Alternative polyadenylation (APA) modulates mRNA processing in the 3'-untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. In this study, we conducted large APA-wide association studies to investigate associations between APA levels and cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA sequencing data from 1,337 samples from the Genotype-Tissue Expression project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European ancestry populations: breast, ovarian, prostate, colorectal, lung, and pancreatic cancers. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3'-UTR APA quantitative trait loci and colocalization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3'-UTR variants demonstrated that the risk alleles of 3'-UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the posttranscriptional activities of their target genes compared with reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers. Significance: Systematic evaluation of associations of alternative polyadenylation with cancer risk reveals 58 putative susceptibility genes, highlighting the contribution of genetically regulated alternative polyadenylation of 3'UTRs to genetic susceptibility to cancer.

• MeSH
• 3' Untranslated Regions * genetics   MeSH
• Genome-Wide Association Study * MeSH
• Genetic Predisposition to Disease * MeSH
• Polymorphism, Single Nucleotide MeSH
• Humans MeSH
• Quantitative Trait Loci MeSH
• RNA, Messenger genetics   metabolism   MeSH
• Cell Line, Tumor MeSH
• Neoplasms * genetics   MeSH
• Polyadenylation * MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• 3' Untranslated Regions * MeSH
• RNA, Messenger MeSH

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

• MeSH
• White People * genetics   MeSH
• Genome-Wide Association Study * MeSH
• Genetic Predisposition to Disease * MeSH
• Polymorphism, Single Nucleotide * MeSH
• Colorectal Neoplasms * genetics   MeSH
• Humans MeSH
• Quantitative Trait Loci * MeSH
• Chromosome Mapping MeSH
• Exome Sequencing MeSH
• Case-Control Studies MeSH
• Transcriptome MeSH
• East Asian People * genetics   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

• MeSH
• Genome-Wide Association Study * MeSH
• Genetic Predisposition to Disease MeSH
• Humans MeSH
• Mutation MeSH
• Breast Neoplasms genetics   pathology   MeSH
• BRCA1 Protein genetics   MeSH
• Case-Control Studies MeSH
• Triple Negative Breast Neoplasms genetics   pathology   MeSH
• Linkage Disequilibrium MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Meta-Analysis MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, N.I.H., Intramural MeSH
• Names of Substances
• BRCA1 protein, human MeSH Browser
• BRCA1 Protein MeSH

The epigenome denotes all the information related to gene expression that is not contained in the DNA sequence but rather results from chemical changes to histones and DNA. Epigenetic modifications act in a cooperative way towards the regulation of gene expression, working at the transcriptional or post-transcriptional level, and play a key role in the determination of phenotypic variations in cells containing the same genotype. Epigenetic modifications are important considerations in relation to anti-cancer therapy and regenerative/reconstructive medicine. Moreover, a range of clinical trials have been performed, exploiting the potential of epigenetics in stem cell engineering towards application in disease treatments and diagnostics. Epigenetic studies will most likely be the basis of future cancer therapies, as epigenetic modifications play major roles in tumour formation, malignancy and metastasis. In fact, a large number of currently designed or tested clinical approaches, based on compounds regulating epigenetic pathways in various types of tumours, employ these mechanisms in stem cell bioengineering.

• Keywords
• cancer, epigenetics, reconstructive medicine, regenerative medicine, stem cells,
• Publication type
• Journal Article MeSH
• Review MeSH