A highly predictive autoantibody-based biomarker panel for prognosis in early-stage NSCLC with potential therapeutic implications.
Br J Cancer
; 126(2): 238-246, 2022 02.
Article
en En
| MEDLINE
| ID: mdl-34728792
ABSTRACT
BACKGROUND:
Lung cancer is the leading cause of cancer-related death worldwide. Surgical resection remains the definitive curative treatment for early-stage disease offering an overall 5-year survival rate of 62%. Despite careful case selection, a significant proportion of early-stage cancers relapse aggressively within the first year post-operatively. Identification of these patients is key to accurate prognostication and understanding the biology that drives early relapse might open up potential novel adjuvant therapies.METHODS:
We performed an unsupervised interrogation of >1600 serum-based autoantibody biomarkers using an iterative machine-learning algorithm.RESULTS:
We identified a 13 biomarker signature that was highly predictive for survivorship in post-operative early-stage lung cancer; this outperforms currently used autoantibody biomarkers in solid cancers. Our results demonstrate significantly poor survivorship in high expressers of this biomarker signature with an overall 5-year survival rate of 7.6%.CONCLUSIONS:
We anticipate that the data will lead to the development of an off-the-shelf prognostic panel and further that the oncogenic relevance of the proteins recognised in the panel may be a starting point for a new adjuvant therapy.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Autoanticuerpos
/
Biomarcadores de Tumor
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Carcinoma de Pulmón de Células no Pequeñas
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Análisis por Matrices de Proteínas
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Neoplasias Pulmonares
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Male
Idioma:
En
Revista:
Br J Cancer
Año:
2022
Tipo del documento:
Article
País de afiliación:
Reino Unido