Steven A Buechler1, Yesim Gökmen-Polar2, Sunil S Badve3. 1. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, United States. 2. Department of Pathology, Indiana University School of Medicine, Indianapolis, IN, United States. 3. Department of Pathology, Indiana University School of Medicine, Indianapolis, IN, United States; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States; Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, United States. Electronic address: sbadve@iupui.edu.
Abstract
BACKGROUND: EarlyR gene signature uses ESPL1, SPAG5, MKI67, PLK1 and PGR to classify ER+ breast cancer (ER+ BC) into EarlyR-Low, EarlyR-Int, and EarlyR-High risk strata and is prognostic in patients treated with adjuvant chemotherapy. The ability of EarlyR to predict pathological complete response (pCR) and long-term survival following neoadjuvant chemotherapy (NACT) is evaluated herein. MATERIALS: The ability of EarlyR gene signature to predict pCR was assessed in publicly available Affymetrix microarray datasets (Cohort A; n = 659; 74 pCR events) derived from NACT-treated ER+ BC patients. Distant relapse-free survival (DRFS) results were analyzed in patients treated with NACT and adjuvant hormone therapy (AHT) (n = 281) and compared with patients treated with AHT alone (n = 455) (Cohort B; n = 736; 142 events). RESULTS: In cohort A, EarlyR was a significant predictor of pCR (p = 5.8 × 10-11) (EarlyR-Low, n = 400, pCR = 40, 5%; EarlyR-Int, n = 69, pCR = 7, 15% and EarlyR-High, n = 190, pCR = 47, 24%). In EarlyR-Low of Cohort B, the 5-year DRFS was not significantly (p = 0.55) different between NACT + AHT [0.81 (95%CI 0.73-0.90)] and AHT-only [0.85 (95%CI 0.81-0.90)]. In contrast, in EarlyR-High, the 5-year DRFS was higher (p = 0.019) in NACT + AHT [0.81 (95%CI 0.70-0.93)] as compared to AHT-only [0.60 (95%CI 0.51-0.71)]. CONCLUSIONS: High EarlyR is strongly associated with pCR in patients treated with neoadjuvant chemotherapy. EarlyR also predicts poor DRFS outcomes for patients in EarlyR-High not receiving NACT, and improved survival in NACT-treated EarlyR-High patients. EarlyR is not only a prognostic assay but also a predictive assay that identifies patients, who are also likely to respond to chemotherapy.
BACKGROUND: EarlyR gene signature uses ESPL1, SPAG5, MKI67, PLK1 and PGR to classify ER+ breast cancer (ER+ BC) into EarlyR-Low, EarlyR-Int, and EarlyR-High risk strata and is prognostic in patients treated with adjuvant chemotherapy. The ability of EarlyR to predict pathological complete response (pCR) and long-term survival following neoadjuvant chemotherapy (NACT) is evaluated herein. MATERIALS: The ability of EarlyR gene signature to predict pCR was assessed in publicly available Affymetrix microarray datasets (Cohort A; n = 659; 74 pCR events) derived from NACT-treated ER+ BC patients. Distant relapse-free survival (DRFS) results were analyzed in patients treated with NACT and adjuvant hormone therapy (AHT) (n = 281) and compared with patients treated with AHT alone (n = 455) (Cohort B; n = 736; 142 events). RESULTS: In cohort A, EarlyR was a significant predictor of pCR (p = 5.8 × 10-11) (EarlyR-Low, n = 400, pCR = 40, 5%; EarlyR-Int, n = 69, pCR = 7, 15% and EarlyR-High, n = 190, pCR = 47, 24%). In EarlyR-Low of Cohort B, the 5-year DRFS was not significantly (p = 0.55) different between NACT + AHT [0.81 (95%CI 0.73-0.90)] and AHT-only [0.85 (95%CI 0.81-0.90)]. In contrast, in EarlyR-High, the 5-year DRFS was higher (p = 0.019) in NACT + AHT [0.81 (95%CI 0.70-0.93)] as compared to AHT-only [0.60 (95%CI 0.51-0.71)]. CONCLUSIONS: High EarlyR is strongly associated with pCR in patients treated with neoadjuvant chemotherapy. EarlyR also predicts poor DRFS outcomes for patients in EarlyR-High not receiving NACT, and improved survival in NACT-treated EarlyR-High patients. EarlyR is not only a prognostic assay but also a predictive assay that identifies patients, who are also likely to respond to chemotherapy.
Authors: Rohit Bhargava; Nicole N Esposito; Siobhan M OʹConnor; Zaibo Li; Bradley M Turner; Ioana Moisini; Aditi Ranade; Ronald P Harris; Dylan V Miller; Xiaoxian Li; Harrison Moosavi; Beth Z Clark; Adam M Brufsky; David J Dabbs Journal: Mod Pathol Date: 2020-07-13 Impact factor: 7.842
Authors: Na Re Ko; Sang Ju Lee; Arun Pandian Chandrasekaran; Apoorvi Tyagi; Suresh Ramakrishna; Seog-Young Kim; Do Won Kim; Chan-Gi Pack; Seung Jun Oh Journal: Int J Mol Sci Date: 2021-10-19 Impact factor: 5.923
Authors: Steven A Buechler; Kathryn P Gray; Yesim Gökmen-Polar; Scooter Willis; Beat Thürlimann; Rosita Kammler; Giuseppe Viale; Brian Leyland-Jones; Sunil S Badve; Meredith M Regan Journal: JNCI Cancer Spectr Date: 2019-08-16