Update on novel antiangiogenic compounds

Les antiangiogéniques de 2e génération sont, pour la majorité, des inhibiteurs de récepteurs tyrosine-kinase membranaires dont nous retenons, dans cet article, les composés ayant atteint les phases II ou III randomisées. Leur rôle consiste, soit à améliorer la puissance d’inhibition sur des cibles déjà validées (VEGFR, PDGFR, KIT), soit à étendre leur spectre d’inhibition envers des cibles supplémentaires telles que FGFR, RET ou EGFR. En dehors de leurs propriétés sur le plan biologique, les chances de succès de ces nouveaux composés reposent également sur le choix judicieux des pathologies auxquelles ils s’adresseront.The second generation of antiangiogenics mainly includes membrane tyrosine kinase receptor inhibitors. This chapter summarizes clinical results of compounds that reached phase II and/or randomized phase III clinical trials. The aims of these agents are to improve the inhibition on validated targets (VEGFR, PDGFR, KIT) or to enlarge the spectrum of inhibition toward additional targets including FGFR, RET or EGFR. Beside intrinsic biological properties, the selection of appropriate disease appears critical to ensure future success in the development of those novel compounds

Identification of glucocorticoid-related molecular signature by whole blood methylome analysis

Objective Cushing's syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing's syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threatening condition of cortisol deprivation. Currently, hormone assays contribute to identify Cushing's syndrome or adrenal insufficiency. However, no biomarker directly quantifies the biological glucocorticoid action. The aim of this study was to identify such markers. Design We evaluated whole blood DNA methylome in 94 samples obtained from patients with different glucocorticoid states (Cushing's syndrome, eucortisolism, adrenal insufficiency). We used an independent cohort of 91 samples for validation. Methods Leukocyte DNA was obtained from whole blood samples. Methylome was determined using the Illumina methylation chip array (~850 000 CpG sites). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore methylome profiles. A Lasso-penalized regression was used to select optimal discriminating features. Results Whole blood methylation profile was able to discriminate samples by their glucocorticoid status: glucocorticoid excess was associated with DNA hypomethylation, recovering within months after Cushing's syndrome correction. In Cushing's syndrome, an enrichment in hypomethylated CpG sites was observed in the region of FKBP5 gene locus. A methylation predictor of glucocorticoid excess was built on a training cohort and validated on two independent cohorts. Potential CpG sites associated with the risk for specific complications, such as glucocorticoid-related hypertension or osteoporosis, were identified, needing now to be confirmed on independent cohorts. Conclusions Whole blood DNA methylome is dynamically impacted by glucocorticoids. This biomarker could contribute to better assessment of glucocorticoid action beyond hormone assays

Whole blood methylome-derived features to discriminate endocrine hypertension

Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches. Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods—Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine—predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL. Conclusions: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder

Targeted molecular markers for the prognosis of adrenocortical carcinoma : from genomics to personalized medicine

Les carcinomes de la corticosurrénale, ou corticosurrénalomes, sont des cancers rares de pronostic sombre, avec un taux de survie à 5 ans inférieur à 40%. L'évaluation pronostique est un élément essentiel de la prise en charge de ces tumeurs. Les principaux facteurs pronostiques sont l'extension tumorale et l'index de prolifération Ki67. Cependant, le pronostic reste hétérogène et difficile à prédire à l'échelle individuelle. Récemment, les études de génomique ont identifié des sous-groupes de corticosurrénalomes sur la base de leurs altérations moléculaires, qui s'associent à des pronostics différents. Un premier groupe est caractérisé par un profil transcriptome « C1A » (signature de prolifération), un profil méthylome « CIMP » (hyperméthylation des îlots CpG), un profil d'altérations chromosomiques « Noisy » (nombreuses cassures chromosomiques) et des mutations récurrentes des gènes des voies p53/Rb et Wnt/ß-caténine. Ce groupe est associé à un mauvais pronostic. Un deuxième groupe est caractérisé par un profil transcriptome « C1B » (signature immune), un profil méthylome « non-CIMP », un profil d'altérations chromosomiques « Chromosomal » (pertes d'hétérozygotie étendues sur plusieurs bras chromosomiques) ou « Quiet » (peu d'altérations) et de rares mutations somatiques. Ce groupe est associé à un pronostic meilleur. La mesure ciblée de l'expression de 2 gènes (BUB1B-PINK1) en RT-qPCR a été proposée comme marqueur pronostique dérivé du transcriptome pour le transfert clinique. Dans la continuité de ces travaux réalisés par mon laboratoire d'accueil, ce travail de thèse vise à développer, à partir des études de génomique, des marqueurs moléculaires utilisables en routine pour l'évaluation pronostique. Dans une première partie, nous avons proposé un marqueur pronostique dérivé du méthylome, consistant en la mesure ciblée de la méthylation de 4 gènes (PAX5, PAX6, PYCARD, GSTP1) par MS-MLPA. Dans une deuxième partie, nous montré que la classe moléculaire pouvait être résumée par différentes combinaisons de marqueurs moléculaires ciblés : soit une combinaison ARN + ADN tumoral, intégrant marqueur ARN BUB1B-PINK1, mesures ciblées de méthylation et d'altérations chromosomiques ; soit, en l'absence de tissu congelé disponible pour l'étude de l'ARN tumoral, une combinaison uniquement basée sur l'ADN, intégrant mesures ciblées de méthylation, d'altérations chromosomiques et mutations des gènes des voies p53/Rb et Wnt/ß-caténine. Dans les corticosurrénalomes localisés, l'association du stade, du grade tumoral et de la classe moléculaire fournissait la meilleure discrimination pronostique. Dans une troisième partie, nous avons étudié l'hétérogénéité intratumorale des marqueurs pronostiques ADN et montré que les mutations somatiques et la mesure ciblée de méthylation pouvaient varier d'une région tumorale à l'autre. La combinaison de différents marqueurs cliniques et moléculaires semble donc préférable à l'utilisation d'un marqueur ADN unique pour l'évaluation pronostique. Enfin, dans une quatrième partie, nous avons étudié le transcriptome sur des tissus en paraffine, en utilisant un nouveau protocole de séquençage des extrémités 3' de l'ARN. Les extrémités 3' de l'ARN sont en effet plus résistantes à la dégradation induite par la fixation et l'inclusion en paraffine. Nous avons montré que le protocole de séquençage ARN 3' identifie les profils transcriptome « C1A » et « C1B » et constitue une solution adaptée pour l'évaluation pronostique sur des échantillons en paraffine. Ces travaux établissent la classe moléculaire comme un élément incontournable de l'évaluation pronostique des corticosurrénalomes. Plusieurs déclinaisons de marqueurs ciblés sont proposées pour le transfert en routine, en fonction des techniques et du matériel tumoral disponibles. Pour l'avenir, la détermination du transcriptome sur paraffine offre la perspective d'une intégration de la médecine génomique dans le soin courant.The prognosis of adrenocortical carcinoma (ACC) is globally poor, with 5-year overall survival below 40%, but varies widely. Prognostic stratification is critical for patients care. Standard prognostic factors mainly include tumor stage and Ki67 proliferation index. However, the risk stratification based on tumor these factors is limited. Recently, pangenomic studies have idenfied ACC subgroups characterized by distinct molecular alterations and associated with different outcomes. A first ACC subgroup is characterized by "C1A" transcriptome profile (proliferation signature), "CIMP" (CpG islands methylator phenotype) methylome profile, "Noisy" chromosome alterations profile (high number of chromosome alterations) and recurrent mutations in p53/Rb and Wnt/ ß-catenin genes. This subgroup is associated with poor prognosis. Conversely, another ACC subgroup is characterized by "C1B" transcriptome profile (immune signature), "non-CIMP" methylome profile, "Chromosomal" (extended loss of heterozygosity) or "Quiet" (limited number of alterations) chromosome alterations profile and low mutational burden. This subgroup is associated with better prognosis. A targeted marker derived from transcriptome - BUB1B-PINK1 expression measured by RT-qPCR - was proposed for ACC prognostication. In line with these previous studies, this thesis aims at developing targeted molecular markers for routine prognostic assessment. First, 4-gene methylation (PAX5, PAX6, PYCARD, GSTP1) measured by MS-MLPA was proposed as a targeted prognostic marker derived from methylome. Then, the molecular classification was summarized using two combinations of targeted molecular markers: 1) a three dimensional (3D)-targeted classifier, based on tumor RNA and DNA, combining BUB1B-PINK1 expression, PAX5-GSTP1-PYCARD-PAX6 methylation, and targeted measurement of chromosome alterations ; 2) a DNA-based targeted classifier, using tumor DNA only, combining PAX5-GSTP1-PYCARD-PAX6 methylation, targeted measurement of chromosome alterations, and somatic mutations of p53/Rb and Wnt/ ß-catenin genes. In localized ACC, combination of tumor stage, tumor-proliferation index, and molecular class provided the most discriminant prognostic model. In a third part, we investigated intratumor heterogeneity of DNA-based prognostic markers. Somatic mutations, and, in a less extent, targeted methylation measurement, could vary from one tumor region to another. Therefore, combination of multiple targeted molecular markers, along with clinical features, should be preferred to gene alterations profile alone for the prognostic assessment of ACC. In the last part, we aimed to determine transcriptome profiles from FFPE samples, using a dedicated protocol of 3' RNA-sequencing. 3' ends are indeed more resistant to paraffin-induced RNA degradation. The 3' RNA-sequencing protocol successfully classified "C1A" and "C1B" transcriptome profiles, and represents a convenient solution for transcriptome-based prognostic classification in FFPE samples. In conclusion, molecular class is established as an essential prognostic factor in localized ACC. Several targeted markers, accounting for the differences in material and techniques availibilty between centers, are proposed for the routine determination of molecular classification. Finally, the determination of transcriptome in FFPE samples paves the way to the integration of genomic medicine into routine care

Value of Molecular Classification for Prognostic Assessment of Adrenocortical Carcinoma

Importance The risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome. Objective To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. Design, Setting, and Participants In this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018. Exposures Meta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts. Main Outcomes and Measures Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. Results Of the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC. Conclusions and Relevance The findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment

Molecular and Clinical Relevance of ZBTB38 Expression Levels in Prostate Cancer

International audienceProstate cancer is one of the most commonly diagnosed cancers in men. A number of genomic and clinical studies have led to a better understanding of prostate cancer biology. Still, the care of patients as well as the prediction of disease aggressiveness, recurrence and outcome remain challenging. Here, we showed that expression of the gene ZBTB38 is associated with poor prognosis in localised prostate cancer and could help discriminate aggressive localised prostate tumours from those who can benefit only from observation. Analysis of different prostate cancer cohorts indicates that low expression levels of ZBTB38 associate with increased levels of chromosomal abnormalities and more aggressive pathological features, including higher rate of biochemical recurrence of the disease. Importantly, gene expression profiling of these tumours, complemented with cellular assays on prostate cancer cell lines, unveiled that tumours with low levels of ZBTB38 expression might be targeted by doxorubicin, a compound generating reactive oxygen species. Our study shows that ZBTB38 is involved in prostate cancer pathogenesis and may represent a useful marker to identify high risk and highly rearranged localised prostate cancer susceptible to doxorubicin