Genome‐wide scan of long noncoding <scp>RNA</scp> single nucleotide polymorphism<scp>s</scp> and pancreatic cancer susceptibility

Corradi, Chiara; Gentiluomo, Manuel; Gajdán, László; Cavestro, Giulia Martina; Kreivėnaitė, Edita; Franco, Gregorio Di; Sperti, Cosimo; Giaccherini, Matteo; Petrone, Maria Chiara; Tavano, Francesca; Gioffreda, Domenica; Morelli, Luca; Souček, Pavel; Andriulli, Angelo; Izbicki, Jakob R.; Napoli, Niccolò; Małecka‐Panas, Ewa; Hegyi, Péter; Neoptolemos, John P.; Landi, Stefano; Vashist, Yogesh K.; Pasquali, Claudio; Lu, Ye; Červená, Klára; Theodoropoulos, George; Moz, Stefania; Capurso, Gabriele; Strobel, Oliver; Carrara, Sandro; Hackert, Thilo; Hlaváč, Viktor; Archibugi, Lívia; Oliverius, Martin; Vanella, Giuseppe; Vodička, Pavel; Arcidiacono, Paolo Giorgio; Pezzilli, Raffaele; Milanetto, Anna Caterina; Lawlor, Rita T.; Ivanauskas, Audrius; Szentesi, Andrea; Kupčinskas, Juozas; Testoni, Sabrina Gloria Giulia; Loveček, Martin; Nentwich, Michael F.; Gazouli, Maria; Luchini, Claudio; Zuppardo, Raffaella Alessia; Darvasi, Erika; Brenner, Hermann; Gheorghe, Cristian; Jamroziak, Krzysztof; Canzian, Federico; Campa, Daniele

doi:10.1002/ijc.33475

Cited by 27 publications

(22 citation statements)

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“…Further, in most of the studies, the roles/mechanisms of the identified proteins in the pathogenesis of PDAC (e.g., why, and how the expression of proteins are correlated with the extent that they are secreted in normal or diseased conditions) remains unclear due to the singularity of techniques used thus limiting the interpretation of the significance of the study. This by no means only applies to proteomics but other fields of research as well (e.g., genomic [231,232], epigenomic-DNA methylation [233], single-cell transcriptomic [234] and metabolomics approaches [50,235]). One way to solve this is via the integration of multi-omics technologies that combine various approaches such as genomics, epigenomics, transcriptomics and metabolomics, together with proteomics.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Vellan

Jayapalan

Yoong

et al. 2022

IJMS

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Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Vellan

Jayapalan

Yoong

et al. 2022

IJMS

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“…Moreover, rare high-penetrance mutations and high-frequency lowpenetrance variants, discovered through genome-wide association studies (GWASs), contribute, alone or in combination, to the genetic susceptibility of PDAC (7)(8)(9)(10)(11)(12)(13)(14)(15). Additional susceptibility variants have been identified through large multicentric gene candidate approaches and through secondary analysis of published GWAS data (16)(17)(18)(19)(20)(21)(22)(23)(24)(25). The number of identified loci is, however, very small if compared with breast, prostate or colorectal cancers and the fraction of the heritability they explain is limited.…”

Section: Introductionmentioning

confidence: 99%

Associations between pancreatic expression quantitative traits and risk of pancreatic ductal adenocarcinoma

Pistoni

Gentiluomo

et al. 2021

Carcinogenesis

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Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Its poor prognosis is predominantly due to the fact that most patients remain asymptomatic until the disease reaches an advanced stage, alongside the lack of early markers and screening strategies. A better understanding of PDAC risk factors is essential for the identification of groups at high risk in the population. Genome-wide association studies (GWAS) have been a powerful tool for detecting genetic variants associated with complex traits, including pancreatic cancer. By exploiting functional and GWAS data, we investigated the associations between polymorphisms affecting gene function in the pancreas (expression quantitative trait loci, eQTLs) and PDAC risk. In a two-phase approach, we analysed 13 713 PDAC cases and 43 784 controls and identified a genome-wide significant association between the A allele of the rs2035875 polymorphism and increased PDAC risk (P=7.14×10 -10). This allele is known to be associated with increased expression in the pancreas of the keratin genes KRT8 and KRT18, whose increased levels have been reported to correlate with various tumor cell characteristics. Additionally, the A allele of the rs789744 variant was associated with decreased risk of developing PDAC (P=3.56×10 -6). This SNP is situated in the SRGAP1 gene and the A allele is associated with higher expression of the gene, which in turn inactivates the cyclin-dependent protein 42 (CDC42) gene expression, thus decreasing the risk of PDAC. In conclusion, we present here a functional-based novel PDAC risk locus and an additional strong candidate supported by significant associations and plausible biological mechanisms.

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“…In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk. Feng et al, 2019;Gentiluomo et al, 2019a,b;Xu et al, 2019;Yang et al, 2019;Corradi et al, 2021). Only a small number of susceptibility loci for PC risk have been found thus far.…”

Section: Introductionmentioning

confidence: 99%

Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

Corradi

Gentiluomo

et al. 2021

Front. Genet.

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Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case–Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07–1.17, p = 3.03 × 10−6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk.

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Genome‐wide scan of long noncoding RNA single nucleotide polymorphisms and pancreatic cancer susceptibility

Cited by 27 publications

References 50 publications

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Associations between pancreatic expression quantitative traits and risk of pancreatic ductal adenocarcinoma

Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

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