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Items: 23

1.

Immunomodulation of the Tumor Microenvironment: Turn Foe Into Friend.

Locy H, de Mey S, de Mey W, De Ridder M, Thielemans K, Maenhout SK.

Front Immunol. 2018 Dec 11;9:2909. doi: 10.3389/fimmu.2018.02909. eCollection 2018. Review.

2.

Dendritic Cell Targeting mRNA Lipopolyplexes Combine Strong Antitumor T-Cell Immunity with Improved Inflammatory Safety.

Van der Jeught K, De Koker S, Bialkowski L, Heirman C, Tjok Joe P, Perche F, Maenhout S, Bevers S, Broos K, Deswarte K, Malard V, Hammad H, Baril P, Benvegnu T, Jaffr├Ęs PA, Kooijmans SAA, Schiffelers R, Lienenklaus S, Midoux P, Pichon C, Breckpot K, Thielemans K.

ACS Nano. 2018 Oct 23;12(10):9815-9829. doi: 10.1021/acsnano.8b00966. Epub 2018 Oct 1.

3.

Combined VEGFR and CTLA-4 blockade increases the antigen-presenting function of intratumoral DCs and reduces the suppressive capacity of intratumoral MDSCs.

Du Four S, Maenhout SK, Niclou SP, Thielemans K, Neyns B, Aerts JL.

Am J Cancer Res. 2016 Nov 1;6(11):2514-2531. eCollection 2016.

4.

Disease progression in recurrent glioblastoma patients treated with the VEGFR inhibitor axitinib is associated with increased regulatory T cell numbers and T cell exhaustion.

Du Four S, Maenhout SK, Benteyn D, De Keersmaecker B, Duerinck J, Thielemans K, Neyns B, Aerts JL.

Cancer Immunol Immunother. 2016 Jun;65(6):727-40. doi: 10.1007/s00262-016-1836-3. Epub 2016 Apr 20.

PMID:
27098427
5.

Needles: Toward Large-Scale Genomic Prediction with Marker-by-Environment Interaction.

De Coninck A, De Baets B, Kourounis D, Verbosio F, Schenk O, Maenhout S, Fostier J.

Genetics. 2016 May;203(1):543-55. doi: 10.1534/genetics.115.179887. Epub 2016 Mar 2.

6.

Intratumoral Delivery of TriMix mRNA Results in T-cell Activation by Cross-Presenting Dendritic Cells.

Van Lint S, Renmans D, Broos K, Goethals L, Maenhout S, Benteyn D, Goyvaerts C, Du Four S, Van der Jeught K, Bialkowski L, Flamand V, Heirman C, Thielemans K, Breckpot K.

Cancer Immunol Res. 2016 Feb;4(2):146-56. doi: 10.1158/2326-6066.CIR-15-0163. Epub 2015 Dec 11.

7.

INCLUDING EXPLICIT MARKER-BY-ENVIRONMENT INTERACTION FOR LARGE-SCALE GENOMIC PREDICTION.

De Coninck A, Kourounis D, Verbosio F, Schenk O, De Baets B, Maenhout S, Fostier J.

Commun Agric Appl Biol Sci. 2015;80(1):117-21. No abstract available.

PMID:
26630765
8.

Axitinib increases the infiltration of immune cells and reduces the suppressive capacity of monocytic MDSCs in an intracranial mouse melanoma model.

Du Four S, Maenhout SK, De Pierre K, Renmans D, Niclou SP, Thielemans K, Neyns B, Aerts JL.

Oncoimmunology. 2015 Jan 22;4(4):e998107. eCollection 2015 Apr.

9.

Location, location, location: functional and phenotypic heterogeneity between tumor-infiltrating and non-infiltrating myeloid-derived suppressor cells.

Maenhout SK, Thielemans K, Aerts JL.

Oncoimmunology. 2014 Dec 15;3(10):e956579. eCollection 2014 Nov. Review.

10.

AZD1480 delays tumor growth in a melanoma model while enhancing the suppressive activity of myeloid-derived suppressor cells.

Maenhout SK, Du Four S, Corthals J, Neyns B, Thielemans K, Aerts JL.

Oncotarget. 2014 Aug 30;5(16):6801-15.

11.

DAIRRy-BLUP: a high-performance computing approach to genomic prediction.

De Coninck A, Fostier J, Maenhout S, De Baets B.

Genetics. 2014 Jul;197(3):813-22. doi: 10.1534/genetics.114.163683. Epub 2014 Apr 15.

12.

A high performance computing approach for genomic prediction.

De Coninck A, Fostier J, Maenhout S, De Baets B.

Commun Agric Appl Biol Sci. 2014;79(1):115-9. No abstract available.

PMID:
25864324
13.

Enhanced suppressive capacity of tumor-infiltrating myeloid-derived suppressor cells compared with their peripheral counterparts.

Maenhout SK, Van Lint S, Emeagi PU, Thielemans K, Aerts JL.

Int J Cancer. 2014 Mar 1;134(5):1077-90. doi: 10.1002/ijc.28449. Epub 2013 Sep 23.

14.

Modulation of regulatory T cell function by monocyte-derived dendritic cells matured through electroporation with mRNA encoding CD40 ligand, constitutively active TLR4, and CD70.

Pen JJ, De Keersmaecker B, Maenhout SK, Van Nuffel AM, Heirman C, Corthals J, Escors D, Bonehill A, Thielemans K, Breckpot K, Aerts JL.

J Immunol. 2013 Aug 15;191(4):1976-83. doi: 10.4049/jimmunol.1201008. Epub 2013 Jul 10.

15.

Downregulation of Stat3 in melanoma: reprogramming the immune microenvironment as an anticancer therapeutic strategy.

Emeagi PU, Maenhout S, Dang N, Heirman C, Thielemans K, Breckpot K.

Gene Ther. 2013 Nov;20(11):1085-92. doi: 10.1038/gt.2013.35. Epub 2013 Jun 27.

PMID:
23804077
16.

Lentiviral vectors: a versatile tool to fight cancer.

Emeagi PU, Goyvaerts C, Maenhout S, Pen J, Thielemans K, Breckpot K.

Curr Mol Med. 2013 May;13(4):602-25. Review.

PMID:
22973872
17.

Proinflammatory characteristics of SMAC/DIABLO-induced cell death in antitumor therapy.

Emeagi PU, Van Lint S, Goyvaerts C, Maenhout S, Cauwels A, McNeish IA, Bos T, Heirman C, Thielemans K, Aerts JL, Breckpot K.

Cancer Res. 2012 Mar 15;72(6):1342-52. doi: 10.1158/0008-5472.CAN-11-2400. Epub 2012 Feb 29.

18.

Preclinical evaluation of TriMix and antigen mRNA-based antitumor therapy.

Van Lint S, Goyvaerts C, Maenhout S, Goethals L, Disy A, Benteyn D, Pen J, Bonehill A, Heirman C, Breckpot K, Thielemans K.

Cancer Res. 2012 Apr 1;72(7):1661-71. doi: 10.1158/0008-5472.CAN-11-2957. Epub 2012 Feb 15.

19.

Graph-based data selection for the construction of genomic prediction models.

Maenhout S, De Baets B, Haesaert G.

Genetics. 2010 Aug;185(4):1463-75. doi: 10.1534/genetics.110.116426. Epub 2010 May 17.

20.

Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction.

Maenhout S, De Baets B, Haesaert G.

Theor Appl Genet. 2010 Jan;120(2):415-27. doi: 10.1007/s00122-009-1200-5. Epub 2009 Nov 11.

PMID:
19904522
21.

CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data.

Maenhout S, De Baets B, Haesaert G.

Bioinformatics. 2009 Oct 15;25(20):2753-4. doi: 10.1093/bioinformatics/btp499. Epub 2009 Aug 17.

PMID:
19689961
22.

Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes.

Maenhout S, De Baets B, Haesaert G.

Theor Appl Genet. 2009 Apr;118(6):1181-92. doi: 10.1007/s00122-009-0972-y. Epub 2009 Feb 18.

PMID:
19224194
23.

Support vector machine regression for the prediction of maize hybrid performance.

Maenhout S, De Baets B, Haesaert G, Van Bockstaele E.

Theor Appl Genet. 2007 Nov;115(7):1003-13. Epub 2007 Sep 6.

PMID:
17849095

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