Immunodiagnostic plasma amino acid residue biomarkers detect cancer early and predict treatment response

Cong Tang (), Patrícia Corredeira, Sandra Casimiro, Qi Shi, Qiwei Han, Wesley Sukdao, Ana Cavaco, Cecília Melo-Alvim, Carolina Ochôa Matos, Catarina Abreu, Steven Walsh, Gonçalo Nogueira-Costa, Leonor Ribeiro, Rita Sousa, Ana Lorena Barradas, João Eurico Fonseca, Luís Costa (), Emma V. Yates () and Gonçalo J. L. Bernardes ()
Additional contact information
Cong Tang: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
Patrícia Corredeira: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
Sandra Casimiro: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
Qi Shi: R. da Holanda 1
Qiwei Han: R. da Holanda 1
Wesley Sukdao: Babraham Research Campus
Ana Cavaco: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
Cecília Melo-Alvim: Unidade Local de Saúde de Santa Maria
Carolina Ochôa Matos: ULS de Santa Maria, Centro Académico de Medicina de Lisboa
Catarina Abreu: Unidade Local de Saúde de Santa Maria
Steven Walsh: Babraham Research Campus
Gonçalo Nogueira-Costa: Unidade Local de Saúde de Santa Maria
Leonor Ribeiro: Unidade Local de Saúde de Santa Maria
Rita Sousa: Unidade Local de Saúde de Santa Maria
Ana Lorena Barradas: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
João Eurico Fonseca: ULS de Santa Maria, Centro Académico de Medicina de Lisboa
Luís Costa: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz
Emma V. Yates: Babraham Research Campus
Gonçalo J. L. Bernardes: GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract The immune response to tumour development is frequently targeted with therapeutics but remains largely unexplored in diagnostics, despite being stronger for early-stage tumours. We present an immunodiagnostic platform to detect this. We identify a panel of amino acid residue biomarkers providing a signature of cancer-specific immune activation associated with tumour development and distinct from autoimmune and infectious diseases, measurable optically in neat blood plasma, and validate within N = 170 participants. By measuring the total concentrations of cysteine, free cysteine, lysine, tryptophan, and tyrosine protein-incorporated biomarkers and analyzing the results with supervised machine learning, we identify 78% of cancers with 0% false positive rate (N = 97) with an AUROC of 0.95. The cancer, healthy, and autoimmune/infectious biomarker pattern are statistically significantly different (p

Date: 2025
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DOI: 10.1038/s41467-025-61685-2

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