Pancreatic Cancer Genetics Amundadottir, Laufey T
International journal of biological sciences,
01/2016, Letnik:
12, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Although relatively rare, pancreatic tumors are highly lethal 1. In the United States, an estimated 48,960 individuals will be diagnosed with pancreatic cancer and 40,560 will die from this disease ...in 2015 1. Globally, 337,872 new pancreatic cancer cases and 330,391 deaths were estimated in 2012 2. In contrast to most other cancers, mortality rates for pancreatic cancer are not improving; in the US, it is predicted to become the second leading cause of cancer related deaths by 2030 3, 4. The vast majority of tumors arise in the exocrine pancreas, with pancreatic ductal adenocarcinoma (PDAC) accounting for approximately 95% of tumors. Tumors arising in the endocrine pancreas (pancreatic neuroendocrine tumors) represent less than 5% of all pancreatic tumors 5. Smoking, type 2 diabetes mellitus (T2D), obesity and pancreatitis are the most consistent epidemiological risk factors for pancreatic cancer 5. Family history is also a risk factor for developing pancreatic cancer with odds ratios (OR) ranging from 1.7-2.3 for first-degree relatives in most studies, indicating that shared genetic factors may play a role in the etiology of this disease 6-9. This review summarizes the current knowledge of germline pancreatic cancer risk variants with a special emphasis on common susceptibility alleles identified through Genome Wide Association Studies (GWAS).
The complex relationship between chromatin accessibility, transcriptional regulation, and cancer transitions presents a daunting puzzle. Terekhanova et al. created a pan-cancer epigenetic and ...transcriptomic atlas at single-cell resolution, yielding important insights into the underlying chromatin architecture of cancer transitions and novel discoveries with the potential to advance precision medicine.
The complex relationship between chromatin accessibility, transcriptional regulation, and cancer transitions presents a daunting puzzle. Terekhanova et al. created a pan-cancer epigenetic and transcriptomic atlas at single cell resolution, yielding important insights into the underlying chromatin architecture of cancer transitions and novel discoveries with the potential to advance precision medicine.
Abstract
Background
Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability ...remains unexplained and the genes responsible largely unknown.
Methods
To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics n = 95 and Genotype-Tissue Expression v7 n = 174 datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples).
Results
We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.
Conclusions
By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
Chronic inflammation increases the risk of developing one of several types of cancer. Inflammatory responses are currently thought to be controlled by mechanisms that rely on transcriptional networks ...that are distinct from those involved in cell differentiation. The orphan nuclear receptor NR5A2 participates in a wide variety of processes, including cholesterol and glucose metabolism in the liver, resolution of endoplasmic reticulum stress, intestinal glucocorticoid production, pancreatic development and acinar differentiation. In genome-wide association studies, single nucleotide polymorphisms in the vicinity of NR5A2 have previously been associated with the risk of pancreatic adenocarcinoma. In mice, Nr5a2 heterozygosity sensitizes the pancreas to damage, impairs regeneration and cooperates with mutant Kras in tumour progression. Here, using a global transcriptomic analysis, we describe an epithelial-cell-autonomous basal pre-inflammatory state in the pancreas of Nr5a2
mice that is reminiscent of the early stages of pancreatitis-induced inflammation and is conserved in histologically normal human pancreases with reduced expression of NR5A2 mRNA. In Nr5a2
mice, NR5A2 undergoes a marked transcriptional switch, relocating from differentiation-specific to inflammatory genes and thereby promoting gene transcription that is dependent on the AP-1 transcription factor. Pancreatic deletion of Jun rescues the pre-inflammatory phenotype, as well as binding of NR5A2 to inflammatory gene promoters and the defective regenerative response to damage. These findings support the notion that, in the pancreas, the transcriptional networks involved in differentiation-specific functions also suppress inflammatory programmes. Under conditions of genetic or environmental constraint, these networks can be subverted to foster inflammation.
Expression QTL (eQTL) analyses have suggested many genes mediating genome-wide association study (GWAS) signals but most GWAS signals still lack compelling explanatory genes. We have leveraged an ...adipose-specific gene regulatory network to infer expression regulator activities and phenotypic master regulators (MRs), which were used to detect activity QTLs (aQTLs) at cardiometabolic trait GWAS loci. Regulator activities were inferred with the VIPER algorithm that integrates enrichment of expected expression changes among a regulator's target genes with confidence in their regulator-target network interactions and target overlap between different regulators (i.e., pleiotropy). Phenotypic MRs were identified as those regulators whose activities were most important in predicting their respective phenotypes using random forest modeling. While eQTLs were typically more significant than aQTLs in cis, the opposite was true among candidate MRs in trans. Several GWAS loci colocalized with MR trans-eQTLs/aQTLs in the absence of colocalized cis-QTLs. Intriguingly, at the 1p36.1 BMI GWAS locus the EPHB2 cis-aQTL was stronger than its cis-eQTL and colocalized with the GWAS signal and 35 BMI MR trans-aQTLs, suggesting the GWAS signal may be mediated by effects on EPHB2 activity and its downstream effects on a network of BMI MRs. These MR and aQTL analyses represent systems genetic methods that may be broadly applied to supplement standard eQTL analyses for suggesting molecular effects mediating GWAS signals.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known ...about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies.
In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits.
After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (
< 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55,
= 0.003), lung and colorectal cancer (rg = 0.31,
= 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27,
= 0.009), and colorectal and breast cancer (rg = 0.22,
= 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected
value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41,
= 1.03 × 10
). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer.
Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors.
This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis.
.
Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse ...summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.
In Western populations, pancreatic ductal adenocarcinoma (PDAC) risk has been found to be greater among individuals with non-O blood types than those with O blood type. However, the association has ...not been fully evaluated with respect to FUT2 (determining secretor status) and FUT3 (determining Lewis antigens) status, two biologically important genes in the expression of ABO blood groups with PDAC.
We examined interactions in data from 8,027 cases and 11,362 controls in large pancreatic cancer consortia (PanScan I-III and PanC4) by using genetic variants to predict ABO blood groups (rs505922 and rs8176746), secretor status (rs601338), and Lewis antigens (rs812936, rs28362459, and rs3894326). Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI) of the risk of PDAC adjusted for age and sex. We examined multiplicative interactions of ABO with secretor status and Lewis antigens by considering each product term between ABO and secretor and between ABO and Lewis antigens individually.
We found that the increased risk associated with non-O blood groups was somewhat stronger among secretors than nonsecretors ORs, 1.28 (95% CI, 1.15-1.42) and 1.17 (95% CI, 1.03-1.32) respectively; Pinteraction = 0.002. We did not find any interactions between ABO and Lewis antigens.
Our large consortia data provide evidence of effect modification in the association between non-O blood type and pancreatic cancer risk by secretor status.
Our results indicate that the association between ABO blood type and PDAC risk may vary by secretor status, but not by Lewis antigens.
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