Investigation of single and synergic effects of NLRC5 and PD-L1 variants on the risk of colorectal cancer
Investigation of single and synergic effects of NLRC5 and PD-L1 variants on the risk of colorectal cancer
Calogerina Catalano 0 1
Miguel Inacio da Silva Filho 0 1
Christoph Frank 0 1
Katerina Jiraskova 1
Veronika Vymetalkova 1
Miroslav Levy 1
Vaclav Liska 1
Ondrej Vycital 1
Alessio Naccarati 1
Ludmila Vodickova 1
Kari Hemminki 0 1
Pavel Vodicka 1
Alexander N. R. Weber 1
Asta FoÈ rsti 0 1
0 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ) , Heidelberg, Germany , 2 Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences , Prague , Czech Republic , 3 Institute of Biology and Medical Genetics , 1
1 Editor: Valli De Re, Istituto di Ricovero e Cura a Carattere Scientifico Centro di Riferimento Oncologico della Basilicata , ITALY
Constitutive activation of interferon signaling pathways has been reported in colorectal cancer (CRC), leading to a strong CD8+ T cell response through stimulation of NLRC5 expression. Primed CD8+ T cell expansion, however, may be negatively regulated by PD-L1 expression. Additionally, aberrant PD-L1 expression enables cancer cells to escape the immune attack. Our study aimed to select potential regulatory variants in the NLRC5 and PD-L1 genes by using several online in silico tools, such as UCSC browser, HaploReg, Regulome DB, Gtex Portal, microRNA and transcription factor binding site prediction tools and to investigate their influence on CRC risk in a Czech cohort of 1424 CRC patients and 1114 healthy controls. Logistic regression analysis adjusted for age and gender reported a moderate association between rectal cancer risk and two NLRC5 SNPs, rs1684575 T>G (OR: 1.60, 95% CI: 1.13±2.27, recessive model) and rs3751710 (OR: 0.70, 95% CI: 0.51±0.96, dominant model). Given that a combination of genetic variants, rather than a single polymorphism, may explain better the genetic etiology of CRC, we studied the interplay between the
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: The work was supported by Internal
Grant Agency of the Ministry of Health of the Czech
Republic AZV 15-27580A (PI: PV) and AZV
1526535A (PI: VV) (http://www.azvcr.cz/o-azv-cr) and
the Grant Agency of the Charles University (GAUK
112515) (PI: KJ) (http://www.cuni.cz/ukeng-33.
html). AW was supported by the University of
variants within NLRC5, PD-L1 and the previously genotyped IFNGR1 and IFNGR2 variants,
to evaluate their involvement in the risk of CRC development. Overall we obtained 18
pairwise interactions within and between the NLRC5 ad PD-L1 genes and 6 more when IFNGR
variants were added. Thirteen out of the 24 interactions were below the threshold for the
FDR calculated and controlled at an arbitrary level q*<0.10. Furthermore, the interaction
IFNGR2 rs1059293 C>TÐNLRC5 rs289747 G>A (P<0.0001) remained statistically
significant even after Bonferroni correction. Our data suggest that not only a single genetic variant
but also an interaction between two or more variants within genes involved in immune
regulation may play important roles in the onset of CRC, providing therefore novel biological
TuÈbingen, the Federal State Baden-WuÈrttemberg
Junior Professor Program (https://www.medizin.
Gender+Equality+Prize.html). The funders had no
role in study design, data collection and analysis,
decision to publish, or preparation of the
Competing interests: The authors have declared
that no competing interests exist.
Abbreviations: AIC, Akaike information criterion;
CI, confidence interval; CRC, Colorectal cancer;
HWE, Hardy-Weinberg equilibrium; IBD,
inflammatory bowel disease; IFN, interferon; IFNγ,
Interferon gamma; IFNGR, interferon gamma
receptor; LD, linkage disequilibrium; MHC, major
histocompatibility complex; MAF, minor allele
frequency; Nf-kB, nuclear factor kappa B; NLRC5,
NLR family, CARD domain containing 5; NLRs,
Nod-like receptors; OR, Odds ratio; PD-1,
programmed death protein 1; PD-L1, programmed
death-ligand 1; PRRs, pattern recognition
receptors; SNPs, single nucleotide polymorphisms;
TAF, TATA-box binding protein associated factor 1;
TLRs, Toll-like receptors; TSS, transcription start
site; UTR, untranslated regions.
information, which could eventually improve CRC risk management but also PD-1-based
immunotherapy in CRC.
Colorectal cancer (CRC) is the third most common cancer and the fourth leading cause of
cancer mortality worldwide [
]. CRC represents a paradigm for the link between inflammation
and cancer [
]. The intestinal tract is continuously exposed to both potential pathogens and
beneficial commensal microorganisms; therefore the homeostatic balance between tolerance
and immunity represents a regulatory challenge to the mucosal immune system [
]. In this
context a pivotal role is played by the epithelial cells that monitor the intestinal
microenvironment for pathogenic and commensal microorganisms via so-called pattern recognition
receptors (PRRs), e.g. Toll-like receptors (TLRs), and in turn influence the function of antigen
presenting cells and lymphocytes [
]. Additionally, the gut microbiota provides crucial
health benefits to its host by contributing to the regulation of the intestinal immune
]. Recently, it has become obvious that alterations of the regulatory pathways that
maintain this homeostasis can result in the development of local and chronic inflammation,
inflammatory bowel disease (IBD) and CRC . Aberrant activation of nuclear factor kappa B
(Nf-kB) and interferon (IFN) signaling pathways have been reported to play a pivotal role in
CRC by triggering the production of several proinflammatory mediators [6±8]. Particularly
IFNγ signaling pathway is known to play an important role in controlling the CD8+ T cell
expansion through the stimulation of NLRC5 (NOD-like receptor C5) expression, a major
histocompatibility complex (MHC) class I transactivator [
]. NLRC5 is a member of the
Nod-like receptor (NLR) family of PRR proteins. It contains a nucleotide-binding domain and
leucine-rich repeats, which are conserved in PRRs that regulate inflammatory responses and
cell death. Given its role in the transcription of MHC class I genes, it is reasonable to think that
NLRC5 may play a prominent role in antitumor immunity and its loss may promote tumor
immune evasion . Moreover, cytokine production and CD8+ T cell expansion is necessary
for generating an effective immune defense against invading harmful pathogens [
By assuming the importance of a balanced immune response, a physiological feedback
mechanism played by PD-L1 (Programmed death-ligand 1) is necessary for terminating the
immune responses in a proper way and for maintaining self- tolerance [
]. However, it has
recently been shown that IFNγ is also involved in promoting PD-L1 expression in tumor cells
]. This results in an aberrant PD-L1 expression that allows cancer cells to escape the
antitumor immune response by suppressing the CD8+ T cell expansion [13±15]. This escape
mechanism is reversed by immune checkpoint inhibitors targeting the PD-1/PD-L1 interaction and
restores anti-tumor immunity [
]. Thus the possibility of PD-1/PD-L1-based therapies has
received much attention in many tumor entities including CRC.
To gain further evidence about the potential role of SNPs within NLRC5 and PD-L1 genes,
we genotyped a set of 16 potential regulatory single nucleotide polymorphisms (SNPs) in a
case-control study of 1424 CRC patients and 1114 healthy controls from the Czech Republic
and evaluated their association with CRC risk. Moreover, given the opposite actions of these
two proteins on the CD8+ T cell expansion, we investigated whether pair-wise interactions
between all the investigated SNPs and the previously genotyped SNPs in the IFNGR1 and
IFNGR2 genes exist [
], which may have interactive effects on the risk of CRC. This strategy
has the potential to identify complex biological links among cancer-related immunity genes
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and processes they are involved in, and could provide novel information for a better basic
understanding, risk-management and therapy of CRC.
Materials and methods
Written informed consent was given by all participants enrolled in the current research
study in accordance with the Helsinki declaration. The project was approved by the ethical
committees of the participating institutes, the Institute of Experimental Medicine, Academy of
Sciences of the Czech Republic, Prague, Czech Republic (who issued the Institutional
Certification for Multicenter Studies on July 16th 2015 covering all studies between 2004±2015) and
the Institute for Clinical and Experimental Medicine and Faculty Thomayer Hospital, Prague,
Czech Republic (786/09 (G09-04-09) and 622/11(G11-04-09)).
The case group contained 1424 CRC patients recruited between the years 2004 and 2013 by
several oncological departments in the Czech Republic (Table 1)[
]. Their mean age was 62.7
years, and 61.8% of them were men. The patients showed positive colonoscopic results for
malignancy, histologically confirmed as colon or rectal carcinomas. Patients with any previous
history of cancer or who met the Amsterdam criteria I or II for hereditary nonpolyposis
colorectal cancer were not included in the study. General information about gender and age at
diagnosis was available for all patients. The control group contained 1114 healthy individuals
recruited by the blood-donor centers in Kralovske Vinohrady Hospital and Vojkov hospital in
]. Their mean age was 47.1 years, and 53.4% of them were men.
A total of 16 SNPs, which captured 32 potential regulatory SNPs (r2 > 0.89), were selected for
genotyping within the NLRC5 (NLR family, CARD domain containing 5) and CD274 (also
known as PD-L1, programmed death ligand 1) genes according to the following selection
criteria: non-coding SNPs in the 5' flanking region (up to 1kb from the transcription start site
(TSS) containing the promoter, enhancer or other transcription factor binding sites), 50 and 30
untranslated regions (UTRs), and SNPs regulating the expression of the selected genes (eQTL
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SNPs) with a minor allele frequency (MAF) 0.10 in the CEU population validated by 1000
Genomes and with a pairwise linkage disequilibrium (LD) r2 0.80 (S1 Table).
SNPs were selected using several in silico tools, such as UCSC browser (https://genome-euro.
ucsc.edu/) to collect all potential functional SNPs in the regulatory regions, HaploReg (http://
www.broadinstitute.org/mammals/haploreg/haploreg.php) and Regulome DB (http://www.
regulomedb.org/) to explore the chromatin state, conservation, and regulatory motif
alterations within sets of genetically linked variants, Gtex Portal (https://gtexportal.org/home/) to
identify all cis-eQTL SNPs that affect the expression of genes of our interest and microRNA
binding site prediction tools (http://www.microrna.org/microrna/home.do, http://epicenter.
iefreiburg.mpg.de/services/microsniper/) to investigate the 3'-UTR and to predict if a SNP
within the target site will disrupt/eliminate or enhance/create a microRNA binding site.
PERFECTOS-APE (http://opera.autosome.ru/perfectosape/scan) and s-Transcription factor
Affinity Prediction (s-TRAP, http://trap.molgen.mpg.de/cgi-bin/trap_two_seq_form.cgi) were used
to identify transcription factors whose binding sites can be significantly affected by a given
polymorphism. LD and the haplotype blocks within the genes were examined based on r2
In this project, genomic DNA from peripheral blood leukocytes was used. The KASP (LGC
genomics, Hoddesdon, Hertfordshire, UK) and the TaqMan (Thermo Fisher Scientific,
Darmstadt, Germany) allelic discrimination methods were used to genotype the selected SNPs. The
genotyping was performed blinded by the case±control status of each sample. DNA
amplification was performed according to the LGC genomics' and TaqManÂs PCR conditions.
Genotype detection was performed using ViiA 7 Real-Time PCR System (Thermo Fisher Scientific).
The sample set contained 142 duplicated samples as quality controls. The genotype correlation
between the duplicate samples was > 90%. Genotype call rate ranged between 94.0 and 100%.
The observed genotype frequencies in the controls were tested for Hardy±Weinberg
equilibrium (HWE) using the chi-square test. Odds ratios (ORs) and 95% confidence intervals (CIs)
for associations between genotypes and CRC risk were calculated by logistic regression (SAS
Version 9.3; SAS Institute, Cary, NC), and adjusted for age and gender. The estimated power
was >98% for OR 1.5 (MAF > 0.10; p = 0.05; dominant model) and >98% for OR 1.5
(MAF > 0.50; p = 0.05; recessive model) (Quanto: http://hydra.usc.edu/gxe/).
All possible SNP combinations were evaluated in binary interaction to find the SNP-SNP
interactions that best predict the disease risk. In addition to the SNPs genotyped in the current
study, we also included all SNPs in the IFNGR1/2 genes genotyped previously in 1327 CRC
patients and 758 controls from the same Czech cohort [
]. Four different modes of
inheritance were calculated and tested for each pair: the so called ªthree genotypes modelº whereby
each SNP was treated as a categorical variable with three levels (genotypes); the ªlog additive
modelº whereby SNPs were modeled as a continuous variable and genotypes were converted
into 0, 1 or 2 risk alleles; the ªdominant modelº whereby AA was used as reference and AB and
BB as the test group; and ªthe recessive modelº whereby AA and AB were used as reference
group and BB as the test group. Likelihood ratio tests were performed to assess whether
including the SNP±SNP interaction term led to a significantly better fit of the data. The SNPs that
significantly interacted with each other according to several competing models were ranked
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according to Akaike information criterion (AIC). The smaller the value of AIC, the better the
model data fit. To assess the contribution of all genetic components (both SNPs and
interaction term) to the model, likelihood ratio test-based P-values were computed. For the best
model of each SNP pair, the corresponding ORs and the Wald estimates for their confidence
intervals (CIs) and P-values were calculated. Altogether, 120 (16 SNPs (16±1)/2) independent
tests were carried out, leading to a Bonferroni corrected p-value of 0.05/120 = 0.0004. In
addition, as an alternative approach, we controlled the false discovery rate (FDR) using the
Benjamini-Hochberg procedure. The p-values were sorted from the smallest to the largest and
ranked in ascending order. The false discovery rate was calculated and controlled at an
arbitrary level q < 0.10, defining q = mP(1)/i, where m is the number of multiple tests, P the
p-value of each interaction and i the Rank. Analysis was performed using R version 3.3.2.
As shown in Table 1, there was a significant difference in the age and sex distribution between
the cases and controls (p-value <0.0001 and p-value 2.6e-05, respectively). The genotype
distribution of all 16 genotyped polymorphisms was consistent with HWE in the control group
(P > 0.05). Logistic regression analysis adjusted for age and sex reported an association
between rectal cancer risk and 2 NLRC5 SNPs, rs1684575 (OR: 1.60, 95% CI: 1.13±2.27,
recessive model) and rs3751710 (OR: 0.70, 95% CI: 0.51±0.96, dominant model) (S2 Table). The
other genotyped SNPs did not show any association with CRC risk (S2 Table).
Possible effect of SNP-SNP interactions on CRC risk
We further investigated whether SNP-SNP interactions among these 16 SNPs within NLRC5
and PD-L1 genes could affect colorectal cancer risk. Eighteen interactions, including
interactions between SNPs both within a gene and between the two genes, were detected at a
significance level of p-value <0.05 (Table 2), however, none of these interaction term p-values
survived the conservative Bonferroni multiple testing correction (p-value< 0.0004); although
the global null hypothesis test was highly significant (p-value< 0.0001). When we calculated
and controlled the FDR at an arbitrary level q < 0.10, a total of 12 of these interactions were
below the given threshold (S3 Table). For the best model of each SNP-SNP interaction, the
association with CRC risk was evaluated (S5 Table).
As shown in the Fig 1 most of the SNPs were interacting with two or more SNPs, either
lying within the same or a different gene. Based on our selection criteria, the genotyped SNPs
had pairwise LD r2 0.80. However, some of the interactions can be explained by a lower level
of LD (S1 Fig).
Three NLRC5 SNPs, rs289747, rs289748 and rs56315364, mapping near/in the promoter
(r2 = 0.42±0.70), showed an interaction with the same PD-L1 promoter SNP rs2890657. Of
note, we observed an increased risk of CRC development when at least one minor allele of
rs2890657 interacted with the GG genotype of rs289747. Conversely, a protective effect was
observed when the CC genotype of rs2890657 interacted with the CC genotype of rs289748
and rs56315364, respectively (Supplementary S5 Table).
On the other hand, the PD-L1 SNP rs2890657 together with another promoter SNP,
rs822338 (r2 = 0.68), interacted with the same NLRC5 promoter SNP rs289747. Similar to
rs2890657-rs289747 interaction, an increased risk of CRC was observed when at least one
minor allele of rs822338 interacted with the GG genotype of rs289747 (S5 Table).
The two PD-L1 promoter SNPs also interacted independently with two eQTL SNPs for
NLRC5. The interaction partner for rs2890657 was rs12445252, whose T allele is predicted to
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decrease NLRC5 expression in the whole blood tissue with an effect size of -0.26 and a p-value
of 1.6e-7. rs822338 interacted with rs289726, whose C allele is reported to increase NLRC5
expression in the whole blood with an effect size of 0.19 and a p-value of 10e-6. Interestingly,
we observed a decreased CRC risk when the CC genotype of PD-L1 rs2890657 interacted with
at least one minor allele of NLRC5 rs12445252, which is related with lower NLRC5 expression
and an increased CRC risk was shown by the interactions between the CC genotypes of both
PD-L1 rs822338 and NLRC5 rs289726 and between the TT genotype of PD-L1 rs822338 and
the genotypes with at least one minor allele T of NLRC5 rs289726 (S5 Table).
Two 3'UTR SNPs in NLRC5, rs43216 and rs27194, which map within a genetic block of 305
bp (r2 = 0.43), revealed a decreased risk of CRC when at least one major allele of rs27194
interacted with the minor allele genotype of rs43216. Additionally, both of them interacted
independently with the two NLRC5 eQTL SNPs, rs12445252 and rs289726, respectively. We
observed an increased risk when the GG genotype of rs43216, which binds a lower number of
miRNAs, interacted with the TT genotype of rs12445252, related to a lower expression of
NLRC5, as well as when the TT genotype of rs27194, which also binds a lower number of
miRNAs, interacted with the CC genotype of rs289726, which instead is related to a higher NLRC5
expression. Moreover, the same genotype of rs27194 showed an increased risk also when it
interacted with the CC genotype of the NLRC5 flanking SNP rs289748 (S5 Table).
When we included the IFNGR genes variants previously analyzed in an older version of
our cohort with a lower number of individuals (1327 cases and 758 healthy controls [
our analysis, we observed 6 additional interactions including three SNPs within IFNGR1
(rs2234711, rs1327474 and rs17181457) and two within IFNGR2 (rs17882748 and rs1059293)
(Table 3). Among them, rs2234711, lying within the 5'UTR of IFNGR1, showed complicated
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Fig 1. NLRC5-PD-L1-IFNGR1/2 pair-wise interactions. The color indicates the SNPs' location displayed by UCSC Genome Browser on
lymphoblastoid cell lines (GM12878).
PLOS ONE | https://doi.org/10.1371/journal.pone.0192385
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interactions with two 3' UTR variants, NLRC5 rs43216 and PD-L1 rs4143815 (S6 Table). The
strongest interaction was observed between a 3'UTR SNP in IFNGR2 rs1059293 C>T and the
NLRC5 promoter SNP rs289747 G>A, which also survived the Bonferroni multiple testing
correction (interaction term p value < 0.0004) and the FDR controlled at an arbitrary level q
< 0.10 (S4 Table). Particularly carriers of rs1059293 CC homozygous genotype and rs289747
heterozygous genotype showed an increased risk of CRC development (S6 Table). Curiously,
an increased risk was also observed for T allele carriers of rs1059293 and GG genotype carriers
In our case-control study comprising up to 1424 cases and 1114 healthy controls, we
investigated the role of genetic polymorphisms in the regulatory regions of NLRC5, PD-L1 and the
previously genotyped regulatory SNPs in the IFNGR genes on the risk of CRC. In the single
SNP analysis, only 2 SNPs out of 16, rs1684575 T>G (OR: 1.60, 95% CI: 1.13±2.27, recessive
model) and rs3751710 C>T (OR: 0.70, 95% CI: 0.51±0.96, dominant model), both mapping
within the NLRC5 gene, showed a nominal association with rectal cancer risk in the Czech
population (p < 0.05). In our previous study on potentially functional IFNGR SNPs, rs2234711
in the 5'UTR of IFNGR1, was reported to be associated with an increased risk of CRC;
particularly the risk allele C was associated with IFNGR1 gene activity in a context-dependent manner
Given that the evaluated 16 SNPs did not show a strong individual association with CRC
risk and that SNPs represent common genetic alterations typically characterized by a low level
of penetrance, we further evaluated whether their binary interactions might uncover
synergistic effects contributing to CRC predisposition. Taking into account that all SNPs were
noncoding variants, though located in regulatory regions (promoter, enhancer, 5Âand 3ÂUTR), a
possible biological mechanism may be an active involvement in the regulation of gene
]. Perturbations in NLRC5 and PD-L1 gene expression may lead, as a consequence, to a
dysregulation of the anti-tumor immune response, which in turn may influence CRC
development [21±23]. Indeed, the immune infiltration is a major outcome factor in CRC [
altering immune-regulatory machinery is one of the mechanisms developed by cancer cells to
evade the immune system and form a tumor [
Altogether, we observed 18 interactions between NLRC5 and PD-L1, and further 6
interactions together with IFNGR1/2 in a smaller sample set. For all interactions, the global null
hypothesis test was highly significant (p-value < .0001). Twelve out of the 18 PD-L1-NLRC5
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interactions were below the threshold for the FDR controlled at an arbitrary level q <0.10,
while only one out of the 6 PD-L1-NLRC5-IFNGR1/2 interactions survived both the FDR and
the Bonferroni multiple testing correction (p-value< 0.0004). It should be pointed out that we
had relatively low power to detect such an association in the first place, due to the limited
number of cases in the interacting genotype categories and the high stringency of the
Bonferroni correction [
]. Finally, the tests were not completely independent, due to the fact that
many SNPs in each gene were studied and there was moderate to low LD between some of the
The main interactions included three moderately linked NLRC5 SNPs rs289747, rs289748,
rs56315364, mapping within a genetic block of 3 kb located in the upstream and promoter
region of the gene that exhibited a significant interaction with the same PD-L1 promoter SNP
rs2890657. Also another PD-L1 promoter SNP rs822338 (r2 = 0.68 with rs2890657) interacted
with the NLRC5 promoter SNP rs289747. Interestingly, rs2890657 showed also an interaction
with an eQTL SNP for NLRC5, rs12445252, while rs822338 interacted with another NLRC5
eQTL SNP rs289726. Additionally, two 3'UTR SNPs in NLRC5, rs43216 and rs27194 (r2 =
0.43), interacted independently with the two NLRC5 eQTL SNPs, and rs27194 also with
another NLRC5 flanking SNP rs289748. Furthermore, we observed interactions between a 5'
UTR SNP in IFNGR1, rs2234711, and 3' UTR variants in NLRC5 (rs43216) and PD-L1
(rs4143815), respectively, and between a 3' UTR SNP in IFNGR2 (rs1059293) and a promoter
SNP in NLRC5 (rs289747).
All upstream and/or promoter SNPs in the NLRC5 and PD-L1 genes involved in the most
significant interactions, and several other SNPs in high LD with them, are located within
promoter histone marks and DNase hypersensivity sites. Two of the NLRC5 SNPs, rs289747 and
rs56315364, are predicted to affect in an opposite way the OCT proteins binding site, reflecting
the opposite associations that they elicit on the CRC development and supporting the
reliability of our interaction analysis. Also the PD-L1 SNPs rs2890657 and rs822338 are estimated to
affect transcription factor binding sites: rs2890657 the c-Myb binding site and rs822338
together with 5 linked SNPs the binding sites of transcription factors such as TAF1
(TATAbox binding protein associated factor 1) and p300. P300 is a histone acetyltransferase that
regulates transcription of genes via chromatin remodeling [
]. Members of the TAF
transcription factor family may participate in basal transcription, as coactivators, or in promoter
recognition or to facilitate complex assembly and transcription initiation [
The two PD-L1 promoter SNPs, rs2890657 and rs822338, also interacted independently
with two NLRC5 eQTL SNPs, rs12445252 and rs289726, respectively. Interestingly, we
observed a lower CRC risk when PD-L1 rs2890657 interacted with the allele of the NLRC5
rs12445252, which is predicted to decrease NLRC5 expression (-0.26 and a p-value of 1.6e-7),
while the interaction between the different genotype categories of PD-L1 rs822338 and NLRC5
rs289726 was more complex, implicating an increased CRC risk for genotype combinations
including rs289726 alleles predicted to either increase or decrease NLRC5 expression.
Furthermore, the two 3'UTR SNPs in NLRC5, rs43216 and rs27194 (r2 = 0.43), exhibited a
decreased risk of CRC, which may be due to the interaction between the alleles that are
predicted to bind a higher number of miRNAs than the other allele, leading to a stricter NLRC5
post-transcriptional repression. Furthermore, both of them were found to be involved in an
independent interaction with the two NLRC5 eQTL SNPs. Particularly, an increased risk was
observed when the rs43216 allele binding a lower number of miRNAs interacted with the
rs12445252 allele related with a lower expression of NLRC5, as well as when the rs27194 allele
which has a less strict post-transcriptional repression, interacted with the rs289726 allele
related to a higher NLRC5 expression, again reflecting the complex interactions between the
genomic regions. Moreover, rs27194 showed an increased risk also when it interacted with
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NLRC5 flanking SNP rs289748, when the allele of rs27194 binding lower number of miRNAs
was involved in the interaction. These results suggest that a deregulation in the NLRC5
expression through complicated interactions between genetic variants may lead to alterations in the
downstream pathways and by that influence the risk of CRC.
Additionally, postulating that both, NLRC5 and PD-L1, are downstream targets of IFNγ, we
evaluated them in binary interaction with IFNGR1 and IFNGR2 variants previously genotyped
by us [
]. We observed that the IFNGR1 5'UTR SNP, rs2234711, interacted with two 3' UTR
variants, NLRC5 rs43216 and PD-L1 rs4143815. The association between the IFNGR1 SNP and
the risk of CRC has already been established in our previous study [
]. In the present study
the previous association was strengthened when the risk allele of rs2234711 interacted with the
variant of rs43216, related with a stricter NLRC5 post-transcriptional repression and with the
allele of rs4143815 whose antisense is targeted by the miR-570, a negative regulator of PD-L1,
as reported by the online prediction tools.
Finally, a 3'UTR SNP in IFNGR2 rs1059293 C>T presented an interaction with the NLRC5
promoter SNP rs289747 G>A. The result pointed to a complicated interaction between the
two variants. An increased risk of CRC was observed both for carriers of the CC genotype for
IFNGR2 rs1059293 and the heterozygous GA genotype for NLRC5 rs289747 and for the T allele
carriers of rs1059293 and the GG genotype carriers of rs289747. In this context the C allele of
rs1059293 has been reported to bind a lower number of miRNAs than the T allele. On the
other hand, the NLRC5 rs289747 is reported to affect OCT1 binding site, with the G allele
showing a nearly inexistent affinity for OCT1, compared to the A allele, which instead is
reported to exhibit a consistently increasing affinity. OCT1 is also reported to be overexpressed
in many cancers, including CRC [31±33] and the IFNγ promoter has been reported to contain
a binding site for Oct proteins [
]. As a consequence, the secretion of IFNγ by Oct proteins
might be increased contributing to a dysregulation of the expression of the downstream
pathway genes, such as NLRC5 and PD-L1 [
Assuming that NLRC5 has been reported to be the major MHC class I transactivator, a
hyper-stimulation of its expression could lead to a strong CD8+ activation. Conversely a lower
NLRC5 expression has been reported to influence the MHC class I expression leading to an
impaired ability to elicit CD8+ T-cell activation, which represent a way used by the tumor cells
to escape the host immune system [
]. Additionally, recent data suggest that 5-Fluorouracil, a
chemotherapeutic frequently used in CRC treatment, impacts on PD-L1 expression [
Therefore the PD-L1 SNPs studied here and their interactions with IFNGR and NLRC5
variants may also be worth studying with regard to therapy response as well as survival of the CRC
In this study, we included only four of the many immune-related genes for several reasons:
first because of the interesting opposite effect that NLRC5 and PD-L1 exert on the regulation
of T-cell mediated immunity, second because both of them are downstream targets of IFNγ
and third because of the emerging role of these genes on CRC as well as on other cancer types.
Furthermore, including a large network of genes would have led to a higher number of
multiple tests, increasing the likelihood of chance findings. However, our study serves as a starting
point to study the interplay between all the genes involved in the mucosal immune system,
which would possibly shed light on the mechanisms underlying CRC development.
In conclusion, we anticipate that the interaction between the inherited genetic variants
contributes to signaling defects, which in turn may lead to alteration in the anti-tumor immune
response. Defects in the immune responses, especially in the expression of genes involved in
immune surveillance, could favor tumorigenesis. Additionally, perturbation of the
physiological immune homeostasis may also affect inflammation, another predisposing step for CRC
development. It will be interesting to monitor the effect of the variants identified here under
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standard therapies for spontaneous and inflammation-related CRC and in ongoing clinical
trials with immune check-point inhibitors where effects may be even more pronounced [
S1 Table. Information about the SNPs evaluated in this study provided by different online tools.
S2 Table. Association between the selected SNPs and the colorectal cancer risk.
S3 Table. False discovery rate for each individual NLRC5-PD-L1 pair-wise interaction.
S4 Table. False discovery rate for each individual NLRC5-PD-L1-IFNGR1/2 pair-wise inter
S5 Table. NLRC5-PD-L1 pair-wise interactions. For the best model of each pair, age and sex
adjusted ORs and 95% CI, with overall p-values based on the likelihood ratio test, were
S6 Table. IFNGR1/2, PD-L1 and NLRC5 pair-wise interactions. For the best model of each
pair, age and sex adjusted ORs and 95% CI, with overall p-values based on the likelihood ratio
test, were calculated.
S1 Fig. Haploview plot showing LD and haplotype blocks within PD-L1 and NLRC5 genes
based on r2.
We thank Dr. Hauke Thomsen for the statistical advice.
Conceptualization: Alexander N. R. Weber, Asta FoÈrsti.
Data curation: Calogerina Catalano, Miguel Inacio da Silva Filho, Christoph Frank, Katerina
Jiraskova, Veronika Vymetalkova, Ludmila Vodickova.
Formal analysis: Calogerina Catalano, Miguel Inacio da Silva Filho, Christoph Frank.
Funding acquisition: Katerina Jiraskova, Veronika Vymetalkova, Pavel Vodicka, Alexander
N. R. Weber.
Investigation: Calogerina Catalano.
Methodology: Calogerina Catalano.
Project administration: Asta FoÈrsti.
Resources: Katerina Jiraskova, Veronika Vymetalkova, Miroslav Levy, Vaclav Liska, Ondrej
Vycital, Alessio Naccarati, Ludmila Vodickova, Pavel Vodicka.
11 / 13
Software: Calogerina Catalano.
Supervision: Asta FoÈrsti.
Visualization: Calogerina Catalano.
Writing ± original draft: Calogerina Catalano, Asta FoÈrsti.
Writing ± review & editing: Ludmila Vodickova, Kari Hemminki, Pavel Vodicka, Alexander
N. R. Weber, Asta FoÈrsti.
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