Mutation spectrum for liver cancer in Romania

Supplements to:

Mutation Spectrum of Hepatocellular Carcinoma

from Eastern-European Patients betrays the Impact of

a complex Exposome

Anna-Maria Tanase1⁑, Agnès Marchio2⁑, Traian Dumitrascu1, Simona Dima1, Vlad Herlea3, Gabriela Oprisan4, Anne Dejean2, Irinel Popescu1, and Pascal Pineau2*

1-Center of General Surgery and Liver Transplantation, Fundeni Clinical Institute, Sos. Fundeni nr. 258, sector 2, Bucharest, Romania

2-Unité «Organisation Génétique et Oncogenèse», INSERM U993, Institut Pasteur, 75015 Paris, France

3-Department of Pathology, Fundeni Clinical Institute, Sos. Fundeni nr. 258, sector 2, Bucharest, Romania

4-Molecular Biology Laboratory, National Institute for Research/Development of Microbiology and Immunology Cantacuzino, Splaiul Independentei 103, 050096 sector 5, Bucharest, Romania

*: corresponding author: Unité «Organisation Nucléaire et Oncogenèse», 28, rue du Docteur Roux, 75724, Paris cedex 15, France. Email: , phone : 33 1 45 68 88 24, fax: 33 1 45 68 89 43

⁑: should be considered as co-first authors


Material and Methods:

Virus detection and Genotyping

DNA and RNA were extracted from tumors and non-tumor livers as described (Pineau et al, 1999; Pineau et al, 2010). For all patients, HBV and HCV were searched by qPCR (TaqMan assays Pa03453406_S1 for HBV and Pa03453408_s1 for HCV). Hepatitis Delta agent was amplified by nested-PCR using HDV1s-r for external amplification (HDV1s: CGGATGCCCAGGTCGGACCGC, HDV1r: CTCAGGGGAGGATTCACCGAC) and HDV2s-r to amplify internal fragment (DV2s: AAACCTGTGAGTGGAAACCCGC, HDV2r: ATCACCGACGAAGGAAGGCCCTCG) (Mederacke et al, 2010).

Mutation Detection

DNA was extracted as described previously (Pineau, et al., 2008). Mutations were detected by direct PCR amplification and subsequent sequencing performed using the Big Dye Terminator procedure (Applied Biosystems). The somatic nature of mutations was validated by sequencing the germline DNA from matched non-tumor tissues.

Loss of heterozygosity assessment

Polymorphic insertions of retroelements were analyzed on standard 2% agarose gels (Invitrogen, Cergy-Pontoise, France) in 0.5X TBE buffer. Marshfield InDels were explored on a 4% <1000-bp agarose gel (Interchim, Montluçon, France) in 1X TBE buffer. Minimal allelic size differences for Marshfield markers were limited to 10bp in order to get a sufficient resolution on agarose. LOH was scored when validated by two independent scientists (AM, PP). For the High Resolution Melting Analysis genomic DNA was quantified with a spectrophotometer (Nanodrop 1000, Fischer Scientific, Illkirch, France). The 10 ul final reaction mixture contained 50 ng of genomic DNA, 5 ul of the SsoFast EvaGreen supermix (Bio-Rad, Marnes-La-Coquette, France) and 5 pmol of each primer. All reactions were performed in duplicate using a 96 well Hard-Shell PCR plates (Bio-Rad) and sealed with Microseal «B» film (Bio-Rad). Real-time PCR and HRM anaysis were carried out in a CFX real-time PCR detection system (Bio-Rad). The amplication conditions were as follow: 98°C for 2 min, then 35 cycles at 95°C for 5 s and 60°C for 20s. Afterwards, PCR products were heated 1min at 95°C and cooled to 50°C for 1 mn. Finally, the melt curve was generated by mesearing fluorescence during a temperature increase from 60°C to 90°C (with 0,2°C/10-s increments). Results were analysed with Bio-Rad CFX Manager software V.2.0 and then with Bio-Rad Precision Melt Analysis software V1.0. The Normalized Melt curve were obtained by adjustement of the pre- and post- melting regions, the shape sensitivity (17-50) and the Tm difference threshold (0,15) to attain the best clustering. To allow comparison and differenciation between de genotypes, curve differences were magnified by substracting each curve from the heterozygous genotype. Prior to Precision Melt Analysis, all the differences observed in the melting profiles were considered significant if the amplification reactions occured before the quantification cycle (Cq) 30 and if the samples showed an equal plateau of fluorescence.

Real-Time Quantitative RT-PCR

Total RNA was prepared from frozen tissus using Tri-Reagent (Euromedex, Souffelweyersheim, France) and Lysin Matrix D homogeneization (MP Biomedicals, Illkirch, France) in accordance with manufacturer’s instructions. RNA integrity and quantification were assessed with an Agilent 2100 Bioanalyzer and the RNA 6000 LabChip kit (Agilent Technologies, Palo Alto, CA). One mg of Tri-Reagent-extracted RNA was reverse transcribed using a high-capacity cDNA Archive Kit (Applied Biosystems, Foster City, CA) according to the manufacturer's specifications. Real-time PCR was performed in a CFX96 qPCR machine (Bio-Rad). All samples were measured in duplicate. The 10 μl PCR included 20 ng of RT product, 1× TaqMan Universal PCR master mix and 1 μl of pre-validated Taqman Gene Expression Assay (PE Applied Biosystems, SXRN1; Hs00607800_m1, CES1; Hs00275607_m1, Keap1; Hs00202227_m1, NFE2L2; Hs00232352_m1). The reactions were incubated in a 96-well optical plate at 95°C for 10 min, followed by 40 cycles of 95°C for 15s and 60° for 1 min.The Ct data was determinate using default threshold settings. The threshold cycle (Ct) is defined as the fractional cycle number at which the fluorescence passes the fixed threshold. For data analysis, gene expression values were determined using the calculation of the relative quantitation (RQ) of target genes normalized to a calibrator corresponding to 5 normal livers. RQ calculation was performed using the {Delta}{Delta}CT method with the geometric mean of three reference genes (TRIM44, Hs00214040_m1, HMBS; Hs00609297_m1 and LMF2; Hs00611068_m1) as reference. The three references genes were selected among 12 constant genes arising from a previous array analysis of 70 HCC samples and 9 normal livers to which were applied algorithms described by Vandesompele et al. in the geNorm manual available on the web site http://medgen.ugent.be/jvdesomp/genorm. (Vandesompele et al, 2002).

References

Mederacke I, Bremer B, Heidrich B, Kirschner J, Deterding K, Bock T, Wursthorn K, Manns M, Wedemeyer H (2010) Establishment of a novel quantitative hepatitis D virus (HDV) RNA assay using the Cobas TaqMan platform to study HDV RNA kinetics. J Clin Microbiol 48: 2022-9

Pineau P, Nagai H, Prigent S, Wei Y, Gyapay G, Weissenbach J, Tiollais P, Buendia M, Dejean A (1999) Identification of three distinct regions of allelic deletions on the short arm of chromosome 8 in hepatocellular carcinoma. Oncogene 18: 3127-3134

Pineau P, Volinia S, McJunkin K, Marchio A, Battiston C, Terris B, Mazzaferro V, Lowe S, Croce C, Dejean A (2010) MiR-221 Overexpression contributes to liver tumorigenesis. Proc Natl Acad Sci, USA 107: 264-9

Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric

averaging of multiple internal control genes. Genome Biol 3: 34
Legends to the Supplementary Figures

Supplementary Figure 1: A) Mutations affecting NFE2L2 gene in HCC from Romanian patients. B) T>S mutations are significantly associated with MDM2 snp309. C) Loss of heterozigosity (LOH) observed at two different loci.

Supplementary Figure 2: A) Selected genomic alterations in HCC are associated with younger age of patients. LOH on chromosome 10q is exclusively present in tumors from males B) Some clinico-pathological features are correlated with genomic changes. FAL is increased in tumors developed from a non cirrhotic tissue or in poorly differentiated samples (Edmonson-Steiner grade III-IV). C) Oxidative stress in tumor microenvironment (non-tumor tissue) correlates tumor differentiation. Stronger antioxidative responses are significantly associated with poor tumor differentiation (Edmonson-Steiner grade III-IV).

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