Integrative and comparative genomic analyses identify clinically relevant pulmonary carcinoid groups and unveil the supra-carcinoids

International audienceThe worldwide incidence of pulmonary carcinoids is increasing, but little is known about their molecular characteristics. Through machine learning and multi-omics factor analysis, we compare and contrast the genomic profiles of 116 pulmonary carcinoids (including 35 atypical), 75 large-cell neuroendocrine carcinomas (LCNEC), and 66 small-cell lung cancers. Here we report that the integrative analyses on 257 lung neuroendocrine neoplasms stratify atypical carcinoids into two prognostic groups with a 10-year overall survival of 88% and 27%, respectively. We identify therapeutically relevant molecular groups of pulmonary car-cinoids, suggesting DLL3 and the immune system as candidate therapeutic targets; we confirm the value of OTP expression levels for the prognosis and diagnosis of these diseases, and we unveil the group of supra-carcinoids. This group comprises samples with carcinoid-like morphology yet the molecular and clinical features of the deadly LCNEC, further supporting the previously proposed molecular link between the low-and high-grade lung neuroendocrine neoplasms

Utiliser la nature systématique des erreurs dans les données NGS pour détecter efficacement les mutations : méthodes de calcul et application à la détection précoce du cancer

Comprehensive characterization of DNA variations can help to progress in multiple cancer genomics fields. Next Generation Sequencing (NGS) is currently the most efficient technique to determine a DNA sequence, due to low experiment cost and time compared to the traditional Sanger sequencing. Nevertheless, detection of mutations from NGS data is still a difficult problem, in particular for somatic mutations present in very low abundance like when trying to identify tumor subclonal mutations, tumor-derived mutations in cell free DNA, or somatic mutations from histological normal tissue. The main difficulty is to precisely distinguish between true mutations from sequencing artifacts as they reach similar levels. In this thesis we have studied the systematic nature of errors in NGS data to propose efficient methodologies in order to accurately identify mutations potentially in low proportion. In a first chapter, we describe needlestack, a new variant caller based on the modelling of systematic errors across multiple samples to extract candidate mutations. In a second chapter, we propose two post-calling variant filtering methods based on new summary statistics and on machine learning, with the aim of boosting the precision of mutation detection through the identification of non-systematic errors. Finally, in a last chapter we apply these approaches to develop cancer early detection biomarkers using circulating tumor DNALa caractérisation exaustive des variations de l'ADN peut aider à progresser dans de nombreux champs liés à la génomique du cancer. Le séquençage nouvelle génération (NGS en anglais pour Next Generation Sequencing) est actuellement la technique la plus efficace pour déterminer une séquence ADN, du aux faibles coûts et durées des expériences comparé à la méthode de séquençage traditionnelle de Sanger. Cependant, la détection de mutations à partir de données NGS reste encore un problème difficile, en particulier pour les mutations somatiques présentes en très faible abondance comme lorsque l'on essaye d'identifier des mutations sous-clonales d'une tumeur, des mutations dérivées de la tumeur dans l'ADN circulant libre, ou des mutations somatiques dans des tissus normaux. La difficulté principale est de précisement distinguer les vraies mutations des artefacts de séquençage du au fait qu'ils atteignent des niveaux similaires. Dans cette thèse nous avons étudié la nature systématique des erreurs dans les données NGS afin de proposer des méthodologies efficaces capables d'identifier des mutations potentiellement en faible abondance. Dans un premier chapitre, nous decrivons needlestack, un nouvel outil d'appel de variants basé sur la modélisation des erreurs systématiques sur plusieurs échantillons pour extraire des mutations candidates. Dans un deuxième chapitre, nous proposons deux méthodes de filtrage des variants basées sur des résumés statistiques et sur de l'apprentissage automatique, dans le but de d'améliorer la précision de la détection des mutations par l'identification des erreurs non-systématiques. Finalement, dans un dernier chapitre nous appliquons ces approches pour développer des biomarqueurs de détection précoce du cancer en utilisant l'ADN circulant tumora

TP53 Targeted Deep Sequencing of Cell-Free DNA in Esophageal Squamous Cell Carcinoma Using Low-Quality Serum: Concordance with Tumor Mutation

Circulating cell-free DNA (cfDNA) is emerging as a potential tumor biomarker. CfDNA-based biomarkers may be applicable in tumors without an available non-invasive screening method among at-risk populations. Esophageal squamous cell carcinoma (ESCC) and residents of the Asian cancer belt are examples of those malignancies and populations. Previous epidemiological studies using cfDNA have pointed to the need for high volumes of good quality plasma (i.e., >1 mL plasma with 0 or 1 cycles of freeze-thaw) rather than archival serum, which is often the main available source of cfDNA in retrospective studies. Here, we have investigated the concordance of TP53 mutations in tumor tissue and cfDNA extracted from archival serum left-over from 42 cases and 39 matched controls (age, gender, residence) in a high-risk area of Northern Iran (Golestan). Deep sequencing of TP53 coding regions was complemented with a specialized variant caller (Needlestack). Overall, 23% to 31% of mutations were concordantly detected in tumor and serum cfDNA (based on two false discovery rate thresholds). Concordance was positively correlated with high cfDNA concentration, smoking history (p-value = 0.02) and mutations with a high potential of neoantigen formation (OR; 95%CI = 1.9 (1.11–3.29)), suggesting that tumor DNA release in the bloodstream might reflect the effects of immune and inflammatory context on tumor cell turnover. We identified TP53 mutations in five controls, one of whom was subsequently diagnosed with ESCC. Overall, the results showed that cfDNA mutations can be reliably identified by deep sequencing of archival serum, with a rate of success comparable to plasma. Nonetheless, 70% non-identifiable mutations among cancer patients and 12% mutation detection in controls are the main challenges in applying cfDNA to detect tumor-related variants when blindly targeting whole coding regions of the TP53 gene in ESCC

The PI3K/mTOR Pathway Is Targeted by Rare Germline Variants in Patients with Both Melanoma and Renal Cell Carcinoma

Background: Malignant melanoma and RCC have different embryonic origins, no common lifestyle risk factors but intriguingly share biological properties such as immune regulation and radioresistance. An excess risk of malignant melanoma is observed in RCC patients and vice versa. This bidirectional association is poorly understood, and hypothetic genetic co-susceptibility remains largely unexplored. Results: We hereby provide a clinical and genetic description of a series of 125 cases affected by both malignant melanoma and RCC. Clinical germline mutation testing identified a pathogenic variant in a melanoma and/or RCC predisposing gene in 17/125 cases (13.6%). This included mutually exclusive variants in MITF (p.E318K locus, N = 9 cases), BAP1 (N = 3), CDKN2A (N = 2), FLCN (N = 2), and PTEN (N = 1). A subset of 46 early-onset cases, without underlying germline variation, was whole-exome sequenced. In this series, thirteen genes were significantly enriched in mostly exclusive rare variants predicted to be deleterious, compared to 19,751 controls of similar ancestry. The observed variation mainly consisted of novel or low-frequency variants (<0.01%) within genes displaying strong evolutionary mutational constraints along the PI3K/mTOR pathway, including PIK3CD, NFRKB, EP300, MTOR, and related epigenetic modifier SETD2. The screening of independently processed germline exomes from The Cancer Genome Atlas confirmed an association with melanoma and RCC but not with cancers of established differing etiology such as lung cancers. Conclusions: Our study highlights that an exome-wide case-control enrichment approach may better characterize the rare variant-based missing heritability of multiple primary cancers. In our series, the co-occurrence of malignant melanoma and RCC was associated with germline variation in the PI3K/mTOR signaling cascade, with potential relevance for early diagnostic and clinical management

The PI3K/mTOR pathway Is targeted by rare germline variants in patients with both melanoma and renal cell carcinoma

International audienceBackground: Malignant melanoma and RCC have different embryonic origins, no common lifestyle risk factors but intriguingly share biological properties such as immune regulation and radioresistance. An excess risk of malignant melanoma is observed in RCC patients and vice versa. This bidirectional association is poorly understood, and hypothetic genetic co-susceptibility remains largely unexplored. Results: We hereby provide a clinical and genetic description of a series of 125 cases affected by both malignant melanoma and RCC. Clinical germline mutation testing identified a pathogenic variant in a melanoma and/or RCC predisposing gene in 17/125 cases (13.6%). This included mutually exclusive variants in MITF (p.E318K locus, N = 9 cases), BAP1 (N = 3), CDKN2A (N = 2), FLCN (N = 2), and PTEN (N = 1). A subset of 46 early-onset cases, without underlying germline variation, was whole-exome sequenced. In this series, thirteen genes were significantly enriched in mostly exclusive rare variants predicted to be deleterious, compared to 19,751 controls of similar ancestry. The observed variation mainly consisted of novel or low-frequency variants (<0.01%) within genes displaying strong evolutionary mutational constraints along the PI3K/mTOR pathway, including PIK3CD, NFRKB, EP300, MTOR, and related epigenetic modifier SETD2. The screening of independently processed germline exomes from The Cancer Genome Atlas confirmed an association with melanoma and RCC but not with cancers of established differing etiology such as lung cancers. Conclusions: Our study highlights that an exome-wide case-control enrichment approach may better characterize the rare variant-based missing heritability of multiple primary cancers. In our series, the co-occurrence of malignant melanoma and RCC was associated with germline variation in the PI3K/mTOR signaling cascade, with potential relevance for early diagnostic and clinical management

Identification of Circulating Tumor DNA for the Early Detection of Small-cell Lung Cancer

Circulating tumor DNA (ctDNA) is emerging as a key potential biomarker for post-diagnosis surveillance but it may also play a crucial role in the detection of pre-clinical cancer. Small-cell lung cancer (SCLC) is an excellent candidate for early detection given there are no successful therapeutic options for late-stage disease, and it displays almost universal inactivation of TP53. We assessed the presence of TP53 mutations in the cell-free DNA (cfDNA) extracted from the plasma of 51 SCLC cases and 123 non-cancer controls. We identified mutations using a pipeline specifically designed to accurately detect variants at very low fractions. We detected TP53 mutations in the cfDNA of 49% SCLC patients and 11.4% of non-cancer controls. When stratifying the 51 initial SCLC cases by stage, TP53 mutations were detected in the cfDNA of 35.7% early-stage and 54.1% late-stage SCLC patients. The results in the controls were further replicated in 10.8% of an independent series of 102 non-cancer controls. The detection of TP53 mutations in 11% of the 225 non-cancer controls suggests that somatic mutations in cfDNA among individuals without any cancer diagnosis is a common occurrence, and poses serious challenges for the development of ctDNA screening tests

Identification of Circulating Tumor DNA for the Early Detection of Small-cell Lung Cancer

Circulating tumor DNA (ctDNA) is emerging as a key potential biomarker for post-diagnosis surveillance but it may also play a crucial role in the detection of pre-clinical cancer. Small-cell lung cancer (SCLC) is an excellent candidate for early detection given there are no successful therapeutic options for late-stage disease, and it displays almost universal inactivation of TP53. We assessed the presence of TP53 mutations in the cell-free DNA (cfDNA) extracted from the plasma of 51 SCLC cases and 123 non-cancer controls. We identified mutations using a pipeline specifically designed to accurately detect variants at very low fractions. We detected TP53 mutations in the cfDNA of 49% SCLC patients and 11.4% of non-cancer controls. When stratifying the 51 initial SCLC cases by stage, TP53 mutations were detected in the cfDNA of 35.7% early-stage and 54.1% late-stage SCLC patients. The results in the controls were further replicated in 10.8% of an independent series of 102 non-cancer controls. The detection of TP53 mutations in 11% of the 225 non-cancer controls suggests that somatic mutations in cfDNA among individuals without any cancer diagnosis is a common occurrence, and poses serious challenges for the development of ctDNA screening tests. (C) 2016 Published by Elsevier B.V

Multi-omics comparative analyses of pulmonary typical carcinoids, atypical carcinoids, and large-cell neuroendocrine carcinoma

Pulmonary grade-1 typical (TC) and grade-2 atypical (AC) carcinoids share molecular characteristics with grade-3 large-cell neuroendocrine carcinoma (LCNEC) despite the distinct clinical behaviors. Most carcinoids can be surgically resected, however, limited treatment options exist for metastatic disease, present in 10-23% of TC and 40-50% of AC. Comprehensive genomic studies could help identify better therapeutic opportunities, novel diagnostic markers, and provide insight on the mechanisms responsible for the increased aggressiveness of AC versus TC. Such studies are rare due to the limited availability of suitable material. We have established a multi-center collaboration that has given us access to a unique collection of samples. We have already characterized 40 TC and 60 LCNEC genomes/exomes, and 61 TC, 8 AC and 69 LCNEC trancriptomes (published data). In the present study, we have performed whole-exome and transcriptome sequencing on 20 AC patients. Methylation data from 850K Illumina arrays were also generated for these samples, and for a subset of 20 TC and 20 LCNEC previously mentioned. When comparing the mutational data on AC with that of TC and LCNEC, we have found that similar to TC, AC harbor recurrent alterations in chromatin remodeling genes (such as MEN1 and ARID1A). They also carry alterations in genes involved in other cancer-related pathways (based on STRING), such as cell motility and cell death explaining their more aggressive phenotype. Integrative clustering analysis (MOFA and iCLUSTER) based on expression and methylation data tends to classify carcinoids into four groups: groups 1 and 2 are mostly composed of females with TC, and differ by their age composition and smoking status (Fisher's exact test p=0.008 and 0.03, respectively). Groups 3 and 4 are mostly composed of males with AC (Fisher's exact test for tumor type p=8x10-5). When including the LCNEC data, the samples from group 3 cluster with LCNEC, suggesting that AC can display a variety of expression and methylation patterns that may be linked to aggressiveness. This result was supported by the better survival of groups 1 and 2 compared to groups 3 and 4 (log-rank p=0.02), for which survival was similar to that of patients with LCNEC. Here, we present for the first time: (i) a multi-omics study on AC; (ii) the methylome characterization of TC, AC, and LCNEC; and (iii) the results of a comparative analysis of TC, AC, and LCNEC based on their molecular characteristics. We have identified the genes and pathways that might explain the progression from low-grade TC to intermediate-grade AC. Our expression and methylation data also supports the existence of a “super-AC” group, which clusters with LCNEC. Finally, we have identified a panel of molecular alterations that may help pathologist distinguishing between these three entities. NL and NA contributed equally. LFC and MF jointly supervised this work. Citation Format: Noémie Leblay, Nicolas Alcala, David Hervás Marin, Tiffany M. Delhomme, Théo Giffon, Akram Ghantous, Amélie Chabrier, Cyrille Cuenin, Janine Altmueller, Geoffroy Durand, Catherine Voegele, Philippe Lorimier, Anne-Claire Toffart, Jules Derks, Odd Terje Brustugun, Joachim H. Clement, Joerg Saenger, John K. Field, Alex Soltermann, Gavin M. Wright, Luca Roz, Lucia Anna Muscarella, Paolo Graziano, Zdenko Herceg, Ernst-Jan Speel, Peter Nuernberg, James McKay, Nicolas Girard, Sylvie Lantuejoul, Juan Sandoval, Elisabeth Brambilla, Matthieu Foll, Lynnette Fernandez-Cuesta. Multi-omics comparative analyses of pulmonary typical carcinoids, atypical carcinoids, and large-cell neuroendocrine carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5358