Whole transcriptome RNA-seq analysis of breast cancer recurrence risk using formalin-fixed paraffin-embedded tumor tissue

PLoS ONE

Volumn 7, Issue 7, 2012, Pages

  Sinicropi, Dominick ^a   Qu, Kunbin ^a   Collin, Francois ^a   Crager, Michael ^a   Liu, Mei Lan ^a   Pelham, Robert J ^a   Pho, Mylan ^a   de Rossi, Andrewi ^a   Jeong, Jennie ^a   Scott, Aaron ^a   Ambannavar, Ranjana ^a   Zheng, Christina ^a   Mena, Raul ^b   Esteban, Jose ^b   Stephans, James ^a   Morlan, John ^a   Baker, Joffre ^a  

^a Genomic Health Inc   (United States)

^b Providence Saint Joseph Medical Center   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORMALDEHYDE; PARAFFIN; TUMOR MARKER;

ARTICLE; BIOINFORMATICS; BIOSTATISTICS; BREAST CANCER; COHORT ANALYSIS; DIAGNOSTIC ACCURACY; DNA FINGERPRINTING; DNA MICROARRAY; EXON; GENETIC ASSOCIATION; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; INTRON; MAJOR CLINICAL STUDY; MOLECULAR LIBRARY; RECURRENCE RISK; RNA SEQUENCE; SENSITIVITY ANALYSIS; SEQUENCE ANALYSIS; TRANSCRIPTOMICS; TUMOR BIOPSY;

BASE SEQUENCE; BREAST NEOPLASMS; DNA, INTERGENIC; FEMALE; FORMALDEHYDE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; INTRONS; NEOPLASM RECURRENCE, LOCAL; PARAFFIN EMBEDDING; PROPORTIONAL HAZARDS MODELS; RISK FACTORS; RNA, MESSENGER; RNA, NEOPLASM; SEQUENCE ANALYSIS, RNA; TISSUE FIXATION; TUMOR MARKERS, BIOLOGICAL;

EID: 84863763618     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0040092     Document Type: Article

References (56)

1. Metzker ML, (2010) Sequencing technologies- the next generation. Nat Rev Genet 11: 31-46.
2. Ozsolak F, Milos PM, (2011) RNA sequencing: advances, challenges and opportunities. Nat Rev Genet 12: 87-98.
3. Wang Z, Gerstein M, Snyder M, (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10: 57-63.
4. Paik S, Shak S, Tang G, Kim C, Baker J, et al. (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351: 2817-2826.
5. Chudova D, Wilde JI, Wang ET, Wang H, Rabbee N, et al. (2010) Molecular classification of thyroid nodules using high-dimensionality genomic data. J Clin Endocrinol Metab 95: 5296-5304.
6. Mehra MR, Kobashigawa JA, Deng MC, Fang KC, Klingler TM, et al. (2007) Transcriptional signals of T-cell and corticosteroid-sensitive genes are associated with future acute cellular rejection in cardiac allografts. J Heart Lung Transplant 26: 1255-1263.
7. Mehra MR, Kobashigawa JA, Deng MC, Fang KC, Klingler TM, et al. (2008) Clinical implications and longitudinal alteration of peripheral blood transcriptional signals indicative of future cardiac allograft rejection. J Heart Lung Transplant 27: 297-301.
8. Paik S, Tang G, Shak S, Kim C, Baker J, et al. (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24: 3726-3734.
9. Habel LA, Shak S, Jacobs MK, Capra A, Alexander C, et al. (2006) A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 8: R25.
10. Gianni L, Zambetti M, Clark K, Baker J, Cronin M, et al. (2005) Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J Clin Oncol 23: 7265-7277.
11. Samson K, (2011) Oncotype DX gene test seen changing over one-third of early breast cancer decisions. Oncology Times 33: 10-11.
12. Lewis F, Maughan NJ, Smith V, Hillan K, Quirke P, (2001) Unlocking the archive - gene expression in paraffin-embedded tissue. The Journal of Pathology 195: 66-71.
13. Godfrey TE, Kim SH, Chavira M, Ruff DW, Warren RS, et al. (2000) Quantitative mRNA expression analysis from formalin-fixed, paraffin-embedded tissues using 5′ nuclease quantitative reverse transcription-polymerase chain reaction. J Mol Diagn 2: 84-91.
14. Goldsworthy SM, Stockton PS, Trempus CS, Foley JF, Maronpot RR, (1999) Effects of fixation on RNA extraction and amplification from laser capture microdissected tissue. Mol Carcinog 25: 86-91.
15. Cronin M, Pho M, Dutta D, Stephans JC, Shak S, et al. (2004) Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol 164: 35-42.
16. Esteban JM, Baker J, Cronin M, Liu M-L, Llamas MG, et al. (2003) Tumor gene expression and prognosis in breast cancer: Multi-gene RT-PCR assay of parafin-embedded tissue. Proc Amer Assoc Cancer Res.
17. Claverie JM, (2005) Fewer genes, more noncoding RNA. Science 309: 1529-1530.
18. Mattick JS, (2005) The functional genomics of noncoding RNA. Science 309: 1527-1528.
19. Bartel DP, (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116: 281-297.
20. Bartel DP, (2009) MicroRNAs: target recognition and regulatory functions. Cell 136: 215-233.
21. Khalil AM, Guttman M, Huarte M, Garber M, Raj A, et al. (2009) Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proc Natl Acad Sci U S A 106: 11667-11672.
22. Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, et al. (2011) Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev 25: 1915-1927.
23. Guttman M, Donaghey J, Carey BW, Garber M, Grenier JK, et al. (2011) lincRNAs act in the circuitry controlling pluripotency and differentiation. Nature.
24. Lin DY, Wei LJ, (1989) The robust inference for the Cox Proportional Hazards Model. Journal of the Royal Statistical Society, Series B 84: 1074-1078.
25. Buchard A, Sanchez JJ, Dalhoff K, Morling N, (2007) Multiplex PCR detection of GSTM1, GSTT1, and GSTP1 gene variants: simultaneously detecting GSTM1 and GSTT1 gene copy number and the allelic status of the GSTP1 Ile105Val genetic variant. J Mol Diagn 9: 612-617.
26. Zhang H, Ahmadi A, Arbman G, Zdolsek J, Carstensen J, et al. (1999) Glutathione S-transferase T1 and M1 genotypes in normal mucosa, transitional mucosa and colorectal adenocarcinoma. Int J Cancer 84: 135-138.
27. Kiefer M HK, Hackett J, Walker M, Baker J, (2006) Multiple GSTM gene family members are recurrence risk markers in breast cancer.
28. van de Vijver MJ, He YD, van 't Veer LJ, Dai H, Hart AAM, et al. (2002) A Gene-Expression Signature as a Predictor of Survival in Breast Cancer. New England Journal of Medicine 347: 1999-2009.
29. Van't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415: 530-536.
30. Eisen MB, Spellman PT, Brown PO, Botstein D, (1998) Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences 95: 14863-14868.
31. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, et al. (2003) Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research 13: 2498-2504.
32. Smoot ME, Ono K, Ruscheinski J, Wang P-L, Ideker T, (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27: 431-432.
33. Joshi-Tope G, Gillespie M, Vastrik I, D'Eustachio P, Schmidt E, et al. (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33: D428-432.
34. Fisher B, Costantino J, Redmond C, Poisson R, Bowman D, et al. (1989) A Randomized Clinical Trial Evaluating Tamoxifen in the Treatment of Patients with Node-Negative Breast Cancer Who Have Estrogen-Receptor-Positive Tumors. New England Journal of Medicine 320: 479-484.
35. Block GE, Ellis RS, DeSombre E, Jensen E, (1978) Correlation of estrophilin content of primary mammary cancer to eventual endocrine treatment. Ann Surg 188: 372-376.
36. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, et al. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 98: 10869-10874.
37. Fisher B, Jeong JH, Bryant J, Anderson S, Dignam J, et al. (2004) Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 364: 858-868.
38. Davies C, Godwin J, Gray R, Clarke M, Cutter D, et al. (2011) Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet 378: 771-784.
39. Kim C, Tang G, Pogue-Geile KL, Costantino JP, Baehner FL, et al. (2011) Estrogen Receptor (ESR1) mRNA Expression and Benefit From Tamoxifen in the Treatment and Prevention of Estrogen Receptor-Positive Breast Cancer. Journal of Clinical Oncology.
40. Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, et al. (2007) Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129: 1311-1323.
41. Guttman M, Amit I, Garber M, French C, Lin MF, et al. (2009) Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 458: 223-227.
42. Kapranov P, St Laurent G, Raz T, Ozsolak F, Reynolds CP, et al. (2010) The majority of total nuclear-encoded non-ribosomal RNA in a human cell is 'dark matter' un-annotated RNA. BMC Biol 8: 149.
43. Mondal T, Rasmussen M, Pandey GK, Isaksson A, Kanduri C, (2010) Characterization of the RNA content of chromatin. Genome Res 20: 899-907.
44. Prensner JR, Iyer MK, Balbin OA, Dhanasekaran SM, Cao Q, et al. (2011) Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression. Nat Biotechnol 29: 742-749.
45. Amaral PP, Clark MB, Gascoigne DK, Dinger ME, Mattick JS, (2011) lncRNAdb: a reference database for long noncoding RNAs. Nucleic Acids Res 39: D146-151.
46. Garber M, Grabherr MG, Guttman M, Trapnell C, (2011) Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods 8: 469-477.
47. Mortazavi A, Williams B, McCue K, Schaeffer L, Wold B, (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods 5: 621-628.
48. Bullard J, Purdom E, Hansen K, Dudoit S, (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics 11: 94.
49. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, et al. (2008) Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 10: R65.
50. Au KF, Jiang H, Lin L, Xing Y, Wong WH, (2010) Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res 38: 4570-4578.
51. Weigelt B, Pusztai L, Ashworth A, Reis-Filho JS, (2011) Challenges translating breast cancer gene signatures into the clinic. Nat Rev Clin Oncol.
52. Langmead B, Trapnell C, Pop M, Salzberg S, (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology 10: R25.
53. Cox DR, (1972) Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B (Methodological) 34: 187-220.
54. Wei LJ, Lin DY, Weissfeld L, (1989) Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of the American Statistical Association 84: 1065-1073.
55. Storey JD, (2002) A direct approach to fase discovery rates. Journal of the Royal Statistical Society, Series B 64: 479-498.
56. Crager MR, (2010) Gene identification using true discovery rate degree of association sets and estimates corrected for regression to the mean. Statistics in Medicine 29: 33-45.