Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population
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  • 作者:Chi-Cheng Huang (1) (2) (3) (4)
    Shih-Hsin Tu (4) (5)
    Heng-Hui Lien (3) (5)
    Jaan-Yeh Jeng (2) (3) (4)
    Jung-Sen Liu (3) (5)
    Ching-Shui Huang (4) (5)
    Yih-Yiing Wu (6)
    Chih-Yi Liu (6)
    Liang-Chuan Lai (7)
    Eric Y Chuang (1)
  • 刊名:Journal of Translational Medicine
  • 出版年:2012
  • 出版时间:September 2012
  • 年:2012
  • 卷:10
  • 期:1-supp
  • 全文大小:191KB
  • 参考文献:1. Perou CM, S?rlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, L?nning PE, B?rresen-Dale AL, Brown PO, Botstein D: Molecular portraits of human breast tumours. / Nature 2000, 406:747-52. CrossRef
    2. S?rlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, L?nning PE, B?rresen-Dale AL: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. / Proc Natl Acad Sci U S A 2001, 98:10869-0874. CrossRef
    3. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, Demeter J, Perou CM, L?nning PE, Brown PO, B?rresen-Dale AL, Botstein D: Repeated observation of breast tumor subtypes in independent gene expression data sets. / Proc Natl Acad Sci U S A 2003, 100:8418-423. CrossRef
    4. Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Ruiz Orrico A, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS, Perou CM: The molecular portraits of breast tumors are conserved across microarray platforms. / BMC Genomics 2006, 7:96. CrossRef
    5. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET: Breast cancer classification and prognosis based on gene expression profiles from a population-based study. / Proc Natl Acad Sci U S A 2003, 100:10393-0398. CrossRef
    6. Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, Quackenbush JF, Stijleman IJ, Palazzo J, Marron JS, Nobel AB, Mardis E, Nielsen TO, Ellis MJ, Perou CM, Bernard PS: Supervised risk predictor of breast cancer based on intrinsic subtypes. / J Clin Oncol 2009, 27:1160-167. CrossRef
    7. Lusa L, McShane LM, Reid JF, De Cecco L, Ambrogi F, Biganzoli E, Gariboldi M, Pierotti MA: Challenges in projecting clustering results across gene expression-profiling datasets. / J Natl Cancer Inst 2007, 99:1715-723. CrossRef
    8. Weigelt B, Mackay A, A'hern R, Natrajan R, Tan DS, Dowsett M, Ashworth A, Reis-Filho JS: Breast cancer molecular profiling with single sample predictors: a retrospective analysis. / Lancet Oncol 2010, 11:339-49. CrossRef
    9. Fan C, Oh DS, Wessels L, Weigelt B, Nuyten DS, Nobel AB, van't Veer LJ, Perou CM: Concordance among gene-expression-based predictors for breast cancer. / N Engl J Med 2006, 355:560-69. CrossRef
    10. Mackay A, Weigelt B, Grigoriadis A, Kreike B, Natrajan R, A'Hern R, Tan DS, Dowsett M, Ashworth A, Reis-Filho JS: Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement. / J Natl Cancer Inst 2011, 103:662-73. CrossRef
    11. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. / Biostatistics 2003, 4:249-64. CrossRef
    12. Lu X, Lu X, Wang ZC, Iglehart JD, Zhang X, Richardson AL: Predicting features of breast cancer with gene expression patterns. / Breast Cancer Res Treat 2008, 108:191-01. CrossRef
    13. S?rlie T, Borgan E, Myhre S, Vollan HK, Russnes H, Zhao X, Nilsen G, Lingjaerde OC, B?rresen-Dale AL, R?dland E: The importance of gene-centring microarray data. / Lancet Oncol 2010, 11:719-20. CrossRef
    14. Benito M, Parker J, Du Q, Wu J, Xiang D, Perou CM, Marron JS: Adjustment of systematic microarray data biases. / Bioinformatics 2004, 20:105-14. CrossRef
    15. Pusztai L, Mazouni C, Anderson K, Wu Y, Symmans WF: Molecular classifications of breast cancer: limitations and potential. / Oncologist 2006, 11:868-77. CrossRef
    16. Weigelt B, Reis-Filho JS: Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry. / Breast Cancer Res 2010,12(Suppl 4):S5. CrossRef
  • 作者单位:Chi-Cheng Huang (1) (2) (3) (4)
    Shih-Hsin Tu (4) (5)
    Heng-Hui Lien (3) (5)
    Jaan-Yeh Jeng (2) (3) (4)
    Jung-Sen Liu (3) (5)
    Ching-Shui Huang (4) (5)
    Yih-Yiing Wu (6)
    Chih-Yi Liu (6)
    Liang-Chuan Lai (7)
    Eric Y Chuang (1)

    1. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei City, Taiwan
    2. Department of Surgery, Cathay General Hospital SiJhih, New Taipei City, Taiwan
    3. School of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
    4. School of Medicine, Taipei Medical University, Taipei City, Taiwan
    5. Department of Surgery, Cathay General Hospital, Taipei City, Taiwan
    6. Department of Pathology, Cathay General Hospital SiJhih, New Taipei City, Taiwan
    7. Graduate Institute of Physiology, National Taiwan University, Taipei City, Taiwan
文摘
Background Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (S?rlie 500, Hu 306 and PAM50) as well as clinical presentations of each molecualr subtype in Han Chinese population. Methods In all, 169 breast cancer samples (44 from Taiwan and 125 from China) of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (S?rlie 500, Hu 306 and PAM50) were retrieved for molecular subtype prediction. Results For S?rlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD) remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed. Conclusions We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective study with longer survival data is needed.

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