Literature DB >> 22035021

Measuring β-tubulin III, Bcl-2, and ERCC1 improves pathological complete remission predictive accuracy in breast cancer.

Xiaosong Chen1, Jiayi Wu, Hongfen Lu, Ou Huang, Kunwei Shen.   

Abstract

Weekly PCb (paclitaxel + carboplatin) in neoadjuvant chemotherapy (NCT) for breast cancer has a high pathological complete remission (pCR) rate. The present study was to identify pCR predictive biomarkers and to test whether integrating candidate molecular biomarkers can improve the pCR predictive accuracy. Ninety-one breast cancer patients treated with weekly PCb NCT were retrospectively analyzed. Eleven candidate molecular biomarkers (Tau, β-tubulin III, PTEN, MAP4, thioredoxin, multidrug resistance-1, Ki67, p53, Bcl-2, BAX, and ERCC1) were detected by immunohistochemistry in pre-NCT core needle biopsy specimens. We analyzed the relationship between these biomarkers and pCR. Univariate analysis showed that estrogen receptor, progesterone receptor, molecular classification (clinicopathological markers), and Tau, β-tubulin III, p53, Bcl-2, ERCC1 (candidate molecular biomarkers) expression were associated with pCR rate; however, multivariate analysis revealed that only β-tubulin III, Bcl-2, and ERCC1 were independent pCR predictive factors. Patients with β-tubulin III negative, Bcl-2 negative, or ERCC1 negative tumors were associated with higher pCR rate, with OR (odds ratios) 6.03 (95% confidence interval [CI], 1.44-25.24, P = 0.014), 7.54 (95% CI, 1.52-37.40, P = 0.013), and 4.09 (95% CI, 1.17-14.30, P = 0.028), respectively. To compare different logistic regression models, built with different combinations of these variables, we found that the model integrating routine clinical and pathological variables, as well as the β-tubulin III, Bcl-2, ERCC1 molecular biomarkers had the highest pCR predictive power. The area under the ROC curve for this model was 0.900 (95% CI, 0.831-0.968), indicating that it deserves further investigation. Trial name: Weekly Paclitaxel Plus Carboplatin in Preoperative Treatment of Breast Cancer.
© 2011 Japanese Cancer Association.

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Year:  2011        PMID: 22035021     DOI: 10.1111/j.1349-7006.2011.02135.x

Source DB:  PubMed          Journal:  Cancer Sci        ISSN: 1347-9032            Impact factor:   6.716


  15 in total

1.  Gene expression and pathologic response to neoadjuvant chemotherapy in breast cancer.

Authors:  Agnieszka Kolacinska; Wojciech Fendler; Janusz Szemraj; Bozena Szymanska; Ewa Borowska-Garganisz; Magdalena Nowik; Justyna Chalubinska; Robert Kubiak; Zofia Pawlowska; Maria Blasinska-Morawiec; Piotr Potemski; Arkadiusz Jeziorski; Zbigniew Morawiec
Journal:  Mol Biol Rep       Date:  2012-02-09       Impact factor: 2.316

2.  β3-tubulin is a good predictor of sensitivity to taxane-based neoadjuvant chemotherapy in primary breast cancer.

Authors:  Youqun Xiang; Yinlong Yang; Guilong Guo; Xiaoqu Hu; Huxiang Zhang; Xiaohua Zhang; Yifei Pan
Journal:  Clin Exp Med       Date:  2015-06-19       Impact factor: 3.984

3.  A five-variable signature predicts radioresistance and prognosis in nasopharyngeal carcinoma patients receiving radical radiotherapy.

Authors:  Hong-Mei Yi; Hong Yi; Jin-Feng Zhu; Ta Xiao; Shan-Shan Lu; Yong-Jun Guan; Zhi-Qiang Xiao
Journal:  Tumour Biol       Date:  2015-09-27

4.  ERCC1 and telomere status in breast tumours treated with neoadjuvant chemotherapy and their association with patient prognosis.

Authors:  Mathilde Gay-Bellile; Pierre Romero; Anne Cayre; Lauren Véronèse; Maud Privat; Shalini Singh; Patricia Combes; Fabrice Kwiatkowski; Catherine Abrial; Yves-Jean Bignon; Philippe Vago; Frédérique Penault-Llorca; Andreï Tchirkov
Journal:  J Pathol Clin Res       Date:  2016-07-13

5.  Class III β-Tubulin in Colorectal Cancer: Tissue Distribution and Clinical Analysis of Chinese Patients.

Authors:  Xiaoli Zhao; Changli Yue; Jiamin Chen; Cheng Tian; Dongmei Yang; Li Xing; Honggang Liu; Yulan Jin
Journal:  Med Sci Monit       Date:  2016-10-23

6.  Identification of potential biomarkers from microarray experiments using multiple criteria optimization.

Authors:  Matilde L Sánchez-Peña; Clara E Isaza; Jaileene Pérez-Morales; Cristina Rodríguez-Padilla; José M Castro; Mauricio Cabrera-Ríos
Journal:  Cancer Med       Date:  2013-02-27       Impact factor: 4.452

7.  An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer.

Authors:  Enery Lorenzo; Katia Camacho-Caceres; Alexander J Ropelewski; Juan Rosas; Michael Ortiz-Mojer; Lynn Perez-Marty; Juan Irizarry; Valerie Gonzalez; Jesús A Rodríguez; Mauricio Cabrera-Rios; Clara Isaza
Journal:  Microarrays (Basel)       Date:  2015-06

Review 8.  Bcl-2 expression predicts sensitivity to chemotherapy in breast cancer: a systematic review and meta-analysis.

Authors:  Dong Yang; Min-Bin Chen; Li-Qiang Wang; Lan Yang; Chao-Ying Liu; Pei-Hua Lu
Journal:  J Exp Clin Cancer Res       Date:  2013-12-27

9.  Microtubule-Associated Protein Tau, α-Tubulin and βIII-Tubulin Expression in Breast Cancer.

Authors:  Soyoung Im; Changyoung Yoo; Ji-Han Jung; Ye-Won Jeon; Young Jin Suh; Youn Soo Lee; Hyun Joo Choi
Journal:  Korean J Pathol       Date:  2013-12-24

10.  High levels of class III β-tubulin expression are associated with aggressive tumor features in breast cancer.

Authors:  Patrick Lebok; Melike Öztürk; Uwe Heilenkötter; Fritz Jaenicke; Volkmar Müller; Peter Paluchowski; Stefan Geist; Christian Wilke; Eicke Burandt; Annette Lebeau; Waldemar Wilczak; Till Krech; Ronald Simon; Guido Sauter; Alexander Quaas
Journal:  Oncol Lett       Date:  2016-02-09       Impact factor: 2.967

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