BACKGROUND: CK2α is a signalling molecule that participates in major events in solid tumour progression. The aim of this study was to evaluate the prognostic significance of the immunohistochemical expression of CK2α in breast carcinomas. METHODS: Quantitative measurements of immunohistochemical expression of 33 biomarkers using high-throughput densitometry, assessed on digitised microscopic tissue micro-array images were correlated with clinical outcome in 1000 breast carcinomas using univariate and multivariate analyses. RESULTS: In univariate analysis, CK2α was a significant prognostic indicator (p<0.001). Moreover, a multivariable model allowed the selection of the best combination of the 33 biomarkers to predict patients' outcome through logistic regression. A nine-marker signature highly predictive of metastatic risk, associating SHARP-2, STAT1, eIF4E, pmapKAPk-2, pAKT, caveolin, VEGF, FGF-1 and CK2α permitted to classify well 82.32% of patients (specificity 81.59%, sensitivity 92.55%, area under ROC curve 0.939). Importantly, in a node negative subset of patients an even more (86%) clinically relevant association of eleven markers was found predictive of poor outcome. CONCLUSION: A strong quantitative CK2α immunohistochemical expression in breast carcinomas is individually a significant indicator of poor prognosis. Moreover, an immunohistochemical signature of 11 markers including CK2α accurately (86%) well classifies node negative patients in good and poor outcome subsets. Our results suggest that CK2α evaluation together with key downstream CK2 targets might be a useful tool to identify patients at high risk of distant metastases and that CK2 can be considered as a relevant target for potential specific therapy.
BACKGROUND: CK2α is a signalling molecule that participates in major events in solid tumour progression. The aim of this study was to evaluate the prognostic significance of the immunohistochemical expression of CK2α in breast carcinomas. METHODS: Quantitative measurements of immunohistochemical expression of 33 biomarkers using high-throughput densitometry, assessed on digitised microscopic tissue micro-array images were correlated with clinical outcome in 1000 breast carcinomas using univariate and multivariate analyses. RESULTS: In univariate analysis, CK2α was a significant prognostic indicator (p<0.001). Moreover, a multivariable model allowed the selection of the best combination of the 33 biomarkers to predict patients' outcome through logistic regression. A nine-marker signature highly predictive of metastatic risk, associating SHARP-2, STAT1, eIF4E, pmapKAPk-2, pAKT, caveolin, VEGF, FGF-1 and CK2α permitted to classify well 82.32% of patients (specificity 81.59%, sensitivity 92.55%, area under ROC curve 0.939). Importantly, in a node negative subset of patients an even more (86%) clinically relevant association of eleven markers was found predictive of poor outcome. CONCLUSION: A strong quantitative CK2α immunohistochemical expression in breast carcinomas is individually a significant indicator of poor prognosis. Moreover, an immunohistochemical signature of 11 markers including CK2α accurately (86%) well classifies node negative patients in good and poor outcome subsets. Our results suggest that CK2α evaluation together with key downstream CK2 targets might be a useful tool to identify patients at high risk of distant metastases and that CK2 can be considered as a relevant target for potential specific therapy.
Authors: Janeen H Trembley; Gretchen M Unger; Diane K Tobolt; Vicci L Korman; Guixia Wang; Kashif A Ahmad; Joel W Slaton; Betsy T Kren; Khalil Ahmed Journal: Mol Cell Biochem Date: 2011-07-15 Impact factor: 3.396
Authors: Claire M Cannon; Janeen H Trembley; Betsy T Kren; Gretchen M Unger; M Gerard O'Sullivan; Ingrid Cornax; Jaime F Modiano; Khalil Ahmed Journal: Hum Gene Ther Clin Dev Date: 2017-03-23 Impact factor: 5.032
Authors: Marine Gilabert; Maria Inés Vaccaro; Martin E Fernandez-Zapico; Ezequiel L Calvo; Olivier Turrini; Véronique Secq; Stéphane Garcia; Vincent Moutardier; Gwen Lomberk; Nelson Dusetti; Raul Urrutia; Juan L Iovanna Journal: J Cell Physiol Date: 2013-09 Impact factor: 6.384