1. |
- Bratulic, Sinisa, 1981, et al.
(författare)
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Noninvasive detection of any-stage cancer using free glycosaminoglycans.
- 2022
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:50
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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2. |
- Brunk, Elizabeth, et al.
(författare)
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Recon3D enables a three-dimensional view of gene variation in human metabolism
- 2018
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 36:3, s. 272-281
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Tidskriftsartikel (refereegranskat)abstract
- Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.
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3. |
- Bratulic, Sinisa, 1981, et al.
(författare)
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Analysis of normal levels of free glycosaminoglycans in urine and plasma in adults
- 2022
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Ingår i: Journal of Biological Chemistry. - : Elsevier BV. - 0021-9258 .- 1083-351X. ; 298:2
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Tidskriftsartikel (refereegranskat)abstract
- Plasma and urine glycosaminoglycans (GAGs) are long, linear sulfated polysaccharides that have been proposed as potential noninvasive biomarkers for several diseases. However, owing to the analytical complexity associated with the measurement of GAG concentration and disaccharide composition (the so-called GAGome), a reference study of the normal healthy GAGome is currently missing. Here, we prospectively enrolled 308 healthy adults and analyzed their free GAGomes in urine and plasma using a standardized ultra-high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry method together with comprehensive demographic and blood chemistry biomarker data. Of 25 blood chemistry biomarkers, we mainly observed weak correlations between the free GAGome and creatinine in urine and hemoglobin or erythrocyte counts in plasma. We found a higher free GAGome concentration - but not a more diverse composition - in males. Partitioned by gender, we also established reference intervals for all detectable free GAGome features in urine and plasma. Finally, we carried out a transference analysis in healthy individuals from two distinct geographical sites, including data from the Lifelines Cohort Study, which validated the reference intervals in urine. Our study is the first large-scale determination of normal free GAGomes reference intervals in plasma and urine and represents a critical resource for future physiology and biomarker research. © 2022 THE AUTHORS. Published by Elsevier Inc on behalf of American Society for Biochemistry and Molecular Biology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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4. |
- Bratulic, Sinisa, 1981, et al.
(författare)
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The Translational Status of Cancer Liquid Biopsies
- 2021
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Ingår i: Regenerative Engineering and Translational Medicine. - : Springer Science and Business Media LLC. - 2364-4133 .- 2364-4141. ; 7:3, s. 312-352
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Tidskriftsartikel (refereegranskat)abstract
- Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research. Lay Summary: Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.
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5. |
- Clausen, Thomas Mandel, et al.
(författare)
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A simple method for detecting oncofetal chondroitin sulfate glycosaminoglycans in bladder cancer urine
- 2020
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Ingår i: Cell Death Discovery. - : Springer Science and Business Media LLC. - 2058-7716. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Proteoglycans in bladder tumors are modified with a distinct oncofetal chondroitin sulfate (ofCS) glycosaminoglycan that is normally restricted to placental trophoblast cells. This ofCS-modification can be detected in bladder tumors by the malarial VAR2CSA protein, which in malaria pathogenesis mediates adherence of parasite-infected erythrocytes within the placenta. In bladder cancer, proteoglycans are constantly shed into the urine, and therefore have the potential to be used for detection of disease. In this study we investigated whether recombinant VAR2CSA (rVAR2) protein could be used to detect ofCS-modified proteoglycans (ofCSPGs) in the urine of bladder cancer patients as an indication of disease presence. We show that ofCSPGs in bladder cancer urine can be immobilized on cationic nitrocellulose membranes and subsequently probed for ofCS content by rVAR2 protein in a custom-made dot-blot assay. Patients with high-grade bladder tumors displayed a marked increase in urinary ofCSPGs as compared to healthy individuals. Urine ofCSPGs decreased significantly after complete tumor resection compared to matched urine collected preoperatively from patients with bladder cancer. Moreover, ofCSPGs in urine correlated with tumor size of bladder cancer patients. These findings demonstrate that rVAR2 can be utilized in a simple biochemical assay to detect cancer-specific ofCS-modifications in the urine of bladder cancer patients, which may be further developed as a noninvasive approach to detect and monitor the disease.
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6. |
- Feizi, Amir, 1980, et al.
(författare)
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Human protein secretory pathway genes are expressed in a tissue-specific pattern to match processing demands of the secretome
- 2017
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Ingår i: npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Protein secretory pathway in eukaryal cells is responsible for delivering functional secretory proteins. The dysfunction of this pathway causes a range of important human diseases from congenital disorders to cancer. Despite the piled-up knowledge on the molecular biology and biochemistry level, the tissue-specific expression of the secretory pathway genes has not been analyzed on the transcriptome level. Based on the recent RNA-sequencing studies, the largest fraction of tissue-specific transcriptome encodes for the secretome (secretory proteins). Here, the question arises that if the expression levels of the secretory pathway genes have a tissue-specific tuning. In this study, we tackled this question by performing a meta-analysis of the recently published transcriptome data on human tissues. As a result, we detected 68 as called “extreme genes” which show an unusual expression pattern in specific gene families of the secretory pathway. We also inspected the potential functional link between detected extreme genes and the corresponding tissues enriched secretome. As a result, the detected extreme genes showed correlation with the enrichment of the nature and number of specific post-translational modifications in each tissue’s secretome. Our findings conciliate both the housekeeping and tissue-specific nature of the protein secretory pathway, which we attribute to a fine-tuned regulation of defined gene families to support the diversity of secreted proteins and their modifications.
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7. |
- Ferreira, Raphael, 1990, et al.
(författare)
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Exploiting off-targeting in guide-RNAs for CRISPR systems for simultaneous editing of multiple genes
- 2017
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Ingår i: FEBS Letters. - : Wiley. - 1873-3468 .- 0014-5793. ; 591:20, s. 3288-3295
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Tidskriftsartikel (refereegranskat)abstract
- Bioinformatics tools to design guide-RNAs (gRNAs) in Clustered Regularly Interspaced Short Palindromic Repeats systems mostly focused on minimizing off-targeting to enhance efficacy of genome editing. However, there are circumstances in which off-targeting might be desirable to target multiple genes simultaneously with a single gRNA. We termed these gRNAs as promiscuous gRNAs. Here, we present a computational workflow to identify promiscuous gRNAs that putatively bind to the region of interest for a defined list of genes in a genome. We experimentally validated two promiscuous gRNA for gene deletion, one targeting FAA1 and FAA4 and one targeting PLB1 and PLB2, thus demonstrating that multiplexed genome editing through design of promiscuous gRNA can be performed in a time and cost-effective manner.
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8. |
- Gatto, Francesco, 1987, et al.
(författare)
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Chromosome 3p loss of heterozygosity is associated with a unique metabolic network in clear cell renal carcinoma
- 2014
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 111:9, s. E866-E875
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Tidskriftsartikel (refereegranskat)abstract
- Several common oncogenic pathways have been implicated in the emergence of renowned metabolic features in cancer, which in turn are deemed essential for cancer proliferation and survival. However, the extent to which different cancers coordinate their metabolism to meet these requirements is largely unexplored. Here we show that even in the heterogeneity of metabolic regulation a distinct signature encompassed most cancers. On the other hand, clear cell renal cell carcinoma (ccRCC) strongly deviated in terms of metabolic gene expression changes, showing widespread down-regulation. We observed a metabolic shift that associates differential regulation of enzymes in one-carbon metabolism with high tumor stage and poor clinical outcome. A significant yet limited set of metabolic genes that explained the partial divergence of ccRCC metabolism correlated with loss of von Hippel-Lindau tumor suppressor (VHL) and a potential activation of signal transducer and activator of transcription 1. Further network-dependent analyses revealed unique defects in nucleotide, one-carbon, and glycerophospholipid metabolism at the transcript and protein level, which contrasts findings in other tumors. Notably, this behavior is recapitulated by recurrent loss of heterozygosity in multiple metabolic genes adjacent to VHL. This study therefore shows how loss of heterozygosity, hallmarked by VHL deletion in ccRCC, may uniquely shape tumor metabolism.
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9. |
- Gatto, Francesco, 1987, et al.
(författare)
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Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism
- 2015
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 5, s. Art. no. 10738-
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Tidskriftsartikel (refereegranskat)abstract
- Flux balance analysis is the only modelling approach that is capable of producing genome-wide predictions of gene essentiality that may aid to unveil metabolic liabilities in cancer. Nevertheless, a systemic validation of gene essentiality predictions by flux balance analysis is currently missing. Here, we critically evaluated the accuracy of flux balance analysis in two cancer types, clear cell renal cell carcinoma (ccRCC) and prostate adenocarcinoma, by comparison with large-scale experiments of gene essentiality in vitro. We found that in ccRCC, but not in prostate adenocarcinoma, flux balance analysis could predict essential metabolic genes beyond random expectation. Five of the identified metabolic genes, AGPAT6, GALT, GCLC, GSS, and RRM2B, were predicted to be dispensable in normal cell metabolism. Hence, targeting these genes may selectively prevent ccRCC growth. Based on our analysis, we discuss the benefits and limitations of flux balance analysis for gene essentiality predictions in cancer metabolism, and its use for exposing metabolic liabilities in ccRCC, whose emergent metabolic network enforces outstanding anabolic requirements for cellular proliferation.
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10. |
- Gatto, Francesco, 1987, et al.
(författare)
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Glycosaminoglycan Profiling in Patients' Plasma and Urine Predicts the Occurrence of Metastatic Clear Cell Renal Cell Carcinoma
- 2016
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 15:8, s. 1822-1836
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Tidskriftsartikel (refereegranskat)abstract
- Metabolic reprogramming is a hallmark of clear cell renal cell carcinoma (ccRCC) progression. Here, we used genome-scale metabolic modeling to elucidate metabolic reprogramming in 481 ccRCC samples and discovered strongly coordinated regulation of glycosaminoglycan (GAG) biosynthesis at the transcript and protein levels. Extracellular GAGs are implicated in metastasis, so we speculated that such regulation might translate into a non-invasive biomarker for metastatic ccRCC (mccRCC). We measured 18 GAG properties in 34 mccRCC samples versus 16 healthy plasma and/or urine samples. The GAG profiles were distinctively altered in mccRCC. We derived three GAG scores that distinguished mccRCC patients with 93.1%-100% accuracy. We validated the score accuracies in an independent cohort (up to 18 mccRCC versus nine healthy) and verified that the scores normalized in eight patients with no evidence of disease. In conclusion, coordinated regulation of GAG biosynthesis occurs in ccRCC, and non-invasive GAG profiling is suitable for mccRCC diagnosis.
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11. |
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12. |
- Gatto, Francesco, 1987, et al.
(författare)
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In search for symmetries in the metabolism of cancer
- 2016
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Ingår i: Wiley Interdisciplinary Reviews: Systems Biology and Medicine. - : Wiley. - 1939-5094 .- 1939-005X. ; 8:1, s. 23-35
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Forskningsöversikt (refereegranskat)abstract
- Even though aerobic glycolysis, or the Warburg effect, is arguably the most common trait of metabolic reprogramming in cancer, it is unobserved in certain tumor types. Systems biology advocates a global view on metabolism to dissect which traits are consistently reprogrammed in cancer, and hence likely to constitute an obligate step for the evolution of cancer cells. We refer to such traits as symmetric. Here, we review early systems biology studies that attempted to reveal symmetric traits in the metabolic reprogramming of cancer, discuss the symmetry of reprogramming of nucleotide metabolism, and outline the current limitations that, if unlocked, could elucidate whether symmetries in cancer metabolism may be claimed.
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13. |
- Gatto, Francesco, 1987, et al.
(författare)
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Pan-cancer analysis of the metabolic reaction network
- 2020
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Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 57, s. 51-62
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Tidskriftsartikel (refereegranskat)abstract
- Metabolic reprogramming is considered a hallmark of malignant transformation. However, it is not clear whether the network of metabolic reactions expressed by cancers of different origin differ from each other or from normal human tissues. In this study, we reconstructed functional and connected genome-scale metabolic models for 917 primary tumor samples across 13 types based on the probability of expression for 3765 reference metabolic genes in the sample. This network-centric approach revealed that tumor metabolic networks are largely similar in terms of accounted reactions, despite diversity in the expression of the associated genes. On average, each network contained 4721 reactions, of which 74% were core reactions (present in >95% of all models). Whilst 99.3% of the core reactions were classified as housekeeping also in normal tissues, we identified reactions catalyzed by ARG2, RHAG, SLC6 and SLC16 family gene members, and PTGS1 and PTGS2 as core exclusively in cancer. These findings were subsequently replicated in an independent validation set of 3388 genome-scale metabolic models. The remaining 26% of the reactions were contextual reactions. Their inclusion was dependent in one case (GLS2) on the absence of TP53 mutations and in 94.6% of cases on differences in cancer types. This dependency largely resembled differences in expression patterns in the corresponding normal tissues, with some exceptions like the presence of the NANP-encoded reaction in tumors not from the female reproductive system or of the SLC5A9-encoded reaction in kidney-pancreatic-colorectal tumors. In conclusion, tumors expressed a metabolic network virtually overlapping the matched normal tissues, raising the possibility that metabolic reprogramming simply reflects cancer cell plasticity to adapt to varying conditions thanks to redundancy and complexity of the underlying metabolic networks. At the same time, the here uncovered exceptions represent a resource to identify selective liabilities of tumor metabolism.
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14. |
- Gatto, Francesco, 1987, et al.
(författare)
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Plasma and Urine Free Glycosaminoglycans as Monitoring and Predictive Biomarkers in Metastatic Renal Cell Carcinoma: A Prospective Cohort Study
- 2023
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Ingår i: JCO PRECISION ONCOLOGY. - 2473-4284. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSENo liquid biomarkers are approved in metastatic renal cell carcinoma (mRCC) despite the need to predict and monitor response noninvasively to tailor treatment choices. Urine and plasma free glycosaminoglycan profiles (GAGomes) are promising metabolic biomarkers in mRCC. The objective of this study was to explore if GAGomes could predict and monitor response in mRCC.PATIENTS AND METHODSWe enrolled a single-center prospective cohort of patients with mRCC elected for first-line therapy (ClinicalTrials.gov identifier: NCT02732665) plus three retrospective cohorts (ClinicalTrials.gov identifiers: NCT00715442 and NCT00126594) for external validation. Response was dichotomized as progressive disease (PD) versus non-PD every 8-12 weeks. GAGomes were measured at treatment start, after 6-8 weeks, and every third month in a blinded laboratory. We correlated GAGomes with response and developed scores to classify PD versus non-PD, which were used to predict response at treatment start or after 6-8 weeks.RESULTSFifty patients with mRCC were prospectively included, and all received tyrosine kinase inhibitors (TKIs). PD correlated with alterations in 40% of GAGome features. We developed plasma, urine, and combined glycosaminoglycan progression scores that monitored PD at each response evaluation visit with the area under the receiving operating characteristic curve (AUC) of 0.93, 0.97, and 0.98, respectively. For internal validation, the scores predicted PD at treatment start with the AUC of 0.66, 0.68, and 0.74 and after 6-8 weeks with the AUC of 0.76, 0.66, and 0.75. For external validation, 70 patients with mRCC were retrospectively included and all received TKI-containing regimens. The plasma score predicted PD at treatment start with the AUC of 0.90 and at 6-8 weeks with the AUC of 0.89. The pooled sensitivity and specificity were 58% and 79% at treatment start. Limitations include the exploratory study design.CONCLUSIONGAGomes changed in association with mRCC response to TKIs and may provide biologic insights into mRCC mechanisms of response.
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15. |
- Gatto, Francesco, 1987, et al.
(författare)
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Plasma and Urine Free Glycosaminoglycans as Monitoring Biomarkers in Nonmetastatic Renal Cell Carcinoma—A Prospective Cohort Study
- 2022
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Ingår i: European Urology Open Science. - : Elsevier BV. - 2666-1683 .- 2666-1691. ; 42, s. 30-39
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Tidskriftsartikel (refereegranskat)abstract
- Background: No liquid biomarkers are approved in renal cell carcinoma (RCC), making early detection of recurrence in surgically treated nonmetastatic (M0) patients dependent on radiological imaging. Urine- and plasma free glycosaminoglycan profiles—or free GAGomes—are promising biomarkers reflective of RCC metabolism. Objective: To explore whether free GAGomes could detect M0 RCC recurrence noninvasively. Design, setting, and participants: Between June 2016 and February 2021, we enrolled a prospective consecutive series of patients elected for (1) partial or radical nephrectomy for clinical M0 RCC (cohort 1) or (2) first-line therapy following RCC metachronous metastatic recurrence (cohort 2) at Sahlgrenska University Hospital, Gothenburg, Sweden. The study population included M0 RCC patients with recurrent disease (RD) versus no evidence of disease (NED) in at least one follow-up visit. Plasma and urine free GAGomes—consisting of 40 chondroitin sulfate (CS), heparan sulfate, and hyaluronic acid (HA) features—were measured in a blinded central laboratory preoperatively and at each postoperative follow-up visit until recurrence or end of follow-up in cohort 1, or before treatment start in cohort 2. Outcome measurements and statistical analysis: We used Bayesian logistic regression to correlate GAGome features with RD versus NED and with various histopathological variables. We developed three recurrence scores (plasma, urine, and combined) proportional to the predicted probability of RD. We internally validated the area under the curve (AUC) using bootstrap resampling. We performed a decision curve analysis to select a cutoff and report the corresponding net benefit, sensitivity, and specificity of each score. We used univariable analyses to correlate each preoperative score with recurrence-free survival (RFS). Results and limitations: Of 127 enrolled patients in total, 62 M0 RCC patients were in the study population (median age: 63 year, 35% female, and 82% clear cell). The median follow-up time was 3 months, totaling 72 postoperative visits —17 RD and 55 NED cases. RD was compatible with alterations in 14 (52%) of the detectable GAGome features, mostly free CS. Eleven (79%) of these correlated with at least one histopathological variable. We developed a plasma, a urine, and a combined free CS RCC recurrence score to diagnose RD versus NED with AUCs 0.91, 0.93, and 0.94, respectively. At a cutoff equivalent to ≥30% predicted probability of RD, the sensitivity and specificity were, respectively, 69% and 84% in plasma, 81% and 80% in urine, and 80% and 82% when combined, and the net benefit was equivalent to finding an extra ten, 13, and 12 cases of RD per hundred patients without any unnecessary imaging for plasma, urine, and combined, respectively. The combined score was prognostic of RFS in univariable analysis (hazard ratio = 1.90, p = 0.02). Limitations include a lack of external validation. Conclusions: Free CS scores detected postsurgical recurrence noninvasively in M0 RCC with substantial net benefit. External validity is required before wider clinical implementation. Patient summary: In this study, we examined a new noninvasive blood and urine test to detect whether renal cell carcinoma recurred after surgery.
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16. |
- Gatto, Francesco, 1987, et al.
(författare)
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Plasma Glycosaminoglycans as Diagnostic and Prognostic Biomarkers in Surgically Treated Renal Cell Carcinoma
- 2018
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Ingår i: European Urology Oncology. - : Elsevier BV. - 2588-9311. ; 1:5, s. 364-377
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Tidskriftsartikel (refereegranskat)abstract
- Plasma glycosaminoglycan (GAG) measurements, when aggregated into diagnostic scores, accurately distinguish metastatic clear-cell renal cell carcinoma (RCC) from healthy samples and correlate with prognosis. However, it is unknown if GAG scores can detect RCC in earlier stages or if they correlate with prognosis after surgery. Objective: To explore the sensitivity and specificity of plasma GAGs for detection of early-stage RCC and prediction of recurrence and death after RCC surgery. Design, setting, and participants: This was a retrospective case-control study consisting of a consecutive series of 175 RCC patients surgically treated between May 2011 and February 2014 and 19 healthy controls. Outcome measurements and statistical analysis: Plasma GAGs in preoperative and postoperative RCC and healthy samples were measured using capillary electrophoresis with laser-induced fluorescence in a single blinded laboratory. A discovery set was first analyzed to update the historical GAG score. The sensitivity of the new GAG score for RCC detection versus healthy subjects was validated using the remaining samples. The correlation of the new GAG score to histopathologic variables, overall survival, and recurrence-free survival was evaluated using nonparametric and log-rank tests and multivariable Cox regression analyses. Results and limitations: The RCC cohort included 94 stage I, 58 stage II–III, and 22 stage IV cases. In the first discovery set (n = 67), the new GAG score distinguished RCC from healthy samples with an area under the receiver operating characteristic curve (AUC) of 0.999. In the validation set (n = 108), the GAG score achieved an AUC of 0.991, with 93.5% sensitivity. GAG scores were elevated in RCC compared to healthy samples, irrespective of and uncorrelated to stage, grade, histology, age, or gender. The total chondroitin sulfate concentration was an independent prognostic factor for both overall and recurrence-free survival (hazard ratios 1.51 and 1.25) with high concordance when combined with variables available at pathologic diagnosis (C-index 0.926 and 0.849) or preoperatively (C-index 0.846 and 0.736). Limitations of the study include its retrospective nature and moderate variability in GAG laboratory measurements. Conclusions: Plasma GAGs are highly sensitive diagnostic and prognostic biomarkers in surgically treated RCC independent of stage, grade, or histology. Prospective validation studies on GAG scores for early detection, prediction, and surveillance for RCC recurrence are thus warranted. Patient summary: In this study, we examined if a new molecular blood test can detect renal cell carcinoma in the early stages and predict if the cancer might relapse after surgery. The trial is registered on ClinicalTrial.gov as NCT03471897. Plasma glycosaminoglycan measurements aggregated into scores had higher sensitivity for the detection of any-stage renal cell carcinoma and high concordance with survival after surgery.
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17. |
- Gatto, Francesco, 1987, et al.
(författare)
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Prognostic Value of Plasma and Urine glycosaminoglycan scores in clear cell renal cell carcinoma
- 2016
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Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 6:NOV, s. Art. no. 253-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The prognosis of metastatic clear cell renal cell carcinoma (ccRCC) vastly improved since the introduction of antiangiogenic-targeted therapy. However, it is still unclear which biological processes underlie ccRCC aggressiveness and affect prognosis. Here, we checked whether a recently discovered systems biomarker based on plasmatic or urinary measurements of glycosaminoglycans (GAGs) aggregated into diagnostic scores correlated with ccRCC prognosis. Methods: Thirty-one patients with a diagnosis of ccRCC (23 metastatic) were prospectively enrolled, and their urine and plasma biomarker scores were correlated to progression-free survival (PFS) and overall survival (OS) as either a dichotomous ("Low" vs. "High") or a continuous variable in a multivariate survival analysis. Results: The survival difference between "High"-vs. "Low"-scored patients was significant in the case of urine scores (2-year PFS rate = 53.3 vs. 100%, p = 3 x 10(-4) and 2-year OS rate = 73.3 vs. 100%, p = 0.0078) and in the case of OS for plasma scores (2-year PFS rate = 60 vs. 84%, p = 0.0591 and 2-year OS rate = 66.7 vs. 90%, p = 0.0206). In multivariate analysis, the urine biomarker score as a continuous variable was an independent predictor of PFS [hazard ratio (HR): 4.62, 95% CI: 1.66-12.83, p = 0.003] and OS (HR: 10.13, 95% CI: 1.80-57.04, p = 0.009). Conclusion: This is the first report on an association between plasma or urine GAG scores and the prognosis of ccRCC patients. Prospective trials validating the prognostic and predictive role of this novel systems biomarker are warranted.
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18. |
- Gatto, Francesco, 1987, et al.
(författare)
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Systematic analysis of overall survival and interactions between tumor mutations and drug treatment
- 2016
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Ingår i: Journal of Hematology and Oncology. - : Springer Science and Business Media LLC. - 1756-8722. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Few exceptional responses in cancer treatment were attributed to a genetic predisposition of the tumor. Methods: We analyzed a cohort of 3105 patients from 12 different cancer types and systematically sought the existence of a correlation between overall survival and the interaction of 21 antineoplastic treatments with 6 tumor mutations. Results: We identified a single significant correlation resulting in increased overall survival from temozolomide in lower-grade glioma with IDH1 R132H mutations. The trend could not be attributed to either the treatment or the mutation alone. Univariate and multivariate Cox regression demonstrated that this interaction stood as an independent prognostic predictor of survival. Conclusion: Our results suggest infrequent instances of exceptional responses ascribable to tumor genomics yet corroborate the existence of an interaction of temozolomide with IDH1 mutations in lower-grade glioma.
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19. |
- Gatto, Francesco, 1987, et al.
(författare)
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Systematic Analysis Reveals that Cancer Mutations Converge on Deregulated Metabolism of Arachidonate and Xenobiotics
- 2016
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 16:3, s. 878-895
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Tidskriftsartikel (refereegranskat)abstract
- Mutations are the basis of the clonal evolution of most cancers. Nevertheless, a systematic analysis of whether mutations are selected in cancer because they lead to the deregulation of specific biological processes independent of the type of cancer is still lacking. In this study, we correlated the genome and transcriptome of 1,082 tumors. We found that nine commonly mutated genes correlated with substantial changes in gene expression, which primarily converged on metabolism. Further network analyses circumscribed the convergence to a network of reactions, termed AraX, that involves the glutathione- and oxygen-mediated metabolism of arachidonic acid and xenobiotics. In an independent cohort of 4,462 samples, all nine mutated genes were consistently correlated with the deregulation of AraX. Among all of the metabolic pathways, AraX deregulation represented the strongest predictor of patient survival. These findings suggest that oncogenic mutations drive a selection process that converges on the deregulation of the AraX network.
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20. |
- Gatto, Francesco, 1987
(författare)
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The origin of symmetry in the metabolism of cancer – From systems biology to translational medicine
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Why do not we have a cure for cancer yet? Cancer is the malady of the century, the most intensely studied disease of all time. The question is puzzling. It assumes that cancer is a single entity that we can target and eradicate. On the contrary, the current theory on the origin of cancer dictates that each patient bears a cancer that is an exquisite experiment of nature, in which a unique constellation of genetic aberrations confers the cell with malignant traits that enable it to proliferate and survive until death of the host. Nevertheless, the question is legitimate. Cancer is also a single entity because, in spite of the heterogeneity of origins, every individual cancer in its evolution ought to converge in the acquisition of the same malignant traits, e.g. abnormal proliferation and ability to metastasize. I define this phenomenon of convergent evolution as the symmetry of cancer and each of these traits as symmetric, reminiscent of the fact that as diverse as two individual cancers can be in its origin, they can be repositioned along the trait to be identical.This thesis is dedicated to understanding the origin of symmetry of cancer through systems biology. In particular, I focused my interest in a specific malignant trait, the reprogramming of cell metabolism. Metabolic reprogramming in cancer is associated with deregulation of anabolism and energy metabolism to foster rapid cell proliferation and plastic adaptation to enable cell survival. Human metabolism is a complex system, which consists of thousands of biochemical reactions that transform nutrients into energy, building blocks for cell growth (like membrane phospholipids), macromolecules with specialized functions (like hormones), and in general support life by maintaining whole body homeostasis. I sought to explore whether the transformation to cancer entailed some symmetric patterns of regulation of metabolism. In order to undertake an unbiased view of this complex system, I adopted a systems level perspective, in which genome-scale changes of gene and protein expression (so-called omics) attributable to cancer were bridged with the network of reactions that form the backbone of human metabolism. The results were two-fold. First, any cancer seemed to acquire a symmetric overexpression of nucleotide metabolism, regardless from where it originated (Paper I). However, the comparison was performed against the matched healthy tissues of origin, mostly composed of quiescent cells. Therefore we ascribed this symmetry to an adaptation to a metabolic requirement of cellular proliferation. In order to discern what regulatory patterns in metabolism are not adaptive but oncogenic, meaning an obligate metabolic reprogramming to foster evolution, we characterized those gene expression changes occurring in presence of an oncogenic mutation, again irrespective of the tissue of origin or other confounding factor (Paper II). This analysis revealed that oncogenic mutations independently converge on the deregulation of a sub-network revolving around the metabolism of arachidonic acid and xenobiotics mediated by glutathione and oxygen, which we termed AraX. Deregulation of AraX can be associated with a successful engagement of the immune system in tumor evolution, suggesting that the symmetry of cancer metabolism may exclusively rely on reprogramming fluxes to support pro-tumorigenic inflammation. Second, the symmetry of cancer metabolism broke with the most common form of kidney cancer, clear cell renal cell carcinoma (ccRCC). We reported that a ccRCC-specific set of genetic aberrations is associated with the emergence of a uniquely compromised metabolic network (Paper I). These outstanding features of ccRCC metabolism provided an opportunity for translational medicine. We proved that it is possible to exploit ccRCC defective network to predict computationally metabolic liabilities that induce selective cell death in ccRCC (Paper III). Moreover, these changes in metabolic regulation unique to ccRCC can be distilled, through an algorithm of our creation, Kiwi (Paper V), in a coordinated regulation of glycosaminoglycan biosynthesis (GAGs) (Paper IV). This is mirrored by an altered profile of GAGs in kidney-proximal fluids, urine and blood, that we prove bearing a strong, accurate, and robust diagnostic value in metastatic ccRCC. The case of ccRCC and potential role of inflammation in AraX may raise more doubt than support on the existence of symmetry in the metabolic reprogramming in any cancer cell (Paper VI). Perhaps researchers are simply observing an enhanced plasticity in the adaptation to ever-changing conditions that is induced by mutations, but which is not symmetric under any specific trait and as such not essential to cancer. Yet, I argue that the quest for searching the symmetry in cancer should not be abandoned. This quest is in my opinion of paramount importance to unlock the discovery of a cure for cancer.
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21. |
- Gatto, Francesco, 1987, et al.
(författare)
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Urinary Free Glycosaminoglycans Identify Adults at High Risk of Developing Early-stage High-grade Bladder Cancer
- 2024
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Ingår i: European Urology Open Science. - 2666-1683 .- 2666-1691. ; 68, s. 40-47
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Screening for bladder cancer (BCa) could reduce mortality via early detection of early-stage high-grade (Ta/T1 N0 M0 grade 2–3) disease. Noninvasive biomarkers could aid in screening, but current markers lack the specificity required. The urinary free glycosaminoglycan profile (GAGome) is a promising biomarker for early detection of BCa metabolism. Methods: In a prospective case-control development study, we included patients with BCa or no evidence of disease (NED) and measured the urinary GAGome. We then developed a score to predict the probability of BCa using GAGome features that correlated with BCa versus NED according to Bayesian regression. Next, in a retrospective, population-based, case-control study, we included adults from the Lifelines Cohort Study who were presumed healthy at baseline. All cases with BCa confirmed in the cancer registry by the 2-yr or 6-yr study visit were matched to randomly selected control subjects. We developed a reference logistic regression model using age and sex to predict BCa at 7 yr after baseline. We then added the GAGome score to the model and assessed model improvement using the likelihood ratio test. We dichotomized outputs for the reference model and saturated model (reference + GAGome score) into high-risk versus low-risk categories using a 99% specificity cutoff and estimated the sensitivity for association with BCa at 7 yr. Key findings and limitations: We prospectively included 51 individuals with BCa and 38 with NED and observed alterations in three GAGome features compatible with BCa. We developed a score that discriminated BCa with an area under the receiver operating characteristic curve of 0.77 (95% confidence interval [CI] 0.67–0.87). We retrospectively selected a cohort of 1088 presumed healthy adults (median age 48 yr, 56% females), of whom 48 had developed BCa by 7 yr after baseline (median time to diagnosis 1.4 yr). The GAGome score was an independent predictor of BCa at 7 yr when added to the reference model (p < 0.001). The sensitivity for BCa at 7 yr for high-risk subjects was 31% (95% CI 20–43%) using the saturated model and 17% (95% CI 4.7–29%) using the reference model at 99% specificity (95% CI 98–99%). Conclusions and clinical implications: The urinary free GAGome is specifically altered in BCa and can be used for noninvasive identification of adults at high risk of developing BCa, independent of age and sex. This information could be useful for the design of risk-stratified targeted screening programs for BCa. Patient summary: We tested whether measurement of a class of sugars called glycosaminoglycans (GAGs) in urine could be used for early detection of bladder cancer. Our results show that GAG levels in urine can distinguish people at high risk of developing bladder cancer within 7 years, even if they are healthy at the time of the urine sampling.
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23. |
- Lahtvee, Petri-Jaan, 1985, et al.
(författare)
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Absolute Quantification of Protein and mRNA Abundances Demonstrate Variability in Gene-Specific Translation Efficiency in Yeast
- 2017
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Ingår i: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 4:5, s. 495-504.e5
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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24. |
- Limeta, Angelo, 1996, et al.
(författare)
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Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors
- 2023
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Ingår i: Computational and Structural Biotechnology Journal. - 2001-0370. ; 21, s. 3912-3919
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Forskningsöversikt (refereegranskat)abstract
- A long-standing goal of personalized and precision medicine is to enable accurate prediction of the outcomes of a given treatment regimen for patients harboring a disease. Currently, many clinical trials fail to meet their endpoints due to underlying factors in the patient population that contribute to either poor responses to the drug of interest or to treatment-related adverse events. Identifying these factors beforehand and correcting for them can lead to an increased success of clinical trials. Comprehensive and large-scale data gathering efforts in biomedicine by omics profiling of the healthy and diseased individuals has led to a treasure-trove of host, disease and environmental factors that contribute to the effectiveness of drugs aiming to treat disease. With increasing omics data, artificial intelligence allows an in-depth analysis of big data and offers a wide range of applications for real-world clinical use, including improved patient selection and identification of actionable targets for companion therapeutics for improved translatability across more patients. As a blueprint for complex drug-disease-host interactions, we here discuss the challenges of utilizing omics data for predicting responses and adverse events in cancer immunotherapy with immune checkpoint inhibitors (ICIs). The omics-based methodologies for improving patient outcomes as in the ICI case have also been applied across a wide-range of complex disease settings, exemplifying the use of omics for in-depth disease profiling and clinical use.
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25. |
- Limeta, Angelo, 1996, et al.
(författare)
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Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma.
- 2020
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Ingår i: JCI insight. - : American Society for Clinical Investigation. - 2379-3708. ; 5:23
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUNDIdentifying 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.METHODSWe 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.RESULTSOur 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).CONCLUSIONThese results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes.FUNDINGThis work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden.
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