Your browser doesn't support javascript.
loading
Protein Signatures for Distinguishing Colorectal Cancer Liver Metastases from Primary Liver Cancer Using Tissue Slide Proteomics.
Zhou, Xiaoman; Wang, Xiuyuan; Bai, Ruizhen; Li, Hanjie; Hua, Dong; Gao, Xiao-Dong; Yang, Ganglong; Liu, Quan.
Afiliación
  • Zhou X; The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 214122 Wuxi, Jiangsu, China.
  • Wang X; The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 214122 Wuxi, Jiangsu, China.
  • Bai R; Department of Pathology, Affiliated Hospital of Jiangnan University, 214122 Wuxi, Jiangsu, China.
  • Li H; The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 214122 Wuxi, Jiangsu, China.
  • Hua D; Department of Oncology, Wuxi People's Hospital Affiliated to Nanjing Medical University, 214122 Wuxi, Jiangsu, China.
  • Gao XD; State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, 100190 Beijing, China.
  • Yang G; The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 214122 Wuxi, Jiangsu, China.
  • Liu Q; State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, 100190 Beijing, China.
Front Biosci (Landmark Ed) ; 29(1): 3, 2024 01 09.
Article en En | MEDLINE | ID: mdl-38287800
ABSTRACT

BACKGROUND:

Colorectal cancer liver metastasis (CRLM) and hepatocellular carcinoma (HCC) are both high incidence tumors in China. In certain poorly differentiated cases they can exhibit comparable imaging and pathological characteristics, which impedes accurate clinical diagnosis. The use of protein-based techniques with tissue slides offers a more precise means to assess pathological changes and has the potential to assist with tumor diagnosis.

METHODS:

A simple in situ protein digestion protocol was established for protein fingerprint analysis of paraffin-embedded tissue slide samples. Additionally, machine learning techniques were employed to construct predictive models for CRLM and HCC. The accuracy of these models was validated using tissue slides and a clinical database.

RESULTS:

Analysis of differential protein expression between CRLM and HCC groups reliably identified 977 proteins. Among these, 53 were highly abundant in CRLM samples and 57 were highly abundant in HCC samples. A prediction model based on the expression of six proteins (CD9, GSTA1, KRT20, COL1A2, AKR1C3, and HIST2H2BD) had an area under curve (AUC) of 0.9667. This was further refined to three proteins (CD9, ALDH1A1, and GSTA1) with an AUC of 0.9333.

CONCLUSIONS:

Tissue slide proteomics can facilitate accurate differentiation between CRLM and HCC. This methodology holds great promise for improving clinical tumor diagnosis and for identifying novel markers for challenging pathological specimens.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Guideline / Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Front Biosci (Landmark Ed) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Singapur
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Guideline / Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Front Biosci (Landmark Ed) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Singapur