Literature DB >> 19593632

Presenting features of breast cancer differ by molecular subtype.

Lisa Wiechmann1, Michelle Sampson, Michelle Stempel, Lindsay M Jacks, Sujata M Patil, Tari King, Monica Morrow.   

Abstract

BACKGROUND: Gene expression profiling of breast cancers identifies distinct molecular subtypes that affect prognosis. Our goal was to determine whether presenting features of tumors differ among molecular subtypes.
METHODS: Subtypes were classified by immunohistochemical surrogates as luminal A (estrogen receptor [ER] and/or progesterone receptor [PR] positive, HER-2-), luminal B (ER and/or PR+, HER-2+), HER-2 (ER and PR-, HER-2+), or basal (ER, PR, HER-2-). Data were obtained from an established, registered database of patients with invasive breast cancer treated at our institution between January 1998 and June 2007. A total of 6,072 tumors were classifiable into molecular subtypes. The chi(2) test, analysis of variance, and multivariate logistic regression analysis were used to determine associations between subtype and clinicopathologic variables.
RESULTS: The distribution of subtypes was luminal A, 71%; luminal B, 8%; HER-2, 6%; and basal, 15%. Marked differences in age, tumor size, extent of lymph node involvement, nuclear grade, multicentric/multifocal disease, lymphovascular invasion (LVI), and extensive intraductal component were observed among subtypes. When compared with luminal A tumors, those overexpressing HER-2 (luminal B, HER-2) were significantly more likely to manifest nodal involvement, multifocal, extensive intraductal component, and LVI (P < 0.0001). On multivariate analysis, after controlling for patient age, tumor size, LVI, and nuclear grade, HER-2 subtype tumors were 2.0 times more likely to have four or more metastatic lymph nodes (P < 0.0001) and 1.6 times more likely to have multifocal disease (P < 0.0001) compared with patients with luminal A.
CONCLUSIONS: Tumor presentation varies among molecular subtypes; this information may be useful in selecting local therapy. Neoadjuvant therapy and lymph nodes evaluation before surgery or neoadjuvant therapy are likely to be beneficial in HER-2-overexpressing tumors.

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Year:  2009        PMID: 19593632     DOI: 10.1245/s10434-009-0606-2

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  49 in total

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4.  Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study.

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7.  Role of MRI in the staging of breast cancer patients: does histological type and molecular subtype matter?

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8.  Lobular Histology Does Not Predict the Need for Axillary Dissection Among ACOSOG Z0011-Eligible Breast Cancers.

Authors:  Anita Mamtani; Emily C Zabor; Michelle Stempel; Monica Morrow
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9.  Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.

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Journal:  J Digit Imaging       Date:  2019-04       Impact factor: 4.056

10.  Breast cancer subtypes and survival in chinese women with operable primary breast cancer.

Authors:  Zhao-Sheng Li; Lu Yao; Yi-Qiang Liu; Tao Ouyang; Jin-Feng Li; Tian-Feng Wang; Zhao-Qing Fan; Tie Fan; Ben-Yao Lin; Yun-Tao Xie
Journal:  Chin J Cancer Res       Date:  2011-06       Impact factor: 5.087

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