Machine Learning Reveals Genetic Modifiers of the Immune Microenvironment of Cancer

Overview

Journal iScience

Publisher Cell Press

Date 2023 Sep 4

PMID 37664640

Authors

Bridget Riley-Gillis

Shirng-Wern Tsaih

Emily King

Sabrina Wollenhaupt

Jonas Reeb

Amy R Peck

Kelsey Wackman

Angela Lemke

Hallgeir Rui

Zoltan Dezso

Michael J Flister

Affiliations

Soon will be listed here.

Abstract

Heritability in the immune tumor microenvironment (iTME) has been widely observed yet remains largely uncharacterized. Here, we developed a machine learning approach to map iTME modifiers within loci from genome-wide association studies (GWASs) for breast cancer (BrCa) incidence. A random forest model was trained on a positive set of immune-oncology (I-O) targets, and then used to assign I-O target probability scores to 1,362 candidate genes in linkage disequilibrium with 155 BrCa GWAS loci. Cluster analysis of the most probable candidates revealed two subfamilies of genes related to effector functions and adaptive immune responses, suggesting that iTME modifiers impact multiple aspects of anticancer immunity. Two of the top ranking BrCa candidates, and , were orthogonally validated as iTME modifiers using BrCa patient biopsies and comparative mapping studies, respectively. Collectively, these data demonstrate a robust and flexible framework for functionally fine-mapping GWAS risk loci to identify translatable therapeutic targets.

References

Schmiedel B, Singh D, Madrigal A, Valdovino-Gonzalez A, White B, Zapardiel-Gonzalo J . Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression. Cell. 2018; 175(6):1701-1715.e16. PMC: 6289654. DOI: 10.1016/j.cell.2018.10.022. View

Gregorova S, Forejt J . PWD/Ph and PWK/Ph inbred mouse strains of Mus m. musculus subspecies--a valuable resource of phenotypic variations and genomic polymorphisms. Folia Biol (Praha). 2000; 46(1):31-41. View

Jonsson S, Sveinbjornsson G, Lopez de Lapuente Portilla A, Swaminathan B, Plomp R, Dekkers G . Identification of sequence variants influencing immunoglobulin levels. Nat Genet. 2017; 49(8):1182-1191. DOI: 10.1038/ng.3897. View

Durinck S, Moreau Y, Kasprzyk A, Davis S, De Moor B, Brazma A . BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics. 2005; 21(16):3439-40. DOI: 10.1093/bioinformatics/bti525. View

Fasching P, Pharoah P, Cox A, Nevanlinna H, Bojesen S, Karn T . The role of genetic breast cancer susceptibility variants as prognostic factors. Hum Mol Genet. 2012; 21(17):3926-39. PMC: 3412377. DOI: 10.1093/hmg/dds159. View

Jostins L, Ripke S, Weersma R, Duerr R, McGovern D, Hui K . Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012; 491(7422):119-24. PMC: 3491803. DOI: 10.1038/nature11582. View

Durinck S, Spellman P, Birney E, Huber W . Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat Protoc. 2009; 4(8):1184-91. PMC: 3159387. DOI: 10.1038/nprot.2009.97. View

Covarrubias S, Vollmers A, Capili A, Boettcher M, Shulkin A, Ramos Correa M . High-Throughput CRISPR Screening Identifies Genes Involved in Macrophage Viability and Inflammatory Pathways. Cell Rep. 2020; 33(13):108541. PMC: 7901356. DOI: 10.1016/j.celrep.2020.108541. View

Alexopoulou L, Thomas V, Schnare M, Lobet Y, Anguita J, Schoen R . Hyporesponsiveness to vaccination with Borrelia burgdorferi OspA in humans and in TLR1- and TLR2-deficient mice. Nat Med. 2002; 8(8):878-84. DOI: 10.1038/nm732. View

10.

Sayaman R, Saad M, Thorsson V, Hu D, Hendrickx W, Roelands J . Germline genetic contribution to the immune landscape of cancer. Immunity. 2021; 54(2):367-386.e8. PMC: 8414660. DOI: 10.1016/j.immuni.2021.01.011. View

11.

Brodin P, Jojic V, Gao T, Bhattacharya S, Lopez Angel C, Furman D . Variation in the human immune system is largely driven by non-heritable influences. Cell. 2015; 160(1-2):37-47. PMC: 4302727. DOI: 10.1016/j.cell.2014.12.020. View

12.

Mayerle J, den Hoed C, Schurmann C, Stolk L, Homuth G, Peters M . Identification of genetic loci associated with Helicobacter pylori serologic status. JAMA. 2013; 309(18):1912-20. DOI: 10.1001/jama.2013.4350. View

13.

Hendrickx W, Simeone I, Anjum S, Mokrab Y, Bertucci F, Finetti P . Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis. Oncoimmunology. 2017; 6(2):e1253654. PMC: 5353940. DOI: 10.1080/2162402X.2016.1253654. View

14.

Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne R . Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013; 45(4):353-61, 361e1-2. PMC: 3771688. DOI: 10.1038/ng.2563. View

15.

Fachal L, Aschard H, Beesley J, Barnes D, Allen J, Kar S . Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes. Nat Genet. 2020; 52(1):56-73. PMC: 6974400. DOI: 10.1038/s41588-019-0537-1. View

16.

Park Y, Zhao X, Lesueur F, Lowy D, Lancaster M, Pharoah P . Sipa1 is a candidate for underlying the metastasis efficiency modifier locus Mtes1. Nat Genet. 2005; 37(10):1055-62. PMC: 2140048. DOI: 10.1038/ng1635. View

17.

Sondka Z, Bamford S, Cole C, Ward S, Dunham I, Forbes S . The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers. Nat Rev Cancer. 2018; 18(11):696-705. PMC: 6450507. DOI: 10.1038/s41568-018-0060-1. View

18.

Bult C, Eppig J, Kadin J, Richardson J, Blake J . The Mouse Genome Database (MGD): mouse biology and model systems. Nucleic Acids Res. 2007; 36(Database issue):D724-8. PMC: 2238849. DOI: 10.1093/nar/gkm961. View

19.

Sen S, Churchill G . A statistical framework for quantitative trait mapping. Genetics. 2001; 159(1):371-87. PMC: 1461799. DOI: 10.1093/genetics/159.1.371. View

20.

Liu J, van Sommeren S, Huang H, Ng S, Alberts R, Takahashi A . Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015; 47(9):979-986. PMC: 4881818. DOI: 10.1038/ng.3359. View