Abstract P5-01-02: Quantitative assessment of tumor response to neoadjuvant chemotherapy in women with locoregional invasive breast cancer using Tc99m sestamibi molecular breast imaging - preliminary results

Author(s):  
GM Rauch ◽  
BE Adrada ◽  
C Kappadath ◽  
RP Candelaria ◽  
ML Huang ◽  
...  
2019 ◽  
Vol 213 (4) ◽  
pp. 932-943 ◽  
Author(s):  
Katie N. Hunt ◽  
Amy Lynn Conners ◽  
Matthew P. Goetz ◽  
Michael K. O'Connor ◽  
Vera Suman ◽  
...  

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Juanjuan Gu ◽  
Eric C. Polley ◽  
Max Denis ◽  
Jodi M. Carter ◽  
Sandhya Pruthi ◽  
...  

Abstract Background Early prediction of tumor response to neoadjuvant chemotherapy (NACT) is crucial for optimal treatment and improved outcome in breast cancer patients. The purpose of this study is to investigate the role of shear wave elastography (SWE) for early assessment of response to NACT in patients with invasive breast cancer. Methods In a prospective study, 62 patients with biopsy-proven invasive breast cancer were enrolled. Three SWE studies were conducted on each patient: before, at mid-course, and after NACT but before surgery. A new parameter, mass characteristic frequency (fmass), along with SWE measurements and mass size was obtained from each SWE study visit. The clinical biomarkers were acquired from the pre-NACT core-needle biopsy. The efficacy of different models, generated with the leave-one-out cross-validation, in predicting response to NACT was shown by the area under the receiver operating characteristic curve and the corresponding sensitivity and specificity. Results A significant difference was found for SWE parameters measured before, at mid-course, and after NACT between the responders and non-responders. The combination of Emean2 and mass size (s2) gave an AUC of 0.75 (0.95 CI 0.62–0.88). For the ER+ tumors, the combination of Emean_ratio1, s1, and Ki-67 index gave an improved AUC of 0.84 (0.95 CI 0.65–0.96). For responders, fmass was significantly higher during the third visit. Conclusions Our study findings highlight the value of SWE estimation in the mid-course of NACT for the early prediction of treatment response. For ER+ tumors, the addition of Ki-67improves the predictive power of SWE. Moreover, fmass is presented as a new marker in predicting the endpoint of NACT in responders.


2018 ◽  
Vol 169 (3) ◽  
pp. 513-522 ◽  
Author(s):  
Angela Collarino ◽  
Renato A. Valdés Olmos ◽  
Lotta G. A. J. van Berkel ◽  
Peter A. Neijenhuis ◽  
Lidy M. H. Wijers ◽  
...  

2012 ◽  
Vol 136 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Esther H. Lips ◽  
◽  
Rita A. Mukhtar ◽  
Christina Yau ◽  
Jorma J. de Ronde ◽  
...  

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 669-669
Author(s):  
D. Shen ◽  
J. He ◽  
J. Gornbein ◽  
Z. Chen ◽  
K. F. Faull ◽  
...  

669 Background: Neoadjuvant chemotherapy provides an excellent opportunity for objective assessment of treatment-induced tumor response and for studying biomarkers characteristic of therapy-induced tumor responses. Methods: Proteomic analysis of T3/T4 breast cancer was performed in patients with locally advanced breast cancer in a phase II clinical trial. The breast cancer specimen was obtained before and after four cycles of Taxotere/Carboplatin/±Herceptin treatment. Two proteomic approaches, SELDI mass spectrometry and Clontech Ab Microarray 500, were used to screen for protein biomarkers that predict response of breast cancer to chemotherapy. Results: Five tumors with pathologically complete response (pCR) and 29 tumors with various amounts of residual tumors (Non-pCR) were analyzed by SELDI-TOF using the NP 20 chip. The normalized mass signals were compared between pCR vs Non-pCR at each aligned location by Wilcoxon rank sum test. Statistically significant differences were found at 22 m/z locations using a liberal p <0.20 criterion. The best univariate predictor occurred at m/z 14960 (p=0.004), which correctly classified 5/5 pCR spectra (100%) and 24/29 Non-pCR spectra (83%). A multivariate classification tree developed using m/z 14960 and m/z 12138 intensities correctly classified all 34 spectra. Ab microarray analysis was performed on five pCR tumors and in five tumors with the largest residual cancer. The Internal Normalization Ratio (INR) was calculated and used to compare the difference of protein expression between the two groups. Eight differentially expressed protein biomarkers were selected with the criteria of a statistically significant (Student t, p<0.05) expression change of <0.77 or >1.3 fold. Three proteins (Tat-SF1, PYK2 and PTP1B) were higher, and five (E2F2, IL1b, FEN1, CDC37 and ACM1) were lower in tumors with pCR. The unsupervised hierarchical clustering of the 10 samples by these eight proteins completely separated the pCR tumors from the poor responders. Conclusions: Our study suggests that bothSELDImass spectrometry and antibody microarray may be used to predict the tumor response to neoadjuvant chemotherapy. Proteomic analysis may be useful in developing tailored chemotherapy for breast cancer. [Table: see text]


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