The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population

Daniele Balasus, Michael Way, Caterina Fusilli, Tommaso Mazza, Marsha Y Morgan, Melchiorre Cervello, Lydia Giannitrapani, Maurizio Soresi, Rosalia Agliastro, Manlio Vinciguerra, Giuseppe Montalto

Research output: Contribution to journalArticle

Abstract

Hepatocellular carcinoma (HCC) has one of the worst prognoses amongst all malignancies. It commonly arises in patients with established liver disease and the diagnosis often occurs at an advanced stage. Genetic variations, such as single nucleotide polymorphisms (SNPs), may alter disease risk and thus may have use as predictive markers of disease outcome. The aims of this study were (i) to assess the association of two SNPs, rs430397 in GRP78 and rs738409 in PNPLA3 with the risk of developing HCC in a Sicilian association cohort and, (ii) to use a machine learning technique to establish a predictive combinatorial phenotypic model for HCC including rs430397 and rs738409 genotypes and clinical and laboratory attributes. The controls comprised of 304 healthy subjects while the cases comprised of 170 HCC patients the majority of whom had hepatitis C (HCV)-related cirrhosis. Significant associations were identified between the risk of developing HCC and both rs430397 (p=0.0095) and rs738409 (p=0.0063). The association between rs738409 and HCC was significantly stronger in the HCV positive cases. In the best prediction model, represented graphically by a decision tree with an acceptable misclassification rate of 17.0%, the A/A and G/A genotypes of the rs430397 variant were fixed and combined with the three rs738409 genotypes; the attributes were age, sex and alcohol. These results demonstrate significant associations between both rs430397 and rs738409 and HCC development in a Sicilian cohort. The combinatorial predictive model developed to include these genetic variants may, if validated in independent cohorts, allow for earlier diagnosis of HCC.

Original languageEnglish
Pages (from-to)86791-86802
Number of pages12
JournalOncotarget
Volume7
Issue number52
DOIs
Publication statusPublished - Dec 27 2016

Fingerprint

Hepatocellular Carcinoma
Population
Genotype
Single Nucleotide Polymorphism
Decision Trees
Hepatitis C
Liver Diseases
Early Diagnosis
Healthy Volunteers
Fibrosis
Alcohols
Neoplasms

Keywords

  • Journal Article

Cite this

The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population. / Balasus, Daniele; Way, Michael; Fusilli, Caterina; Mazza, Tommaso; Morgan, Marsha Y; Cervello, Melchiorre; Giannitrapani, Lydia; Soresi, Maurizio; Agliastro, Rosalia; Vinciguerra, Manlio; Montalto, Giuseppe.

In: Oncotarget, Vol. 7, No. 52, 27.12.2016, p. 86791-86802.

Research output: Contribution to journalArticle

Balasus, D, Way, M, Fusilli, C, Mazza, T, Morgan, MY, Cervello, M, Giannitrapani, L, Soresi, M, Agliastro, R, Vinciguerra, M & Montalto, G 2016, 'The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population', Oncotarget, vol. 7, no. 52, pp. 86791-86802. https://doi.org/10.18632/oncotarget.13558
Balasus, Daniele ; Way, Michael ; Fusilli, Caterina ; Mazza, Tommaso ; Morgan, Marsha Y ; Cervello, Melchiorre ; Giannitrapani, Lydia ; Soresi, Maurizio ; Agliastro, Rosalia ; Vinciguerra, Manlio ; Montalto, Giuseppe. / The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population. In: Oncotarget. 2016 ; Vol. 7, No. 52. pp. 86791-86802.
@article{c8177af80c514ce8a53806a8316b2857,
title = "The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population",
abstract = "Hepatocellular carcinoma (HCC) has one of the worst prognoses amongst all malignancies. It commonly arises in patients with established liver disease and the diagnosis often occurs at an advanced stage. Genetic variations, such as single nucleotide polymorphisms (SNPs), may alter disease risk and thus may have use as predictive markers of disease outcome. The aims of this study were (i) to assess the association of two SNPs, rs430397 in GRP78 and rs738409 in PNPLA3 with the risk of developing HCC in a Sicilian association cohort and, (ii) to use a machine learning technique to establish a predictive combinatorial phenotypic model for HCC including rs430397 and rs738409 genotypes and clinical and laboratory attributes. The controls comprised of 304 healthy subjects while the cases comprised of 170 HCC patients the majority of whom had hepatitis C (HCV)-related cirrhosis. Significant associations were identified between the risk of developing HCC and both rs430397 (p=0.0095) and rs738409 (p=0.0063). The association between rs738409 and HCC was significantly stronger in the HCV positive cases. In the best prediction model, represented graphically by a decision tree with an acceptable misclassification rate of 17.0{\%}, the A/A and G/A genotypes of the rs430397 variant were fixed and combined with the three rs738409 genotypes; the attributes were age, sex and alcohol. These results demonstrate significant associations between both rs430397 and rs738409 and HCC development in a Sicilian cohort. The combinatorial predictive model developed to include these genetic variants may, if validated in independent cohorts, allow for earlier diagnosis of HCC.",
keywords = "Journal Article",
author = "Daniele Balasus and Michael Way and Caterina Fusilli and Tommaso Mazza and Morgan, {Marsha Y} and Melchiorre Cervello and Lydia Giannitrapani and Maurizio Soresi and Rosalia Agliastro and Manlio Vinciguerra and Giuseppe Montalto",
year = "2016",
month = "12",
day = "27",
doi = "10.18632/oncotarget.13558",
language = "English",
volume = "7",
pages = "86791--86802",
journal = "Oncotarget",
issn = "1949-2553",
publisher = "Impact Journals LLC",
number = "52",

}

TY - JOUR

T1 - The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population

AU - Balasus, Daniele

AU - Way, Michael

AU - Fusilli, Caterina

AU - Mazza, Tommaso

AU - Morgan, Marsha Y

AU - Cervello, Melchiorre

AU - Giannitrapani, Lydia

AU - Soresi, Maurizio

AU - Agliastro, Rosalia

AU - Vinciguerra, Manlio

AU - Montalto, Giuseppe

PY - 2016/12/27

Y1 - 2016/12/27

N2 - Hepatocellular carcinoma (HCC) has one of the worst prognoses amongst all malignancies. It commonly arises in patients with established liver disease and the diagnosis often occurs at an advanced stage. Genetic variations, such as single nucleotide polymorphisms (SNPs), may alter disease risk and thus may have use as predictive markers of disease outcome. The aims of this study were (i) to assess the association of two SNPs, rs430397 in GRP78 and rs738409 in PNPLA3 with the risk of developing HCC in a Sicilian association cohort and, (ii) to use a machine learning technique to establish a predictive combinatorial phenotypic model for HCC including rs430397 and rs738409 genotypes and clinical and laboratory attributes. The controls comprised of 304 healthy subjects while the cases comprised of 170 HCC patients the majority of whom had hepatitis C (HCV)-related cirrhosis. Significant associations were identified between the risk of developing HCC and both rs430397 (p=0.0095) and rs738409 (p=0.0063). The association between rs738409 and HCC was significantly stronger in the HCV positive cases. In the best prediction model, represented graphically by a decision tree with an acceptable misclassification rate of 17.0%, the A/A and G/A genotypes of the rs430397 variant were fixed and combined with the three rs738409 genotypes; the attributes were age, sex and alcohol. These results demonstrate significant associations between both rs430397 and rs738409 and HCC development in a Sicilian cohort. The combinatorial predictive model developed to include these genetic variants may, if validated in independent cohorts, allow for earlier diagnosis of HCC.

AB - Hepatocellular carcinoma (HCC) has one of the worst prognoses amongst all malignancies. It commonly arises in patients with established liver disease and the diagnosis often occurs at an advanced stage. Genetic variations, such as single nucleotide polymorphisms (SNPs), may alter disease risk and thus may have use as predictive markers of disease outcome. The aims of this study were (i) to assess the association of two SNPs, rs430397 in GRP78 and rs738409 in PNPLA3 with the risk of developing HCC in a Sicilian association cohort and, (ii) to use a machine learning technique to establish a predictive combinatorial phenotypic model for HCC including rs430397 and rs738409 genotypes and clinical and laboratory attributes. The controls comprised of 304 healthy subjects while the cases comprised of 170 HCC patients the majority of whom had hepatitis C (HCV)-related cirrhosis. Significant associations were identified between the risk of developing HCC and both rs430397 (p=0.0095) and rs738409 (p=0.0063). The association between rs738409 and HCC was significantly stronger in the HCV positive cases. In the best prediction model, represented graphically by a decision tree with an acceptable misclassification rate of 17.0%, the A/A and G/A genotypes of the rs430397 variant were fixed and combined with the three rs738409 genotypes; the attributes were age, sex and alcohol. These results demonstrate significant associations between both rs430397 and rs738409 and HCC development in a Sicilian cohort. The combinatorial predictive model developed to include these genetic variants may, if validated in independent cohorts, allow for earlier diagnosis of HCC.

KW - Journal Article

U2 - 10.18632/oncotarget.13558

DO - 10.18632/oncotarget.13558

M3 - Article

C2 - 27888630

VL - 7

SP - 86791

EP - 86802

JO - Oncotarget

JF - Oncotarget

SN - 1949-2553

IS - 52

ER -