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Lu G, Ma L, Xu P, Xian B, Wu L, Ding J, He X, Xia H, Ding W, Yang Z, Peng Q. A de Novo ZMIZ1 Pathogenic Variant for Neurodevelopmental Disorder With Dysmorphic Facies and Distal Skeletal Anomalies. Front Genet 2022; 13:840577. [PMID: 35432459 PMCID: PMC9008544 DOI: 10.3389/fgene.2022.840577] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 02/22/2022] [Indexed: 12/30/2022] Open
Abstract
Background: Neurodevelopmental disorder with dysmorphic facies and distal skeletal anomalies (NEDDFSA) is a rare syndromic disorder characterized by global neurodevelopmental delay, early-onset hypotonia, poor overall growth, poor speech/language ability, and additional common phenotypes such as eye anomalies, joint hypermobility, and skeletal anomalies of the hands and feet. NEDDFSA is caused by heterozygous pathogenic variants in the ZMIZ1 gene on chromosome 10q22.3 with autosomal dominant (AD) mode of inheritance. All the 32 reported cases with variants in ZMIZ1 gene had a genetic background in Caucasian, Hispanic, North African, and Southeastern Asian. Until now, there are no reports of Chinese patients with ZMIZ1 pathogenic variants. Methods: A 5-year-old girl was found to have the characteristic phenotypes of NEDDFSA. Array-Comparative Genomic Hybridization (array-CGH) and whole exome sequencing (WES) were applied for the trio of this female patient. Sanger sequencing was used to verify the selected variants. A comprehensive molecular analysis was carried out by protein structure prediction, evolutionary conservation, motif scanning, tissue-specific expression, and protein interaction network to elucidate pathogenicity of the identified ZMIZ1 variants. Results: The karyotype was 46, XX with no micro-chromosomal abnormalities identified by array-CGH. There were 20 variants detected in the female patient by WES. A de novo heterozygous missense variant (c.2330G > A, p.Gly777Glu, G777E) was identified in the exon 20 of ZMIZ1. No variants of ZMIZ1 were identified in the non-consanguineous parents and her healthy elder sister. It was predicted that G777E was pathogenic and detrimental to the spatial conformation of the MIZ/SP-RING zinc finger domain of ZMIZ1. Conclusion: Thus far, only four scientific articles reported deleterious variants in ZMIZ1 and most of the cases were from Western countries. This is the first report about a Chinese patient with ZMIZ1 variant. It will broaden the current knowledge of ZMIZ1 variants and variable clinical presentations for clinicians and genetic counselors.
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Affiliation(s)
- Guanting Lu
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
| | - Liya Ma
- Department of Child Healthcare, Shenzhen Baoan Women’s and Children’s Hospital, Jinan University, Shenzhen, China
| | - Pei Xu
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
| | - Binqiang Xian
- Department of Child Healthcare, Shenzhen Baoan Women’s and Children’s Hospital, Jinan University, Shenzhen, China
| | - Lianying Wu
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
| | - Jianying Ding
- Department of Child Healthcare, Shenzhen Baoan Women’s and Children’s Hospital, Jinan University, Shenzhen, China
| | - Xiaoyan He
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
| | - Huiyun Xia
- Department of Child Healthcare, Shenzhen Baoan Women’s and Children’s Hospital, Jinan University, Shenzhen, China
| | - Wuwu Ding
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
| | - Zhirong Yang
- Deyang Key Laboratory of Tumor Molecular Research, Department of Pathology, Translational Medicine Research Center, Deyang People’s Hospital, Deyang, China
- *Correspondence: Qiongling Peng, ; Zhirong Yang,
| | - Qiongling Peng
- Department of Child Healthcare, Shenzhen Baoan Women’s and Children’s Hospital, Jinan University, Shenzhen, China
- *Correspondence: Qiongling Peng, ; Zhirong Yang,
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2
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Emelyanova M, Pudova E, Khomich D, Krasnov G, Popova A, Abramov I, Mikhailovich V, Filipenko M, Menshikova S, Tjulandin S, Pokataev I. Platinum-based chemotherapy for pancreatic cancer: impact of mutations in the homologous recombination repair and Fanconi anemia genes. Ther Adv Med Oncol 2022; 14:17588359221083050. [PMID: 35309086 PMCID: PMC8928350 DOI: 10.1177/17588359221083050] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 01/31/2022] [Indexed: 12/24/2022] Open
Abstract
Background Mutations in homologous recombination (HR) and Fanconi anemia (FA) genes may predispose to pancreatic cancer (PC) and enable the prediction of sensitivity to platinum-based chemotherapy. FOLFIRINOX is a standard treatment option for non-selected PC patients and could be effective due to undiagnosed DNA repair deficiency. Here, we aimed to determine the frequency of mutations in genes involved in the HR and FA pathways, evaluate their clinical implications, and determine the objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) of PC patients treated with platinum. Methods We performed targeted DNA sequencing of 30 genes (ABRAXAS1, ATM, ATR, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDKN2A, CHEK1, CHEK2, FANCC, FANCF, FANCG, FANCI, FANCL, FANCM, MRE11A, NBN, PALB2, PTEN, RAD50, RAD51C, RAD51D, RAD52, RAD54B, RBBP8, RINT1, SLX4, and XRCC2) for 543 PC patients. Results In BRCA/PALB2-mutated patients with advanced PC (33 patients, 6.1%), the PFS and OS were higher for first-line platinum therapy than for non-platinum therapy [PFS: HR = 0.28, 95% confidence interval (CI) = 0.10-0.81, p = 0.02; OS: HR = 0.31, 95% CI = 0.08-1.16, p = 0.08]. Among 93 patients (17.1%) with mutations in other HR/FA genes, no statistically significant difference in PFS and OS was observed between first-line platinum therapy and non-platinum therapy (PFS: HR = 0.83, 95% CI = 0.43-1.62, p = 0.59; OS: HR = 0.58, 95% CI = 0.28-1.22, p = 0.15). For patients with early PC, no prognostic value was observed for BRCA1/2, PALB2, or other HR/FA genes mutations. Moreover, a personal history of breast, ovarian, pancreatic, or prostate cancer was identified as the only independent predictor of the risk of BRCA/PALB2 mutations (HR = 5.83, 95% CI = 2.16-15.73, p < 0.01). Conclusion Mutations in the BRCA1/2 and PALB2 genes increase the sensitivity of PC to platinum agents. Thus, alterations in these genes in PC patients must be determined prior to anticancer therapy.
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Affiliation(s)
- Marina Emelyanova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russian Federation
| | - Elena Pudova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Darya Khomich
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - George Krasnov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Anna Popova
- N.N. Blokhin National Medical Research Center for Oncology, Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Ivan Abramov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Vladimir Mikhailovich
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Maxim Filipenko
- Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
| | | | - Sergey Tjulandin
- N.N. Blokhin National Medical Research Center for Oncology, Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Ilya Pokataev
- N.N. Blokhin National Medical Research Center for Oncology, Ministry of Health of the Russian Federation, Moscow, Russian Federation
- City Clinical Cancer Hospital No. 1, Moscow Department of Health, Moscow, Russian Federation
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Li B, Wang Z, Chen Q, Li K, Wang X, Wang Y, Zeng Q, Han Y, Lu B, Zhao Y, Zhang R, Jiang L, Pan H, Luo T, Zhang Y, Fang Z, Xiao X, Zhou X, Wang R, Zhou L, Wang Y, Yuan Z, Xia L, Guo J, Tang B, Xia K, Zhao G, Li J. GPCards: An integrated database of genotype-phenotype correlations in human genetic diseases. Comput Struct Biotechnol J 2021; 19:1603-1611. [PMID: 33868597 PMCID: PMC8042245 DOI: 10.1016/j.csbj.2021.03.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 02/28/2021] [Accepted: 03/10/2021] [Indexed: 01/02/2023] Open
Abstract
The patient-level genotype-phenotype correlations in GPCards accelerated the development of medical genetics. The integrated 62 genomic sources provide comprehensive information for interpreting pathogenicity. Analysis function in GPCards would help users to decipher their data of genotype-phenotype correlations.
Genotype–phenotype correlations are the basis of precision medicine of human genetic diseases. However, it remains a challenge for clinicians and researchers to conveniently access detailed individual-level clinical phenotypic features of patients with various genetic variants. To address this urgent need, we manually searched for genetic studies in PubMed and catalogued 8,309 genetic variants in 1,288 genes from 17,738 patients with detailed clinical phenotypic features from 1,855 publications. Based on genotype–phenotype correlations in this dataset, we developed an user-friendly online database called GPCards (http://genemed.tech/gpcards/), which not only provided the association between genetic diseases and disease genes, but also the prevalence of various clinical phenotypes related to disease genes and the patient-level mapping between these clinical phenotypes and genetic variants. To accelerate the interpretation of genetic variants, we integrated 62 well-known variant-level and gene-level genomic data sources, including functional predictions, allele frequencies in different populations, and disease-related information. Furthermore, GPCards enables automatic analyses of users’ own genetic data, comprehensive annotation, prioritization of candidate functional variants, and identification of genotype–phenotype correlations using custom parameters. In conclusion, GPCards is expected to accelerate the interpretation of genotype–phenotype correlations, subtype classification, and candidate gene prioritisation in human genetic diseases.
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Affiliation(s)
- Bin Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Mobile Health Ministry of Education - China Mobile Joint Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zheng Wang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Qian Chen
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Kuokuo Li
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Xiaomeng Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Yijing Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Qian Zeng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Ying Han
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Bin Lu
- Department of Pathogen Biology, School of Basic Medical Sciences, Central South University, Changsha, Hunan 410008, China
| | - Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Rui Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Li Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Tengfei Luo
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Yi Zhang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhenghuan Fang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Xuewen Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xun Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Rui Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Lu Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhenhua Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Lu Xia
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Beisha Tang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Kun Xia
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
| | - Guihu Zhao
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
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Di Resta C, Pipitone GB, Carrera P, Ferrari M. Current scenario of the genetic testing for rare neurological disorders exploiting next generation sequencing. Neural Regen Res 2021; 16:475-481. [PMID: 32985468 PMCID: PMC7996035 DOI: 10.4103/1673-5374.293135] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Next generation sequencing is currently a cornerstone of genetic testing in routine diagnostics, allowing for the detection of sequence variants with so far unprecedented large scale, mainly in genetically heterogenous diseases, such as neurological disorders. It is a fast-moving field, where new wet enrichment protocols and bioinformatics tools are constantly being developed to overcome initial limitations. Despite the as yet undiscussed advantages, however, there are still some challenges in data analysis and the interpretation of variants. In this review, we address the current state of next generation sequencing diagnostic testing for inherited human disorders, particularly giving an overview of the available high-throughput sequencing approaches; including targeted, whole-exome and whole-genome sequencing; and discussing the main critical aspects of the bioinformatic process, from raw data analysis to molecular diagnosis.
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Affiliation(s)
- Chiara Di Resta
- Vita-Salute San Raffaele University; Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Paola Carrera
- Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute; Clinical Molecular Biology Laboratory, IRCCS San Raffaele Hospital, Milan, Italy
| | - Maurizio Ferrari
- Vita-Salute San Raffaele University; Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute; Clinical Molecular Biology Laboratory, IRCCS San Raffaele Hospital, Milan, Italy
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5
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Siddappa M, Wani SA, Long MD, Leach DA, Mathé EA, Bevan CL, Campbell MJ. Identification of transcription factor co-regulators that drive prostate cancer progression. Sci Rep 2020; 10:20332. [PMID: 33230156 PMCID: PMC7683598 DOI: 10.1038/s41598-020-77055-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 11/05/2020] [Indexed: 12/13/2022] Open
Abstract
In prostate cancer (PCa), and many other hormone-dependent cancers, there is clear evidence for distorted transcriptional control as disease driver mechanisms. Defining which transcription factor (TF) and coregulators are altered and combine to become oncogenic drivers remains a challenge, in part because of the multitude of TFs and coregulators and the diverse genomic space on which they function. The current study was undertaken to identify which TFs and coregulators are commonly altered in PCa. We generated unique lists of TFs (n = 2662), coactivators (COA; n = 766); corepressors (COR; n = 599); mixed function coregulators (MIXED; n = 511), and to address the challenge of defining how these genes are altered we tested how expression, copy number alterations and mutation status varied across seven prostate cancer (PCa) cohorts (three of localized and four advanced disease). Testing of significant changes was undertaken by bootstrapping approaches and the most significant changes were identified. For one commonly and significantly altered gene were stably knocked-down expression and undertook cell biology experiments and RNA-Seq to identify differentially altered gene networks and their association with PCa progression risks. COAS, CORS, MIXED and TFs all displayed significant down-regulated expression (q.value < 0.1) and correlated with protein expression (r 0.4-0.55). In localized PCa, stringent expression filtering identified commonly altered TFs and coregulator genes, including well-established (e.g. ERG) and underexplored (e.g. PPARGC1A, encodes PGC1α). Reduced PPARGC1A expression significantly associated with worse disease-free survival in two cohorts of localized PCa. Stable PGC1α knockdown in LNCaP cells increased growth rates and invasiveness and RNA-Seq revealed a profound basal impact on gene expression (~ 2300 genes; FDR < 0.05, logFC > 1.5), but only modestly impacted PPARγ responses. GSEA analyses of the PGC1α transcriptome revealed that it significantly altered the AR-dependent transcriptome, and was enriched for epigenetic modifiers. PGC1α-dependent genes were overlapped with PGC1α-ChIP-Seq genes and significantly associated in TCGA with higher grade tumors and worse disease-free survival. These methods and data demonstrate an approach to identify cancer-driver coregulators in cancer, and that PGC1α expression is clinically significant yet underexplored coregulator in aggressive early stage PCa.
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Affiliation(s)
- Manjunath Siddappa
- College of Pharmacy, Pharmaceutics and Pharmaceutical Chemistry, The Ohio State University, 536 Parks Hall, 500 West 12th Ave, Columbus, OH, 43210, USA
| | - Sajad A Wani
- College of Pharmacy, Pharmaceutics and Pharmaceutical Chemistry, The Ohio State University, 536 Parks Hall, 500 West 12th Ave, Columbus, OH, 43210, USA
| | - Mark D Long
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center (RPCCC), Buffalo, NY, 14263, USA
| | - Damien A Leach
- Department of Surgery and Cancer, Imperial Centre for Translational and Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - Ewy A Mathé
- Biomedical Informatics Department, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.,Division of Preclinical Innovation, National Center for Advancing Translational Sciences, NIH, 9800 Medical Center Dr, Rockville, MD, 20892, USA
| | - Charlotte L Bevan
- Department of Surgery and Cancer, Imperial Centre for Translational and Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - Moray J Campbell
- College of Pharmacy, Pharmaceutics and Pharmaceutical Chemistry, The Ohio State University, 536 Parks Hall, 500 West 12th Ave, Columbus, OH, 43210, USA. .,The James, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA. .,Biomedical Informatics Shared Resource, The Ohio State University, Columbus, OH, 43210, USA.
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