Computational Tumor Infiltration Phenotypes Enable the Spatial and Genomic Analysis of Immune Infiltration in Colorectal Cancer.

colorectal cancer immune response immunotherapy machine learning spatial statistics

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2021
Historique:
received: 15 04 2020
accepted: 10 02 2021
entrez: 1 4 2021
pubmed: 2 4 2021
medline: 2 4 2021
Statut: epublish

Résumé

Cancer immunotherapy has led to significant therapeutic progress in the treatment of metastatic and formerly untreatable tumors. However, drug response rates are variable and often only a subgroup of patients will show durable response to a treatment. Biomarkers that help to select those patients that will benefit the most from immunotherapy are thus of crucial importance. Here, we aim to identify such biomarkers by investigating the tumor microenvironment, i.e., the interplay between different cell types like immune cells, stromal cells and malignant cells within the tumor and developed a computational method that determines spatial tumor infiltration phenotypes. Our method is based on spatial point pattern analysis of immunohistochemically stained colorectal cancer tumor tissue and accounts for the intra-tumor heterogeneity of immune infiltration. We show that, compared to base-line models, tumor infiltration phenotypes provide significant additional support for the prediction of established biomarkers in a colorectal cancer patient cohort (

Identifiants

pubmed: 33791196
doi: 10.3389/fonc.2021.552331
pmc: PMC8006941
doi:

Types de publication

Journal Article

Langues

eng

Pagination

552331

Informations de copyright

Copyright © 2021 Failmezger, Zwing, Tresch, Korski and Schmich.

Déclaration de conflit d'intérêts

HF, NZ, KK, and FS are employees of F. Hoffmann-La Roche Ltd. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Nat Commun. 2017 Apr 27;8:15095
pubmed: 28447602
Nat Med. 2020 Jul;26(7):1054-1062
pubmed: 32461698
Cancer Immunol Immunother. 2017 Feb;66(2):171-179
pubmed: 27866242
Comput Struct Biotechnol J. 2019 Apr 04;17:484-497
pubmed: 31011407
Cancer Res. 2015 Sep 1;75(17):3446-55
pubmed: 26060019
Mol Cancer Res. 2015 Mar;13(3):493-501
pubmed: 25351767
Front Immunol. 2018 Jul 10;9:1578
pubmed: 30042763
Mod Pathol. 2015 Jun;28(6):766-77
pubmed: 25720324
Genome Biol. 2010;11(10):R106
pubmed: 20979621
Cancer Immunol Immunother. 2019 Mar;68(3):433-442
pubmed: 30564892
Ann Oncol. 2019 Jan 1;30(1):44-56
pubmed: 30395155
Nucleic Acids Res. 2012 Sep 1;40(17):e133
pubmed: 22638577
IEEE/ACM Trans Comput Biol Bioinform. 2012 Jul-Aug;9(4):947-54
pubmed: 21788678
Clin Cancer Res. 2016 Nov 15;22(22):5553-5563
pubmed: 27166398
Nat Biotechnol. 2013 Nov;31(11):1023-31
pubmed: 24142049
Proc Natl Acad Sci U S A. 2010 Jan 26;107(4):1488-93
pubmed: 20080638
Front Immunol. 2020 Oct 29;11:550250
pubmed: 33193316
Mol Cancer Ther. 2020 Oct;19(10):2139-2145
pubmed: 32747422
Eur J Cancer. 2004 Mar;40(4):494-502
pubmed: 14962714
Lab Invest. 2017 Jul;97(7):873-885
pubmed: 28504684
J Natl Cancer Inst. 2016 Oct 5;109(1):
pubmed: 27707838
Future Oncol. 2018 Nov;14(26):2725-2739
pubmed: 30004261
Cancer Immunol Res. 2018 Sep;6(9):990-1000
pubmed: 30181337
J Thorac Dis. 2018 Aug;10(8):4689-4693
pubmed: 30233840
Genome Biol. 2015 Mar 31;16:64
pubmed: 25853550
Biom J. 2010 Feb;52(1):70-84
pubmed: 19937997
Front Oncol. 2018 Dec 18;8:627
pubmed: 30619761
Bioinformatics. 2014 Jan 1;30(1):127-8
pubmed: 24132929
Nucleic Acids Res. 2016 May 5;44(8):e71
pubmed: 26704973
Science. 2015 Apr 3;348(6230):69-74
pubmed: 25838375
Sci Transl Med. 2012 Oct 24;4(157):157ra143
pubmed: 23100629
Genome Biol. 2016 Aug 22;17(1):174
pubmed: 27549193
Nature. 2017 Jan 18;541(7637):321-330
pubmed: 28102259
Virchows Arch. 2019 Apr;474(4):511-522
pubmed: 30470933
Nucleic Acids Res. 2000 Jan 1;28(1):27-30
pubmed: 10592173
Nat Commun. 2018 Jul 16;9(1):2736
pubmed: 30013081
Mol Ther. 2009 Mar;17(3):439-47
pubmed: 19107122
Cancer. 2008 Aug 15;113(4):733-42
pubmed: 18543306
Int J Mol Sci. 2016 Nov 19;17(11):
pubmed: 27869779
Cell Res. 2020 Jun;30(6):507-519
pubmed: 32467593
Annu Rev Biophys. 2014;43:257-78
pubmed: 24773018

Auteurs

Henrik Failmezger (H)

Data Science, Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany.

Natalie Zwing (N)

Early Biomarker Development Oncology, Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany.

Achim Tresch (A)

Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany.
Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany.
Center for Data and Simulation Science, University of Cologne, Cologne, Germany.

Konstanty Korski (K)

Early Biomarker Development Oncology, Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany.

Fabian Schmich (F)

Data Science, Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany.

Classifications MeSH