Damage-associated molecular patterns modulation by microrna: Relevance on immunogenic cell death and cancer treatment outcome

Immunogenic cell death (ICD) in cancer is a functionally unique regulated form of stress-mediated cell death that activates both the innate and adaptive immune response against tumor cells. ICD makes dying cancer cells immunogenic by improving both antigenicity and adjuvanticity. The latter relies on the spatiotemporally coordinated release or exposure of danger signals (DAMPs) that drive robust antigen-presenting cell activation. The expression of DAMPs is often constitutive in tumor cells, but it is the initiating stressor, called ICD-inducer, which finally triggers the intracellular response that determines the kinetics and intensity of their release. However, the contribution of cell-autonomous features, such as the epigenetic background, to the development of ICD has not been addressed in sufficient depth. In this context, it has been revealed that several microRNAs (miRNAs), besides acting as tumor promoters or suppressors, can control the ICD-associated exposure of some DAMPs and their basal expression in cancer. Here, we provide a general overview of the dysregulation of cancer-associated miRNAs whose targets are DAMPs, through which new molecular mediators that underlie the immunogenicity of ICD were identified. The current status of miRNA-targeted therapeutics combined with ICD inducers is discussed. A solid comprehension of these processes will provide a framework to evaluate miRNA targets for cancer immunotherapy.Fil: Lamberti, María Julia. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Biotecnologia Ambiental y Salud. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Biotecnologia Ambiental y Salud.; Argentina. Universita di Salerno; ItaliaFil: Nigro, Annunziata. Universita di Salerno; ItaliaFil: Casolaro, Vicenzo. Universita di Salerno; ItaliaFil: Rumie Vittar, Natalia Belen. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Biotecnologia Ambiental y Salud. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Biotecnologia Ambiental y Salud.; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Biología Molecular. Sección Química Biológica; ArgentinaFil: Dal Col, Jessica. Universita di Salerno; Itali

A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis

Funder: The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257Abstract: The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Cardiovascular involvement in mtDNA disease: diagnosis, management, and therapeutic options

: Mitochondrial diseases (MD) include an heterogenous group of systemic disorders caused by sporadic or inherited mutations in nuclear or mitochondrial DNA (mtDNA), causing impairment of oxidative phosphorylation system. Hypertrophic cardiomyopathy is the dominant pattern of cardiomyopathy in all forms of mtDNA disease, being observed in almost 40% of the patients. Dilated cardiomyopathy, left ventricular noncompaction, and conduction system disturbances have been also reported. In this article, the authors discuss the current clinical knowledge on MD, focusing on diagnosis and management of mitochondrial diseases caused by mtDNA mutations

Snijders Blok–Campeau Syndrome: Description of 20 Additional Individuals with Variants in <i>CHD3</i> and Literature Review

Snijders Blok–Campeau syndrome (SNIBCPS, OMIM# 618205) is an extremely infrequent disease with only approximately 60 cases reported so far. SNIBCPS belongs to the group of neurodevelopmental disorders (NDDs). Clinical features of patients with SNIBCPS include global developmental delay, intellectual disability, speech and language difficulties and behavioral disorders like autism spectrum disorder. In addition, patients with SNIBCPS exhibit typical dysmorphic features including macrocephaly, hypertelorism, sparse eyebrows, broad forehead, prominent nose and pointed chin. The severity of the neurological effects as well as the presence of other features is variable among subjects. SNIBCPS is caused likely by pathogenic and pathogenic variants in CHD3 (Chromodomain Helicase DNA Binding Protein 3), which seems to be involved in chromatin remodeling by deacetylating histones. Here, we report 20 additional patients with clinical features compatible with SNIBCPS from 17 unrelated families with confirmed likely pathogenic/pathogenic variants in CHD3. Patients were analyzed by whole exome sequencing and segregation studies were performed by Sanger sequencing. Patients in this study showed different pathogenic variants affecting several functional domains of the protein. Additionally, none of the variants described here were reported in control population databases, and most computational predictors suggest that they are deleterious. The most common clinical features of the whole cohort of patients are global developmental delay (98%) and speech disorder/delay (92%). Other frequent features (51–74%) include intellectual disability, hypotonia, hypertelorism, abnormality of vision, macrocephaly and prominent forehead, among others. This study expands the number of individuals with confirmed SNIBCPS due to pathogenic or likely pathogenic variants in CHD3. Furthermore, we add evidence of the importance of the application of massive parallel sequencing for NDD patients for whom the clinical diagnosis might be challenging and where deep phenotyping is extremely useful to accurately manage and follow up the patients

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

International audienceReanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics