Invasive lobular carcinoma of the breast: assessment of proliferative activity using automated Ki-67 immunostaining.
Pathology
; 51(7): 681-687, 2019 Dec.
Article
en En
| MEDLINE
| ID: mdl-31630876
Invasive lobular carcinoma (ILC) is almost always classified as Nottingham histological grade 2. Despite this, prognosis is markedly varied, with some ILCs behaving more akin to grade 3 invasive ductal carcinoma (IDC). Methods to separate these aggressive ILCs are needed. Digital image analysis (DIA) of the Ki-67 biomarker has potential in this regard; thus, we sought to determine the feasibility of its use for automated evaluation of ILC. An initial pilot study demonstrated no ILC specific changes were required to our Ki-67 DIA algorithm for reproducible results. Subsequently, 42 consecutive cases of ILC were evaluated by visual mitosis counting in H&E stained sections and by DIA on Ki-67 stained sections. Ki-67 proliferative index (PI) DIA showed significant correlation with visual mitosis counting on H&E stained sections (rs=0.63; p<0.05), significant strong correlation (rs=0.78; p<0.05) and substantial agreement (κ=0.62) with manual/visual Ki-67 assessment and significant positive associations with grade, nodal status and 'pleomorphic' ILC subtype, and a wide stratification of values in classical/grade 2 ILC. In conclusion, DIA of Ki-67 PI in ILC is feasible, correlates with mitotic index, manual/visual Ki-67 PI and clinico-pathological variables. The broad stratification of Ki-67 PI in classical/grade 2 ILC supports its practicability as a biomarker with prognostic and predictive potential, although large studies with outcome data are required for validation.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
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Biomarcadores de Tumor
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Carcinoma Lobular
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Antígeno Ki-67
Tipo de estudio:
Etiology_studies
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Guideline
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Aged
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Female
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Humans
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Middle aged
Idioma:
En
Revista:
Pathology
Año:
2019
Tipo del documento:
Article