PURPOSE: Currently, there are no definite biomarkers of triple-negative breast cancer. The study aims to identify the metastasis-associated proteins of triple-negative breast tumors. EXPERIMENTAL DESIGN: A murine metastatic breast cancer model has been established by using TA2 mice. Parallel proteomic analyses were done on a murine metastatic breast cancer model and its primary breast cancer using two-dimensional gel electrophoresis. The differentially expressed proteins were detected in TA2 mice developing spontaneous breast cancer and lung metastasis. Furthermore, their expression were detected in human breast cancer with or without metastasis, and their prediction values were assessed in a second set of samples. RESULTS: Nineteen of 36 differentially expressed proteins were identified by peptide mass fingerprinting using matrix-assisted laser-desorption ionization-time of flight-mass spectrometry. These proteins were also validated in mouse tumor tissues by immunohistochemical staining. Actin, 14-3-3, vimentin, HSP70, CK18, and moesin were up-regulated in the metastatic tumors, whereas HSP90 and tubulin were absent or down-regulated. Furthermore, 61 patients with triple-negative breast cancer and 39 patients with estrogen receptor-positive/progesterone receptor-positive breast cancer were selected for exploring the clinical relevance of these identified proteins to human breast cancer metastasis. Expression of 14-3-3 and HSP70 was significantly correlated with metastasis of human triple-negative breast cancer. Moreover, the validation study in the second set confirmed that 14-3-3, HSP70, and their combination had high sensitivities and specificities in predicting metastatic potential of triple-negative breast cancer. CONCLUSIONS: These tumor metastasis-associated proteins validated may be useful as biomarkers and targets for diagnosis and treatment of human triple-negative breast cancer.
PURPOSE: Currently, there are no definite biomarkers of triple-negative breast cancer. The study aims to identify the metastasis-associated proteins of triple-negative breast tumors. EXPERIMENTAL DESIGN: A murine metastatic breast cancer model has been established by using TA2mice. Parallel proteomic analyses were done on a murine metastatic breast cancer model and its primary breast cancer using two-dimensional gel electrophoresis. The differentially expressed proteins were detected in TA2mice developing spontaneous breast cancer and lung metastasis. Furthermore, their expression were detected in humanbreast cancer with or without metastasis, and their prediction values were assessed in a second set of samples. RESULTS: Nineteen of 36 differentially expressed proteins were identified by peptide mass fingerprinting using matrix-assisted laser-desorption ionization-time of flight-mass spectrometry. These proteins were also validated in mousetumor tissues by immunohistochemical staining. Actin, 14-3-3, vimentin, HSP70, CK18, and moesin were up-regulated in the metastatic tumors, whereas HSP90 and tubulin were absent or down-regulated. Furthermore, 61 patients with triple-negative breast cancer and 39 patients with estrogen receptor-positive/progesterone receptor-positive breast cancer were selected for exploring the clinical relevance of these identified proteins to humanbreast cancer metastasis. Expression of 14-3-3 and HSP70 was significantly correlated with metastasis of human triple-negative breast cancer. Moreover, the validation study in the second set confirmed that 14-3-3, HSP70, and their combination had high sensitivities and specificities in predicting metastatic potential of triple-negative breast cancer. CONCLUSIONS: These tumor metastasis-associated proteins validated may be useful as biomarkers and targets for diagnosis and treatment of human triple-negative breast cancer.
Authors: Marc Warmoes; Janneke E Jaspers; Thang V Pham; Sander R Piersma; Gideon Oudgenoeg; Maarten P G Massink; Quinten Waisfisz; Sven Rottenberg; Epie Boven; Jos Jonkers; Connie R Jimenez Journal: Mol Cell Proteomics Date: 2012-02-24 Impact factor: 5.911
Authors: Sijana H Dzinic; M Margarida Bernardo; Xiaohua Li; Rodrigo Fernandez-Valdivia; Ye-Shih Ho; Qing-Sheng Mi; Sudeshna Bandyopadhyay; Fulvio Lonardo; Semir Vranic; Daniel S M Oliveira; R Daniel Bonfil; Gregory Dyson; Kang Chen; Almasa Omerovic; Xiujie Sheng; Xiang Han; Dinghong Wu; Xinling Bi; Dzenana Cabaravdic; Una Jakupovic; Marian Wahba; Aaron Pang; Deanna Harajli; Wael A Sakr; Shijie Sheng Journal: Cancer Res Date: 2016-12-06 Impact factor: 12.701
Authors: Mercedes Zurita; Pedro C Lara; Rosario del Moral; Blanca Torres; José Luis Linares-Fernández; Sandra Ríos Arrabal; Joaquina Martínez-Galán; Francisco Javier Oliver; José Mariano Ruiz de Almodóvar Journal: BMC Cancer Date: 2010-05-20 Impact factor: 4.430
Authors: Flora Zagouri; Theodoros N Sergentanis; Afrodite Nonni; Christos A Papadimitriou; Nikolaos V Michalopoulos; Philip Domeyer; George Theodoropoulos; Andreas Lazaris; Effstratios Patsouris; Eleni Zogafos; Anastazia Pazaiti; George C Zografos Journal: BMC Cancer Date: 2010-07-05 Impact factor: 4.430
Authors: Sara Sannino; Megan E Yates; Mark E Schurdak; Steffi Oesterreich; Adrian V Lee; Peter Wipf; Jeffrey L Brodsky Journal: Elife Date: 2021-06-28 Impact factor: 8.140