Literature DB >> 23884597

Comparison of efficacy of 95-gene and 21-gene classifier (Oncotype DX) for prediction of recurrence in ER-positive and node-negative breast cancer patients.

Yasuto Naoi1, Kazuki Kishi, Ryo Tsunashima, Kenzo Shimazu, Atsushi Shimomura, Naomi Maruyama, Masafumi Shimoda, Naofumi Kagara, Yosuke Baba, Seung Jin Kim, Shinzaburo Noguchi.   

Abstract

We recently developed a 95-gene classifier (95(GC)) for the prognostic prediction for ER-positive and node-negative breast cancer patients treated with only adjuvant hormonal therapy. The aim of this study was to validate the efficacy of 95(GC) and compare it with that of 21(GC) (Oncotype DX) as well as to evaluate the combination of 95(GC) and 21(GC). DNA microarray data (gene expression) of ER-positive and node-negative breast cancer patients (n = 459) treated with adjuvant hormone therapy alone as well as those of ER-positive breast cancer patients treated with neoadjuvant chemotherapy (n = 359) were classified with 95(GC) and 21(GC) (Recurrence Online at http://www.recurrenceonline.com/ ). 95(GC) classified the 459 patients into low-risk (n = 285; 10 year relapse-free survival: 88.8 %) and high-risk groups (n = 174; 70.6 %) (P = 5.5e-10), and 21(GC) into low-risk group (n = 286; 89.3 %), intermediate-risk (n = 81; 75.7 %), and high-risk (n = 92; 64.7 %) groups (P = 2.9e-10). The combination of 95(GC) and 21(GC) classified them into low-risk (n = 324; 88.9 %) and high-risk (n = 135; 65.0 %) groups (P = 5.9e-14), and also showed that pathological complete response rates were significantly (P = 2.5e-6) higher for the high-risk (17.9 %) than the low-risk group (3.6 %). In addition, we demonstrated that 95(GC) was calculated on a single-sample basis if the reference robust multi-array average workflow was used for normalization. The prognostic prediction capability of 95(GC) appears to be comparable to that of 21(GC). Moreover, their combination seems to result in the identification of more low-risk patients who do not need chemotherapy than either classification alone. The patients in the high-risk group were found to be more chemo-sensitive so that they can benefit more from adjuvant chemotherapy.

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Year:  2013        PMID: 23884597     DOI: 10.1007/s10549-013-2640-9

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


  8 in total

1.  A 95-gene signature stratifies recurrence risk of invasive disease in ER-positive, HER2-negative, node-negative breast cancer with intermediate 21-gene signature recurrence scores.

Authors:  Takeo Fujii; Hiroko Masuda; Yee Chung Cheng; Fei Yang; Aysegul A Sahin; Yasuto Naoi; Yuki Matsunaga; Akshara Raghavendra; Arup Kumar Sinha; Jose Rodrigo Espinosa Fernandez; Anjali James; Keisuke Yamagishi; Tomoko Matsushima; Robert Schuetz; Debu Tripathy; Sachiyo Tada; Rubie S Jackson; Shinzaburo Noguchi; Seigo Nakamura; Jared D Acoba; Naoto T Ueno
Journal:  Breast Cancer Res Treat       Date:  2021-06-15       Impact factor: 4.872

2.  Novel rapid-immunohistochemistry using an alternating current electric field for intraoperative diagnosis of sentinel lymph nodes in breast cancer.

Authors:  Kaori Terata; Hajime Saito; Hiroshi Nanjo; Yuko Hiroshima; Satoru Ito; Kasumi Narita; Yoichi Akagami; Ryuta Nakamura; Hayato Konno; Aki Ito; Satoru Motoyama; Yoshihiro Minamiya
Journal:  Sci Rep       Date:  2017-06-05       Impact factor: 4.379

Review 3.  Decision of Adjuvant Systemic Treatment in HR+ HER2- Early Invasive Breast Cancer: Which Biomarkers Could Help?

Authors:  Marie Alexandre; Aurélie Maran-Gonzalez; Marie Viala; Nelly Firmin; Véronique D'Hondt; Marian Gutowski; Céline Bourgier; William Jacot; Séverine Guiu
Journal:  Cancer Manag Res       Date:  2019-12-11       Impact factor: 3.989

Review 4.  The multigene classifiers 95GC/42GC/155GC for precision medicine in ER-positive HER2-negative early breast cancer.

Authors:  Yasuto Naoi; Ryo Tsunashima; Kenzo Shimazu; Shinzaburo Noguchi
Journal:  Cancer Sci       Date:  2021-02-26       Impact factor: 6.716

5.  Racial differences in predictive value of the 21-gene recurrence score assay: a population-based study using the SEER database.

Authors:  Jiwoong Jung; Ki-Tae Hwang; In Sil Choi; Byoung Hyuck Kim; Sohee Oh; Jongjin Kim; Jeong Hwan Park; Jin Hyun Park; Se Hyun Paek; Sook Young Jeon; Tae-Hoon Yeo
Journal:  Breast Cancer       Date:  2022-05-26       Impact factor: 3.307

6.  The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures.

Authors:  Jessica G Cockburn; Robin M Hallett; Amy E Gillgrass; Kay N Dias; T Whelan; M N Levine; John A Hassell; Anita Bane
Journal:  BMC Cancer       Date:  2016-07-28       Impact factor: 4.430

7.  Endocrine sensitivity of estrogen receptor-positive breast cancer is negatively correlated with aspartate-β-hydroxylase expression.

Authors:  Masafumi Shimoda; Ami Hori; Jack R Wands; Ryo Tsunashima; Yasuto Naoi; Tomohiro Miyake; Tomonori Tanei; Naofumi Kagara; Kenzo Shimazu; Seung Jin Kim; Shinzaburo Noguchi
Journal:  Cancer Sci       Date:  2017-10-21       Impact factor: 6.716

8.  Radiogenomics of magnetic resonance imaging and a new multi-gene classifier for predicting recurrence prognosis in estrogen receptor-positive breast cancer: A preliminary study.

Authors:  Yukiko Tokuda; Masahiro Yanagawa; Kaori Minamitani; Yasuto Naoi; Shinzaburo Noguchi; Noriyuki Tomiyama
Journal:  Medicine (Baltimore)       Date:  2020-04       Impact factor: 1.817

  8 in total

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