Sandrine M Caputo | Institut Curie (original) (raw)

Papers by Sandrine M Caputo

Innovations & thérapeutiques en oncologie/Innovations & thérapeutiques en oncologie, 2024

FrOG est la base de données de référence des variants génétiques identifiés dans les laboratoires... more FrOG est la base de données de référence des variants génétiques identifiés dans les laboratoires d'oncogénétique dont l'interprétation est validée par les différents groupes d'experts du Groupe génétique et cancer (GGC). La mission de FrOG est de garantir et de diffuser une interprétation cliniquement pertinente, harmonisée au niveau national, pour une meilleure prise en charge des familles. La gouvernance de FrOG est régie par un accord de consortium regroupant 21 établissements de santé, centres hospitalouniversitaires (CHU) et centres de lutte contre le cancer (CLCC), avec Unicancer en tant que coordinateur. Les laboratoires de ces établissements, en lien avec le GGC, disposent d'un outil informatique permettant la collecte des données de patients, la curation et le partage des informations via une page web (www.frog-db.fr). FrOG est conforme aux exigences du règlement général sur la protection des données (RGPD). Une note d'information aux patients, validée par le bureau du GGC, a été diffusée lors des consultations d'oncogénétique afin d'harmoniser les discours concernant l'intérêt, voire la nécessité, du programme FrOG et d'expliquer les droits des patients. FrOG bénéficie d'une infrastructure chez un hébergeur de données de santé agréé. Le dépôt de nouveaux variants et des données phénotypiques associées est réalisé par les contributeurs autorisés, sous une forme pseudo-anonymisée, sur un espace de stockage sécurisé. FrOG est consulté plusieurs centaines de fois par jour dans le cadre de la réalisation d'un diagnostic moléculaire. Ce projet académique est aujourd'hui conforme aux différentes exigences réglementaires en vigueur et est devenu un outil indispensable au diagnostic des patients du réseau d'oncogénétique français.

medRxiv (Cold Spring Harbor Laboratory), Jan 23, 2024

The ENIGMA research consortium () develops and applies methods to determine clinical significance... more The ENIGMA research consortium () develops and applies methods to determine clinical significance of variants in Hereditary Breast and Ovarian Cancer genes. An ENIGMA BRCA1/2 classification sub-group, originally formed in 2016 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Federal Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants, and documentation revised for clarity and ease-of-use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 Uncertain Significance or Conflicting, 14 Pathogenic and/or Likely Pathogenic, and 13 Benign and/or Likely Benign. Review resolved classification for 11/13 Uncertain Significance or Conflicting variants, and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in both the research processes and the baseline ACMG/AMP criteria. Calibration of evidence types was key to justify utility and strength of different evidence types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Supplementary Figure 2. Classification of the VUS as a function of the impact of the corresponding missense variations on BRCT domain expression in E. coli. from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on C...

Human Mutation, Mar 12, 2018

Author response for "Is BRCA2 involved in early onset colorectal cancer risk?

Research Square (Research Square), Sep 16, 2020

Supplementary Data Tables S1-S4 from Skipping Nonsense to Maintain Function: The Paradigm of BRCA2 Exon 12

Supplementary Tables S1-S4. Table S1. Description of primers used in this study. Table S2. Varian... more Supplementary Tables S1-S4. Table S1. Description of primers used in this study. Table S2. Variants selected in BRCA2 exon 12 and its flanking intronic regions. Table S3. Overview of bioinformatics predictions and experimental data obtained for the 40 selected BRCA2 exon 12 variants. Table S4. Clinical and family data of patients carrying BRCA2 exon 12 spliceogenic variants.

Supplementary Data from Skipping Nonsense to Maintain Function: The Paradigm of BRCA2 Exon 12

Fig. S1 to S10. Figure S1. Variant selection from human variation databases; Figure S2. Capillary... more Fig. S1 to S10. Figure S1. Variant selection from human variation databases; Figure S2. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in minigene assays of presumed LoF variants; Figure S3. Bioinformatics predictions of 3'/5' ss alterations for variants located at position IVS{plus minus}1/2 of BRCA2 exon 12; Figure S4. Bioinformatics analysis of variants predicted to alter 3'/5' ss of BRCA2 exon 12 (â^†MES {less than or equal to} -15%); Figure S5. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in minigene assays of variants predicted to alter 3'/5' ss (A) or ESR (B); Figure S6. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in control and patient lymphoblastoid cell lines; Figure S7. RT-PCR analysis of BRCA2 exon 12 splicing patterns in puromycin- or mock-treated lymphoblastoid cell lines of control individuals and patients carrying the c.6844G>T or c.6901G>T nonsense variants; Figure S8. Capillary electrophoresis analyses of BRCA2 exon 12 splicing patterns in variant-expressing mESC; Figure S9. Quantitation of BRCA2 protein expression in mESC; Figure S10. Sensitivity of BRCA2 variants to cisplatin and PARP inhibitors.

Supplementary Figure 1 (A). from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk

Western blot analysis of the expression of BRCA1 and I-SceI measured after expression of either W... more Western blot analysis of the expression of BRCA1 and I-SceI measured after expression of either WT BRCA1 or VUS in the HR assays. BRCA1 was revealed using an anti-BRCA1 (mouse, ab16780, Abcam) and I-SceI with an anti-HA (mouse, sc-7392, Santa Cruz Biotechnology Inc.).

Supplementary Figure 3. Classification of the 42 purified mutated BRCT domains as a function of their thermostability as measured using a high throughput fluorescence assay. from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 B...

Supp tables from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk

Supplementary table I: List of 78 BRCA1 BRCT missense VUS from the UMD-BRCA1 database. Bioinforma... more Supplementary table I: List of 78 BRCA1 BRCT missense VUS from the UMD-BRCA1 database. Bioinformatics in silico protein and 3D prediction scores, classification from BRCAShare (ex-UMD-BRCA1), BIC, kConfab and ClinVar databases. Supplementary table II: Classification of the BRCA1 VUS C1697R on the basis of multifactorial information Supplementary table III: Quantification of the percentage of fluorescence corresponding to nuclear BRCA1. The yes/no results extracted from this quantification to obtain Figure 3B were deduced from a statistical analysis using a t-test calculation.

Supplementary Figure 4. (A-D) from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk

Isothermal Titration Calorimetry curves obtained by adding the different phosphopeptides at (A-B)... more Isothermal Titration Calorimetry curves obtained by adding the different phosphopeptides at (A-B) 200 mM onto the WT BRCT domains at 20 mM and (C-D) 100 mM onto the WT BRCT domains at 10 mM .

Supplementary Figure 1 (B). from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk

Supplementary Figure 5. (A-B) from Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk

Size Exclusion Chromatography profiles obtained on BRCA1 BRCT domains free (red curve) or in comp... more Size Exclusion Chromatography profiles obtained on BRCA1 BRCT domains free (red curve) or in complex with BACH1-P (purple), AB-1P (green), AB-2P (blue). The experiment was performed using a Superdex-75 10/300 GL column (GE Healthcare) pre-equilibrated with 50mM Tris-HCl pH 7.5, 150 mM NaCl, 10 mM β-mercaptoethanol and protease inhibitors (Roche).

International Journal of Molecular Sciences, Jul 18, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Data from Skipping Nonsense to Maintain Function: The Paradigm of BRCA2 Exon 12

Germline nonsense and canonical splice site variants identified in disease-causing genes are gene... more Germline nonsense and canonical splice site variants identified in disease-causing genes are generally considered as loss-of-function (LoF) alleles and classified as pathogenic. However, a fraction of such variants could maintain function through their impact on RNA splicing. To test this hypothesis, we used the alternatively spliced BRCA2 exon 12 (E12) as a model system because its in-frame skipping leads to a potentially functional protein. All E12 variants corresponding to putative LoF variants or predicted to alter splicing (n = 40) were selected from human variation databases and characterized for their impact on splicing in minigene assays and, when available, in patient lymphoblastoid cell lines. Moreover, a selection of variants was analyzed in a mouse embryonic stem cell–based functional assay. Using these complementary approaches, we demonstrate that a subset of variants, including nonsense variants, induced in-frame E12 skipping through the modification of splice sites or regulatory elements and, consequently, led to an internally deleted but partially functional protein. These data provide evidence, for the first time in a cancer-predisposition gene, that certain presumed null variants can retain function due to their impact on splicing. Further studies are required to estimate cancer risk associated with these hypomorphic variants. More generally, our findings highlight the need to exercise caution in the interpretation of putative LoF variants susceptible to induce in-frame splicing modifications.Significance:This study presents evidence that certain presumed loss-of-function variants in a cancer predisposition gene can retain function due to their direct impact on RNA splicing.

P076: The ClinGen ENIGMA BRCA1/2 expert panel: A dynamic framework for evidence-based recommendations to improve classification criteria for variants in BRCA1/2*

Genetics in Medicine Open