RESUMEN
PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.
Asunto(s)
Biología Computacional/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Análisis de Secuencia de ADN/métodos , Algoritmos , Bases de Datos Genéticas , Aprendizaje Profundo , Exoma/genética , Femenino , Genómica , Humanos , Masculino , Fenotipo , Programas InformáticosRESUMEN
BACKGROUND: Endometriosis is frequently associated with and thought of having propensity to develop into ovarian clear cell carcinoma (OCCC), although the molecular transformation mechanism is not completely understood. METHODS: We employed immunohistochemical (IHC) staining for marker expression along the potential progression continuum. Expression profiling of microdissected endometriotic and OCCC cells from patient-matched formalin-fixed, paraffin-embedded samples was performed to explore the carcinogenic pathways. Function of novel biomarkers was confirmed by knockdown experiments. RESULTS: PTEN was significantly lost in both endometriosis and invasive tumour tissues, while oestrogen receptor (ER) expression was lost in OCCC relative to endometriosis. XRCC5, PTCH2, eEF1A2 and PPP1R14B were significantly overexpressed in OCCC and associated endometriosis, but not in benign endometriosis (p ⩽ 0.004). Knockdown experiments with XRCC5 and PTCH2 in a clear cell cancer cell line resulted in significant growth inhibition. There was also significant silencing of a panel of target genes with histone H3 lysine 27 trimethylation, a signature of polycomb chromatin-remodelling complex in OCCC. IHC confirmed the loss of expression of one such polycomb target gene, the serous ovarian cancer lineage marker Wilms' tumour protein 1 (WT1) in OCCC, while endometriotic tissues showed significant co-expression of WT1 and ER. CONCLUSIONS: Loss of PTEN expression is proposed as an early and permissive event in endometriosis development, while the loss of ER and polycomb-mediated transcriptional reprogramming for pluripotency may play an important role in the ultimate transformation process. Our study provides new evidence to redefine the pathogenic programme for lineage-specific transformation of endometriosis to OCCC.
Asunto(s)
Biomarcadores de Tumor/metabolismo , Carcinoma/etiología , Transformación Celular Neoplásica/metabolismo , Endometriosis/complicaciones , Neoplasias Ováricas/etiología , Biomarcadores de Tumor/genética , Carcinoma/genética , Carcinoma/metabolismo , Carcinoma/patología , Línea Celular Tumoral , Proliferación Celular , Transformación Celular Neoplásica/genética , Transformación Celular Neoplásica/patología , Femenino , Perfilación de la Expresión Génica/métodos , Regulación Neoplásica de la Expresión Génica , Estudio de Asociación del Genoma Completo , Humanos , Inmunohistoquímica , Análisis de Secuencia por Matrices de Oligonucleótidos , Neoplasias Ováricas/genética , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/patología , Fenotipo , Interferencia de ARN , Transducción de Señal , Análisis de Matrices Tisulares , TransfecciónRESUMEN
Minimally invasive alternatives to abdominal sacrocolpopexy have been shown to be equivalent with low overall complication rates. A small number of direct mesh-related gastrointestinal complications have been reported in the literature. Sacrocolpopexy with mesh retroperitonealization is recommended to minimize bowel adhesions. A 53-year-old nulligravid woman presented with persistent right lower-quadrant pain 1 year after laparoscopic sacrocolpopexy. The polypropylene mesh used during the case was retroperitonealized. Computed tomography (CT) prior to surgical exploration revealed no obvious pathology. On diagnostic laparoscopy, appendiceal adhesion to mesh requiring an appendectomy was observed. The patient's symptoms resolved after surgical intervention. Appendiceal adhesion to surgical mesh leading to chronic discomfort is a potential complication of intraperitoneal synthetic mesh placement. Our case emphasizes that bowel adhesions may occur even after proper mesh retroperitonealization. Appendiceal adhesion to the surgical site is a potential complication of retroperitonealized synthetic mesh placement at the time of sacrocolpopexy.