Noninvasive detection of any-stage cancer using free glycosaminoglycans

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  • Sinisa Bratulic
  • Angelo Limeta
  • Saeed Dabestani
  • Helgi Birgisson
  • Gunilla Enblad
  • Karin Stålberg
  • Göran Hesselager
  • Michael Häggman
  • Martin Höglund
  • Oscar E Simonson
  • Peter Stålberg
  • Henrik Lindman
  • Anna Bång-Rudenstam
  • Matias Ekstrand
  • Gunjan Kumar
  • Ilaria Cavarretta
  • Massimo Alfano
  • Francesco Pellegrino
  • Francesca Maccari
  • Fabio Galeotti
  • Nicola Volpi
  • Mads Daugaard
  • Mattias Belting
  • Sven Lundstam
  • Ulrika Stierner
  • Jan Nyman
  • Bengt Bergman
  • Per-Henrik Edqvist
  • Max Levin
  • Andrea Salonia
  • Henrik Kjölhede
  • Eric Jonasch
  • Jens Nielsen
  • Francesco Gatto

Cancer mortality is exacerbated by late-stage diagnosis. Liquid biopsies based on genomic biomarkers can noninvasively diagnose cancers. However, validation studies have reported ~10% sensitivity to detect stage I cancer in a screening population and specific types, such as brain or genitourinary tumors, remain undetectable. We investigated urine and plasma free glycosaminoglycan profiles (GAGomes) as tumor metabolism biomarkers for multi-cancer early detection (MCED) of 14 cancer types using 2,064 samples from 1,260 cancer or healthy subjects. We observed widespread cancer-specific changes in biofluidic GAGomes recapitulated in an in vivo cancer progression model. We developed three machine learning models based on urine (Nurine = 220 cancer vs. 360 healthy) and plasma (Nplasma = 517 vs. 425) GAGomes that can detect any cancer with an area under the receiver operating characteristic curve of 0.83-0.93 with up to 62% sensitivity to stage I disease at 95% specificity. Undetected patients had a 39 to 50% lower risk of death. GAGomes predicted the putative cancer location with 89% accuracy. In a validation study on a screening-like population requiring ≥ 99% specificity, combined GAGomes predicted any cancer type with poor prognosis within 18 months with 43% sensitivity (21% in stage I; N = 121 and 49 cases). Overall, GAGomes appeared to be powerful MCED metabolic biomarkers, potentially doubling the number of stage I cancers detectable using genomic biomarkers.

Original languageEnglish
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number50
Pages (from-to)e2115328119
Publication statusPublished - 2022

    Research areas

  • Humans, Glycosaminoglycans, Biomarkers, Tumor/genetics, Liquid Biopsy, Early Detection of Cancer, Neoplasms/diagnosis

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