Cancer-associated SNPs Research Articles

Evaluation of linkage disequilibrium between CYP2D6 gene polymorphisms associated with breast cancer in women

Introduction: the CYP2D6 gene is highly polymorphic and is involved in the metabolism of a wide variety of drugs and xenobiotics. Three allelic variants of the gene (rs3892097, rs1065852 and rs28371725) have been studied in relation to breast cancer, but the degree of genetic linkage between them is unknown.Objetive: to test whether the three breast cancer-associated SNPs are inherited en bloc.Methods: genotypes of 280 SNPs of the CYP2D6 gene were obtained from the 1000Genomes database and linkage disequilibrium between the three breast cancer-associated SNPs and the other 277 SNPs in the gene was analysed. A threshold of r2= 0,7 was used to identify loci in linkage disequilibrium.Results: a strong correlation was found between rs3892097 and rs1065852 in Europe and Latin America. In addition, eleven polymorphisms with a high level of linkage were identified, four of which have a non-synonymous mutation effect.Conclusions: both polymorphisms could have a causal effect on breast cancer or that one of them is associated by linkage. Continuing to study both polymorphisms and considering the eleven new polymorphisms for analysis would be of relevance to deepen knowledge in relation to breast cancer in women

A review on CRISPR/Cas: a versatile tool for cancer screening, diagnosis, and clinic treatment.

Cancer is one of the leading causes of death worldwide and it has the trend of increase incidence. However, in the past decades, as quickly developed new technologies and modified old techniques for cancer screening, diagnosis, and treatment, the cancer-caused mortality rates dropped quickly, and the survival times of cancer patients are enhanced. However, the current death rate is still about 50% and the survival patients always suffer from the side effect of current cancer treatments. Recently developed Nobel Prize-winning CRISPR/Cas technology provides new hope on cancer screening, early diagnosis, and clinic treatment as well as new drug development. Currently, four major CRISPR/Cas9-derived genome editors, CRISPR/Cas9 nucleotide sequence editor, CRISPR/Cas base editor(BE), CRISPR prime editor(PE), and CRISPR interference (CRISPRi) (including both CRISPRa and CRISPRr), were well developed and used to various research and applications, including cancer biology study and cancer screening, diagnosis, and treatment. Additionally, CRISPR/Cas12 and CRISPR/Cas13 genome editors were also widely used in cancer-related basic and applied research as well as treatment. Cancer-associated SNPs and genetic mutations as well as both oncogenes and tumor suppressor genes are perfect targets for CRISPR/Cas-based gene therapy for cancer treatment. CRISPR/Cas is also employed to modify and generate new Chimeric antigen receptor (CAR) T-cells for improving its safety, efficiency, and longer-time last for treating various cancers. Currently, there are many clinic trails of CRISPR-based gene therapy for cancer treatments. Although all CRISPR/Cas-derived genome and epigenome tools are promising methods for cancer biology study and treatment, the efficiency and long term-safety are still the major concerns for CRISPR-based gene therapy. Developing new CRISPR/Cas delivery methods and reducing the potential side effects, including off-target impacts, will enhance CRISPR/Cas application in cancer-related research, diagnosis, and therapeutical treatment.

Long noncodingRNA polymorphisms and hepatocellular carcinoma and pancreatic cancer risk.

Hepatocellular carcinoma (HCC) and pancreatic cancer (PC) are among serious malignancies with no proper biomarker suffering from poor prognosis and late onset. Regulation of long noncoding RNAs (lncRNAs) is disturbed in tumors, making them appropriate diagnostic markers or therapeutic targets in systemic therapies. The expression and function of some significant lncRNAs are under the influence of SNPs, highlighting their key role in carcinogenesis. This review assesses the associations between SNPs in lncRNAs and HCC and PC risk. A panel of cancer-associated SNPs in lncRNA genes could help evaluate the clinical use of lncRNAs, including their role as diagnostic markers and therapeutic targets. Nonetheless, more large-scale surveys on various ethnic groups are required to validate results.

A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs

GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information.

Structural insights into substrate recognition by the SOCS2 E3 ubiquitin ligase

The suppressor of cytokine signaling 2 (SOCS2) acts as substrate recognition subunit of a Cullin5 E3 ubiquitin ligase complex. SOCS2 binds to phosphotyrosine-modified epitopes as degrons for ubiquitination and proteasomal degradation, yet the molecular basis of substrate recognition has remained elusive. Here, we report co-crystal structures of SOCS2-ElonginB-ElonginC in complex with phosphorylated peptides from substrates growth hormone receptor (GHR-pY595) and erythropoietin receptor (EpoR-pY426) at 1.98 Å and 2.69 Å, respectively. Both peptides bind in an extended conformation recapitulating the canonical SH2 domain-pY pose, but capture different conformations of the EF loop via specific hydrophobic interactions. The flexible BG loop is fully defined in the electron density, and does not contact the substrate degron directly. Cancer-associated SNPs located around the pY pocket weaken substrate-binding affinity in biophysical assays. Our findings reveal insights into substrate recognition and specificity by SOCS2, and provide a blueprint for small molecule ligand design.

Are VNTRs co-localizing with breast cancer-associated SNPs?

Several common genetic variants (single-nucleotide polymorphisms, SNPs) have been shown to be associated with breast cancer (BC) risk in the general population, and to modify BC risk for BRCA1 and BRCA2 mutation carriers. Co-localization of variable number of tandem repeats (VNTRs) with these BC-associated SNPS has not been comprehensively studied. Cross referencing of genome-wide VNTRs with the known BC genome-wide association studies (GWAS) SNPs significantly associated with increased risk for developing breast cancer was carried out. Analysis was based on the overlap between the VNTRs and 10-kb windows around these BC-susceptibility SNPs. Cross referencing of the 1.2 million TR with the 161 known BC-associated SNPs in the general population led to 690 matches. Of those, in 17 VNTRs, the SNP was within the VNTR. Analysis restricted to loci known to modify BC penetrance in BRCA1 (n=31) and BRCA2 (n=33) mutation carriers led to 139 and 170 co-localization matches, respectively. For these, none of the SNPs were within the VNTR. The distances between the SNPs and the VNTRs were not significantly different from what was expected to occur by chance alone (p=0.61; p=0.44; p=0.25, respectively). There is no evidence that VNTRs co-localize with currently reported SNP tagged BC GWAS loci.

Highlights from Recent Cancer Literature

Highlights from Recent Cancer Literature

Pancreatic cancer-associated gene polymorphisms in a nation-wide cohort of p16-Leiden germline mutation carriers; a case–control study

BackgroundThe p16-Leiden founder mutation in the CDKN2A gene is the most common cause of Familial Atypical Multiple Mole Melanoma (FAMMM) syndrome in the Netherlands. Individuals with this mutation are at increased risk for developing melanoma of the skin, as well as pancreatic cancer. However, there is a notable interfamilial variability in the occurrence of pancreatic cancer among p16-Leiden families. We aimed to test whether previously identified genetic risk factors for pancreatic cancer modify the risk for pancreatic cancer in p16-Leiden germline mutation carriers.MethodsSeven pancreatic cancer-associated SNPs were selected from the literature and were genotyped in a cohort of 185 p16-Leiden germline mutation carriers from 88 families, including 50 cases (median age 55 years) with pancreatic cancer and 135 controls (median age 64 years) without pancreatic cancer. Allelic odds ratios per SNP were calculated.ResultsNo significant association with pancreatic cancer was found for any of the seven SNPs.ConclusionsSince genetic modifiers for developing melanoma have already been identified in CDKN2A mutation carriers, this study does not exclude that genetic modifiers do not play a role in the individual pancreatic cancer risk in this cohort of p16-Leiden germline mutation carriers. The search for these modifiers should therefore continue, because they can potentially facilitate more targeted pancreatic surveillance programs.

Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33

Background: TERT encodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG) n nucleotide repeats at the telomere. Recent genome-wide association studies have found common genetic variants at the TERT-CLPTM1L locus (5p15.33) associated with an increased risk of several cancers. Results: Data were acquired for 1627 variants in 1092 unrelated individuals from 14 populations within the 1000 Genomes Project. We assessed the population genetics of the 5p15.33 region, including recombination hotspots, diversity, heterozygosity, differentiation among populations, and potential functional impacts. There were significantly lower polymorphism rates, divergence, and heterozygosity for the coding variants, particularly for non-synonymous sites, compared with non-coding and silent changes. Many of the cancer-associated SNPs had differing genotype frequencies among ancestral groups and were associated with potential regulatory changes. Conclusions: Surrogate SNPs in linkage disequilibrium with the majority of cancer-associated SNPs were functional variants with a likely role in regulation of TERT and/or CLPTM1L. Our findings highlight several SNPs that future studies should prioritize for evaluation of functional consequences.

Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33.

TERT encodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG) n nucleotide repeats at the telomere. Recent genome-wide association studies have found common genetic variants at the TERT-CLPTM1L locus (5p15.33) associated with an increased risk of several cancers. Data were acquired for 1627 variants in 1092 unrelated individuals from 14 populations within the 1000 Genomes Project. We assessed the population genetics of the 5p15.33 region, including recombination hotspots, diversity, heterozygosity, differentiation among populations, and potential functional impacts. There were significantly lower polymorphism rates, divergence, and heterozygosity for the coding variants, particularly for non-synonymous sites, compared with non-coding and silent changes. Many of the cancer-associated SNPs had differing genotype frequencies among ancestral groups and were associated with potential regulatory changes. Surrogate SNPs in linkage disequilibrium with the majority of cancer-associated SNPs were functional variants with a likely role in regulation of TERT and/or CLPTM1L. Our findings highlight several SNPs that future studies should prioritize for evaluation of functional consequences.

Use of long term molecular dynamics simulation in predicting cancer associated SNPs.

Computational prediction of cancer associated SNPs from the large pool of SNP dataset is now being used as a tool for detecting the probable oncogenes, which are further examined in the wet lab experiments. The lack in prediction accuracy has been a major hurdle in relying on the computational results obtained by implementing multiple tools, platforms and algorithms for cancer associated SNP prediction. Our result obtained from the initial computational compilations suggests the strong chance of Aurora-A G325W mutation (rs11539196) to cause hepatocellular carcinoma. The implementation of molecular dynamics simulation (MDS) approaches has significantly aided in raising the prediction accuracy of these results, but measuring the difference in the convergence time of mutant protein structures has been a challenging task while setting the simulation timescale. The convergence time of most of the protein structures may vary from 10 ns to 100 ns or more, depending upon its size. Thus, in this work we have implemented 200 ns of MDS to aid the final results obtained from computational SNP prediction technique. The MDS results have significantly explained the atomic alteration related with the mutant protein and are useful in elaborating the change in structural conformations coupled with the computationally predicted cancer associated mutation. With further advancements in the computational techniques, it will become much easier to predict such mutations with higher accuracy level.

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GWAS reported associations between HLA region SNPs and multiple cancers whose mechanisms remain unexplored. In most cases, whether the associated SNP represents a proxy for an already known HLA association, and if so, whether it is a non-functional proxy or possibly the causal SNP underlying the HLA association, is unknown. To gain mechanistic insight into the reported associations, we compiled cancer associations listed in NHGRI-GWAS catalog and selected ones found in candidate gene studies. We also included hits from the HLA region in breast cancer GWAS. We mapped 32 of them on HLA haplotypes using 103 HLA-typed IHWG reference cell lines, examined their independence, and assessed their functionality by bioinformatics tools and existing empirical evidence. Most SNPs were not exclusive to HLA alleles/haplotypes/lineages, but the SNPs associated with lymphoid malignancies, lung cancer, and nasopharyngeal cancer showed some correlations. One common finding was that most of the cancer-associated SNPs were correlated with MICA/B or HLA class I/II gene expression (especially HLA-DQA1), and some had functional effects on other genes. The non-HLA genes involved in BCL signaling pathway (BAK1 ‘BCL2-antagonist/killer 1’; BAG6 ‘BCL2-associated athanogene 6’), stress response (MICA; HSPA1A/B; BAG6/BAT3), and DNA damage repair (MDC1) appeared to be involved in more than one cancer as causal pathways. Two SNPs showed LD (rs130067/prostate cancer and rs1265100/breast cancer hit in the HLA region), but all others were independent. Overall results showed that there are multiple cancer risk markers within the HLA region, they are independent markers for different cancers, and not simply proxy markers for certain HLA types. This analysis suggests that besides cancer immune surveillance mediated by specific HLA types, involvement of the diverse and rich set of non-HLA genes within the HLA region should be considered in mechanistic studies of HLA and cancer associations.

Long noncoding RNAs and the genetics of cancer.

Cancer is a disease of aberrant gene expression. While the genetic causes of cancer have been intensively studied, it is becoming evident that a large proportion of cancer susceptibility cannot be attributed to variation in protein-coding sequences. This is highlighted by genome-wide association studies in cancer that reveal that more than 80% of cancer-associated SNPs occur in noncoding regions of the genome. In this review, we posit that a significant fraction of the genetic aetiology of cancer is exacted by noncoding regulatory sequences, particularly by long noncoding RNAs (lncRNAs). Recent studies indicate that several cancer risk loci are transcribed into lncRNAs and these transcripts play key roles in tumorigenesis. We discuss the epigenetic and other mechanisms through which lncRNAs function and how they contribute to each stage of cancer progression, understanding of which will be crucial for realising new opportunities in cancer diagnosis and treatment. Long noncoding RNAs play important roles in almost every aspect of cell biology from nuclear organisation and epigenetic regulation to post-transcriptional regulation and splicing, and we link these processes to the hallmarks and genetics of cancer. Finally, we highlight recent progress and future potential in the application of lncRNAs as therapeutic targets and diagnostic markers.

Abstract 2546: Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression.

Abstract We have previously reported an association between prostate cancer (PrCa) risk and rs2242652 on 5p15. rs2242652 lies in intron 4 of TERT, which encodes telomerase reverse transcriptase, the catalytic subunit of the telomerase ribonucleoprotein complex. Telomerase catalyzes the de novo addition of telomere repeat sequences on to chromosome ends and thereby counterbalances telomere-dependent replicative senescence. Associations between SNPs in the TERT region and multiple cancer types have been reported; however no correlation has been observed thus far between the cancer-associated SNPs in TERT and gene expression or telomere length. To comprehensively evaluate the association between genetic variation across this region and PrCa we performed a fine-mapping analysis by direct genotyping using either a custom Illumina iSelect array (114 SNPs on iCOGS) or Sequenom MassArray iPlex (25 SNPs) followed by imputation of 1,094 SNPs in 22,301 PrCa cases and 22,320 controls in the PRACTICAL consortium. To determine independently associated variants in this region, we performed multiple stepwise logistic regression analysis; SNPs were included in the model if they were significant at P<10−4 after adjustment for other SNPs. Regression models identified multiple independent associations, reflecting the complexity of this region. These SNPs fall into four regions consisting of clusters of highly or moderately correlated variants, and there is only weak LD between SNPs in different regions. To investigate whether SNPs in any of these regions were associated with TERT gene expression, we performed qPCR assays on RNA from benign prostate tissue samples using the Fluidigm Biomark™ HD system. We found evidence that the risk reducing alleles of several variants in region one associated with elevated TERT expression, providing a plausible mechanism for the differential effect of SNPs on PrCa risk. Deep re-sequencing of these loci may help to further refine this region and facilitate selection of prospective causal variants for functional validation studies. Citation Format: Zsofia Kote-Jarai, Edward Saunders, Daniel Leongamornlert, Malgorzata Tymrakiewicz, Tokhir Dadaev, Sarah Jugurnauth, Sara Benlloch, Ali Amin Al Olama, Helen Ross-Adams, David Neal, The UKGPCS Collaborators and The PRACTICAL Consortium, Douglas Easton, Rosalind Eeles. Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2546. doi:10.1158/1538-7445.AM2013-2546

A functional link between FOXA1 and breast cancer SNPs

Genome-wide association studies have revealed a multitude of breast cancer-associated SNPs. The majority of these SNPs are located in noncoding regions of the genome. Yet how they contribute to breast cancer development is unknown. Recently, a groundbreaking study by the Lupien group has shown that risk-associated SNPs of breast cancer are enriched for FOXA1 binding sites, which influences the function of this transcription factor.