—guiding principles and technical considerations. Radiology 270(2):320-25PubMed View Article
  18.Karlo CA, Di Paolo PL, Chaim J, et al. (2014) Radiogenomics of clear cell renal cell carcinoma: associations between CT imaging features and mutations. Radiology 270(2):464-71PubMed Central PubMed View Article
  19.CIP TCGA Radiology Initiative—The Cancer Imaging Archive (TCIA) Public Access—Cancer Imaging Archive Wiki [Internet]. https://?wiki.?cancerimagingarc?hive.?net/?display/?Public/?CIP+TCGA+Radiolo?gy+Initiative;jsessionid=-2ACC1CC632A2219?F9A6F965E2325B68-/span> . Accessed 23 Sep 2014
  20.Software Tools: Department of Radiology: Feinberg School of Medicine: Northwestern University [Internet]. http://?www.?radiology.?northwestern.?edu/?research/?areas-of-research/?Imaging-Informatics-home/?Software%20?Tools.?html . Accessed 18 Sep 2014
  21.Mongkolwat P, Kleper V, Talbot S, Rubin D (2014) The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation Model. J Digit Imaging. 27:692-01PubMed View Article
  22.Mongkolwat P, Channin DS, Kleper V, Rubin DL (2012) Informatics in radiology: an open-source and open-access cancer biomedical informatics grid annotation and image markup template builder. Radiographics 32(4):1223-232PubMed Central PubMed View Article
  23.McGraw KO, Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychol Methods 1(1):30-6View Article
• 作者单位：Atul B. Shinagare (1)
  Raghu Vikram (2)
  Carl Jaffe (3)
  Oguz Akin (4)
  Justin Kirby (5)
  Erich Huang (5)
  John Freymann (5)
  Nisha I. Sainani (1)
  Cheryl A. Sadow (1)
  Tharakeswara K. Bathala (2)
  Daniel L. Rubin (6)
  Aytekin Oto (7)
  Matthew T. Heller (8)
  Venkateswar R. Surabhi (9)
  Venkat Katabathina (10)
  Stuart G. Silverman (1)
  
  1. Brigham and Women’s Hospital, Boston, MA, USA
  2. University of Texas MD Anderson Cancer Center, Houston, TX, USA
  3. Boston Medical Center, Boston, MA, USA
  4. Memorial Sloan Kettering Cancer Center, New York, NY, USA
  5. National Cancer Institute, Bethesda, USA
  6. Stanford University School of Medicine, Stanford, CA, USA
  7. University of Chicago, Chicago, IL, USA
  8. University of Pittsburgh Medical Center, Pittsburgh, PA, USA
  9. University of Texas Health Science Center, Houston, TX, USA
  10. University of Texas Health Science Center, San Antonio, TX, USA
  
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Imaging and Radiology
  Gastroenterology
  Hepatology
  
• 出版者：Springer New York
• ISSN：1432-0509

文摘

Purpose To investigate associations between imaging features and mutational status of clear cell renal cell carcinoma (ccRCC). Materials and methods This multi-institutional, multi-reader study included 103 patients (77 men; median age 59?years, range 34-9) with ccRCC examined with CT in 81 patients, MRI in 19, and both CT and MRI in three; images were downloaded from The Cancer Imaging Archive, an NCI-funded project for genome-mapping and analyses. Imaging features [size (mm), margin (well-defined or ill-defined), composition (solid or cystic), necrosis (for solid tumors: 0%, 1%-3%, 34%-6% or >66%), growth pattern (endophytic, <50% exophytic, or ?0% exophytic), and calcification (present, absent, or indeterminate)] were reviewed independently by three readers blinded to mutational data. The association of imaging features with mutational status (VHL, BAP1, PBRM1, SETD2, KDM5C, and MUC4) was assessed. Results Median tumor size was 49?mm (range 14-62?mm), 73 (71%) tumors had well-defined margins, 98 (95%) tumors were solid, 95 (92%) showed presence of necrosis, 46 (45%) had ?0% exophytic component, and 18 (19.8%) had calcification. VHL (n?=?52) and PBRM1 (n?=?24) were the most common mutations. BAP1 mutation was associated with ill-defined margin and presence of calcification (p?=?0.02 and 0.002, respectively, Pearson’s χ 2 test); MUC4 mutation was associated with an exophytic growth pattern (p?=?0.002, Mann–Whitney U test). Conclusions BAP1 mutation was associated with ill-defined tumor margins and presence of calcification; MUC4 mutation was associated with exophytic growth. Given the known prognostic implications of BAP1 and MUC4 mutations, these results support using radiogenomics to aid in prognostication and management.