Validation of absolutely quantitated Ki67 and cyclinD1 protein levels for prognosis of Luminal‐like breast cancer patients

Autor: Guohua Yu, Jiahong Lyu, Yalun Li, Yunyun Zhang, Yan Lyu, Wengfeng Zhang, Jianbo Zhang, Bocheng Cai, Jiandi Zhang, Fangrong Tang
Rok vydání: 2022
Předmět:
Zdroj: Journal of Clinical Laboratory Analysis. 36
ISSN: 1098-2825
0887-8013
DOI: 10.1002/jcla.24601
Popis: To translate a clinical research finding into daily clinical practice requires well-controlled clinical trials. We have demonstrated the usage of absolute quantitation of Ki67 and cyclinD1 protein levels to improve prognosis of Luminal-like patients based on overall survival (OS) analysis of a cohort of 155 breast cancer specimens (cohort 1). However, this finding is considered the D level of evidence (LOE) to require subsequent validation before it may be used in daily clinical practice. To set the stage for future clinical trials, our findings were validated through OS analysis of an independent cohort (cohort 2) of 173 Luminal-like patients.Both Ki67 and cyclinD1 levels were measured absolutely and quantitatively using the Quantitative Dot Blot (QDB) method in cohort 2. The proposed cutoffs for both biomarkers from cohort 1 were re-evaluated in cohort 2 and in the merged cohort of 1 and 2, respectively, through univariate, multivariate and Kaplan-Meier survival analysis.The proposed cutoffs of 2.31 nmol/g for Ki67 and 0.44 μmol/g for cyclinD1 were validated as effective cutoffs in cohort 2 and the merged cohort through OS analysis. The combined use of both biomarkers allowed us to identify patients with both biomarker levels below the cutoffs (59.3%) with10-year survival probability (SP) of 89%, in comparison to those above the cutoffs (8.3%) with 8 year SP of 28% through OS analysis in the merged cohort.This study validated our findings that absolute quantitation of Ki67 and cyclinD1 allows effective subtyping of luminal-like patients. It sets the stage for prospective or prospective-retrospective clinical studies.
Databáze: OpenAIRE
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