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Antti, Henrik
Alternative names
Publications (10 of 96) Show all publications
Zborayova, K., Antti, H., Blomqvist, L., Flygare, L., Gebre-Medhin, M., Jonsson, J., . . . Zackrisson, B. (2019). Early changes in multiparametric imaging parameters during radiotherapy of squamous carcinoma. Paper presented at 7th International Congress on Innovative Approaches in Head and Neck Oncology (ICHNO), Barcelona, SPAIN, MAR 14-16, 2019.. Radiotherapy and Oncology, 132, 63-63
Open this publication in new window or tab >>Early changes in multiparametric imaging parameters during radiotherapy of squamous carcinoma
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2019 (English)In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 132, p. 63-63Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
Elsevier, 2019
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-158753 (URN)10.1016/S0167-8140(19)30289-0 (DOI)000463820400107 ()
Conference
7th International Congress on Innovative Approaches in Head and Neck Oncology (ICHNO), Barcelona, SPAIN, MAR 14-16, 2019.
Note

Supplement 1.

Available from: 2019-05-15 Created: 2019-05-15 Last updated: 2019-05-15Bibliographically approved
Antti, H. & Sellstedt, M. (2018). Cell-Based Kinetic Target-Guided Synthesis of an Enzyme Inhibitor. ACS Medicinal Chemistry Letters, 9(4), 351-353
Open this publication in new window or tab >>Cell-Based Kinetic Target-Guided Synthesis of an Enzyme Inhibitor
2018 (English)In: ACS Medicinal Chemistry Letters, ISSN 1948-5875, E-ISSN 1948-5875, Vol. 9, no 4, p. 351-353Article in journal (Refereed) Published
Abstract [en]

Finding a new drug candidate for a selected target is an expensive and time-consuming process. Target guided-synthesis, or in situ click chemistry, is a concept where the drug target is used to template the formation of its own inhibitors from reactive building blocks. This could simplify the identification of drug candidates. However, with the exception of one example of an RNA-target, target-guided synthesis has always employed purified targets. This limits the number of targets that can be screened by the method. By applying methods from the field of metabolomics, we demonstrate that target-guided synthesis with protein targets also can be performed directly in cell-based systems. These methods offer new possibilities to conduct screening for drug candidates of difficult protein targets in cellular environments.

Keywords
target-guided synthesis, in situ click chemistry, enzyme catalysis, drug discovery
National Category
Medicinal Chemistry
Identifiers
urn:nbn:se:umu:diva-147832 (URN)10.1021/acsmedchemlett.7b00535 (DOI)000430256200010 ()29670699 (PubMedID)
Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-06-09Bibliographically approved
Näsström, E., Jonsson, P., Johansson, A., Dongol, S., Karkey, A., Basnyat, B., . . . Baker, S. (2018). Diagnostic metabolite biomarkers of chronic typhoid carriage. PLoS Neglected Tropical Diseases, 12(1), Article ID e0006215.
Open this publication in new window or tab >>Diagnostic metabolite biomarkers of chronic typhoid carriage
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2018 (English)In: PLoS Neglected Tropical Diseases, ISSN 1935-2727, E-ISSN 1935-2735, Vol. 12, no 1, article id e0006215Article in journal (Refereed) Published
Abstract [en]

Background: Salmonella Typhi and Salmonella Paratyphi A are the agents of enteric (typhoid) fever; both can establish chronic carriage in the gallbladder. Chronic Salmonella carriers are typically asymptomatic, intermittently shedding bacteria in the feces, and contributing to disease transmission. Detecting chronic carriers is of public health relevance in areas where enteric fever is endemic, but there are no routinely used methods for prospectively identifying those carrying Salmonella in their gallbladder.

Methodology/Principal findings: Here we aimed to identify biomarkers of Salmonella carriage using metabolite profiling. We performed metabolite profiling on plasma from Nepali patients undergoing cholecystectomy with confirmed S. Typhi or S. Paratyphi A gallbladder carriage (and non-carriage controls) using two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS) and supervised pattern recognition modeling. We were able to significantly discriminate Salmonella carriage samples from non-carriage control samples. We were also able to detect differential signatures between S. Typhi and S. Paratyphi A carriers. We additionally compared carriage metabolite profiles with profiles generated during acute infection; these data revealed substantial heterogeneity between metabolites associated with acute enteric fever and chronic carriage. Lastly, we found that Salmonella carriers could be significantly distinguished from non-carriage controls using only five metabolites, indicating the potential of these metabolites as diagnostic markers for detecting chronic Salmonella carriers.

Conclusions/Significance: Our novel approach has highlighted the potential of using metabolomics to search for diagnostic markers of chronic Salmonella carriage. We suggest further epidemiological investigations of these potential biomarkers in alternative endemic enteric fever settings.

National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-145618 (URN)10.1371/journal.pntd.0006215 (DOI)000424022700063 ()29373578 (PubMedID)
Funder
Swedish Research Council, VR-U 2015-03442
Available from: 2018-04-17 Created: 2018-04-17 Last updated: 2018-06-09Bibliographically approved
Antti, H. & Sellstedt, M. (2018). Metabolic effects of an aspartate aminotransferase-inhibitor on two T-cell lines. PLoS ONE, 13(12), Article ID e0208025.
Open this publication in new window or tab >>Metabolic effects of an aspartate aminotransferase-inhibitor on two T-cell lines
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 12, article id e0208025Article in journal (Refereed) Published
Abstract [en]

An emerging method to help elucidate the mode of action of experimental drugs is to use untargeted metabolomics of cell-systems. The interpretations of such screens are however complex and more examples with inhibitors of known targets are needed. Here two T-cell lines were treated with an inhibitor of aspartate aminotransferase and analyzed with untargeted GC-MS. The interpretation of the data was enhanced by the use of two different cell-lines and supports aspartate aminotransferase as a target. In addition, the data suggest an unexpected off-target effect on glutamate decarboxylase. The results exemplify the potency of metabolomics to provide insight into both mode of action and off-target effects of drug candidates.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2018
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-154872 (URN)10.1371/journal.pone.0208025 (DOI)000452640900007 ()30532126 (PubMedID)2-s2.0-85058105205 (Scopus ID)
Available from: 2019-01-04 Created: 2019-01-04 Last updated: 2019-01-04Bibliographically approved
Mörén, L., Perryman, R., Crook, T., Langer, J. K., Oneill, K., Syed, N. & Antti, H. (2018). Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM. BMC Cancer, 18, Article ID 167.
Open this publication in new window or tab >>Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM
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2018 (English)In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 18, article id 167Article in journal (Refereed) Published
Abstract [en]

Background: Tumour cells have a high demand for arginine. However, a subset of glioblastomas has a defect in the arginine biosynthetic pathway due to epigenetic silencing of the rate limiting enzyme argininosuccinate synthetase (ASS1). These tumours are auxotrophic for arginine and susceptible to the arginine degrading enzyme, pegylated arginine deiminase (ADI-PEG20). Moreover, ASS1 deficient GBM have a worse prognosis compared to ASS1 positive tumours. Since altered tumour metabolism is one of the hallmarks of cancer we were interested to determine if these two subtypes exhibited different metabolic profiles that could allow for their non-invasive detection as well as unveil additional novel therapeutic opportunities.

Methods: We looked for basal metabolic differences using one and two-dimensional gas chromatography-time-of-flight mass spectrometry (1D/2DGC-TOFMS) followed by targeted analysis of 29 amino acids using liquid chromatography-time-of-flight mass spectrometry (LC-TOFMS). We also looked for differences upon arginine deprivation in a single ASS1 negative and positive cell line (SNB19 and U87 respectively). The acquired data was evaluated by chemometric based bioinformatic methods.

Results: Orthogonal partial least squares-discriminant analysis (OPLS-DA) of both the 1D and 2D GC-TOFMS data revealed significant systematic difference in metabolites between the two subgroups with ASS1 positive cells generally exhibiting an overall elevation of identified metabolites, including those involved in the arginine biosynthetic pathway. Pathway and network analysis of the metabolite profile show that ASS1 negative cells have altered arginine and citrulline metabolism as well as altered amino acid metabolism. As expected, we observed significant metabolite perturbations in ASS negative cells in response to ADI-PEG20 treatment.

Conclusions: This study has highlighted significant differences in the metabolome of ASS1 negative and positive GBM which warrants further study to determine their diagnostic and therapeutic potential for the treatment of this devastating disease.

Place, publisher, year, edition, pages
BioMed Central, 2018
Keywords
Glioblastoma, Epigenetics, ASS1, Arginine, ADI-PEG20, Metabolomics, Chemometrics
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-145374 (URN)10.1186/s12885-018-4040-3 (DOI)000424776100003 ()29422017 (PubMedID)
Note

Errata: Mörén L., Perryman R., Crook T., Langer J. K., Oneill K., Syed N., Antti H. Correction to: Metabolomic profilingidentifies distinct phenotypes for ASS1positive and negative GBM. BMC Cancer. 2018;18:268. DOI: 10.1186/s12885-018-4128-9

Available from: 2018-03-09 Created: 2018-03-09 Last updated: 2018-06-09Bibliographically approved
Franklin, O., Jonsson, P., Billing, O., Lundberg, E., Öhlund, D., Nyström, H., . . . Sund, M. (2018). Plasma micro-RNA alterations appear late in pancreatic cancer. Annals of Surgery, 267(4), 775-781
Open this publication in new window or tab >>Plasma micro-RNA alterations appear late in pancreatic cancer
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2018 (English)In: Annals of Surgery, ISSN 0003-4932, E-ISSN 1528-1140, Vol. 267, no 4, p. 775-781Article in journal (Refereed) Published
Abstract [en]

Objectives: The aim of this research was to study whether plasma microRNAs (miRNA) can be used for early detection of pancreatic cancer (PC) by analyzing prediagnostic plasma samples collected before a PC diagnosis. Background: PC has a poor prognosis due to late presenting symptoms and early metastasis. Circulating miRNAs are altered in PC at diagnosis but have not been evaluated in a prediagnostic setting. Methods: We first performed an initial screen using a panel of 372 miRNAs in a retrospective case-control cohort that included early-stage PC patients and healthy controls. Significantly altered miRNAs at diagnosis were then measured in an early detection case-control cohort wherein plasma samples in the cases are collected before a PC diagnosis. Carbohydrate antigen 19–9 (Ca 19–9) levels were measured in all samples for comparison. Results: Our initial screen, including 23 stage I-II PC cases and 22 controls, revealed 15 candidate miRNAs that were differentially expressed in plasma samples at PC diagnosis. We combined all 15 miRNAs into a multivariate statistical model, which outperformed Ca 19–9 in receiver-operating characteristics analysis. However, none of the candidate miRNAs, individually or in combination, were significantly altered in prediagnostic plasma samples from 67 future PC patients compared with 132 matched controls. In comparison, Ca 19–9 levels were significantly higher in the cases at <5 years before diagnosis. Conclusion: Plasma miRNAs are altered in PC patients at diagnosis, but the candidate miRNAs found in this study appear late in the course of the disease and cannot be used for early detection of the disease.

Keywords
blood samples, early detection, micro-RNA, miRNA, pancreatic cancer
National Category
Clinical Laboratory Medicine Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-127998 (URN)10.1097/SLA.0000000000002124 (DOI)000435846900046 ()28425921 (PubMedID)2-s2.0-85044257717 (Scopus ID)
Note

Originally included in thesis in manuscript form.

Available from: 2016-11-21 Created: 2016-11-21 Last updated: 2018-09-27Bibliographically approved
Björkblom, B., Jonsson, P., Späth, F., Melin, B. S. & Antti, H. (2018). PRE-DIAGNOSTIC PLASMA METABOLITES LINKED TO FUTURE BRAIN TUMOR DEVELOPMENT. Paper presented at 13th Meeting of the European-Association-of-Neurooncology (EANO), OCT 10-14, 2018, Stockholm, SWEDEN. Neuro-Oncology, 20, 288-289
Open this publication in new window or tab >>PRE-DIAGNOSTIC PLASMA METABOLITES LINKED TO FUTURE BRAIN TUMOR DEVELOPMENT
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2018 (English)In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 20, p. 288-289Article in journal, Meeting abstract (Other academic) Published
Abstract [en]

BACKGROUND: The Northern Sweden Health and Disease Study is a unique population-based biobank linked to the clinical data registries. The samples originate from over 133 000 individuals living in the northern part of Sweden, and primarily collected during health checkups from the age of 40 years. Our project aims to investigate alterations in metabolite signatures in blood plasma of healthy blood donors that later in life developed a tumor. Brain tumors, especially glioblastoma is associated with poor prognosis. To explore early events of metabolic reprograming linked to future diagnosis, we investigated alterations in metabolite concentrations in plasma collected several years before diagnosis with matched healthy controls. MATERIALS AND METHODS: In total 392 analytical samples (256 repeated timepoint and 136 single timepoint, case-control samples) were analyzed using GCTOFMS. Constrained randomization of run order was utilized to maximize information output and minimize the false discovery rate. By use of reference databases, we could with high confidence quantify and identify 150 plasma metabolites. We detected metabolites with significant alterations in concertation between pre-clinical glioma cases and healthy controls by the effect projection approach based on orthogonal partial least squares (OPLSEP). RESULTS AND CONCLUSIONS: For the repeated blood samples, we designed and applied a novel multivariate strategy for high resolution biomarker pattern discovery. We utilize the fact that we have available samples from two repeated time points prior to diagnosis for each future glioma case and their matched controls to construct a small design of experiment (DoE) of four samples for each match pair. The data for each individual DoE was evaluated by OPLS-EP to determine the effect of each individual metabolite in relation to control-case, time and their interaction. Finally, latent significance calculations by means of OPLS were used to extract and evaluate the correct latent biomarker and highlight true significance of individual metabolites. Our study presents an approach to minimize confounding effects due to systematic noise from sampling, the analytical method, as well as take into account personalized metabolic levels over time, enabling biomarker detection within a smaller sample group. We will present and discuss the latest results and biomarkers from this exploratory metabolomics study at the meeting

Place, publisher, year, edition, pages
OXFORD UNIV PRESS INC, 2018
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-157548 (URN)10.1093/neuonc/noy139.277 (DOI)000460645600279 ()
Conference
13th Meeting of the European-Association-of-Neurooncology (EANO), OCT 10-14, 2018, Stockholm, SWEDEN
Available from: 2019-03-26 Created: 2019-03-26 Last updated: 2019-03-26Bibliographically approved
Näsström, E., Parry, C. M., Thieu, N. T., Maude, R. R., de Jong, H. K., Fukushima, M., . . . Baker, S. (2017). Reproducible diagnostic metabolites in plasma from typhoid fever patients in Asia and Africa. eLIFE, 6, Article ID e15651.
Open this publication in new window or tab >>Reproducible diagnostic metabolites in plasma from typhoid fever patients in Asia and Africa
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2017 (English)In: eLIFE, E-ISSN 2050-084X, Vol. 6, article id e15651Article in journal (Refereed) Published
Abstract [en]

Salmonella Typhi is the causative agent of typhoid. Typhoid is diagnosed by blood culture, a method that lacks sensitivity, portability and speed. We have previously shown that specific metabolomic profiles can be detected in the blood of typhoid patients from Nepal (Nasstrom et al., 2014). Here, we performed mass spectrometry on plasma from Bangladeshi and Senegalese patients with culture confirmed typhoid fever, clinically suspected typhoid, and other febrile diseases including malaria. After applying supervised pattern recognition modelling, we could significantly distinguish metabolite profiles in plasma from the culture confirmed typhoid patients. After comparing the direction of change and degree of multivariate significance, we identified 24 metabolites that were consistently up- or down regulated in a further Bangladeshi/Senegalese validation cohort, and the Nepali cohort from our previous work. We have identified and validated a metabolite panel that can distinguish typhoid from other febrile diseases, providing a new approach for typhoid diagnostics.

Place, publisher, year, edition, pages
eLife Sciences Publications, 2017
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-135532 (URN)10.7554/eLife.15651 (DOI)000400828100001 ()
Available from: 2017-06-13 Created: 2017-06-13 Last updated: 2018-06-09Bibliographically approved
Mörén, L., Wibom, C., Bergström, P., Johansson, M., Antti, H. & Bergenheim, A. T. (2016). Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas. Radiation Oncology, 11, Article ID 51.
Open this publication in new window or tab >>Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas
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2016 (English)In: Radiation Oncology, ISSN 1748-717X, E-ISSN 1748-717X, Vol. 11, article id 51Article in journal (Refereed) Published
Abstract [en]

Background: Glioblastomas progress rapidly making response evaluation using MRI insufficient since treatment effects are not detectable until months after initiation of treatment. Thus, there is a strong need for supplementary biomarkers that could provide reliable and early assessment of treatment efficacy. Analysis of alterations in the metabolome may be a source for identification of new biomarker patterns harboring predictive information. Ideally, the biomarkers should be found within an easily accessible compartment such as the blood. Method: Using gas-chromatographic-time-of-flight-mass spectroscopy we have analyzed serum samples from 11 patients with glioblastoma during the initial phase of radiotherapy. Fasting serum samples were collected at admittance, on the same day as, but before first treatment and in the morning after the second and fifth dose of radiation. The acquired data was analyzed and evaluated by chemometrics based bioinformatics methods. Our findings were compared and discussed in relation to previous data from microdialysis in tumor tissue, i.e. the extracellular compartment, from the same patients. Results: We found a significant change in metabolite pattern in serum comparing samples taken before radiotherapy to samples taken during early radiotherapy. In all, 68 metabolites were lowered in concentration following treatment while 16 metabolites were elevated in concentration. All detected and identified amino acids and fatty acids together with myo-inositol, creatinine, and urea were among the metabolites that decreased in concentration during treatment, while citric acid was among the metabolites that increased in concentration. Furthermore, when comparing results from the serum analysis with findings in tumor extracellular fluid we found a common change in metabolite patterns in both compartments on an individual patient level. On an individual metabolite level similar changes in ornithine, tyrosine and urea were detected. However, in serum, glutamine and glutamate were lowered after treatment while being elevated in the tumor extracellular fluid. Conclusion: Cross-validated multivariate statistical models verified that the serum metabolome was significantly changed in relation to radiation in a similar pattern to earlier findings in tumor tissue. However, all individual changes in tissue did not translate into changes in serum. Our study indicates that serum metabolomics could be of value to investigate as a potential marker for assessing early response to radiotherapy in malignant glioma.

Place, publisher, year, edition, pages
BioMed Central, 2016
Keywords
Glioblastoma, Radiation therapy, Treatment response, Metabolomics, Chemometrics
National Category
Cancer and Oncology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-119631 (URN)10.1186/s13014-016-0626-6 (DOI)000373185900001 ()27039175 (PubMedID)
Available from: 2016-05-20 Created: 2016-04-25 Last updated: 2018-06-07Bibliographically approved
Björkblom, B., Wibom, C., Jonsson, P., Mörén, L., Andersson, U., Johannesen, T. B., . . . Melin, B. (2016). Metabolomic screening of pre-diagnostic serum samples identifies association between alpha- and gamma-tocopherols and glioblastoma risk. OncoTarget, 7(24), 37043-37053
Open this publication in new window or tab >>Metabolomic screening of pre-diagnostic serum samples identifies association between alpha- and gamma-tocopherols and glioblastoma risk
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2016 (English)In: OncoTarget, ISSN 1949-2553, E-ISSN 1949-2553, Vol. 7, no 24, p. 37043-37053Article in journal (Refereed) Published
Abstract [en]

Glioblastoma is associated with poor prognosis with a median survival of one year. High doses of ionizing radiation is the only established exogenous risk factor. To explore new potential biological risk factors for glioblastoma, we investigated alterations in metabolite concentrations in pre-diagnosed serum samples from glioblastoma patients diagnosed up to 22 years after sample collection, and undiseased controls. The study points out a latent biomarker for future glioblastoma consisting of nine metabolites (gamma-tocopherol, alpha-tocopherol, erythritol, erythronic acid, myo-inositol, cystine, 2-keto-L-gluconic acid, hypoxanthine and xanthine) involved in antioxidant metabolism. We detected significantly higher serum concentrations of alpha-tocopherol (p=0.0018) and gamma-tocopherol (p=0.0009) in future glioblastoma cases. Compared to their matched controls, the cases showed a significant average fold increase of alpha- and gamma-tocopherol levels: 1.2 for alpha-T (p=0.018) and 1.6 for gamma-T (p=0.003). These tocopherol levels were associated with a glioblastoma odds ratio of 1.7 (alpha-T, 95% CI: 1.0-3.0) and 2.1 (gamma-T, 95% CI: 1.2-3.8). Our exploratory metabolomics study detected elevated serum levels of a panel of molecules with antioxidant properties as well as oxidative stress generated compounds. Additional studies are necessary to confirm the association between the observed serum metabolite pattern and future glioblastoma development.

Keywords
population-based, serum metabolite, vitamin E, antioxidants, brain tumor
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-123973 (URN)10.18632/oncotarget.9242 (DOI)000377756800119 ()
Available from: 2016-11-15 Created: 2016-07-07 Last updated: 2018-06-09Bibliographically approved
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