Noninvasive detection of any-stage cancer using free glycosaminoglycans
Journal article, 2022
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.
metabolomics
liquid biopsy
cancer biomarkers
prognosis
multi-cancer early detection
Author
Sinisa Bratulic
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Angelo Limeta
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Saeed Dabestani
Lund University
Kristianstad Central Hospital
Helgi Birgisson
Akademiska Sjukhuset
Gunilla Enblad
Uppsala University
Karin Stålberg
Uppsala University
Göran Hesselager
Akademiska Sjukhuset
Michael Häggman
Akademiska Sjukhuset
Martin Höglund
Akademiska Sjukhuset
Oscar E. Simonson
Akademiska Sjukhuset
Peter Stålberg
Akademiska Sjukhuset
Henrik Lindman
Uppsala University
Anna Bång-Rudenstam
Lund University
Matias Ekstrand
Wallenberg Lab.
Gunjan Kumar
Vancouver Prostate Centre
University of British Columbia (UBC)
Ilaria Cavarretta
IRCCS Ospedale San Raffaele
Massimo Alfano
IRCCS Ospedale San Raffaele
Francesco Pellegrino
IRCCS Ospedale San Raffaele
Thomas Mandel Clausen
University of California
Ali Salanti
University of Copenhagen
Copenhagen University Hospital
F. Maccari
University of Modena and Reggio Emilia
F. Galeotti
University of Modena and Reggio Emilia
N. Volpi
University of Modena and Reggio Emilia
Mads Daugaard
Vancouver Prostate Centre
University of British Columbia (UBC)
M. Belting
Lund University
Sven Lundstam
University of Gothenburg
Ulrika Stierner
University of Gothenburg
Jan Nyman
University of Gothenburg
Bengt Bergman
University of Gothenburg
P. H. Edqvist
Uppsala University
Max Levin
Wallenberg Lab.
University of Gothenburg
Andrea Salonia
Università Vita-Salute San Raffaele
IRCCS Ospedale San Raffaele
Henrik Kjölhede
University of Gothenburg
Sahlgrenska University Hospital
Eric Jonasch
University of Texas MD Anderson Cancer Center
Jens B Nielsen
BioInnovation Institute
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Francesco Gatto
Karolinska Institutet
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Proceedings of the National Academy of Sciences of the United States of America
0027-8424 (ISSN) 1091-6490 (eISSN)
Vol. 119 50Subject Categories
Clinical Laboratory Medicine
Urology and Nephrology
Cancer and Oncology
DOI
10.1073/pnas.2115328119
PubMed
36469776