Literature DB >> 21833625

First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations.

Takayuki Iwamoto1, Ju-Seog Lee, Giampaolo Bianchini, Rebekah E Hubbard, Elliana Young, Junji Matsuoka, Sang Bae Kim, W Fraser Symmans, Gabriel N Hortobagyi, Lajos Pusztai.   

Abstract

The aims of this study were to compare the performance of six different genomic prognostic markers to predict long-term survival and chemotherapy response on the same patient cohort and assess if clinicopathological variables carry independent prognostic and predictive values. We examined seven clinical variables and six previously described prognostic signatures on 228 tumors from patients who received homogeneous preoperative chemotherapy and had long-term follow-up information for survival. We used the area under the receiver operator characteristic curve (AUC) to compare predictors and also performed univariate and multivariate analyses including the genomic and clinical variables and plotted Kaplan-Meir survival curves. All genomic prognostic markers had statistically similar AUCs and sensitivity to predict 5-year progression-free survival (PFS, sensitivities ranged from 0.591 to 0.773, and AUCs: 0.599-0.673), overall survival (OS, sensitivities: 0.590-0.769, AUCs: 0.596-0.684) and pathologic complete response (pCR, sensitivities: 0.596-0.851, AUCs: 0.614-0.805). In multivariate analysis, the genomic markers were not independent from one another; however, estrogen receptor (Odds Ratio [OR] 7.63, P < 0.001) and HER2 status (OR: 0.37, P = 0.021) showed significant independent predictive values for pCR. Nodal status remained an independent prognostic, but not predictive, variable (OR for PFS: 2.77, P = 0.021, OR for OS: 3.62, P = 0.01). There was moderate to good agreement between different prediction results in pair-wise comparisons. First-generation prognostic-gene signatures predict both chemotherapy response and long-term survival. When multiple predictors are applied to the same case discordant risk prediction frequently occurs.

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Year:  2011        PMID: 21833625     DOI: 10.1007/s10549-011-1706-9

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  7 in total

1.  Toward individualized breast cancer therapy: translating biological concepts to the bedside.

Authors:  Gabriel N Hortobagyi
Journal:  Oncologist       Date:  2012-04-02

2.  Molecular subtyping predicts pathologic tumor response in early-stage breast cancer treated with neoadjuvant docetaxel plus capecitabine with or without trastuzumab chemotherapy.

Authors:  Soley Bayraktar; Melanie Royce; Lisette Stork-Sloots; Femke de Snoo; Stefan Glück
Journal:  Med Oncol       Date:  2014-09-04       Impact factor: 3.064

3.  Agreement in risk prediction between the 21-gene recurrence score assay (Oncotype DX®) and the PAM50 breast cancer intrinsic Classifier™ in early-stage estrogen receptor-positive breast cancer.

Authors:  Catherine M Kelly; Philip S Bernard; Savitri Krishnamurthy; Bailiang Wang; Mark T W Ebbert; Roy R L Bastien; Kenneth M Boucher; Elliana Young; Takayuki Iwamoto; Lajos Pusztai
Journal:  Oncologist       Date:  2012-03-14

4.  Distinct genes related to drug response identified in ER positive and ER negative breast cancer cell lines.

Authors:  Kui Shen; Shara D Rice; David A Gingrich; Dakun Wang; Zhibao Mi; Chunqiao Tian; Zhenyu Ding; Stacey L Brower; Paul R Ervin; Michael J Gabrin; George Tseng; Nan Song
Journal:  PLoS One       Date:  2012-07-16       Impact factor: 3.240

5.  Association between tumor 18F-fluorodeoxyglucose metabolism and survival in women with estrogen receptor-positive, HER2-negative breast cancer.

Authors:  Sun Young Chae; Seol Hoon Park; Hyo Sang Lee; Jin-Hee Ahn; Sung-Bae Kim; Kyung Hae Jung; Jeong Eun Kim; Sei Hyun Ahn; Byung Ho Son; Jong Won Lee; Beom Seok Ko; Hee Jeong Kim; Gyungyub Gong; Jungsu S Oh; Seo Young Park; Dae Hyuk Moon
Journal:  Sci Rep       Date:  2022-05-12       Impact factor: 4.996

Review 6.  Multigene prognostic tests in breast cancer: past, present, future.

Authors:  Balázs Győrffy; Christos Hatzis; Tara Sanft; Erin Hofstatter; Bilge Aktas; Lajos Pusztai
Journal:  Breast Cancer Res       Date:  2015-01-27       Impact factor: 6.466

Review 7.  Towards decision-making using individualized risk estimates for personalized medicine: A systematic review of genomic classifiers of solid tumors.

Authors:  Daniel M Trifiletti; Vanessa N Sturz; Timothy N Showalter; Jennifer M Lobo
Journal:  PLoS One       Date:  2017-05-09       Impact factor: 3.240

  7 in total

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