Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer

被引:532
作者
Ivshina, Anna V.
George, Joshy
Senko, Oleg
Mow, Benjamin
Putti, Thomas C.
Smeds, Johanna
Lindahl, Thomas
Pawitan, Yudi
Hall, Per
Nordgren, Hans
Wong, John E. L.
Liu, Edison T.
Bergh, Jonas
Kuznetsov, Vladimir A.
Miller, Lance D.
机构
[1] Natl Univ Singapore, Genome Inst Singapore, Singapore 13872, Singapore
[2] Natl Univ Singapore Hosp, Dept Haematol Oncol, Singapore 117548, Singapore
[3] Natl Univ Singapore, Dept Pathol, Singapore 117548, Singapore
[4] Natl Univ Singapore, Dept Med, Singapore 117548, Singapore
[5] Russian Acad Sci, Ctr Comp, Moscow, Russia
[6] Karolinska Hosp & Inst, Radiumhemmet, Dept Pathol & Oncol, Stockholm, Sweden
[7] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
[8] Uppsala Univ, Akad Sjukhuset, Dept Pathol, S-75105 Uppsala, Sweden
关键词
D O I
10.1158/0008-5472.CAN-05-4414
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (W) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression.
引用
收藏
页码:10292 / 10301
页数:10
相关论文
共 52 条
[31]   A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer [J].
Paik, S ;
Shak, S ;
Tang, G ;
Kim, C ;
Baker, J ;
Cronin, M ;
Baehner, FL ;
Walker, MG ;
Watson, D ;
Park, T ;
Hiller, W ;
Fisher, ER ;
Wickerham, DL ;
Bryant, J ;
Wolmark, N .
NEW ENGLAND JOURNAL OF MEDICINE, 2004, 351 (27) :2817-2826
[32]   Gene expression profiling spares early breast cancer patients from adjuvant therapy:: derived and validated in two population-based cohorts [J].
Pawitan, Y ;
Bjöhle, J ;
Amler, L ;
Borg, AL ;
Egyhazi, S ;
Hall, P ;
Han, X ;
Holmberg, L ;
Huang, F ;
Klaar, S ;
Liu, ET ;
Miller, L ;
Nordgren, H ;
Ploner, A ;
Sandelin, K ;
Shaw, PM ;
Smeds, J ;
Skoog, L ;
Wedrén, S ;
Bergh, J .
BREAST CANCER RESEARCH, 2005, 7 (06) :R953-R964
[33]   HISTOLOGICAL GRADING OF BREAST CARCINOMAS - A STUDY OF INTEROBSERVER AGREEMENT [J].
ROBBINS, P ;
PINDER, S ;
DEKLERK, N ;
DAWKINS, H ;
HARVEY, J ;
STERRETT, G ;
ELLIS, I ;
ELSTON, C .
HUMAN PATHOLOGY, 1995, 26 (08) :873-879
[34]  
Roberti NE, 1997, CANCER-AM CANCER SOC, V80, P1708, DOI 10.1002/(SICI)1097-0142(19971101)80:9<1708::AID-CNCR3>3.0.CO
[35]  
2-A
[36]  
Roylance R, 1999, CANCER RES, V59, P1433
[37]  
Rutqvist LE, 1996, J NATL CANCER I, V88, P1543
[38]   THE PROGNOSTIC EFFECT OF HISTOLOGICAL TUMOR GRADE IN NODE-NEGATIVE BREAST-CANCER PATIENTS [J].
SCHUMACHER, M ;
SCHMOOR, C ;
SAUERBREI, W ;
SCHAUER, A ;
UMMENHOFER, L ;
GATZEMEIER, W ;
RAUSCHECKER, H .
BREAST CANCER RESEARCH AND TREATMENT, 1993, 25 (03) :235-245
[39]   Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications [J].
Sorlie, 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 ;
Lonning, PE ;
Borresen-Dale, AL .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2001, 98 (19) :10869-10874
[40]   Breast cancer classification and prognosis based on gene expression profiles from a population-based study [J].
Sotiriou, C ;
Neo, SY ;
McShane, LM ;
Korn, EL ;
Long, PM ;
Jazaeri, A ;
Martiat, P ;
Fox, SB ;
Harris, AL ;
Liu, ET .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (18) :10393-10398