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Cancer mortality is exacerbated by late-stage diagnosis. Liquid biopsies based on genomic biomarkers can noninvasively diagnose cancers. However, validation studies have reported similar to 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 (N-urine = 220 cancer vs. 360 healthy) and plasma (N-plasma = 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.

Placental malaria infection is mediated by the binding of the malarial VAR2CSA protein to the placental glycosaminoglycan, chondroitin sulfate. Recombinant sub-fragments of VAR2CSA (rVAR2) have also been shown to bind specifically and with high affinity to cancer cells and tissues, suggesting the presence of a shared type of oncofetal chondroitin sulfate (ofCS) in the placenta and in tumors. However, the exact structure of ofCS and what determines the selective tropism of VAR2CSA remains poorly understood. In this study, ofCS was purified by affinity chromatography using rVAR2 and subjected to detailed structural analysis. We found high levels of N-acetylgalactosamine 4-O-sulfation (∼80-85%) in placenta- and tumor-derived ofCS. This level of 4-O-sulfation was also found in other tissues that do not support parasite sequestration, suggesting that VAR2CSA tropism is not exclusively determined by placenta- and tumor-specific sulfation. Here, we show that both placenta and tumors contain significantly more chondroitin sulfate moieties of higher molecular weight than other tissues. In line with this, CHPF and CHPF2, which encode proteins required for chondroitin polymerization, are significantly upregulated in most cancer types. CRISPR/Cas9 targeting of CHPF and CHPF2 in tumor cells reduced the average molecular weight of cell-surface chondroitin sulfate and resulted in a marked reduction of rVAR2 binding. Finally, utilizing a cell-based glycocalyx model, we showed that rVAR2 binding correlates with the length of the chondroitin sulfate chains in the cellular glycocalyx. These data demonstrate that the total amount and cellular accessibility of chondroitin sulfate chains impact rVAR2 binding and thus malaria infection.

BACKGROUND. Identifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which gut microbial features are applicable across different patient cohorts has not been extensively explored. METHODS. We performed a meta-analysis of 4 published shotgun metagenomic studies (Ntot = 130 patients) investigating differential microbiome composition and imputed metabolic function between responders and nonresponders to ICI. RESULTS. Our analysis identified both known microbial features enriched in responders, such as Faecalibacterium as the prevailing taxa, as well as additional features, including overrepresentation of Barnesiella intestinihominis and the components of vitamin B metabolism. A classifier designed to predict responders based on these features identified responders in an independent cohort of 27 patients with the area under the receiver operating characteristic curve of 0.625 (95% CI: 0.348-0.899) and was predictive of prognosis (HR = 0.35, P = 0.081). CONCLUSION. These results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes. FUNDING. This work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden.

Protein synthesis is the most energy-consuming process in a proliferating cell, and understanding what controls protein abundances represents a key question in biology and biotechnology. We quantified absolute abundances of 5,354 mRNAs and 2,198 proteins in Saccharomyces cerevisiae under ten environmental conditions and protein turnover for 1,384 proteins under a reference condition. The overall correlation between mRNA and protein abundances across all conditions was low (0.46), but for differentially expressed proteins (n = 202), the median mRNA-protein correlation was 0.88. We used these data to model translation efficiencies and found that they vary more than 400-fold between genes. Non-linear regression analysis detected that mRNA abundance and translation elongation were the dominant factors controlling protein synthesis, explaining 61% and 15% of its variance. Metabolic flux balance analysis further showed that only mitochondrial fluxes were positively associated with changes at the transcript level. The present dataset represents a crucial expansion to the current resources for future studies on yeast physiology.