Proteomic profiling identifies prognostic signature for Krukenberg tumor of gastrointestinal origin

TL;DR

This study identifies proteomic signatures in Krukenberg tumors that help distinguish them and predict ovarian metastasis in gastrointestinal cancers.

Contribution

The study introduces protein-based classifiers and identifies ECM pathways as potential therapeutic targets for KT.

Findings

Distinct proteomic signatures were found in primary gastrointestinal lesions of Krukenberg tumors.

Protein-based classifiers showed diagnostic value in distinguishing KT from other tumors.

ECM and MET pathways were enriched in KT primary lesions, suggesting therapeutic relevance.

Abstract

Krukenberg tumor (KT) primarily originates from the stomach and colorectum, but reliable biomarkers for distinguishing KT from other tumors at the same sites and predicting ovarian metastasis remain lacking. Using pressure cycling technology (PCT) and data-independent acquisition (DIA) mass spectrometry, we analyzed 263 formalin-fixed paraffin-embedded (FFPE) samples, identifying 10,837 proteins. The results revealed distinct proteomic signatures from the primary gastrointestinal lesions of KT. Comparative analyses identified group-specific pathways, particularly mesenchymal-epithelial transition (MET) signaling pathways and extracellular matrix (ECM) pathways, that were enriched in the primary lesions of KT. We developed protein-based classifiers with promising diagnostic value in distinguishing the primary gastrointestinal lesions of KT from those without ovarian metastases. We depicted distinct proteomic signatures in the primary gastrointestinal lesions of KT and identified potential biomarkers for prediction and early intervention of gastrointestinal cancer patients at risk of ovarian metastases.

•Identification of proteomic signatures provides valuable characterization of KT•Protein-based classifiers can aid in accurate identification and classification of KT•ECM pathways identify therapeutic targets for GI cancer with ovarian metastases

Identification of proteomic signatures provides valuable characterization of KT

Protein-based classifiers can aid in accurate identification and classification of KT

ECM pathways identify therapeutic targets for GI cancer with ovarian metastases

Cancer; Proteomics

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