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

Journal: Nature communications
Published Date:

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 < 0.0001). Smaller-scale changes in biomarker concentrations reveal inter-patient differences in immune activation that predict treatment response. Specific concentration ranges of these biomarkers predict response to Cyclin-dependent kinase inhibitors in advanced breast cancer patients (p < 0.05), identifying 98% of responders (N = 33). Here we provide an immunodiagnostic technology platform that, to our knowledge, has not been previously reported, and prove initial clinical application in a cohort of N = 170, including proof of concept in Multi Cancer Early Detection and personalized medicine.

Authors

  • Cong Tang
    GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz, Lisboa, Portugal. cong.tang@gimm.pt.
  • Patrícia Corredeira
    GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz, Lisboa, Portugal.
  • Sandra Casimiro
    GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz, Lisboa, Portugal.
  • Qi Shi
    MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-infective Medicine, Institute of Molecular Enzymology, School of Life Sciences, Suzhou Medical College of Soochow University, Suzhou, China.
  • Qiwei Han
    Nova School of Business and Economics, R. da Holanda 1, Carcavelos, Portugal.
  • Wesley Sukdao
    Proteotype Diagnostics Ltd, Babraham Research Campus, Cambridge, UK.
  • Ana Cavaco
    GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz, Lisboa, Portugal.
  • Cecília Melo-Alvim
    Serviço de Oncologia Médica, ULSSM, Unidade Local de Saúde de Santa Maria, Lisboa, Portugal.
  • Carolina Ochôa Matos
    Serviço de Reumatologia, ULS de Santa Maria, Centro Académico de Medicina de Lisboa, Lisbon, Portugal.
  • Catarina Abreu
    Serviço de Oncologia Médica, ULSSM, Unidade Local de Saúde de Santa Maria, Lisboa, Portugal.
  • Steven Walsh
    Proteotype Diagnostics Ltd, Babraham Research Campus, Cambridge, UK.
  • Gonçalo Nogueira-Costa
    Serviço de Oncologia Médica, ULSSM, Unidade Local de Saúde de Santa Maria, Lisboa, Portugal.
  • Leonor Ribeiro
    Serviço de Oncologia Médica, ULSSM, Unidade Local de Saúde de Santa Maria, Lisboa, Portugal.
  • Rita Sousa
    Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos s/n, 4450-208 Porto, Portugal.
  • Ana Lorena Barradas
    GIMM - Gulbenkian Institute for Molecular Medicine; Avenida Prof. Egas Moniz, Lisboa, Portugal.
  • João Eurico Fonseca
    Serviço de Reumatologia, ULS de Santa Maria, Centro Académico de Medicina de Lisboa, Lisbon, Portugal.
  • Luís Costa
    Algoritmi Center, Department of Industrial Electronics, School of Engineering, University of Minho, Braga, Portugal.
  • Emma V Yates
    Proteotype Diagnostics Ltd, Babraham Research Campus, Cambridge, UK. emma@proteotype.com.
  • Gonçalo J L Bernardes
    Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK.