Comparative LC‐MS Proteomics of Quinoa Grains: Evaluation of Bioactivity and Health Benefits by Combining In Silico Techniques With In Vitro Assays on Colorectal Adenocarcinoma Cells

In the present study, we investigated the potential biological effects of proteins and peptides extracted from four different commercial quinoa grain varieties: Black (B), Red (R), White (W), and Royal White (RO), using Caco-2 cells as a proliferation model. Concentration-response curves were constructed to evaluate cytotoxicity and antiproliferative effects. Interestingly, peptides exhibited higher cytotoxicity than proteins, particularly in R and RO quinoa varieties. Based on these findings, we used a data mining approach to identify and compare the cytotoxic proteins in the four quinoa varieties. Using their relative abundance, we successfully classified R and RO quinoa as a cohesive group using classification models. To gain deeper insights into the biological effects on cells, we comprehensively analyzed the differential expression of apoptosis biomarkers using liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted proteomics. Finally, we correlated the apoptosis profile with the relative abundance of cytotoxic proteins. All these studies were supported by the application of multivariate data analysis. The results demonstrated the potential anticancer of quinoa grain proteins and peptides and provided the basis for more focused mechanistic studies aimed at developing functional foods and nutraceuticals.

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Publication Details

Journal
Molecular Nutrition & Food Research
Published
2025-05-23
DOI
https://doi.org/10.1002/mnfr.70125
Citations
1
Primary Topic
Seed and Plant Biochemistry
Type
article
Field-Weighted Citation Impact
1.16

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article

Comparative LC‐MS Proteomics of Quinoa Grains: Evaluation of Bioactivity and Health Benefits by Combining In Silico Techniques With In Vitro Assays on Colorectal Adenocarcinoma Cells

Laura Pont, Lisa Elviri, Fernando Benavente, Rocío Galindo‐Luján et al.
1 citations
Molecular Nutrition & Food Research
Seed and Plant Biochemistry
1.16
article

Comparative LC‐MS Proteomics of Quinoa Grains: Evaluation of Bioactivity and Health Benefits by Combining In Silico Techniques With In Vitro Assays on Colorectal Adenocarcinoma Cells

Laura Pont, Lisa Elviri, Fernando Benavente, Rocío Galindo‐Luján, Alessandro Zaccarelli, Ilaria Zanotti, Beatrice Mattina
article en
1 citations

Abstract

In the present study, we investigated the potential biological effects of proteins and peptides extracted from four different commercial quinoa grain varieties: Black (B), Red (R), White (W), and Royal White (RO), using Caco-2 cells as a proliferation model. Concentration-response curves were constructed to evaluate cytotoxicity and antiproliferative effects. Interestingly, peptides exhibited higher cytotoxicity than proteins, particularly in R and RO quinoa varieties. Based on these findings, we used a data mining approach to identify and compare the cytotoxic proteins in the four quinoa varieties. Using their relative abundance, we successfully classified R and RO quinoa as a cohesive group using classification models. To gain deeper insights into the biological effects on cells, we comprehensively analyzed the differential expression of apoptosis biomarkers using liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted proteomics. Finally, we correlated the apoptosis profile with the relative abundance of cytotoxic proteins. All these studies were supported by the application of multivariate data analysis. The results demonstrated the potential anticancer of quinoa grain proteins and peptides and provided the basis for more focused mechanistic studies aimed at developing functional foods and nutraceuticals.

Molecular Nutrition & Food ResearchVol. 69(14)
University of Parma (IT), Generalitat de Catalunya (ES), Universitat de Barcelona (ES)
Indian National Science Academy, Dipartimenti di Eccellenza, Università degli Studi di Parma, Universitat de Barcelona, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 22%
Seed and Plant Biochemistry
1.16
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