Literature DB >> 35241543

Stratification of Prognosis by Biological Features Following Neoadjuvant Chemotherapy in Luminal Breast Cancer.

Shinya Yamamoto1,2, Takashi Chishima3, Yukako Shibata1, Shiori Inoue1, Fumi Harada1, Hideki Takeuchi1, Akimitsu Yamada4, Kazutaka Narui2, Itaru Endo4.   

Abstract

BACKGROUND/AIM: There are few models predicting breast cancer prognosis among patients receiving neoadjuvant chemotherapy (NAC) for estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative (luminal) breast cancer. We examined whether biological features (BFs) of residual tumors are prognostic factors following NAC. PATIENTS AND METHODS: We enrolled patients with remnant tumors following NAC for luminal breast cancer and evaluated clinical stage, pathological stage, BFs prior to NAC, and BFs following NAC as prognostic factors. BFs were divided into high and low risk using the previously reported YR-IHC4 model calculated according to ER, progesterone receptor (PgR), HER2, and the proliferation marker Ki-67.
RESULTS: A total of 57 patients were enrolled in the current study. We observed a statistically significant difference in relapse-free survival (RFS) between the BF risk categories via YR-IHC4 predictions following NAC (p=0.044). The 5-year RFS rates of the BF low- and high-risk groups following NAC were 84.2% and 52.5%, respectively.
CONCLUSION: BFs of residual tumors following NAC may be important prognostic factors in luminal breast cancer. Copyright
© 2022, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Entities:  

Keywords:  Breast cancer; biological features; neoadjuvant chemotherapy; prognostic factors

Mesh:

Substances:

Year:  2022        PMID: 35241543      PMCID: PMC8931917          DOI: 10.21873/invivo.12774

Source DB:  PubMed          Journal:  In Vivo        ISSN: 0258-851X            Impact factor:   2.155


  23 in total

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Journal:  J Clin Oncol       Date:  2006-05-23       Impact factor: 44.544

2.  Validation of a novel staging system for disease-specific survival in patients with breast cancer treated with neoadjuvant chemotherapy.

Authors:  Elizabeth A Mittendorf; Jacqueline S Jeruss; Susan L Tucker; Aparna Kolli; Lisa A Newman; Ana M Gonzalez-Angulo; Thomas A Buchholz; Aysegul A Sahin; Janice N Cormier; Aman U Buzdar; Gabriel N Hortobagyi; Kelly K Hunt
Journal:  J Clin Oncol       Date:  2011-04-11       Impact factor: 44.544

3.  Intrinsic breast tumor subtypes, race, and long-term survival in the Carolina Breast Cancer Study.

Authors:  Katie M O'Brien; Stephen R Cole; Chiu-Kit Tse; Charles M Perou; Lisa A Carey; William D Foulkes; Lynn G Dressler; Joseph Geradts; Robert C Millikan
Journal:  Clin Cancer Res       Date:  2010-12-15       Impact factor: 12.531

4.  Neo-Bioscore in Guiding Post-surgical Therapy in Patients With Triple-negative Breast Cancer Who Received Neoadjuvant Chemotherapy.

Authors:  Yoriko Hasegawa; Nobuaki Matsubara; Takahiro Kogawa; Yoichi Naito; Kenichi Harano; Ako Hosono; Tatsuya Onishi; Takashi Hojo; Mototsugu Shimokawa; Toru Mukohara
Journal:  In Vivo       Date:  2021 Mar-Apr       Impact factor: 2.155

5.  Adjuvant Capecitabine for Breast Cancer after Preoperative Chemotherapy.

Authors:  Norikazu Masuda; Soo-Jung Lee; Shoichiro Ohtani; Young-Hyuck Im; Eun-Sook Lee; Isao Yokota; Katsumasa Kuroi; Seock-Ah Im; Byeong-Woo Park; Sung-Bae Kim; Yasuhiro Yanagita; Shinji Ohno; Shintaro Takao; Kenjiro Aogi; Hiroji Iwata; Joon Jeong; Aeree Kim; Kyong-Hwa Park; Hironobu Sasano; Yasuo Ohashi; Masakazu Toi
Journal:  N Engl J Med       Date:  2017-06-01       Impact factor: 91.245

6.  Racial Differences in PAM50 Subtypes in the Carolina Breast Cancer Study.

Authors:  Melissa A Troester; Xuezheng Sun; Emma H Allott; Joseph Geradts; Stephanie M Cohen; Chiu-Kit Tse; Erin L Kirk; Leigh B Thorne; Michelle Mathews; Yan Li; Zhiyuan Hu; Whitney R Robinson; Katherine A Hoadley; Olufunmilayo I Olopade; Katherine E Reeder-Hayes; H Shelton Earp; Andrew F Olshan; Lisa A Carey; Charles M Perou
Journal:  J Natl Cancer Inst       Date:  2018-02-01       Impact factor: 13.506

7.  A risk score to predict disease-free survival in patients not achieving a pathological complete remission after preoperative chemotherapy for breast cancer.

Authors:  M Colleoni; V Bagnardi; N Rotmensz; S Dellapasqua; G Viale; G Pruneri; P Veronesi; R Torrisi; A Luini; M Intra; V Galimberti; E Montagna; A Goldhirsch
Journal:  Ann Oncol       Date:  2009-02-13       Impact factor: 32.976

Review 8.  Clinical use of the Oncotype DX genomic test to guide treatment decisions for patients with invasive breast cancer.

Authors:  Terri P McVeigh; Michael J Kerin
Journal:  Breast Cancer (Dove Med Press)       Date:  2017-05-29

9.  Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis.

Authors:  Molly E Klein; David J Dabbs; Yongli Shuai; Adam M Brufsky; Rachel Jankowitz; Shannon L Puhalla; Rohit Bhargava
Journal:  Mod Pathol       Date:  2013-03-15       Impact factor: 7.842

10.  Abemaciclib Combined With Endocrine Therapy for the Adjuvant Treatment of HR+, HER2-, Node-Positive, High-Risk, Early Breast Cancer (monarchE).

Authors:  Stephen R D Johnston; Nadia Harbeck; Roberto Hegg; Masakazu Toi; Miguel Martin; Zhi Min Shao; Qing Yuan Zhang; Jorge Luis Martinez Rodriguez; Mario Campone; Erika Hamilton; Joohyuk Sohn; Valentina Guarneri; Morihito Okada; Frances Boyle; Patrick Neven; Javier Cortés; Jens Huober; Andrew Wardley; Sara M Tolaney; Irfan Cicin; Ian C Smith; Martin Frenzel; Desirée Headley; Ran Wei; Belen San Antonio; Maarten Hulstijn; Joanne Cox; Joyce O'Shaughnessy; Priya Rastogi
Journal:  J Clin Oncol       Date:  2020-09-20       Impact factor: 50.717

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