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Items: 46

1.

TP53 outperforms other androgen receptor biomarkers to predict abiraterone or enzalutamide outcome in metastatic castration-resistant prostate cancer.

De Laere B, Oeyen S, Mayrhofer M, Whitington T, van Dam PJ, Van Oyen P, Ghysel C, Ampe J, Ost P, Demey W, Hoekx L, Schrijvers D, Brouwers B, Lybaert W, Everaert EG, De Maeseneer D, Strijbos M, Bols A, Fransis K, Beije N, de Kruijff IE, van Dam V, Brouwer A, Goossens D, Heyrman L, Van den Eynden GG, Rutten A, Del Favero J, Rantalainen M, Rajan P, Sleijfer S, Ullén A, Yachnin J, Grönberg H, Van Laere SJ, Lindberg J, Dirix LY.

Clin Cancer Res. 2018 Sep 12. pii: clincanres.1943.2018. doi: 10.1158/1078-0432.CCR-18-1943. [Epub ahead of print]

PMID:
30209161
2.

Expression levels of long non-coding RNAs are prognostic for AML outcome.

Mer AS, Lindberg J, Nilsson C, Klevebring D, Wang M, Grönberg H, Lehmann S, Rantalainen M.

J Hematol Oncol. 2018 Apr 7;11(1):52. doi: 10.1186/s13045-018-0596-2.

3.

Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer.

Robertson S, Stålhammar G, Darai-Ramqvist E, Rantalainen M, Tobin NP, Bergh J, Hartman J.

J Clin Pathol. 2018 Sep;71(9):787-794. doi: 10.1136/jclinpath-2017-204976. Epub 2018 Mar 27.

PMID:
29588372
4.

Development and Validation of a Novel RNA Sequencing-Based Prognostic Score for Acute Myeloid Leukemia.

Wang M, Lindberg J, Klevebring D, Nilsson C, Lehmann S, Grönberg H, Rantalainen M.

J Natl Cancer Inst. 2018 Mar 1. doi: 10.1093/jnci/djy021. [Epub ahead of print]

PMID:
29506270
5.

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

Vu TN, Wills QF, Kalari KR, Niu N, Wang L, Pawitan Y, Rantalainen M.

Bioinformatics. 2018 Jul 15;34(14):2392-2400. doi: 10.1093/bioinformatics/bty100.

6.

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer.

Stålhammar G, Robertson S, Wedlund L, Lippert M, Rantalainen M, Bergh J, Hartman J.

Histopathology. 2018 May;72(6):974-989. doi: 10.1111/his.13452. Epub 2018 Feb 14.

PMID:
29220095
7.

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling.

Karthik GM, Rantalainen M, Stålhammar G, Lövrot J, Ullah I, Alkodsi A, Ma R, Wedlund L, Lindberg J, Frisell J, Bergh J, Hartman J.

BMC Cancer. 2017 Nov 29;17(1):802. doi: 10.1186/s12885-017-3815-2.

8.

Application of single-cell sequencing in human cancer.

Rantalainen M.

Brief Funct Genomics. 2018 Jul 1;17(4):273-282. doi: 10.1093/bfgp/elx036.

9.

Assessment of Breast Cancer Risk Factors Reveals Subtype Heterogeneity.

Holm J, Eriksson L, Ploner A, Eriksson M, Rantalainen M, Li J, Hall P, Czene K.

Cancer Res. 2017 Jul 1;77(13):3708-3717. doi: 10.1158/0008-5472.CAN-16-2574. Epub 2017 May 16.

10.

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.

Spjuth O, Karlsson A, Clements M, Humphreys K, Ivansson E, Dowling J, Eklund M, Jauhiainen A, Czene K, Grönberg H, Sparén P, Wiklund F, Cheddad A, Pálsdóttir Þ, Rantalainen M, Abrahamsson L, Laure E, Litton JE, Palmgren J.

J Am Med Inform Assoc. 2017 Sep 1;24(5):950-957. doi: 10.1093/jamia/ocx038.

PMID:
28444384
11.

Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling.

Wang M, Lindberg J, Klevebring D, Nilsson C, Mer AS, Rantalainen M, Lehmann S, Grönberg H.

Leukemia. 2017 Oct;31(10):2029-2036. doi: 10.1038/leu.2017.48. Epub 2017 Feb 7.

12.

Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers.

Rantalainen M, Klevebring D, Lindberg J, Ivansson E, Rosin G, Kis L, Celebioglu F, Fredriksson I, Czene K, Frisell J, Hartman J, Bergh J, Grönberg H.

Sci Rep. 2016 Nov 30;6:38037. doi: 10.1038/srep38037.

13.

Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes.

Li J, Ivansson E, Klevebring D, Tobin NP, Lindström LS, Holm J, Prochazka G, Cristando C, Palmgren J, Törnberg S, Humphreys K, Hartman J, Frisell J, Rantalainen M, Lindberg J, Hall P, Bergh J, Grönberg H, Czene K.

Clin Cancer Res. 2017 May 15;23(10):2584-2592. doi: 10.1158/1078-0432.CCR-16-0967. Epub 2016 Sep 1.

14.

Reprogramming Tumor-Associated Macrophages by Antibody Targeting Inhibits Cancer Progression and Metastasis.

Georgoudaki AM, Prokopec KE, Boura VF, Hellqvist E, Sohn S, Östling J, Dahan R, Harris RA, Rantalainen M, Klevebring D, Sund M, Brage SE, Fuxe J, Rolny C, Li F, Ravetch JV, Karlsson MC.

Cell Rep. 2016 May 31;15(9):2000-11. doi: 10.1016/j.celrep.2016.04.084. Epub 2016 May 19.

15.

Determining breast cancer histological grade from RNA-sequencing data.

Wang M, Klevebring D, Lindberg J, Czene K, Grönberg H, Rantalainen M.

Breast Cancer Res. 2016 May 10;18(1):48. doi: 10.1186/s13058-016-0710-8.

16.

Beta-Poisson model for single-cell RNA-seq data analyses.

Vu TN, Wills QF, Kalari KR, Niu N, Wang L, Rantalainen M, Pawitan Y.

Bioinformatics. 2016 Jul 15;32(14):2128-35. doi: 10.1093/bioinformatics/btw202. Epub 2016 Apr 19.

PMID:
27153638
17.

Digital image analysis outperforms manual biomarker assessment in breast cancer.

Stålhammar G, Fuentes Martinez N, Lippert M, Tobin NP, Mølholm I, Kis L, Rosin G, Rantalainen M, Pedersen L, Bergh J, Grunkin M, Hartman J.

Mod Pathol. 2016 Apr;29(4):318-29. doi: 10.1038/modpathol.2016.34. Epub 2016 Feb 26.

18.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

Mer AS, Klevebring D, Grönberg H, Rantalainen M.

Sci Rep. 2016 Feb 1;6:20200. doi: 10.1038/srep20200.

19.

Robust Linear Models for Cis-eQTL Analysis.

Rantalainen M, Lindgren CM, Holmes CC.

PLoS One. 2015 May 18;10(5):e0127882. doi: 10.1371/journal.pone.0127882. eCollection 2015.

20.

An Integrated Bioinformatics Approach for Identifying Genetic Markers that Predict Cerebrospinal Fluid Biomarker p-tau181/Aβ1-42 Ratio in ApoE4-Negative Mild Cognitive Impairment Patients.

Sun Y, Bresell A, Rantalainen M, Höglund K, Lebouvier T, Salter H; Alzheimer Disease Neuroimaging Initiative.

J Alzheimers Dis. 2015;45(4):1061-76. doi: 10.3233/JAD-142118.

PMID:
25720397
21.

Combining metabonomics and other -omics data.

Rantalainen M.

Methods Mol Biol. 2015;1277:147-59. doi: 10.1007/978-1-4939-2377-9_12.

PMID:
25677153
22.

Integrative transcriptomic and metabonomic molecular profiling of colonic mucosal biopsies indicates a unique molecular phenotype for ulcerative colitis.

Rantalainen M, Bjerrum JT, Olsen J, Nielsen OH, Wang Y.

J Proteome Res. 2015 Jan 2;14(1):479-90. doi: 10.1021/pr500699h. Epub 2014 Oct 27.

PMID:
25283053
23.

Integration of transcriptomics and metabonomics: improving diagnostics, biomarker identification and phenotyping in ulcerative colitis.

Bjerrum JT, Rantalainen M, Wang Y, Olsen J, Nielsen OH.

Metabolomics. 2014;10(2):280-290. doi: 10.1007/s11306-013-0580-3. Epub 2013 Aug 21.

24.

The presence of methylation quantitative trait loci indicates a direct genetic influence on the level of DNA methylation in adipose tissue.

Drong AW, Nicholson G, Hedman AK, Meduri E, Grundberg E, Small KS, Shin SY, Bell JT, Karpe F, Soranzo N, Spector TD, McCarthy MI, Deloukas P, Rantalainen M, Lindgren CM; MolPAGE Consortia.

PLoS One. 2013;8(2):e55923. doi: 10.1371/journal.pone.0055923. Epub 2013 Feb 19.

25.

Systems responses of rats to mequindox revealed by metabolic and transcriptomic profiling.

Zhao XJ, Hao F, Huang C, Rantalainen M, Lei H, Tang H, Wang Y.

J Proteome Res. 2012 Sep 7;11(9):4712-21. doi: 10.1021/pr300533a. Epub 2012 Aug 15.

PMID:
22845897
26.

Extent, causes, and consequences of small RNA expression variation in human adipose tissue.

Parts L, Hedman ÅK, Keildson S, Knights AJ, Abreu-Goodger C, van de Bunt M, Guerra-Assunção JA, Bartonicek N, van Dongen S, Mägi R, Nisbet J, Barrett A, Rantalainen M, Nica AC, Quail MA, Small KS, Glass D, Enright AJ, Winn J; MuTHER Consortium, Deloukas P, Dermitzakis ET, McCarthy MI, Spector TD, Durbin R, Lindgren CM.

PLoS Genet. 2012;8(5):e1002704. doi: 10.1371/journal.pgen.1002704. Epub 2012 May 10.

27.

MicroRNA expression in abdominal and gluteal adipose tissue is associated with mRNA expression levels and partly genetically driven.

Rantalainen M, Herrera BM, Nicholson G, Bowden R, Wills QF, Min JL, Neville MJ, Barrett A, Allen M, Rayner NW, Fleckner J, McCarthy MI, Zondervan KT, Karpe F, Holmes CC, Lindgren CM.

PLoS One. 2011;6(11):e27338. doi: 10.1371/journal.pone.0027338. Epub 2011 Nov 15.

28.

Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model.

Kato BS, Nicholson G, Neiman M, Rantalainen M, Holmes CC, Barrett A, Uhlén M, Nilsson P, Spector TD, Schwenk JM.

Proteome Sci. 2011 Nov 17;9:73. doi: 10.1186/1477-5956-9-73.

29.

Accounting for control mislabeling in case-control biomarker studies.

Rantalainen M, Holmes CC.

J Proteome Res. 2011 Dec 2;10(12):5562-7. doi: 10.1021/pr200507b. Epub 2011 Nov 8.

30.

Non-linear modeling of 1H NMR metabonomic data using kernel-based orthogonal projections to latent structures optimized by simulated annealing.

Fonville JM, Bylesjö M, Coen M, Nicholson JK, Holmes E, Lindon JC, Rantalainen M.

Anal Chim Acta. 2011 Oct 31;705(1-2):72-80. doi: 10.1016/j.aca.2011.04.016. Epub 2011 Apr 20.

PMID:
21962350
31.

A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection.

Nicholson G, Rantalainen M, Li JV, Maher AD, Malmodin D, Ahmadi KR, Faber JH, Barrett A, Min JL, Rayner NW, Toft H, Krestyaninova M, Viksna J, Neogi SG, Dumas ME, Sarkans U; MolPAGE Consortium, Donnelly P, Illig T, Adamski J, Suhre K, Allen M, Zondervan KT, Spector TD, Nicholson JK, Lindon JC, Baunsgaard D, Holmes E, McCarthy MI, Holmes CC.

PLoS Genet. 2011 Sep;7(9):e1002270. doi: 10.1371/journal.pgen.1002270. Epub 2011 Sep 8.

32.

Human metabolic profiles are stably controlled by genetic and environmental variation.

Nicholson G, Rantalainen M, Maher AD, Li JV, Malmodin D, Ahmadi KR, Faber JH, Hallgrímsdóttir IB, Barrett A, Toft H, Krestyaninova M, Viksna J, Neogi SG, Dumas ME, Sarkans U, The Molpage Consortium, Silverman BW, Donnelly P, Nicholson JK, Allen M, Zondervan KT, Lindon JC, Spector TD, McCarthy MI, Holmes E, Baunsgaard D, Holmes CC.

Mol Syst Biol. 2011 Aug 30;7:525. doi: 10.1038/msb.2011.57.

33.

Structural shifts of gut microbiota as surrogate endpoints for monitoring host health changes induced by carcinogen exposure.

Wei H, Dong L, Wang T, Zhang M, Hua W, Zhang C, Pang X, Chen M, Su M, Qiu Y, Zhou M, Yang S, Chen Z, Rantalainen M, Nicholson JK, Jia W, Wu D, Zhao L.

FEMS Microbiol Ecol. 2010 Sep;73(3):577-86. doi: 10.1111/j.1574-6941.2010.00924.x. Epub 2010 Jul 7.

34.

Top-down systems biology modeling of host metabotype-microbiome associations in obese rodents.

Waldram A, Holmes E, Wang Y, Rantalainen M, Wilson ID, Tuohy KM, McCartney AL, Gibson GR, Nicholson JK.

J Proteome Res. 2009 May;8(5):2361-75. doi: 10.1021/pr8009885.

PMID:
19275195
35.

Analytic properties of statistical total correlation spectroscopy based information recovery in 1H NMR metabolic data sets.

Alves AC, Rantalainen M, Holmes E, Nicholson JK, Ebbels TM.

Anal Chem. 2009 Mar 15;81(6):2075-84. doi: 10.1021/ac801982h.

36.

K-OPLS package: kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space.

Bylesjö M, Rantalainen M, Nicholson JK, Holmes E, Trygg J.

BMC Bioinformatics. 2008 Feb 19;9:106. doi: 10.1186/1471-2105-9-106.

37.

Piecewise multivariate modelling of sequential metabolic profiling data.

Rantalainen M, Cloarec O, Ebbels TM, Lundstedt T, Nicholson JK, Holmes E, Trygg J.

BMC Bioinformatics. 2008 Feb 19;9:105. doi: 10.1186/1471-2105-9-105.

38.

Symbiotic gut microbes modulate human metabolic phenotypes.

Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, Zhang Y, Shen J, Pang X, Zhang M, Wei H, Chen Y, Lu H, Zuo J, Su M, Qiu Y, Jia W, Xiao C, Smith LM, Yang S, Holmes E, Tang H, Zhao G, Nicholson JK, Li L, Zhao L.

Proc Natl Acad Sci U S A. 2008 Feb 12;105(6):2117-22. doi: 10.1073/pnas.0712038105. Epub 2008 Feb 5.

39.

Topographical variation in metabolic signatures of human gastrointestinal biopsies revealed by high-resolution magic-angle spinning 1H NMR spectroscopy.

Wang Y, Holmes E, Comelli EM, Fotopoulos G, Dorta G, Tang H, Rantalainen MJ, Lindon JC, Corthésy-Theulaz IE, Fay LB, Kochhar S, Nicholson JK.

J Proteome Res. 2007 Oct;6(10):3944-51. Epub 2007 Aug 21.

PMID:
17711324
40.

Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples.

Smith LM, Maher AD, Cloarec O, Rantalainen M, Tang H, Elliott P, Stamler J, Lindon JC, Holmes E, Nicholson JK.

Anal Chem. 2007 Aug 1;79(15):5682-9. Epub 2007 Jun 23.

PMID:
17585837
41.

Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice.

Rantalainen M, Cloarec O, Beckonert O, Wilson ID, Jackson D, Tonge R, Rowlinson R, Rayner S, Nickson J, Wilkinson RW, Mills JD, Trygg J, Nicholson JK, Holmes E.

J Proteome Res. 2006 Oct;5(10):2642-55.

PMID:
17022635
42.
43.

The comparative metabonomics of age-related changes in the urinary composition of male Wistar-derived and Zucker (fa/fa) obese rats.

Williams RE, Lenz EM, Rantalainen M, Wilson ID.

Mol Biosyst. 2006 Mar;2(3-4):193-202. Epub 2006 Feb 15.

PMID:
16880937
44.

Lead contamination of an old shooting range affecting the local ecosystem--A case study with a holistic approach.

Rantalainen ML, Torkkeli M, Strömmer R, Setälä H.

Sci Total Environ. 2006 Oct 1;369(1-3):99-108. Epub 2006 Jun 30.

PMID:
16814846
45.

Temperature-time relationship in collembolan response to chemical exposure.

Martikainen E, Rantalainen ML.

Ecotoxicol Environ Saf. 1999 Mar;42(3):236-44.

PMID:
10090812
46.

Late results of paraoesophageal hiatus hernia repair with fundoplication.

Luostarinen M, Rantalainen M, Helve O, Reinikainen P, Isolauri J.

Br J Surg. 1998 Feb;85(2):272-5.

PMID:
9501834

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