The overall objective of the GCS Group is the evaluation of inherited genetic factors in the etiology and outcome of cancer and the interaction between environmental factors and susceptibility genes.

All common cancer types aggregate in families, with the disease being 2-4-fold more common in the first-degree relatives of the cases of the same type than in the general population. Some of the familial risk can be explained by rare mutation in high-penetrance genes, of which the most important are BRCA1 and BRCA2 for breast and ovarian cancer, mismatch repair genes for colorectal cancer and CDKN2A for melanoma. However, these mutations explain a small fraction of the familial risk. Empirical genome-wide association studies (GWAS) have successfully implicated common SNPs in the etiology of these cancers, but the variants identified so far confer relatively small increments in risk (1.1-1.5-fold), and explain only a small proportion of familial clustering. One strong possibility is that uncommon-to-rare variants in intermediate-risk susceptibility genes, typified by ATM, CHEK2 and PALB2 in breast cancer, and MC1R in melanoma, are responsible for an important component of the missing heritability. GCS projects aim to examine this hypothesis. In the long run, one would hope that, just as discovery of the known high-risk susceptibility genes has led in many cases to effective strategies for reducing risk in carriers, understanding the majority of the genetic risk of these diseases will eventually lead to more widely applicable risk-reduction strategies.


At this time, it is not known what fraction of the genetic risk of breast cancer, melanoma, colon cancer, or papillary thyroid cancer is explained by genes harbouring yet to be identified rare but high-risk sequence variants vs more common modest-risk variants vs less common (or rare) modest-risk variants. By combining case-control genotyping, case-control mutation screening, expression studies and bioinformatics, we are carrying out an integrative analysis of genetic alterations implicated in the development of cancers investigated by GCS. Our research programs aim also to investigate how these genetic factors interact with known environmental factors to modify the risk of developing cancer.

In parallel of its research topics, GCS aims to maintain and to further develop the genetic platform and related Laboratory Information Management System (LIMS) to support GEN large-scale molecular epidemiology projects and other IARC genomics projects.

Current Research Topics:

  • Investigation of the genetic factors influencing prognosis of melanoma, tumour characteristics and outcome.

  • Melanoma provides a unique model for studies of gene-gene and gene-environment interactions in the development of multifactorial diseases, due to several key features. First, there is a major environmental cause of melanoma, exposure to solar UV radiation, which may account for as much as 90% of cases in populations of European origin. Second, sequence variants in 3 classes of genes may determine variation in melanoma risk: high-, intermediate-, and low-risk genes. Third, known susceptibility genes are involved in protection against the effects of UV radiation. These features permit the study of gene-gene and gene-environment interactions, and functional studies on genes whose relationships to the environmental factors are reasonably well understood. We are conducting population and family-based studies to better understand the full frequency spectrum of the genetic factors influencing melanoma risk. The identification of susceptible individuals may aid in increasing sun protection and early detection of melanocytic tumours at the precancerous stage of the disease, altering attitudes toward exposure to sunlight and use of suntans, and protecting the skin from UV damage in populations at risk.

  • Investigation of common and rare genetic variants in breast cancer susceptibility genes.

  • Bioinformatics tools can be used to classify variants as functional or non-functional or to quantify the functionality of the variants. We have developed a new bioinformatics-driven analysis strategy to characterize rare, likely pathogenic sequence variants identified through a case-control mutation screening approach. The underlying assumption for the analysis of rare missense substitutions is that amino acid positions that are important to the native biological functioning of the protein should be conserved across evolutionary history. Our recent studies on the breast cancer susceptibility genes ATM and CHEK2 demonstrate the efficiency of ranking rare missense substitutions using in silico program before comparing the distribution and frequencies of the different types of variants in cases vs controls. Although loss of function mutations in ATM had been associated with intermediate-risk of breast cancer, our strategy allowed us to demonstrate for the first time that a subset of rare missense substitutions also conferred an intermediate-risk of the disease.

  • Classification of missense variants in BRCA1, BRCA2, and in other high-risk susceptibility genes.

  • Disease susceptibility diagnostics based on mutation screening of genes such as BRCA1 and BRCA2 is fast becoming a part of medical practice. At this time, most of the sequence variants that are classified as high-risk are frameshift / nonsense mutations, obvious splice junction inactivating mutations, or large indels. In the course of mutation screening, many missense changes are also observed. While many of these are probably deleterious, and many others are probably innocuous, classifying them presents a challenging problem. Drawing from model organism genome sequence data, we are using cross-species multiple sequence alignment as a tool to aid in classification of such sequence variants.

  • Molecular epidemiology study on radiation-associated thyroid cancer.

  • Papillary Thyroid Carcinoma (PTC) among individuals exposed to radioactive iodine in their childhood or adolescence is a major recognized health consequence of the Chernobyl accident. The risk of radiation-related PTC falls rapidly with increasing age at exposure. Other factors linked to susceptibility to thyroid carcinogenesis after Chernobyl include dose, iodine deficiency, and genetic factors. In collaboration with ENV/RAD, we are conducting a genetic study in young people in the wake of the Chernobyl accident to identify genes that may modify the risk of radiation-related PTC.

  • Whole genome expression profiling and high-density SNP arrays to profile genetic aberrations in kidney cancer, in collaboration with GEN/GEP.

  • To follow-up on results obtained from kidney cancer GWAS undertaken by GEN/GEP, we will investigate the relationship between gene expression profiles and kidney cancer outcome, as well as clinico-pathological characteristics of the cancer, including tumour stage and nuclear grade. The analyses will be conducted on a series of approximately 120 patients diagnosed with clear cell Renal Cell Carcinoma (ccRCC).

  • Maintenance and further development of a partially automated, high throughput genetics platform that supports genotyping, sequence variant discovery, array-based genomics and transcriptomics analyses for all IARC groups.

  • This has required the set up and validation of automated laboratory workflows, development of a GCS lab database, and a Laboratory Information Management System (LIMS) that tracks every step of the laboratory processes and drives communication between the database and laboratory robotics. In 2010, the Illumina array-based platform will be upgraded to Infinium applications for whole genome analyses. Genomics projects that can be conducted on the GSP platform include expression profiling, methylation profiling, large-scale genotyping and mutation screening of candidate genes or loci. For example, in 2009, methylation profiles have been evaluated as potential biomarkers in hepatocellular carcinomas in collaboration with MCA/EGE. In 2010, follow-up studies on tobacco-related cancers candidate genes identified through GWAS by GEN/GEP will be conducted on the mutation-screening platform.

    A more detailed description of the Genetic Services Platform (GSP) is available at: http://www-gcs.iarc.fr/gsp.php

Recent Publications:

  1. Hernandez-Vargas H, Lambert MP, Le Calvez-Kelm F, Gouysse G, McKay-Chopin S, Tavtigian SV, Scoazec JY, Herceg Z (2010). Hepatocellular carcinoma displays distinct DNA methylation signatures with potential as clinical predictors. PLoS One, 5, e9749. PMID: 20305825
  2. Szymanska K, Moore LE, Rothman N, Chow WH, Waldman F, Jaeger E, Waterboer T, Foretova L, Navratilova M, Janout V, Kollarova H, Zaridze D, Matveev V, Mates D, Szeszenia-Dabrowska N, Holcatova I, Bencko V, Le Calvez-Kelm F, Villar S, Pawlita M, Boffetta P, Hainaut P, Brennan P (2010). TP53, EGFR, and KRAS mutations in relation to VHL inactivation and lifestyle risk factors in renal-cell carcinoma from central and eastern Europe. Cancer Lett. [Epub ahead of print] PMID: 20137853
  3. Garritano S, Gemignani F, Palmero EI, Olivier M, Martel-Planche G, Le Calvez-Kelm F, Brugiéres L, Vargas FR, Brentani RR, Ashton-Prolla P, Landi S, Tavtigian SV, Hainaut P, Achatz MI (2010). Detailed haplotype analysis at the TP53 locus in p.R337H mutation carriers in the population of Southern Brazil: evidence for a founder effect. Hum Mutat. 31, 143-50. PMID: 19877175
  4. Tavtigian SV, Oefner PJ, Hartmann A, Healey S, Le Calvez-Kelm F, Lesueur F, Babikyan D, Byrnes GB, Chuang S-C, Forey N, Feuchtinger C, Gioia L, Hall J, Hashibe M, Herte B, McKay-Chopin S, Thomas S, Vallée M, Voegele C, Webb PM, Whiteman DC, Australian Cancer Study, BCFR, kConFab, Sangrajrang S, Hopper JL, Southey MC, Andrulis IL, John EM, Chenevix-Trench G (2009). Rare evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. Am J Hum Genet., 85, 427-46. PMID 19781682
  5. Nguyen-Dumont T, Le Calvez-Kelm F, Forey N, McKay-Chopin S, Garritano S, Gioia-Patricola L, De Silva D, Weigel R, BCFR, KConFab, Sangrajang S, Lesueur F, Tavtigian SV. (2009) Description and validation of high-throughput simultaneous genotyping and mutation scanning by high-resolution melting curve analysis. Hum Mutat, 30, 884-90. PMID19347964
  6. Garritano S, Gemignani F, Voegele C, Nguyen-Dumont T, Le Calvez-Kelm F, De Silva D, Lesueur F, Landi S, Tavtigian SV (2009) Determining the effectiveness of High Resolution Melting analysis for SNP genotyping and mutation scanning at the TP53 locus. BMC Genet, 10,5. PMID19222838
  7. Chaudru V, Lo MT, Lesueur F, Marian C, Mohamdi H, Laud K, Barrois M, Chompret A, Avril MF, Demenais F, Bressac-de Paillerets B. (2009) Protective effect of copy number polymorphism of Glutathione S-Transferase T1 gene on melanoma risk in presence of CDKN2A mutations, MC1R variants and host-related phenotypes. Fam Cancer, 8, 371-7. PMID 19484507
  8. Plon SE, Eccles DM, Easton DF, Foulkes WD, Genuardi M, Greenblatt MS, Hogervorst FB, Hoogerbrugge N, Spurdle AB, and Tavtigian SV for the IARC Unclassified Genetic Variants Working Group (2008) Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum. Mutat., 29, 1282-1291. PMID 18951446
  9. Tavtigian SV, Greenblatt MS, Lesueur F, Byrnes GB; IARC Unclassified Genetic Variants Working Group (2008) In silico analysis of missense substitutions using sequence-alignment based methods. Hum Mutat, 29, 1327-1336. PMID 18951440
  10. Tavtigian SV, Byrnes GB, Goldgar DE, and Thomas A (2008) Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications. Hum Mutat., 29, 1342-1354. PMID 18951461
  11. Lesueur F, de Lichy, M, Barrois M, Durand G, Bombled J, Avril MF, Chompret A, Boitier F, Lenoir G, French Familial Study Group, Bressac-de Paillerets B. (2008) The contribution of large genomic deletions at the CDKN2A locus to the burden of familial melanoma. Br J Cancer, 99, 364-370. PMID 18612309
  12. Voegele C, Tavtigian SV, de Silva D, Cuber S, Thomas A and Le Calvez-Kelm F (2007) A laboratory Information Management System (LIMS) for high throughput genetic platform aimed at candidate gene mutation screening. Bioinformatics, 23, 2504-6. PMID 17709339
  13. Easton DF, Deffenbaugh AM, Pruss D, Frye C, Wenstrom RJ, Allen-Brady K, Tavtigian SV, Monteiro ANA, Iversen ES, Couch FJ, Goldgar DE (2007) A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer predisposition genes. Am J Hum Genet, 81, 873-883. PMID 17924331
  14. Sodha N, Mantoni TS, Tavtigian SV, Eeles R, Garrett MD (2006) Rare germline CHEK2 variants identified in breast cancer families encode proteins that show impaired activation. Cancer Res., 66, 8966-8970. PMID 16982735
  15. Tavtigian SV, Deffenbaugh AM, Yin L, Judkins T, Scholl T, Samollow PB, de Silva D, Zharkikh A, and Thomas A (2006) Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet., 43(4), 295-305. PMID 16014699
  16. Mathe E, Olivier M, Kato S, Ishioka C, Hainaut P, Tavtigian SV (2006) Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of 3 sequence analysis based methods. Nucleic Acids Res, 34(5): 1317-1325. PMID 16395672