Genetic factors for differentiated thyroid cancer in French Polynesia: new candidate loci.

Background: Populations of French Polynesia (FP), where France performed atmospheric tests between 1966 and 1974, experience a high incidence of differentiated thyroid cancer (DTC). However, up to now, no sufficiently large study of DTC genetic factors in this population has been performed to reach definitive conclusion. This research aimed to analyze the genetic factors of DTC risk among the native FP populations. Methods: We analyzed more than 300 000 single nucleotide polymorphisms (SNPs) genotyped in 283 DTC cases and 418 matched controls born in FP, most being younger than 15 years old at the time of the first nuclear tests. We analyzed the genetic profile of our cohort to identify population subgroups. We then completed a genome-wide analysis study on the whole population. Results: We identified a specific genetic structure in the FP population reflecting admixture from Asian and European populations. We identified three regions associated with increased DTC risk at 6q24.3, 10p12.2, and 17q21.32. The lead SNPs at these loci showed respective p-values of 1.66 × 10-7, 2.39 × 10-7, and 7.19 × 10-7 and corresponding odds ratios of 2.02, 1.89, and 2.37. Conclusion: Our study results suggest a role of the loci 6q24.3, 10p12.2 and 17q21.32 in DTC risk. However, a whole genome sequencing approach would be better suited to characterize these factors than genotyping with microarray chip designed for the Caucasian population. Moreover, the functional impact of these three new loci needs to be further explored and validated.

Assessment of Differentiated Thyroid Carcinomas in French Polynesia After Atmospheric Nuclear Tests Performed by France.

Importance: Due to the amount of iodine 131 released in nuclear tests and its active uptake by the thyroid, differentiated thyroid carcinoma (DTC) is the most serious health risk for the population living near sites of nuclear tests. Whether low doses to the thyroid from nuclear fallout are associated with increased risk of thyroid cancer remains a controversial issue in medicine and public health, and a misunderstanding of this issue may be associated with overdiagnosis of DTCs. Design, Setting, and Participants: This case-control study was conducted by extending a case-control study published in 2010 that included DTCs diagnosed between 1984 and 2003 by adding DTCs diagnosed between 2004 and 2016 and improving the dose assessment methodology. Data on 41 atmospheric nuclear tests conducted by France between 1966 and 1974 in French Polynesia (FP) were assessed from original internal radiation-protection reports, which the French military declassified in 2013 and which included measurements in soil, air, water, milk, and food in all FP archipelagos. These original reports led to an upward reassessment of the nuclear fallout from the tests and a doubling of estimates of the mean thyroid radiation dose received by inhabitants from 2 mGy to nearly 5 mGy. Included patients were diagnosed from 1984 to 2016 with DTC at age 55 years or younger and were born in and resided in FP at diagnosis; 395 of 457 eligible cases were included, and up to 2 controls per case nearest by birthdate and matched on sex were identified from the FP birth registry. Data were analyzed from March 2019 through October 2021. Exposure: The radiation dose to the thyroid gland was estimated using recently declassified original radiation-protection service reports, meteorological reports, self-reported lifestyle information, and group interviews of key informants and female individuals who had children at the time of these tests. Main Outcomes and Measures: The lifetime risk of DTC based on Biological Effects of Ionizing Radiation (BEIR) VII models was estimated. Results: A total of 395 DTC cases (336 females [85.1%]; mean [SD] age at end of follow-up, 43.6 [12.9] years) and 555 controls (473 females [85.2%]; mean [SD] age at end of follow-up, 42.3 [12.5] years) were included. No association was found between thyroid radiation dose received before age 15 years and risk of DTC (excess relative risk [ERR] per milligray, 0.04; 95% CI, -0.09 to 0.17; P = .27). When excluding unifocal noninvasive microcarcinomas, the dose response was significant (ERR per milligray, 0.09; 95% CI, -0.03 to 0.02; P = .02), but several incoherencies with the results of the initial study reduce the credibility of this result. The lifetime risk for the entire FP population was 29 cases of DTC (95% CI, 8-97 cases), or 2.3% (95% CI, 0.6%-7.7%) of 1524 sporadic DTC cases in this population. Conclusions and Relevance: This case-control study found that French nuclear tests were associated with an increase in lifetime risk of PTC in FP residents of 29 cases of PTC. This finding suggests that the number of thyroid cancer cases and the true order of magnitude of health outcomes associated with these nuclear tests were small, which may reassure populations of this Pacific territory.

Role of DNA Repair Variants and Diagnostic Radiology Exams in Differentiated Thyroid Cancer Risk: A Pooled Analysis of Two Case-Control Studies.

BACKGROUND: Given the increased use and diversity of diagnostic procedures, it is important to understand genetic susceptibility to radiation-induced thyroid cancer. METHODS: On the basis of self-declared diagnostic radiology examination records in addition to existing literature, we estimated the radiation dose delivered to the thyroid gland from diagnostic procedures during childhood and adulthood in two case-control studies conducted in France. A total of 1,071 differentiated thyroid cancer (DTC) cases and 1,188 controls from the combined studies were genotyped using a custom-made Illumina OncoArray DNA chip. We focused our analysis on variants in genes involved in DNA damage response and repair pathways, representing a total of 5,817 SNPs in 571 genes. We estimated the OR per milli-Gray (OR/mGy) of the radiation dose delivered to the thyroid gland using conditional logistic regression. We then used an unconditional logistic regression model to assess the association between DNA repair gene variants and DTC risk. We performed a meta-analysis of the two studies. RESULTS: The OR/mGy was 1.02 (95% confidence interval, 1.00-1.03). We found significant associations between DTC and rs7164173 in CHD2 (P = 5.79 × 10-5), rs6067822 in NFATc2 (P = 9.26 × 10-5), rs1059394 and rs699517 both in ENOSF1/THYS, rs12702628 in RPA3, and an interaction between rs7068306 in MGMT and thyroid radiation doses (P = 3.40 × 10-4). CONCLUSIONS: Our results suggest a role for variants in CDH2, NFATc2, ENOSF1/THYS, RPA3, and MGMT in DTC risk. IMPACT: CDH2, NFATc2, ENOSF1/THYS, and RPA3 have not previously been shown to be associated with DTC risk.

Genetic susceptibility to radiation-related differentiated thyroid cancers: a systematic review of literature.

The first study establishing exposure to ionizing radiations (IRs) as a risk factor for differentiated thyroid cancer (DTC) was published 70 years ago. Given that radiation exposure causes direct DNA damage, genetic alterations in the different DNA repair mechanisms are assumed to play an important role in long-term IR-induced DNA damage prevention. Individual variations in DNA repair capacity may cause different reactions to damage made by IR exposure. The aim of this review is to recapitulate current knowledge about constitutional genetic polymorphisms found to be significantly associated with DTC occurring after IR exposure. Studies were screened online using electronic databases - only fully available articles, and studies performed among irradiated population or taking radiation exposure as adjustment factors and showing significant results are included. Nine articles were identified. Ten variants in/near to genes in six biological pathways, namely thyroid activity regulations, generic transcription, RET signaling, ATM signaling and DNA repair pathways were found to be associated with radiation-related DTC in these studies. Only seven variants were found to be in interaction with IR exposure in DTC risk. Most of these variants are also associated to sporadic DTC and are not specific to IR-related DTC. In the published studies, no data on children treated with radiotherapy is described. In conclusion, more studies carried out on larger cohorts or on case-control studies with well-documented individual radiation dose estimations are needed to get a comprehensive picture of genetic susceptibility factors involved in radiation-related DTC.

Comparative analysis of micro-RNAs in human papillomavirus-positive versus -negative oropharyngeal cancers.

BACKGROUND: Oncogenic mechanisms of human papillomavirus (HPV)-positive oropharyngeal cancer are still poorly characterized. Analysis of their microRNA expression profile might provide valuable information. METHODS: The microRNA expression profiles were analyzed by micro-arrays in 26 oropharyngeal cancers. A microRNA signature specific to HPV-status was identified by analyzing a learning/training set consisting of 16 oropharyngeal cancers. The robustness of this signature was further confirmed by blind case-by-case classification of a validation set composed of 10 independent tumors. Putative targeted molecular pathways were proposed using DIANA miRPath online software (http://microrna.gr/mirpath). RESULTS: We have identified 25 miRNA signatures, which discriminates HPV16-positive oropharyngeal cancer from their HPV-negative counterparts. These 25 microRNAs play a potential role in Wnt and PI3K-pathways, cell-adhesion/cell-polarity, and the cytoskeleton regulation. CONCLUSION: Our study contributes to a better understanding of pathogenic mechanisms involved in the development of HPV-positive oropharyngeal cancer and in the identification of potential therapeutic molecular targets. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1708-1716, 2016.

A predictive transcriptomic signature of oropharyngeal cancer according to HPV16 status exclusively.

OBJECTIVE: Human-papillomaviruses (HPV) type 16 is a causative agent in an increasing subset of oropharyngeal squamous cell carcinomas (OPSCCs). These tumors have distinct oncogenic mechanisms and a more favorable prognosis than tobacco-induced OPSCCs. Although these differences emphasize the need for a specific therapeutic approach, HPV status is still not used to guide treatment. A better characterization of the molecular profile related to HPV16-induced OPSCC might help to develop personalized treatments. PATIENTS AND METHODS: Using a human whole-genome DNA-microarray, we have examined the gene expression profiles in 15 HPV-negative and 15 transcriptionally-active HPV-positive OPSCCs. The study was conducted in two steps. Firstly, a learning/training-set consisting of 8 HPV16-positive and 8 HPV16-negative OPSCCs was analyzed to identify a specific signature. Potentially confounding factors (stage, sex and tobacco) were equally distributed in both groups. Subsequently the robustness of this signature was confirmed by blind case-by-case classification of a validation-set composed of the 14 remaining tumors. RESULTS: We have identified a signature composed of 224 genes, which discriminates HPV16-induced OPSCC from their HPV-negative counterparts. After the blind classification of the 14 tumours, the viral status was revealed: 13 out of 14 tumors were correctly classified according to tumor etiology, 1/14 was not determined and none were misclassified. Several of the differentially expressed genes were involved in cell-cycle regulation, DNA replication and repair, transcription regulation, immune response and apoptosis. CONCLUSION: Our study contributes to a better understanding of pathogenic mechanisms involved in the development of HPV-positive OPSCCs and in the identification of potential therapeutic targets.

Comparison of transcriptomic signature of post-Chernobyl and postradiotherapy thyroid tumors.

BACKGROUND: We previously identified two highly discriminating and predictive radiation-induced transcriptomic signatures by comparing series of sporadic and postradiotherapy thyroid tumors (322-gene signature), and by reanalyzing a previously published data set of sporadic and post-Chernobyl thyroid tumors (106-gene signature). The aim of the present work was (i) to compare the two signatures in terms of gene expression deregulations and molecular features/pathways, and (ii) to test the capacity of the postradiotherapy signature in classifying the post-Chernobyl series of tumors and reciprocally of the post-Chernobyl signature in classifying the postradiotherapy-induced tumors. METHODS: We now explored if postradiotherapy and post-Chernobyl papillary thyroid carcinomas (PTC) display common molecular features by comparing molecular pathways deregulated in the two tumor series, and tested the potential of gene subsets of the postradiotherapy signature to classify the post-Chernobyl series (14 sporadic and 12 post-Chernobyl PTC), and reciprocally of gene subsets of the post-Chernobyl signature to classify the postradiotherapy series (15 sporadic and 12 postradiotherapy PTC), by using conventional principal component analysis. RESULTS: We found that the five genes common to the two signatures classified the learning/training tumors (used to search these signatures) of both the postradiotherapy (seven PTC) and the post-Chernobyl (six PTC) thyroid tumor series as compared with the sporadic tumors (seven sporadic PTC in each series). Importantly, these five genes were also effective for classifying independent series of postradiotherapy (five PTC) and post-Chernobyl (six PTC) tumors compared to independent series of sporadic tumors (eight PTC and six PTC respectively; testing tumors). Moreover, part of each postradiotherapy (32 genes) and post-Chernobyl signature (16 genes) cross-classified the respective series of thyroid tumors. Finally, several molecular pathways deregulated in post-Chernobyl tumors matched those found to be deregulated in postradiotherapy tumors. CONCLUSIONS: Overall, our data suggest that thyroid tumors that developed following either external exposure or internal (131)I contamination shared common molecular features, related to DNA repair, oxidative and endoplasmic reticulum stresses, allowing their classification as radiation-induced tumors in comparison with sporadic counterparts, independently of doses and dose rates, which suggests there may be a "general" radiation-induced signature of thyroid tumors.

Strategy to find molecular signatures in a small series of rare cancers: validation for radiation-induced breast and thyroid tumors.

Methods of classification using transcriptome analysis for case-by-case tumor diagnosis could be limited by tumor heterogeneity and masked information in the gene expression profiles, especially as the number of tumors is small. We propose a new strategy, EMts_2PCA, based on: 1) The identification of a gene expression signature with a great potential for discriminating subgroups of tumors (EMts stage), which includes: a) a learning step, based on an expectation-maximization (EM) algorithm, to select sets of candidate genes whose expressions discriminate two subgroups, b) a training step to select from the sets of candidate genes those with the highest potential to classify training tumors, c) the compilation of genes selected during the training step, and standardization of their levels of expression to finalize the signature. 2) The predictive classification of independent prospective tumors, according to the two subgroups of interest, by the definition of a validation space based on a two-step principal component analysis (2PCA). The present method was evaluated by classifying three series of tumors and its robustness, in terms of tumor clustering and prediction, was further compared with that of three classification methods (Gene expression bar code, Top-scoring pair(s) and a PCA-based method). Results showed that EMts_2PCA was very efficient in tumor classification and prediction, with scores always better that those obtained by the most common methods of tumor clustering. Specifically, EMts_2PCA permitted identification of highly discriminating molecular signatures to differentiate post-Chernobyl thyroid or post-radiotherapy breast tumors from their sporadic counterparts that were previously unsuccessfully classified or classified with errors.

A transcriptome signature distinguished sporadic from postradiotherapy radiation-induced sarcomas.

Exposure to ionizing radiation is a known risk factor for cancer. However, up to now, rigorously defined scientific criteria that could establish case-by-case the radiation-induced (RI) origin of a tumour have been lacking. To identify genes that could constitute a RI signature, we compared the transcriptome of 12 sarcomas arising in the irradiation field of a primary tumour following radiotherapy with the transcriptome of 12 sporadic sarcomas. This learning/training set contained four leiomyosarcomas, four osteosarcomas and four angiosarcomas in each subgroup. We identified a signature of 135 genes discriminating RI from sporadic sarcomas. The robustness of this signature was tested by the blind case-by-case classification of an independent set of 36 sarcomas of various histologies. Thirty-one sarcomas were classified as RI or sporadic; it was not possible to propose an aetiology for the five others. After the code break, it was found that one sporadic sarcoma was misclassified as RI. Thus, the signature is robust with a sensitivity of 96%, a positive and a negative predictive value of 96 and 100%, respectively and a specificity of 62%. The functions of the genes of the signature suggest that RI sarcomas were subject to chronic oxidative stress probably due to mitochondrial dysfunction.

Discriminating gene expression signature of radiation-induced thyroid tumors after either external exposure or internal contamination.

Both external radiation exposure and internal radionuclide contamination are well known risk factors in the development of thyroid epithelial tumors. The identification of specific molecular markers deregulated in radiation-induced thyroid tumors is important for the etiological diagnosis since neither histological features nor genetic alterations can discriminate between sporadic and radiation-induced tumors. Identification of highly discriminating markers in radiation-induced tumors is challenging as it relies on the ability to identify marker deregulation which is associated with a cellular stress that occurred many years before in the thyroid cells. The existence of such a signature is still controversial, as it was not found in several studies while a highly discriminating signature was found in both post-radiotherapy and post-Chernobyl series in other studies. Overall, published studies searching for radiation-induced thyroid tumor specificities, using transcriptomic, proteomic and comparative genomic hybridization approaches, and bearing in mind the analytical constraints required to analyze such small series of tumors, suggest that such a molecular signature could be found. In comparison with sporadic tumors, we highlight molecular similarities and specificities in tumors occurring after high-dose external radiation exposure, such as radiotherapy, and in post-Chernobyl tumors that occurred after internal 131I contamination. We discuss the relevance of signature extrapolation from series of tumors developing after high and low doses in the identification of tumors induced at very low doses of radiation.

Gene expression signature discriminates sporadic from post-radiotherapy-induced thyroid tumors.

Both external and internal exposure to ionizing radiation are strong risk factors for the development of thyroid tumors. Until now, the diagnosis of radiation-induced thyroid tumors has been deduced from a network of arguments taken together with the individual history of radiation exposure. Neither the histological features nor the genetic alterations observed in these tumors have been shown to be specific fingerprints of an exposure to radiation. The aim of our work is to define ionizing radiation-related molecular specificities in a series of secondary thyroid tumors developed in the radiation field of patients treated by radiotherapy. To identify molecular markers that could represent a radiation-induction signature, we compared 25K microarray transcriptome profiles of a learning set of 28 thyroid tumors, which comprised 14 follicular thyroid adenomas (FTA) and 14 papillary thyroid carcinomas (PTC), either sporadic or consecutive to external radiotherapy in childhood. We identified a signature composed of 322 genes which discriminates radiation-induced tumors (FTA and PTC) from their sporadic counterparts. The robustness of this signature was further confirmed by blind case-by-case classification of an independent set of 29 tumors (16 FTA and 13 PTC). After the histology code break by the clinicians, 26/29 tumors were well classified regarding tumor etiology, 1 was undetermined, and 2 were misclassified. Our results help shed light on radiation-induced thyroid carcinogenesis, since specific molecular pathways are deregulated in radiation-induced tumors.