Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response

Abstract

With the continued promise of immunotherapy as an avenue for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer risk screening and treatment strategies. Using genotypes from over 8,000 European individuals in The Cancer Genome Atlas (TCGA) and 137 heritable tumor immune phenotype components (IP components), we identified and investigated 482 TIME associations and 475 unique TIME-associated variants. Many TIME-associated variants influence gene activities in specific immune cell subsets, such as macrophages and dendritic cells, and interact to promote more extreme TIME phenotypes. TIME-associated variants were predictive of immunotherapy response in human cohorts treated with immune-checkpoint blockade (ICB) in 3 cancer types, causally implicating specific immune-related genes that modulate myeloid cells of the TIME. Moreover, we validated the function of these genes in driving tumor response to ICB in preclinical studies. Through an integrative approach, we link host genetics to TIME characteristics, informing novel biomarkers for cancer risk and target identification in immunotherapy.

Machine Learning Reveals Genetic Modifiers of the Immune Microenvironment of Cancer

“…The collective estimates of iTME heritability from TCGA (Sayaman et al 2021;Pagadala et al 2021) match the estimated heritability of immune traits in healthy individuals by larger GWAS (Astle et al 2016;Orrù et al 2013) and twin studies (Brodin et al 2015), suggesting that the heritability of immunity is consistent in normal and malignant settings. However, despite comparable levels of heritable immunity in normal (Orrù et al 2013) and malignant settings (Sayaman et al 2021;Pagadala et al 2021), only a handful of iTME candidates were detected by GWAS in TCGA pan-cancer cohort (~9,000 patients) as compared with >2,700 modifier loci of immune traits in a much larger cohort of >500,000 healthy individuals (Astle et al 2016). Together, these observations indicate that GWAS in TCGA is currently underpowered to detect all but the most penetrant iTME modifier loci, and larger cohorts with matched germline and RNAseq data are needed to replicate and expand the catalog of germline iTME modifiers (Shahamatdar et al 2020).…”

“…The estimated heritability of iTME modifiers from these studies approached 20% of variance for some traits (Sayaman et al 2021;Pagadala et al 2021), excluding highly polymorphic regions with much higher estimates of heritability, such as the HLA and KIR regions (Pagadala et al 2021). The collective estimates of iTME heritability from TCGA (Sayaman et al 2021;Pagadala et al 2021) match the estimated heritability of immune traits in healthy individuals by larger GWAS (Astle et al 2016;Orrù et al 2013) and twin studies (Brodin et al 2015), suggesting that the heritability of immunity is consistent in normal and malignant settings.…”

“…Although the heritability of germline genetic modifiers of the iTME has long been suspected (Flister and Bergom 2018), it has only recently been measured using TCGA cohorts that uniquely have both patient genotypes and immune phenotypes inferred from bulk RNAseq (Sayaman et al 2021;Shahamatdar et al 2020;Pagadala et al 2021;Thorsson et al 2018;Lim et al 2018).…”

The translational challenges of precision oncology

“…Recently, analysis of 28,000 tumours across 66 tumour types uncovered 568 mutational drivers (Martínez-Jiménez et al, 2020). Other key studies have focussed on the characterisation of copy number (Zack et al, 2013), structural variation , methylation (De Carvalho et al, 2012;Pan et al, 2021) and gene fusions (Yoshihara et al, 2015), revealing alternative drivers of tumourigenesis. Alterations through these mechanisms include focal amplifications of EGFR in glioblastoma multiforme (GBM) (McLendon et al, 2008b), BRCA1 methylation in breast cancers (Esteller et al, 2000), and EML4-ALK fusions in non-small cell lung cancer (NSCLC) (Soda et al, 2007).…”

“…The interaction between the cancer cell and the microenvironment can also be modulated by germline variation. Specific germline variants, including those affecting STING1, TMEM108, IFIH1, and MHC-I and MHC-II genes can have an impact on antigen presentation, immune infiltration and immunotherapy responses (Chowell et al, 2019;Marty et al, 2017;Marty Pyke et al, 2018;Naranbhai et al, 2022;Pagadala et al, 2021;Sayaman et al, 2021;Shahamatdar et al, 2020).…”